Research ArticleResearch on the Attenuation Characteristics of AE Signals ofMarble and Granite Stone

HaiyanWang12 JiMa 3 FengDu 45 GongdaWang 2 Quan Zhang6 andXiaoshen Li6

1China Coal Research Institute Beijing 100013 China2State Key Laboratory of the Ministry of Education of China for High-efficient Mining and Safety of Metal MinesUniversity of Science and Technology Beijing Beijing 100083 China3School of Safety Science and Engineering Henan Polytechnic University Jiaozuo Henan 454000 China4Beijing Key Laboratory for Precise Mining of Intergrown Energy and ResourcesChina University of Mining amp Technology (Beijing) Beijing 100083 China5State Key Laboratory Cultivation Base for Gas Geology and Gas Control Henan Polytechnic University Jiaozuo 454000 China6Tingnan Coal Industry Co Ltd Taiyuan Shanxi 713600 China

Correspondence should be addressed to Ji Ma jmacumtb126com and Feng Du fengducumtb126com

Received 29 October 2020 Revised 19 November 2020 Accepted 14 December 2020 Published 24 December 2020

Academic Editor Chun Zhu

Copyright copy 2020 HaiyanWang et alis is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

When an underground rock is deformed or fractured by an external or internal force the energy will be released in the form of anelastic wave which is known as the acoustic emission (AE) phenomenon Extracting useful information from complex AE signalsfor the early warning of fracture characteristics and the damage monitoring of rock materials is of great significance for theprevention and control of dynamic disasters in coal mines In this work by taking rod-shaped rocks and plate-shaped rocks withdifferent lithologies as the research objects the elastic wave propagation characteristics of the rod-shaped rocks and plate-shapedrocks were studied by a self-constructed experimental platform e results demonstrate that the elastic wave attenuation of therod-shaped marble was the fastest and the elastic wave attenuation characteristics of the three groups of rod-shaped granite weresimilare attenuation of the P-wave preceded that of the S-waveWith the increase in the propagation distance the amplitude ofthe large-scale plate-shaped rock showed an approximate exponential attenuation characteristic e elastic wave attenuation ofthe plate-shaped granite in the 0deg direction was stronger than that of the plate-shaped marble and it was weaker than that of theplate-shaped marble in the 45deg and 90deg directions e energy changes in marble were more severe than those in granite e maindominant energy of the AE signals of experimental rock was concentrated in the range of 0ndash17678 kHz and part of the residualenergy was located in the high-frequency band of 28225ndash35256 kHz

1 Introduction

Coal resource is an important strategic resource [1ndash3]Before the excavation of underground rock mass in coalmines the original rock stress is in an equilibrium state eoriginal state of stress balance is destroyed because of theinfluence of mining activities resulting in the redistributionof the rock stress and causing fracture damage to the rockmass [4ndash7] e changes in the stress state and internalstructure often lead to the instability and fracturing of therock mass resulting in rockbursts mine earthquakes andother coal rock dynamic disasters [8ndash13] e process of

instability and fracturing of the rock mass is the process ofinitiation propagation and aggregation of internal micro-cracks resulting in the formation of macrocracks and theloss of bearing capacity During this process the acousticemission (AE) instrument can detect a large number of AEsignals [14ndash26] Nowadays AE technology can be used forthe dynamic and real-time monitoring of AE signals in theprocess of rock failure as well as the timely analysis of thechanging characteristics of AE signals Not only that but ithelps explore rock stability and predict the development andfracture degree of rock internal cracks which has become aneffective early warning and prevention means for coal rock

HindawiAdvances in Civil EngineeringVolume 2020 Article ID 6680347 19 pageshttpsdoiorg10115520206680347

dynamic disasters [17ndash21] Each AE signal contains a wealthof information concerning changes in the internal structureof the rock mass Understanding how to extract useful in-formation from complex AE signals for the early warning offracture characteristics and the damage monitoring of rockmasses is still an urgent problem that needs to be solved

To date several studies focusing on the application of AEtechnology on rock damage monitoring and the AE signalprocessing of rock failure have been conducted roughrepeated load stress experiments Goodman and Richard[22] presented that the AE of rock can be divided into threetypes the first type only appears under low stress and it willnot exist under the second load the second type appearsunder low stress and it will still exist under the second loadand the third type only appears under high stress con-firming that the rock also has a Kaiser effect It lays afoundation for the development of AE technology in thefield of rock mechanics Cai et al [15 23] and Saltas et al[24 25] systematically investigated the deformation andfailure mechanisms of rocks using AEs Qi [26] introducedthe research of wavelet signal processing technology in thefracture behavior of composite materials Manthei et al [27]analyzed the dispersion characteristics of AE signals in theplate structure using the wavelet transform method eyfound the time when the wave arrived at the sensor anddetermined an accurate location of the AE source Jeong andJang [28] examined the failure mechanisms in rocks throughmoment tensor methods applied to AE events Chang andLee [29] applied the tensor analysis of the AE to evaluate thecracks and damage of rocks under triaxial compression Inaddition some scholars studied the AE spatial location incoal rock instability engineering [15 30ndash34] However fewanalyses have compared and studied the similarities anddifferences of the elastic wave propagation characteristics indifferent rock materials by comprehensively using themethods of signal analysis and wavelet packet waveformanalysis In these analyses the AE signal waveform is an-alyzed and the time-frequency characteristics of the AEsignal waveform received by different position sensors wereextracted

erefore in this work the rod-shaped and plate-shapedrock materials with different lithologies were selected andthe elastic wave propagation characteristic experimentalplatform was constructede propagation characteristics ofthe elastic wave in the rod-shaped rock materials of the samelithology with different AE sources were studied Further-more the propagation characteristics of the elastic wave inthe rod-shaped rock materials with different lithologies werecompared e general laws of waveform attenuation anddistance satisfaction of the thin plate-shaped rock materialswere summarized In general the rock materials of differentlithologies and those with the same lithology but fromdifferent regions were selected e laws of elastic wave andenergy in the time and frequency domains of these rocksunder one-dimensional rod-shaped and two-dimensionalplate-shaped conditions were compared and analyzedrough this research certain research methods are pre-sented and a theoretical basis for the study of wave prop-agation law in complex three-dimensional rock is provided

2 Experiments

21 Preparation of Test Samples Considering the mineral-ogical and petrological characteristics of facing stones theexperimental rocks mainly consisted of marble and granitewhich included 5 groups of rod-shaped rocks and 2 groupsof plate-shaped rocks For the rod-shaped rocks threegroups were granite and two groups were marble For theplate-shaped rocks one group was granite and the other wasmarble According to the unified number of natural stone inChina [35] the numbers of these 7 groups of experimentalrocks are G3768 G3561 TBG AAM GAM G3761-L andGAM-L respectively e specific names types and sizes ofthese various rocks are presented in Table 1

22 Experimental Scheme In accordance with the purposeof this experimental work two kinds of experimentalplatforms for AE wave propagation characteristics werecorrespondingly designed for the rod-shaped and plate-shaped rocks

221 Experiment of Elastic Wave Propagation Characteris-tics of Rod-Shaped Rock When the length of the detectedobject is much larger than its width the object can beregarded as a rod As shown in Table 1 the first five samplesare rod-shaped rocks A rod-shaped rock was horizontallyfixed on the self-made fixture with 6 AE sensors arranged onits upper surface As for the GAM sample with a length of1m 5 sensors were arranged on its upper surface as shownin Figure 1 To make the sensor better receive the AE signalVaseline was used as the coupling agent between the sensorand the rod-shaped rock and the sensor was fixed withinsulating electrical tape e position coordinates of eachsensor are shown in Table 2 To simulate the generation ofthe S-wave and P-wave and analyze their propagationcharacteristics in different stone materials the signal sourcepoints were arranged on the top surface of the right end andthe vertical surface of the end of the rod-shaped rock epulse excitation source was used as the known AE source Itshould be noted that the P-wave is excited by terminal pulseexcitation and the S-wave is excited by end pulse excitation

222 Experiment of Elastic Wave Propagation Characteris-tics of Plate-Shaped Rock e AE receiving signal sensorwas fixed on the upper surface of the GAM-L sample (89 30)and the G3761-L sample (111 205) e point was thenmarked every 5 cm from the sensor in three directions of 0deg90deg and 45deg on the surface of the samples to lay the excitationpulse signal source as exhibited in Figure 2

23 Experimental System

231 Composition of Experimental System e experi-mental system was mainly composed of the DS5 series AEdata acquisition system adjustable excitation pulse sourcegain amplifier and DS5 series AE signal acquisition andanalysis software as shown in Figure 3 Among them the AE

2 Advances in Civil Engineering

data acquisition system mainly included the DS5-8B AEanalyzer RS-2A AE sensor adjustable gain amplifier ex-citation pulse source signal gain amplifier relevant dataacquisition processing software and computer As the peak

frequency of the RS-2A AE sensor was 150 kHz it can re-ceive an AE signal in the range of 60ndash400 kHz To meet theaccuracy of experimental data acquisition the samplingfrequency was set to 3MHz

Table 1 Parameters of the rod-shaped and plate-shaped rock samples

Scientific name Number Type SizemmLength times width times thickness

Wu Lianhong G3768 Granite 1440times 38times15Ma Hui stone G3561 Granite 2150times 40times 20Tan Brown TBG Granite 1400times 60times16Ariston AAM Artificial marble 1500times 59times12Giallo Atlantide GAM Marble 1000times 30times18Wu Lianhong lamel G3761-L Granite 2220times 620times12Giallo Atlantide lamel GAM-L Marble 1780times 760times15

Figure 1 e sensors network layout for the rod-shaped rock samples

Table 2 e coordinates of sensors on the rod-shaped rock samples

Number of rocksNumber of sensors

S1 S2 S3 S4 S5 S6G3768 5 20 50 70 100 135G3561 5 20 50 70 100 135TBG 5 20 50 70 100 135AAM 5 20 50 70 100 135GAM 5 20 50 70 100 -e location of each sensor is the distance from the right end of the fixed bar cm

1780cm

760

cm

(8930)0deg

45deg90deg

x

y

GAM-L

(a)

2220cm

620

cm

(111205)0deg

45deg90deg

x

y

G3761-L

(b)

Figure 2 e diagram of sensor placement plate-shaped rock (a) GAM-L (b) G3761-L

Advances in Civil Engineering 3

232 Setting of Acoustic Emission Detection ParametersBefore the experiment it is necessary to reasonably set therelevant parameters of the AE instrumentndashincluding thedetection threshold timing parameters and wave speedndashtotruly reflect the characteristics of the AE source It should benoted that the propagation speed of the wave is the materialproperty related to the elastic modulus and density of themedium which is the inherent property of the materialGenerally the wave velocity is mainly used for the locationcalculation of the AE source and its uncertainty becomes themain factor affecting the source location In the process ofactual source location the experimental measurement ofwave velocity is needed first However the experiments ofthis work focus on collecting the characteristic parametersand waveform information of the AE signal to study thepropagation characteristics of the elastic wave which doesnot involve the location of the AE source erefore theexperimental acquisition of wave velocity is not the focus ofthis work as it does not affect the acquisition of the researchobjectives of this paper

(1) Detection threshold setting

e indoor environment of this experiment was rela-tively quiet Under the general rules of different thresholdsettings and applicable scope the threshold value of theexperimental system should be carried out at a mediumsensitivity of 35ndash55 dB After the connection of the exper-imental system the AE data acquisition and processingsystem are activated and the entire channel is set at 50mVAt this time the threshold value is about 40 dB based on unitconversion meeting the experimental requirement

(2) Timing parameter setting

In this experiment lead breaking was used to simulatethe AE source Combined with the recommended values ofmetal materials and composite materials summarized inrelevant literature [36] the optimal timing parameters aredetermined including peak definition time (PDT) hitdefinition time (HDT) and hit locking time (HLT) etiming parameters are shown in Table 3

3 Analysis of Experimental Results of ElasticWave Propagation Characteristics

rough the implementation of the above experimentalscheme and the reasonable setting of relevant parameters ofthe AE acquisition instrument effective AE signals of theelastic waves in the propagation process were obtained echaracteristics and parameters of the AE signals and thewaveforms of the AE signals were processed and analyzedand the discussion was carried oute specific experimentalresults and analysis are as follows

31Analysis ofCharacteristic Parameters ofAcoustic EmissionSignals

311 Characteristic Parameter Analysis of Rod-Shaped RockAmplitude frequency and duration are the three elementsthat could be used to describe microvibration or micro-fracture By analyzing the amplitude changes of the moni-toring points at different positions the elastic wave intensitychange trend in the rod can be determined e frequencyinformation at the monitoring points can be used to identifythe area where the AE events are concentrated e types ofAE signals can be clearly identified based on the durationwaveform changes Two characteristic parameters of energycount and amplitude are used to analyze the propagationcharacteristics of elastic waves of different rod-shaped rocksAccording to the definition of energy count since the ac-quisition system obtains discrete point data the energy ofthe AE signal is expressed as

E 1113944N

i1V(i)

2 (1)

where N is the number of discrete points of the AE signalsand V(i) represents the amplitude of the signal discretepoints e amplitude usually reflects the magnitude of theevent [28] and the attenuation characteristics of the AE signalwaveform can be explored through the change in amplitude

+ndash60dB20dB40dB

60dB20dB40dB

40dB20dB60dB

40dB20dB60dB

40dB20dB60dB

USB

6

7

1 2 3

4

5

Figure 3 Experimental system 1 RS-2A sensor 2 adjustable gain amplifier 3 adjustable gain amplifier of excitation pulse source 4computer 5 acoustic emission analyzer 6 top view of the position of the end face excitation pulse signal 7 profile of the position ofterminal excitation pulse signal

4 Advances in Civil Engineering

Assuming that the AE signal is monitored at a distance of5 cm from the pulse excitation source as the reference theamplitude relative attenuation rate and energy relative at-tenuation rate of the elastic wave passing through the robcan be expressed as

ΔAj 20lgAj

As1 (2)

ΔEj 20lgEj

Es1 (3)

where As1 and Es1 represent the amplitude and energyparameters measured at point s1 (j s2 s3 s4 s5 s6)

Taking the existence of error factors into considerationpulse vibration was carried out four times for each group ofrock and the average value of the results was taken fordiscussion e curves of the energy and amplitude distancerelative attenuation rate for each group of rocks are shown inFigure 4

It can be seen from Figure 4 that the characteristicparameters of amplitude and energy in the rod-shaped rocksshow the characteristics of gradual attenuation with theincrease of distance Compared with the characteristic pa-rameter values collected at the 5 cm measuring point therelative attenuation rate of amplitude is greater than that ofenergy It shows that the amplitude directly reflects theintensity of the AE events at different measuring pointsHowever the energy only reflects the relative intensity ofevents which is affected by factors such as threshold valueand working frequency and the relative attenuation ratewith distance cannot show the energy change characteristicsof the AE signals e relative attenuation rate of the S-wavegenerated by the source signal excited by the pulse on theend surface of each group of rocks is lower than that of thepulse compression wave at the terminal area indicating thatthe P-wave came before the S-wave in the process of linearelastic wave propagation and changed violently

e mutation points of the relative amplitude attenua-tion rate both appear at the measuring point of 100 cm forG3768 G3561 and TBG because the length of G3768 andTBG is close to their amplitudes Furthermore the relativeattenuation rate tends to be stable after 100 cm e ab-normal phenomenon appears after 100 cm because the AEsignal produced by the excitation pulse in the terminal areaof TBG suddenly increases It shows that even if the rockwith the same lithology is limited by its complex compo-sition anisotropy and size the AE wave propagation doesnot decay exponentially but exhibits a sudden attenuationcharacteristic Moreover because of the fast propagationspeed of the P-wave the reflection of the rock boundary onthe original AE signal is superimposed on the original signal

and the frequency dispersion of the original signal increaseswith the increase of the propagation distance As a result thesignal after 100 cm in TBG is a mixed distortion signal elength of G3561 is 2150 cm and its relative attenuation rateof energy and amplitude exhibited decreasing trends erelative attenuation rates of energy at the 70 cm measuringpoint were abnormal which were respectively 15 dB and09 dB compared with those at the 5 cm measuring pointe relative attenuation rates of energy at the previous 50 cmmeasuring point were 13 dB and 11 dB respectively eattenuation in this section was relatively weak which may becaused by the gap in the transverse boundary of this rod-shaped rock e abnormal superposition of the boundarywave on the original wave enhanced the original AE signal

For different groups of rocks with different lithologiesthe relative attenuation rates of the amplitude and energy ofAAM presented a relatively flat attenuation trend andslightly strengthened from the position of the 100 cm abruptpoint to the end of the rod is indicates that the atten-uation characteristics of elastic wave propagation were clearwithout abnormal mutation even though the composition ofthe artificial stone is complicated is is because vacuumpressure technology was used to press the binder and varioussizes of crushed stone under vacuum vibration and pressureIt was then made by cutting and grinding erefore itsductility and compactness were good For marble materialGAM with a size of only 100 cm the relative attenuationrates of the amplitude of the end and terminal pulse exci-tation at 50 cm were 373 dB and 366 dB respectively ForG3768 these two values at 70 cm were 193 dB and 223 dBrespectively For the other four rock samples these twovalues at 70 cm were as follows 179 dB and 177 dB forG3561 232 dB and 261 dB for TBG and 256 dB and 271 dBfor AAM It can be seen that the elastic wave attenuation wasthe fastest in the marble and the elastic wave attenuation ofthe three types of granite was similar Among them the TBGhad the fastest elastic wave attenuation In general the at-tenuation of the P-wave came before the S-wave

312 Characteristic Parameter Analysis of Rod-Shaped RockAccording to the experimental schemes of the G3761-L andGAM-L samples the elastic wave propagation characteris-tics in the thin plate-shaped rock were discussed by ana-lyzing the changes in the amplitude of the AE signalsConsidering the error factor pulse vibration was carried outfour times for each group of rod-shaped rocks where theaverage value of the results was taken for discussion eattenuation curves of the amplitude of each measuring pointin different directions and different lithological samples arepresented in Figure 5

Table 3 Timing parameters in the experiment

Timing parameter G3768 G3561 TBG AAM GAM G3761-L GAM-LPDTμs 100 150 150 150 150 100 100HDTμs 200 300 300 300 300 200 200HLTμs 300 500 500 500 500 300 300

Advances in Civil Engineering 5

Amplitude

Energy

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

TBGRelat

ive d

ecay

rate

(dB)

Distance (cm)

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

AAMRelat

ive d

ecay

rate

(dB)

Amplitude

Energy

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

G3768Relat

ive d

ecay

rate

(dB)

Distance (cm)

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash3

ndash2

ndash1

0

G3561

Relat

ive d

ecay

rate

(dB)

Amplitude

Energy

Distance (cm)

20 50 70 100ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

GAM

(a)

Figure 4 Continued

6 Advances in Civil Engineering

It can be seen from Figure 5 that the amplitude of thelarge-scale plane plate rock showed similar exponentialattenuation characteristics with the increase of the propa-gation distance e AE wave attenuation of granite wasstronger than that of marble in the direction of 0deg and wasweaker than that of marble in the directions of 90deg and 45deg

Specifically due to the diversity and anisotropy of rockcomponents the attenuation of the AE wave in the range of20ndash80 cm in the direction of 0deg showed the fluctuation ofamplitude between 72 and 83 dB in both kinds of rockthough the overall trend was declining e amplitudecharacteristic parameters extracted from each measuring

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash5

ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

G3768

Amplitude

Energy

Distance (cm)

20 50 70 100 135

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

G3561

Amplitude

Energy

Distance (cm)

20 50 70 100 135

ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

TBG

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

AAM

Amplitude

Energy

Distance (cm)

20 50 70 100ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

GAM

(b)

Figure 4 e attenuation rates of energyamplitude with distance (a) End-pulse excitation (S-wave) (b) Terminal pulse excitation (P-wave)

Advances in Civil Engineering 7

point arranged in the front and back of the marble in the 45degdirection and 90deg direction presented significant changes Asudden decrease of amplitude appeared at 30ndash40 cm with adecrease of 1965 dB in the 45deg direction and 2455 dB in the90deg directione amplitude attenuation of granite tended tobe stable

e attenuation curves of the AE energy in differentdirections for G3761-L and GAM-L are shown in Figure 6 Itcan be seen that the energy in the marble changes violentlyand the energy value in the range of 45ndash55 cm in the di-rection of 0deg exhibits the abnormal phenomenon of stepeenergy attenuation was lower than that of the granite stonewhich shows the same trend with the amplitude attenuatione energy value of granite from 45 cm back to the end of thethin plate is almost maintained at 20ndash50mVms and tends tobe stable In the 45deg direction the marble exhibited theenhancement of energy value after 55 cm It is the reflectionof the AE wave along the 45deg direction when it met theboundary and the wave enhancement phenomenon wasformed by the superposition of multiple reflections andrefractions e marble and granite showed the same trendin the 90deg direction

32 Waveform Analysis of Acoustic Emission Signal

321 Time Domain Waveform and Spectrum Analysis ofAcoustic Emission Original Signal According to a largenumber of AE signal waveforms obtained by pulse excitationon the surface of each group of samples the AE signalwaveforms of rod-shaped and plate-shaped rocks were se-lected from the closest measuring point to the pulse sourcee middle measuring point in their respective directionsand the end measuring points were analyzed e specificlayout of measuring points is presented in Table 4

Since the original statistics of the nonstationary AEsignal is a time-varying function FFT transform was used toanalyze the spectral characteristics of the time-domain signalto better understand the variation law of elastic wave in thepropagation process Figure 7 presents the original signaltime-domain waveforms of measuring point M2 of eachgroup of rod-shaped rocks and the corresponding frequencyspectrum is shown in Figure 8 e related curves of the AE

signal excited from measuring points M2 on the surface ofthe plate-shaped rocks in the three directions of 0deg 90deg and45deg are shown in Figure 9

It can be seen from the time-domain diagram that thewaveforms of the AE signal generated by pulse excitationwere very similar and the duration was short For the rod-shaped rocks the durations for granites G3768 G3561 andTBG were in the range of 025ndash15ms where the waveformsdecayed quickly and the coda waves were not developede durations for AAM and GAM were in the range of05ndash20ms and 05ndash10ms respectively For the plate-shapedrocks the duration of G3761-L was 05ndash15ms in the 0degdirectione duration for GAM-L was 025ndash15ms and theamplitude attenuation variation was small Similarly in the45deg direction and 90deg direction the G3761-l granite showed ashorter duration of time than the GAM-L marble dem-onstrating that the homogeneity of the natural granite plate-shaped rock is better

It can be seen from the spectrum that the frequency ofthe AE signal generated by pulse excitation was relativelyhigh and the frequency band was relatively narrow emain frequency domain of each group of rod-shaped rockswas 0ndash250 kHz and the frequency domain of the AE signalat the M2 position measuring point in each direction of theplate-shaped rocks was 0ndash300 kHz In this frequency do-main each group of samples with different lithologies showsmultiple peaks of frequency indicating that the waveform ofthe AE signal is very complex and is a mixture of waves withdifferent characteristics

322 Wavelet Packet Energy Analysis of Acoustic EmissionSignal According to previous research wavelet transformonly decomposes the low-frequency partndashbut not the high-frequency part of the original signal e time-frequencylocalization could be better analyzed through the intro-duction of wavelet packet transform in which the high-frequency part of the signal could be further decomposed Asshown in Table 4 considering that wavelet packet analysishas the advantages of multilayer decomposition of signaldetails and scale information the following wavelet packetenergy feature extraction was conducted for the AE signal

0 20 40 60 80 100 12060

65

70

75

80

85

90

95

100A

mpl

itude

(dB)

G3761-L

GAM-L

0deg

Distance (cm)

G3761-L

GAM-L

0 10 20 30 40 50 6050

60

70

80

90

100

45deg

Distance (cm)

Am

plitu

de (d

B)

G3761-L

GAM-L

0 10 20 30 40 5050

60

70

80

90

100

90deg

Distance (cm)

Am

plitu

de (d

B)

Figure 5 e attenuation curves of the amplitude in different directions for G3761-L and GAM-L

8 Advances in Civil Engineering

waveform obtained at different measuring points in eachgroup of rock samples to explore the local feature infor-mation of the AE signal waveform at different positions ofrod-shaped and plate-shaped rocks

Choosing a suitable wavelet base plays an important rolein signal processing and analysis Guo [37] introduced theeffect of different wavelet bases in vibration signal processingin detail which presents that the db5 db7 db10 db13 db16bior26 bior39 coif4 sym7 and sym8 wavelet bases aremore suitable for the shock feature extraction of vibrationsignals Of this wavelet set db7 was selected as the waveletbase for the wavelet packet analysis because of its Daubechiesseries wavelet set characteristics such as high-order van-ishing moment tight support regularity approximatesymmetry and orthogonalityndashand because of the similaritiesit shares with the rock AE signal Its wavelet function ispresented in Figure 10

e sampling frequency is 3MHz According to thesampling theorem its Nyquist frequency is 1500 kHz ewavelet packet decomposition principle and algorithm wereapplied to decompose the signal to the 7th layer (ie thescale is 7) which has 27 wavelet packets in total ereforein the frequency domain the original signal was decom-posed into 128 subbands e width of each band was1172 kHz e frequency band range of each layer recon-structed after the decomposition of the original signal ispresented in Table 5

As can be seen from the table the original signal isexpressed as

S S70 + S71 + S72 + middot middot middot + S7127 (4)

where S70 is the low-frequency part of the decomposedsignal the other variables represent the decomposition of the

high-frequency part of the signal Assuming that the cor-responding energy of S7j(j 0 1 2 middot middot middot 127) isE7j(j 0 1 2 middot middot middot 127) then the energy characterization ofthe original AE signal decomposition in each frequencyband range can be obtained by formula (1)

Assuming that the total energy of the analyzed signal isE0 then

E0 1113944127

j0E7j (5)

e ratio of the energy of each frequency band to thetotal energy of the analyzed signal is

Ej E7j

E0times 100 (6)

In the formula j 012 27ndash1From Equation (1) the energy changes of the corre-

sponding AE signals in different frequency bands after theoriginal signal decomposition were calculated so the energydistribution characteristics of the elastic wave in differentfrequency bands could be found [38] According to Table 4the main frequency range of the AE signal waveform of eachmeasuring point was 0ndash300 kHz indicating that the energyvalue must also be concentrated in this frequency rangeerefore with MATLAB programming the energy dis-tribution of each subband in the frequency domain of0ndash500 kHz was obtained as shown in Figures 11 and 12

For rod-shaped rocks G3768 G3561 and TBG of thesame lithology from different places of origin the M1measuring point was closest to the pulse excitation sourceerefore the value of the M1 measuring point could ef-fectively reflect the energy value of the real pulse As can be

G3761-L

GAM-L

0deg

0 20 40 60 80 100 120

0

100

200

300

400

500

600

Distance (cm)

Ener

gy (m

Vlowast

ms)

G3761-L

GAM-L

45deg

Distance (cm)

Ener

gy (m

Vlowast

ms)

0 10 20 30 40 50 600

100

200

300

400

500

600

700

G3761-L

GAM-L

90deg

Distance (cm)

Ener

gy (m

Vlowast

ms)

0 10 20 30 40 50

100

200

300

400

500

600

700

Figure 6 e attenuation curves of the AE Energy in different directions for G3761-L and GAM-L

Table 4 e measuring point positions of AE waveforms

Rock number (measuring point) (cm) G3768 G3561 TBG AAM GAMG3761-L GAM-L

0deg 90deg 45deg 0deg 90deg 45deg

M1 5 5 5 5 5 5 5 5 5 5 5M2 70 70 70 70 50 55 20 30 40 25 30M3 135 135 135 135 100 100 35 50 75 40 50

Advances in Civil Engineering 9

seen from Figure 11 the energy is widely distributed in thefrequency domain e value of energy is generally smallwhich was mainly concentrated in the range of0ndash36428 kHz Combined with Formulas (5) and (6) it couldbe calculated that the main dominant energy of the three

groups of granite was concentrated in the frequency band of7131ndash12991 kHz which correspondingly accounted for646 5605 and 5828 of the total energy About2326 of the energy in G3561 was concentrated in thefrequency band of 23538ndash35256 kHz which is different

0 05 10 15 20 25ndash15

ndash10

ndash05

0

05

10

Am

plitu

de (m

V)

Time (ms)

G3768

TBG

0 05 10 15 20 25 3ndash08

ndash06

ndash04

ndash02

0

02

04

06

08

Am

plitu

de (m

V)

Time (ms)

G3561

0 05 10 15 20 25

ndash15

ndash10

ndash05

0

05

10

15

Time (ms)

Am

plitu

de (m

V)

AAM

0 05 10 15 2ndash20

ndash15

ndash10

ndash05

0

05

10

15

Time (ms)

Am

plitu

de (m

V)

GAM

0 05 10 15 20 25 30 35ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

Figure 7 Time domain waveform of measuring point M2 of rod-shaped rock

10 Advances in Civil Engineering

from other samples of the same lithology With the increaseof the propagation distance of the elastic wave its energyexhibited the characteristics of rapid attenuation edominant energy distribution frequency bands of the threerod-shaped rock materials at the M2 measuring point ex-panded from the initial 7131ndash12991 kHz to 0ndash17678 kHz

and the energy percentages were 8987 9407 and8658 respectively In the high-frequency band of28225ndash31741 kHz there was respectively 10 and 1269energy concentration for G3768 and TBG When the elasticwave propagated to the end of the rod (M3) the energy ofeach group of samples was relatively concentrated and

0 100 200 300 400 5000

001

002

003

004

Am

plitu

de (m

V)

Frequency (KHz)

G3768

TBG

0 100 200 300 400 5000

001

002

003

Am

plitu

de (m

V)

Frequency (KHz)

G3561

0 100 200 300 400 5000

001

002

003

004

005

006

007

Frequency (KHz)

Am

plitu

de (m

V)

AAM

0 100 200 300 400 5000

001

002

003

004

005

006

Frequency (KHz)

Am

plitu

de (m

V)

GAM

0 100 200 300 400 5000

0002

0004

0006

0008

0010

0012

Am

plitu

de (m

V)

Frequency (KHz)

Figure 8 e spectrogram of measuring point M2 of rod-shaped rock

Advances in Civil Engineering 11

G3761-L(90deg)

0 05 10 15 2ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

G3761-L(90deg)

0 100 200 300 400 500000

002

004

006

008

010

Am

plitu

de (m

V)

Frequency (KHz)

G3761-L(45deg)

0 05 10 15 20 25

ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

G3761-L(45deg)

0 100 200 300 400 5000

001

002

003

004

005

006

007

Am

plitu

de (m

V)

Frequency (KHz)

0 05 10 15 20 25 3ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

G3761-L(0deg)

Am

plitu

de (m

V)

Time (ms)

G3761-L(0deg)

0 100 200 300 400 5000

0002

0004

0006

0008

0010

Am

plitu

de (m

V)

Frequency (KHz)

(a)

Figure 9 Continued

12 Advances in Civil Engineering

mainly distributed within 0ndash10647 kHz at the percentages of9211 9022 and 9188 respectively By comparing thethree groups of rod-shaped rocks with the same lithology itcan be seen that the energy attenuation was the fastest inTBG and the dominant energy value was the lowest at theM3 measuring point For G3768 the energy attenuation wasthe slowest Only the distribution rule of the dominant

energy value at the M2 and M3 measuring points changedwhereas the maximum energy value hardly changed ereason may be that the internal structure or componentdensity of G3768 was better and the energy was relativelymaintained rather than rapidly attenuated with the elasticwave propagation For AAM artificial marble its maindominant energy also exhibited the same change trend as

GAM-L(45deg)

0 05 10 15 20 25

ndash3

ndash2

ndash1

0

1

2

3

4

Am

plitu

de (m

V)

Time (ms)

GAM-L(45deg)

0 100 200 300 400 5000

002

004

006

008

010

012

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(0deg)

0 05 10 15 20 25 30 35

ndash09

ndash06

ndash03

0

03

06

09

Am

plitu

de (m

V)

Time (ms)

GAM-L(0deg)

0 100 200 300 400 5000

0005

0010

0015

0020

0025

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(90deg)

0 05 10 15 20 25ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

GAM-L(90deg)

Am

plitu

de (m

V)

0 100 200 300 400 500000

002

004

006

008

010

Frequency (KHz)

(b)

Figure 9 e time waveform and spectrogram of measuring point M2 of pate-shaped rock

Advances in Civil Engineering 13

0 3 6 9 12 15ndash15

ndash10

ndash05

00

05

10

Wavelet function

0 3 6 9 12 15

ndash05

00

05

10

Scaling function

Figure 10 Wavelet function and scaling function for db7

Table 5 e frequency band range of reconstructed signal by wavelet packet decomposition

Layer S (i 0) S (i 1) S (i 2) S (i jminus 1) S (i j)1 0ndash750 ndash ndash ndash ndash 750ndash15002 0ndash375 375ndash750 750ndash1125 ndash ndash 1125ndash15003 0ndash1875 1875ndash375 375ndash5625 1125ndash13125 13125ndash15004 0ndash9375 9375ndash1875 1875ndash28125 13125ndash140625 140625ndash15005 0ndash46875 46875ndash9375 9375ndash140625 140625ndash1453125 1453125ndash15006 0ndash234375 234375ndash46875 46875ndash703125 1453125ndash14765625 14765625ndash15007 0ndash1171875 1171875ndash234375 234375ndash3515625 14765625ndash148828125 148828125ndash1500S (i j) represents the reconstruction signal of the j-th wavelet packet decomposition coefficient in the i-th layer i 1234 j 012 2i-1

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M3

(a)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500

1000

1500

2000

2500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

20

40

60

80

100

120

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

M3

(b)

Figure 11 Continued

14 Advances in Civil Engineering

granite From Figure 11 it can be observed that the energy ofthe original pulse signal is concentrated in the range of9475ndash16506 kHz and 2185 of the energy existed in thefrequency band of 28225ndash35256 kHz For GAMmarble themain dominant energy distribution of the initial signal wasvery wide and was distributed in the frequency band of0ndash36428 kHz Among them the dominant energy wasdistributed within the 10647ndash12991 kHz range accountingfor 3213 of the total energy Similar attenuation charac-teristics as granite were presented with the increase of elasticwave propagation distance In general for GAM the exci-tation energy of the AE signal generated by pulse excitationwas the weakest and the attenuation was the fastest with theincrease of distancee initial excitation energy of the threegroups of granite was partially concentrated in the frequency

band of 23538ndash35256 kHz of which the performance ofG3561 was the most obvious

e pulse AE signal was very complex for 2 groups of theplate-shaped rocks (Figure 12) erefore the initial energyof the M1 measuring point in each direction was also quitedifferent In the direction of 0deg the dominant energy of theoriginal pulse signal in G3761-L was concentrated in thefrequency band of 0ndash17678 kHz which accounted for8904 of the total energy Meanwhile about 628 of theenergy was distributed in the frequency band of29397ndash32913 kHz e same law was also shown in GAM-L but the main dominant frequency in GAM-L was rela-tively concentrated in the short frequency band of10647ndash17678 kHz which accounted for 6357 of the totalenergy With the spread of the elastic wave the energy in

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50002468

10121416

M3

(c)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5001000150020002500300035004000

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40

50

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M3

(d)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

100

200

300

400

500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M2

0 100 200 300 400 5000

2

4

6

8En

ergy

(mVlowast

mS)

Frequency (KHZ)

M3

0 100 200 300 400 500012345678

(e)

Figure 11e energy distribution of acoustic emission signal frequency band of rod-shaped rock (a) G3768 (b) G3561 (c) TBG (d) AAM(e) GAM

Advances in Civil Engineering 15

0 100 200 300 400 5000

200400600800

100012001400

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

M2

0 100 200 300 400 5000005101520253035

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

M3

0 100 200 300 400 50000020406081012

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

(a)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40En

ergy

(mVlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 5000

2

4

6

8

Ener

gy (m

Vlowast

mS)

(b)

M1

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

1020304050607080

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50002468

1012141618

Ener

gy (m

Vlowast

mS)

(c)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700800

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 50005

101520253035

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

Ener

gy (m

Vlowast

mS)

(d)

Figure 12 Continued

16 Advances in Civil Engineering

G3761-L showed a trend of attenuation and the energy intheM2measuring point was still distributed in the frequencyband of 0ndash17678 kHz e energy distribution at the M3measuring point was relatively concentrated and was locatedin the frequency band of 0ndash10647 kHz accounting for8340 of the total energy e energy at the measuringpoint M3 of GAM-L was more extensive in the frequencydomain and the energy value changed dramatically dem-onstrating the abnormal phenomenon that the maindominant energy increased e frequency range of thismeasuring point was 0ndash1885 kHz accounting for 8589 ofthe total energyere was also residual energy concentratedin the frequency band of 29397ndash32913 kHz e AE signalat M3 was superposed by the boundary reflection wave andthe energy was enhanced because of the high homogeneityand good ductility of GAM-L For G3761-L the dominantenergy of the elastic wave almost dissipated at the M3measuring point In the direction of 45deg the dominantenergy band of the original signal in G3761-L was distributedwithin 0ndash17678 kHz and 28225ndash35256 kHz respectivelyaccounting for 6415 and 3278 of the total energyMoreover it can be observed that the distribution of thedominant energy band was from distribution to concen-tration which was distributed in the frequency band of7131ndash17678 kHz at M2 With the increase of distance theenergy frequency band of the M3 measuring point near theedge of the plate was spread again and it was restored to theenergy frequency band range of the initial signal Howeverthe energy value was attenuated to a very small value at this

moment e energies of GAM-L in the measuring pointsM1 M2 and M3 were all distributed in the frequency bandof 0ndash36428 kHz In the direction of 90deg the primarydominant energy frequency bands of the two plate-shapedrocks were concentrated in 9475ndash1885 kHz e differenceis that the energy distribution of GAM-L was still con-centrated and the energy variation was much smaller thanG3761-L at the M2 measuring point In general the energyfrequency band of the two plate-shaped rocks with differentlithologies was the same as that of the rod-shape rock whichis mainly distributed in the range of 0ndash36428 kHz More-over they also exhibited the characteristics that the maindominant energy was distributed in the range of0ndash17678 kHz and the residual energy was distributed in therange of 28225ndash35256 kHz

4 Discussion

e purpose of this work was to study the propagationcharacteristics of elastic wave in lithological rock materialsrough the above research and analysis a preliminaryunderstanding was obtained Based on the deep waveletpacket analysis of amplitude energy characteristic param-eters and AE waveform the frequency band characteristicsof the local energy distribution of elastic wave with itspropagation were summarized However its propagationcharacteristics are difficult to be regularly grasped becausethe elastic wave itself is extremely complex Furthermore AEtechnology is mostly used in the damage detection and

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

20406080

100120140160

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

10

20

30

40

50

(e)

M1

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

200400600800

10001200140016001800

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

50

100

150

200

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 50005

101520253035

(f )

Figure 12e energy distribution of acoustic emission signal frequency band of plate-shaped rock (a) G3761-L (00) (b) G3761-L (450) (c)G3761-L (900) (d) GAM-L (00) (e) GAM-L (450) (f ) GAM-L (900)

Advances in Civil Engineering 17

defect location of metal or related materials with goodcompactness ductility and within the same medium ereare many uncertain interference factors in the experimentsIn some aspects the analysis of this paper only stays at thelevel of the apparent phenomenon and there are still manydeficiencies and areas worthy of improvement For instancethe density wave velocity and wave impedance of the rod-shaped rock samples should be tested and the micro-structure imaging experiments of the rock samples should beconducted e quality factor Q of different rock samplesshould be calculated Moreover the correlation between thequality factor and wave impedance should be studied andthe influence of different microcompositions of rod-shapedrocks on elastic wave attenuation should be deeply analyzedBased on the modal AE theory the influence of Lamb wavein plate-shaped rocks should be studied and the propagationmodel of two-dimensional AE should be constructed eGabor wavelet should be introduced to analyze the AE signalby time-frequency analysis e influence of differentwavelets based on the propagation effect of AE will becompared and analyzed and the time of the same mode ofthe AE wave arriving at the sensor will be determined tofurther optimize the plane location algorithm However theresearch in this work is still useful for studying large-scalerock samples in the future and provides effective researchmethods and ideas for the study of elastic wave propagationcharacteristics of different rock materials and compositematerials

5 Conclusions

In this work the characteristic parameter analysis andwaveform analysis of the AE signals obtained from differentexperimental schemes in 5 groups of rod-shaped rocks and 2groups of plate-shaped rocks were carried out e con-clusions are as follows

(1) e amplitude and energy of the rod-shaped rocksgradually attenuated with the increase of distancee amplitude can directly reflect the intensity of theAE counts at different measuring areas In theprocess of elastic wave propagation of the rod-sha-ped rock the P-wave preceded the S-wave andchanged violently e elastic wave of marble at-tenuated faster and the elastic wave of the threekinds of granite decayed attenuated closely Amongthem the elastic wave of TBG exhibited the fastestattenuation

(2) In flat plate-shaped rocks the amplitude exhibited anapproximate exponential attenuation characteristicwith the increase of the propagation distanceGranite exhibited a stronger elastic wave attenuationin the 0deg direction than the marble and the marblepresented fast attenuations in the 45deg and 90deg di-rections e energy change of marble was dramaticand the energy value in the interval of 45ndash55 cm atthe direction of 0deg showed the abnormal step phe-nomenon e energy value of the marble increasedafter 55 cm in the 45deg direction e energy value of

granite from the back to the end of the plate wasalmost maintained and tended to be stable at20ndash50mVms

(3) e frequency range of the energy distribution ofsamples in this work was within 0ndash36428 kHz Withthe increase of distance the main dominant energydistribution of the 5 groups of rod-shaped rocks inthe frequency range was characterized by distribu-tion to relative concentration and rapid energy at-tenuationemain dominant energy distribution ofthe 2 groups of plate-shaped rocks was distributed inthe range of 0ndash17678 kHz All rod-shaped rocks andplate-shaped rocks exhibited the characteristics ofresidual energy distribution in the frequency band of28225ndash35256 kHz

Data Availability

e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

e authors certify that they have no conflicts of interest

Acknowledgments

is research was funded by the National Natural ScienceFoundation of China (51804161 52074156 and 52004291)the Chinese Postdoctoral Science Foundation(2019M660861) and the State Key Laboratory CultivationBase for Gas Geology and Gas Control (Henan PolytechnicUniversity) (WS2020A04)

References

[1] J T Chen J H Zhao S C Zhang Y Zhang F Yang andM Li ldquoAn experimental and analytical research on theevolution of mining cracks in deep floor rock massrdquo Pure andApplied Geophysics vol 177 no 11 pp 5325ndash5348 2020

[2] K Wang and F Du ldquoCoal-gas compound dynamic disastersin China a reviewrdquo Process Safety and Environmental Pro-tection vol 133 pp 1ndash17 2020

[3] C Zhu M He M Karakus X Cui and Z Tao ldquoInvestigatingtoppling failure mechanism of anti-dip layered slope due toexcavation by physical modellingrdquo Rock Mechanics and RockEngineering vol 53 no 11 pp 5029ndash5050 2020

[4] X Wang C Liu S Chen L Chen K Li and N Liu ldquoImpactof coal sectorrsquos de-capacity policy on coal pricerdquo AppliedEnergy vol 265 Article ID 114802 2020

[5] D Liu Z Gu R Liang et al ldquoImpacts of pore-throat systemon fractal characterization of tight sandstonesrdquo Geofluidsvol 2020 no 9 17 pages Article ID 4941501 2020

[6] J Wang Y Zhang Z Qin S Song and P Lin ldquoAnalysismethod of water inrush for tunnels with damaged water-resisting rock mass based on finite element method-smoothparticle hydrodynamics couplingrdquo Computers and Geo-technics vol 126 Article ID 103725 2020

[7] B Chen S C Zhang Y Y Li Z K Li and H J ZhouldquoPhysical simulation study of crack propagation and insta-bility information discrimination of rock-like materials withfaultsrdquo Arabian Journal of Geosciences vol 13 p 966 2020

18 Advances in Civil Engineering

[8] F Du K Wang X Zhang C Xin and G Wang ldquoExperi-mental study of coal-gas outburst insights from coal-rockstructure gas pressure and adsorptivityrdquo Natural ResourcesResearch vol 29 no 4 pp 2481ndash2493 2020

[9] H Y Wang J Ma G D Wang et al ldquoResearch on AE sourcelocation of linear and plane rock massrdquo Shock and Vibrationvol 2020 Article ID 8846582 18 pages 2020

[10] V A Mansurov ldquoPrediction of rockbursts by analysis ofinduced seismicity datardquo International Journal of Rock Me-chanics and Mining Sciences vol 38 no 6 pp 893ndash901 2001

[11] M C He J L Miao and J L Feng ldquoRock burst process oflimestone and its acoustic emission characteristics under true-triaxial unloading conditionsrdquo International Journal of RockMechanics and Mining Sciences vol 47 no 2 pp 286ndash2982010

[12] F Gong J Yan X Li and S Luo ldquoA peak-strength strainenergy storage index for rock burst proneness of rock ma-terialsrdquo International Journal of Rock Mechanics and MiningSciences vol 117 pp 76ndash89 2019

[13] F Du and KWang ldquoUnstable failure of gas-bearing coal-rockcombination bodies insights from physical experiments andnumerical simulationsrdquo Process Safety and EnvironmentalProtection vol 129 pp 264ndash279 2019

[14] S D Butt C Mukherjee and G Lebans ldquoEvaluation ofacoustic attenuation as an indicator of roof stability in ad-vancing headingsrdquo International Journal of Rock Mechanicsand Mining Sciences vol 37 no 7 pp 1123ndash1131 2000

[15] M Cai H Morioka P K Kaiser et al ldquoBack-analysis of rockmass strength parameters using ae monitoring datardquo Inter-national Journal of Rock Mechanics and Mining Sciencesvol 44 no 4 pp 538ndash549 2007

[16] D P Jansen S R Carlson R P Young and D A HutchinsldquoUltrasonic imaging and acoustic emission monitoring ofthermally induced microcracks in Lac du Bonnet graniterdquoJournal of Geophysical Research Solid Earth vol 98 no B12pp 22231ndash22243 1993

[17] U Bismayer ldquoEarly warning signs for mining accidentsdetecting crackling noiserdquo American Mineralogist vol 102no 1 pp 3-4 2017

[18] X Kong E Wang S Li H Lin P Xiao and K ZhangldquoFractals and chaos characteristics of acoustic emission energyabout gas-bearing coal during loaded failurerdquo Fractals vol 27no 5 Article ID 195072 2019

[19] F Du K Wang G Wang Y Jiang C Xin and X ZhangldquoInvestigation of the acoustic emission characteristics duringdeformation and failure of gas-bearing coal-rock combinedbodiesrdquo Journal of Loss Prevention in the Process Industriesvol 55 pp 253ndash266 2018

[20] R P Young D A Hutchins S Talebi et al ldquoLaboratory andfield investigations of rockburst phenomena using concurrentgeotomographic imaging and acoustic emissionmicroseismictechniquesrdquo Seismicity in Mines vol 129 no 3-4pp 647ndash659 1989

[21] X Jansen H Xu M He and F Zhang ldquoExperimental in-vestigation of the occurrence of rockburst in a rock specimenthrough infrared thermography and acoustic emissionrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 93 pp 250ndash259 2017

[22] R E Goodman and E Richard ldquoSubaudible noise duringcompression of rocksrdquo Geological Society of America Bulletinvol 74 no 4 pp 487ndash490 1963

[23] M Cai P K Kaiser H Morioka et al ldquoFLACPFC couplednumerical simulation of AE in large-scale underground

excavationsrdquo International Journal of Rock Mechanics andMining Sciences vol 44 no 4 pp 550ndash564 2007

[24] V Saltas F Vallianatos D Triantis T Koumoudeli andI Stavrakas ldquoNon-extensive statistical analysis of acousticemissions series recorded during the uniaxial compression ofbrittle rocksrdquo Physica A Statistical Mechanics and Its Ap-plications vol 528 Article ID 121498 2019

[25] V Saltas I Fitilis and F Vallianatos ldquoA combined complexelectrical impedance and acoustic emission study in limestonesamples under uniaxial loadingrdquo Tectonophysics vol 637pp 198ndash206 2014

[26] G Qi ldquoWavelet-based AE characterization of compositematerialsrdquo NDTamp E International vol 33 no 3 pp 133ndash1442000

[27] G Manthei J Eisenblatter and T Dahm ldquoMoment tensorevaluation of acoustic emission sources in salt rockrdquo Con-struction and Building Materials vol 15 no 5-6 pp 297ndash3092001

[28] H Jeong and Y-S Jang ldquoWavelet analysis of plate wavepropagation in composite laminatesrdquo Composite Structuresvol 49 no 4 pp 443ndash450 2000

[29] S-H Chang and C-I Lee ldquoEstimation of cracking anddamage mechanisms in rock under triaxial compression bymoment tensor analysis of acoustic emissionrdquo InternationalJournal of Rock Mechanics and Mining Sciences vol 41 no 7pp 1069ndash1086 2004

[30] T Hirata T Satoh and K Ito ldquoFractal structure of spatialdistribution of microfracturing in rockrdquo Geophysical JournalInternational vol 90 no 2 pp 369ndash374 1987

[31] X Lei K Masuda O Nishizawa et al ldquoDetailed analysis ofacoustic emission activity during catastrophic fracture offaults in rockrdquo Journal of Structural Geology vol 26 no 2pp 247ndash258 2004

[32] J Jouniaux J Pei J Liu et al ldquoInvestigation on acousticemission behavior and its time-space evolution mechanism infailure process of coalndashrock combined bodyrdquo Chinese Journalof Rock Mechanics and Engineering vol 30 pp 1564ndash15702011

[33] E Townend B D ompson P M Benson PG MeredithP Baud and R P Young ldquoImaging compaction bandpropagation in Diemelstadt sandstone using acoustic emis-sion locationsrdquo Geophysical Research Letters vol 35 no 15pp 189ndash193 2008

[34] M Naderloo M Moosavi and M Ahmadi ldquoUsing acousticemission technique tomonitor damage progress around jointsin brittle materialsrdquo Deoretical and Applied Fracture Me-chanics vol 104 Article ID 102368 2019

[35] GBT Unified Number of Natural Stone China StandardsPress Beijing China 2009

[36] G Shen Acoustic Emission Detection Technology and Appli-cation Science Press Beijing China 2015

[37] Y Guo Research on Wavelet Base Selection for VibrationSignal Processing Hefei University of Technology HefeiChina 2003

[38] F Xu E Wang and D Song ldquoLong-range correlation andmultifractal distribution of acoustic emission of coal-rockrdquoRock and Soil Mechanics vol 32 no 7 pp 2111ndash2116 2011

Advances in Civil Engineering 19

data acquisition system mainly included the DS5-8B AEanalyzer RS-2A AE sensor adjustable gain amplifier ex-citation pulse source signal gain amplifier relevant dataacquisition processing software and computer As the peak

frequency of the RS-2A AE sensor was 150 kHz it can re-ceive an AE signal in the range of 60ndash400 kHz To meet theaccuracy of experimental data acquisition the samplingfrequency was set to 3MHz

Table 1 Parameters of the rod-shaped and plate-shaped rock samples

Scientific name Number Type SizemmLength times width times thickness

Wu Lianhong G3768 Granite 1440times 38times15Ma Hui stone G3561 Granite 2150times 40times 20Tan Brown TBG Granite 1400times 60times16Ariston AAM Artificial marble 1500times 59times12Giallo Atlantide GAM Marble 1000times 30times18Wu Lianhong lamel G3761-L Granite 2220times 620times12Giallo Atlantide lamel GAM-L Marble 1780times 760times15

Figure 1 e sensors network layout for the rod-shaped rock samples

Table 2 e coordinates of sensors on the rod-shaped rock samples

Number of rocksNumber of sensors

S1 S2 S3 S4 S5 S6G3768 5 20 50 70 100 135G3561 5 20 50 70 100 135TBG 5 20 50 70 100 135AAM 5 20 50 70 100 135GAM 5 20 50 70 100 -e location of each sensor is the distance from the right end of the fixed bar cm

1780cm

760

cm

(8930)0deg

45deg90deg

x

y

GAM-L

(a)

2220cm

620

cm

(111205)0deg

45deg90deg

x

y

G3761-L

(b)

Figure 2 e diagram of sensor placement plate-shaped rock (a) GAM-L (b) G3761-L

Advances in Civil Engineering 3

232 Setting of Acoustic Emission Detection ParametersBefore the experiment it is necessary to reasonably set therelevant parameters of the AE instrumentndashincluding thedetection threshold timing parameters and wave speedndashtotruly reflect the characteristics of the AE source It should benoted that the propagation speed of the wave is the materialproperty related to the elastic modulus and density of themedium which is the inherent property of the materialGenerally the wave velocity is mainly used for the locationcalculation of the AE source and its uncertainty becomes themain factor affecting the source location In the process ofactual source location the experimental measurement ofwave velocity is needed first However the experiments ofthis work focus on collecting the characteristic parametersand waveform information of the AE signal to study thepropagation characteristics of the elastic wave which doesnot involve the location of the AE source erefore theexperimental acquisition of wave velocity is not the focus ofthis work as it does not affect the acquisition of the researchobjectives of this paper

(1) Detection threshold setting

e indoor environment of this experiment was rela-tively quiet Under the general rules of different thresholdsettings and applicable scope the threshold value of theexperimental system should be carried out at a mediumsensitivity of 35ndash55 dB After the connection of the exper-imental system the AE data acquisition and processingsystem are activated and the entire channel is set at 50mVAt this time the threshold value is about 40 dB based on unitconversion meeting the experimental requirement

(2) Timing parameter setting

In this experiment lead breaking was used to simulatethe AE source Combined with the recommended values ofmetal materials and composite materials summarized inrelevant literature [36] the optimal timing parameters aredetermined including peak definition time (PDT) hitdefinition time (HDT) and hit locking time (HLT) etiming parameters are shown in Table 3

3 Analysis of Experimental Results of ElasticWave Propagation Characteristics

rough the implementation of the above experimentalscheme and the reasonable setting of relevant parameters ofthe AE acquisition instrument effective AE signals of theelastic waves in the propagation process were obtained echaracteristics and parameters of the AE signals and thewaveforms of the AE signals were processed and analyzedand the discussion was carried oute specific experimentalresults and analysis are as follows

31Analysis ofCharacteristic Parameters ofAcoustic EmissionSignals

311 Characteristic Parameter Analysis of Rod-Shaped RockAmplitude frequency and duration are the three elementsthat could be used to describe microvibration or micro-fracture By analyzing the amplitude changes of the moni-toring points at different positions the elastic wave intensitychange trend in the rod can be determined e frequencyinformation at the monitoring points can be used to identifythe area where the AE events are concentrated e types ofAE signals can be clearly identified based on the durationwaveform changes Two characteristic parameters of energycount and amplitude are used to analyze the propagationcharacteristics of elastic waves of different rod-shaped rocksAccording to the definition of energy count since the ac-quisition system obtains discrete point data the energy ofthe AE signal is expressed as

E 1113944N

i1V(i)

2 (1)

where N is the number of discrete points of the AE signalsand V(i) represents the amplitude of the signal discretepoints e amplitude usually reflects the magnitude of theevent [28] and the attenuation characteristics of the AE signalwaveform can be explored through the change in amplitude

+ndash60dB20dB40dB

60dB20dB40dB

40dB20dB60dB

40dB20dB60dB

40dB20dB60dB

USB

6

7

1 2 3

4

5

Figure 3 Experimental system 1 RS-2A sensor 2 adjustable gain amplifier 3 adjustable gain amplifier of excitation pulse source 4computer 5 acoustic emission analyzer 6 top view of the position of the end face excitation pulse signal 7 profile of the position ofterminal excitation pulse signal

4 Advances in Civil Engineering

Assuming that the AE signal is monitored at a distance of5 cm from the pulse excitation source as the reference theamplitude relative attenuation rate and energy relative at-tenuation rate of the elastic wave passing through the robcan be expressed as

ΔAj 20lgAj

As1 (2)

ΔEj 20lgEj

Es1 (3)

where As1 and Es1 represent the amplitude and energyparameters measured at point s1 (j s2 s3 s4 s5 s6)

Taking the existence of error factors into considerationpulse vibration was carried out four times for each group ofrock and the average value of the results was taken fordiscussion e curves of the energy and amplitude distancerelative attenuation rate for each group of rocks are shown inFigure 4

It can be seen from Figure 4 that the characteristicparameters of amplitude and energy in the rod-shaped rocksshow the characteristics of gradual attenuation with theincrease of distance Compared with the characteristic pa-rameter values collected at the 5 cm measuring point therelative attenuation rate of amplitude is greater than that ofenergy It shows that the amplitude directly reflects theintensity of the AE events at different measuring pointsHowever the energy only reflects the relative intensity ofevents which is affected by factors such as threshold valueand working frequency and the relative attenuation ratewith distance cannot show the energy change characteristicsof the AE signals e relative attenuation rate of the S-wavegenerated by the source signal excited by the pulse on theend surface of each group of rocks is lower than that of thepulse compression wave at the terminal area indicating thatthe P-wave came before the S-wave in the process of linearelastic wave propagation and changed violently

e mutation points of the relative amplitude attenua-tion rate both appear at the measuring point of 100 cm forG3768 G3561 and TBG because the length of G3768 andTBG is close to their amplitudes Furthermore the relativeattenuation rate tends to be stable after 100 cm e ab-normal phenomenon appears after 100 cm because the AEsignal produced by the excitation pulse in the terminal areaof TBG suddenly increases It shows that even if the rockwith the same lithology is limited by its complex compo-sition anisotropy and size the AE wave propagation doesnot decay exponentially but exhibits a sudden attenuationcharacteristic Moreover because of the fast propagationspeed of the P-wave the reflection of the rock boundary onthe original AE signal is superimposed on the original signal

and the frequency dispersion of the original signal increaseswith the increase of the propagation distance As a result thesignal after 100 cm in TBG is a mixed distortion signal elength of G3561 is 2150 cm and its relative attenuation rateof energy and amplitude exhibited decreasing trends erelative attenuation rates of energy at the 70 cm measuringpoint were abnormal which were respectively 15 dB and09 dB compared with those at the 5 cm measuring pointe relative attenuation rates of energy at the previous 50 cmmeasuring point were 13 dB and 11 dB respectively eattenuation in this section was relatively weak which may becaused by the gap in the transverse boundary of this rod-shaped rock e abnormal superposition of the boundarywave on the original wave enhanced the original AE signal

For different groups of rocks with different lithologiesthe relative attenuation rates of the amplitude and energy ofAAM presented a relatively flat attenuation trend andslightly strengthened from the position of the 100 cm abruptpoint to the end of the rod is indicates that the atten-uation characteristics of elastic wave propagation were clearwithout abnormal mutation even though the composition ofthe artificial stone is complicated is is because vacuumpressure technology was used to press the binder and varioussizes of crushed stone under vacuum vibration and pressureIt was then made by cutting and grinding erefore itsductility and compactness were good For marble materialGAM with a size of only 100 cm the relative attenuationrates of the amplitude of the end and terminal pulse exci-tation at 50 cm were 373 dB and 366 dB respectively ForG3768 these two values at 70 cm were 193 dB and 223 dBrespectively For the other four rock samples these twovalues at 70 cm were as follows 179 dB and 177 dB forG3561 232 dB and 261 dB for TBG and 256 dB and 271 dBfor AAM It can be seen that the elastic wave attenuation wasthe fastest in the marble and the elastic wave attenuation ofthe three types of granite was similar Among them the TBGhad the fastest elastic wave attenuation In general the at-tenuation of the P-wave came before the S-wave

312 Characteristic Parameter Analysis of Rod-Shaped RockAccording to the experimental schemes of the G3761-L andGAM-L samples the elastic wave propagation characteris-tics in the thin plate-shaped rock were discussed by ana-lyzing the changes in the amplitude of the AE signalsConsidering the error factor pulse vibration was carried outfour times for each group of rod-shaped rocks where theaverage value of the results was taken for discussion eattenuation curves of the amplitude of each measuring pointin different directions and different lithological samples arepresented in Figure 5

Table 3 Timing parameters in the experiment

Timing parameter G3768 G3561 TBG AAM GAM G3761-L GAM-LPDTμs 100 150 150 150 150 100 100HDTμs 200 300 300 300 300 200 200HLTμs 300 500 500 500 500 300 300

Advances in Civil Engineering 5

Amplitude

Energy

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

TBGRelat

ive d

ecay

rate

(dB)

Distance (cm)

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

AAMRelat

ive d

ecay

rate

(dB)

Amplitude

Energy

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

G3768Relat

ive d

ecay

rate

(dB)

Distance (cm)

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash3

ndash2

ndash1

0

G3561

Relat

ive d

ecay

rate

(dB)

Amplitude

Energy

Distance (cm)

20 50 70 100ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

GAM

(a)

Figure 4 Continued

6 Advances in Civil Engineering

It can be seen from Figure 5 that the amplitude of thelarge-scale plane plate rock showed similar exponentialattenuation characteristics with the increase of the propa-gation distance e AE wave attenuation of granite wasstronger than that of marble in the direction of 0deg and wasweaker than that of marble in the directions of 90deg and 45deg

Specifically due to the diversity and anisotropy of rockcomponents the attenuation of the AE wave in the range of20ndash80 cm in the direction of 0deg showed the fluctuation ofamplitude between 72 and 83 dB in both kinds of rockthough the overall trend was declining e amplitudecharacteristic parameters extracted from each measuring

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash5

ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

G3768

Amplitude

Energy

Distance (cm)

20 50 70 100 135

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

G3561

Amplitude

Energy

Distance (cm)

20 50 70 100 135

ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

TBG

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

AAM

Amplitude

Energy

Distance (cm)

20 50 70 100ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

GAM

(b)

Figure 4 e attenuation rates of energyamplitude with distance (a) End-pulse excitation (S-wave) (b) Terminal pulse excitation (P-wave)

Advances in Civil Engineering 7

point arranged in the front and back of the marble in the 45degdirection and 90deg direction presented significant changes Asudden decrease of amplitude appeared at 30ndash40 cm with adecrease of 1965 dB in the 45deg direction and 2455 dB in the90deg directione amplitude attenuation of granite tended tobe stable

e attenuation curves of the AE energy in differentdirections for G3761-L and GAM-L are shown in Figure 6 Itcan be seen that the energy in the marble changes violentlyand the energy value in the range of 45ndash55 cm in the di-rection of 0deg exhibits the abnormal phenomenon of stepeenergy attenuation was lower than that of the granite stonewhich shows the same trend with the amplitude attenuatione energy value of granite from 45 cm back to the end of thethin plate is almost maintained at 20ndash50mVms and tends tobe stable In the 45deg direction the marble exhibited theenhancement of energy value after 55 cm It is the reflectionof the AE wave along the 45deg direction when it met theboundary and the wave enhancement phenomenon wasformed by the superposition of multiple reflections andrefractions e marble and granite showed the same trendin the 90deg direction

32 Waveform Analysis of Acoustic Emission Signal

321 Time Domain Waveform and Spectrum Analysis ofAcoustic Emission Original Signal According to a largenumber of AE signal waveforms obtained by pulse excitationon the surface of each group of samples the AE signalwaveforms of rod-shaped and plate-shaped rocks were se-lected from the closest measuring point to the pulse sourcee middle measuring point in their respective directionsand the end measuring points were analyzed e specificlayout of measuring points is presented in Table 4

Since the original statistics of the nonstationary AEsignal is a time-varying function FFT transform was used toanalyze the spectral characteristics of the time-domain signalto better understand the variation law of elastic wave in thepropagation process Figure 7 presents the original signaltime-domain waveforms of measuring point M2 of eachgroup of rod-shaped rocks and the corresponding frequencyspectrum is shown in Figure 8 e related curves of the AE

signal excited from measuring points M2 on the surface ofthe plate-shaped rocks in the three directions of 0deg 90deg and45deg are shown in Figure 9

It can be seen from the time-domain diagram that thewaveforms of the AE signal generated by pulse excitationwere very similar and the duration was short For the rod-shaped rocks the durations for granites G3768 G3561 andTBG were in the range of 025ndash15ms where the waveformsdecayed quickly and the coda waves were not developede durations for AAM and GAM were in the range of05ndash20ms and 05ndash10ms respectively For the plate-shapedrocks the duration of G3761-L was 05ndash15ms in the 0degdirectione duration for GAM-L was 025ndash15ms and theamplitude attenuation variation was small Similarly in the45deg direction and 90deg direction the G3761-l granite showed ashorter duration of time than the GAM-L marble dem-onstrating that the homogeneity of the natural granite plate-shaped rock is better

It can be seen from the spectrum that the frequency ofthe AE signal generated by pulse excitation was relativelyhigh and the frequency band was relatively narrow emain frequency domain of each group of rod-shaped rockswas 0ndash250 kHz and the frequency domain of the AE signalat the M2 position measuring point in each direction of theplate-shaped rocks was 0ndash300 kHz In this frequency do-main each group of samples with different lithologies showsmultiple peaks of frequency indicating that the waveform ofthe AE signal is very complex and is a mixture of waves withdifferent characteristics

322 Wavelet Packet Energy Analysis of Acoustic EmissionSignal According to previous research wavelet transformonly decomposes the low-frequency partndashbut not the high-frequency part of the original signal e time-frequencylocalization could be better analyzed through the intro-duction of wavelet packet transform in which the high-frequency part of the signal could be further decomposed Asshown in Table 4 considering that wavelet packet analysishas the advantages of multilayer decomposition of signaldetails and scale information the following wavelet packetenergy feature extraction was conducted for the AE signal

0 20 40 60 80 100 12060

65

70

75

80

85

90

95

100A

mpl

itude

(dB)

G3761-L

GAM-L

0deg

Distance (cm)

G3761-L

GAM-L

0 10 20 30 40 50 6050

60

70

80

90

100

45deg

Distance (cm)

Am

plitu

de (d

B)

G3761-L

GAM-L

0 10 20 30 40 5050

60

70

80

90

100

90deg

Distance (cm)

Am

plitu

de (d

B)

Figure 5 e attenuation curves of the amplitude in different directions for G3761-L and GAM-L

8 Advances in Civil Engineering

waveform obtained at different measuring points in eachgroup of rock samples to explore the local feature infor-mation of the AE signal waveform at different positions ofrod-shaped and plate-shaped rocks

Choosing a suitable wavelet base plays an important rolein signal processing and analysis Guo [37] introduced theeffect of different wavelet bases in vibration signal processingin detail which presents that the db5 db7 db10 db13 db16bior26 bior39 coif4 sym7 and sym8 wavelet bases aremore suitable for the shock feature extraction of vibrationsignals Of this wavelet set db7 was selected as the waveletbase for the wavelet packet analysis because of its Daubechiesseries wavelet set characteristics such as high-order van-ishing moment tight support regularity approximatesymmetry and orthogonalityndashand because of the similaritiesit shares with the rock AE signal Its wavelet function ispresented in Figure 10

e sampling frequency is 3MHz According to thesampling theorem its Nyquist frequency is 1500 kHz ewavelet packet decomposition principle and algorithm wereapplied to decompose the signal to the 7th layer (ie thescale is 7) which has 27 wavelet packets in total ereforein the frequency domain the original signal was decom-posed into 128 subbands e width of each band was1172 kHz e frequency band range of each layer recon-structed after the decomposition of the original signal ispresented in Table 5

As can be seen from the table the original signal isexpressed as

S S70 + S71 + S72 + middot middot middot + S7127 (4)

where S70 is the low-frequency part of the decomposedsignal the other variables represent the decomposition of the

high-frequency part of the signal Assuming that the cor-responding energy of S7j(j 0 1 2 middot middot middot 127) isE7j(j 0 1 2 middot middot middot 127) then the energy characterization ofthe original AE signal decomposition in each frequencyband range can be obtained by formula (1)

Assuming that the total energy of the analyzed signal isE0 then

E0 1113944127

j0E7j (5)

e ratio of the energy of each frequency band to thetotal energy of the analyzed signal is

Ej E7j

E0times 100 (6)

In the formula j 012 27ndash1From Equation (1) the energy changes of the corre-

sponding AE signals in different frequency bands after theoriginal signal decomposition were calculated so the energydistribution characteristics of the elastic wave in differentfrequency bands could be found [38] According to Table 4the main frequency range of the AE signal waveform of eachmeasuring point was 0ndash300 kHz indicating that the energyvalue must also be concentrated in this frequency rangeerefore with MATLAB programming the energy dis-tribution of each subband in the frequency domain of0ndash500 kHz was obtained as shown in Figures 11 and 12

For rod-shaped rocks G3768 G3561 and TBG of thesame lithology from different places of origin the M1measuring point was closest to the pulse excitation sourceerefore the value of the M1 measuring point could ef-fectively reflect the energy value of the real pulse As can be

G3761-L

GAM-L

0deg

0 20 40 60 80 100 120

0

100

200

300

400

500

600

Distance (cm)

Ener

gy (m

Vlowast

ms)

G3761-L

GAM-L

45deg

Distance (cm)

Ener

gy (m

Vlowast

ms)

0 10 20 30 40 50 600

100

200

300

400

500

600

700

G3761-L

GAM-L

90deg

Distance (cm)

Ener

gy (m

Vlowast

ms)

0 10 20 30 40 50

100

200

300

400

500

600

700

Figure 6 e attenuation curves of the AE Energy in different directions for G3761-L and GAM-L

Table 4 e measuring point positions of AE waveforms

Rock number (measuring point) (cm) G3768 G3561 TBG AAM GAMG3761-L GAM-L

0deg 90deg 45deg 0deg 90deg 45deg

M1 5 5 5 5 5 5 5 5 5 5 5M2 70 70 70 70 50 55 20 30 40 25 30M3 135 135 135 135 100 100 35 50 75 40 50

Advances in Civil Engineering 9

seen from Figure 11 the energy is widely distributed in thefrequency domain e value of energy is generally smallwhich was mainly concentrated in the range of0ndash36428 kHz Combined with Formulas (5) and (6) it couldbe calculated that the main dominant energy of the three

groups of granite was concentrated in the frequency band of7131ndash12991 kHz which correspondingly accounted for646 5605 and 5828 of the total energy About2326 of the energy in G3561 was concentrated in thefrequency band of 23538ndash35256 kHz which is different

0 05 10 15 20 25ndash15

ndash10

ndash05

0

05

10

Am

plitu

de (m

V)

Time (ms)

G3768

TBG

0 05 10 15 20 25 3ndash08

ndash06

ndash04

ndash02

0

02

04

06

08

Am

plitu

de (m

V)

Time (ms)

G3561

0 05 10 15 20 25

ndash15

ndash10

ndash05

0

05

10

15

Time (ms)

Am

plitu

de (m

V)

AAM

0 05 10 15 2ndash20

ndash15

ndash10

ndash05

0

05

10

15

Time (ms)

Am

plitu

de (m

V)

GAM

0 05 10 15 20 25 30 35ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

Figure 7 Time domain waveform of measuring point M2 of rod-shaped rock

10 Advances in Civil Engineering

from other samples of the same lithology With the increaseof the propagation distance of the elastic wave its energyexhibited the characteristics of rapid attenuation edominant energy distribution frequency bands of the threerod-shaped rock materials at the M2 measuring point ex-panded from the initial 7131ndash12991 kHz to 0ndash17678 kHz

and the energy percentages were 8987 9407 and8658 respectively In the high-frequency band of28225ndash31741 kHz there was respectively 10 and 1269energy concentration for G3768 and TBG When the elasticwave propagated to the end of the rod (M3) the energy ofeach group of samples was relatively concentrated and

0 100 200 300 400 5000

001

002

003

004

Am

plitu

de (m

V)

Frequency (KHz)

G3768

TBG

0 100 200 300 400 5000

001

002

003

Am

plitu

de (m

V)

Frequency (KHz)

G3561

0 100 200 300 400 5000

001

002

003

004

005

006

007

Frequency (KHz)

Am

plitu

de (m

V)

AAM

0 100 200 300 400 5000

001

002

003

004

005

006

Frequency (KHz)

Am

plitu

de (m

V)

GAM

0 100 200 300 400 5000

0002

0004

0006

0008

0010

0012

Am

plitu

de (m

V)

Frequency (KHz)

Figure 8 e spectrogram of measuring point M2 of rod-shaped rock

Advances in Civil Engineering 11

G3761-L(90deg)

0 05 10 15 2ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

G3761-L(90deg)

0 100 200 300 400 500000

002

004

006

008

010

Am

plitu

de (m

V)

Frequency (KHz)

G3761-L(45deg)

0 05 10 15 20 25

ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

G3761-L(45deg)

0 100 200 300 400 5000

001

002

003

004

005

006

007

Am

plitu

de (m

V)

Frequency (KHz)

0 05 10 15 20 25 3ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

G3761-L(0deg)

Am

plitu

de (m

V)

Time (ms)

G3761-L(0deg)

0 100 200 300 400 5000

0002

0004

0006

0008

0010

Am

plitu

de (m

V)

Frequency (KHz)

(a)

Figure 9 Continued

12 Advances in Civil Engineering

mainly distributed within 0ndash10647 kHz at the percentages of9211 9022 and 9188 respectively By comparing thethree groups of rod-shaped rocks with the same lithology itcan be seen that the energy attenuation was the fastest inTBG and the dominant energy value was the lowest at theM3 measuring point For G3768 the energy attenuation wasthe slowest Only the distribution rule of the dominant

energy value at the M2 and M3 measuring points changedwhereas the maximum energy value hardly changed ereason may be that the internal structure or componentdensity of G3768 was better and the energy was relativelymaintained rather than rapidly attenuated with the elasticwave propagation For AAM artificial marble its maindominant energy also exhibited the same change trend as

GAM-L(45deg)

0 05 10 15 20 25

ndash3

ndash2

ndash1

0

1

2

3

4

Am

plitu

de (m

V)

Time (ms)

GAM-L(45deg)

0 100 200 300 400 5000

002

004

006

008

010

012

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(0deg)

0 05 10 15 20 25 30 35

ndash09

ndash06

ndash03

0

03

06

09

Am

plitu

de (m

V)

Time (ms)

GAM-L(0deg)

0 100 200 300 400 5000

0005

0010

0015

0020

0025

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(90deg)

0 05 10 15 20 25ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

GAM-L(90deg)

Am

plitu

de (m

V)

0 100 200 300 400 500000

002

004

006

008

010

Frequency (KHz)

(b)

Figure 9 e time waveform and spectrogram of measuring point M2 of pate-shaped rock

Advances in Civil Engineering 13

0 3 6 9 12 15ndash15

ndash10

ndash05

00

05

10

Wavelet function

0 3 6 9 12 15

ndash05

00

05

10

Scaling function

Figure 10 Wavelet function and scaling function for db7

Table 5 e frequency band range of reconstructed signal by wavelet packet decomposition

Layer S (i 0) S (i 1) S (i 2) S (i jminus 1) S (i j)1 0ndash750 ndash ndash ndash ndash 750ndash15002 0ndash375 375ndash750 750ndash1125 ndash ndash 1125ndash15003 0ndash1875 1875ndash375 375ndash5625 1125ndash13125 13125ndash15004 0ndash9375 9375ndash1875 1875ndash28125 13125ndash140625 140625ndash15005 0ndash46875 46875ndash9375 9375ndash140625 140625ndash1453125 1453125ndash15006 0ndash234375 234375ndash46875 46875ndash703125 1453125ndash14765625 14765625ndash15007 0ndash1171875 1171875ndash234375 234375ndash3515625 14765625ndash148828125 148828125ndash1500S (i j) represents the reconstruction signal of the j-th wavelet packet decomposition coefficient in the i-th layer i 1234 j 012 2i-1

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M3

(a)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500

1000

1500

2000

2500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

20

40

60

80

100

120

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

M3

(b)

Figure 11 Continued

14 Advances in Civil Engineering

granite From Figure 11 it can be observed that the energy ofthe original pulse signal is concentrated in the range of9475ndash16506 kHz and 2185 of the energy existed in thefrequency band of 28225ndash35256 kHz For GAMmarble themain dominant energy distribution of the initial signal wasvery wide and was distributed in the frequency band of0ndash36428 kHz Among them the dominant energy wasdistributed within the 10647ndash12991 kHz range accountingfor 3213 of the total energy Similar attenuation charac-teristics as granite were presented with the increase of elasticwave propagation distance In general for GAM the exci-tation energy of the AE signal generated by pulse excitationwas the weakest and the attenuation was the fastest with theincrease of distancee initial excitation energy of the threegroups of granite was partially concentrated in the frequency

band of 23538ndash35256 kHz of which the performance ofG3561 was the most obvious

e pulse AE signal was very complex for 2 groups of theplate-shaped rocks (Figure 12) erefore the initial energyof the M1 measuring point in each direction was also quitedifferent In the direction of 0deg the dominant energy of theoriginal pulse signal in G3761-L was concentrated in thefrequency band of 0ndash17678 kHz which accounted for8904 of the total energy Meanwhile about 628 of theenergy was distributed in the frequency band of29397ndash32913 kHz e same law was also shown in GAM-L but the main dominant frequency in GAM-L was rela-tively concentrated in the short frequency band of10647ndash17678 kHz which accounted for 6357 of the totalenergy With the spread of the elastic wave the energy in

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50002468

10121416

M3

(c)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5001000150020002500300035004000

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40

50

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M3

(d)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

100

200

300

400

500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M2

0 100 200 300 400 5000

2

4

6

8En

ergy

(mVlowast

mS)

Frequency (KHZ)

M3

0 100 200 300 400 500012345678

(e)

Figure 11e energy distribution of acoustic emission signal frequency band of rod-shaped rock (a) G3768 (b) G3561 (c) TBG (d) AAM(e) GAM

Advances in Civil Engineering 15

0 100 200 300 400 5000

200400600800

100012001400

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

M2

0 100 200 300 400 5000005101520253035

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

M3

0 100 200 300 400 50000020406081012

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

(a)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40En

ergy

(mVlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 5000

2

4

6

8

Ener

gy (m

Vlowast

mS)

(b)

M1

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

1020304050607080

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50002468

1012141618

Ener

gy (m

Vlowast

mS)

(c)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700800

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 50005

101520253035

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

Ener

gy (m

Vlowast

mS)

(d)

Figure 12 Continued

16 Advances in Civil Engineering

G3761-L showed a trend of attenuation and the energy intheM2measuring point was still distributed in the frequencyband of 0ndash17678 kHz e energy distribution at the M3measuring point was relatively concentrated and was locatedin the frequency band of 0ndash10647 kHz accounting for8340 of the total energy e energy at the measuringpoint M3 of GAM-L was more extensive in the frequencydomain and the energy value changed dramatically dem-onstrating the abnormal phenomenon that the maindominant energy increased e frequency range of thismeasuring point was 0ndash1885 kHz accounting for 8589 ofthe total energyere was also residual energy concentratedin the frequency band of 29397ndash32913 kHz e AE signalat M3 was superposed by the boundary reflection wave andthe energy was enhanced because of the high homogeneityand good ductility of GAM-L For G3761-L the dominantenergy of the elastic wave almost dissipated at the M3measuring point In the direction of 45deg the dominantenergy band of the original signal in G3761-L was distributedwithin 0ndash17678 kHz and 28225ndash35256 kHz respectivelyaccounting for 6415 and 3278 of the total energyMoreover it can be observed that the distribution of thedominant energy band was from distribution to concen-tration which was distributed in the frequency band of7131ndash17678 kHz at M2 With the increase of distance theenergy frequency band of the M3 measuring point near theedge of the plate was spread again and it was restored to theenergy frequency band range of the initial signal Howeverthe energy value was attenuated to a very small value at this

moment e energies of GAM-L in the measuring pointsM1 M2 and M3 were all distributed in the frequency bandof 0ndash36428 kHz In the direction of 90deg the primarydominant energy frequency bands of the two plate-shapedrocks were concentrated in 9475ndash1885 kHz e differenceis that the energy distribution of GAM-L was still con-centrated and the energy variation was much smaller thanG3761-L at the M2 measuring point In general the energyfrequency band of the two plate-shaped rocks with differentlithologies was the same as that of the rod-shape rock whichis mainly distributed in the range of 0ndash36428 kHz More-over they also exhibited the characteristics that the maindominant energy was distributed in the range of0ndash17678 kHz and the residual energy was distributed in therange of 28225ndash35256 kHz

4 Discussion

e purpose of this work was to study the propagationcharacteristics of elastic wave in lithological rock materialsrough the above research and analysis a preliminaryunderstanding was obtained Based on the deep waveletpacket analysis of amplitude energy characteristic param-eters and AE waveform the frequency band characteristicsof the local energy distribution of elastic wave with itspropagation were summarized However its propagationcharacteristics are difficult to be regularly grasped becausethe elastic wave itself is extremely complex Furthermore AEtechnology is mostly used in the damage detection and

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

20406080

100120140160

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

10

20

30

40

50

(e)

M1

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

200400600800

10001200140016001800

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

50

100

150

200

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 50005

101520253035

(f )

Figure 12e energy distribution of acoustic emission signal frequency band of plate-shaped rock (a) G3761-L (00) (b) G3761-L (450) (c)G3761-L (900) (d) GAM-L (00) (e) GAM-L (450) (f ) GAM-L (900)

Advances in Civil Engineering 17

defect location of metal or related materials with goodcompactness ductility and within the same medium ereare many uncertain interference factors in the experimentsIn some aspects the analysis of this paper only stays at thelevel of the apparent phenomenon and there are still manydeficiencies and areas worthy of improvement For instancethe density wave velocity and wave impedance of the rod-shaped rock samples should be tested and the micro-structure imaging experiments of the rock samples should beconducted e quality factor Q of different rock samplesshould be calculated Moreover the correlation between thequality factor and wave impedance should be studied andthe influence of different microcompositions of rod-shapedrocks on elastic wave attenuation should be deeply analyzedBased on the modal AE theory the influence of Lamb wavein plate-shaped rocks should be studied and the propagationmodel of two-dimensional AE should be constructed eGabor wavelet should be introduced to analyze the AE signalby time-frequency analysis e influence of differentwavelets based on the propagation effect of AE will becompared and analyzed and the time of the same mode ofthe AE wave arriving at the sensor will be determined tofurther optimize the plane location algorithm However theresearch in this work is still useful for studying large-scalerock samples in the future and provides effective researchmethods and ideas for the study of elastic wave propagationcharacteristics of different rock materials and compositematerials

5 Conclusions

In this work the characteristic parameter analysis andwaveform analysis of the AE signals obtained from differentexperimental schemes in 5 groups of rod-shaped rocks and 2groups of plate-shaped rocks were carried out e con-clusions are as follows

(1) e amplitude and energy of the rod-shaped rocksgradually attenuated with the increase of distancee amplitude can directly reflect the intensity of theAE counts at different measuring areas In theprocess of elastic wave propagation of the rod-sha-ped rock the P-wave preceded the S-wave andchanged violently e elastic wave of marble at-tenuated faster and the elastic wave of the threekinds of granite decayed attenuated closely Amongthem the elastic wave of TBG exhibited the fastestattenuation

(2) In flat plate-shaped rocks the amplitude exhibited anapproximate exponential attenuation characteristicwith the increase of the propagation distanceGranite exhibited a stronger elastic wave attenuationin the 0deg direction than the marble and the marblepresented fast attenuations in the 45deg and 90deg di-rections e energy change of marble was dramaticand the energy value in the interval of 45ndash55 cm atthe direction of 0deg showed the abnormal step phe-nomenon e energy value of the marble increasedafter 55 cm in the 45deg direction e energy value of

granite from the back to the end of the plate wasalmost maintained and tended to be stable at20ndash50mVms

(3) e frequency range of the energy distribution ofsamples in this work was within 0ndash36428 kHz Withthe increase of distance the main dominant energydistribution of the 5 groups of rod-shaped rocks inthe frequency range was characterized by distribu-tion to relative concentration and rapid energy at-tenuationemain dominant energy distribution ofthe 2 groups of plate-shaped rocks was distributed inthe range of 0ndash17678 kHz All rod-shaped rocks andplate-shaped rocks exhibited the characteristics ofresidual energy distribution in the frequency band of28225ndash35256 kHz

Data Availability

e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

e authors certify that they have no conflicts of interest

Acknowledgments

is research was funded by the National Natural ScienceFoundation of China (51804161 52074156 and 52004291)the Chinese Postdoctoral Science Foundation(2019M660861) and the State Key Laboratory CultivationBase for Gas Geology and Gas Control (Henan PolytechnicUniversity) (WS2020A04)

References

[1] J T Chen J H Zhao S C Zhang Y Zhang F Yang andM Li ldquoAn experimental and analytical research on theevolution of mining cracks in deep floor rock massrdquo Pure andApplied Geophysics vol 177 no 11 pp 5325ndash5348 2020

[2] K Wang and F Du ldquoCoal-gas compound dynamic disastersin China a reviewrdquo Process Safety and Environmental Pro-tection vol 133 pp 1ndash17 2020

[3] C Zhu M He M Karakus X Cui and Z Tao ldquoInvestigatingtoppling failure mechanism of anti-dip layered slope due toexcavation by physical modellingrdquo Rock Mechanics and RockEngineering vol 53 no 11 pp 5029ndash5050 2020

[4] X Wang C Liu S Chen L Chen K Li and N Liu ldquoImpactof coal sectorrsquos de-capacity policy on coal pricerdquo AppliedEnergy vol 265 Article ID 114802 2020

[5] D Liu Z Gu R Liang et al ldquoImpacts of pore-throat systemon fractal characterization of tight sandstonesrdquo Geofluidsvol 2020 no 9 17 pages Article ID 4941501 2020

[6] J Wang Y Zhang Z Qin S Song and P Lin ldquoAnalysismethod of water inrush for tunnels with damaged water-resisting rock mass based on finite element method-smoothparticle hydrodynamics couplingrdquo Computers and Geo-technics vol 126 Article ID 103725 2020

[7] B Chen S C Zhang Y Y Li Z K Li and H J ZhouldquoPhysical simulation study of crack propagation and insta-bility information discrimination of rock-like materials withfaultsrdquo Arabian Journal of Geosciences vol 13 p 966 2020

18 Advances in Civil Engineering

[8] F Du K Wang X Zhang C Xin and G Wang ldquoExperi-mental study of coal-gas outburst insights from coal-rockstructure gas pressure and adsorptivityrdquo Natural ResourcesResearch vol 29 no 4 pp 2481ndash2493 2020

[9] H Y Wang J Ma G D Wang et al ldquoResearch on AE sourcelocation of linear and plane rock massrdquo Shock and Vibrationvol 2020 Article ID 8846582 18 pages 2020

[10] V A Mansurov ldquoPrediction of rockbursts by analysis ofinduced seismicity datardquo International Journal of Rock Me-chanics and Mining Sciences vol 38 no 6 pp 893ndash901 2001

[11] M C He J L Miao and J L Feng ldquoRock burst process oflimestone and its acoustic emission characteristics under true-triaxial unloading conditionsrdquo International Journal of RockMechanics and Mining Sciences vol 47 no 2 pp 286ndash2982010

[12] F Gong J Yan X Li and S Luo ldquoA peak-strength strainenergy storage index for rock burst proneness of rock ma-terialsrdquo International Journal of Rock Mechanics and MiningSciences vol 117 pp 76ndash89 2019

[13] F Du and KWang ldquoUnstable failure of gas-bearing coal-rockcombination bodies insights from physical experiments andnumerical simulationsrdquo Process Safety and EnvironmentalProtection vol 129 pp 264ndash279 2019

[14] S D Butt C Mukherjee and G Lebans ldquoEvaluation ofacoustic attenuation as an indicator of roof stability in ad-vancing headingsrdquo International Journal of Rock Mechanicsand Mining Sciences vol 37 no 7 pp 1123ndash1131 2000

[15] M Cai H Morioka P K Kaiser et al ldquoBack-analysis of rockmass strength parameters using ae monitoring datardquo Inter-national Journal of Rock Mechanics and Mining Sciencesvol 44 no 4 pp 538ndash549 2007

[16] D P Jansen S R Carlson R P Young and D A HutchinsldquoUltrasonic imaging and acoustic emission monitoring ofthermally induced microcracks in Lac du Bonnet graniterdquoJournal of Geophysical Research Solid Earth vol 98 no B12pp 22231ndash22243 1993

[17] U Bismayer ldquoEarly warning signs for mining accidentsdetecting crackling noiserdquo American Mineralogist vol 102no 1 pp 3-4 2017

[18] X Kong E Wang S Li H Lin P Xiao and K ZhangldquoFractals and chaos characteristics of acoustic emission energyabout gas-bearing coal during loaded failurerdquo Fractals vol 27no 5 Article ID 195072 2019

[19] F Du K Wang G Wang Y Jiang C Xin and X ZhangldquoInvestigation of the acoustic emission characteristics duringdeformation and failure of gas-bearing coal-rock combinedbodiesrdquo Journal of Loss Prevention in the Process Industriesvol 55 pp 253ndash266 2018

[20] R P Young D A Hutchins S Talebi et al ldquoLaboratory andfield investigations of rockburst phenomena using concurrentgeotomographic imaging and acoustic emissionmicroseismictechniquesrdquo Seismicity in Mines vol 129 no 3-4pp 647ndash659 1989

[21] X Jansen H Xu M He and F Zhang ldquoExperimental in-vestigation of the occurrence of rockburst in a rock specimenthrough infrared thermography and acoustic emissionrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 93 pp 250ndash259 2017

[22] R E Goodman and E Richard ldquoSubaudible noise duringcompression of rocksrdquo Geological Society of America Bulletinvol 74 no 4 pp 487ndash490 1963

[23] M Cai P K Kaiser H Morioka et al ldquoFLACPFC couplednumerical simulation of AE in large-scale underground

excavationsrdquo International Journal of Rock Mechanics andMining Sciences vol 44 no 4 pp 550ndash564 2007

[24] V Saltas F Vallianatos D Triantis T Koumoudeli andI Stavrakas ldquoNon-extensive statistical analysis of acousticemissions series recorded during the uniaxial compression ofbrittle rocksrdquo Physica A Statistical Mechanics and Its Ap-plications vol 528 Article ID 121498 2019

[25] V Saltas I Fitilis and F Vallianatos ldquoA combined complexelectrical impedance and acoustic emission study in limestonesamples under uniaxial loadingrdquo Tectonophysics vol 637pp 198ndash206 2014

[26] G Qi ldquoWavelet-based AE characterization of compositematerialsrdquo NDTamp E International vol 33 no 3 pp 133ndash1442000

[27] G Manthei J Eisenblatter and T Dahm ldquoMoment tensorevaluation of acoustic emission sources in salt rockrdquo Con-struction and Building Materials vol 15 no 5-6 pp 297ndash3092001

[28] H Jeong and Y-S Jang ldquoWavelet analysis of plate wavepropagation in composite laminatesrdquo Composite Structuresvol 49 no 4 pp 443ndash450 2000

[29] S-H Chang and C-I Lee ldquoEstimation of cracking anddamage mechanisms in rock under triaxial compression bymoment tensor analysis of acoustic emissionrdquo InternationalJournal of Rock Mechanics and Mining Sciences vol 41 no 7pp 1069ndash1086 2004

[30] T Hirata T Satoh and K Ito ldquoFractal structure of spatialdistribution of microfracturing in rockrdquo Geophysical JournalInternational vol 90 no 2 pp 369ndash374 1987

[31] X Lei K Masuda O Nishizawa et al ldquoDetailed analysis ofacoustic emission activity during catastrophic fracture offaults in rockrdquo Journal of Structural Geology vol 26 no 2pp 247ndash258 2004

[32] J Jouniaux J Pei J Liu et al ldquoInvestigation on acousticemission behavior and its time-space evolution mechanism infailure process of coalndashrock combined bodyrdquo Chinese Journalof Rock Mechanics and Engineering vol 30 pp 1564ndash15702011

[33] E Townend B D ompson P M Benson PG MeredithP Baud and R P Young ldquoImaging compaction bandpropagation in Diemelstadt sandstone using acoustic emis-sion locationsrdquo Geophysical Research Letters vol 35 no 15pp 189ndash193 2008

[34] M Naderloo M Moosavi and M Ahmadi ldquoUsing acousticemission technique tomonitor damage progress around jointsin brittle materialsrdquo Deoretical and Applied Fracture Me-chanics vol 104 Article ID 102368 2019

[35] GBT Unified Number of Natural Stone China StandardsPress Beijing China 2009

[36] G Shen Acoustic Emission Detection Technology and Appli-cation Science Press Beijing China 2015

[37] Y Guo Research on Wavelet Base Selection for VibrationSignal Processing Hefei University of Technology HefeiChina 2003

[38] F Xu E Wang and D Song ldquoLong-range correlation andmultifractal distribution of acoustic emission of coal-rockrdquoRock and Soil Mechanics vol 32 no 7 pp 2111ndash2116 2011

Advances in Civil Engineering 19

232 Setting of Acoustic Emission Detection ParametersBefore the experiment it is necessary to reasonably set therelevant parameters of the AE instrumentndashincluding thedetection threshold timing parameters and wave speedndashtotruly reflect the characteristics of the AE source It should benoted that the propagation speed of the wave is the materialproperty related to the elastic modulus and density of themedium which is the inherent property of the materialGenerally the wave velocity is mainly used for the locationcalculation of the AE source and its uncertainty becomes themain factor affecting the source location In the process ofactual source location the experimental measurement ofwave velocity is needed first However the experiments ofthis work focus on collecting the characteristic parametersand waveform information of the AE signal to study thepropagation characteristics of the elastic wave which doesnot involve the location of the AE source erefore theexperimental acquisition of wave velocity is not the focus ofthis work as it does not affect the acquisition of the researchobjectives of this paper

(1) Detection threshold setting

e indoor environment of this experiment was rela-tively quiet Under the general rules of different thresholdsettings and applicable scope the threshold value of theexperimental system should be carried out at a mediumsensitivity of 35ndash55 dB After the connection of the exper-imental system the AE data acquisition and processingsystem are activated and the entire channel is set at 50mVAt this time the threshold value is about 40 dB based on unitconversion meeting the experimental requirement

(2) Timing parameter setting

In this experiment lead breaking was used to simulatethe AE source Combined with the recommended values ofmetal materials and composite materials summarized inrelevant literature [36] the optimal timing parameters aredetermined including peak definition time (PDT) hitdefinition time (HDT) and hit locking time (HLT) etiming parameters are shown in Table 3

3 Analysis of Experimental Results of ElasticWave Propagation Characteristics

rough the implementation of the above experimentalscheme and the reasonable setting of relevant parameters ofthe AE acquisition instrument effective AE signals of theelastic waves in the propagation process were obtained echaracteristics and parameters of the AE signals and thewaveforms of the AE signals were processed and analyzedand the discussion was carried oute specific experimentalresults and analysis are as follows

31Analysis ofCharacteristic Parameters ofAcoustic EmissionSignals

311 Characteristic Parameter Analysis of Rod-Shaped RockAmplitude frequency and duration are the three elementsthat could be used to describe microvibration or micro-fracture By analyzing the amplitude changes of the moni-toring points at different positions the elastic wave intensitychange trend in the rod can be determined e frequencyinformation at the monitoring points can be used to identifythe area where the AE events are concentrated e types ofAE signals can be clearly identified based on the durationwaveform changes Two characteristic parameters of energycount and amplitude are used to analyze the propagationcharacteristics of elastic waves of different rod-shaped rocksAccording to the definition of energy count since the ac-quisition system obtains discrete point data the energy ofthe AE signal is expressed as

E 1113944N

i1V(i)

2 (1)

where N is the number of discrete points of the AE signalsand V(i) represents the amplitude of the signal discretepoints e amplitude usually reflects the magnitude of theevent [28] and the attenuation characteristics of the AE signalwaveform can be explored through the change in amplitude

+ndash60dB20dB40dB

60dB20dB40dB

40dB20dB60dB

40dB20dB60dB

40dB20dB60dB

USB

6

7

1 2 3

4

5

Figure 3 Experimental system 1 RS-2A sensor 2 adjustable gain amplifier 3 adjustable gain amplifier of excitation pulse source 4computer 5 acoustic emission analyzer 6 top view of the position of the end face excitation pulse signal 7 profile of the position ofterminal excitation pulse signal

4 Advances in Civil Engineering

Assuming that the AE signal is monitored at a distance of5 cm from the pulse excitation source as the reference theamplitude relative attenuation rate and energy relative at-tenuation rate of the elastic wave passing through the robcan be expressed as

ΔAj 20lgAj

As1 (2)

ΔEj 20lgEj

Es1 (3)

where As1 and Es1 represent the amplitude and energyparameters measured at point s1 (j s2 s3 s4 s5 s6)

Taking the existence of error factors into considerationpulse vibration was carried out four times for each group ofrock and the average value of the results was taken fordiscussion e curves of the energy and amplitude distancerelative attenuation rate for each group of rocks are shown inFigure 4

It can be seen from Figure 4 that the characteristicparameters of amplitude and energy in the rod-shaped rocksshow the characteristics of gradual attenuation with theincrease of distance Compared with the characteristic pa-rameter values collected at the 5 cm measuring point therelative attenuation rate of amplitude is greater than that ofenergy It shows that the amplitude directly reflects theintensity of the AE events at different measuring pointsHowever the energy only reflects the relative intensity ofevents which is affected by factors such as threshold valueand working frequency and the relative attenuation ratewith distance cannot show the energy change characteristicsof the AE signals e relative attenuation rate of the S-wavegenerated by the source signal excited by the pulse on theend surface of each group of rocks is lower than that of thepulse compression wave at the terminal area indicating thatthe P-wave came before the S-wave in the process of linearelastic wave propagation and changed violently

e mutation points of the relative amplitude attenua-tion rate both appear at the measuring point of 100 cm forG3768 G3561 and TBG because the length of G3768 andTBG is close to their amplitudes Furthermore the relativeattenuation rate tends to be stable after 100 cm e ab-normal phenomenon appears after 100 cm because the AEsignal produced by the excitation pulse in the terminal areaof TBG suddenly increases It shows that even if the rockwith the same lithology is limited by its complex compo-sition anisotropy and size the AE wave propagation doesnot decay exponentially but exhibits a sudden attenuationcharacteristic Moreover because of the fast propagationspeed of the P-wave the reflection of the rock boundary onthe original AE signal is superimposed on the original signal

and the frequency dispersion of the original signal increaseswith the increase of the propagation distance As a result thesignal after 100 cm in TBG is a mixed distortion signal elength of G3561 is 2150 cm and its relative attenuation rateof energy and amplitude exhibited decreasing trends erelative attenuation rates of energy at the 70 cm measuringpoint were abnormal which were respectively 15 dB and09 dB compared with those at the 5 cm measuring pointe relative attenuation rates of energy at the previous 50 cmmeasuring point were 13 dB and 11 dB respectively eattenuation in this section was relatively weak which may becaused by the gap in the transverse boundary of this rod-shaped rock e abnormal superposition of the boundarywave on the original wave enhanced the original AE signal

For different groups of rocks with different lithologiesthe relative attenuation rates of the amplitude and energy ofAAM presented a relatively flat attenuation trend andslightly strengthened from the position of the 100 cm abruptpoint to the end of the rod is indicates that the atten-uation characteristics of elastic wave propagation were clearwithout abnormal mutation even though the composition ofthe artificial stone is complicated is is because vacuumpressure technology was used to press the binder and varioussizes of crushed stone under vacuum vibration and pressureIt was then made by cutting and grinding erefore itsductility and compactness were good For marble materialGAM with a size of only 100 cm the relative attenuationrates of the amplitude of the end and terminal pulse exci-tation at 50 cm were 373 dB and 366 dB respectively ForG3768 these two values at 70 cm were 193 dB and 223 dBrespectively For the other four rock samples these twovalues at 70 cm were as follows 179 dB and 177 dB forG3561 232 dB and 261 dB for TBG and 256 dB and 271 dBfor AAM It can be seen that the elastic wave attenuation wasthe fastest in the marble and the elastic wave attenuation ofthe three types of granite was similar Among them the TBGhad the fastest elastic wave attenuation In general the at-tenuation of the P-wave came before the S-wave

312 Characteristic Parameter Analysis of Rod-Shaped RockAccording to the experimental schemes of the G3761-L andGAM-L samples the elastic wave propagation characteris-tics in the thin plate-shaped rock were discussed by ana-lyzing the changes in the amplitude of the AE signalsConsidering the error factor pulse vibration was carried outfour times for each group of rod-shaped rocks where theaverage value of the results was taken for discussion eattenuation curves of the amplitude of each measuring pointin different directions and different lithological samples arepresented in Figure 5

Table 3 Timing parameters in the experiment

Timing parameter G3768 G3561 TBG AAM GAM G3761-L GAM-LPDTμs 100 150 150 150 150 100 100HDTμs 200 300 300 300 300 200 200HLTμs 300 500 500 500 500 300 300

Advances in Civil Engineering 5

Amplitude

Energy

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

TBGRelat

ive d

ecay

rate

(dB)

Distance (cm)

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

AAMRelat

ive d

ecay

rate

(dB)

Amplitude

Energy

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

G3768Relat

ive d

ecay

rate

(dB)

Distance (cm)

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash3

ndash2

ndash1

0

G3561

Relat

ive d

ecay

rate

(dB)

Amplitude

Energy

Distance (cm)

20 50 70 100ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

GAM

(a)

Figure 4 Continued

6 Advances in Civil Engineering

It can be seen from Figure 5 that the amplitude of thelarge-scale plane plate rock showed similar exponentialattenuation characteristics with the increase of the propa-gation distance e AE wave attenuation of granite wasstronger than that of marble in the direction of 0deg and wasweaker than that of marble in the directions of 90deg and 45deg

Specifically due to the diversity and anisotropy of rockcomponents the attenuation of the AE wave in the range of20ndash80 cm in the direction of 0deg showed the fluctuation ofamplitude between 72 and 83 dB in both kinds of rockthough the overall trend was declining e amplitudecharacteristic parameters extracted from each measuring

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash5

ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

G3768

Amplitude

Energy

Distance (cm)

20 50 70 100 135

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

G3561

Amplitude

Energy

Distance (cm)

20 50 70 100 135

ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

TBG

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

AAM

Amplitude

Energy

Distance (cm)

20 50 70 100ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

GAM

(b)

Figure 4 e attenuation rates of energyamplitude with distance (a) End-pulse excitation (S-wave) (b) Terminal pulse excitation (P-wave)

Advances in Civil Engineering 7

point arranged in the front and back of the marble in the 45degdirection and 90deg direction presented significant changes Asudden decrease of amplitude appeared at 30ndash40 cm with adecrease of 1965 dB in the 45deg direction and 2455 dB in the90deg directione amplitude attenuation of granite tended tobe stable

e attenuation curves of the AE energy in differentdirections for G3761-L and GAM-L are shown in Figure 6 Itcan be seen that the energy in the marble changes violentlyand the energy value in the range of 45ndash55 cm in the di-rection of 0deg exhibits the abnormal phenomenon of stepeenergy attenuation was lower than that of the granite stonewhich shows the same trend with the amplitude attenuatione energy value of granite from 45 cm back to the end of thethin plate is almost maintained at 20ndash50mVms and tends tobe stable In the 45deg direction the marble exhibited theenhancement of energy value after 55 cm It is the reflectionof the AE wave along the 45deg direction when it met theboundary and the wave enhancement phenomenon wasformed by the superposition of multiple reflections andrefractions e marble and granite showed the same trendin the 90deg direction

32 Waveform Analysis of Acoustic Emission Signal

321 Time Domain Waveform and Spectrum Analysis ofAcoustic Emission Original Signal According to a largenumber of AE signal waveforms obtained by pulse excitationon the surface of each group of samples the AE signalwaveforms of rod-shaped and plate-shaped rocks were se-lected from the closest measuring point to the pulse sourcee middle measuring point in their respective directionsand the end measuring points were analyzed e specificlayout of measuring points is presented in Table 4

Since the original statistics of the nonstationary AEsignal is a time-varying function FFT transform was used toanalyze the spectral characteristics of the time-domain signalto better understand the variation law of elastic wave in thepropagation process Figure 7 presents the original signaltime-domain waveforms of measuring point M2 of eachgroup of rod-shaped rocks and the corresponding frequencyspectrum is shown in Figure 8 e related curves of the AE

signal excited from measuring points M2 on the surface ofthe plate-shaped rocks in the three directions of 0deg 90deg and45deg are shown in Figure 9

It can be seen from the time-domain diagram that thewaveforms of the AE signal generated by pulse excitationwere very similar and the duration was short For the rod-shaped rocks the durations for granites G3768 G3561 andTBG were in the range of 025ndash15ms where the waveformsdecayed quickly and the coda waves were not developede durations for AAM and GAM were in the range of05ndash20ms and 05ndash10ms respectively For the plate-shapedrocks the duration of G3761-L was 05ndash15ms in the 0degdirectione duration for GAM-L was 025ndash15ms and theamplitude attenuation variation was small Similarly in the45deg direction and 90deg direction the G3761-l granite showed ashorter duration of time than the GAM-L marble dem-onstrating that the homogeneity of the natural granite plate-shaped rock is better

It can be seen from the spectrum that the frequency ofthe AE signal generated by pulse excitation was relativelyhigh and the frequency band was relatively narrow emain frequency domain of each group of rod-shaped rockswas 0ndash250 kHz and the frequency domain of the AE signalat the M2 position measuring point in each direction of theplate-shaped rocks was 0ndash300 kHz In this frequency do-main each group of samples with different lithologies showsmultiple peaks of frequency indicating that the waveform ofthe AE signal is very complex and is a mixture of waves withdifferent characteristics

322 Wavelet Packet Energy Analysis of Acoustic EmissionSignal According to previous research wavelet transformonly decomposes the low-frequency partndashbut not the high-frequency part of the original signal e time-frequencylocalization could be better analyzed through the intro-duction of wavelet packet transform in which the high-frequency part of the signal could be further decomposed Asshown in Table 4 considering that wavelet packet analysishas the advantages of multilayer decomposition of signaldetails and scale information the following wavelet packetenergy feature extraction was conducted for the AE signal

0 20 40 60 80 100 12060

65

70

75

80

85

90

95

100A

mpl

itude

(dB)

G3761-L

GAM-L

0deg

Distance (cm)

G3761-L

GAM-L

0 10 20 30 40 50 6050

60

70

80

90

100

45deg

Distance (cm)

Am

plitu

de (d

B)

G3761-L

GAM-L

0 10 20 30 40 5050

60

70

80

90

100

90deg

Distance (cm)

Am

plitu

de (d

B)

Figure 5 e attenuation curves of the amplitude in different directions for G3761-L and GAM-L

8 Advances in Civil Engineering

waveform obtained at different measuring points in eachgroup of rock samples to explore the local feature infor-mation of the AE signal waveform at different positions ofrod-shaped and plate-shaped rocks

Choosing a suitable wavelet base plays an important rolein signal processing and analysis Guo [37] introduced theeffect of different wavelet bases in vibration signal processingin detail which presents that the db5 db7 db10 db13 db16bior26 bior39 coif4 sym7 and sym8 wavelet bases aremore suitable for the shock feature extraction of vibrationsignals Of this wavelet set db7 was selected as the waveletbase for the wavelet packet analysis because of its Daubechiesseries wavelet set characteristics such as high-order van-ishing moment tight support regularity approximatesymmetry and orthogonalityndashand because of the similaritiesit shares with the rock AE signal Its wavelet function ispresented in Figure 10

e sampling frequency is 3MHz According to thesampling theorem its Nyquist frequency is 1500 kHz ewavelet packet decomposition principle and algorithm wereapplied to decompose the signal to the 7th layer (ie thescale is 7) which has 27 wavelet packets in total ereforein the frequency domain the original signal was decom-posed into 128 subbands e width of each band was1172 kHz e frequency band range of each layer recon-structed after the decomposition of the original signal ispresented in Table 5

As can be seen from the table the original signal isexpressed as

S S70 + S71 + S72 + middot middot middot + S7127 (4)

where S70 is the low-frequency part of the decomposedsignal the other variables represent the decomposition of the

high-frequency part of the signal Assuming that the cor-responding energy of S7j(j 0 1 2 middot middot middot 127) isE7j(j 0 1 2 middot middot middot 127) then the energy characterization ofthe original AE signal decomposition in each frequencyband range can be obtained by formula (1)

Assuming that the total energy of the analyzed signal isE0 then

E0 1113944127

j0E7j (5)

e ratio of the energy of each frequency band to thetotal energy of the analyzed signal is

Ej E7j

E0times 100 (6)

In the formula j 012 27ndash1From Equation (1) the energy changes of the corre-

sponding AE signals in different frequency bands after theoriginal signal decomposition were calculated so the energydistribution characteristics of the elastic wave in differentfrequency bands could be found [38] According to Table 4the main frequency range of the AE signal waveform of eachmeasuring point was 0ndash300 kHz indicating that the energyvalue must also be concentrated in this frequency rangeerefore with MATLAB programming the energy dis-tribution of each subband in the frequency domain of0ndash500 kHz was obtained as shown in Figures 11 and 12

For rod-shaped rocks G3768 G3561 and TBG of thesame lithology from different places of origin the M1measuring point was closest to the pulse excitation sourceerefore the value of the M1 measuring point could ef-fectively reflect the energy value of the real pulse As can be

G3761-L

GAM-L

0deg

0 20 40 60 80 100 120

0

100

200

300

400

500

600

Distance (cm)

Ener

gy (m

Vlowast

ms)

G3761-L

GAM-L

45deg

Distance (cm)

Ener

gy (m

Vlowast

ms)

0 10 20 30 40 50 600

100

200

300

400

500

600

700

G3761-L

GAM-L

90deg

Distance (cm)

Ener

gy (m

Vlowast

ms)

0 10 20 30 40 50

100

200

300

400

500

600

700

Figure 6 e attenuation curves of the AE Energy in different directions for G3761-L and GAM-L

Table 4 e measuring point positions of AE waveforms

Rock number (measuring point) (cm) G3768 G3561 TBG AAM GAMG3761-L GAM-L

0deg 90deg 45deg 0deg 90deg 45deg

M1 5 5 5 5 5 5 5 5 5 5 5M2 70 70 70 70 50 55 20 30 40 25 30M3 135 135 135 135 100 100 35 50 75 40 50

Advances in Civil Engineering 9

seen from Figure 11 the energy is widely distributed in thefrequency domain e value of energy is generally smallwhich was mainly concentrated in the range of0ndash36428 kHz Combined with Formulas (5) and (6) it couldbe calculated that the main dominant energy of the three

groups of granite was concentrated in the frequency band of7131ndash12991 kHz which correspondingly accounted for646 5605 and 5828 of the total energy About2326 of the energy in G3561 was concentrated in thefrequency band of 23538ndash35256 kHz which is different

0 05 10 15 20 25ndash15

ndash10

ndash05

0

05

10

Am

plitu

de (m

V)

Time (ms)

G3768

TBG

0 05 10 15 20 25 3ndash08

ndash06

ndash04

ndash02

0

02

04

06

08

Am

plitu

de (m

V)

Time (ms)

G3561

0 05 10 15 20 25

ndash15

ndash10

ndash05

0

05

10

15

Time (ms)

Am

plitu

de (m

V)

AAM

0 05 10 15 2ndash20

ndash15

ndash10

ndash05

0

05

10

15

Time (ms)

Am

plitu

de (m

V)

GAM

0 05 10 15 20 25 30 35ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

Figure 7 Time domain waveform of measuring point M2 of rod-shaped rock

10 Advances in Civil Engineering

from other samples of the same lithology With the increaseof the propagation distance of the elastic wave its energyexhibited the characteristics of rapid attenuation edominant energy distribution frequency bands of the threerod-shaped rock materials at the M2 measuring point ex-panded from the initial 7131ndash12991 kHz to 0ndash17678 kHz

and the energy percentages were 8987 9407 and8658 respectively In the high-frequency band of28225ndash31741 kHz there was respectively 10 and 1269energy concentration for G3768 and TBG When the elasticwave propagated to the end of the rod (M3) the energy ofeach group of samples was relatively concentrated and

0 100 200 300 400 5000

001

002

003

004

Am

plitu

de (m

V)

Frequency (KHz)

G3768

TBG

0 100 200 300 400 5000

001

002

003

Am

plitu

de (m

V)

Frequency (KHz)

G3561

0 100 200 300 400 5000

001

002

003

004

005

006

007

Frequency (KHz)

Am

plitu

de (m

V)

AAM

0 100 200 300 400 5000

001

002

003

004

005

006

Frequency (KHz)

Am

plitu

de (m

V)

GAM

0 100 200 300 400 5000

0002

0004

0006

0008

0010

0012

Am

plitu

de (m

V)

Frequency (KHz)

Figure 8 e spectrogram of measuring point M2 of rod-shaped rock

Advances in Civil Engineering 11

G3761-L(90deg)

0 05 10 15 2ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

G3761-L(90deg)

0 100 200 300 400 500000

002

004

006

008

010

Am

plitu

de (m

V)

Frequency (KHz)

G3761-L(45deg)

0 05 10 15 20 25

ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

G3761-L(45deg)

0 100 200 300 400 5000

001

002

003

004

005

006

007

Am

plitu

de (m

V)

Frequency (KHz)

0 05 10 15 20 25 3ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

G3761-L(0deg)

Am

plitu

de (m

V)

Time (ms)

G3761-L(0deg)

0 100 200 300 400 5000

0002

0004

0006

0008

0010

Am

plitu

de (m

V)

Frequency (KHz)

(a)

Figure 9 Continued

12 Advances in Civil Engineering

mainly distributed within 0ndash10647 kHz at the percentages of9211 9022 and 9188 respectively By comparing thethree groups of rod-shaped rocks with the same lithology itcan be seen that the energy attenuation was the fastest inTBG and the dominant energy value was the lowest at theM3 measuring point For G3768 the energy attenuation wasthe slowest Only the distribution rule of the dominant

energy value at the M2 and M3 measuring points changedwhereas the maximum energy value hardly changed ereason may be that the internal structure or componentdensity of G3768 was better and the energy was relativelymaintained rather than rapidly attenuated with the elasticwave propagation For AAM artificial marble its maindominant energy also exhibited the same change trend as

GAM-L(45deg)

0 05 10 15 20 25

ndash3

ndash2

ndash1

0

1

2

3

4

Am

plitu

de (m

V)

Time (ms)

GAM-L(45deg)

0 100 200 300 400 5000

002

004

006

008

010

012

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(0deg)

0 05 10 15 20 25 30 35

ndash09

ndash06

ndash03

0

03

06

09

Am

plitu

de (m

V)

Time (ms)

GAM-L(0deg)

0 100 200 300 400 5000

0005

0010

0015

0020

0025

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(90deg)

0 05 10 15 20 25ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

GAM-L(90deg)

Am

plitu

de (m

V)

0 100 200 300 400 500000

002

004

006

008

010

Frequency (KHz)

(b)

Figure 9 e time waveform and spectrogram of measuring point M2 of pate-shaped rock

Advances in Civil Engineering 13

0 3 6 9 12 15ndash15

ndash10

ndash05

00

05

10

Wavelet function

0 3 6 9 12 15

ndash05

00

05

10

Scaling function

Figure 10 Wavelet function and scaling function for db7

Table 5 e frequency band range of reconstructed signal by wavelet packet decomposition

Layer S (i 0) S (i 1) S (i 2) S (i jminus 1) S (i j)1 0ndash750 ndash ndash ndash ndash 750ndash15002 0ndash375 375ndash750 750ndash1125 ndash ndash 1125ndash15003 0ndash1875 1875ndash375 375ndash5625 1125ndash13125 13125ndash15004 0ndash9375 9375ndash1875 1875ndash28125 13125ndash140625 140625ndash15005 0ndash46875 46875ndash9375 9375ndash140625 140625ndash1453125 1453125ndash15006 0ndash234375 234375ndash46875 46875ndash703125 1453125ndash14765625 14765625ndash15007 0ndash1171875 1171875ndash234375 234375ndash3515625 14765625ndash148828125 148828125ndash1500S (i j) represents the reconstruction signal of the j-th wavelet packet decomposition coefficient in the i-th layer i 1234 j 012 2i-1

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M3

(a)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500

1000

1500

2000

2500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

20

40

60

80

100

120

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

M3

(b)

Figure 11 Continued

14 Advances in Civil Engineering

granite From Figure 11 it can be observed that the energy ofthe original pulse signal is concentrated in the range of9475ndash16506 kHz and 2185 of the energy existed in thefrequency band of 28225ndash35256 kHz For GAMmarble themain dominant energy distribution of the initial signal wasvery wide and was distributed in the frequency band of0ndash36428 kHz Among them the dominant energy wasdistributed within the 10647ndash12991 kHz range accountingfor 3213 of the total energy Similar attenuation charac-teristics as granite were presented with the increase of elasticwave propagation distance In general for GAM the exci-tation energy of the AE signal generated by pulse excitationwas the weakest and the attenuation was the fastest with theincrease of distancee initial excitation energy of the threegroups of granite was partially concentrated in the frequency

band of 23538ndash35256 kHz of which the performance ofG3561 was the most obvious

e pulse AE signal was very complex for 2 groups of theplate-shaped rocks (Figure 12) erefore the initial energyof the M1 measuring point in each direction was also quitedifferent In the direction of 0deg the dominant energy of theoriginal pulse signal in G3761-L was concentrated in thefrequency band of 0ndash17678 kHz which accounted for8904 of the total energy Meanwhile about 628 of theenergy was distributed in the frequency band of29397ndash32913 kHz e same law was also shown in GAM-L but the main dominant frequency in GAM-L was rela-tively concentrated in the short frequency band of10647ndash17678 kHz which accounted for 6357 of the totalenergy With the spread of the elastic wave the energy in

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50002468

10121416

M3

(c)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5001000150020002500300035004000

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40

50

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M3

(d)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

100

200

300

400

500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M2

0 100 200 300 400 5000

2

4

6

8En

ergy

(mVlowast

mS)

Frequency (KHZ)

M3

0 100 200 300 400 500012345678

(e)

Figure 11e energy distribution of acoustic emission signal frequency band of rod-shaped rock (a) G3768 (b) G3561 (c) TBG (d) AAM(e) GAM

Advances in Civil Engineering 15

0 100 200 300 400 5000

200400600800

100012001400

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

M2

0 100 200 300 400 5000005101520253035

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

M3

0 100 200 300 400 50000020406081012

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

(a)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40En

ergy

(mVlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 5000

2

4

6

8

Ener

gy (m

Vlowast

mS)

(b)

M1

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

1020304050607080

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50002468

1012141618

Ener

gy (m

Vlowast

mS)

(c)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700800

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 50005

101520253035

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

Ener

gy (m

Vlowast

mS)

(d)

Figure 12 Continued

16 Advances in Civil Engineering

G3761-L showed a trend of attenuation and the energy intheM2measuring point was still distributed in the frequencyband of 0ndash17678 kHz e energy distribution at the M3measuring point was relatively concentrated and was locatedin the frequency band of 0ndash10647 kHz accounting for8340 of the total energy e energy at the measuringpoint M3 of GAM-L was more extensive in the frequencydomain and the energy value changed dramatically dem-onstrating the abnormal phenomenon that the maindominant energy increased e frequency range of thismeasuring point was 0ndash1885 kHz accounting for 8589 ofthe total energyere was also residual energy concentratedin the frequency band of 29397ndash32913 kHz e AE signalat M3 was superposed by the boundary reflection wave andthe energy was enhanced because of the high homogeneityand good ductility of GAM-L For G3761-L the dominantenergy of the elastic wave almost dissipated at the M3measuring point In the direction of 45deg the dominantenergy band of the original signal in G3761-L was distributedwithin 0ndash17678 kHz and 28225ndash35256 kHz respectivelyaccounting for 6415 and 3278 of the total energyMoreover it can be observed that the distribution of thedominant energy band was from distribution to concen-tration which was distributed in the frequency band of7131ndash17678 kHz at M2 With the increase of distance theenergy frequency band of the M3 measuring point near theedge of the plate was spread again and it was restored to theenergy frequency band range of the initial signal Howeverthe energy value was attenuated to a very small value at this

moment e energies of GAM-L in the measuring pointsM1 M2 and M3 were all distributed in the frequency bandof 0ndash36428 kHz In the direction of 90deg the primarydominant energy frequency bands of the two plate-shapedrocks were concentrated in 9475ndash1885 kHz e differenceis that the energy distribution of GAM-L was still con-centrated and the energy variation was much smaller thanG3761-L at the M2 measuring point In general the energyfrequency band of the two plate-shaped rocks with differentlithologies was the same as that of the rod-shape rock whichis mainly distributed in the range of 0ndash36428 kHz More-over they also exhibited the characteristics that the maindominant energy was distributed in the range of0ndash17678 kHz and the residual energy was distributed in therange of 28225ndash35256 kHz

4 Discussion

e purpose of this work was to study the propagationcharacteristics of elastic wave in lithological rock materialsrough the above research and analysis a preliminaryunderstanding was obtained Based on the deep waveletpacket analysis of amplitude energy characteristic param-eters and AE waveform the frequency band characteristicsof the local energy distribution of elastic wave with itspropagation were summarized However its propagationcharacteristics are difficult to be regularly grasped becausethe elastic wave itself is extremely complex Furthermore AEtechnology is mostly used in the damage detection and

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

20406080

100120140160

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

10

20

30

40

50

(e)

M1

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

200400600800

10001200140016001800

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

50

100

150

200

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 50005

101520253035

(f )

Figure 12e energy distribution of acoustic emission signal frequency band of plate-shaped rock (a) G3761-L (00) (b) G3761-L (450) (c)G3761-L (900) (d) GAM-L (00) (e) GAM-L (450) (f ) GAM-L (900)

Advances in Civil Engineering 17

defect location of metal or related materials with goodcompactness ductility and within the same medium ereare many uncertain interference factors in the experimentsIn some aspects the analysis of this paper only stays at thelevel of the apparent phenomenon and there are still manydeficiencies and areas worthy of improvement For instancethe density wave velocity and wave impedance of the rod-shaped rock samples should be tested and the micro-structure imaging experiments of the rock samples should beconducted e quality factor Q of different rock samplesshould be calculated Moreover the correlation between thequality factor and wave impedance should be studied andthe influence of different microcompositions of rod-shapedrocks on elastic wave attenuation should be deeply analyzedBased on the modal AE theory the influence of Lamb wavein plate-shaped rocks should be studied and the propagationmodel of two-dimensional AE should be constructed eGabor wavelet should be introduced to analyze the AE signalby time-frequency analysis e influence of differentwavelets based on the propagation effect of AE will becompared and analyzed and the time of the same mode ofthe AE wave arriving at the sensor will be determined tofurther optimize the plane location algorithm However theresearch in this work is still useful for studying large-scalerock samples in the future and provides effective researchmethods and ideas for the study of elastic wave propagationcharacteristics of different rock materials and compositematerials

5 Conclusions

In this work the characteristic parameter analysis andwaveform analysis of the AE signals obtained from differentexperimental schemes in 5 groups of rod-shaped rocks and 2groups of plate-shaped rocks were carried out e con-clusions are as follows

(1) e amplitude and energy of the rod-shaped rocksgradually attenuated with the increase of distancee amplitude can directly reflect the intensity of theAE counts at different measuring areas In theprocess of elastic wave propagation of the rod-sha-ped rock the P-wave preceded the S-wave andchanged violently e elastic wave of marble at-tenuated faster and the elastic wave of the threekinds of granite decayed attenuated closely Amongthem the elastic wave of TBG exhibited the fastestattenuation

(2) In flat plate-shaped rocks the amplitude exhibited anapproximate exponential attenuation characteristicwith the increase of the propagation distanceGranite exhibited a stronger elastic wave attenuationin the 0deg direction than the marble and the marblepresented fast attenuations in the 45deg and 90deg di-rections e energy change of marble was dramaticand the energy value in the interval of 45ndash55 cm atthe direction of 0deg showed the abnormal step phe-nomenon e energy value of the marble increasedafter 55 cm in the 45deg direction e energy value of

granite from the back to the end of the plate wasalmost maintained and tended to be stable at20ndash50mVms

(3) e frequency range of the energy distribution ofsamples in this work was within 0ndash36428 kHz Withthe increase of distance the main dominant energydistribution of the 5 groups of rod-shaped rocks inthe frequency range was characterized by distribu-tion to relative concentration and rapid energy at-tenuationemain dominant energy distribution ofthe 2 groups of plate-shaped rocks was distributed inthe range of 0ndash17678 kHz All rod-shaped rocks andplate-shaped rocks exhibited the characteristics ofresidual energy distribution in the frequency band of28225ndash35256 kHz

Data Availability

e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

e authors certify that they have no conflicts of interest

Acknowledgments

is research was funded by the National Natural ScienceFoundation of China (51804161 52074156 and 52004291)the Chinese Postdoctoral Science Foundation(2019M660861) and the State Key Laboratory CultivationBase for Gas Geology and Gas Control (Henan PolytechnicUniversity) (WS2020A04)

References

[1] J T Chen J H Zhao S C Zhang Y Zhang F Yang andM Li ldquoAn experimental and analytical research on theevolution of mining cracks in deep floor rock massrdquo Pure andApplied Geophysics vol 177 no 11 pp 5325ndash5348 2020

[2] K Wang and F Du ldquoCoal-gas compound dynamic disastersin China a reviewrdquo Process Safety and Environmental Pro-tection vol 133 pp 1ndash17 2020

[3] C Zhu M He M Karakus X Cui and Z Tao ldquoInvestigatingtoppling failure mechanism of anti-dip layered slope due toexcavation by physical modellingrdquo Rock Mechanics and RockEngineering vol 53 no 11 pp 5029ndash5050 2020

[4] X Wang C Liu S Chen L Chen K Li and N Liu ldquoImpactof coal sectorrsquos de-capacity policy on coal pricerdquo AppliedEnergy vol 265 Article ID 114802 2020

[5] D Liu Z Gu R Liang et al ldquoImpacts of pore-throat systemon fractal characterization of tight sandstonesrdquo Geofluidsvol 2020 no 9 17 pages Article ID 4941501 2020

[6] J Wang Y Zhang Z Qin S Song and P Lin ldquoAnalysismethod of water inrush for tunnels with damaged water-resisting rock mass based on finite element method-smoothparticle hydrodynamics couplingrdquo Computers and Geo-technics vol 126 Article ID 103725 2020

[7] B Chen S C Zhang Y Y Li Z K Li and H J ZhouldquoPhysical simulation study of crack propagation and insta-bility information discrimination of rock-like materials withfaultsrdquo Arabian Journal of Geosciences vol 13 p 966 2020

18 Advances in Civil Engineering

[8] F Du K Wang X Zhang C Xin and G Wang ldquoExperi-mental study of coal-gas outburst insights from coal-rockstructure gas pressure and adsorptivityrdquo Natural ResourcesResearch vol 29 no 4 pp 2481ndash2493 2020

[9] H Y Wang J Ma G D Wang et al ldquoResearch on AE sourcelocation of linear and plane rock massrdquo Shock and Vibrationvol 2020 Article ID 8846582 18 pages 2020

[10] V A Mansurov ldquoPrediction of rockbursts by analysis ofinduced seismicity datardquo International Journal of Rock Me-chanics and Mining Sciences vol 38 no 6 pp 893ndash901 2001

[11] M C He J L Miao and J L Feng ldquoRock burst process oflimestone and its acoustic emission characteristics under true-triaxial unloading conditionsrdquo International Journal of RockMechanics and Mining Sciences vol 47 no 2 pp 286ndash2982010

[12] F Gong J Yan X Li and S Luo ldquoA peak-strength strainenergy storage index for rock burst proneness of rock ma-terialsrdquo International Journal of Rock Mechanics and MiningSciences vol 117 pp 76ndash89 2019

[13] F Du and KWang ldquoUnstable failure of gas-bearing coal-rockcombination bodies insights from physical experiments andnumerical simulationsrdquo Process Safety and EnvironmentalProtection vol 129 pp 264ndash279 2019

[14] S D Butt C Mukherjee and G Lebans ldquoEvaluation ofacoustic attenuation as an indicator of roof stability in ad-vancing headingsrdquo International Journal of Rock Mechanicsand Mining Sciences vol 37 no 7 pp 1123ndash1131 2000

[15] M Cai H Morioka P K Kaiser et al ldquoBack-analysis of rockmass strength parameters using ae monitoring datardquo Inter-national Journal of Rock Mechanics and Mining Sciencesvol 44 no 4 pp 538ndash549 2007

[16] D P Jansen S R Carlson R P Young and D A HutchinsldquoUltrasonic imaging and acoustic emission monitoring ofthermally induced microcracks in Lac du Bonnet graniterdquoJournal of Geophysical Research Solid Earth vol 98 no B12pp 22231ndash22243 1993

[17] U Bismayer ldquoEarly warning signs for mining accidentsdetecting crackling noiserdquo American Mineralogist vol 102no 1 pp 3-4 2017

[18] X Kong E Wang S Li H Lin P Xiao and K ZhangldquoFractals and chaos characteristics of acoustic emission energyabout gas-bearing coal during loaded failurerdquo Fractals vol 27no 5 Article ID 195072 2019

[19] F Du K Wang G Wang Y Jiang C Xin and X ZhangldquoInvestigation of the acoustic emission characteristics duringdeformation and failure of gas-bearing coal-rock combinedbodiesrdquo Journal of Loss Prevention in the Process Industriesvol 55 pp 253ndash266 2018

[20] R P Young D A Hutchins S Talebi et al ldquoLaboratory andfield investigations of rockburst phenomena using concurrentgeotomographic imaging and acoustic emissionmicroseismictechniquesrdquo Seismicity in Mines vol 129 no 3-4pp 647ndash659 1989

[21] X Jansen H Xu M He and F Zhang ldquoExperimental in-vestigation of the occurrence of rockburst in a rock specimenthrough infrared thermography and acoustic emissionrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 93 pp 250ndash259 2017

[22] R E Goodman and E Richard ldquoSubaudible noise duringcompression of rocksrdquo Geological Society of America Bulletinvol 74 no 4 pp 487ndash490 1963

[23] M Cai P K Kaiser H Morioka et al ldquoFLACPFC couplednumerical simulation of AE in large-scale underground

excavationsrdquo International Journal of Rock Mechanics andMining Sciences vol 44 no 4 pp 550ndash564 2007

[24] V Saltas F Vallianatos D Triantis T Koumoudeli andI Stavrakas ldquoNon-extensive statistical analysis of acousticemissions series recorded during the uniaxial compression ofbrittle rocksrdquo Physica A Statistical Mechanics and Its Ap-plications vol 528 Article ID 121498 2019

[25] V Saltas I Fitilis and F Vallianatos ldquoA combined complexelectrical impedance and acoustic emission study in limestonesamples under uniaxial loadingrdquo Tectonophysics vol 637pp 198ndash206 2014

[26] G Qi ldquoWavelet-based AE characterization of compositematerialsrdquo NDTamp E International vol 33 no 3 pp 133ndash1442000

[27] G Manthei J Eisenblatter and T Dahm ldquoMoment tensorevaluation of acoustic emission sources in salt rockrdquo Con-struction and Building Materials vol 15 no 5-6 pp 297ndash3092001

[28] H Jeong and Y-S Jang ldquoWavelet analysis of plate wavepropagation in composite laminatesrdquo Composite Structuresvol 49 no 4 pp 443ndash450 2000

[29] S-H Chang and C-I Lee ldquoEstimation of cracking anddamage mechanisms in rock under triaxial compression bymoment tensor analysis of acoustic emissionrdquo InternationalJournal of Rock Mechanics and Mining Sciences vol 41 no 7pp 1069ndash1086 2004

[30] T Hirata T Satoh and K Ito ldquoFractal structure of spatialdistribution of microfracturing in rockrdquo Geophysical JournalInternational vol 90 no 2 pp 369ndash374 1987

[31] X Lei K Masuda O Nishizawa et al ldquoDetailed analysis ofacoustic emission activity during catastrophic fracture offaults in rockrdquo Journal of Structural Geology vol 26 no 2pp 247ndash258 2004

[32] J Jouniaux J Pei J Liu et al ldquoInvestigation on acousticemission behavior and its time-space evolution mechanism infailure process of coalndashrock combined bodyrdquo Chinese Journalof Rock Mechanics and Engineering vol 30 pp 1564ndash15702011

[33] E Townend B D ompson P M Benson PG MeredithP Baud and R P Young ldquoImaging compaction bandpropagation in Diemelstadt sandstone using acoustic emis-sion locationsrdquo Geophysical Research Letters vol 35 no 15pp 189ndash193 2008

[34] M Naderloo M Moosavi and M Ahmadi ldquoUsing acousticemission technique tomonitor damage progress around jointsin brittle materialsrdquo Deoretical and Applied Fracture Me-chanics vol 104 Article ID 102368 2019

[35] GBT Unified Number of Natural Stone China StandardsPress Beijing China 2009

[36] G Shen Acoustic Emission Detection Technology and Appli-cation Science Press Beijing China 2015

[37] Y Guo Research on Wavelet Base Selection for VibrationSignal Processing Hefei University of Technology HefeiChina 2003

[38] F Xu E Wang and D Song ldquoLong-range correlation andmultifractal distribution of acoustic emission of coal-rockrdquoRock and Soil Mechanics vol 32 no 7 pp 2111ndash2116 2011

Advances in Civil Engineering 19

Assuming that the AE signal is monitored at a distance of5 cm from the pulse excitation source as the reference theamplitude relative attenuation rate and energy relative at-tenuation rate of the elastic wave passing through the robcan be expressed as

ΔAj 20lgAj

As1 (2)

ΔEj 20lgEj

Es1 (3)

where As1 and Es1 represent the amplitude and energyparameters measured at point s1 (j s2 s3 s4 s5 s6)

Taking the existence of error factors into considerationpulse vibration was carried out four times for each group ofrock and the average value of the results was taken fordiscussion e curves of the energy and amplitude distancerelative attenuation rate for each group of rocks are shown inFigure 4

It can be seen from Figure 4 that the characteristicparameters of amplitude and energy in the rod-shaped rocksshow the characteristics of gradual attenuation with theincrease of distance Compared with the characteristic pa-rameter values collected at the 5 cm measuring point therelative attenuation rate of amplitude is greater than that ofenergy It shows that the amplitude directly reflects theintensity of the AE events at different measuring pointsHowever the energy only reflects the relative intensity ofevents which is affected by factors such as threshold valueand working frequency and the relative attenuation ratewith distance cannot show the energy change characteristicsof the AE signals e relative attenuation rate of the S-wavegenerated by the source signal excited by the pulse on theend surface of each group of rocks is lower than that of thepulse compression wave at the terminal area indicating thatthe P-wave came before the S-wave in the process of linearelastic wave propagation and changed violently

e mutation points of the relative amplitude attenua-tion rate both appear at the measuring point of 100 cm forG3768 G3561 and TBG because the length of G3768 andTBG is close to their amplitudes Furthermore the relativeattenuation rate tends to be stable after 100 cm e ab-normal phenomenon appears after 100 cm because the AEsignal produced by the excitation pulse in the terminal areaof TBG suddenly increases It shows that even if the rockwith the same lithology is limited by its complex compo-sition anisotropy and size the AE wave propagation doesnot decay exponentially but exhibits a sudden attenuationcharacteristic Moreover because of the fast propagationspeed of the P-wave the reflection of the rock boundary onthe original AE signal is superimposed on the original signal

and the frequency dispersion of the original signal increaseswith the increase of the propagation distance As a result thesignal after 100 cm in TBG is a mixed distortion signal elength of G3561 is 2150 cm and its relative attenuation rateof energy and amplitude exhibited decreasing trends erelative attenuation rates of energy at the 70 cm measuringpoint were abnormal which were respectively 15 dB and09 dB compared with those at the 5 cm measuring pointe relative attenuation rates of energy at the previous 50 cmmeasuring point were 13 dB and 11 dB respectively eattenuation in this section was relatively weak which may becaused by the gap in the transverse boundary of this rod-shaped rock e abnormal superposition of the boundarywave on the original wave enhanced the original AE signal

For different groups of rocks with different lithologiesthe relative attenuation rates of the amplitude and energy ofAAM presented a relatively flat attenuation trend andslightly strengthened from the position of the 100 cm abruptpoint to the end of the rod is indicates that the atten-uation characteristics of elastic wave propagation were clearwithout abnormal mutation even though the composition ofthe artificial stone is complicated is is because vacuumpressure technology was used to press the binder and varioussizes of crushed stone under vacuum vibration and pressureIt was then made by cutting and grinding erefore itsductility and compactness were good For marble materialGAM with a size of only 100 cm the relative attenuationrates of the amplitude of the end and terminal pulse exci-tation at 50 cm were 373 dB and 366 dB respectively ForG3768 these two values at 70 cm were 193 dB and 223 dBrespectively For the other four rock samples these twovalues at 70 cm were as follows 179 dB and 177 dB forG3561 232 dB and 261 dB for TBG and 256 dB and 271 dBfor AAM It can be seen that the elastic wave attenuation wasthe fastest in the marble and the elastic wave attenuation ofthe three types of granite was similar Among them the TBGhad the fastest elastic wave attenuation In general the at-tenuation of the P-wave came before the S-wave

312 Characteristic Parameter Analysis of Rod-Shaped RockAccording to the experimental schemes of the G3761-L andGAM-L samples the elastic wave propagation characteris-tics in the thin plate-shaped rock were discussed by ana-lyzing the changes in the amplitude of the AE signalsConsidering the error factor pulse vibration was carried outfour times for each group of rod-shaped rocks where theaverage value of the results was taken for discussion eattenuation curves of the amplitude of each measuring pointin different directions and different lithological samples arepresented in Figure 5

Table 3 Timing parameters in the experiment

Timing parameter G3768 G3561 TBG AAM GAM G3761-L GAM-LPDTμs 100 150 150 150 150 100 100HDTμs 200 300 300 300 300 200 200HLTμs 300 500 500 500 500 300 300

Advances in Civil Engineering 5

Amplitude

Energy

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

TBGRelat

ive d

ecay

rate

(dB)

Distance (cm)

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

AAMRelat

ive d

ecay

rate

(dB)

Amplitude

Energy

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

G3768Relat

ive d

ecay

rate

(dB)

Distance (cm)

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash3

ndash2

ndash1

0

G3561

Relat

ive d

ecay

rate

(dB)

Amplitude

Energy

Distance (cm)

20 50 70 100ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

GAM

(a)

Figure 4 Continued

6 Advances in Civil Engineering

It can be seen from Figure 5 that the amplitude of thelarge-scale plane plate rock showed similar exponentialattenuation characteristics with the increase of the propa-gation distance e AE wave attenuation of granite wasstronger than that of marble in the direction of 0deg and wasweaker than that of marble in the directions of 90deg and 45deg

Specifically due to the diversity and anisotropy of rockcomponents the attenuation of the AE wave in the range of20ndash80 cm in the direction of 0deg showed the fluctuation ofamplitude between 72 and 83 dB in both kinds of rockthough the overall trend was declining e amplitudecharacteristic parameters extracted from each measuring

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash5

ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

G3768

Amplitude

Energy

Distance (cm)

20 50 70 100 135

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

G3561

Amplitude

Energy

Distance (cm)

20 50 70 100 135

ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

TBG

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

AAM

Amplitude

Energy

Distance (cm)

20 50 70 100ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

GAM

(b)

Figure 4 e attenuation rates of energyamplitude with distance (a) End-pulse excitation (S-wave) (b) Terminal pulse excitation (P-wave)

Advances in Civil Engineering 7

point arranged in the front and back of the marble in the 45degdirection and 90deg direction presented significant changes Asudden decrease of amplitude appeared at 30ndash40 cm with adecrease of 1965 dB in the 45deg direction and 2455 dB in the90deg directione amplitude attenuation of granite tended tobe stable

e attenuation curves of the AE energy in differentdirections for G3761-L and GAM-L are shown in Figure 6 Itcan be seen that the energy in the marble changes violentlyand the energy value in the range of 45ndash55 cm in the di-rection of 0deg exhibits the abnormal phenomenon of stepeenergy attenuation was lower than that of the granite stonewhich shows the same trend with the amplitude attenuatione energy value of granite from 45 cm back to the end of thethin plate is almost maintained at 20ndash50mVms and tends tobe stable In the 45deg direction the marble exhibited theenhancement of energy value after 55 cm It is the reflectionof the AE wave along the 45deg direction when it met theboundary and the wave enhancement phenomenon wasformed by the superposition of multiple reflections andrefractions e marble and granite showed the same trendin the 90deg direction

32 Waveform Analysis of Acoustic Emission Signal

321 Time Domain Waveform and Spectrum Analysis ofAcoustic Emission Original Signal According to a largenumber of AE signal waveforms obtained by pulse excitationon the surface of each group of samples the AE signalwaveforms of rod-shaped and plate-shaped rocks were se-lected from the closest measuring point to the pulse sourcee middle measuring point in their respective directionsand the end measuring points were analyzed e specificlayout of measuring points is presented in Table 4

Since the original statistics of the nonstationary AEsignal is a time-varying function FFT transform was used toanalyze the spectral characteristics of the time-domain signalto better understand the variation law of elastic wave in thepropagation process Figure 7 presents the original signaltime-domain waveforms of measuring point M2 of eachgroup of rod-shaped rocks and the corresponding frequencyspectrum is shown in Figure 8 e related curves of the AE

signal excited from measuring points M2 on the surface ofthe plate-shaped rocks in the three directions of 0deg 90deg and45deg are shown in Figure 9

It can be seen from the time-domain diagram that thewaveforms of the AE signal generated by pulse excitationwere very similar and the duration was short For the rod-shaped rocks the durations for granites G3768 G3561 andTBG were in the range of 025ndash15ms where the waveformsdecayed quickly and the coda waves were not developede durations for AAM and GAM were in the range of05ndash20ms and 05ndash10ms respectively For the plate-shapedrocks the duration of G3761-L was 05ndash15ms in the 0degdirectione duration for GAM-L was 025ndash15ms and theamplitude attenuation variation was small Similarly in the45deg direction and 90deg direction the G3761-l granite showed ashorter duration of time than the GAM-L marble dem-onstrating that the homogeneity of the natural granite plate-shaped rock is better

It can be seen from the spectrum that the frequency ofthe AE signal generated by pulse excitation was relativelyhigh and the frequency band was relatively narrow emain frequency domain of each group of rod-shaped rockswas 0ndash250 kHz and the frequency domain of the AE signalat the M2 position measuring point in each direction of theplate-shaped rocks was 0ndash300 kHz In this frequency do-main each group of samples with different lithologies showsmultiple peaks of frequency indicating that the waveform ofthe AE signal is very complex and is a mixture of waves withdifferent characteristics

322 Wavelet Packet Energy Analysis of Acoustic EmissionSignal According to previous research wavelet transformonly decomposes the low-frequency partndashbut not the high-frequency part of the original signal e time-frequencylocalization could be better analyzed through the intro-duction of wavelet packet transform in which the high-frequency part of the signal could be further decomposed Asshown in Table 4 considering that wavelet packet analysishas the advantages of multilayer decomposition of signaldetails and scale information the following wavelet packetenergy feature extraction was conducted for the AE signal

0 20 40 60 80 100 12060

65

70

75

80

85

90

95

100A

mpl

itude

(dB)

G3761-L

GAM-L

0deg

Distance (cm)

G3761-L

GAM-L

0 10 20 30 40 50 6050

60

70

80

90

100

45deg

Distance (cm)

Am

plitu

de (d

B)

G3761-L

GAM-L

0 10 20 30 40 5050

60

70

80

90

100

90deg

Distance (cm)

Am

plitu

de (d

B)

Figure 5 e attenuation curves of the amplitude in different directions for G3761-L and GAM-L

8 Advances in Civil Engineering

waveform obtained at different measuring points in eachgroup of rock samples to explore the local feature infor-mation of the AE signal waveform at different positions ofrod-shaped and plate-shaped rocks

Choosing a suitable wavelet base plays an important rolein signal processing and analysis Guo [37] introduced theeffect of different wavelet bases in vibration signal processingin detail which presents that the db5 db7 db10 db13 db16bior26 bior39 coif4 sym7 and sym8 wavelet bases aremore suitable for the shock feature extraction of vibrationsignals Of this wavelet set db7 was selected as the waveletbase for the wavelet packet analysis because of its Daubechiesseries wavelet set characteristics such as high-order van-ishing moment tight support regularity approximatesymmetry and orthogonalityndashand because of the similaritiesit shares with the rock AE signal Its wavelet function ispresented in Figure 10

e sampling frequency is 3MHz According to thesampling theorem its Nyquist frequency is 1500 kHz ewavelet packet decomposition principle and algorithm wereapplied to decompose the signal to the 7th layer (ie thescale is 7) which has 27 wavelet packets in total ereforein the frequency domain the original signal was decom-posed into 128 subbands e width of each band was1172 kHz e frequency band range of each layer recon-structed after the decomposition of the original signal ispresented in Table 5

As can be seen from the table the original signal isexpressed as

S S70 + S71 + S72 + middot middot middot + S7127 (4)

where S70 is the low-frequency part of the decomposedsignal the other variables represent the decomposition of the

high-frequency part of the signal Assuming that the cor-responding energy of S7j(j 0 1 2 middot middot middot 127) isE7j(j 0 1 2 middot middot middot 127) then the energy characterization ofthe original AE signal decomposition in each frequencyband range can be obtained by formula (1)

Assuming that the total energy of the analyzed signal isE0 then

E0 1113944127

j0E7j (5)

e ratio of the energy of each frequency band to thetotal energy of the analyzed signal is

Ej E7j

E0times 100 (6)

In the formula j 012 27ndash1From Equation (1) the energy changes of the corre-

sponding AE signals in different frequency bands after theoriginal signal decomposition were calculated so the energydistribution characteristics of the elastic wave in differentfrequency bands could be found [38] According to Table 4the main frequency range of the AE signal waveform of eachmeasuring point was 0ndash300 kHz indicating that the energyvalue must also be concentrated in this frequency rangeerefore with MATLAB programming the energy dis-tribution of each subband in the frequency domain of0ndash500 kHz was obtained as shown in Figures 11 and 12

For rod-shaped rocks G3768 G3561 and TBG of thesame lithology from different places of origin the M1measuring point was closest to the pulse excitation sourceerefore the value of the M1 measuring point could ef-fectively reflect the energy value of the real pulse As can be

G3761-L

GAM-L

0deg

0 20 40 60 80 100 120

0

100

200

300

400

500

600

Distance (cm)

Ener

gy (m

Vlowast

ms)

G3761-L

GAM-L

45deg

Distance (cm)

Ener

gy (m

Vlowast

ms)

0 10 20 30 40 50 600

100

200

300

400

500

600

700

G3761-L

GAM-L

90deg

Distance (cm)

Ener

gy (m

Vlowast

ms)

0 10 20 30 40 50

100

200

300

400

500

600

700

Figure 6 e attenuation curves of the AE Energy in different directions for G3761-L and GAM-L

Table 4 e measuring point positions of AE waveforms

Rock number (measuring point) (cm) G3768 G3561 TBG AAM GAMG3761-L GAM-L

0deg 90deg 45deg 0deg 90deg 45deg

M1 5 5 5 5 5 5 5 5 5 5 5M2 70 70 70 70 50 55 20 30 40 25 30M3 135 135 135 135 100 100 35 50 75 40 50

Advances in Civil Engineering 9

seen from Figure 11 the energy is widely distributed in thefrequency domain e value of energy is generally smallwhich was mainly concentrated in the range of0ndash36428 kHz Combined with Formulas (5) and (6) it couldbe calculated that the main dominant energy of the three

groups of granite was concentrated in the frequency band of7131ndash12991 kHz which correspondingly accounted for646 5605 and 5828 of the total energy About2326 of the energy in G3561 was concentrated in thefrequency band of 23538ndash35256 kHz which is different

0 05 10 15 20 25ndash15

ndash10

ndash05

0

05

10

Am

plitu

de (m

V)

Time (ms)

G3768

TBG

0 05 10 15 20 25 3ndash08

ndash06

ndash04

ndash02

0

02

04

06

08

Am

plitu

de (m

V)

Time (ms)

G3561

0 05 10 15 20 25

ndash15

ndash10

ndash05

0

05

10

15

Time (ms)

Am

plitu

de (m

V)

AAM

0 05 10 15 2ndash20

ndash15

ndash10

ndash05

0

05

10

15

Time (ms)

Am

plitu

de (m

V)

GAM

0 05 10 15 20 25 30 35ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

Figure 7 Time domain waveform of measuring point M2 of rod-shaped rock

10 Advances in Civil Engineering

from other samples of the same lithology With the increaseof the propagation distance of the elastic wave its energyexhibited the characteristics of rapid attenuation edominant energy distribution frequency bands of the threerod-shaped rock materials at the M2 measuring point ex-panded from the initial 7131ndash12991 kHz to 0ndash17678 kHz

and the energy percentages were 8987 9407 and8658 respectively In the high-frequency band of28225ndash31741 kHz there was respectively 10 and 1269energy concentration for G3768 and TBG When the elasticwave propagated to the end of the rod (M3) the energy ofeach group of samples was relatively concentrated and

0 100 200 300 400 5000

001

002

003

004

Am

plitu

de (m

V)

Frequency (KHz)

G3768

TBG

0 100 200 300 400 5000

001

002

003

Am

plitu

de (m

V)

Frequency (KHz)

G3561

0 100 200 300 400 5000

001

002

003

004

005

006

007

Frequency (KHz)

Am

plitu

de (m

V)

AAM

0 100 200 300 400 5000

001

002

003

004

005

006

Frequency (KHz)

Am

plitu

de (m

V)

GAM

0 100 200 300 400 5000

0002

0004

0006

0008

0010

0012

Am

plitu

de (m

V)

Frequency (KHz)

Figure 8 e spectrogram of measuring point M2 of rod-shaped rock

Advances in Civil Engineering 11

G3761-L(90deg)

0 05 10 15 2ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

G3761-L(90deg)

0 100 200 300 400 500000

002

004

006

008

010

Am

plitu

de (m

V)

Frequency (KHz)

G3761-L(45deg)

0 05 10 15 20 25

ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

G3761-L(45deg)

0 100 200 300 400 5000

001

002

003

004

005

006

007

Am

plitu

de (m

V)

Frequency (KHz)

0 05 10 15 20 25 3ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

G3761-L(0deg)

Am

plitu

de (m

V)

Time (ms)

G3761-L(0deg)

0 100 200 300 400 5000

0002

0004

0006

0008

0010

Am

plitu

de (m

V)

Frequency (KHz)

(a)

Figure 9 Continued

12 Advances in Civil Engineering

mainly distributed within 0ndash10647 kHz at the percentages of9211 9022 and 9188 respectively By comparing thethree groups of rod-shaped rocks with the same lithology itcan be seen that the energy attenuation was the fastest inTBG and the dominant energy value was the lowest at theM3 measuring point For G3768 the energy attenuation wasthe slowest Only the distribution rule of the dominant

energy value at the M2 and M3 measuring points changedwhereas the maximum energy value hardly changed ereason may be that the internal structure or componentdensity of G3768 was better and the energy was relativelymaintained rather than rapidly attenuated with the elasticwave propagation For AAM artificial marble its maindominant energy also exhibited the same change trend as

GAM-L(45deg)

0 05 10 15 20 25

ndash3

ndash2

ndash1

0

1

2

3

4

Am

plitu

de (m

V)

Time (ms)

GAM-L(45deg)

0 100 200 300 400 5000

002

004

006

008

010

012

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(0deg)

0 05 10 15 20 25 30 35

ndash09

ndash06

ndash03

0

03

06

09

Am

plitu

de (m

V)

Time (ms)

GAM-L(0deg)

0 100 200 300 400 5000

0005

0010

0015

0020

0025

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(90deg)

0 05 10 15 20 25ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

GAM-L(90deg)

Am

plitu

de (m

V)

0 100 200 300 400 500000

002

004

006

008

010

Frequency (KHz)

(b)

Figure 9 e time waveform and spectrogram of measuring point M2 of pate-shaped rock

Advances in Civil Engineering 13

0 3 6 9 12 15ndash15

ndash10

ndash05

00

05

10

Wavelet function

0 3 6 9 12 15

ndash05

00

05

10

Scaling function

Figure 10 Wavelet function and scaling function for db7

Table 5 e frequency band range of reconstructed signal by wavelet packet decomposition

Layer S (i 0) S (i 1) S (i 2) S (i jminus 1) S (i j)1 0ndash750 ndash ndash ndash ndash 750ndash15002 0ndash375 375ndash750 750ndash1125 ndash ndash 1125ndash15003 0ndash1875 1875ndash375 375ndash5625 1125ndash13125 13125ndash15004 0ndash9375 9375ndash1875 1875ndash28125 13125ndash140625 140625ndash15005 0ndash46875 46875ndash9375 9375ndash140625 140625ndash1453125 1453125ndash15006 0ndash234375 234375ndash46875 46875ndash703125 1453125ndash14765625 14765625ndash15007 0ndash1171875 1171875ndash234375 234375ndash3515625 14765625ndash148828125 148828125ndash1500S (i j) represents the reconstruction signal of the j-th wavelet packet decomposition coefficient in the i-th layer i 1234 j 012 2i-1

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M3

(a)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500

1000

1500

2000

2500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

20

40

60

80

100

120

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

M3

(b)

Figure 11 Continued

14 Advances in Civil Engineering

granite From Figure 11 it can be observed that the energy ofthe original pulse signal is concentrated in the range of9475ndash16506 kHz and 2185 of the energy existed in thefrequency band of 28225ndash35256 kHz For GAMmarble themain dominant energy distribution of the initial signal wasvery wide and was distributed in the frequency band of0ndash36428 kHz Among them the dominant energy wasdistributed within the 10647ndash12991 kHz range accountingfor 3213 of the total energy Similar attenuation charac-teristics as granite were presented with the increase of elasticwave propagation distance In general for GAM the exci-tation energy of the AE signal generated by pulse excitationwas the weakest and the attenuation was the fastest with theincrease of distancee initial excitation energy of the threegroups of granite was partially concentrated in the frequency

band of 23538ndash35256 kHz of which the performance ofG3561 was the most obvious

e pulse AE signal was very complex for 2 groups of theplate-shaped rocks (Figure 12) erefore the initial energyof the M1 measuring point in each direction was also quitedifferent In the direction of 0deg the dominant energy of theoriginal pulse signal in G3761-L was concentrated in thefrequency band of 0ndash17678 kHz which accounted for8904 of the total energy Meanwhile about 628 of theenergy was distributed in the frequency band of29397ndash32913 kHz e same law was also shown in GAM-L but the main dominant frequency in GAM-L was rela-tively concentrated in the short frequency band of10647ndash17678 kHz which accounted for 6357 of the totalenergy With the spread of the elastic wave the energy in

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50002468

10121416

M3

(c)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5001000150020002500300035004000

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40

50

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M3

(d)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

100

200

300

400

500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M2

0 100 200 300 400 5000

2

4

6

8En

ergy

(mVlowast

mS)

Frequency (KHZ)

M3

0 100 200 300 400 500012345678

(e)

Figure 11e energy distribution of acoustic emission signal frequency band of rod-shaped rock (a) G3768 (b) G3561 (c) TBG (d) AAM(e) GAM

Advances in Civil Engineering 15

0 100 200 300 400 5000

200400600800

100012001400

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

M2

0 100 200 300 400 5000005101520253035

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

M3

0 100 200 300 400 50000020406081012

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

(a)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40En

ergy

(mVlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 5000

2

4

6

8

Ener

gy (m

Vlowast

mS)

(b)

M1

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

1020304050607080

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50002468

1012141618

Ener

gy (m

Vlowast

mS)

(c)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700800

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 50005

101520253035

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

Ener

gy (m

Vlowast

mS)

(d)

Figure 12 Continued

16 Advances in Civil Engineering

G3761-L showed a trend of attenuation and the energy intheM2measuring point was still distributed in the frequencyband of 0ndash17678 kHz e energy distribution at the M3measuring point was relatively concentrated and was locatedin the frequency band of 0ndash10647 kHz accounting for8340 of the total energy e energy at the measuringpoint M3 of GAM-L was more extensive in the frequencydomain and the energy value changed dramatically dem-onstrating the abnormal phenomenon that the maindominant energy increased e frequency range of thismeasuring point was 0ndash1885 kHz accounting for 8589 ofthe total energyere was also residual energy concentratedin the frequency band of 29397ndash32913 kHz e AE signalat M3 was superposed by the boundary reflection wave andthe energy was enhanced because of the high homogeneityand good ductility of GAM-L For G3761-L the dominantenergy of the elastic wave almost dissipated at the M3measuring point In the direction of 45deg the dominantenergy band of the original signal in G3761-L was distributedwithin 0ndash17678 kHz and 28225ndash35256 kHz respectivelyaccounting for 6415 and 3278 of the total energyMoreover it can be observed that the distribution of thedominant energy band was from distribution to concen-tration which was distributed in the frequency band of7131ndash17678 kHz at M2 With the increase of distance theenergy frequency band of the M3 measuring point near theedge of the plate was spread again and it was restored to theenergy frequency band range of the initial signal Howeverthe energy value was attenuated to a very small value at this

moment e energies of GAM-L in the measuring pointsM1 M2 and M3 were all distributed in the frequency bandof 0ndash36428 kHz In the direction of 90deg the primarydominant energy frequency bands of the two plate-shapedrocks were concentrated in 9475ndash1885 kHz e differenceis that the energy distribution of GAM-L was still con-centrated and the energy variation was much smaller thanG3761-L at the M2 measuring point In general the energyfrequency band of the two plate-shaped rocks with differentlithologies was the same as that of the rod-shape rock whichis mainly distributed in the range of 0ndash36428 kHz More-over they also exhibited the characteristics that the maindominant energy was distributed in the range of0ndash17678 kHz and the residual energy was distributed in therange of 28225ndash35256 kHz

4 Discussion

e purpose of this work was to study the propagationcharacteristics of elastic wave in lithological rock materialsrough the above research and analysis a preliminaryunderstanding was obtained Based on the deep waveletpacket analysis of amplitude energy characteristic param-eters and AE waveform the frequency band characteristicsof the local energy distribution of elastic wave with itspropagation were summarized However its propagationcharacteristics are difficult to be regularly grasped becausethe elastic wave itself is extremely complex Furthermore AEtechnology is mostly used in the damage detection and

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

20406080

100120140160

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

10

20

30

40

50

(e)

M1

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

200400600800

10001200140016001800

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

50

100

150

200

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 50005

101520253035

(f )

Figure 12e energy distribution of acoustic emission signal frequency band of plate-shaped rock (a) G3761-L (00) (b) G3761-L (450) (c)G3761-L (900) (d) GAM-L (00) (e) GAM-L (450) (f ) GAM-L (900)

Advances in Civil Engineering 17

defect location of metal or related materials with goodcompactness ductility and within the same medium ereare many uncertain interference factors in the experimentsIn some aspects the analysis of this paper only stays at thelevel of the apparent phenomenon and there are still manydeficiencies and areas worthy of improvement For instancethe density wave velocity and wave impedance of the rod-shaped rock samples should be tested and the micro-structure imaging experiments of the rock samples should beconducted e quality factor Q of different rock samplesshould be calculated Moreover the correlation between thequality factor and wave impedance should be studied andthe influence of different microcompositions of rod-shapedrocks on elastic wave attenuation should be deeply analyzedBased on the modal AE theory the influence of Lamb wavein plate-shaped rocks should be studied and the propagationmodel of two-dimensional AE should be constructed eGabor wavelet should be introduced to analyze the AE signalby time-frequency analysis e influence of differentwavelets based on the propagation effect of AE will becompared and analyzed and the time of the same mode ofthe AE wave arriving at the sensor will be determined tofurther optimize the plane location algorithm However theresearch in this work is still useful for studying large-scalerock samples in the future and provides effective researchmethods and ideas for the study of elastic wave propagationcharacteristics of different rock materials and compositematerials

5 Conclusions

In this work the characteristic parameter analysis andwaveform analysis of the AE signals obtained from differentexperimental schemes in 5 groups of rod-shaped rocks and 2groups of plate-shaped rocks were carried out e con-clusions are as follows

(1) e amplitude and energy of the rod-shaped rocksgradually attenuated with the increase of distancee amplitude can directly reflect the intensity of theAE counts at different measuring areas In theprocess of elastic wave propagation of the rod-sha-ped rock the P-wave preceded the S-wave andchanged violently e elastic wave of marble at-tenuated faster and the elastic wave of the threekinds of granite decayed attenuated closely Amongthem the elastic wave of TBG exhibited the fastestattenuation

(2) In flat plate-shaped rocks the amplitude exhibited anapproximate exponential attenuation characteristicwith the increase of the propagation distanceGranite exhibited a stronger elastic wave attenuationin the 0deg direction than the marble and the marblepresented fast attenuations in the 45deg and 90deg di-rections e energy change of marble was dramaticand the energy value in the interval of 45ndash55 cm atthe direction of 0deg showed the abnormal step phe-nomenon e energy value of the marble increasedafter 55 cm in the 45deg direction e energy value of

granite from the back to the end of the plate wasalmost maintained and tended to be stable at20ndash50mVms

(3) e frequency range of the energy distribution ofsamples in this work was within 0ndash36428 kHz Withthe increase of distance the main dominant energydistribution of the 5 groups of rod-shaped rocks inthe frequency range was characterized by distribu-tion to relative concentration and rapid energy at-tenuationemain dominant energy distribution ofthe 2 groups of plate-shaped rocks was distributed inthe range of 0ndash17678 kHz All rod-shaped rocks andplate-shaped rocks exhibited the characteristics ofresidual energy distribution in the frequency band of28225ndash35256 kHz

Data Availability

e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

e authors certify that they have no conflicts of interest

Acknowledgments

is research was funded by the National Natural ScienceFoundation of China (51804161 52074156 and 52004291)the Chinese Postdoctoral Science Foundation(2019M660861) and the State Key Laboratory CultivationBase for Gas Geology and Gas Control (Henan PolytechnicUniversity) (WS2020A04)

References

[1] J T Chen J H Zhao S C Zhang Y Zhang F Yang andM Li ldquoAn experimental and analytical research on theevolution of mining cracks in deep floor rock massrdquo Pure andApplied Geophysics vol 177 no 11 pp 5325ndash5348 2020

[2] K Wang and F Du ldquoCoal-gas compound dynamic disastersin China a reviewrdquo Process Safety and Environmental Pro-tection vol 133 pp 1ndash17 2020

[3] C Zhu M He M Karakus X Cui and Z Tao ldquoInvestigatingtoppling failure mechanism of anti-dip layered slope due toexcavation by physical modellingrdquo Rock Mechanics and RockEngineering vol 53 no 11 pp 5029ndash5050 2020

[4] X Wang C Liu S Chen L Chen K Li and N Liu ldquoImpactof coal sectorrsquos de-capacity policy on coal pricerdquo AppliedEnergy vol 265 Article ID 114802 2020

[5] D Liu Z Gu R Liang et al ldquoImpacts of pore-throat systemon fractal characterization of tight sandstonesrdquo Geofluidsvol 2020 no 9 17 pages Article ID 4941501 2020

[6] J Wang Y Zhang Z Qin S Song and P Lin ldquoAnalysismethod of water inrush for tunnels with damaged water-resisting rock mass based on finite element method-smoothparticle hydrodynamics couplingrdquo Computers and Geo-technics vol 126 Article ID 103725 2020

[7] B Chen S C Zhang Y Y Li Z K Li and H J ZhouldquoPhysical simulation study of crack propagation and insta-bility information discrimination of rock-like materials withfaultsrdquo Arabian Journal of Geosciences vol 13 p 966 2020

18 Advances in Civil Engineering

[8] F Du K Wang X Zhang C Xin and G Wang ldquoExperi-mental study of coal-gas outburst insights from coal-rockstructure gas pressure and adsorptivityrdquo Natural ResourcesResearch vol 29 no 4 pp 2481ndash2493 2020

[9] H Y Wang J Ma G D Wang et al ldquoResearch on AE sourcelocation of linear and plane rock massrdquo Shock and Vibrationvol 2020 Article ID 8846582 18 pages 2020

[10] V A Mansurov ldquoPrediction of rockbursts by analysis ofinduced seismicity datardquo International Journal of Rock Me-chanics and Mining Sciences vol 38 no 6 pp 893ndash901 2001

[11] M C He J L Miao and J L Feng ldquoRock burst process oflimestone and its acoustic emission characteristics under true-triaxial unloading conditionsrdquo International Journal of RockMechanics and Mining Sciences vol 47 no 2 pp 286ndash2982010

[12] F Gong J Yan X Li and S Luo ldquoA peak-strength strainenergy storage index for rock burst proneness of rock ma-terialsrdquo International Journal of Rock Mechanics and MiningSciences vol 117 pp 76ndash89 2019

[13] F Du and KWang ldquoUnstable failure of gas-bearing coal-rockcombination bodies insights from physical experiments andnumerical simulationsrdquo Process Safety and EnvironmentalProtection vol 129 pp 264ndash279 2019

[14] S D Butt C Mukherjee and G Lebans ldquoEvaluation ofacoustic attenuation as an indicator of roof stability in ad-vancing headingsrdquo International Journal of Rock Mechanicsand Mining Sciences vol 37 no 7 pp 1123ndash1131 2000

[15] M Cai H Morioka P K Kaiser et al ldquoBack-analysis of rockmass strength parameters using ae monitoring datardquo Inter-national Journal of Rock Mechanics and Mining Sciencesvol 44 no 4 pp 538ndash549 2007

[16] D P Jansen S R Carlson R P Young and D A HutchinsldquoUltrasonic imaging and acoustic emission monitoring ofthermally induced microcracks in Lac du Bonnet graniterdquoJournal of Geophysical Research Solid Earth vol 98 no B12pp 22231ndash22243 1993

[17] U Bismayer ldquoEarly warning signs for mining accidentsdetecting crackling noiserdquo American Mineralogist vol 102no 1 pp 3-4 2017

[18] X Kong E Wang S Li H Lin P Xiao and K ZhangldquoFractals and chaos characteristics of acoustic emission energyabout gas-bearing coal during loaded failurerdquo Fractals vol 27no 5 Article ID 195072 2019

[19] F Du K Wang G Wang Y Jiang C Xin and X ZhangldquoInvestigation of the acoustic emission characteristics duringdeformation and failure of gas-bearing coal-rock combinedbodiesrdquo Journal of Loss Prevention in the Process Industriesvol 55 pp 253ndash266 2018

[20] R P Young D A Hutchins S Talebi et al ldquoLaboratory andfield investigations of rockburst phenomena using concurrentgeotomographic imaging and acoustic emissionmicroseismictechniquesrdquo Seismicity in Mines vol 129 no 3-4pp 647ndash659 1989

[21] X Jansen H Xu M He and F Zhang ldquoExperimental in-vestigation of the occurrence of rockburst in a rock specimenthrough infrared thermography and acoustic emissionrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 93 pp 250ndash259 2017

[22] R E Goodman and E Richard ldquoSubaudible noise duringcompression of rocksrdquo Geological Society of America Bulletinvol 74 no 4 pp 487ndash490 1963

[23] M Cai P K Kaiser H Morioka et al ldquoFLACPFC couplednumerical simulation of AE in large-scale underground

excavationsrdquo International Journal of Rock Mechanics andMining Sciences vol 44 no 4 pp 550ndash564 2007

[24] V Saltas F Vallianatos D Triantis T Koumoudeli andI Stavrakas ldquoNon-extensive statistical analysis of acousticemissions series recorded during the uniaxial compression ofbrittle rocksrdquo Physica A Statistical Mechanics and Its Ap-plications vol 528 Article ID 121498 2019

[25] V Saltas I Fitilis and F Vallianatos ldquoA combined complexelectrical impedance and acoustic emission study in limestonesamples under uniaxial loadingrdquo Tectonophysics vol 637pp 198ndash206 2014

[26] G Qi ldquoWavelet-based AE characterization of compositematerialsrdquo NDTamp E International vol 33 no 3 pp 133ndash1442000

[27] G Manthei J Eisenblatter and T Dahm ldquoMoment tensorevaluation of acoustic emission sources in salt rockrdquo Con-struction and Building Materials vol 15 no 5-6 pp 297ndash3092001

[28] H Jeong and Y-S Jang ldquoWavelet analysis of plate wavepropagation in composite laminatesrdquo Composite Structuresvol 49 no 4 pp 443ndash450 2000

[29] S-H Chang and C-I Lee ldquoEstimation of cracking anddamage mechanisms in rock under triaxial compression bymoment tensor analysis of acoustic emissionrdquo InternationalJournal of Rock Mechanics and Mining Sciences vol 41 no 7pp 1069ndash1086 2004

[30] T Hirata T Satoh and K Ito ldquoFractal structure of spatialdistribution of microfracturing in rockrdquo Geophysical JournalInternational vol 90 no 2 pp 369ndash374 1987

[31] X Lei K Masuda O Nishizawa et al ldquoDetailed analysis ofacoustic emission activity during catastrophic fracture offaults in rockrdquo Journal of Structural Geology vol 26 no 2pp 247ndash258 2004

[32] J Jouniaux J Pei J Liu et al ldquoInvestigation on acousticemission behavior and its time-space evolution mechanism infailure process of coalndashrock combined bodyrdquo Chinese Journalof Rock Mechanics and Engineering vol 30 pp 1564ndash15702011

[33] E Townend B D ompson P M Benson PG MeredithP Baud and R P Young ldquoImaging compaction bandpropagation in Diemelstadt sandstone using acoustic emis-sion locationsrdquo Geophysical Research Letters vol 35 no 15pp 189ndash193 2008

[34] M Naderloo M Moosavi and M Ahmadi ldquoUsing acousticemission technique tomonitor damage progress around jointsin brittle materialsrdquo Deoretical and Applied Fracture Me-chanics vol 104 Article ID 102368 2019

[35] GBT Unified Number of Natural Stone China StandardsPress Beijing China 2009

[36] G Shen Acoustic Emission Detection Technology and Appli-cation Science Press Beijing China 2015

[37] Y Guo Research on Wavelet Base Selection for VibrationSignal Processing Hefei University of Technology HefeiChina 2003

[38] F Xu E Wang and D Song ldquoLong-range correlation andmultifractal distribution of acoustic emission of coal-rockrdquoRock and Soil Mechanics vol 32 no 7 pp 2111ndash2116 2011

Advances in Civil Engineering 19

Amplitude

Energy

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

TBGRelat

ive d

ecay

rate

(dB)

Distance (cm)

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

AAMRelat

ive d

ecay

rate

(dB)

Amplitude

Energy

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

G3768Relat

ive d

ecay

rate

(dB)

Distance (cm)

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash3

ndash2

ndash1

0

G3561

Relat

ive d

ecay

rate

(dB)

Amplitude

Energy

Distance (cm)

20 50 70 100ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

GAM

(a)

Figure 4 Continued

6 Advances in Civil Engineering

It can be seen from Figure 5 that the amplitude of thelarge-scale plane plate rock showed similar exponentialattenuation characteristics with the increase of the propa-gation distance e AE wave attenuation of granite wasstronger than that of marble in the direction of 0deg and wasweaker than that of marble in the directions of 90deg and 45deg

Specifically due to the diversity and anisotropy of rockcomponents the attenuation of the AE wave in the range of20ndash80 cm in the direction of 0deg showed the fluctuation ofamplitude between 72 and 83 dB in both kinds of rockthough the overall trend was declining e amplitudecharacteristic parameters extracted from each measuring

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash5

ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

G3768

Amplitude

Energy

Distance (cm)

20 50 70 100 135

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

G3561

Amplitude

Energy

Distance (cm)

20 50 70 100 135

ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

TBG

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

AAM

Amplitude

Energy

Distance (cm)

20 50 70 100ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

GAM

(b)

Figure 4 e attenuation rates of energyamplitude with distance (a) End-pulse excitation (S-wave) (b) Terminal pulse excitation (P-wave)

Advances in Civil Engineering 7

point arranged in the front and back of the marble in the 45degdirection and 90deg direction presented significant changes Asudden decrease of amplitude appeared at 30ndash40 cm with adecrease of 1965 dB in the 45deg direction and 2455 dB in the90deg directione amplitude attenuation of granite tended tobe stable

e attenuation curves of the AE energy in differentdirections for G3761-L and GAM-L are shown in Figure 6 Itcan be seen that the energy in the marble changes violentlyand the energy value in the range of 45ndash55 cm in the di-rection of 0deg exhibits the abnormal phenomenon of stepeenergy attenuation was lower than that of the granite stonewhich shows the same trend with the amplitude attenuatione energy value of granite from 45 cm back to the end of thethin plate is almost maintained at 20ndash50mVms and tends tobe stable In the 45deg direction the marble exhibited theenhancement of energy value after 55 cm It is the reflectionof the AE wave along the 45deg direction when it met theboundary and the wave enhancement phenomenon wasformed by the superposition of multiple reflections andrefractions e marble and granite showed the same trendin the 90deg direction

32 Waveform Analysis of Acoustic Emission Signal

321 Time Domain Waveform and Spectrum Analysis ofAcoustic Emission Original Signal According to a largenumber of AE signal waveforms obtained by pulse excitationon the surface of each group of samples the AE signalwaveforms of rod-shaped and plate-shaped rocks were se-lected from the closest measuring point to the pulse sourcee middle measuring point in their respective directionsand the end measuring points were analyzed e specificlayout of measuring points is presented in Table 4

Since the original statistics of the nonstationary AEsignal is a time-varying function FFT transform was used toanalyze the spectral characteristics of the time-domain signalto better understand the variation law of elastic wave in thepropagation process Figure 7 presents the original signaltime-domain waveforms of measuring point M2 of eachgroup of rod-shaped rocks and the corresponding frequencyspectrum is shown in Figure 8 e related curves of the AE

signal excited from measuring points M2 on the surface ofthe plate-shaped rocks in the three directions of 0deg 90deg and45deg are shown in Figure 9

It can be seen from the time-domain diagram that thewaveforms of the AE signal generated by pulse excitationwere very similar and the duration was short For the rod-shaped rocks the durations for granites G3768 G3561 andTBG were in the range of 025ndash15ms where the waveformsdecayed quickly and the coda waves were not developede durations for AAM and GAM were in the range of05ndash20ms and 05ndash10ms respectively For the plate-shapedrocks the duration of G3761-L was 05ndash15ms in the 0degdirectione duration for GAM-L was 025ndash15ms and theamplitude attenuation variation was small Similarly in the45deg direction and 90deg direction the G3761-l granite showed ashorter duration of time than the GAM-L marble dem-onstrating that the homogeneity of the natural granite plate-shaped rock is better

It can be seen from the spectrum that the frequency ofthe AE signal generated by pulse excitation was relativelyhigh and the frequency band was relatively narrow emain frequency domain of each group of rod-shaped rockswas 0ndash250 kHz and the frequency domain of the AE signalat the M2 position measuring point in each direction of theplate-shaped rocks was 0ndash300 kHz In this frequency do-main each group of samples with different lithologies showsmultiple peaks of frequency indicating that the waveform ofthe AE signal is very complex and is a mixture of waves withdifferent characteristics

322 Wavelet Packet Energy Analysis of Acoustic EmissionSignal According to previous research wavelet transformonly decomposes the low-frequency partndashbut not the high-frequency part of the original signal e time-frequencylocalization could be better analyzed through the intro-duction of wavelet packet transform in which the high-frequency part of the signal could be further decomposed Asshown in Table 4 considering that wavelet packet analysishas the advantages of multilayer decomposition of signaldetails and scale information the following wavelet packetenergy feature extraction was conducted for the AE signal

0 20 40 60 80 100 12060

65

70

75

80

85

90

95

100A

mpl

itude

(dB)

G3761-L

GAM-L

0deg

Distance (cm)

G3761-L

GAM-L

0 10 20 30 40 50 6050

60

70

80

90

100

45deg

Distance (cm)

Am

plitu

de (d

B)

G3761-L

GAM-L

0 10 20 30 40 5050

60

70

80

90

100

90deg

Distance (cm)

Am

plitu

de (d

B)

Figure 5 e attenuation curves of the amplitude in different directions for G3761-L and GAM-L

8 Advances in Civil Engineering

waveform obtained at different measuring points in eachgroup of rock samples to explore the local feature infor-mation of the AE signal waveform at different positions ofrod-shaped and plate-shaped rocks

Choosing a suitable wavelet base plays an important rolein signal processing and analysis Guo [37] introduced theeffect of different wavelet bases in vibration signal processingin detail which presents that the db5 db7 db10 db13 db16bior26 bior39 coif4 sym7 and sym8 wavelet bases aremore suitable for the shock feature extraction of vibrationsignals Of this wavelet set db7 was selected as the waveletbase for the wavelet packet analysis because of its Daubechiesseries wavelet set characteristics such as high-order van-ishing moment tight support regularity approximatesymmetry and orthogonalityndashand because of the similaritiesit shares with the rock AE signal Its wavelet function ispresented in Figure 10

e sampling frequency is 3MHz According to thesampling theorem its Nyquist frequency is 1500 kHz ewavelet packet decomposition principle and algorithm wereapplied to decompose the signal to the 7th layer (ie thescale is 7) which has 27 wavelet packets in total ereforein the frequency domain the original signal was decom-posed into 128 subbands e width of each band was1172 kHz e frequency band range of each layer recon-structed after the decomposition of the original signal ispresented in Table 5

As can be seen from the table the original signal isexpressed as

S S70 + S71 + S72 + middot middot middot + S7127 (4)

where S70 is the low-frequency part of the decomposedsignal the other variables represent the decomposition of the

high-frequency part of the signal Assuming that the cor-responding energy of S7j(j 0 1 2 middot middot middot 127) isE7j(j 0 1 2 middot middot middot 127) then the energy characterization ofthe original AE signal decomposition in each frequencyband range can be obtained by formula (1)

Assuming that the total energy of the analyzed signal isE0 then

E0 1113944127

j0E7j (5)

e ratio of the energy of each frequency band to thetotal energy of the analyzed signal is

Ej E7j

E0times 100 (6)

In the formula j 012 27ndash1From Equation (1) the energy changes of the corre-

sponding AE signals in different frequency bands after theoriginal signal decomposition were calculated so the energydistribution characteristics of the elastic wave in differentfrequency bands could be found [38] According to Table 4the main frequency range of the AE signal waveform of eachmeasuring point was 0ndash300 kHz indicating that the energyvalue must also be concentrated in this frequency rangeerefore with MATLAB programming the energy dis-tribution of each subband in the frequency domain of0ndash500 kHz was obtained as shown in Figures 11 and 12

For rod-shaped rocks G3768 G3561 and TBG of thesame lithology from different places of origin the M1measuring point was closest to the pulse excitation sourceerefore the value of the M1 measuring point could ef-fectively reflect the energy value of the real pulse As can be

G3761-L

GAM-L

0deg

0 20 40 60 80 100 120

0

100

200

300

400

500

600

Distance (cm)

Ener

gy (m

Vlowast

ms)

G3761-L

GAM-L

45deg

Distance (cm)

Ener

gy (m

Vlowast

ms)

0 10 20 30 40 50 600

100

200

300

400

500

600

700

G3761-L

GAM-L

90deg

Distance (cm)

Ener

gy (m

Vlowast

ms)

0 10 20 30 40 50

100

200

300

400

500

600

700

Figure 6 e attenuation curves of the AE Energy in different directions for G3761-L and GAM-L

Table 4 e measuring point positions of AE waveforms

Rock number (measuring point) (cm) G3768 G3561 TBG AAM GAMG3761-L GAM-L

0deg 90deg 45deg 0deg 90deg 45deg

M1 5 5 5 5 5 5 5 5 5 5 5M2 70 70 70 70 50 55 20 30 40 25 30M3 135 135 135 135 100 100 35 50 75 40 50

Advances in Civil Engineering 9

seen from Figure 11 the energy is widely distributed in thefrequency domain e value of energy is generally smallwhich was mainly concentrated in the range of0ndash36428 kHz Combined with Formulas (5) and (6) it couldbe calculated that the main dominant energy of the three

groups of granite was concentrated in the frequency band of7131ndash12991 kHz which correspondingly accounted for646 5605 and 5828 of the total energy About2326 of the energy in G3561 was concentrated in thefrequency band of 23538ndash35256 kHz which is different

0 05 10 15 20 25ndash15

ndash10

ndash05

0

05

10

Am

plitu

de (m

V)

Time (ms)

G3768

TBG

0 05 10 15 20 25 3ndash08

ndash06

ndash04

ndash02

0

02

04

06

08

Am

plitu

de (m

V)

Time (ms)

G3561

0 05 10 15 20 25

ndash15

ndash10

ndash05

0

05

10

15

Time (ms)

Am

plitu

de (m

V)

AAM

0 05 10 15 2ndash20

ndash15

ndash10

ndash05

0

05

10

15

Time (ms)

Am

plitu

de (m

V)

GAM

0 05 10 15 20 25 30 35ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

Figure 7 Time domain waveform of measuring point M2 of rod-shaped rock

10 Advances in Civil Engineering

from other samples of the same lithology With the increaseof the propagation distance of the elastic wave its energyexhibited the characteristics of rapid attenuation edominant energy distribution frequency bands of the threerod-shaped rock materials at the M2 measuring point ex-panded from the initial 7131ndash12991 kHz to 0ndash17678 kHz

and the energy percentages were 8987 9407 and8658 respectively In the high-frequency band of28225ndash31741 kHz there was respectively 10 and 1269energy concentration for G3768 and TBG When the elasticwave propagated to the end of the rod (M3) the energy ofeach group of samples was relatively concentrated and

0 100 200 300 400 5000

001

002

003

004

Am

plitu

de (m

V)

Frequency (KHz)

G3768

TBG

0 100 200 300 400 5000

001

002

003

Am

plitu

de (m

V)

Frequency (KHz)

G3561

0 100 200 300 400 5000

001

002

003

004

005

006

007

Frequency (KHz)

Am

plitu

de (m

V)

AAM

0 100 200 300 400 5000

001

002

003

004

005

006

Frequency (KHz)

Am

plitu

de (m

V)

GAM

0 100 200 300 400 5000

0002

0004

0006

0008

0010

0012

Am

plitu

de (m

V)

Frequency (KHz)

Figure 8 e spectrogram of measuring point M2 of rod-shaped rock

Advances in Civil Engineering 11

G3761-L(90deg)

0 05 10 15 2ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

G3761-L(90deg)

0 100 200 300 400 500000

002

004

006

008

010

Am

plitu

de (m

V)

Frequency (KHz)

G3761-L(45deg)

0 05 10 15 20 25

ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

G3761-L(45deg)

0 100 200 300 400 5000

001

002

003

004

005

006

007

Am

plitu

de (m

V)

Frequency (KHz)

0 05 10 15 20 25 3ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

G3761-L(0deg)

Am

plitu

de (m

V)

Time (ms)

G3761-L(0deg)

0 100 200 300 400 5000

0002

0004

0006

0008

0010

Am

plitu

de (m

V)

Frequency (KHz)

(a)

Figure 9 Continued

12 Advances in Civil Engineering

mainly distributed within 0ndash10647 kHz at the percentages of9211 9022 and 9188 respectively By comparing thethree groups of rod-shaped rocks with the same lithology itcan be seen that the energy attenuation was the fastest inTBG and the dominant energy value was the lowest at theM3 measuring point For G3768 the energy attenuation wasthe slowest Only the distribution rule of the dominant

energy value at the M2 and M3 measuring points changedwhereas the maximum energy value hardly changed ereason may be that the internal structure or componentdensity of G3768 was better and the energy was relativelymaintained rather than rapidly attenuated with the elasticwave propagation For AAM artificial marble its maindominant energy also exhibited the same change trend as

GAM-L(45deg)

0 05 10 15 20 25

ndash3

ndash2

ndash1

0

1

2

3

4

Am

plitu

de (m

V)

Time (ms)

GAM-L(45deg)

0 100 200 300 400 5000

002

004

006

008

010

012

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(0deg)

0 05 10 15 20 25 30 35

ndash09

ndash06

ndash03

0

03

06

09

Am

plitu

de (m

V)

Time (ms)

GAM-L(0deg)

0 100 200 300 400 5000

0005

0010

0015

0020

0025

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(90deg)

0 05 10 15 20 25ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

GAM-L(90deg)

Am

plitu

de (m

V)

0 100 200 300 400 500000

002

004

006

008

010

Frequency (KHz)

(b)

Figure 9 e time waveform and spectrogram of measuring point M2 of pate-shaped rock

Advances in Civil Engineering 13

0 3 6 9 12 15ndash15

ndash10

ndash05

00

05

10

Wavelet function

0 3 6 9 12 15

ndash05

00

05

10

Scaling function

Figure 10 Wavelet function and scaling function for db7

Table 5 e frequency band range of reconstructed signal by wavelet packet decomposition

Layer S (i 0) S (i 1) S (i 2) S (i jminus 1) S (i j)1 0ndash750 ndash ndash ndash ndash 750ndash15002 0ndash375 375ndash750 750ndash1125 ndash ndash 1125ndash15003 0ndash1875 1875ndash375 375ndash5625 1125ndash13125 13125ndash15004 0ndash9375 9375ndash1875 1875ndash28125 13125ndash140625 140625ndash15005 0ndash46875 46875ndash9375 9375ndash140625 140625ndash1453125 1453125ndash15006 0ndash234375 234375ndash46875 46875ndash703125 1453125ndash14765625 14765625ndash15007 0ndash1171875 1171875ndash234375 234375ndash3515625 14765625ndash148828125 148828125ndash1500S (i j) represents the reconstruction signal of the j-th wavelet packet decomposition coefficient in the i-th layer i 1234 j 012 2i-1

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M3

(a)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500

1000

1500

2000

2500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

20

40

60

80

100

120

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

M3

(b)

Figure 11 Continued

14 Advances in Civil Engineering

granite From Figure 11 it can be observed that the energy ofthe original pulse signal is concentrated in the range of9475ndash16506 kHz and 2185 of the energy existed in thefrequency band of 28225ndash35256 kHz For GAMmarble themain dominant energy distribution of the initial signal wasvery wide and was distributed in the frequency band of0ndash36428 kHz Among them the dominant energy wasdistributed within the 10647ndash12991 kHz range accountingfor 3213 of the total energy Similar attenuation charac-teristics as granite were presented with the increase of elasticwave propagation distance In general for GAM the exci-tation energy of the AE signal generated by pulse excitationwas the weakest and the attenuation was the fastest with theincrease of distancee initial excitation energy of the threegroups of granite was partially concentrated in the frequency

band of 23538ndash35256 kHz of which the performance ofG3561 was the most obvious

e pulse AE signal was very complex for 2 groups of theplate-shaped rocks (Figure 12) erefore the initial energyof the M1 measuring point in each direction was also quitedifferent In the direction of 0deg the dominant energy of theoriginal pulse signal in G3761-L was concentrated in thefrequency band of 0ndash17678 kHz which accounted for8904 of the total energy Meanwhile about 628 of theenergy was distributed in the frequency band of29397ndash32913 kHz e same law was also shown in GAM-L but the main dominant frequency in GAM-L was rela-tively concentrated in the short frequency band of10647ndash17678 kHz which accounted for 6357 of the totalenergy With the spread of the elastic wave the energy in

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50002468

10121416

M3

(c)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5001000150020002500300035004000

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40

50

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M3

(d)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

100

200

300

400

500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M2

0 100 200 300 400 5000

2

4

6

8En

ergy

(mVlowast

mS)

Frequency (KHZ)

M3

0 100 200 300 400 500012345678

(e)

Figure 11e energy distribution of acoustic emission signal frequency band of rod-shaped rock (a) G3768 (b) G3561 (c) TBG (d) AAM(e) GAM

Advances in Civil Engineering 15

0 100 200 300 400 5000

200400600800

100012001400

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

M2

0 100 200 300 400 5000005101520253035

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

M3

0 100 200 300 400 50000020406081012

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

(a)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40En

ergy

(mVlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 5000

2

4

6

8

Ener

gy (m

Vlowast

mS)

(b)

M1

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

1020304050607080

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50002468

1012141618

Ener

gy (m

Vlowast

mS)

(c)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700800

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 50005

101520253035

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

Ener

gy (m

Vlowast

mS)

(d)

Figure 12 Continued

16 Advances in Civil Engineering

G3761-L showed a trend of attenuation and the energy intheM2measuring point was still distributed in the frequencyband of 0ndash17678 kHz e energy distribution at the M3measuring point was relatively concentrated and was locatedin the frequency band of 0ndash10647 kHz accounting for8340 of the total energy e energy at the measuringpoint M3 of GAM-L was more extensive in the frequencydomain and the energy value changed dramatically dem-onstrating the abnormal phenomenon that the maindominant energy increased e frequency range of thismeasuring point was 0ndash1885 kHz accounting for 8589 ofthe total energyere was also residual energy concentratedin the frequency band of 29397ndash32913 kHz e AE signalat M3 was superposed by the boundary reflection wave andthe energy was enhanced because of the high homogeneityand good ductility of GAM-L For G3761-L the dominantenergy of the elastic wave almost dissipated at the M3measuring point In the direction of 45deg the dominantenergy band of the original signal in G3761-L was distributedwithin 0ndash17678 kHz and 28225ndash35256 kHz respectivelyaccounting for 6415 and 3278 of the total energyMoreover it can be observed that the distribution of thedominant energy band was from distribution to concen-tration which was distributed in the frequency band of7131ndash17678 kHz at M2 With the increase of distance theenergy frequency band of the M3 measuring point near theedge of the plate was spread again and it was restored to theenergy frequency band range of the initial signal Howeverthe energy value was attenuated to a very small value at this

moment e energies of GAM-L in the measuring pointsM1 M2 and M3 were all distributed in the frequency bandof 0ndash36428 kHz In the direction of 90deg the primarydominant energy frequency bands of the two plate-shapedrocks were concentrated in 9475ndash1885 kHz e differenceis that the energy distribution of GAM-L was still con-centrated and the energy variation was much smaller thanG3761-L at the M2 measuring point In general the energyfrequency band of the two plate-shaped rocks with differentlithologies was the same as that of the rod-shape rock whichis mainly distributed in the range of 0ndash36428 kHz More-over they also exhibited the characteristics that the maindominant energy was distributed in the range of0ndash17678 kHz and the residual energy was distributed in therange of 28225ndash35256 kHz

4 Discussion

e purpose of this work was to study the propagationcharacteristics of elastic wave in lithological rock materialsrough the above research and analysis a preliminaryunderstanding was obtained Based on the deep waveletpacket analysis of amplitude energy characteristic param-eters and AE waveform the frequency band characteristicsof the local energy distribution of elastic wave with itspropagation were summarized However its propagationcharacteristics are difficult to be regularly grasped becausethe elastic wave itself is extremely complex Furthermore AEtechnology is mostly used in the damage detection and

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

20406080

100120140160

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

10

20

30

40

50

(e)

M1

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

200400600800

10001200140016001800

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

50

100

150

200

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 50005

101520253035

(f )

Figure 12e energy distribution of acoustic emission signal frequency band of plate-shaped rock (a) G3761-L (00) (b) G3761-L (450) (c)G3761-L (900) (d) GAM-L (00) (e) GAM-L (450) (f ) GAM-L (900)

Advances in Civil Engineering 17

defect location of metal or related materials with goodcompactness ductility and within the same medium ereare many uncertain interference factors in the experimentsIn some aspects the analysis of this paper only stays at thelevel of the apparent phenomenon and there are still manydeficiencies and areas worthy of improvement For instancethe density wave velocity and wave impedance of the rod-shaped rock samples should be tested and the micro-structure imaging experiments of the rock samples should beconducted e quality factor Q of different rock samplesshould be calculated Moreover the correlation between thequality factor and wave impedance should be studied andthe influence of different microcompositions of rod-shapedrocks on elastic wave attenuation should be deeply analyzedBased on the modal AE theory the influence of Lamb wavein plate-shaped rocks should be studied and the propagationmodel of two-dimensional AE should be constructed eGabor wavelet should be introduced to analyze the AE signalby time-frequency analysis e influence of differentwavelets based on the propagation effect of AE will becompared and analyzed and the time of the same mode ofthe AE wave arriving at the sensor will be determined tofurther optimize the plane location algorithm However theresearch in this work is still useful for studying large-scalerock samples in the future and provides effective researchmethods and ideas for the study of elastic wave propagationcharacteristics of different rock materials and compositematerials

5 Conclusions

In this work the characteristic parameter analysis andwaveform analysis of the AE signals obtained from differentexperimental schemes in 5 groups of rod-shaped rocks and 2groups of plate-shaped rocks were carried out e con-clusions are as follows

(1) e amplitude and energy of the rod-shaped rocksgradually attenuated with the increase of distancee amplitude can directly reflect the intensity of theAE counts at different measuring areas In theprocess of elastic wave propagation of the rod-sha-ped rock the P-wave preceded the S-wave andchanged violently e elastic wave of marble at-tenuated faster and the elastic wave of the threekinds of granite decayed attenuated closely Amongthem the elastic wave of TBG exhibited the fastestattenuation

(2) In flat plate-shaped rocks the amplitude exhibited anapproximate exponential attenuation characteristicwith the increase of the propagation distanceGranite exhibited a stronger elastic wave attenuationin the 0deg direction than the marble and the marblepresented fast attenuations in the 45deg and 90deg di-rections e energy change of marble was dramaticand the energy value in the interval of 45ndash55 cm atthe direction of 0deg showed the abnormal step phe-nomenon e energy value of the marble increasedafter 55 cm in the 45deg direction e energy value of

granite from the back to the end of the plate wasalmost maintained and tended to be stable at20ndash50mVms

(3) e frequency range of the energy distribution ofsamples in this work was within 0ndash36428 kHz Withthe increase of distance the main dominant energydistribution of the 5 groups of rod-shaped rocks inthe frequency range was characterized by distribu-tion to relative concentration and rapid energy at-tenuationemain dominant energy distribution ofthe 2 groups of plate-shaped rocks was distributed inthe range of 0ndash17678 kHz All rod-shaped rocks andplate-shaped rocks exhibited the characteristics ofresidual energy distribution in the frequency band of28225ndash35256 kHz

Data Availability

e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

e authors certify that they have no conflicts of interest

Acknowledgments

is research was funded by the National Natural ScienceFoundation of China (51804161 52074156 and 52004291)the Chinese Postdoctoral Science Foundation(2019M660861) and the State Key Laboratory CultivationBase for Gas Geology and Gas Control (Henan PolytechnicUniversity) (WS2020A04)

References

[1] J T Chen J H Zhao S C Zhang Y Zhang F Yang andM Li ldquoAn experimental and analytical research on theevolution of mining cracks in deep floor rock massrdquo Pure andApplied Geophysics vol 177 no 11 pp 5325ndash5348 2020

[2] K Wang and F Du ldquoCoal-gas compound dynamic disastersin China a reviewrdquo Process Safety and Environmental Pro-tection vol 133 pp 1ndash17 2020

[3] C Zhu M He M Karakus X Cui and Z Tao ldquoInvestigatingtoppling failure mechanism of anti-dip layered slope due toexcavation by physical modellingrdquo Rock Mechanics and RockEngineering vol 53 no 11 pp 5029ndash5050 2020

[4] X Wang C Liu S Chen L Chen K Li and N Liu ldquoImpactof coal sectorrsquos de-capacity policy on coal pricerdquo AppliedEnergy vol 265 Article ID 114802 2020

[5] D Liu Z Gu R Liang et al ldquoImpacts of pore-throat systemon fractal characterization of tight sandstonesrdquo Geofluidsvol 2020 no 9 17 pages Article ID 4941501 2020

[6] J Wang Y Zhang Z Qin S Song and P Lin ldquoAnalysismethod of water inrush for tunnels with damaged water-resisting rock mass based on finite element method-smoothparticle hydrodynamics couplingrdquo Computers and Geo-technics vol 126 Article ID 103725 2020

[7] B Chen S C Zhang Y Y Li Z K Li and H J ZhouldquoPhysical simulation study of crack propagation and insta-bility information discrimination of rock-like materials withfaultsrdquo Arabian Journal of Geosciences vol 13 p 966 2020

18 Advances in Civil Engineering

[8] F Du K Wang X Zhang C Xin and G Wang ldquoExperi-mental study of coal-gas outburst insights from coal-rockstructure gas pressure and adsorptivityrdquo Natural ResourcesResearch vol 29 no 4 pp 2481ndash2493 2020

[9] H Y Wang J Ma G D Wang et al ldquoResearch on AE sourcelocation of linear and plane rock massrdquo Shock and Vibrationvol 2020 Article ID 8846582 18 pages 2020

[10] V A Mansurov ldquoPrediction of rockbursts by analysis ofinduced seismicity datardquo International Journal of Rock Me-chanics and Mining Sciences vol 38 no 6 pp 893ndash901 2001

[11] M C He J L Miao and J L Feng ldquoRock burst process oflimestone and its acoustic emission characteristics under true-triaxial unloading conditionsrdquo International Journal of RockMechanics and Mining Sciences vol 47 no 2 pp 286ndash2982010

[12] F Gong J Yan X Li and S Luo ldquoA peak-strength strainenergy storage index for rock burst proneness of rock ma-terialsrdquo International Journal of Rock Mechanics and MiningSciences vol 117 pp 76ndash89 2019

[13] F Du and KWang ldquoUnstable failure of gas-bearing coal-rockcombination bodies insights from physical experiments andnumerical simulationsrdquo Process Safety and EnvironmentalProtection vol 129 pp 264ndash279 2019

[14] S D Butt C Mukherjee and G Lebans ldquoEvaluation ofacoustic attenuation as an indicator of roof stability in ad-vancing headingsrdquo International Journal of Rock Mechanicsand Mining Sciences vol 37 no 7 pp 1123ndash1131 2000

[15] M Cai H Morioka P K Kaiser et al ldquoBack-analysis of rockmass strength parameters using ae monitoring datardquo Inter-national Journal of Rock Mechanics and Mining Sciencesvol 44 no 4 pp 538ndash549 2007

[16] D P Jansen S R Carlson R P Young and D A HutchinsldquoUltrasonic imaging and acoustic emission monitoring ofthermally induced microcracks in Lac du Bonnet graniterdquoJournal of Geophysical Research Solid Earth vol 98 no B12pp 22231ndash22243 1993

[17] U Bismayer ldquoEarly warning signs for mining accidentsdetecting crackling noiserdquo American Mineralogist vol 102no 1 pp 3-4 2017

[18] X Kong E Wang S Li H Lin P Xiao and K ZhangldquoFractals and chaos characteristics of acoustic emission energyabout gas-bearing coal during loaded failurerdquo Fractals vol 27no 5 Article ID 195072 2019

[19] F Du K Wang G Wang Y Jiang C Xin and X ZhangldquoInvestigation of the acoustic emission characteristics duringdeformation and failure of gas-bearing coal-rock combinedbodiesrdquo Journal of Loss Prevention in the Process Industriesvol 55 pp 253ndash266 2018

[20] R P Young D A Hutchins S Talebi et al ldquoLaboratory andfield investigations of rockburst phenomena using concurrentgeotomographic imaging and acoustic emissionmicroseismictechniquesrdquo Seismicity in Mines vol 129 no 3-4pp 647ndash659 1989

[21] X Jansen H Xu M He and F Zhang ldquoExperimental in-vestigation of the occurrence of rockburst in a rock specimenthrough infrared thermography and acoustic emissionrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 93 pp 250ndash259 2017

[22] R E Goodman and E Richard ldquoSubaudible noise duringcompression of rocksrdquo Geological Society of America Bulletinvol 74 no 4 pp 487ndash490 1963

[23] M Cai P K Kaiser H Morioka et al ldquoFLACPFC couplednumerical simulation of AE in large-scale underground

excavationsrdquo International Journal of Rock Mechanics andMining Sciences vol 44 no 4 pp 550ndash564 2007

[24] V Saltas F Vallianatos D Triantis T Koumoudeli andI Stavrakas ldquoNon-extensive statistical analysis of acousticemissions series recorded during the uniaxial compression ofbrittle rocksrdquo Physica A Statistical Mechanics and Its Ap-plications vol 528 Article ID 121498 2019

[25] V Saltas I Fitilis and F Vallianatos ldquoA combined complexelectrical impedance and acoustic emission study in limestonesamples under uniaxial loadingrdquo Tectonophysics vol 637pp 198ndash206 2014

[26] G Qi ldquoWavelet-based AE characterization of compositematerialsrdquo NDTamp E International vol 33 no 3 pp 133ndash1442000

[27] G Manthei J Eisenblatter and T Dahm ldquoMoment tensorevaluation of acoustic emission sources in salt rockrdquo Con-struction and Building Materials vol 15 no 5-6 pp 297ndash3092001

[28] H Jeong and Y-S Jang ldquoWavelet analysis of plate wavepropagation in composite laminatesrdquo Composite Structuresvol 49 no 4 pp 443ndash450 2000

[29] S-H Chang and C-I Lee ldquoEstimation of cracking anddamage mechanisms in rock under triaxial compression bymoment tensor analysis of acoustic emissionrdquo InternationalJournal of Rock Mechanics and Mining Sciences vol 41 no 7pp 1069ndash1086 2004

[30] T Hirata T Satoh and K Ito ldquoFractal structure of spatialdistribution of microfracturing in rockrdquo Geophysical JournalInternational vol 90 no 2 pp 369ndash374 1987

[31] X Lei K Masuda O Nishizawa et al ldquoDetailed analysis ofacoustic emission activity during catastrophic fracture offaults in rockrdquo Journal of Structural Geology vol 26 no 2pp 247ndash258 2004

[32] J Jouniaux J Pei J Liu et al ldquoInvestigation on acousticemission behavior and its time-space evolution mechanism infailure process of coalndashrock combined bodyrdquo Chinese Journalof Rock Mechanics and Engineering vol 30 pp 1564ndash15702011

[33] E Townend B D ompson P M Benson PG MeredithP Baud and R P Young ldquoImaging compaction bandpropagation in Diemelstadt sandstone using acoustic emis-sion locationsrdquo Geophysical Research Letters vol 35 no 15pp 189ndash193 2008

[34] M Naderloo M Moosavi and M Ahmadi ldquoUsing acousticemission technique tomonitor damage progress around jointsin brittle materialsrdquo Deoretical and Applied Fracture Me-chanics vol 104 Article ID 102368 2019

[35] GBT Unified Number of Natural Stone China StandardsPress Beijing China 2009

[36] G Shen Acoustic Emission Detection Technology and Appli-cation Science Press Beijing China 2015

[37] Y Guo Research on Wavelet Base Selection for VibrationSignal Processing Hefei University of Technology HefeiChina 2003

[38] F Xu E Wang and D Song ldquoLong-range correlation andmultifractal distribution of acoustic emission of coal-rockrdquoRock and Soil Mechanics vol 32 no 7 pp 2111ndash2116 2011

Advances in Civil Engineering 19

It can be seen from Figure 5 that the amplitude of thelarge-scale plane plate rock showed similar exponentialattenuation characteristics with the increase of the propa-gation distance e AE wave attenuation of granite wasstronger than that of marble in the direction of 0deg and wasweaker than that of marble in the directions of 90deg and 45deg

Specifically due to the diversity and anisotropy of rockcomponents the attenuation of the AE wave in the range of20ndash80 cm in the direction of 0deg showed the fluctuation ofamplitude between 72 and 83 dB in both kinds of rockthough the overall trend was declining e amplitudecharacteristic parameters extracted from each measuring

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash5

ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

G3768

Amplitude

Energy

Distance (cm)

20 50 70 100 135

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

G3561

Amplitude

Energy

Distance (cm)

20 50 70 100 135

ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

TBG

Amplitude

Energy

Distance (cm)

20 50 70 100 135ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

AAM

Amplitude

Energy

Distance (cm)

20 50 70 100ndash4

ndash3

ndash2

ndash1

0

Relat

ive d

ecay

rate

(dB)

GAM

(b)

Figure 4 e attenuation rates of energyamplitude with distance (a) End-pulse excitation (S-wave) (b) Terminal pulse excitation (P-wave)

Advances in Civil Engineering 7

point arranged in the front and back of the marble in the 45degdirection and 90deg direction presented significant changes Asudden decrease of amplitude appeared at 30ndash40 cm with adecrease of 1965 dB in the 45deg direction and 2455 dB in the90deg directione amplitude attenuation of granite tended tobe stable

e attenuation curves of the AE energy in differentdirections for G3761-L and GAM-L are shown in Figure 6 Itcan be seen that the energy in the marble changes violentlyand the energy value in the range of 45ndash55 cm in the di-rection of 0deg exhibits the abnormal phenomenon of stepeenergy attenuation was lower than that of the granite stonewhich shows the same trend with the amplitude attenuatione energy value of granite from 45 cm back to the end of thethin plate is almost maintained at 20ndash50mVms and tends tobe stable In the 45deg direction the marble exhibited theenhancement of energy value after 55 cm It is the reflectionof the AE wave along the 45deg direction when it met theboundary and the wave enhancement phenomenon wasformed by the superposition of multiple reflections andrefractions e marble and granite showed the same trendin the 90deg direction

32 Waveform Analysis of Acoustic Emission Signal

321 Time Domain Waveform and Spectrum Analysis ofAcoustic Emission Original Signal According to a largenumber of AE signal waveforms obtained by pulse excitationon the surface of each group of samples the AE signalwaveforms of rod-shaped and plate-shaped rocks were se-lected from the closest measuring point to the pulse sourcee middle measuring point in their respective directionsand the end measuring points were analyzed e specificlayout of measuring points is presented in Table 4

Since the original statistics of the nonstationary AEsignal is a time-varying function FFT transform was used toanalyze the spectral characteristics of the time-domain signalto better understand the variation law of elastic wave in thepropagation process Figure 7 presents the original signaltime-domain waveforms of measuring point M2 of eachgroup of rod-shaped rocks and the corresponding frequencyspectrum is shown in Figure 8 e related curves of the AE

signal excited from measuring points M2 on the surface ofthe plate-shaped rocks in the three directions of 0deg 90deg and45deg are shown in Figure 9

It can be seen from the time-domain diagram that thewaveforms of the AE signal generated by pulse excitationwere very similar and the duration was short For the rod-shaped rocks the durations for granites G3768 G3561 andTBG were in the range of 025ndash15ms where the waveformsdecayed quickly and the coda waves were not developede durations for AAM and GAM were in the range of05ndash20ms and 05ndash10ms respectively For the plate-shapedrocks the duration of G3761-L was 05ndash15ms in the 0degdirectione duration for GAM-L was 025ndash15ms and theamplitude attenuation variation was small Similarly in the45deg direction and 90deg direction the G3761-l granite showed ashorter duration of time than the GAM-L marble dem-onstrating that the homogeneity of the natural granite plate-shaped rock is better

It can be seen from the spectrum that the frequency ofthe AE signal generated by pulse excitation was relativelyhigh and the frequency band was relatively narrow emain frequency domain of each group of rod-shaped rockswas 0ndash250 kHz and the frequency domain of the AE signalat the M2 position measuring point in each direction of theplate-shaped rocks was 0ndash300 kHz In this frequency do-main each group of samples with different lithologies showsmultiple peaks of frequency indicating that the waveform ofthe AE signal is very complex and is a mixture of waves withdifferent characteristics

322 Wavelet Packet Energy Analysis of Acoustic EmissionSignal According to previous research wavelet transformonly decomposes the low-frequency partndashbut not the high-frequency part of the original signal e time-frequencylocalization could be better analyzed through the intro-duction of wavelet packet transform in which the high-frequency part of the signal could be further decomposed Asshown in Table 4 considering that wavelet packet analysishas the advantages of multilayer decomposition of signaldetails and scale information the following wavelet packetenergy feature extraction was conducted for the AE signal

0 20 40 60 80 100 12060

65

70

75

80

85

90

95

100A

mpl

itude

(dB)

G3761-L

GAM-L

0deg

Distance (cm)

G3761-L

GAM-L

0 10 20 30 40 50 6050

60

70

80

90

100

45deg

Distance (cm)

Am

plitu

de (d

B)

G3761-L

GAM-L

0 10 20 30 40 5050

60

70

80

90

100

90deg

Distance (cm)

Am

plitu

de (d

B)

Figure 5 e attenuation curves of the amplitude in different directions for G3761-L and GAM-L

8 Advances in Civil Engineering

waveform obtained at different measuring points in eachgroup of rock samples to explore the local feature infor-mation of the AE signal waveform at different positions ofrod-shaped and plate-shaped rocks

Choosing a suitable wavelet base plays an important rolein signal processing and analysis Guo [37] introduced theeffect of different wavelet bases in vibration signal processingin detail which presents that the db5 db7 db10 db13 db16bior26 bior39 coif4 sym7 and sym8 wavelet bases aremore suitable for the shock feature extraction of vibrationsignals Of this wavelet set db7 was selected as the waveletbase for the wavelet packet analysis because of its Daubechiesseries wavelet set characteristics such as high-order van-ishing moment tight support regularity approximatesymmetry and orthogonalityndashand because of the similaritiesit shares with the rock AE signal Its wavelet function ispresented in Figure 10

e sampling frequency is 3MHz According to thesampling theorem its Nyquist frequency is 1500 kHz ewavelet packet decomposition principle and algorithm wereapplied to decompose the signal to the 7th layer (ie thescale is 7) which has 27 wavelet packets in total ereforein the frequency domain the original signal was decom-posed into 128 subbands e width of each band was1172 kHz e frequency band range of each layer recon-structed after the decomposition of the original signal ispresented in Table 5

As can be seen from the table the original signal isexpressed as

S S70 + S71 + S72 + middot middot middot + S7127 (4)

where S70 is the low-frequency part of the decomposedsignal the other variables represent the decomposition of the

high-frequency part of the signal Assuming that the cor-responding energy of S7j(j 0 1 2 middot middot middot 127) isE7j(j 0 1 2 middot middot middot 127) then the energy characterization ofthe original AE signal decomposition in each frequencyband range can be obtained by formula (1)

Assuming that the total energy of the analyzed signal isE0 then

E0 1113944127

j0E7j (5)

e ratio of the energy of each frequency band to thetotal energy of the analyzed signal is

Ej E7j

E0times 100 (6)

In the formula j 012 27ndash1From Equation (1) the energy changes of the corre-

sponding AE signals in different frequency bands after theoriginal signal decomposition were calculated so the energydistribution characteristics of the elastic wave in differentfrequency bands could be found [38] According to Table 4the main frequency range of the AE signal waveform of eachmeasuring point was 0ndash300 kHz indicating that the energyvalue must also be concentrated in this frequency rangeerefore with MATLAB programming the energy dis-tribution of each subband in the frequency domain of0ndash500 kHz was obtained as shown in Figures 11 and 12

For rod-shaped rocks G3768 G3561 and TBG of thesame lithology from different places of origin the M1measuring point was closest to the pulse excitation sourceerefore the value of the M1 measuring point could ef-fectively reflect the energy value of the real pulse As can be

G3761-L

GAM-L

0deg

0 20 40 60 80 100 120

0

100

200

300

400

500

600

Distance (cm)

Ener

gy (m

Vlowast

ms)

G3761-L

GAM-L

45deg

Distance (cm)

Ener

gy (m

Vlowast

ms)

0 10 20 30 40 50 600

100

200

300

400

500

600

700

G3761-L

GAM-L

90deg

Distance (cm)

Ener

gy (m

Vlowast

ms)

0 10 20 30 40 50

100

200

300

400

500

600

700

Figure 6 e attenuation curves of the AE Energy in different directions for G3761-L and GAM-L

Table 4 e measuring point positions of AE waveforms

Rock number (measuring point) (cm) G3768 G3561 TBG AAM GAMG3761-L GAM-L

0deg 90deg 45deg 0deg 90deg 45deg

M1 5 5 5 5 5 5 5 5 5 5 5M2 70 70 70 70 50 55 20 30 40 25 30M3 135 135 135 135 100 100 35 50 75 40 50

Advances in Civil Engineering 9

seen from Figure 11 the energy is widely distributed in thefrequency domain e value of energy is generally smallwhich was mainly concentrated in the range of0ndash36428 kHz Combined with Formulas (5) and (6) it couldbe calculated that the main dominant energy of the three

groups of granite was concentrated in the frequency band of7131ndash12991 kHz which correspondingly accounted for646 5605 and 5828 of the total energy About2326 of the energy in G3561 was concentrated in thefrequency band of 23538ndash35256 kHz which is different

0 05 10 15 20 25ndash15

ndash10

ndash05

0

05

10

Am

plitu

de (m

V)

Time (ms)

G3768

TBG

0 05 10 15 20 25 3ndash08

ndash06

ndash04

ndash02

0

02

04

06

08

Am

plitu

de (m

V)

Time (ms)

G3561

0 05 10 15 20 25

ndash15

ndash10

ndash05

0

05

10

15

Time (ms)

Am

plitu

de (m

V)

AAM

0 05 10 15 2ndash20

ndash15

ndash10

ndash05

0

05

10

15

Time (ms)

Am

plitu

de (m

V)

GAM

0 05 10 15 20 25 30 35ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

Figure 7 Time domain waveform of measuring point M2 of rod-shaped rock

10 Advances in Civil Engineering

from other samples of the same lithology With the increaseof the propagation distance of the elastic wave its energyexhibited the characteristics of rapid attenuation edominant energy distribution frequency bands of the threerod-shaped rock materials at the M2 measuring point ex-panded from the initial 7131ndash12991 kHz to 0ndash17678 kHz

and the energy percentages were 8987 9407 and8658 respectively In the high-frequency band of28225ndash31741 kHz there was respectively 10 and 1269energy concentration for G3768 and TBG When the elasticwave propagated to the end of the rod (M3) the energy ofeach group of samples was relatively concentrated and

0 100 200 300 400 5000

001

002

003

004

Am

plitu

de (m

V)

Frequency (KHz)

G3768

TBG

0 100 200 300 400 5000

001

002

003

Am

plitu

de (m

V)

Frequency (KHz)

G3561

0 100 200 300 400 5000

001

002

003

004

005

006

007

Frequency (KHz)

Am

plitu

de (m

V)

AAM

0 100 200 300 400 5000

001

002

003

004

005

006

Frequency (KHz)

Am

plitu

de (m

V)

GAM

0 100 200 300 400 5000

0002

0004

0006

0008

0010

0012

Am

plitu

de (m

V)

Frequency (KHz)

Figure 8 e spectrogram of measuring point M2 of rod-shaped rock

Advances in Civil Engineering 11

G3761-L(90deg)

0 05 10 15 2ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

G3761-L(90deg)

0 100 200 300 400 500000

002

004

006

008

010

Am

plitu

de (m

V)

Frequency (KHz)

G3761-L(45deg)

0 05 10 15 20 25

ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

G3761-L(45deg)

0 100 200 300 400 5000

001

002

003

004

005

006

007

Am

plitu

de (m

V)

Frequency (KHz)

0 05 10 15 20 25 3ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

G3761-L(0deg)

Am

plitu

de (m

V)

Time (ms)

G3761-L(0deg)

0 100 200 300 400 5000

0002

0004

0006

0008

0010

Am

plitu

de (m

V)

Frequency (KHz)

(a)

Figure 9 Continued

12 Advances in Civil Engineering

mainly distributed within 0ndash10647 kHz at the percentages of9211 9022 and 9188 respectively By comparing thethree groups of rod-shaped rocks with the same lithology itcan be seen that the energy attenuation was the fastest inTBG and the dominant energy value was the lowest at theM3 measuring point For G3768 the energy attenuation wasthe slowest Only the distribution rule of the dominant

energy value at the M2 and M3 measuring points changedwhereas the maximum energy value hardly changed ereason may be that the internal structure or componentdensity of G3768 was better and the energy was relativelymaintained rather than rapidly attenuated with the elasticwave propagation For AAM artificial marble its maindominant energy also exhibited the same change trend as

GAM-L(45deg)

0 05 10 15 20 25

ndash3

ndash2

ndash1

0

1

2

3

4

Am

plitu

de (m

V)

Time (ms)

GAM-L(45deg)

0 100 200 300 400 5000

002

004

006

008

010

012

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(0deg)

0 05 10 15 20 25 30 35

ndash09

ndash06

ndash03

0

03

06

09

Am

plitu

de (m

V)

Time (ms)

GAM-L(0deg)

0 100 200 300 400 5000

0005

0010

0015

0020

0025

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(90deg)

0 05 10 15 20 25ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

GAM-L(90deg)

Am

plitu

de (m

V)

0 100 200 300 400 500000

002

004

006

008

010

Frequency (KHz)

(b)

Figure 9 e time waveform and spectrogram of measuring point M2 of pate-shaped rock

Advances in Civil Engineering 13

0 3 6 9 12 15ndash15

ndash10

ndash05

00

05

10

Wavelet function

0 3 6 9 12 15

ndash05

00

05

10

Scaling function

Figure 10 Wavelet function and scaling function for db7

Table 5 e frequency band range of reconstructed signal by wavelet packet decomposition

Layer S (i 0) S (i 1) S (i 2) S (i jminus 1) S (i j)1 0ndash750 ndash ndash ndash ndash 750ndash15002 0ndash375 375ndash750 750ndash1125 ndash ndash 1125ndash15003 0ndash1875 1875ndash375 375ndash5625 1125ndash13125 13125ndash15004 0ndash9375 9375ndash1875 1875ndash28125 13125ndash140625 140625ndash15005 0ndash46875 46875ndash9375 9375ndash140625 140625ndash1453125 1453125ndash15006 0ndash234375 234375ndash46875 46875ndash703125 1453125ndash14765625 14765625ndash15007 0ndash1171875 1171875ndash234375 234375ndash3515625 14765625ndash148828125 148828125ndash1500S (i j) represents the reconstruction signal of the j-th wavelet packet decomposition coefficient in the i-th layer i 1234 j 012 2i-1

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M3

(a)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500

1000

1500

2000

2500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

20

40

60

80

100

120

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

M3

(b)

Figure 11 Continued

14 Advances in Civil Engineering

granite From Figure 11 it can be observed that the energy ofthe original pulse signal is concentrated in the range of9475ndash16506 kHz and 2185 of the energy existed in thefrequency band of 28225ndash35256 kHz For GAMmarble themain dominant energy distribution of the initial signal wasvery wide and was distributed in the frequency band of0ndash36428 kHz Among them the dominant energy wasdistributed within the 10647ndash12991 kHz range accountingfor 3213 of the total energy Similar attenuation charac-teristics as granite were presented with the increase of elasticwave propagation distance In general for GAM the exci-tation energy of the AE signal generated by pulse excitationwas the weakest and the attenuation was the fastest with theincrease of distancee initial excitation energy of the threegroups of granite was partially concentrated in the frequency

band of 23538ndash35256 kHz of which the performance ofG3561 was the most obvious

e pulse AE signal was very complex for 2 groups of theplate-shaped rocks (Figure 12) erefore the initial energyof the M1 measuring point in each direction was also quitedifferent In the direction of 0deg the dominant energy of theoriginal pulse signal in G3761-L was concentrated in thefrequency band of 0ndash17678 kHz which accounted for8904 of the total energy Meanwhile about 628 of theenergy was distributed in the frequency band of29397ndash32913 kHz e same law was also shown in GAM-L but the main dominant frequency in GAM-L was rela-tively concentrated in the short frequency band of10647ndash17678 kHz which accounted for 6357 of the totalenergy With the spread of the elastic wave the energy in

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50002468

10121416

M3

(c)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5001000150020002500300035004000

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40

50

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M3

(d)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

100

200

300

400

500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M2

0 100 200 300 400 5000

2

4

6

8En

ergy

(mVlowast

mS)

Frequency (KHZ)

M3

0 100 200 300 400 500012345678

(e)

Figure 11e energy distribution of acoustic emission signal frequency band of rod-shaped rock (a) G3768 (b) G3561 (c) TBG (d) AAM(e) GAM

Advances in Civil Engineering 15

0 100 200 300 400 5000

200400600800

100012001400

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

M2

0 100 200 300 400 5000005101520253035

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

M3

0 100 200 300 400 50000020406081012

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

(a)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40En

ergy

(mVlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 5000

2

4

6

8

Ener

gy (m

Vlowast

mS)

(b)

M1

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

1020304050607080

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50002468

1012141618

Ener

gy (m

Vlowast

mS)

(c)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700800

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 50005

101520253035

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

Ener

gy (m

Vlowast

mS)

(d)

Figure 12 Continued

16 Advances in Civil Engineering

G3761-L showed a trend of attenuation and the energy intheM2measuring point was still distributed in the frequencyband of 0ndash17678 kHz e energy distribution at the M3measuring point was relatively concentrated and was locatedin the frequency band of 0ndash10647 kHz accounting for8340 of the total energy e energy at the measuringpoint M3 of GAM-L was more extensive in the frequencydomain and the energy value changed dramatically dem-onstrating the abnormal phenomenon that the maindominant energy increased e frequency range of thismeasuring point was 0ndash1885 kHz accounting for 8589 ofthe total energyere was also residual energy concentratedin the frequency band of 29397ndash32913 kHz e AE signalat M3 was superposed by the boundary reflection wave andthe energy was enhanced because of the high homogeneityand good ductility of GAM-L For G3761-L the dominantenergy of the elastic wave almost dissipated at the M3measuring point In the direction of 45deg the dominantenergy band of the original signal in G3761-L was distributedwithin 0ndash17678 kHz and 28225ndash35256 kHz respectivelyaccounting for 6415 and 3278 of the total energyMoreover it can be observed that the distribution of thedominant energy band was from distribution to concen-tration which was distributed in the frequency band of7131ndash17678 kHz at M2 With the increase of distance theenergy frequency band of the M3 measuring point near theedge of the plate was spread again and it was restored to theenergy frequency band range of the initial signal Howeverthe energy value was attenuated to a very small value at this

moment e energies of GAM-L in the measuring pointsM1 M2 and M3 were all distributed in the frequency bandof 0ndash36428 kHz In the direction of 90deg the primarydominant energy frequency bands of the two plate-shapedrocks were concentrated in 9475ndash1885 kHz e differenceis that the energy distribution of GAM-L was still con-centrated and the energy variation was much smaller thanG3761-L at the M2 measuring point In general the energyfrequency band of the two plate-shaped rocks with differentlithologies was the same as that of the rod-shape rock whichis mainly distributed in the range of 0ndash36428 kHz More-over they also exhibited the characteristics that the maindominant energy was distributed in the range of0ndash17678 kHz and the residual energy was distributed in therange of 28225ndash35256 kHz

4 Discussion

e purpose of this work was to study the propagationcharacteristics of elastic wave in lithological rock materialsrough the above research and analysis a preliminaryunderstanding was obtained Based on the deep waveletpacket analysis of amplitude energy characteristic param-eters and AE waveform the frequency band characteristicsof the local energy distribution of elastic wave with itspropagation were summarized However its propagationcharacteristics are difficult to be regularly grasped becausethe elastic wave itself is extremely complex Furthermore AEtechnology is mostly used in the damage detection and

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

20406080

100120140160

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

10

20

30

40

50

(e)

M1

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

200400600800

10001200140016001800

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

50

100

150

200

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 50005

101520253035

(f )

Figure 12e energy distribution of acoustic emission signal frequency band of plate-shaped rock (a) G3761-L (00) (b) G3761-L (450) (c)G3761-L (900) (d) GAM-L (00) (e) GAM-L (450) (f ) GAM-L (900)

Advances in Civil Engineering 17

defect location of metal or related materials with goodcompactness ductility and within the same medium ereare many uncertain interference factors in the experimentsIn some aspects the analysis of this paper only stays at thelevel of the apparent phenomenon and there are still manydeficiencies and areas worthy of improvement For instancethe density wave velocity and wave impedance of the rod-shaped rock samples should be tested and the micro-structure imaging experiments of the rock samples should beconducted e quality factor Q of different rock samplesshould be calculated Moreover the correlation between thequality factor and wave impedance should be studied andthe influence of different microcompositions of rod-shapedrocks on elastic wave attenuation should be deeply analyzedBased on the modal AE theory the influence of Lamb wavein plate-shaped rocks should be studied and the propagationmodel of two-dimensional AE should be constructed eGabor wavelet should be introduced to analyze the AE signalby time-frequency analysis e influence of differentwavelets based on the propagation effect of AE will becompared and analyzed and the time of the same mode ofthe AE wave arriving at the sensor will be determined tofurther optimize the plane location algorithm However theresearch in this work is still useful for studying large-scalerock samples in the future and provides effective researchmethods and ideas for the study of elastic wave propagationcharacteristics of different rock materials and compositematerials

5 Conclusions

In this work the characteristic parameter analysis andwaveform analysis of the AE signals obtained from differentexperimental schemes in 5 groups of rod-shaped rocks and 2groups of plate-shaped rocks were carried out e con-clusions are as follows

(1) e amplitude and energy of the rod-shaped rocksgradually attenuated with the increase of distancee amplitude can directly reflect the intensity of theAE counts at different measuring areas In theprocess of elastic wave propagation of the rod-sha-ped rock the P-wave preceded the S-wave andchanged violently e elastic wave of marble at-tenuated faster and the elastic wave of the threekinds of granite decayed attenuated closely Amongthem the elastic wave of TBG exhibited the fastestattenuation

(2) In flat plate-shaped rocks the amplitude exhibited anapproximate exponential attenuation characteristicwith the increase of the propagation distanceGranite exhibited a stronger elastic wave attenuationin the 0deg direction than the marble and the marblepresented fast attenuations in the 45deg and 90deg di-rections e energy change of marble was dramaticand the energy value in the interval of 45ndash55 cm atthe direction of 0deg showed the abnormal step phe-nomenon e energy value of the marble increasedafter 55 cm in the 45deg direction e energy value of

granite from the back to the end of the plate wasalmost maintained and tended to be stable at20ndash50mVms

(3) e frequency range of the energy distribution ofsamples in this work was within 0ndash36428 kHz Withthe increase of distance the main dominant energydistribution of the 5 groups of rod-shaped rocks inthe frequency range was characterized by distribu-tion to relative concentration and rapid energy at-tenuationemain dominant energy distribution ofthe 2 groups of plate-shaped rocks was distributed inthe range of 0ndash17678 kHz All rod-shaped rocks andplate-shaped rocks exhibited the characteristics ofresidual energy distribution in the frequency band of28225ndash35256 kHz

Data Availability

e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

e authors certify that they have no conflicts of interest

Acknowledgments

is research was funded by the National Natural ScienceFoundation of China (51804161 52074156 and 52004291)the Chinese Postdoctoral Science Foundation(2019M660861) and the State Key Laboratory CultivationBase for Gas Geology and Gas Control (Henan PolytechnicUniversity) (WS2020A04)

References

[1] J T Chen J H Zhao S C Zhang Y Zhang F Yang andM Li ldquoAn experimental and analytical research on theevolution of mining cracks in deep floor rock massrdquo Pure andApplied Geophysics vol 177 no 11 pp 5325ndash5348 2020

[2] K Wang and F Du ldquoCoal-gas compound dynamic disastersin China a reviewrdquo Process Safety and Environmental Pro-tection vol 133 pp 1ndash17 2020

[3] C Zhu M He M Karakus X Cui and Z Tao ldquoInvestigatingtoppling failure mechanism of anti-dip layered slope due toexcavation by physical modellingrdquo Rock Mechanics and RockEngineering vol 53 no 11 pp 5029ndash5050 2020

[4] X Wang C Liu S Chen L Chen K Li and N Liu ldquoImpactof coal sectorrsquos de-capacity policy on coal pricerdquo AppliedEnergy vol 265 Article ID 114802 2020

[5] D Liu Z Gu R Liang et al ldquoImpacts of pore-throat systemon fractal characterization of tight sandstonesrdquo Geofluidsvol 2020 no 9 17 pages Article ID 4941501 2020

[6] J Wang Y Zhang Z Qin S Song and P Lin ldquoAnalysismethod of water inrush for tunnels with damaged water-resisting rock mass based on finite element method-smoothparticle hydrodynamics couplingrdquo Computers and Geo-technics vol 126 Article ID 103725 2020

[7] B Chen S C Zhang Y Y Li Z K Li and H J ZhouldquoPhysical simulation study of crack propagation and insta-bility information discrimination of rock-like materials withfaultsrdquo Arabian Journal of Geosciences vol 13 p 966 2020

18 Advances in Civil Engineering

[8] F Du K Wang X Zhang C Xin and G Wang ldquoExperi-mental study of coal-gas outburst insights from coal-rockstructure gas pressure and adsorptivityrdquo Natural ResourcesResearch vol 29 no 4 pp 2481ndash2493 2020

[9] H Y Wang J Ma G D Wang et al ldquoResearch on AE sourcelocation of linear and plane rock massrdquo Shock and Vibrationvol 2020 Article ID 8846582 18 pages 2020

[10] V A Mansurov ldquoPrediction of rockbursts by analysis ofinduced seismicity datardquo International Journal of Rock Me-chanics and Mining Sciences vol 38 no 6 pp 893ndash901 2001

[11] M C He J L Miao and J L Feng ldquoRock burst process oflimestone and its acoustic emission characteristics under true-triaxial unloading conditionsrdquo International Journal of RockMechanics and Mining Sciences vol 47 no 2 pp 286ndash2982010

[12] F Gong J Yan X Li and S Luo ldquoA peak-strength strainenergy storage index for rock burst proneness of rock ma-terialsrdquo International Journal of Rock Mechanics and MiningSciences vol 117 pp 76ndash89 2019

[13] F Du and KWang ldquoUnstable failure of gas-bearing coal-rockcombination bodies insights from physical experiments andnumerical simulationsrdquo Process Safety and EnvironmentalProtection vol 129 pp 264ndash279 2019

[14] S D Butt C Mukherjee and G Lebans ldquoEvaluation ofacoustic attenuation as an indicator of roof stability in ad-vancing headingsrdquo International Journal of Rock Mechanicsand Mining Sciences vol 37 no 7 pp 1123ndash1131 2000

[15] M Cai H Morioka P K Kaiser et al ldquoBack-analysis of rockmass strength parameters using ae monitoring datardquo Inter-national Journal of Rock Mechanics and Mining Sciencesvol 44 no 4 pp 538ndash549 2007

[16] D P Jansen S R Carlson R P Young and D A HutchinsldquoUltrasonic imaging and acoustic emission monitoring ofthermally induced microcracks in Lac du Bonnet graniterdquoJournal of Geophysical Research Solid Earth vol 98 no B12pp 22231ndash22243 1993

[17] U Bismayer ldquoEarly warning signs for mining accidentsdetecting crackling noiserdquo American Mineralogist vol 102no 1 pp 3-4 2017

[18] X Kong E Wang S Li H Lin P Xiao and K ZhangldquoFractals and chaos characteristics of acoustic emission energyabout gas-bearing coal during loaded failurerdquo Fractals vol 27no 5 Article ID 195072 2019

[19] F Du K Wang G Wang Y Jiang C Xin and X ZhangldquoInvestigation of the acoustic emission characteristics duringdeformation and failure of gas-bearing coal-rock combinedbodiesrdquo Journal of Loss Prevention in the Process Industriesvol 55 pp 253ndash266 2018

[20] R P Young D A Hutchins S Talebi et al ldquoLaboratory andfield investigations of rockburst phenomena using concurrentgeotomographic imaging and acoustic emissionmicroseismictechniquesrdquo Seismicity in Mines vol 129 no 3-4pp 647ndash659 1989

[21] X Jansen H Xu M He and F Zhang ldquoExperimental in-vestigation of the occurrence of rockburst in a rock specimenthrough infrared thermography and acoustic emissionrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 93 pp 250ndash259 2017

[22] R E Goodman and E Richard ldquoSubaudible noise duringcompression of rocksrdquo Geological Society of America Bulletinvol 74 no 4 pp 487ndash490 1963

[23] M Cai P K Kaiser H Morioka et al ldquoFLACPFC couplednumerical simulation of AE in large-scale underground

excavationsrdquo International Journal of Rock Mechanics andMining Sciences vol 44 no 4 pp 550ndash564 2007

[24] V Saltas F Vallianatos D Triantis T Koumoudeli andI Stavrakas ldquoNon-extensive statistical analysis of acousticemissions series recorded during the uniaxial compression ofbrittle rocksrdquo Physica A Statistical Mechanics and Its Ap-plications vol 528 Article ID 121498 2019

[25] V Saltas I Fitilis and F Vallianatos ldquoA combined complexelectrical impedance and acoustic emission study in limestonesamples under uniaxial loadingrdquo Tectonophysics vol 637pp 198ndash206 2014

[26] G Qi ldquoWavelet-based AE characterization of compositematerialsrdquo NDTamp E International vol 33 no 3 pp 133ndash1442000

[27] G Manthei J Eisenblatter and T Dahm ldquoMoment tensorevaluation of acoustic emission sources in salt rockrdquo Con-struction and Building Materials vol 15 no 5-6 pp 297ndash3092001

[28] H Jeong and Y-S Jang ldquoWavelet analysis of plate wavepropagation in composite laminatesrdquo Composite Structuresvol 49 no 4 pp 443ndash450 2000

[29] S-H Chang and C-I Lee ldquoEstimation of cracking anddamage mechanisms in rock under triaxial compression bymoment tensor analysis of acoustic emissionrdquo InternationalJournal of Rock Mechanics and Mining Sciences vol 41 no 7pp 1069ndash1086 2004

[30] T Hirata T Satoh and K Ito ldquoFractal structure of spatialdistribution of microfracturing in rockrdquo Geophysical JournalInternational vol 90 no 2 pp 369ndash374 1987

[31] X Lei K Masuda O Nishizawa et al ldquoDetailed analysis ofacoustic emission activity during catastrophic fracture offaults in rockrdquo Journal of Structural Geology vol 26 no 2pp 247ndash258 2004

[32] J Jouniaux J Pei J Liu et al ldquoInvestigation on acousticemission behavior and its time-space evolution mechanism infailure process of coalndashrock combined bodyrdquo Chinese Journalof Rock Mechanics and Engineering vol 30 pp 1564ndash15702011

[33] E Townend B D ompson P M Benson PG MeredithP Baud and R P Young ldquoImaging compaction bandpropagation in Diemelstadt sandstone using acoustic emis-sion locationsrdquo Geophysical Research Letters vol 35 no 15pp 189ndash193 2008

[34] M Naderloo M Moosavi and M Ahmadi ldquoUsing acousticemission technique tomonitor damage progress around jointsin brittle materialsrdquo Deoretical and Applied Fracture Me-chanics vol 104 Article ID 102368 2019

[35] GBT Unified Number of Natural Stone China StandardsPress Beijing China 2009

[36] G Shen Acoustic Emission Detection Technology and Appli-cation Science Press Beijing China 2015

[37] Y Guo Research on Wavelet Base Selection for VibrationSignal Processing Hefei University of Technology HefeiChina 2003

[38] F Xu E Wang and D Song ldquoLong-range correlation andmultifractal distribution of acoustic emission of coal-rockrdquoRock and Soil Mechanics vol 32 no 7 pp 2111ndash2116 2011

Advances in Civil Engineering 19

point arranged in the front and back of the marble in the 45degdirection and 90deg direction presented significant changes Asudden decrease of amplitude appeared at 30ndash40 cm with adecrease of 1965 dB in the 45deg direction and 2455 dB in the90deg directione amplitude attenuation of granite tended tobe stable

e attenuation curves of the AE energy in differentdirections for G3761-L and GAM-L are shown in Figure 6 Itcan be seen that the energy in the marble changes violentlyand the energy value in the range of 45ndash55 cm in the di-rection of 0deg exhibits the abnormal phenomenon of stepeenergy attenuation was lower than that of the granite stonewhich shows the same trend with the amplitude attenuatione energy value of granite from 45 cm back to the end of thethin plate is almost maintained at 20ndash50mVms and tends tobe stable In the 45deg direction the marble exhibited theenhancement of energy value after 55 cm It is the reflectionof the AE wave along the 45deg direction when it met theboundary and the wave enhancement phenomenon wasformed by the superposition of multiple reflections andrefractions e marble and granite showed the same trendin the 90deg direction

32 Waveform Analysis of Acoustic Emission Signal

321 Time Domain Waveform and Spectrum Analysis ofAcoustic Emission Original Signal According to a largenumber of AE signal waveforms obtained by pulse excitationon the surface of each group of samples the AE signalwaveforms of rod-shaped and plate-shaped rocks were se-lected from the closest measuring point to the pulse sourcee middle measuring point in their respective directionsand the end measuring points were analyzed e specificlayout of measuring points is presented in Table 4

Since the original statistics of the nonstationary AEsignal is a time-varying function FFT transform was used toanalyze the spectral characteristics of the time-domain signalto better understand the variation law of elastic wave in thepropagation process Figure 7 presents the original signaltime-domain waveforms of measuring point M2 of eachgroup of rod-shaped rocks and the corresponding frequencyspectrum is shown in Figure 8 e related curves of the AE

signal excited from measuring points M2 on the surface ofthe plate-shaped rocks in the three directions of 0deg 90deg and45deg are shown in Figure 9

It can be seen from the time-domain diagram that thewaveforms of the AE signal generated by pulse excitationwere very similar and the duration was short For the rod-shaped rocks the durations for granites G3768 G3561 andTBG were in the range of 025ndash15ms where the waveformsdecayed quickly and the coda waves were not developede durations for AAM and GAM were in the range of05ndash20ms and 05ndash10ms respectively For the plate-shapedrocks the duration of G3761-L was 05ndash15ms in the 0degdirectione duration for GAM-L was 025ndash15ms and theamplitude attenuation variation was small Similarly in the45deg direction and 90deg direction the G3761-l granite showed ashorter duration of time than the GAM-L marble dem-onstrating that the homogeneity of the natural granite plate-shaped rock is better

It can be seen from the spectrum that the frequency ofthe AE signal generated by pulse excitation was relativelyhigh and the frequency band was relatively narrow emain frequency domain of each group of rod-shaped rockswas 0ndash250 kHz and the frequency domain of the AE signalat the M2 position measuring point in each direction of theplate-shaped rocks was 0ndash300 kHz In this frequency do-main each group of samples with different lithologies showsmultiple peaks of frequency indicating that the waveform ofthe AE signal is very complex and is a mixture of waves withdifferent characteristics

322 Wavelet Packet Energy Analysis of Acoustic EmissionSignal According to previous research wavelet transformonly decomposes the low-frequency partndashbut not the high-frequency part of the original signal e time-frequencylocalization could be better analyzed through the intro-duction of wavelet packet transform in which the high-frequency part of the signal could be further decomposed Asshown in Table 4 considering that wavelet packet analysishas the advantages of multilayer decomposition of signaldetails and scale information the following wavelet packetenergy feature extraction was conducted for the AE signal

0 20 40 60 80 100 12060

65

70

75

80

85

90

95

100A

mpl

itude

(dB)

G3761-L

GAM-L

0deg

Distance (cm)

G3761-L

GAM-L

0 10 20 30 40 50 6050

60

70

80

90

100

45deg

Distance (cm)

Am

plitu

de (d

B)

G3761-L

GAM-L

0 10 20 30 40 5050

60

70

80

90

100

90deg

Distance (cm)

Am

plitu

de (d

B)

Figure 5 e attenuation curves of the amplitude in different directions for G3761-L and GAM-L

8 Advances in Civil Engineering

waveform obtained at different measuring points in eachgroup of rock samples to explore the local feature infor-mation of the AE signal waveform at different positions ofrod-shaped and plate-shaped rocks

Choosing a suitable wavelet base plays an important rolein signal processing and analysis Guo [37] introduced theeffect of different wavelet bases in vibration signal processingin detail which presents that the db5 db7 db10 db13 db16bior26 bior39 coif4 sym7 and sym8 wavelet bases aremore suitable for the shock feature extraction of vibrationsignals Of this wavelet set db7 was selected as the waveletbase for the wavelet packet analysis because of its Daubechiesseries wavelet set characteristics such as high-order van-ishing moment tight support regularity approximatesymmetry and orthogonalityndashand because of the similaritiesit shares with the rock AE signal Its wavelet function ispresented in Figure 10

e sampling frequency is 3MHz According to thesampling theorem its Nyquist frequency is 1500 kHz ewavelet packet decomposition principle and algorithm wereapplied to decompose the signal to the 7th layer (ie thescale is 7) which has 27 wavelet packets in total ereforein the frequency domain the original signal was decom-posed into 128 subbands e width of each band was1172 kHz e frequency band range of each layer recon-structed after the decomposition of the original signal ispresented in Table 5

As can be seen from the table the original signal isexpressed as

S S70 + S71 + S72 + middot middot middot + S7127 (4)

where S70 is the low-frequency part of the decomposedsignal the other variables represent the decomposition of the

high-frequency part of the signal Assuming that the cor-responding energy of S7j(j 0 1 2 middot middot middot 127) isE7j(j 0 1 2 middot middot middot 127) then the energy characterization ofthe original AE signal decomposition in each frequencyband range can be obtained by formula (1)

Assuming that the total energy of the analyzed signal isE0 then

E0 1113944127

j0E7j (5)

e ratio of the energy of each frequency band to thetotal energy of the analyzed signal is

Ej E7j

E0times 100 (6)

In the formula j 012 27ndash1From Equation (1) the energy changes of the corre-

sponding AE signals in different frequency bands after theoriginal signal decomposition were calculated so the energydistribution characteristics of the elastic wave in differentfrequency bands could be found [38] According to Table 4the main frequency range of the AE signal waveform of eachmeasuring point was 0ndash300 kHz indicating that the energyvalue must also be concentrated in this frequency rangeerefore with MATLAB programming the energy dis-tribution of each subband in the frequency domain of0ndash500 kHz was obtained as shown in Figures 11 and 12

For rod-shaped rocks G3768 G3561 and TBG of thesame lithology from different places of origin the M1measuring point was closest to the pulse excitation sourceerefore the value of the M1 measuring point could ef-fectively reflect the energy value of the real pulse As can be

G3761-L

GAM-L

0deg

0 20 40 60 80 100 120

0

100

200

300

400

500

600

Distance (cm)

Ener

gy (m

Vlowast

ms)

G3761-L

GAM-L

45deg

Distance (cm)

Ener

gy (m

Vlowast

ms)

0 10 20 30 40 50 600

100

200

300

400

500

600

700

G3761-L

GAM-L

90deg

Distance (cm)

Ener

gy (m

Vlowast

ms)

0 10 20 30 40 50

100

200

300

400

500

600

700

Figure 6 e attenuation curves of the AE Energy in different directions for G3761-L and GAM-L

Table 4 e measuring point positions of AE waveforms

Rock number (measuring point) (cm) G3768 G3561 TBG AAM GAMG3761-L GAM-L

0deg 90deg 45deg 0deg 90deg 45deg

M1 5 5 5 5 5 5 5 5 5 5 5M2 70 70 70 70 50 55 20 30 40 25 30M3 135 135 135 135 100 100 35 50 75 40 50

Advances in Civil Engineering 9

seen from Figure 11 the energy is widely distributed in thefrequency domain e value of energy is generally smallwhich was mainly concentrated in the range of0ndash36428 kHz Combined with Formulas (5) and (6) it couldbe calculated that the main dominant energy of the three

groups of granite was concentrated in the frequency band of7131ndash12991 kHz which correspondingly accounted for646 5605 and 5828 of the total energy About2326 of the energy in G3561 was concentrated in thefrequency band of 23538ndash35256 kHz which is different

0 05 10 15 20 25ndash15

ndash10

ndash05

0

05

10

Am

plitu

de (m

V)

Time (ms)

G3768

TBG

0 05 10 15 20 25 3ndash08

ndash06

ndash04

ndash02

0

02

04

06

08

Am

plitu

de (m

V)

Time (ms)

G3561

0 05 10 15 20 25

ndash15

ndash10

ndash05

0

05

10

15

Time (ms)

Am

plitu

de (m

V)

AAM

0 05 10 15 2ndash20

ndash15

ndash10

ndash05

0

05

10

15

Time (ms)

Am

plitu

de (m

V)

GAM

0 05 10 15 20 25 30 35ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

Figure 7 Time domain waveform of measuring point M2 of rod-shaped rock

10 Advances in Civil Engineering

from other samples of the same lithology With the increaseof the propagation distance of the elastic wave its energyexhibited the characteristics of rapid attenuation edominant energy distribution frequency bands of the threerod-shaped rock materials at the M2 measuring point ex-panded from the initial 7131ndash12991 kHz to 0ndash17678 kHz

and the energy percentages were 8987 9407 and8658 respectively In the high-frequency band of28225ndash31741 kHz there was respectively 10 and 1269energy concentration for G3768 and TBG When the elasticwave propagated to the end of the rod (M3) the energy ofeach group of samples was relatively concentrated and

0 100 200 300 400 5000

001

002

003

004

Am

plitu

de (m

V)

Frequency (KHz)

G3768

TBG

0 100 200 300 400 5000

001

002

003

Am

plitu

de (m

V)

Frequency (KHz)

G3561

0 100 200 300 400 5000

001

002

003

004

005

006

007

Frequency (KHz)

Am

plitu

de (m

V)

AAM

0 100 200 300 400 5000

001

002

003

004

005

006

Frequency (KHz)

Am

plitu

de (m

V)

GAM

0 100 200 300 400 5000

0002

0004

0006

0008

0010

0012

Am

plitu

de (m

V)

Frequency (KHz)

Figure 8 e spectrogram of measuring point M2 of rod-shaped rock

Advances in Civil Engineering 11

G3761-L(90deg)

0 05 10 15 2ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

G3761-L(90deg)

0 100 200 300 400 500000

002

004

006

008

010

Am

plitu

de (m

V)

Frequency (KHz)

G3761-L(45deg)

0 05 10 15 20 25

ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

G3761-L(45deg)

0 100 200 300 400 5000

001

002

003

004

005

006

007

Am

plitu

de (m

V)

Frequency (KHz)

0 05 10 15 20 25 3ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

G3761-L(0deg)

Am

plitu

de (m

V)

Time (ms)

G3761-L(0deg)

0 100 200 300 400 5000

0002

0004

0006

0008

0010

Am

plitu

de (m

V)

Frequency (KHz)

(a)

Figure 9 Continued

12 Advances in Civil Engineering

mainly distributed within 0ndash10647 kHz at the percentages of9211 9022 and 9188 respectively By comparing thethree groups of rod-shaped rocks with the same lithology itcan be seen that the energy attenuation was the fastest inTBG and the dominant energy value was the lowest at theM3 measuring point For G3768 the energy attenuation wasthe slowest Only the distribution rule of the dominant

energy value at the M2 and M3 measuring points changedwhereas the maximum energy value hardly changed ereason may be that the internal structure or componentdensity of G3768 was better and the energy was relativelymaintained rather than rapidly attenuated with the elasticwave propagation For AAM artificial marble its maindominant energy also exhibited the same change trend as

GAM-L(45deg)

0 05 10 15 20 25

ndash3

ndash2

ndash1

0

1

2

3

4

Am

plitu

de (m

V)

Time (ms)

GAM-L(45deg)

0 100 200 300 400 5000

002

004

006

008

010

012

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(0deg)

0 05 10 15 20 25 30 35

ndash09

ndash06

ndash03

0

03

06

09

Am

plitu

de (m

V)

Time (ms)

GAM-L(0deg)

0 100 200 300 400 5000

0005

0010

0015

0020

0025

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(90deg)

0 05 10 15 20 25ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

GAM-L(90deg)

Am

plitu

de (m

V)

0 100 200 300 400 500000

002

004

006

008

010

Frequency (KHz)

(b)

Figure 9 e time waveform and spectrogram of measuring point M2 of pate-shaped rock

Advances in Civil Engineering 13

0 3 6 9 12 15ndash15

ndash10

ndash05

00

05

10

Wavelet function

0 3 6 9 12 15

ndash05

00

05

10

Scaling function

Figure 10 Wavelet function and scaling function for db7

Table 5 e frequency band range of reconstructed signal by wavelet packet decomposition

Layer S (i 0) S (i 1) S (i 2) S (i jminus 1) S (i j)1 0ndash750 ndash ndash ndash ndash 750ndash15002 0ndash375 375ndash750 750ndash1125 ndash ndash 1125ndash15003 0ndash1875 1875ndash375 375ndash5625 1125ndash13125 13125ndash15004 0ndash9375 9375ndash1875 1875ndash28125 13125ndash140625 140625ndash15005 0ndash46875 46875ndash9375 9375ndash140625 140625ndash1453125 1453125ndash15006 0ndash234375 234375ndash46875 46875ndash703125 1453125ndash14765625 14765625ndash15007 0ndash1171875 1171875ndash234375 234375ndash3515625 14765625ndash148828125 148828125ndash1500S (i j) represents the reconstruction signal of the j-th wavelet packet decomposition coefficient in the i-th layer i 1234 j 012 2i-1

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M3

(a)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500

1000

1500

2000

2500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

20

40

60

80

100

120

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

M3

(b)

Figure 11 Continued

14 Advances in Civil Engineering

granite From Figure 11 it can be observed that the energy ofthe original pulse signal is concentrated in the range of9475ndash16506 kHz and 2185 of the energy existed in thefrequency band of 28225ndash35256 kHz For GAMmarble themain dominant energy distribution of the initial signal wasvery wide and was distributed in the frequency band of0ndash36428 kHz Among them the dominant energy wasdistributed within the 10647ndash12991 kHz range accountingfor 3213 of the total energy Similar attenuation charac-teristics as granite were presented with the increase of elasticwave propagation distance In general for GAM the exci-tation energy of the AE signal generated by pulse excitationwas the weakest and the attenuation was the fastest with theincrease of distancee initial excitation energy of the threegroups of granite was partially concentrated in the frequency

band of 23538ndash35256 kHz of which the performance ofG3561 was the most obvious

e pulse AE signal was very complex for 2 groups of theplate-shaped rocks (Figure 12) erefore the initial energyof the M1 measuring point in each direction was also quitedifferent In the direction of 0deg the dominant energy of theoriginal pulse signal in G3761-L was concentrated in thefrequency band of 0ndash17678 kHz which accounted for8904 of the total energy Meanwhile about 628 of theenergy was distributed in the frequency band of29397ndash32913 kHz e same law was also shown in GAM-L but the main dominant frequency in GAM-L was rela-tively concentrated in the short frequency band of10647ndash17678 kHz which accounted for 6357 of the totalenergy With the spread of the elastic wave the energy in

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50002468

10121416

M3

(c)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5001000150020002500300035004000

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40

50

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M3

(d)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

100

200

300

400

500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M2

0 100 200 300 400 5000

2

4

6

8En

ergy

(mVlowast

mS)

Frequency (KHZ)

M3

0 100 200 300 400 500012345678

(e)

Figure 11e energy distribution of acoustic emission signal frequency band of rod-shaped rock (a) G3768 (b) G3561 (c) TBG (d) AAM(e) GAM

Advances in Civil Engineering 15

0 100 200 300 400 5000

200400600800

100012001400

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

M2

0 100 200 300 400 5000005101520253035

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

M3

0 100 200 300 400 50000020406081012

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

(a)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40En

ergy

(mVlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 5000

2

4

6

8

Ener

gy (m

Vlowast

mS)

(b)

M1

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

1020304050607080

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50002468

1012141618

Ener

gy (m

Vlowast

mS)

(c)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700800

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 50005

101520253035

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

Ener

gy (m

Vlowast

mS)

(d)

Figure 12 Continued

16 Advances in Civil Engineering

G3761-L showed a trend of attenuation and the energy intheM2measuring point was still distributed in the frequencyband of 0ndash17678 kHz e energy distribution at the M3measuring point was relatively concentrated and was locatedin the frequency band of 0ndash10647 kHz accounting for8340 of the total energy e energy at the measuringpoint M3 of GAM-L was more extensive in the frequencydomain and the energy value changed dramatically dem-onstrating the abnormal phenomenon that the maindominant energy increased e frequency range of thismeasuring point was 0ndash1885 kHz accounting for 8589 ofthe total energyere was also residual energy concentratedin the frequency band of 29397ndash32913 kHz e AE signalat M3 was superposed by the boundary reflection wave andthe energy was enhanced because of the high homogeneityand good ductility of GAM-L For G3761-L the dominantenergy of the elastic wave almost dissipated at the M3measuring point In the direction of 45deg the dominantenergy band of the original signal in G3761-L was distributedwithin 0ndash17678 kHz and 28225ndash35256 kHz respectivelyaccounting for 6415 and 3278 of the total energyMoreover it can be observed that the distribution of thedominant energy band was from distribution to concen-tration which was distributed in the frequency band of7131ndash17678 kHz at M2 With the increase of distance theenergy frequency band of the M3 measuring point near theedge of the plate was spread again and it was restored to theenergy frequency band range of the initial signal Howeverthe energy value was attenuated to a very small value at this

moment e energies of GAM-L in the measuring pointsM1 M2 and M3 were all distributed in the frequency bandof 0ndash36428 kHz In the direction of 90deg the primarydominant energy frequency bands of the two plate-shapedrocks were concentrated in 9475ndash1885 kHz e differenceis that the energy distribution of GAM-L was still con-centrated and the energy variation was much smaller thanG3761-L at the M2 measuring point In general the energyfrequency band of the two plate-shaped rocks with differentlithologies was the same as that of the rod-shape rock whichis mainly distributed in the range of 0ndash36428 kHz More-over they also exhibited the characteristics that the maindominant energy was distributed in the range of0ndash17678 kHz and the residual energy was distributed in therange of 28225ndash35256 kHz

4 Discussion

e purpose of this work was to study the propagationcharacteristics of elastic wave in lithological rock materialsrough the above research and analysis a preliminaryunderstanding was obtained Based on the deep waveletpacket analysis of amplitude energy characteristic param-eters and AE waveform the frequency band characteristicsof the local energy distribution of elastic wave with itspropagation were summarized However its propagationcharacteristics are difficult to be regularly grasped becausethe elastic wave itself is extremely complex Furthermore AEtechnology is mostly used in the damage detection and

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

20406080

100120140160

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

10

20

30

40

50

(e)

M1

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

200400600800

10001200140016001800

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

50

100

150

200

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 50005

101520253035

(f )

Figure 12e energy distribution of acoustic emission signal frequency band of plate-shaped rock (a) G3761-L (00) (b) G3761-L (450) (c)G3761-L (900) (d) GAM-L (00) (e) GAM-L (450) (f ) GAM-L (900)

Advances in Civil Engineering 17

defect location of metal or related materials with goodcompactness ductility and within the same medium ereare many uncertain interference factors in the experimentsIn some aspects the analysis of this paper only stays at thelevel of the apparent phenomenon and there are still manydeficiencies and areas worthy of improvement For instancethe density wave velocity and wave impedance of the rod-shaped rock samples should be tested and the micro-structure imaging experiments of the rock samples should beconducted e quality factor Q of different rock samplesshould be calculated Moreover the correlation between thequality factor and wave impedance should be studied andthe influence of different microcompositions of rod-shapedrocks on elastic wave attenuation should be deeply analyzedBased on the modal AE theory the influence of Lamb wavein plate-shaped rocks should be studied and the propagationmodel of two-dimensional AE should be constructed eGabor wavelet should be introduced to analyze the AE signalby time-frequency analysis e influence of differentwavelets based on the propagation effect of AE will becompared and analyzed and the time of the same mode ofthe AE wave arriving at the sensor will be determined tofurther optimize the plane location algorithm However theresearch in this work is still useful for studying large-scalerock samples in the future and provides effective researchmethods and ideas for the study of elastic wave propagationcharacteristics of different rock materials and compositematerials

5 Conclusions

In this work the characteristic parameter analysis andwaveform analysis of the AE signals obtained from differentexperimental schemes in 5 groups of rod-shaped rocks and 2groups of plate-shaped rocks were carried out e con-clusions are as follows

(1) e amplitude and energy of the rod-shaped rocksgradually attenuated with the increase of distancee amplitude can directly reflect the intensity of theAE counts at different measuring areas In theprocess of elastic wave propagation of the rod-sha-ped rock the P-wave preceded the S-wave andchanged violently e elastic wave of marble at-tenuated faster and the elastic wave of the threekinds of granite decayed attenuated closely Amongthem the elastic wave of TBG exhibited the fastestattenuation

(2) In flat plate-shaped rocks the amplitude exhibited anapproximate exponential attenuation characteristicwith the increase of the propagation distanceGranite exhibited a stronger elastic wave attenuationin the 0deg direction than the marble and the marblepresented fast attenuations in the 45deg and 90deg di-rections e energy change of marble was dramaticand the energy value in the interval of 45ndash55 cm atthe direction of 0deg showed the abnormal step phe-nomenon e energy value of the marble increasedafter 55 cm in the 45deg direction e energy value of

granite from the back to the end of the plate wasalmost maintained and tended to be stable at20ndash50mVms

(3) e frequency range of the energy distribution ofsamples in this work was within 0ndash36428 kHz Withthe increase of distance the main dominant energydistribution of the 5 groups of rod-shaped rocks inthe frequency range was characterized by distribu-tion to relative concentration and rapid energy at-tenuationemain dominant energy distribution ofthe 2 groups of plate-shaped rocks was distributed inthe range of 0ndash17678 kHz All rod-shaped rocks andplate-shaped rocks exhibited the characteristics ofresidual energy distribution in the frequency band of28225ndash35256 kHz

Data Availability

e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

e authors certify that they have no conflicts of interest

Acknowledgments

is research was funded by the National Natural ScienceFoundation of China (51804161 52074156 and 52004291)the Chinese Postdoctoral Science Foundation(2019M660861) and the State Key Laboratory CultivationBase for Gas Geology and Gas Control (Henan PolytechnicUniversity) (WS2020A04)

References

[1] J T Chen J H Zhao S C Zhang Y Zhang F Yang andM Li ldquoAn experimental and analytical research on theevolution of mining cracks in deep floor rock massrdquo Pure andApplied Geophysics vol 177 no 11 pp 5325ndash5348 2020

[2] K Wang and F Du ldquoCoal-gas compound dynamic disastersin China a reviewrdquo Process Safety and Environmental Pro-tection vol 133 pp 1ndash17 2020

[3] C Zhu M He M Karakus X Cui and Z Tao ldquoInvestigatingtoppling failure mechanism of anti-dip layered slope due toexcavation by physical modellingrdquo Rock Mechanics and RockEngineering vol 53 no 11 pp 5029ndash5050 2020

[4] X Wang C Liu S Chen L Chen K Li and N Liu ldquoImpactof coal sectorrsquos de-capacity policy on coal pricerdquo AppliedEnergy vol 265 Article ID 114802 2020

[5] D Liu Z Gu R Liang et al ldquoImpacts of pore-throat systemon fractal characterization of tight sandstonesrdquo Geofluidsvol 2020 no 9 17 pages Article ID 4941501 2020

[6] J Wang Y Zhang Z Qin S Song and P Lin ldquoAnalysismethod of water inrush for tunnels with damaged water-resisting rock mass based on finite element method-smoothparticle hydrodynamics couplingrdquo Computers and Geo-technics vol 126 Article ID 103725 2020

[7] B Chen S C Zhang Y Y Li Z K Li and H J ZhouldquoPhysical simulation study of crack propagation and insta-bility information discrimination of rock-like materials withfaultsrdquo Arabian Journal of Geosciences vol 13 p 966 2020

18 Advances in Civil Engineering

[8] F Du K Wang X Zhang C Xin and G Wang ldquoExperi-mental study of coal-gas outburst insights from coal-rockstructure gas pressure and adsorptivityrdquo Natural ResourcesResearch vol 29 no 4 pp 2481ndash2493 2020

[9] H Y Wang J Ma G D Wang et al ldquoResearch on AE sourcelocation of linear and plane rock massrdquo Shock and Vibrationvol 2020 Article ID 8846582 18 pages 2020

[10] V A Mansurov ldquoPrediction of rockbursts by analysis ofinduced seismicity datardquo International Journal of Rock Me-chanics and Mining Sciences vol 38 no 6 pp 893ndash901 2001

[11] M C He J L Miao and J L Feng ldquoRock burst process oflimestone and its acoustic emission characteristics under true-triaxial unloading conditionsrdquo International Journal of RockMechanics and Mining Sciences vol 47 no 2 pp 286ndash2982010

[12] F Gong J Yan X Li and S Luo ldquoA peak-strength strainenergy storage index for rock burst proneness of rock ma-terialsrdquo International Journal of Rock Mechanics and MiningSciences vol 117 pp 76ndash89 2019

[13] F Du and KWang ldquoUnstable failure of gas-bearing coal-rockcombination bodies insights from physical experiments andnumerical simulationsrdquo Process Safety and EnvironmentalProtection vol 129 pp 264ndash279 2019

[14] S D Butt C Mukherjee and G Lebans ldquoEvaluation ofacoustic attenuation as an indicator of roof stability in ad-vancing headingsrdquo International Journal of Rock Mechanicsand Mining Sciences vol 37 no 7 pp 1123ndash1131 2000

[15] M Cai H Morioka P K Kaiser et al ldquoBack-analysis of rockmass strength parameters using ae monitoring datardquo Inter-national Journal of Rock Mechanics and Mining Sciencesvol 44 no 4 pp 538ndash549 2007

[16] D P Jansen S R Carlson R P Young and D A HutchinsldquoUltrasonic imaging and acoustic emission monitoring ofthermally induced microcracks in Lac du Bonnet graniterdquoJournal of Geophysical Research Solid Earth vol 98 no B12pp 22231ndash22243 1993

[17] U Bismayer ldquoEarly warning signs for mining accidentsdetecting crackling noiserdquo American Mineralogist vol 102no 1 pp 3-4 2017

[18] X Kong E Wang S Li H Lin P Xiao and K ZhangldquoFractals and chaos characteristics of acoustic emission energyabout gas-bearing coal during loaded failurerdquo Fractals vol 27no 5 Article ID 195072 2019

[19] F Du K Wang G Wang Y Jiang C Xin and X ZhangldquoInvestigation of the acoustic emission characteristics duringdeformation and failure of gas-bearing coal-rock combinedbodiesrdquo Journal of Loss Prevention in the Process Industriesvol 55 pp 253ndash266 2018

[20] R P Young D A Hutchins S Talebi et al ldquoLaboratory andfield investigations of rockburst phenomena using concurrentgeotomographic imaging and acoustic emissionmicroseismictechniquesrdquo Seismicity in Mines vol 129 no 3-4pp 647ndash659 1989

[21] X Jansen H Xu M He and F Zhang ldquoExperimental in-vestigation of the occurrence of rockburst in a rock specimenthrough infrared thermography and acoustic emissionrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 93 pp 250ndash259 2017

[22] R E Goodman and E Richard ldquoSubaudible noise duringcompression of rocksrdquo Geological Society of America Bulletinvol 74 no 4 pp 487ndash490 1963

[23] M Cai P K Kaiser H Morioka et al ldquoFLACPFC couplednumerical simulation of AE in large-scale underground

excavationsrdquo International Journal of Rock Mechanics andMining Sciences vol 44 no 4 pp 550ndash564 2007

[24] V Saltas F Vallianatos D Triantis T Koumoudeli andI Stavrakas ldquoNon-extensive statistical analysis of acousticemissions series recorded during the uniaxial compression ofbrittle rocksrdquo Physica A Statistical Mechanics and Its Ap-plications vol 528 Article ID 121498 2019

[25] V Saltas I Fitilis and F Vallianatos ldquoA combined complexelectrical impedance and acoustic emission study in limestonesamples under uniaxial loadingrdquo Tectonophysics vol 637pp 198ndash206 2014

[26] G Qi ldquoWavelet-based AE characterization of compositematerialsrdquo NDTamp E International vol 33 no 3 pp 133ndash1442000

[27] G Manthei J Eisenblatter and T Dahm ldquoMoment tensorevaluation of acoustic emission sources in salt rockrdquo Con-struction and Building Materials vol 15 no 5-6 pp 297ndash3092001

[28] H Jeong and Y-S Jang ldquoWavelet analysis of plate wavepropagation in composite laminatesrdquo Composite Structuresvol 49 no 4 pp 443ndash450 2000

[29] S-H Chang and C-I Lee ldquoEstimation of cracking anddamage mechanisms in rock under triaxial compression bymoment tensor analysis of acoustic emissionrdquo InternationalJournal of Rock Mechanics and Mining Sciences vol 41 no 7pp 1069ndash1086 2004

[30] T Hirata T Satoh and K Ito ldquoFractal structure of spatialdistribution of microfracturing in rockrdquo Geophysical JournalInternational vol 90 no 2 pp 369ndash374 1987

[31] X Lei K Masuda O Nishizawa et al ldquoDetailed analysis ofacoustic emission activity during catastrophic fracture offaults in rockrdquo Journal of Structural Geology vol 26 no 2pp 247ndash258 2004

[32] J Jouniaux J Pei J Liu et al ldquoInvestigation on acousticemission behavior and its time-space evolution mechanism infailure process of coalndashrock combined bodyrdquo Chinese Journalof Rock Mechanics and Engineering vol 30 pp 1564ndash15702011

[33] E Townend B D ompson P M Benson PG MeredithP Baud and R P Young ldquoImaging compaction bandpropagation in Diemelstadt sandstone using acoustic emis-sion locationsrdquo Geophysical Research Letters vol 35 no 15pp 189ndash193 2008

[34] M Naderloo M Moosavi and M Ahmadi ldquoUsing acousticemission technique tomonitor damage progress around jointsin brittle materialsrdquo Deoretical and Applied Fracture Me-chanics vol 104 Article ID 102368 2019

[35] GBT Unified Number of Natural Stone China StandardsPress Beijing China 2009

[36] G Shen Acoustic Emission Detection Technology and Appli-cation Science Press Beijing China 2015

[37] Y Guo Research on Wavelet Base Selection for VibrationSignal Processing Hefei University of Technology HefeiChina 2003

[38] F Xu E Wang and D Song ldquoLong-range correlation andmultifractal distribution of acoustic emission of coal-rockrdquoRock and Soil Mechanics vol 32 no 7 pp 2111ndash2116 2011

Advances in Civil Engineering 19

waveform obtained at different measuring points in eachgroup of rock samples to explore the local feature infor-mation of the AE signal waveform at different positions ofrod-shaped and plate-shaped rocks

Choosing a suitable wavelet base plays an important rolein signal processing and analysis Guo [37] introduced theeffect of different wavelet bases in vibration signal processingin detail which presents that the db5 db7 db10 db13 db16bior26 bior39 coif4 sym7 and sym8 wavelet bases aremore suitable for the shock feature extraction of vibrationsignals Of this wavelet set db7 was selected as the waveletbase for the wavelet packet analysis because of its Daubechiesseries wavelet set characteristics such as high-order van-ishing moment tight support regularity approximatesymmetry and orthogonalityndashand because of the similaritiesit shares with the rock AE signal Its wavelet function ispresented in Figure 10

e sampling frequency is 3MHz According to thesampling theorem its Nyquist frequency is 1500 kHz ewavelet packet decomposition principle and algorithm wereapplied to decompose the signal to the 7th layer (ie thescale is 7) which has 27 wavelet packets in total ereforein the frequency domain the original signal was decom-posed into 128 subbands e width of each band was1172 kHz e frequency band range of each layer recon-structed after the decomposition of the original signal ispresented in Table 5

As can be seen from the table the original signal isexpressed as

S S70 + S71 + S72 + middot middot middot + S7127 (4)

where S70 is the low-frequency part of the decomposedsignal the other variables represent the decomposition of the

high-frequency part of the signal Assuming that the cor-responding energy of S7j(j 0 1 2 middot middot middot 127) isE7j(j 0 1 2 middot middot middot 127) then the energy characterization ofthe original AE signal decomposition in each frequencyband range can be obtained by formula (1)

Assuming that the total energy of the analyzed signal isE0 then

E0 1113944127

j0E7j (5)

e ratio of the energy of each frequency band to thetotal energy of the analyzed signal is

Ej E7j

E0times 100 (6)

In the formula j 012 27ndash1From Equation (1) the energy changes of the corre-

sponding AE signals in different frequency bands after theoriginal signal decomposition were calculated so the energydistribution characteristics of the elastic wave in differentfrequency bands could be found [38] According to Table 4the main frequency range of the AE signal waveform of eachmeasuring point was 0ndash300 kHz indicating that the energyvalue must also be concentrated in this frequency rangeerefore with MATLAB programming the energy dis-tribution of each subband in the frequency domain of0ndash500 kHz was obtained as shown in Figures 11 and 12

For rod-shaped rocks G3768 G3561 and TBG of thesame lithology from different places of origin the M1measuring point was closest to the pulse excitation sourceerefore the value of the M1 measuring point could ef-fectively reflect the energy value of the real pulse As can be

G3761-L

GAM-L

0deg

0 20 40 60 80 100 120

0

100

200

300

400

500

600

Distance (cm)

Ener

gy (m

Vlowast

ms)

G3761-L

GAM-L

45deg

Distance (cm)

Ener

gy (m

Vlowast

ms)

0 10 20 30 40 50 600

100

200

300

400

500

600

700

G3761-L

GAM-L

90deg

Distance (cm)

Ener

gy (m

Vlowast

ms)

0 10 20 30 40 50

100

200

300

400

500

600

700

Figure 6 e attenuation curves of the AE Energy in different directions for G3761-L and GAM-L

Table 4 e measuring point positions of AE waveforms

Rock number (measuring point) (cm) G3768 G3561 TBG AAM GAMG3761-L GAM-L

0deg 90deg 45deg 0deg 90deg 45deg

M1 5 5 5 5 5 5 5 5 5 5 5M2 70 70 70 70 50 55 20 30 40 25 30M3 135 135 135 135 100 100 35 50 75 40 50

Advances in Civil Engineering 9

seen from Figure 11 the energy is widely distributed in thefrequency domain e value of energy is generally smallwhich was mainly concentrated in the range of0ndash36428 kHz Combined with Formulas (5) and (6) it couldbe calculated that the main dominant energy of the three

groups of granite was concentrated in the frequency band of7131ndash12991 kHz which correspondingly accounted for646 5605 and 5828 of the total energy About2326 of the energy in G3561 was concentrated in thefrequency band of 23538ndash35256 kHz which is different

0 05 10 15 20 25ndash15

ndash10

ndash05

0

05

10

Am

plitu

de (m

V)

Time (ms)

G3768

TBG

0 05 10 15 20 25 3ndash08

ndash06

ndash04

ndash02

0

02

04

06

08

Am

plitu

de (m

V)

Time (ms)

G3561

0 05 10 15 20 25

ndash15

ndash10

ndash05

0

05

10

15

Time (ms)

Am

plitu

de (m

V)

AAM

0 05 10 15 2ndash20

ndash15

ndash10

ndash05

0

05

10

15

Time (ms)

Am

plitu

de (m

V)

GAM

0 05 10 15 20 25 30 35ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

Figure 7 Time domain waveform of measuring point M2 of rod-shaped rock

10 Advances in Civil Engineering

from other samples of the same lithology With the increaseof the propagation distance of the elastic wave its energyexhibited the characteristics of rapid attenuation edominant energy distribution frequency bands of the threerod-shaped rock materials at the M2 measuring point ex-panded from the initial 7131ndash12991 kHz to 0ndash17678 kHz

and the energy percentages were 8987 9407 and8658 respectively In the high-frequency band of28225ndash31741 kHz there was respectively 10 and 1269energy concentration for G3768 and TBG When the elasticwave propagated to the end of the rod (M3) the energy ofeach group of samples was relatively concentrated and

0 100 200 300 400 5000

001

002

003

004

Am

plitu

de (m

V)

Frequency (KHz)

G3768

TBG

0 100 200 300 400 5000

001

002

003

Am

plitu

de (m

V)

Frequency (KHz)

G3561

0 100 200 300 400 5000

001

002

003

004

005

006

007

Frequency (KHz)

Am

plitu

de (m

V)

AAM

0 100 200 300 400 5000

001

002

003

004

005

006

Frequency (KHz)

Am

plitu

de (m

V)

GAM

0 100 200 300 400 5000

0002

0004

0006

0008

0010

0012

Am

plitu

de (m

V)

Frequency (KHz)

Figure 8 e spectrogram of measuring point M2 of rod-shaped rock

Advances in Civil Engineering 11

G3761-L(90deg)

0 05 10 15 2ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

G3761-L(90deg)

0 100 200 300 400 500000

002

004

006

008

010

Am

plitu

de (m

V)

Frequency (KHz)

G3761-L(45deg)

0 05 10 15 20 25

ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

G3761-L(45deg)

0 100 200 300 400 5000

001

002

003

004

005

006

007

Am

plitu

de (m

V)

Frequency (KHz)

0 05 10 15 20 25 3ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

G3761-L(0deg)

Am

plitu

de (m

V)

Time (ms)

G3761-L(0deg)

0 100 200 300 400 5000

0002

0004

0006

0008

0010

Am

plitu

de (m

V)

Frequency (KHz)

(a)

Figure 9 Continued

12 Advances in Civil Engineering

mainly distributed within 0ndash10647 kHz at the percentages of9211 9022 and 9188 respectively By comparing thethree groups of rod-shaped rocks with the same lithology itcan be seen that the energy attenuation was the fastest inTBG and the dominant energy value was the lowest at theM3 measuring point For G3768 the energy attenuation wasthe slowest Only the distribution rule of the dominant

energy value at the M2 and M3 measuring points changedwhereas the maximum energy value hardly changed ereason may be that the internal structure or componentdensity of G3768 was better and the energy was relativelymaintained rather than rapidly attenuated with the elasticwave propagation For AAM artificial marble its maindominant energy also exhibited the same change trend as

GAM-L(45deg)

0 05 10 15 20 25

ndash3

ndash2

ndash1

0

1

2

3

4

Am

plitu

de (m

V)

Time (ms)

GAM-L(45deg)

0 100 200 300 400 5000

002

004

006

008

010

012

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(0deg)

0 05 10 15 20 25 30 35

ndash09

ndash06

ndash03

0

03

06

09

Am

plitu

de (m

V)

Time (ms)

GAM-L(0deg)

0 100 200 300 400 5000

0005

0010

0015

0020

0025

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(90deg)

0 05 10 15 20 25ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

GAM-L(90deg)

Am

plitu

de (m

V)

0 100 200 300 400 500000

002

004

006

008

010

Frequency (KHz)

(b)

Figure 9 e time waveform and spectrogram of measuring point M2 of pate-shaped rock

Advances in Civil Engineering 13

0 3 6 9 12 15ndash15

ndash10

ndash05

00

05

10

Wavelet function

0 3 6 9 12 15

ndash05

00

05

10

Scaling function

Figure 10 Wavelet function and scaling function for db7

Table 5 e frequency band range of reconstructed signal by wavelet packet decomposition

Layer S (i 0) S (i 1) S (i 2) S (i jminus 1) S (i j)1 0ndash750 ndash ndash ndash ndash 750ndash15002 0ndash375 375ndash750 750ndash1125 ndash ndash 1125ndash15003 0ndash1875 1875ndash375 375ndash5625 1125ndash13125 13125ndash15004 0ndash9375 9375ndash1875 1875ndash28125 13125ndash140625 140625ndash15005 0ndash46875 46875ndash9375 9375ndash140625 140625ndash1453125 1453125ndash15006 0ndash234375 234375ndash46875 46875ndash703125 1453125ndash14765625 14765625ndash15007 0ndash1171875 1171875ndash234375 234375ndash3515625 14765625ndash148828125 148828125ndash1500S (i j) represents the reconstruction signal of the j-th wavelet packet decomposition coefficient in the i-th layer i 1234 j 012 2i-1

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M3

(a)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500

1000

1500

2000

2500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

20

40

60

80

100

120

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

M3

(b)

Figure 11 Continued

14 Advances in Civil Engineering

granite From Figure 11 it can be observed that the energy ofthe original pulse signal is concentrated in the range of9475ndash16506 kHz and 2185 of the energy existed in thefrequency band of 28225ndash35256 kHz For GAMmarble themain dominant energy distribution of the initial signal wasvery wide and was distributed in the frequency band of0ndash36428 kHz Among them the dominant energy wasdistributed within the 10647ndash12991 kHz range accountingfor 3213 of the total energy Similar attenuation charac-teristics as granite were presented with the increase of elasticwave propagation distance In general for GAM the exci-tation energy of the AE signal generated by pulse excitationwas the weakest and the attenuation was the fastest with theincrease of distancee initial excitation energy of the threegroups of granite was partially concentrated in the frequency

band of 23538ndash35256 kHz of which the performance ofG3561 was the most obvious

e pulse AE signal was very complex for 2 groups of theplate-shaped rocks (Figure 12) erefore the initial energyof the M1 measuring point in each direction was also quitedifferent In the direction of 0deg the dominant energy of theoriginal pulse signal in G3761-L was concentrated in thefrequency band of 0ndash17678 kHz which accounted for8904 of the total energy Meanwhile about 628 of theenergy was distributed in the frequency band of29397ndash32913 kHz e same law was also shown in GAM-L but the main dominant frequency in GAM-L was rela-tively concentrated in the short frequency band of10647ndash17678 kHz which accounted for 6357 of the totalenergy With the spread of the elastic wave the energy in

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50002468

10121416

M3

(c)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5001000150020002500300035004000

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40

50

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M3

(d)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

100

200

300

400

500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M2

0 100 200 300 400 5000

2

4

6

8En

ergy

(mVlowast

mS)

Frequency (KHZ)

M3

0 100 200 300 400 500012345678

(e)

Figure 11e energy distribution of acoustic emission signal frequency band of rod-shaped rock (a) G3768 (b) G3561 (c) TBG (d) AAM(e) GAM

Advances in Civil Engineering 15

0 100 200 300 400 5000

200400600800

100012001400

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

M2

0 100 200 300 400 5000005101520253035

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

M3

0 100 200 300 400 50000020406081012

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

(a)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40En

ergy

(mVlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 5000

2

4

6

8

Ener

gy (m

Vlowast

mS)

(b)

M1

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

1020304050607080

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50002468

1012141618

Ener

gy (m

Vlowast

mS)

(c)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700800

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 50005

101520253035

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

Ener

gy (m

Vlowast

mS)

(d)

Figure 12 Continued

16 Advances in Civil Engineering

G3761-L showed a trend of attenuation and the energy intheM2measuring point was still distributed in the frequencyband of 0ndash17678 kHz e energy distribution at the M3measuring point was relatively concentrated and was locatedin the frequency band of 0ndash10647 kHz accounting for8340 of the total energy e energy at the measuringpoint M3 of GAM-L was more extensive in the frequencydomain and the energy value changed dramatically dem-onstrating the abnormal phenomenon that the maindominant energy increased e frequency range of thismeasuring point was 0ndash1885 kHz accounting for 8589 ofthe total energyere was also residual energy concentratedin the frequency band of 29397ndash32913 kHz e AE signalat M3 was superposed by the boundary reflection wave andthe energy was enhanced because of the high homogeneityand good ductility of GAM-L For G3761-L the dominantenergy of the elastic wave almost dissipated at the M3measuring point In the direction of 45deg the dominantenergy band of the original signal in G3761-L was distributedwithin 0ndash17678 kHz and 28225ndash35256 kHz respectivelyaccounting for 6415 and 3278 of the total energyMoreover it can be observed that the distribution of thedominant energy band was from distribution to concen-tration which was distributed in the frequency band of7131ndash17678 kHz at M2 With the increase of distance theenergy frequency band of the M3 measuring point near theedge of the plate was spread again and it was restored to theenergy frequency band range of the initial signal Howeverthe energy value was attenuated to a very small value at this

moment e energies of GAM-L in the measuring pointsM1 M2 and M3 were all distributed in the frequency bandof 0ndash36428 kHz In the direction of 90deg the primarydominant energy frequency bands of the two plate-shapedrocks were concentrated in 9475ndash1885 kHz e differenceis that the energy distribution of GAM-L was still con-centrated and the energy variation was much smaller thanG3761-L at the M2 measuring point In general the energyfrequency band of the two plate-shaped rocks with differentlithologies was the same as that of the rod-shape rock whichis mainly distributed in the range of 0ndash36428 kHz More-over they also exhibited the characteristics that the maindominant energy was distributed in the range of0ndash17678 kHz and the residual energy was distributed in therange of 28225ndash35256 kHz

4 Discussion

e purpose of this work was to study the propagationcharacteristics of elastic wave in lithological rock materialsrough the above research and analysis a preliminaryunderstanding was obtained Based on the deep waveletpacket analysis of amplitude energy characteristic param-eters and AE waveform the frequency band characteristicsof the local energy distribution of elastic wave with itspropagation were summarized However its propagationcharacteristics are difficult to be regularly grasped becausethe elastic wave itself is extremely complex Furthermore AEtechnology is mostly used in the damage detection and

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

20406080

100120140160

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

10

20

30

40

50

(e)

M1

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

200400600800

10001200140016001800

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

50

100

150

200

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 50005

101520253035

(f )

Figure 12e energy distribution of acoustic emission signal frequency band of plate-shaped rock (a) G3761-L (00) (b) G3761-L (450) (c)G3761-L (900) (d) GAM-L (00) (e) GAM-L (450) (f ) GAM-L (900)

Advances in Civil Engineering 17

defect location of metal or related materials with goodcompactness ductility and within the same medium ereare many uncertain interference factors in the experimentsIn some aspects the analysis of this paper only stays at thelevel of the apparent phenomenon and there are still manydeficiencies and areas worthy of improvement For instancethe density wave velocity and wave impedance of the rod-shaped rock samples should be tested and the micro-structure imaging experiments of the rock samples should beconducted e quality factor Q of different rock samplesshould be calculated Moreover the correlation between thequality factor and wave impedance should be studied andthe influence of different microcompositions of rod-shapedrocks on elastic wave attenuation should be deeply analyzedBased on the modal AE theory the influence of Lamb wavein plate-shaped rocks should be studied and the propagationmodel of two-dimensional AE should be constructed eGabor wavelet should be introduced to analyze the AE signalby time-frequency analysis e influence of differentwavelets based on the propagation effect of AE will becompared and analyzed and the time of the same mode ofthe AE wave arriving at the sensor will be determined tofurther optimize the plane location algorithm However theresearch in this work is still useful for studying large-scalerock samples in the future and provides effective researchmethods and ideas for the study of elastic wave propagationcharacteristics of different rock materials and compositematerials

5 Conclusions

In this work the characteristic parameter analysis andwaveform analysis of the AE signals obtained from differentexperimental schemes in 5 groups of rod-shaped rocks and 2groups of plate-shaped rocks were carried out e con-clusions are as follows

(1) e amplitude and energy of the rod-shaped rocksgradually attenuated with the increase of distancee amplitude can directly reflect the intensity of theAE counts at different measuring areas In theprocess of elastic wave propagation of the rod-sha-ped rock the P-wave preceded the S-wave andchanged violently e elastic wave of marble at-tenuated faster and the elastic wave of the threekinds of granite decayed attenuated closely Amongthem the elastic wave of TBG exhibited the fastestattenuation

(2) In flat plate-shaped rocks the amplitude exhibited anapproximate exponential attenuation characteristicwith the increase of the propagation distanceGranite exhibited a stronger elastic wave attenuationin the 0deg direction than the marble and the marblepresented fast attenuations in the 45deg and 90deg di-rections e energy change of marble was dramaticand the energy value in the interval of 45ndash55 cm atthe direction of 0deg showed the abnormal step phe-nomenon e energy value of the marble increasedafter 55 cm in the 45deg direction e energy value of

granite from the back to the end of the plate wasalmost maintained and tended to be stable at20ndash50mVms

(3) e frequency range of the energy distribution ofsamples in this work was within 0ndash36428 kHz Withthe increase of distance the main dominant energydistribution of the 5 groups of rod-shaped rocks inthe frequency range was characterized by distribu-tion to relative concentration and rapid energy at-tenuationemain dominant energy distribution ofthe 2 groups of plate-shaped rocks was distributed inthe range of 0ndash17678 kHz All rod-shaped rocks andplate-shaped rocks exhibited the characteristics ofresidual energy distribution in the frequency band of28225ndash35256 kHz

Data Availability

e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

e authors certify that they have no conflicts of interest

Acknowledgments

is research was funded by the National Natural ScienceFoundation of China (51804161 52074156 and 52004291)the Chinese Postdoctoral Science Foundation(2019M660861) and the State Key Laboratory CultivationBase for Gas Geology and Gas Control (Henan PolytechnicUniversity) (WS2020A04)

References

[1] J T Chen J H Zhao S C Zhang Y Zhang F Yang andM Li ldquoAn experimental and analytical research on theevolution of mining cracks in deep floor rock massrdquo Pure andApplied Geophysics vol 177 no 11 pp 5325ndash5348 2020

[2] K Wang and F Du ldquoCoal-gas compound dynamic disastersin China a reviewrdquo Process Safety and Environmental Pro-tection vol 133 pp 1ndash17 2020

[3] C Zhu M He M Karakus X Cui and Z Tao ldquoInvestigatingtoppling failure mechanism of anti-dip layered slope due toexcavation by physical modellingrdquo Rock Mechanics and RockEngineering vol 53 no 11 pp 5029ndash5050 2020

[4] X Wang C Liu S Chen L Chen K Li and N Liu ldquoImpactof coal sectorrsquos de-capacity policy on coal pricerdquo AppliedEnergy vol 265 Article ID 114802 2020

[5] D Liu Z Gu R Liang et al ldquoImpacts of pore-throat systemon fractal characterization of tight sandstonesrdquo Geofluidsvol 2020 no 9 17 pages Article ID 4941501 2020

[6] J Wang Y Zhang Z Qin S Song and P Lin ldquoAnalysismethod of water inrush for tunnels with damaged water-resisting rock mass based on finite element method-smoothparticle hydrodynamics couplingrdquo Computers and Geo-technics vol 126 Article ID 103725 2020

[7] B Chen S C Zhang Y Y Li Z K Li and H J ZhouldquoPhysical simulation study of crack propagation and insta-bility information discrimination of rock-like materials withfaultsrdquo Arabian Journal of Geosciences vol 13 p 966 2020

18 Advances in Civil Engineering

[8] F Du K Wang X Zhang C Xin and G Wang ldquoExperi-mental study of coal-gas outburst insights from coal-rockstructure gas pressure and adsorptivityrdquo Natural ResourcesResearch vol 29 no 4 pp 2481ndash2493 2020

[9] H Y Wang J Ma G D Wang et al ldquoResearch on AE sourcelocation of linear and plane rock massrdquo Shock and Vibrationvol 2020 Article ID 8846582 18 pages 2020

[10] V A Mansurov ldquoPrediction of rockbursts by analysis ofinduced seismicity datardquo International Journal of Rock Me-chanics and Mining Sciences vol 38 no 6 pp 893ndash901 2001

[11] M C He J L Miao and J L Feng ldquoRock burst process oflimestone and its acoustic emission characteristics under true-triaxial unloading conditionsrdquo International Journal of RockMechanics and Mining Sciences vol 47 no 2 pp 286ndash2982010

[12] F Gong J Yan X Li and S Luo ldquoA peak-strength strainenergy storage index for rock burst proneness of rock ma-terialsrdquo International Journal of Rock Mechanics and MiningSciences vol 117 pp 76ndash89 2019

[13] F Du and KWang ldquoUnstable failure of gas-bearing coal-rockcombination bodies insights from physical experiments andnumerical simulationsrdquo Process Safety and EnvironmentalProtection vol 129 pp 264ndash279 2019

[14] S D Butt C Mukherjee and G Lebans ldquoEvaluation ofacoustic attenuation as an indicator of roof stability in ad-vancing headingsrdquo International Journal of Rock Mechanicsand Mining Sciences vol 37 no 7 pp 1123ndash1131 2000

[15] M Cai H Morioka P K Kaiser et al ldquoBack-analysis of rockmass strength parameters using ae monitoring datardquo Inter-national Journal of Rock Mechanics and Mining Sciencesvol 44 no 4 pp 538ndash549 2007

[16] D P Jansen S R Carlson R P Young and D A HutchinsldquoUltrasonic imaging and acoustic emission monitoring ofthermally induced microcracks in Lac du Bonnet graniterdquoJournal of Geophysical Research Solid Earth vol 98 no B12pp 22231ndash22243 1993

[17] U Bismayer ldquoEarly warning signs for mining accidentsdetecting crackling noiserdquo American Mineralogist vol 102no 1 pp 3-4 2017

[18] X Kong E Wang S Li H Lin P Xiao and K ZhangldquoFractals and chaos characteristics of acoustic emission energyabout gas-bearing coal during loaded failurerdquo Fractals vol 27no 5 Article ID 195072 2019

[19] F Du K Wang G Wang Y Jiang C Xin and X ZhangldquoInvestigation of the acoustic emission characteristics duringdeformation and failure of gas-bearing coal-rock combinedbodiesrdquo Journal of Loss Prevention in the Process Industriesvol 55 pp 253ndash266 2018

[20] R P Young D A Hutchins S Talebi et al ldquoLaboratory andfield investigations of rockburst phenomena using concurrentgeotomographic imaging and acoustic emissionmicroseismictechniquesrdquo Seismicity in Mines vol 129 no 3-4pp 647ndash659 1989

[21] X Jansen H Xu M He and F Zhang ldquoExperimental in-vestigation of the occurrence of rockburst in a rock specimenthrough infrared thermography and acoustic emissionrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 93 pp 250ndash259 2017

[22] R E Goodman and E Richard ldquoSubaudible noise duringcompression of rocksrdquo Geological Society of America Bulletinvol 74 no 4 pp 487ndash490 1963

[23] M Cai P K Kaiser H Morioka et al ldquoFLACPFC couplednumerical simulation of AE in large-scale underground

excavationsrdquo International Journal of Rock Mechanics andMining Sciences vol 44 no 4 pp 550ndash564 2007

[24] V Saltas F Vallianatos D Triantis T Koumoudeli andI Stavrakas ldquoNon-extensive statistical analysis of acousticemissions series recorded during the uniaxial compression ofbrittle rocksrdquo Physica A Statistical Mechanics and Its Ap-plications vol 528 Article ID 121498 2019

[25] V Saltas I Fitilis and F Vallianatos ldquoA combined complexelectrical impedance and acoustic emission study in limestonesamples under uniaxial loadingrdquo Tectonophysics vol 637pp 198ndash206 2014

[26] G Qi ldquoWavelet-based AE characterization of compositematerialsrdquo NDTamp E International vol 33 no 3 pp 133ndash1442000

[27] G Manthei J Eisenblatter and T Dahm ldquoMoment tensorevaluation of acoustic emission sources in salt rockrdquo Con-struction and Building Materials vol 15 no 5-6 pp 297ndash3092001

[28] H Jeong and Y-S Jang ldquoWavelet analysis of plate wavepropagation in composite laminatesrdquo Composite Structuresvol 49 no 4 pp 443ndash450 2000

[29] S-H Chang and C-I Lee ldquoEstimation of cracking anddamage mechanisms in rock under triaxial compression bymoment tensor analysis of acoustic emissionrdquo InternationalJournal of Rock Mechanics and Mining Sciences vol 41 no 7pp 1069ndash1086 2004

[30] T Hirata T Satoh and K Ito ldquoFractal structure of spatialdistribution of microfracturing in rockrdquo Geophysical JournalInternational vol 90 no 2 pp 369ndash374 1987

[31] X Lei K Masuda O Nishizawa et al ldquoDetailed analysis ofacoustic emission activity during catastrophic fracture offaults in rockrdquo Journal of Structural Geology vol 26 no 2pp 247ndash258 2004

[32] J Jouniaux J Pei J Liu et al ldquoInvestigation on acousticemission behavior and its time-space evolution mechanism infailure process of coalndashrock combined bodyrdquo Chinese Journalof Rock Mechanics and Engineering vol 30 pp 1564ndash15702011

[33] E Townend B D ompson P M Benson PG MeredithP Baud and R P Young ldquoImaging compaction bandpropagation in Diemelstadt sandstone using acoustic emis-sion locationsrdquo Geophysical Research Letters vol 35 no 15pp 189ndash193 2008

[34] M Naderloo M Moosavi and M Ahmadi ldquoUsing acousticemission technique tomonitor damage progress around jointsin brittle materialsrdquo Deoretical and Applied Fracture Me-chanics vol 104 Article ID 102368 2019

[35] GBT Unified Number of Natural Stone China StandardsPress Beijing China 2009

[36] G Shen Acoustic Emission Detection Technology and Appli-cation Science Press Beijing China 2015

[37] Y Guo Research on Wavelet Base Selection for VibrationSignal Processing Hefei University of Technology HefeiChina 2003

[38] F Xu E Wang and D Song ldquoLong-range correlation andmultifractal distribution of acoustic emission of coal-rockrdquoRock and Soil Mechanics vol 32 no 7 pp 2111ndash2116 2011

Advances in Civil Engineering 19

seen from Figure 11 the energy is widely distributed in thefrequency domain e value of energy is generally smallwhich was mainly concentrated in the range of0ndash36428 kHz Combined with Formulas (5) and (6) it couldbe calculated that the main dominant energy of the three

groups of granite was concentrated in the frequency band of7131ndash12991 kHz which correspondingly accounted for646 5605 and 5828 of the total energy About2326 of the energy in G3561 was concentrated in thefrequency band of 23538ndash35256 kHz which is different

0 05 10 15 20 25ndash15

ndash10

ndash05

0

05

10

Am

plitu

de (m

V)

Time (ms)

G3768

TBG

0 05 10 15 20 25 3ndash08

ndash06

ndash04

ndash02

0

02

04

06

08

Am

plitu

de (m

V)

Time (ms)

G3561

0 05 10 15 20 25

ndash15

ndash10

ndash05

0

05

10

15

Time (ms)

Am

plitu

de (m

V)

AAM

0 05 10 15 2ndash20

ndash15

ndash10

ndash05

0

05

10

15

Time (ms)

Am

plitu

de (m

V)

GAM

0 05 10 15 20 25 30 35ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

Figure 7 Time domain waveform of measuring point M2 of rod-shaped rock

10 Advances in Civil Engineering

from other samples of the same lithology With the increaseof the propagation distance of the elastic wave its energyexhibited the characteristics of rapid attenuation edominant energy distribution frequency bands of the threerod-shaped rock materials at the M2 measuring point ex-panded from the initial 7131ndash12991 kHz to 0ndash17678 kHz

and the energy percentages were 8987 9407 and8658 respectively In the high-frequency band of28225ndash31741 kHz there was respectively 10 and 1269energy concentration for G3768 and TBG When the elasticwave propagated to the end of the rod (M3) the energy ofeach group of samples was relatively concentrated and

0 100 200 300 400 5000

001

002

003

004

Am

plitu

de (m

V)

Frequency (KHz)

G3768

TBG

0 100 200 300 400 5000

001

002

003

Am

plitu

de (m

V)

Frequency (KHz)

G3561

0 100 200 300 400 5000

001

002

003

004

005

006

007

Frequency (KHz)

Am

plitu

de (m

V)

AAM

0 100 200 300 400 5000

001

002

003

004

005

006

Frequency (KHz)

Am

plitu

de (m

V)

GAM

0 100 200 300 400 5000

0002

0004

0006

0008

0010

0012

Am

plitu

de (m

V)

Frequency (KHz)

Figure 8 e spectrogram of measuring point M2 of rod-shaped rock

Advances in Civil Engineering 11

G3761-L(90deg)

0 05 10 15 2ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

G3761-L(90deg)

0 100 200 300 400 500000

002

004

006

008

010

Am

plitu

de (m

V)

Frequency (KHz)

G3761-L(45deg)

0 05 10 15 20 25

ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

G3761-L(45deg)

0 100 200 300 400 5000

001

002

003

004

005

006

007

Am

plitu

de (m

V)

Frequency (KHz)

0 05 10 15 20 25 3ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

G3761-L(0deg)

Am

plitu

de (m

V)

Time (ms)

G3761-L(0deg)

0 100 200 300 400 5000

0002

0004

0006

0008

0010

Am

plitu

de (m

V)

Frequency (KHz)

(a)

Figure 9 Continued

12 Advances in Civil Engineering

mainly distributed within 0ndash10647 kHz at the percentages of9211 9022 and 9188 respectively By comparing thethree groups of rod-shaped rocks with the same lithology itcan be seen that the energy attenuation was the fastest inTBG and the dominant energy value was the lowest at theM3 measuring point For G3768 the energy attenuation wasthe slowest Only the distribution rule of the dominant

energy value at the M2 and M3 measuring points changedwhereas the maximum energy value hardly changed ereason may be that the internal structure or componentdensity of G3768 was better and the energy was relativelymaintained rather than rapidly attenuated with the elasticwave propagation For AAM artificial marble its maindominant energy also exhibited the same change trend as

GAM-L(45deg)

0 05 10 15 20 25

ndash3

ndash2

ndash1

0

1

2

3

4

Am

plitu

de (m

V)

Time (ms)

GAM-L(45deg)

0 100 200 300 400 5000

002

004

006

008

010

012

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(0deg)

0 05 10 15 20 25 30 35

ndash09

ndash06

ndash03

0

03

06

09

Am

plitu

de (m

V)

Time (ms)

GAM-L(0deg)

0 100 200 300 400 5000

0005

0010

0015

0020

0025

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(90deg)

0 05 10 15 20 25ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

GAM-L(90deg)

Am

plitu

de (m

V)

0 100 200 300 400 500000

002

004

006

008

010

Frequency (KHz)

(b)

Figure 9 e time waveform and spectrogram of measuring point M2 of pate-shaped rock

Advances in Civil Engineering 13

0 3 6 9 12 15ndash15

ndash10

ndash05

00

05

10

Wavelet function

0 3 6 9 12 15

ndash05

00

05

10

Scaling function

Figure 10 Wavelet function and scaling function for db7

Table 5 e frequency band range of reconstructed signal by wavelet packet decomposition

Layer S (i 0) S (i 1) S (i 2) S (i jminus 1) S (i j)1 0ndash750 ndash ndash ndash ndash 750ndash15002 0ndash375 375ndash750 750ndash1125 ndash ndash 1125ndash15003 0ndash1875 1875ndash375 375ndash5625 1125ndash13125 13125ndash15004 0ndash9375 9375ndash1875 1875ndash28125 13125ndash140625 140625ndash15005 0ndash46875 46875ndash9375 9375ndash140625 140625ndash1453125 1453125ndash15006 0ndash234375 234375ndash46875 46875ndash703125 1453125ndash14765625 14765625ndash15007 0ndash1171875 1171875ndash234375 234375ndash3515625 14765625ndash148828125 148828125ndash1500S (i j) represents the reconstruction signal of the j-th wavelet packet decomposition coefficient in the i-th layer i 1234 j 012 2i-1

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M3

(a)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500

1000

1500

2000

2500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

20

40

60

80

100

120

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

M3

(b)

Figure 11 Continued

14 Advances in Civil Engineering

granite From Figure 11 it can be observed that the energy ofthe original pulse signal is concentrated in the range of9475ndash16506 kHz and 2185 of the energy existed in thefrequency band of 28225ndash35256 kHz For GAMmarble themain dominant energy distribution of the initial signal wasvery wide and was distributed in the frequency band of0ndash36428 kHz Among them the dominant energy wasdistributed within the 10647ndash12991 kHz range accountingfor 3213 of the total energy Similar attenuation charac-teristics as granite were presented with the increase of elasticwave propagation distance In general for GAM the exci-tation energy of the AE signal generated by pulse excitationwas the weakest and the attenuation was the fastest with theincrease of distancee initial excitation energy of the threegroups of granite was partially concentrated in the frequency

band of 23538ndash35256 kHz of which the performance ofG3561 was the most obvious

e pulse AE signal was very complex for 2 groups of theplate-shaped rocks (Figure 12) erefore the initial energyof the M1 measuring point in each direction was also quitedifferent In the direction of 0deg the dominant energy of theoriginal pulse signal in G3761-L was concentrated in thefrequency band of 0ndash17678 kHz which accounted for8904 of the total energy Meanwhile about 628 of theenergy was distributed in the frequency band of29397ndash32913 kHz e same law was also shown in GAM-L but the main dominant frequency in GAM-L was rela-tively concentrated in the short frequency band of10647ndash17678 kHz which accounted for 6357 of the totalenergy With the spread of the elastic wave the energy in

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50002468

10121416

M3

(c)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5001000150020002500300035004000

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40

50

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M3

(d)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

100

200

300

400

500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M2

0 100 200 300 400 5000

2

4

6

8En

ergy

(mVlowast

mS)

Frequency (KHZ)

M3

0 100 200 300 400 500012345678

(e)

Figure 11e energy distribution of acoustic emission signal frequency band of rod-shaped rock (a) G3768 (b) G3561 (c) TBG (d) AAM(e) GAM

Advances in Civil Engineering 15

0 100 200 300 400 5000

200400600800

100012001400

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

M2

0 100 200 300 400 5000005101520253035

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

M3

0 100 200 300 400 50000020406081012

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

(a)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40En

ergy

(mVlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 5000

2

4

6

8

Ener

gy (m

Vlowast

mS)

(b)

M1

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

1020304050607080

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50002468

1012141618

Ener

gy (m

Vlowast

mS)

(c)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700800

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 50005

101520253035

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

Ener

gy (m

Vlowast

mS)

(d)

Figure 12 Continued

16 Advances in Civil Engineering

G3761-L showed a trend of attenuation and the energy intheM2measuring point was still distributed in the frequencyband of 0ndash17678 kHz e energy distribution at the M3measuring point was relatively concentrated and was locatedin the frequency band of 0ndash10647 kHz accounting for8340 of the total energy e energy at the measuringpoint M3 of GAM-L was more extensive in the frequencydomain and the energy value changed dramatically dem-onstrating the abnormal phenomenon that the maindominant energy increased e frequency range of thismeasuring point was 0ndash1885 kHz accounting for 8589 ofthe total energyere was also residual energy concentratedin the frequency band of 29397ndash32913 kHz e AE signalat M3 was superposed by the boundary reflection wave andthe energy was enhanced because of the high homogeneityand good ductility of GAM-L For G3761-L the dominantenergy of the elastic wave almost dissipated at the M3measuring point In the direction of 45deg the dominantenergy band of the original signal in G3761-L was distributedwithin 0ndash17678 kHz and 28225ndash35256 kHz respectivelyaccounting for 6415 and 3278 of the total energyMoreover it can be observed that the distribution of thedominant energy band was from distribution to concen-tration which was distributed in the frequency band of7131ndash17678 kHz at M2 With the increase of distance theenergy frequency band of the M3 measuring point near theedge of the plate was spread again and it was restored to theenergy frequency band range of the initial signal Howeverthe energy value was attenuated to a very small value at this

moment e energies of GAM-L in the measuring pointsM1 M2 and M3 were all distributed in the frequency bandof 0ndash36428 kHz In the direction of 90deg the primarydominant energy frequency bands of the two plate-shapedrocks were concentrated in 9475ndash1885 kHz e differenceis that the energy distribution of GAM-L was still con-centrated and the energy variation was much smaller thanG3761-L at the M2 measuring point In general the energyfrequency band of the two plate-shaped rocks with differentlithologies was the same as that of the rod-shape rock whichis mainly distributed in the range of 0ndash36428 kHz More-over they also exhibited the characteristics that the maindominant energy was distributed in the range of0ndash17678 kHz and the residual energy was distributed in therange of 28225ndash35256 kHz

4 Discussion

e purpose of this work was to study the propagationcharacteristics of elastic wave in lithological rock materialsrough the above research and analysis a preliminaryunderstanding was obtained Based on the deep waveletpacket analysis of amplitude energy characteristic param-eters and AE waveform the frequency band characteristicsof the local energy distribution of elastic wave with itspropagation were summarized However its propagationcharacteristics are difficult to be regularly grasped becausethe elastic wave itself is extremely complex Furthermore AEtechnology is mostly used in the damage detection and

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

20406080

100120140160

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

10

20

30

40

50

(e)

M1

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

200400600800

10001200140016001800

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

50

100

150

200

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 50005

101520253035

(f )

Figure 12e energy distribution of acoustic emission signal frequency band of plate-shaped rock (a) G3761-L (00) (b) G3761-L (450) (c)G3761-L (900) (d) GAM-L (00) (e) GAM-L (450) (f ) GAM-L (900)

Advances in Civil Engineering 17

defect location of metal or related materials with goodcompactness ductility and within the same medium ereare many uncertain interference factors in the experimentsIn some aspects the analysis of this paper only stays at thelevel of the apparent phenomenon and there are still manydeficiencies and areas worthy of improvement For instancethe density wave velocity and wave impedance of the rod-shaped rock samples should be tested and the micro-structure imaging experiments of the rock samples should beconducted e quality factor Q of different rock samplesshould be calculated Moreover the correlation between thequality factor and wave impedance should be studied andthe influence of different microcompositions of rod-shapedrocks on elastic wave attenuation should be deeply analyzedBased on the modal AE theory the influence of Lamb wavein plate-shaped rocks should be studied and the propagationmodel of two-dimensional AE should be constructed eGabor wavelet should be introduced to analyze the AE signalby time-frequency analysis e influence of differentwavelets based on the propagation effect of AE will becompared and analyzed and the time of the same mode ofthe AE wave arriving at the sensor will be determined tofurther optimize the plane location algorithm However theresearch in this work is still useful for studying large-scalerock samples in the future and provides effective researchmethods and ideas for the study of elastic wave propagationcharacteristics of different rock materials and compositematerials

5 Conclusions

In this work the characteristic parameter analysis andwaveform analysis of the AE signals obtained from differentexperimental schemes in 5 groups of rod-shaped rocks and 2groups of plate-shaped rocks were carried out e con-clusions are as follows

(1) e amplitude and energy of the rod-shaped rocksgradually attenuated with the increase of distancee amplitude can directly reflect the intensity of theAE counts at different measuring areas In theprocess of elastic wave propagation of the rod-sha-ped rock the P-wave preceded the S-wave andchanged violently e elastic wave of marble at-tenuated faster and the elastic wave of the threekinds of granite decayed attenuated closely Amongthem the elastic wave of TBG exhibited the fastestattenuation

(2) In flat plate-shaped rocks the amplitude exhibited anapproximate exponential attenuation characteristicwith the increase of the propagation distanceGranite exhibited a stronger elastic wave attenuationin the 0deg direction than the marble and the marblepresented fast attenuations in the 45deg and 90deg di-rections e energy change of marble was dramaticand the energy value in the interval of 45ndash55 cm atthe direction of 0deg showed the abnormal step phe-nomenon e energy value of the marble increasedafter 55 cm in the 45deg direction e energy value of

granite from the back to the end of the plate wasalmost maintained and tended to be stable at20ndash50mVms

(3) e frequency range of the energy distribution ofsamples in this work was within 0ndash36428 kHz Withthe increase of distance the main dominant energydistribution of the 5 groups of rod-shaped rocks inthe frequency range was characterized by distribu-tion to relative concentration and rapid energy at-tenuationemain dominant energy distribution ofthe 2 groups of plate-shaped rocks was distributed inthe range of 0ndash17678 kHz All rod-shaped rocks andplate-shaped rocks exhibited the characteristics ofresidual energy distribution in the frequency band of28225ndash35256 kHz

Data Availability

e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

e authors certify that they have no conflicts of interest

Acknowledgments

is research was funded by the National Natural ScienceFoundation of China (51804161 52074156 and 52004291)the Chinese Postdoctoral Science Foundation(2019M660861) and the State Key Laboratory CultivationBase for Gas Geology and Gas Control (Henan PolytechnicUniversity) (WS2020A04)

References

[1] J T Chen J H Zhao S C Zhang Y Zhang F Yang andM Li ldquoAn experimental and analytical research on theevolution of mining cracks in deep floor rock massrdquo Pure andApplied Geophysics vol 177 no 11 pp 5325ndash5348 2020

[2] K Wang and F Du ldquoCoal-gas compound dynamic disastersin China a reviewrdquo Process Safety and Environmental Pro-tection vol 133 pp 1ndash17 2020

[3] C Zhu M He M Karakus X Cui and Z Tao ldquoInvestigatingtoppling failure mechanism of anti-dip layered slope due toexcavation by physical modellingrdquo Rock Mechanics and RockEngineering vol 53 no 11 pp 5029ndash5050 2020

[4] X Wang C Liu S Chen L Chen K Li and N Liu ldquoImpactof coal sectorrsquos de-capacity policy on coal pricerdquo AppliedEnergy vol 265 Article ID 114802 2020

[5] D Liu Z Gu R Liang et al ldquoImpacts of pore-throat systemon fractal characterization of tight sandstonesrdquo Geofluidsvol 2020 no 9 17 pages Article ID 4941501 2020

[6] J Wang Y Zhang Z Qin S Song and P Lin ldquoAnalysismethod of water inrush for tunnels with damaged water-resisting rock mass based on finite element method-smoothparticle hydrodynamics couplingrdquo Computers and Geo-technics vol 126 Article ID 103725 2020

[7] B Chen S C Zhang Y Y Li Z K Li and H J ZhouldquoPhysical simulation study of crack propagation and insta-bility information discrimination of rock-like materials withfaultsrdquo Arabian Journal of Geosciences vol 13 p 966 2020

18 Advances in Civil Engineering

[8] F Du K Wang X Zhang C Xin and G Wang ldquoExperi-mental study of coal-gas outburst insights from coal-rockstructure gas pressure and adsorptivityrdquo Natural ResourcesResearch vol 29 no 4 pp 2481ndash2493 2020

[9] H Y Wang J Ma G D Wang et al ldquoResearch on AE sourcelocation of linear and plane rock massrdquo Shock and Vibrationvol 2020 Article ID 8846582 18 pages 2020

[10] V A Mansurov ldquoPrediction of rockbursts by analysis ofinduced seismicity datardquo International Journal of Rock Me-chanics and Mining Sciences vol 38 no 6 pp 893ndash901 2001

[11] M C He J L Miao and J L Feng ldquoRock burst process oflimestone and its acoustic emission characteristics under true-triaxial unloading conditionsrdquo International Journal of RockMechanics and Mining Sciences vol 47 no 2 pp 286ndash2982010

[12] F Gong J Yan X Li and S Luo ldquoA peak-strength strainenergy storage index for rock burst proneness of rock ma-terialsrdquo International Journal of Rock Mechanics and MiningSciences vol 117 pp 76ndash89 2019

[13] F Du and KWang ldquoUnstable failure of gas-bearing coal-rockcombination bodies insights from physical experiments andnumerical simulationsrdquo Process Safety and EnvironmentalProtection vol 129 pp 264ndash279 2019

[14] S D Butt C Mukherjee and G Lebans ldquoEvaluation ofacoustic attenuation as an indicator of roof stability in ad-vancing headingsrdquo International Journal of Rock Mechanicsand Mining Sciences vol 37 no 7 pp 1123ndash1131 2000

[15] M Cai H Morioka P K Kaiser et al ldquoBack-analysis of rockmass strength parameters using ae monitoring datardquo Inter-national Journal of Rock Mechanics and Mining Sciencesvol 44 no 4 pp 538ndash549 2007

[16] D P Jansen S R Carlson R P Young and D A HutchinsldquoUltrasonic imaging and acoustic emission monitoring ofthermally induced microcracks in Lac du Bonnet graniterdquoJournal of Geophysical Research Solid Earth vol 98 no B12pp 22231ndash22243 1993

[17] U Bismayer ldquoEarly warning signs for mining accidentsdetecting crackling noiserdquo American Mineralogist vol 102no 1 pp 3-4 2017

[18] X Kong E Wang S Li H Lin P Xiao and K ZhangldquoFractals and chaos characteristics of acoustic emission energyabout gas-bearing coal during loaded failurerdquo Fractals vol 27no 5 Article ID 195072 2019

[19] F Du K Wang G Wang Y Jiang C Xin and X ZhangldquoInvestigation of the acoustic emission characteristics duringdeformation and failure of gas-bearing coal-rock combinedbodiesrdquo Journal of Loss Prevention in the Process Industriesvol 55 pp 253ndash266 2018

[20] R P Young D A Hutchins S Talebi et al ldquoLaboratory andfield investigations of rockburst phenomena using concurrentgeotomographic imaging and acoustic emissionmicroseismictechniquesrdquo Seismicity in Mines vol 129 no 3-4pp 647ndash659 1989

[21] X Jansen H Xu M He and F Zhang ldquoExperimental in-vestigation of the occurrence of rockburst in a rock specimenthrough infrared thermography and acoustic emissionrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 93 pp 250ndash259 2017

[22] R E Goodman and E Richard ldquoSubaudible noise duringcompression of rocksrdquo Geological Society of America Bulletinvol 74 no 4 pp 487ndash490 1963

[23] M Cai P K Kaiser H Morioka et al ldquoFLACPFC couplednumerical simulation of AE in large-scale underground

excavationsrdquo International Journal of Rock Mechanics andMining Sciences vol 44 no 4 pp 550ndash564 2007

[24] V Saltas F Vallianatos D Triantis T Koumoudeli andI Stavrakas ldquoNon-extensive statistical analysis of acousticemissions series recorded during the uniaxial compression ofbrittle rocksrdquo Physica A Statistical Mechanics and Its Ap-plications vol 528 Article ID 121498 2019

[25] V Saltas I Fitilis and F Vallianatos ldquoA combined complexelectrical impedance and acoustic emission study in limestonesamples under uniaxial loadingrdquo Tectonophysics vol 637pp 198ndash206 2014

[26] G Qi ldquoWavelet-based AE characterization of compositematerialsrdquo NDTamp E International vol 33 no 3 pp 133ndash1442000

[27] G Manthei J Eisenblatter and T Dahm ldquoMoment tensorevaluation of acoustic emission sources in salt rockrdquo Con-struction and Building Materials vol 15 no 5-6 pp 297ndash3092001

[28] H Jeong and Y-S Jang ldquoWavelet analysis of plate wavepropagation in composite laminatesrdquo Composite Structuresvol 49 no 4 pp 443ndash450 2000

[29] S-H Chang and C-I Lee ldquoEstimation of cracking anddamage mechanisms in rock under triaxial compression bymoment tensor analysis of acoustic emissionrdquo InternationalJournal of Rock Mechanics and Mining Sciences vol 41 no 7pp 1069ndash1086 2004

[30] T Hirata T Satoh and K Ito ldquoFractal structure of spatialdistribution of microfracturing in rockrdquo Geophysical JournalInternational vol 90 no 2 pp 369ndash374 1987

[31] X Lei K Masuda O Nishizawa et al ldquoDetailed analysis ofacoustic emission activity during catastrophic fracture offaults in rockrdquo Journal of Structural Geology vol 26 no 2pp 247ndash258 2004

[32] J Jouniaux J Pei J Liu et al ldquoInvestigation on acousticemission behavior and its time-space evolution mechanism infailure process of coalndashrock combined bodyrdquo Chinese Journalof Rock Mechanics and Engineering vol 30 pp 1564ndash15702011

[33] E Townend B D ompson P M Benson PG MeredithP Baud and R P Young ldquoImaging compaction bandpropagation in Diemelstadt sandstone using acoustic emis-sion locationsrdquo Geophysical Research Letters vol 35 no 15pp 189ndash193 2008

[34] M Naderloo M Moosavi and M Ahmadi ldquoUsing acousticemission technique tomonitor damage progress around jointsin brittle materialsrdquo Deoretical and Applied Fracture Me-chanics vol 104 Article ID 102368 2019

[35] GBT Unified Number of Natural Stone China StandardsPress Beijing China 2009

[36] G Shen Acoustic Emission Detection Technology and Appli-cation Science Press Beijing China 2015

[37] Y Guo Research on Wavelet Base Selection for VibrationSignal Processing Hefei University of Technology HefeiChina 2003

[38] F Xu E Wang and D Song ldquoLong-range correlation andmultifractal distribution of acoustic emission of coal-rockrdquoRock and Soil Mechanics vol 32 no 7 pp 2111ndash2116 2011

Advances in Civil Engineering 19

from other samples of the same lithology With the increaseof the propagation distance of the elastic wave its energyexhibited the characteristics of rapid attenuation edominant energy distribution frequency bands of the threerod-shaped rock materials at the M2 measuring point ex-panded from the initial 7131ndash12991 kHz to 0ndash17678 kHz

and the energy percentages were 8987 9407 and8658 respectively In the high-frequency band of28225ndash31741 kHz there was respectively 10 and 1269energy concentration for G3768 and TBG When the elasticwave propagated to the end of the rod (M3) the energy ofeach group of samples was relatively concentrated and

0 100 200 300 400 5000

001

002

003

004

Am

plitu

de (m

V)

Frequency (KHz)

G3768

TBG

0 100 200 300 400 5000

001

002

003

Am

plitu

de (m

V)

Frequency (KHz)

G3561

0 100 200 300 400 5000

001

002

003

004

005

006

007

Frequency (KHz)

Am

plitu

de (m

V)

AAM

0 100 200 300 400 5000

001

002

003

004

005

006

Frequency (KHz)

Am

plitu

de (m

V)

GAM

0 100 200 300 400 5000

0002

0004

0006

0008

0010

0012

Am

plitu

de (m

V)

Frequency (KHz)

Figure 8 e spectrogram of measuring point M2 of rod-shaped rock

Advances in Civil Engineering 11

G3761-L(90deg)

0 05 10 15 2ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

G3761-L(90deg)

0 100 200 300 400 500000

002

004

006

008

010

Am

plitu

de (m

V)

Frequency (KHz)

G3761-L(45deg)

0 05 10 15 20 25

ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

G3761-L(45deg)

0 100 200 300 400 5000

001

002

003

004

005

006

007

Am

plitu

de (m

V)

Frequency (KHz)

0 05 10 15 20 25 3ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

G3761-L(0deg)

Am

plitu

de (m

V)

Time (ms)

G3761-L(0deg)

0 100 200 300 400 5000

0002

0004

0006

0008

0010

Am

plitu

de (m

V)

Frequency (KHz)

(a)

Figure 9 Continued

12 Advances in Civil Engineering

mainly distributed within 0ndash10647 kHz at the percentages of9211 9022 and 9188 respectively By comparing thethree groups of rod-shaped rocks with the same lithology itcan be seen that the energy attenuation was the fastest inTBG and the dominant energy value was the lowest at theM3 measuring point For G3768 the energy attenuation wasthe slowest Only the distribution rule of the dominant

energy value at the M2 and M3 measuring points changedwhereas the maximum energy value hardly changed ereason may be that the internal structure or componentdensity of G3768 was better and the energy was relativelymaintained rather than rapidly attenuated with the elasticwave propagation For AAM artificial marble its maindominant energy also exhibited the same change trend as

GAM-L(45deg)

0 05 10 15 20 25

ndash3

ndash2

ndash1

0

1

2

3

4

Am

plitu

de (m

V)

Time (ms)

GAM-L(45deg)

0 100 200 300 400 5000

002

004

006

008

010

012

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(0deg)

0 05 10 15 20 25 30 35

ndash09

ndash06

ndash03

0

03

06

09

Am

plitu

de (m

V)

Time (ms)

GAM-L(0deg)

0 100 200 300 400 5000

0005

0010

0015

0020

0025

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(90deg)

0 05 10 15 20 25ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

GAM-L(90deg)

Am

plitu

de (m

V)

0 100 200 300 400 500000

002

004

006

008

010

Frequency (KHz)

(b)

Figure 9 e time waveform and spectrogram of measuring point M2 of pate-shaped rock

Advances in Civil Engineering 13

0 3 6 9 12 15ndash15

ndash10

ndash05

00

05

10

Wavelet function

0 3 6 9 12 15

ndash05

00

05

10

Scaling function

Figure 10 Wavelet function and scaling function for db7

Table 5 e frequency band range of reconstructed signal by wavelet packet decomposition

Layer S (i 0) S (i 1) S (i 2) S (i jminus 1) S (i j)1 0ndash750 ndash ndash ndash ndash 750ndash15002 0ndash375 375ndash750 750ndash1125 ndash ndash 1125ndash15003 0ndash1875 1875ndash375 375ndash5625 1125ndash13125 13125ndash15004 0ndash9375 9375ndash1875 1875ndash28125 13125ndash140625 140625ndash15005 0ndash46875 46875ndash9375 9375ndash140625 140625ndash1453125 1453125ndash15006 0ndash234375 234375ndash46875 46875ndash703125 1453125ndash14765625 14765625ndash15007 0ndash1171875 1171875ndash234375 234375ndash3515625 14765625ndash148828125 148828125ndash1500S (i j) represents the reconstruction signal of the j-th wavelet packet decomposition coefficient in the i-th layer i 1234 j 012 2i-1

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M3

(a)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500

1000

1500

2000

2500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

20

40

60

80

100

120

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

M3

(b)

Figure 11 Continued

14 Advances in Civil Engineering

granite From Figure 11 it can be observed that the energy ofthe original pulse signal is concentrated in the range of9475ndash16506 kHz and 2185 of the energy existed in thefrequency band of 28225ndash35256 kHz For GAMmarble themain dominant energy distribution of the initial signal wasvery wide and was distributed in the frequency band of0ndash36428 kHz Among them the dominant energy wasdistributed within the 10647ndash12991 kHz range accountingfor 3213 of the total energy Similar attenuation charac-teristics as granite were presented with the increase of elasticwave propagation distance In general for GAM the exci-tation energy of the AE signal generated by pulse excitationwas the weakest and the attenuation was the fastest with theincrease of distancee initial excitation energy of the threegroups of granite was partially concentrated in the frequency

band of 23538ndash35256 kHz of which the performance ofG3561 was the most obvious

e pulse AE signal was very complex for 2 groups of theplate-shaped rocks (Figure 12) erefore the initial energyof the M1 measuring point in each direction was also quitedifferent In the direction of 0deg the dominant energy of theoriginal pulse signal in G3761-L was concentrated in thefrequency band of 0ndash17678 kHz which accounted for8904 of the total energy Meanwhile about 628 of theenergy was distributed in the frequency band of29397ndash32913 kHz e same law was also shown in GAM-L but the main dominant frequency in GAM-L was rela-tively concentrated in the short frequency band of10647ndash17678 kHz which accounted for 6357 of the totalenergy With the spread of the elastic wave the energy in

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50002468

10121416

M3

(c)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5001000150020002500300035004000

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40

50

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M3

(d)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

100

200

300

400

500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M2

0 100 200 300 400 5000

2

4

6

8En

ergy

(mVlowast

mS)

Frequency (KHZ)

M3

0 100 200 300 400 500012345678

(e)

Figure 11e energy distribution of acoustic emission signal frequency band of rod-shaped rock (a) G3768 (b) G3561 (c) TBG (d) AAM(e) GAM

Advances in Civil Engineering 15

0 100 200 300 400 5000

200400600800

100012001400

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

M2

0 100 200 300 400 5000005101520253035

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

M3

0 100 200 300 400 50000020406081012

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

(a)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40En

ergy

(mVlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 5000

2

4

6

8

Ener

gy (m

Vlowast

mS)

(b)

M1

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

1020304050607080

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50002468

1012141618

Ener

gy (m

Vlowast

mS)

(c)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700800

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 50005

101520253035

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

Ener

gy (m

Vlowast

mS)

(d)

Figure 12 Continued

16 Advances in Civil Engineering

G3761-L showed a trend of attenuation and the energy intheM2measuring point was still distributed in the frequencyband of 0ndash17678 kHz e energy distribution at the M3measuring point was relatively concentrated and was locatedin the frequency band of 0ndash10647 kHz accounting for8340 of the total energy e energy at the measuringpoint M3 of GAM-L was more extensive in the frequencydomain and the energy value changed dramatically dem-onstrating the abnormal phenomenon that the maindominant energy increased e frequency range of thismeasuring point was 0ndash1885 kHz accounting for 8589 ofthe total energyere was also residual energy concentratedin the frequency band of 29397ndash32913 kHz e AE signalat M3 was superposed by the boundary reflection wave andthe energy was enhanced because of the high homogeneityand good ductility of GAM-L For G3761-L the dominantenergy of the elastic wave almost dissipated at the M3measuring point In the direction of 45deg the dominantenergy band of the original signal in G3761-L was distributedwithin 0ndash17678 kHz and 28225ndash35256 kHz respectivelyaccounting for 6415 and 3278 of the total energyMoreover it can be observed that the distribution of thedominant energy band was from distribution to concen-tration which was distributed in the frequency band of7131ndash17678 kHz at M2 With the increase of distance theenergy frequency band of the M3 measuring point near theedge of the plate was spread again and it was restored to theenergy frequency band range of the initial signal Howeverthe energy value was attenuated to a very small value at this

moment e energies of GAM-L in the measuring pointsM1 M2 and M3 were all distributed in the frequency bandof 0ndash36428 kHz In the direction of 90deg the primarydominant energy frequency bands of the two plate-shapedrocks were concentrated in 9475ndash1885 kHz e differenceis that the energy distribution of GAM-L was still con-centrated and the energy variation was much smaller thanG3761-L at the M2 measuring point In general the energyfrequency band of the two plate-shaped rocks with differentlithologies was the same as that of the rod-shape rock whichis mainly distributed in the range of 0ndash36428 kHz More-over they also exhibited the characteristics that the maindominant energy was distributed in the range of0ndash17678 kHz and the residual energy was distributed in therange of 28225ndash35256 kHz

4 Discussion

e purpose of this work was to study the propagationcharacteristics of elastic wave in lithological rock materialsrough the above research and analysis a preliminaryunderstanding was obtained Based on the deep waveletpacket analysis of amplitude energy characteristic param-eters and AE waveform the frequency band characteristicsof the local energy distribution of elastic wave with itspropagation were summarized However its propagationcharacteristics are difficult to be regularly grasped becausethe elastic wave itself is extremely complex Furthermore AEtechnology is mostly used in the damage detection and

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

20406080

100120140160

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

10

20

30

40

50

(e)

M1

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

200400600800

10001200140016001800

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

50

100

150

200

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 50005

101520253035

(f )

Figure 12e energy distribution of acoustic emission signal frequency band of plate-shaped rock (a) G3761-L (00) (b) G3761-L (450) (c)G3761-L (900) (d) GAM-L (00) (e) GAM-L (450) (f ) GAM-L (900)

Advances in Civil Engineering 17

defect location of metal or related materials with goodcompactness ductility and within the same medium ereare many uncertain interference factors in the experimentsIn some aspects the analysis of this paper only stays at thelevel of the apparent phenomenon and there are still manydeficiencies and areas worthy of improvement For instancethe density wave velocity and wave impedance of the rod-shaped rock samples should be tested and the micro-structure imaging experiments of the rock samples should beconducted e quality factor Q of different rock samplesshould be calculated Moreover the correlation between thequality factor and wave impedance should be studied andthe influence of different microcompositions of rod-shapedrocks on elastic wave attenuation should be deeply analyzedBased on the modal AE theory the influence of Lamb wavein plate-shaped rocks should be studied and the propagationmodel of two-dimensional AE should be constructed eGabor wavelet should be introduced to analyze the AE signalby time-frequency analysis e influence of differentwavelets based on the propagation effect of AE will becompared and analyzed and the time of the same mode ofthe AE wave arriving at the sensor will be determined tofurther optimize the plane location algorithm However theresearch in this work is still useful for studying large-scalerock samples in the future and provides effective researchmethods and ideas for the study of elastic wave propagationcharacteristics of different rock materials and compositematerials

5 Conclusions

In this work the characteristic parameter analysis andwaveform analysis of the AE signals obtained from differentexperimental schemes in 5 groups of rod-shaped rocks and 2groups of plate-shaped rocks were carried out e con-clusions are as follows

(1) e amplitude and energy of the rod-shaped rocksgradually attenuated with the increase of distancee amplitude can directly reflect the intensity of theAE counts at different measuring areas In theprocess of elastic wave propagation of the rod-sha-ped rock the P-wave preceded the S-wave andchanged violently e elastic wave of marble at-tenuated faster and the elastic wave of the threekinds of granite decayed attenuated closely Amongthem the elastic wave of TBG exhibited the fastestattenuation

(2) In flat plate-shaped rocks the amplitude exhibited anapproximate exponential attenuation characteristicwith the increase of the propagation distanceGranite exhibited a stronger elastic wave attenuationin the 0deg direction than the marble and the marblepresented fast attenuations in the 45deg and 90deg di-rections e energy change of marble was dramaticand the energy value in the interval of 45ndash55 cm atthe direction of 0deg showed the abnormal step phe-nomenon e energy value of the marble increasedafter 55 cm in the 45deg direction e energy value of

granite from the back to the end of the plate wasalmost maintained and tended to be stable at20ndash50mVms

(3) e frequency range of the energy distribution ofsamples in this work was within 0ndash36428 kHz Withthe increase of distance the main dominant energydistribution of the 5 groups of rod-shaped rocks inthe frequency range was characterized by distribu-tion to relative concentration and rapid energy at-tenuationemain dominant energy distribution ofthe 2 groups of plate-shaped rocks was distributed inthe range of 0ndash17678 kHz All rod-shaped rocks andplate-shaped rocks exhibited the characteristics ofresidual energy distribution in the frequency band of28225ndash35256 kHz

Data Availability

e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

e authors certify that they have no conflicts of interest

Acknowledgments

is research was funded by the National Natural ScienceFoundation of China (51804161 52074156 and 52004291)the Chinese Postdoctoral Science Foundation(2019M660861) and the State Key Laboratory CultivationBase for Gas Geology and Gas Control (Henan PolytechnicUniversity) (WS2020A04)

References

[1] J T Chen J H Zhao S C Zhang Y Zhang F Yang andM Li ldquoAn experimental and analytical research on theevolution of mining cracks in deep floor rock massrdquo Pure andApplied Geophysics vol 177 no 11 pp 5325ndash5348 2020

[2] K Wang and F Du ldquoCoal-gas compound dynamic disastersin China a reviewrdquo Process Safety and Environmental Pro-tection vol 133 pp 1ndash17 2020

[3] C Zhu M He M Karakus X Cui and Z Tao ldquoInvestigatingtoppling failure mechanism of anti-dip layered slope due toexcavation by physical modellingrdquo Rock Mechanics and RockEngineering vol 53 no 11 pp 5029ndash5050 2020

[4] X Wang C Liu S Chen L Chen K Li and N Liu ldquoImpactof coal sectorrsquos de-capacity policy on coal pricerdquo AppliedEnergy vol 265 Article ID 114802 2020

[5] D Liu Z Gu R Liang et al ldquoImpacts of pore-throat systemon fractal characterization of tight sandstonesrdquo Geofluidsvol 2020 no 9 17 pages Article ID 4941501 2020

[6] J Wang Y Zhang Z Qin S Song and P Lin ldquoAnalysismethod of water inrush for tunnels with damaged water-resisting rock mass based on finite element method-smoothparticle hydrodynamics couplingrdquo Computers and Geo-technics vol 126 Article ID 103725 2020

[7] B Chen S C Zhang Y Y Li Z K Li and H J ZhouldquoPhysical simulation study of crack propagation and insta-bility information discrimination of rock-like materials withfaultsrdquo Arabian Journal of Geosciences vol 13 p 966 2020

18 Advances in Civil Engineering

[8] F Du K Wang X Zhang C Xin and G Wang ldquoExperi-mental study of coal-gas outburst insights from coal-rockstructure gas pressure and adsorptivityrdquo Natural ResourcesResearch vol 29 no 4 pp 2481ndash2493 2020

[9] H Y Wang J Ma G D Wang et al ldquoResearch on AE sourcelocation of linear and plane rock massrdquo Shock and Vibrationvol 2020 Article ID 8846582 18 pages 2020

[10] V A Mansurov ldquoPrediction of rockbursts by analysis ofinduced seismicity datardquo International Journal of Rock Me-chanics and Mining Sciences vol 38 no 6 pp 893ndash901 2001

[11] M C He J L Miao and J L Feng ldquoRock burst process oflimestone and its acoustic emission characteristics under true-triaxial unloading conditionsrdquo International Journal of RockMechanics and Mining Sciences vol 47 no 2 pp 286ndash2982010

[12] F Gong J Yan X Li and S Luo ldquoA peak-strength strainenergy storage index for rock burst proneness of rock ma-terialsrdquo International Journal of Rock Mechanics and MiningSciences vol 117 pp 76ndash89 2019

[13] F Du and KWang ldquoUnstable failure of gas-bearing coal-rockcombination bodies insights from physical experiments andnumerical simulationsrdquo Process Safety and EnvironmentalProtection vol 129 pp 264ndash279 2019

[14] S D Butt C Mukherjee and G Lebans ldquoEvaluation ofacoustic attenuation as an indicator of roof stability in ad-vancing headingsrdquo International Journal of Rock Mechanicsand Mining Sciences vol 37 no 7 pp 1123ndash1131 2000

[15] M Cai H Morioka P K Kaiser et al ldquoBack-analysis of rockmass strength parameters using ae monitoring datardquo Inter-national Journal of Rock Mechanics and Mining Sciencesvol 44 no 4 pp 538ndash549 2007

[16] D P Jansen S R Carlson R P Young and D A HutchinsldquoUltrasonic imaging and acoustic emission monitoring ofthermally induced microcracks in Lac du Bonnet graniterdquoJournal of Geophysical Research Solid Earth vol 98 no B12pp 22231ndash22243 1993

[17] U Bismayer ldquoEarly warning signs for mining accidentsdetecting crackling noiserdquo American Mineralogist vol 102no 1 pp 3-4 2017

[18] X Kong E Wang S Li H Lin P Xiao and K ZhangldquoFractals and chaos characteristics of acoustic emission energyabout gas-bearing coal during loaded failurerdquo Fractals vol 27no 5 Article ID 195072 2019

[19] F Du K Wang G Wang Y Jiang C Xin and X ZhangldquoInvestigation of the acoustic emission characteristics duringdeformation and failure of gas-bearing coal-rock combinedbodiesrdquo Journal of Loss Prevention in the Process Industriesvol 55 pp 253ndash266 2018

[20] R P Young D A Hutchins S Talebi et al ldquoLaboratory andfield investigations of rockburst phenomena using concurrentgeotomographic imaging and acoustic emissionmicroseismictechniquesrdquo Seismicity in Mines vol 129 no 3-4pp 647ndash659 1989

[21] X Jansen H Xu M He and F Zhang ldquoExperimental in-vestigation of the occurrence of rockburst in a rock specimenthrough infrared thermography and acoustic emissionrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 93 pp 250ndash259 2017

[22] R E Goodman and E Richard ldquoSubaudible noise duringcompression of rocksrdquo Geological Society of America Bulletinvol 74 no 4 pp 487ndash490 1963

[23] M Cai P K Kaiser H Morioka et al ldquoFLACPFC couplednumerical simulation of AE in large-scale underground

excavationsrdquo International Journal of Rock Mechanics andMining Sciences vol 44 no 4 pp 550ndash564 2007

[24] V Saltas F Vallianatos D Triantis T Koumoudeli andI Stavrakas ldquoNon-extensive statistical analysis of acousticemissions series recorded during the uniaxial compression ofbrittle rocksrdquo Physica A Statistical Mechanics and Its Ap-plications vol 528 Article ID 121498 2019

[25] V Saltas I Fitilis and F Vallianatos ldquoA combined complexelectrical impedance and acoustic emission study in limestonesamples under uniaxial loadingrdquo Tectonophysics vol 637pp 198ndash206 2014

[26] G Qi ldquoWavelet-based AE characterization of compositematerialsrdquo NDTamp E International vol 33 no 3 pp 133ndash1442000

[27] G Manthei J Eisenblatter and T Dahm ldquoMoment tensorevaluation of acoustic emission sources in salt rockrdquo Con-struction and Building Materials vol 15 no 5-6 pp 297ndash3092001

[28] H Jeong and Y-S Jang ldquoWavelet analysis of plate wavepropagation in composite laminatesrdquo Composite Structuresvol 49 no 4 pp 443ndash450 2000

[29] S-H Chang and C-I Lee ldquoEstimation of cracking anddamage mechanisms in rock under triaxial compression bymoment tensor analysis of acoustic emissionrdquo InternationalJournal of Rock Mechanics and Mining Sciences vol 41 no 7pp 1069ndash1086 2004

[30] T Hirata T Satoh and K Ito ldquoFractal structure of spatialdistribution of microfracturing in rockrdquo Geophysical JournalInternational vol 90 no 2 pp 369ndash374 1987

[31] X Lei K Masuda O Nishizawa et al ldquoDetailed analysis ofacoustic emission activity during catastrophic fracture offaults in rockrdquo Journal of Structural Geology vol 26 no 2pp 247ndash258 2004

[32] J Jouniaux J Pei J Liu et al ldquoInvestigation on acousticemission behavior and its time-space evolution mechanism infailure process of coalndashrock combined bodyrdquo Chinese Journalof Rock Mechanics and Engineering vol 30 pp 1564ndash15702011

[33] E Townend B D ompson P M Benson PG MeredithP Baud and R P Young ldquoImaging compaction bandpropagation in Diemelstadt sandstone using acoustic emis-sion locationsrdquo Geophysical Research Letters vol 35 no 15pp 189ndash193 2008

[34] M Naderloo M Moosavi and M Ahmadi ldquoUsing acousticemission technique tomonitor damage progress around jointsin brittle materialsrdquo Deoretical and Applied Fracture Me-chanics vol 104 Article ID 102368 2019

[35] GBT Unified Number of Natural Stone China StandardsPress Beijing China 2009

[36] G Shen Acoustic Emission Detection Technology and Appli-cation Science Press Beijing China 2015

[37] Y Guo Research on Wavelet Base Selection for VibrationSignal Processing Hefei University of Technology HefeiChina 2003

[38] F Xu E Wang and D Song ldquoLong-range correlation andmultifractal distribution of acoustic emission of coal-rockrdquoRock and Soil Mechanics vol 32 no 7 pp 2111ndash2116 2011

Advances in Civil Engineering 19

G3761-L(90deg)

0 05 10 15 2ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

G3761-L(90deg)

0 100 200 300 400 500000

002

004

006

008

010

Am

plitu

de (m

V)

Frequency (KHz)

G3761-L(45deg)

0 05 10 15 20 25

ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

Am

plitu

de (m

V)

Time (ms)

G3761-L(45deg)

0 100 200 300 400 5000

001

002

003

004

005

006

007

Am

plitu

de (m

V)

Frequency (KHz)

0 05 10 15 20 25 3ndash04

ndash03

ndash02

ndash01

0

01

02

03

04

G3761-L(0deg)

Am

plitu

de (m

V)

Time (ms)

G3761-L(0deg)

0 100 200 300 400 5000

0002

0004

0006

0008

0010

Am

plitu

de (m

V)

Frequency (KHz)

(a)

Figure 9 Continued

12 Advances in Civil Engineering

mainly distributed within 0ndash10647 kHz at the percentages of9211 9022 and 9188 respectively By comparing thethree groups of rod-shaped rocks with the same lithology itcan be seen that the energy attenuation was the fastest inTBG and the dominant energy value was the lowest at theM3 measuring point For G3768 the energy attenuation wasthe slowest Only the distribution rule of the dominant

energy value at the M2 and M3 measuring points changedwhereas the maximum energy value hardly changed ereason may be that the internal structure or componentdensity of G3768 was better and the energy was relativelymaintained rather than rapidly attenuated with the elasticwave propagation For AAM artificial marble its maindominant energy also exhibited the same change trend as

GAM-L(45deg)

0 05 10 15 20 25

ndash3

ndash2

ndash1

0

1

2

3

4

Am

plitu

de (m

V)

Time (ms)

GAM-L(45deg)

0 100 200 300 400 5000

002

004

006

008

010

012

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(0deg)

0 05 10 15 20 25 30 35

ndash09

ndash06

ndash03

0

03

06

09

Am

plitu

de (m

V)

Time (ms)

GAM-L(0deg)

0 100 200 300 400 5000

0005

0010

0015

0020

0025

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(90deg)

0 05 10 15 20 25ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

GAM-L(90deg)

Am

plitu

de (m

V)

0 100 200 300 400 500000

002

004

006

008

010

Frequency (KHz)

(b)

Figure 9 e time waveform and spectrogram of measuring point M2 of pate-shaped rock

Advances in Civil Engineering 13

0 3 6 9 12 15ndash15

ndash10

ndash05

00

05

10

Wavelet function

0 3 6 9 12 15

ndash05

00

05

10

Scaling function

Figure 10 Wavelet function and scaling function for db7

Table 5 e frequency band range of reconstructed signal by wavelet packet decomposition

Layer S (i 0) S (i 1) S (i 2) S (i jminus 1) S (i j)1 0ndash750 ndash ndash ndash ndash 750ndash15002 0ndash375 375ndash750 750ndash1125 ndash ndash 1125ndash15003 0ndash1875 1875ndash375 375ndash5625 1125ndash13125 13125ndash15004 0ndash9375 9375ndash1875 1875ndash28125 13125ndash140625 140625ndash15005 0ndash46875 46875ndash9375 9375ndash140625 140625ndash1453125 1453125ndash15006 0ndash234375 234375ndash46875 46875ndash703125 1453125ndash14765625 14765625ndash15007 0ndash1171875 1171875ndash234375 234375ndash3515625 14765625ndash148828125 148828125ndash1500S (i j) represents the reconstruction signal of the j-th wavelet packet decomposition coefficient in the i-th layer i 1234 j 012 2i-1

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M3

(a)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500

1000

1500

2000

2500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

20

40

60

80

100

120

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

M3

(b)

Figure 11 Continued

14 Advances in Civil Engineering

granite From Figure 11 it can be observed that the energy ofthe original pulse signal is concentrated in the range of9475ndash16506 kHz and 2185 of the energy existed in thefrequency band of 28225ndash35256 kHz For GAMmarble themain dominant energy distribution of the initial signal wasvery wide and was distributed in the frequency band of0ndash36428 kHz Among them the dominant energy wasdistributed within the 10647ndash12991 kHz range accountingfor 3213 of the total energy Similar attenuation charac-teristics as granite were presented with the increase of elasticwave propagation distance In general for GAM the exci-tation energy of the AE signal generated by pulse excitationwas the weakest and the attenuation was the fastest with theincrease of distancee initial excitation energy of the threegroups of granite was partially concentrated in the frequency

band of 23538ndash35256 kHz of which the performance ofG3561 was the most obvious

e pulse AE signal was very complex for 2 groups of theplate-shaped rocks (Figure 12) erefore the initial energyof the M1 measuring point in each direction was also quitedifferent In the direction of 0deg the dominant energy of theoriginal pulse signal in G3761-L was concentrated in thefrequency band of 0ndash17678 kHz which accounted for8904 of the total energy Meanwhile about 628 of theenergy was distributed in the frequency band of29397ndash32913 kHz e same law was also shown in GAM-L but the main dominant frequency in GAM-L was rela-tively concentrated in the short frequency band of10647ndash17678 kHz which accounted for 6357 of the totalenergy With the spread of the elastic wave the energy in

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50002468

10121416

M3

(c)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5001000150020002500300035004000

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40

50

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M3

(d)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

100

200

300

400

500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M2

0 100 200 300 400 5000

2

4

6

8En

ergy

(mVlowast

mS)

Frequency (KHZ)

M3

0 100 200 300 400 500012345678

(e)

Figure 11e energy distribution of acoustic emission signal frequency band of rod-shaped rock (a) G3768 (b) G3561 (c) TBG (d) AAM(e) GAM

Advances in Civil Engineering 15

0 100 200 300 400 5000

200400600800

100012001400

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

M2

0 100 200 300 400 5000005101520253035

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

M3

0 100 200 300 400 50000020406081012

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

(a)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40En

ergy

(mVlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 5000

2

4

6

8

Ener

gy (m

Vlowast

mS)

(b)

M1

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

1020304050607080

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50002468

1012141618

Ener

gy (m

Vlowast

mS)

(c)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700800

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 50005

101520253035

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

Ener

gy (m

Vlowast

mS)

(d)

Figure 12 Continued

16 Advances in Civil Engineering

G3761-L showed a trend of attenuation and the energy intheM2measuring point was still distributed in the frequencyband of 0ndash17678 kHz e energy distribution at the M3measuring point was relatively concentrated and was locatedin the frequency band of 0ndash10647 kHz accounting for8340 of the total energy e energy at the measuringpoint M3 of GAM-L was more extensive in the frequencydomain and the energy value changed dramatically dem-onstrating the abnormal phenomenon that the maindominant energy increased e frequency range of thismeasuring point was 0ndash1885 kHz accounting for 8589 ofthe total energyere was also residual energy concentratedin the frequency band of 29397ndash32913 kHz e AE signalat M3 was superposed by the boundary reflection wave andthe energy was enhanced because of the high homogeneityand good ductility of GAM-L For G3761-L the dominantenergy of the elastic wave almost dissipated at the M3measuring point In the direction of 45deg the dominantenergy band of the original signal in G3761-L was distributedwithin 0ndash17678 kHz and 28225ndash35256 kHz respectivelyaccounting for 6415 and 3278 of the total energyMoreover it can be observed that the distribution of thedominant energy band was from distribution to concen-tration which was distributed in the frequency band of7131ndash17678 kHz at M2 With the increase of distance theenergy frequency band of the M3 measuring point near theedge of the plate was spread again and it was restored to theenergy frequency band range of the initial signal Howeverthe energy value was attenuated to a very small value at this

moment e energies of GAM-L in the measuring pointsM1 M2 and M3 were all distributed in the frequency bandof 0ndash36428 kHz In the direction of 90deg the primarydominant energy frequency bands of the two plate-shapedrocks were concentrated in 9475ndash1885 kHz e differenceis that the energy distribution of GAM-L was still con-centrated and the energy variation was much smaller thanG3761-L at the M2 measuring point In general the energyfrequency band of the two plate-shaped rocks with differentlithologies was the same as that of the rod-shape rock whichis mainly distributed in the range of 0ndash36428 kHz More-over they also exhibited the characteristics that the maindominant energy was distributed in the range of0ndash17678 kHz and the residual energy was distributed in therange of 28225ndash35256 kHz

4 Discussion

e purpose of this work was to study the propagationcharacteristics of elastic wave in lithological rock materialsrough the above research and analysis a preliminaryunderstanding was obtained Based on the deep waveletpacket analysis of amplitude energy characteristic param-eters and AE waveform the frequency band characteristicsof the local energy distribution of elastic wave with itspropagation were summarized However its propagationcharacteristics are difficult to be regularly grasped becausethe elastic wave itself is extremely complex Furthermore AEtechnology is mostly used in the damage detection and

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

20406080

100120140160

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

10

20

30

40

50

(e)

M1

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

200400600800

10001200140016001800

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

50

100

150

200

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 50005

101520253035

(f )

Figure 12e energy distribution of acoustic emission signal frequency band of plate-shaped rock (a) G3761-L (00) (b) G3761-L (450) (c)G3761-L (900) (d) GAM-L (00) (e) GAM-L (450) (f ) GAM-L (900)

Advances in Civil Engineering 17

defect location of metal or related materials with goodcompactness ductility and within the same medium ereare many uncertain interference factors in the experimentsIn some aspects the analysis of this paper only stays at thelevel of the apparent phenomenon and there are still manydeficiencies and areas worthy of improvement For instancethe density wave velocity and wave impedance of the rod-shaped rock samples should be tested and the micro-structure imaging experiments of the rock samples should beconducted e quality factor Q of different rock samplesshould be calculated Moreover the correlation between thequality factor and wave impedance should be studied andthe influence of different microcompositions of rod-shapedrocks on elastic wave attenuation should be deeply analyzedBased on the modal AE theory the influence of Lamb wavein plate-shaped rocks should be studied and the propagationmodel of two-dimensional AE should be constructed eGabor wavelet should be introduced to analyze the AE signalby time-frequency analysis e influence of differentwavelets based on the propagation effect of AE will becompared and analyzed and the time of the same mode ofthe AE wave arriving at the sensor will be determined tofurther optimize the plane location algorithm However theresearch in this work is still useful for studying large-scalerock samples in the future and provides effective researchmethods and ideas for the study of elastic wave propagationcharacteristics of different rock materials and compositematerials

5 Conclusions

In this work the characteristic parameter analysis andwaveform analysis of the AE signals obtained from differentexperimental schemes in 5 groups of rod-shaped rocks and 2groups of plate-shaped rocks were carried out e con-clusions are as follows

(1) e amplitude and energy of the rod-shaped rocksgradually attenuated with the increase of distancee amplitude can directly reflect the intensity of theAE counts at different measuring areas In theprocess of elastic wave propagation of the rod-sha-ped rock the P-wave preceded the S-wave andchanged violently e elastic wave of marble at-tenuated faster and the elastic wave of the threekinds of granite decayed attenuated closely Amongthem the elastic wave of TBG exhibited the fastestattenuation

(2) In flat plate-shaped rocks the amplitude exhibited anapproximate exponential attenuation characteristicwith the increase of the propagation distanceGranite exhibited a stronger elastic wave attenuationin the 0deg direction than the marble and the marblepresented fast attenuations in the 45deg and 90deg di-rections e energy change of marble was dramaticand the energy value in the interval of 45ndash55 cm atthe direction of 0deg showed the abnormal step phe-nomenon e energy value of the marble increasedafter 55 cm in the 45deg direction e energy value of

granite from the back to the end of the plate wasalmost maintained and tended to be stable at20ndash50mVms

(3) e frequency range of the energy distribution ofsamples in this work was within 0ndash36428 kHz Withthe increase of distance the main dominant energydistribution of the 5 groups of rod-shaped rocks inthe frequency range was characterized by distribu-tion to relative concentration and rapid energy at-tenuationemain dominant energy distribution ofthe 2 groups of plate-shaped rocks was distributed inthe range of 0ndash17678 kHz All rod-shaped rocks andplate-shaped rocks exhibited the characteristics ofresidual energy distribution in the frequency band of28225ndash35256 kHz

Data Availability

e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

e authors certify that they have no conflicts of interest

Acknowledgments

is research was funded by the National Natural ScienceFoundation of China (51804161 52074156 and 52004291)the Chinese Postdoctoral Science Foundation(2019M660861) and the State Key Laboratory CultivationBase for Gas Geology and Gas Control (Henan PolytechnicUniversity) (WS2020A04)

References

[1] J T Chen J H Zhao S C Zhang Y Zhang F Yang andM Li ldquoAn experimental and analytical research on theevolution of mining cracks in deep floor rock massrdquo Pure andApplied Geophysics vol 177 no 11 pp 5325ndash5348 2020

[2] K Wang and F Du ldquoCoal-gas compound dynamic disastersin China a reviewrdquo Process Safety and Environmental Pro-tection vol 133 pp 1ndash17 2020

[3] C Zhu M He M Karakus X Cui and Z Tao ldquoInvestigatingtoppling failure mechanism of anti-dip layered slope due toexcavation by physical modellingrdquo Rock Mechanics and RockEngineering vol 53 no 11 pp 5029ndash5050 2020

[4] X Wang C Liu S Chen L Chen K Li and N Liu ldquoImpactof coal sectorrsquos de-capacity policy on coal pricerdquo AppliedEnergy vol 265 Article ID 114802 2020

[5] D Liu Z Gu R Liang et al ldquoImpacts of pore-throat systemon fractal characterization of tight sandstonesrdquo Geofluidsvol 2020 no 9 17 pages Article ID 4941501 2020

[6] J Wang Y Zhang Z Qin S Song and P Lin ldquoAnalysismethod of water inrush for tunnels with damaged water-resisting rock mass based on finite element method-smoothparticle hydrodynamics couplingrdquo Computers and Geo-technics vol 126 Article ID 103725 2020

[7] B Chen S C Zhang Y Y Li Z K Li and H J ZhouldquoPhysical simulation study of crack propagation and insta-bility information discrimination of rock-like materials withfaultsrdquo Arabian Journal of Geosciences vol 13 p 966 2020

18 Advances in Civil Engineering

[8] F Du K Wang X Zhang C Xin and G Wang ldquoExperi-mental study of coal-gas outburst insights from coal-rockstructure gas pressure and adsorptivityrdquo Natural ResourcesResearch vol 29 no 4 pp 2481ndash2493 2020

[9] H Y Wang J Ma G D Wang et al ldquoResearch on AE sourcelocation of linear and plane rock massrdquo Shock and Vibrationvol 2020 Article ID 8846582 18 pages 2020

[10] V A Mansurov ldquoPrediction of rockbursts by analysis ofinduced seismicity datardquo International Journal of Rock Me-chanics and Mining Sciences vol 38 no 6 pp 893ndash901 2001

[11] M C He J L Miao and J L Feng ldquoRock burst process oflimestone and its acoustic emission characteristics under true-triaxial unloading conditionsrdquo International Journal of RockMechanics and Mining Sciences vol 47 no 2 pp 286ndash2982010

[12] F Gong J Yan X Li and S Luo ldquoA peak-strength strainenergy storage index for rock burst proneness of rock ma-terialsrdquo International Journal of Rock Mechanics and MiningSciences vol 117 pp 76ndash89 2019

[13] F Du and KWang ldquoUnstable failure of gas-bearing coal-rockcombination bodies insights from physical experiments andnumerical simulationsrdquo Process Safety and EnvironmentalProtection vol 129 pp 264ndash279 2019

[14] S D Butt C Mukherjee and G Lebans ldquoEvaluation ofacoustic attenuation as an indicator of roof stability in ad-vancing headingsrdquo International Journal of Rock Mechanicsand Mining Sciences vol 37 no 7 pp 1123ndash1131 2000

[15] M Cai H Morioka P K Kaiser et al ldquoBack-analysis of rockmass strength parameters using ae monitoring datardquo Inter-national Journal of Rock Mechanics and Mining Sciencesvol 44 no 4 pp 538ndash549 2007

[16] D P Jansen S R Carlson R P Young and D A HutchinsldquoUltrasonic imaging and acoustic emission monitoring ofthermally induced microcracks in Lac du Bonnet graniterdquoJournal of Geophysical Research Solid Earth vol 98 no B12pp 22231ndash22243 1993

[17] U Bismayer ldquoEarly warning signs for mining accidentsdetecting crackling noiserdquo American Mineralogist vol 102no 1 pp 3-4 2017

[18] X Kong E Wang S Li H Lin P Xiao and K ZhangldquoFractals and chaos characteristics of acoustic emission energyabout gas-bearing coal during loaded failurerdquo Fractals vol 27no 5 Article ID 195072 2019

[19] F Du K Wang G Wang Y Jiang C Xin and X ZhangldquoInvestigation of the acoustic emission characteristics duringdeformation and failure of gas-bearing coal-rock combinedbodiesrdquo Journal of Loss Prevention in the Process Industriesvol 55 pp 253ndash266 2018

[20] R P Young D A Hutchins S Talebi et al ldquoLaboratory andfield investigations of rockburst phenomena using concurrentgeotomographic imaging and acoustic emissionmicroseismictechniquesrdquo Seismicity in Mines vol 129 no 3-4pp 647ndash659 1989

[21] X Jansen H Xu M He and F Zhang ldquoExperimental in-vestigation of the occurrence of rockburst in a rock specimenthrough infrared thermography and acoustic emissionrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 93 pp 250ndash259 2017

[22] R E Goodman and E Richard ldquoSubaudible noise duringcompression of rocksrdquo Geological Society of America Bulletinvol 74 no 4 pp 487ndash490 1963

[23] M Cai P K Kaiser H Morioka et al ldquoFLACPFC couplednumerical simulation of AE in large-scale underground

excavationsrdquo International Journal of Rock Mechanics andMining Sciences vol 44 no 4 pp 550ndash564 2007

[24] V Saltas F Vallianatos D Triantis T Koumoudeli andI Stavrakas ldquoNon-extensive statistical analysis of acousticemissions series recorded during the uniaxial compression ofbrittle rocksrdquo Physica A Statistical Mechanics and Its Ap-plications vol 528 Article ID 121498 2019

[25] V Saltas I Fitilis and F Vallianatos ldquoA combined complexelectrical impedance and acoustic emission study in limestonesamples under uniaxial loadingrdquo Tectonophysics vol 637pp 198ndash206 2014

[26] G Qi ldquoWavelet-based AE characterization of compositematerialsrdquo NDTamp E International vol 33 no 3 pp 133ndash1442000

[27] G Manthei J Eisenblatter and T Dahm ldquoMoment tensorevaluation of acoustic emission sources in salt rockrdquo Con-struction and Building Materials vol 15 no 5-6 pp 297ndash3092001

[28] H Jeong and Y-S Jang ldquoWavelet analysis of plate wavepropagation in composite laminatesrdquo Composite Structuresvol 49 no 4 pp 443ndash450 2000

[29] S-H Chang and C-I Lee ldquoEstimation of cracking anddamage mechanisms in rock under triaxial compression bymoment tensor analysis of acoustic emissionrdquo InternationalJournal of Rock Mechanics and Mining Sciences vol 41 no 7pp 1069ndash1086 2004

[30] T Hirata T Satoh and K Ito ldquoFractal structure of spatialdistribution of microfracturing in rockrdquo Geophysical JournalInternational vol 90 no 2 pp 369ndash374 1987

[31] X Lei K Masuda O Nishizawa et al ldquoDetailed analysis ofacoustic emission activity during catastrophic fracture offaults in rockrdquo Journal of Structural Geology vol 26 no 2pp 247ndash258 2004

[32] J Jouniaux J Pei J Liu et al ldquoInvestigation on acousticemission behavior and its time-space evolution mechanism infailure process of coalndashrock combined bodyrdquo Chinese Journalof Rock Mechanics and Engineering vol 30 pp 1564ndash15702011

[33] E Townend B D ompson P M Benson PG MeredithP Baud and R P Young ldquoImaging compaction bandpropagation in Diemelstadt sandstone using acoustic emis-sion locationsrdquo Geophysical Research Letters vol 35 no 15pp 189ndash193 2008

[34] M Naderloo M Moosavi and M Ahmadi ldquoUsing acousticemission technique tomonitor damage progress around jointsin brittle materialsrdquo Deoretical and Applied Fracture Me-chanics vol 104 Article ID 102368 2019

[35] GBT Unified Number of Natural Stone China StandardsPress Beijing China 2009

[36] G Shen Acoustic Emission Detection Technology and Appli-cation Science Press Beijing China 2015

[37] Y Guo Research on Wavelet Base Selection for VibrationSignal Processing Hefei University of Technology HefeiChina 2003

[38] F Xu E Wang and D Song ldquoLong-range correlation andmultifractal distribution of acoustic emission of coal-rockrdquoRock and Soil Mechanics vol 32 no 7 pp 2111ndash2116 2011

Advances in Civil Engineering 19

mainly distributed within 0ndash10647 kHz at the percentages of9211 9022 and 9188 respectively By comparing thethree groups of rod-shaped rocks with the same lithology itcan be seen that the energy attenuation was the fastest inTBG and the dominant energy value was the lowest at theM3 measuring point For G3768 the energy attenuation wasthe slowest Only the distribution rule of the dominant

energy value at the M2 and M3 measuring points changedwhereas the maximum energy value hardly changed ereason may be that the internal structure or componentdensity of G3768 was better and the energy was relativelymaintained rather than rapidly attenuated with the elasticwave propagation For AAM artificial marble its maindominant energy also exhibited the same change trend as

GAM-L(45deg)

0 05 10 15 20 25

ndash3

ndash2

ndash1

0

1

2

3

4

Am

plitu

de (m

V)

Time (ms)

GAM-L(45deg)

0 100 200 300 400 5000

002

004

006

008

010

012

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(0deg)

0 05 10 15 20 25 30 35

ndash09

ndash06

ndash03

0

03

06

09

Am

plitu

de (m

V)

Time (ms)

GAM-L(0deg)

0 100 200 300 400 5000

0005

0010

0015

0020

0025

Am

plitu

de (m

V)

Frequency (KHz)

GAM-L(90deg)

0 05 10 15 20 25ndash3

ndash2

ndash1

0

1

2

3

Am

plitu

de (m

V)

Time (ms)

GAM-L(90deg)

Am

plitu

de (m

V)

0 100 200 300 400 500000

002

004

006

008

010

Frequency (KHz)

(b)

Figure 9 e time waveform and spectrogram of measuring point M2 of pate-shaped rock

Advances in Civil Engineering 13

0 3 6 9 12 15ndash15

ndash10

ndash05

00

05

10

Wavelet function

0 3 6 9 12 15

ndash05

00

05

10

Scaling function

Figure 10 Wavelet function and scaling function for db7

Table 5 e frequency band range of reconstructed signal by wavelet packet decomposition

Layer S (i 0) S (i 1) S (i 2) S (i jminus 1) S (i j)1 0ndash750 ndash ndash ndash ndash 750ndash15002 0ndash375 375ndash750 750ndash1125 ndash ndash 1125ndash15003 0ndash1875 1875ndash375 375ndash5625 1125ndash13125 13125ndash15004 0ndash9375 9375ndash1875 1875ndash28125 13125ndash140625 140625ndash15005 0ndash46875 46875ndash9375 9375ndash140625 140625ndash1453125 1453125ndash15006 0ndash234375 234375ndash46875 46875ndash703125 1453125ndash14765625 14765625ndash15007 0ndash1171875 1171875ndash234375 234375ndash3515625 14765625ndash148828125 148828125ndash1500S (i j) represents the reconstruction signal of the j-th wavelet packet decomposition coefficient in the i-th layer i 1234 j 012 2i-1

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M3

(a)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500

1000

1500

2000

2500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

20

40

60

80

100

120

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

M3

(b)

Figure 11 Continued

14 Advances in Civil Engineering

granite From Figure 11 it can be observed that the energy ofthe original pulse signal is concentrated in the range of9475ndash16506 kHz and 2185 of the energy existed in thefrequency band of 28225ndash35256 kHz For GAMmarble themain dominant energy distribution of the initial signal wasvery wide and was distributed in the frequency band of0ndash36428 kHz Among them the dominant energy wasdistributed within the 10647ndash12991 kHz range accountingfor 3213 of the total energy Similar attenuation charac-teristics as granite were presented with the increase of elasticwave propagation distance In general for GAM the exci-tation energy of the AE signal generated by pulse excitationwas the weakest and the attenuation was the fastest with theincrease of distancee initial excitation energy of the threegroups of granite was partially concentrated in the frequency

band of 23538ndash35256 kHz of which the performance ofG3561 was the most obvious

e pulse AE signal was very complex for 2 groups of theplate-shaped rocks (Figure 12) erefore the initial energyof the M1 measuring point in each direction was also quitedifferent In the direction of 0deg the dominant energy of theoriginal pulse signal in G3761-L was concentrated in thefrequency band of 0ndash17678 kHz which accounted for8904 of the total energy Meanwhile about 628 of theenergy was distributed in the frequency band of29397ndash32913 kHz e same law was also shown in GAM-L but the main dominant frequency in GAM-L was rela-tively concentrated in the short frequency band of10647ndash17678 kHz which accounted for 6357 of the totalenergy With the spread of the elastic wave the energy in

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50002468

10121416

M3

(c)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5001000150020002500300035004000

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40

50

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M3

(d)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

100

200

300

400

500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M2

0 100 200 300 400 5000

2

4

6

8En

ergy

(mVlowast

mS)

Frequency (KHZ)

M3

0 100 200 300 400 500012345678

(e)

Figure 11e energy distribution of acoustic emission signal frequency band of rod-shaped rock (a) G3768 (b) G3561 (c) TBG (d) AAM(e) GAM

Advances in Civil Engineering 15

0 100 200 300 400 5000

200400600800

100012001400

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

M2

0 100 200 300 400 5000005101520253035

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

M3

0 100 200 300 400 50000020406081012

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

(a)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40En

ergy

(mVlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 5000

2

4

6

8

Ener

gy (m

Vlowast

mS)

(b)

M1

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

1020304050607080

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50002468

1012141618

Ener

gy (m

Vlowast

mS)

(c)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700800

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 50005

101520253035

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

Ener

gy (m

Vlowast

mS)

(d)

Figure 12 Continued

16 Advances in Civil Engineering

G3761-L showed a trend of attenuation and the energy intheM2measuring point was still distributed in the frequencyband of 0ndash17678 kHz e energy distribution at the M3measuring point was relatively concentrated and was locatedin the frequency band of 0ndash10647 kHz accounting for8340 of the total energy e energy at the measuringpoint M3 of GAM-L was more extensive in the frequencydomain and the energy value changed dramatically dem-onstrating the abnormal phenomenon that the maindominant energy increased e frequency range of thismeasuring point was 0ndash1885 kHz accounting for 8589 ofthe total energyere was also residual energy concentratedin the frequency band of 29397ndash32913 kHz e AE signalat M3 was superposed by the boundary reflection wave andthe energy was enhanced because of the high homogeneityand good ductility of GAM-L For G3761-L the dominantenergy of the elastic wave almost dissipated at the M3measuring point In the direction of 45deg the dominantenergy band of the original signal in G3761-L was distributedwithin 0ndash17678 kHz and 28225ndash35256 kHz respectivelyaccounting for 6415 and 3278 of the total energyMoreover it can be observed that the distribution of thedominant energy band was from distribution to concen-tration which was distributed in the frequency band of7131ndash17678 kHz at M2 With the increase of distance theenergy frequency band of the M3 measuring point near theedge of the plate was spread again and it was restored to theenergy frequency band range of the initial signal Howeverthe energy value was attenuated to a very small value at this

moment e energies of GAM-L in the measuring pointsM1 M2 and M3 were all distributed in the frequency bandof 0ndash36428 kHz In the direction of 90deg the primarydominant energy frequency bands of the two plate-shapedrocks were concentrated in 9475ndash1885 kHz e differenceis that the energy distribution of GAM-L was still con-centrated and the energy variation was much smaller thanG3761-L at the M2 measuring point In general the energyfrequency band of the two plate-shaped rocks with differentlithologies was the same as that of the rod-shape rock whichis mainly distributed in the range of 0ndash36428 kHz More-over they also exhibited the characteristics that the maindominant energy was distributed in the range of0ndash17678 kHz and the residual energy was distributed in therange of 28225ndash35256 kHz

4 Discussion

e purpose of this work was to study the propagationcharacteristics of elastic wave in lithological rock materialsrough the above research and analysis a preliminaryunderstanding was obtained Based on the deep waveletpacket analysis of amplitude energy characteristic param-eters and AE waveform the frequency band characteristicsof the local energy distribution of elastic wave with itspropagation were summarized However its propagationcharacteristics are difficult to be regularly grasped becausethe elastic wave itself is extremely complex Furthermore AEtechnology is mostly used in the damage detection and

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

20406080

100120140160

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

10

20

30

40

50

(e)

M1

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

200400600800

10001200140016001800

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

50

100

150

200

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 50005

101520253035

(f )

Figure 12e energy distribution of acoustic emission signal frequency band of plate-shaped rock (a) G3761-L (00) (b) G3761-L (450) (c)G3761-L (900) (d) GAM-L (00) (e) GAM-L (450) (f ) GAM-L (900)

Advances in Civil Engineering 17

defect location of metal or related materials with goodcompactness ductility and within the same medium ereare many uncertain interference factors in the experimentsIn some aspects the analysis of this paper only stays at thelevel of the apparent phenomenon and there are still manydeficiencies and areas worthy of improvement For instancethe density wave velocity and wave impedance of the rod-shaped rock samples should be tested and the micro-structure imaging experiments of the rock samples should beconducted e quality factor Q of different rock samplesshould be calculated Moreover the correlation between thequality factor and wave impedance should be studied andthe influence of different microcompositions of rod-shapedrocks on elastic wave attenuation should be deeply analyzedBased on the modal AE theory the influence of Lamb wavein plate-shaped rocks should be studied and the propagationmodel of two-dimensional AE should be constructed eGabor wavelet should be introduced to analyze the AE signalby time-frequency analysis e influence of differentwavelets based on the propagation effect of AE will becompared and analyzed and the time of the same mode ofthe AE wave arriving at the sensor will be determined tofurther optimize the plane location algorithm However theresearch in this work is still useful for studying large-scalerock samples in the future and provides effective researchmethods and ideas for the study of elastic wave propagationcharacteristics of different rock materials and compositematerials

5 Conclusions

In this work the characteristic parameter analysis andwaveform analysis of the AE signals obtained from differentexperimental schemes in 5 groups of rod-shaped rocks and 2groups of plate-shaped rocks were carried out e con-clusions are as follows

(1) e amplitude and energy of the rod-shaped rocksgradually attenuated with the increase of distancee amplitude can directly reflect the intensity of theAE counts at different measuring areas In theprocess of elastic wave propagation of the rod-sha-ped rock the P-wave preceded the S-wave andchanged violently e elastic wave of marble at-tenuated faster and the elastic wave of the threekinds of granite decayed attenuated closely Amongthem the elastic wave of TBG exhibited the fastestattenuation

(2) In flat plate-shaped rocks the amplitude exhibited anapproximate exponential attenuation characteristicwith the increase of the propagation distanceGranite exhibited a stronger elastic wave attenuationin the 0deg direction than the marble and the marblepresented fast attenuations in the 45deg and 90deg di-rections e energy change of marble was dramaticand the energy value in the interval of 45ndash55 cm atthe direction of 0deg showed the abnormal step phe-nomenon e energy value of the marble increasedafter 55 cm in the 45deg direction e energy value of

granite from the back to the end of the plate wasalmost maintained and tended to be stable at20ndash50mVms

(3) e frequency range of the energy distribution ofsamples in this work was within 0ndash36428 kHz Withthe increase of distance the main dominant energydistribution of the 5 groups of rod-shaped rocks inthe frequency range was characterized by distribu-tion to relative concentration and rapid energy at-tenuationemain dominant energy distribution ofthe 2 groups of plate-shaped rocks was distributed inthe range of 0ndash17678 kHz All rod-shaped rocks andplate-shaped rocks exhibited the characteristics ofresidual energy distribution in the frequency band of28225ndash35256 kHz

Data Availability

e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

e authors certify that they have no conflicts of interest

Acknowledgments

is research was funded by the National Natural ScienceFoundation of China (51804161 52074156 and 52004291)the Chinese Postdoctoral Science Foundation(2019M660861) and the State Key Laboratory CultivationBase for Gas Geology and Gas Control (Henan PolytechnicUniversity) (WS2020A04)

References

[1] J T Chen J H Zhao S C Zhang Y Zhang F Yang andM Li ldquoAn experimental and analytical research on theevolution of mining cracks in deep floor rock massrdquo Pure andApplied Geophysics vol 177 no 11 pp 5325ndash5348 2020

[2] K Wang and F Du ldquoCoal-gas compound dynamic disastersin China a reviewrdquo Process Safety and Environmental Pro-tection vol 133 pp 1ndash17 2020

[3] C Zhu M He M Karakus X Cui and Z Tao ldquoInvestigatingtoppling failure mechanism of anti-dip layered slope due toexcavation by physical modellingrdquo Rock Mechanics and RockEngineering vol 53 no 11 pp 5029ndash5050 2020

[4] X Wang C Liu S Chen L Chen K Li and N Liu ldquoImpactof coal sectorrsquos de-capacity policy on coal pricerdquo AppliedEnergy vol 265 Article ID 114802 2020

[5] D Liu Z Gu R Liang et al ldquoImpacts of pore-throat systemon fractal characterization of tight sandstonesrdquo Geofluidsvol 2020 no 9 17 pages Article ID 4941501 2020

[6] J Wang Y Zhang Z Qin S Song and P Lin ldquoAnalysismethod of water inrush for tunnels with damaged water-resisting rock mass based on finite element method-smoothparticle hydrodynamics couplingrdquo Computers and Geo-technics vol 126 Article ID 103725 2020

[7] B Chen S C Zhang Y Y Li Z K Li and H J ZhouldquoPhysical simulation study of crack propagation and insta-bility information discrimination of rock-like materials withfaultsrdquo Arabian Journal of Geosciences vol 13 p 966 2020

18 Advances in Civil Engineering

[8] F Du K Wang X Zhang C Xin and G Wang ldquoExperi-mental study of coal-gas outburst insights from coal-rockstructure gas pressure and adsorptivityrdquo Natural ResourcesResearch vol 29 no 4 pp 2481ndash2493 2020

[9] H Y Wang J Ma G D Wang et al ldquoResearch on AE sourcelocation of linear and plane rock massrdquo Shock and Vibrationvol 2020 Article ID 8846582 18 pages 2020

[10] V A Mansurov ldquoPrediction of rockbursts by analysis ofinduced seismicity datardquo International Journal of Rock Me-chanics and Mining Sciences vol 38 no 6 pp 893ndash901 2001

[11] M C He J L Miao and J L Feng ldquoRock burst process oflimestone and its acoustic emission characteristics under true-triaxial unloading conditionsrdquo International Journal of RockMechanics and Mining Sciences vol 47 no 2 pp 286ndash2982010

[12] F Gong J Yan X Li and S Luo ldquoA peak-strength strainenergy storage index for rock burst proneness of rock ma-terialsrdquo International Journal of Rock Mechanics and MiningSciences vol 117 pp 76ndash89 2019

[13] F Du and KWang ldquoUnstable failure of gas-bearing coal-rockcombination bodies insights from physical experiments andnumerical simulationsrdquo Process Safety and EnvironmentalProtection vol 129 pp 264ndash279 2019

[14] S D Butt C Mukherjee and G Lebans ldquoEvaluation ofacoustic attenuation as an indicator of roof stability in ad-vancing headingsrdquo International Journal of Rock Mechanicsand Mining Sciences vol 37 no 7 pp 1123ndash1131 2000

[15] M Cai H Morioka P K Kaiser et al ldquoBack-analysis of rockmass strength parameters using ae monitoring datardquo Inter-national Journal of Rock Mechanics and Mining Sciencesvol 44 no 4 pp 538ndash549 2007

[16] D P Jansen S R Carlson R P Young and D A HutchinsldquoUltrasonic imaging and acoustic emission monitoring ofthermally induced microcracks in Lac du Bonnet graniterdquoJournal of Geophysical Research Solid Earth vol 98 no B12pp 22231ndash22243 1993

[17] U Bismayer ldquoEarly warning signs for mining accidentsdetecting crackling noiserdquo American Mineralogist vol 102no 1 pp 3-4 2017

[18] X Kong E Wang S Li H Lin P Xiao and K ZhangldquoFractals and chaos characteristics of acoustic emission energyabout gas-bearing coal during loaded failurerdquo Fractals vol 27no 5 Article ID 195072 2019

[19] F Du K Wang G Wang Y Jiang C Xin and X ZhangldquoInvestigation of the acoustic emission characteristics duringdeformation and failure of gas-bearing coal-rock combinedbodiesrdquo Journal of Loss Prevention in the Process Industriesvol 55 pp 253ndash266 2018

[20] R P Young D A Hutchins S Talebi et al ldquoLaboratory andfield investigations of rockburst phenomena using concurrentgeotomographic imaging and acoustic emissionmicroseismictechniquesrdquo Seismicity in Mines vol 129 no 3-4pp 647ndash659 1989

[21] X Jansen H Xu M He and F Zhang ldquoExperimental in-vestigation of the occurrence of rockburst in a rock specimenthrough infrared thermography and acoustic emissionrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 93 pp 250ndash259 2017

[22] R E Goodman and E Richard ldquoSubaudible noise duringcompression of rocksrdquo Geological Society of America Bulletinvol 74 no 4 pp 487ndash490 1963

[23] M Cai P K Kaiser H Morioka et al ldquoFLACPFC couplednumerical simulation of AE in large-scale underground

excavationsrdquo International Journal of Rock Mechanics andMining Sciences vol 44 no 4 pp 550ndash564 2007

[24] V Saltas F Vallianatos D Triantis T Koumoudeli andI Stavrakas ldquoNon-extensive statistical analysis of acousticemissions series recorded during the uniaxial compression ofbrittle rocksrdquo Physica A Statistical Mechanics and Its Ap-plications vol 528 Article ID 121498 2019

[25] V Saltas I Fitilis and F Vallianatos ldquoA combined complexelectrical impedance and acoustic emission study in limestonesamples under uniaxial loadingrdquo Tectonophysics vol 637pp 198ndash206 2014

[26] G Qi ldquoWavelet-based AE characterization of compositematerialsrdquo NDTamp E International vol 33 no 3 pp 133ndash1442000

[27] G Manthei J Eisenblatter and T Dahm ldquoMoment tensorevaluation of acoustic emission sources in salt rockrdquo Con-struction and Building Materials vol 15 no 5-6 pp 297ndash3092001

[28] H Jeong and Y-S Jang ldquoWavelet analysis of plate wavepropagation in composite laminatesrdquo Composite Structuresvol 49 no 4 pp 443ndash450 2000

[29] S-H Chang and C-I Lee ldquoEstimation of cracking anddamage mechanisms in rock under triaxial compression bymoment tensor analysis of acoustic emissionrdquo InternationalJournal of Rock Mechanics and Mining Sciences vol 41 no 7pp 1069ndash1086 2004

[30] T Hirata T Satoh and K Ito ldquoFractal structure of spatialdistribution of microfracturing in rockrdquo Geophysical JournalInternational vol 90 no 2 pp 369ndash374 1987

[31] X Lei K Masuda O Nishizawa et al ldquoDetailed analysis ofacoustic emission activity during catastrophic fracture offaults in rockrdquo Journal of Structural Geology vol 26 no 2pp 247ndash258 2004

[32] J Jouniaux J Pei J Liu et al ldquoInvestigation on acousticemission behavior and its time-space evolution mechanism infailure process of coalndashrock combined bodyrdquo Chinese Journalof Rock Mechanics and Engineering vol 30 pp 1564ndash15702011

[33] E Townend B D ompson P M Benson PG MeredithP Baud and R P Young ldquoImaging compaction bandpropagation in Diemelstadt sandstone using acoustic emis-sion locationsrdquo Geophysical Research Letters vol 35 no 15pp 189ndash193 2008

[34] M Naderloo M Moosavi and M Ahmadi ldquoUsing acousticemission technique tomonitor damage progress around jointsin brittle materialsrdquo Deoretical and Applied Fracture Me-chanics vol 104 Article ID 102368 2019

[35] GBT Unified Number of Natural Stone China StandardsPress Beijing China 2009

[36] G Shen Acoustic Emission Detection Technology and Appli-cation Science Press Beijing China 2015

[37] Y Guo Research on Wavelet Base Selection for VibrationSignal Processing Hefei University of Technology HefeiChina 2003

[38] F Xu E Wang and D Song ldquoLong-range correlation andmultifractal distribution of acoustic emission of coal-rockrdquoRock and Soil Mechanics vol 32 no 7 pp 2111ndash2116 2011

Advances in Civil Engineering 19

0 3 6 9 12 15ndash15

ndash10

ndash05

00

05

10

Wavelet function

0 3 6 9 12 15

ndash05

00

05

10

Scaling function

Figure 10 Wavelet function and scaling function for db7

Table 5 e frequency band range of reconstructed signal by wavelet packet decomposition

Layer S (i 0) S (i 1) S (i 2) S (i jminus 1) S (i j)1 0ndash750 ndash ndash ndash ndash 750ndash15002 0ndash375 375ndash750 750ndash1125 ndash ndash 1125ndash15003 0ndash1875 1875ndash375 375ndash5625 1125ndash13125 13125ndash15004 0ndash9375 9375ndash1875 1875ndash28125 13125ndash140625 140625ndash15005 0ndash46875 46875ndash9375 9375ndash140625 140625ndash1453125 1453125ndash15006 0ndash234375 234375ndash46875 46875ndash703125 1453125ndash14765625 14765625ndash15007 0ndash1171875 1171875ndash234375 234375ndash3515625 14765625ndash148828125 148828125ndash1500S (i j) represents the reconstruction signal of the j-th wavelet packet decomposition coefficient in the i-th layer i 1234 j 012 2i-1

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

M3

(a)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500

1000

1500

2000

2500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

20

40

60

80

100

120

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

M3

(b)

Figure 11 Continued

14 Advances in Civil Engineering

granite From Figure 11 it can be observed that the energy ofthe original pulse signal is concentrated in the range of9475ndash16506 kHz and 2185 of the energy existed in thefrequency band of 28225ndash35256 kHz For GAMmarble themain dominant energy distribution of the initial signal wasvery wide and was distributed in the frequency band of0ndash36428 kHz Among them the dominant energy wasdistributed within the 10647ndash12991 kHz range accountingfor 3213 of the total energy Similar attenuation charac-teristics as granite were presented with the increase of elasticwave propagation distance In general for GAM the exci-tation energy of the AE signal generated by pulse excitationwas the weakest and the attenuation was the fastest with theincrease of distancee initial excitation energy of the threegroups of granite was partially concentrated in the frequency

band of 23538ndash35256 kHz of which the performance ofG3561 was the most obvious

e pulse AE signal was very complex for 2 groups of theplate-shaped rocks (Figure 12) erefore the initial energyof the M1 measuring point in each direction was also quitedifferent In the direction of 0deg the dominant energy of theoriginal pulse signal in G3761-L was concentrated in thefrequency band of 0ndash17678 kHz which accounted for8904 of the total energy Meanwhile about 628 of theenergy was distributed in the frequency band of29397ndash32913 kHz e same law was also shown in GAM-L but the main dominant frequency in GAM-L was rela-tively concentrated in the short frequency band of10647ndash17678 kHz which accounted for 6357 of the totalenergy With the spread of the elastic wave the energy in

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50002468

10121416

M3

(c)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5001000150020002500300035004000

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40

50

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M3

(d)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

100

200

300

400

500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M2

0 100 200 300 400 5000

2

4

6

8En

ergy

(mVlowast

mS)

Frequency (KHZ)

M3

0 100 200 300 400 500012345678

(e)

Figure 11e energy distribution of acoustic emission signal frequency band of rod-shaped rock (a) G3768 (b) G3561 (c) TBG (d) AAM(e) GAM

Advances in Civil Engineering 15

0 100 200 300 400 5000

200400600800

100012001400

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

M2

0 100 200 300 400 5000005101520253035

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

M3

0 100 200 300 400 50000020406081012

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

(a)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40En

ergy

(mVlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 5000

2

4

6

8

Ener

gy (m

Vlowast

mS)

(b)

M1

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

1020304050607080

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50002468

1012141618

Ener

gy (m

Vlowast

mS)

(c)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700800

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 50005

101520253035

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

Ener

gy (m

Vlowast

mS)

(d)

Figure 12 Continued

16 Advances in Civil Engineering

G3761-L showed a trend of attenuation and the energy intheM2measuring point was still distributed in the frequencyband of 0ndash17678 kHz e energy distribution at the M3measuring point was relatively concentrated and was locatedin the frequency band of 0ndash10647 kHz accounting for8340 of the total energy e energy at the measuringpoint M3 of GAM-L was more extensive in the frequencydomain and the energy value changed dramatically dem-onstrating the abnormal phenomenon that the maindominant energy increased e frequency range of thismeasuring point was 0ndash1885 kHz accounting for 8589 ofthe total energyere was also residual energy concentratedin the frequency band of 29397ndash32913 kHz e AE signalat M3 was superposed by the boundary reflection wave andthe energy was enhanced because of the high homogeneityand good ductility of GAM-L For G3761-L the dominantenergy of the elastic wave almost dissipated at the M3measuring point In the direction of 45deg the dominantenergy band of the original signal in G3761-L was distributedwithin 0ndash17678 kHz and 28225ndash35256 kHz respectivelyaccounting for 6415 and 3278 of the total energyMoreover it can be observed that the distribution of thedominant energy band was from distribution to concen-tration which was distributed in the frequency band of7131ndash17678 kHz at M2 With the increase of distance theenergy frequency band of the M3 measuring point near theedge of the plate was spread again and it was restored to theenergy frequency band range of the initial signal Howeverthe energy value was attenuated to a very small value at this

moment e energies of GAM-L in the measuring pointsM1 M2 and M3 were all distributed in the frequency bandof 0ndash36428 kHz In the direction of 90deg the primarydominant energy frequency bands of the two plate-shapedrocks were concentrated in 9475ndash1885 kHz e differenceis that the energy distribution of GAM-L was still con-centrated and the energy variation was much smaller thanG3761-L at the M2 measuring point In general the energyfrequency band of the two plate-shaped rocks with differentlithologies was the same as that of the rod-shape rock whichis mainly distributed in the range of 0ndash36428 kHz More-over they also exhibited the characteristics that the maindominant energy was distributed in the range of0ndash17678 kHz and the residual energy was distributed in therange of 28225ndash35256 kHz

4 Discussion

e purpose of this work was to study the propagationcharacteristics of elastic wave in lithological rock materialsrough the above research and analysis a preliminaryunderstanding was obtained Based on the deep waveletpacket analysis of amplitude energy characteristic param-eters and AE waveform the frequency band characteristicsof the local energy distribution of elastic wave with itspropagation were summarized However its propagationcharacteristics are difficult to be regularly grasped becausethe elastic wave itself is extremely complex Furthermore AEtechnology is mostly used in the damage detection and

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

20406080

100120140160

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

10

20

30

40

50

(e)

M1

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

200400600800

10001200140016001800

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

50

100

150

200

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 50005

101520253035

(f )

Figure 12e energy distribution of acoustic emission signal frequency band of plate-shaped rock (a) G3761-L (00) (b) G3761-L (450) (c)G3761-L (900) (d) GAM-L (00) (e) GAM-L (450) (f ) GAM-L (900)

Advances in Civil Engineering 17

defect location of metal or related materials with goodcompactness ductility and within the same medium ereare many uncertain interference factors in the experimentsIn some aspects the analysis of this paper only stays at thelevel of the apparent phenomenon and there are still manydeficiencies and areas worthy of improvement For instancethe density wave velocity and wave impedance of the rod-shaped rock samples should be tested and the micro-structure imaging experiments of the rock samples should beconducted e quality factor Q of different rock samplesshould be calculated Moreover the correlation between thequality factor and wave impedance should be studied andthe influence of different microcompositions of rod-shapedrocks on elastic wave attenuation should be deeply analyzedBased on the modal AE theory the influence of Lamb wavein plate-shaped rocks should be studied and the propagationmodel of two-dimensional AE should be constructed eGabor wavelet should be introduced to analyze the AE signalby time-frequency analysis e influence of differentwavelets based on the propagation effect of AE will becompared and analyzed and the time of the same mode ofthe AE wave arriving at the sensor will be determined tofurther optimize the plane location algorithm However theresearch in this work is still useful for studying large-scalerock samples in the future and provides effective researchmethods and ideas for the study of elastic wave propagationcharacteristics of different rock materials and compositematerials

5 Conclusions

In this work the characteristic parameter analysis andwaveform analysis of the AE signals obtained from differentexperimental schemes in 5 groups of rod-shaped rocks and 2groups of plate-shaped rocks were carried out e con-clusions are as follows

(1) e amplitude and energy of the rod-shaped rocksgradually attenuated with the increase of distancee amplitude can directly reflect the intensity of theAE counts at different measuring areas In theprocess of elastic wave propagation of the rod-sha-ped rock the P-wave preceded the S-wave andchanged violently e elastic wave of marble at-tenuated faster and the elastic wave of the threekinds of granite decayed attenuated closely Amongthem the elastic wave of TBG exhibited the fastestattenuation

(2) In flat plate-shaped rocks the amplitude exhibited anapproximate exponential attenuation characteristicwith the increase of the propagation distanceGranite exhibited a stronger elastic wave attenuationin the 0deg direction than the marble and the marblepresented fast attenuations in the 45deg and 90deg di-rections e energy change of marble was dramaticand the energy value in the interval of 45ndash55 cm atthe direction of 0deg showed the abnormal step phe-nomenon e energy value of the marble increasedafter 55 cm in the 45deg direction e energy value of

granite from the back to the end of the plate wasalmost maintained and tended to be stable at20ndash50mVms

(3) e frequency range of the energy distribution ofsamples in this work was within 0ndash36428 kHz Withthe increase of distance the main dominant energydistribution of the 5 groups of rod-shaped rocks inthe frequency range was characterized by distribu-tion to relative concentration and rapid energy at-tenuationemain dominant energy distribution ofthe 2 groups of plate-shaped rocks was distributed inthe range of 0ndash17678 kHz All rod-shaped rocks andplate-shaped rocks exhibited the characteristics ofresidual energy distribution in the frequency band of28225ndash35256 kHz

Data Availability

e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

e authors certify that they have no conflicts of interest

Acknowledgments

is research was funded by the National Natural ScienceFoundation of China (51804161 52074156 and 52004291)the Chinese Postdoctoral Science Foundation(2019M660861) and the State Key Laboratory CultivationBase for Gas Geology and Gas Control (Henan PolytechnicUniversity) (WS2020A04)

References

[1] J T Chen J H Zhao S C Zhang Y Zhang F Yang andM Li ldquoAn experimental and analytical research on theevolution of mining cracks in deep floor rock massrdquo Pure andApplied Geophysics vol 177 no 11 pp 5325ndash5348 2020

[2] K Wang and F Du ldquoCoal-gas compound dynamic disastersin China a reviewrdquo Process Safety and Environmental Pro-tection vol 133 pp 1ndash17 2020

[3] C Zhu M He M Karakus X Cui and Z Tao ldquoInvestigatingtoppling failure mechanism of anti-dip layered slope due toexcavation by physical modellingrdquo Rock Mechanics and RockEngineering vol 53 no 11 pp 5029ndash5050 2020

[4] X Wang C Liu S Chen L Chen K Li and N Liu ldquoImpactof coal sectorrsquos de-capacity policy on coal pricerdquo AppliedEnergy vol 265 Article ID 114802 2020

[5] D Liu Z Gu R Liang et al ldquoImpacts of pore-throat systemon fractal characterization of tight sandstonesrdquo Geofluidsvol 2020 no 9 17 pages Article ID 4941501 2020

[6] J Wang Y Zhang Z Qin S Song and P Lin ldquoAnalysismethod of water inrush for tunnels with damaged water-resisting rock mass based on finite element method-smoothparticle hydrodynamics couplingrdquo Computers and Geo-technics vol 126 Article ID 103725 2020

[7] B Chen S C Zhang Y Y Li Z K Li and H J ZhouldquoPhysical simulation study of crack propagation and insta-bility information discrimination of rock-like materials withfaultsrdquo Arabian Journal of Geosciences vol 13 p 966 2020

18 Advances in Civil Engineering

[8] F Du K Wang X Zhang C Xin and G Wang ldquoExperi-mental study of coal-gas outburst insights from coal-rockstructure gas pressure and adsorptivityrdquo Natural ResourcesResearch vol 29 no 4 pp 2481ndash2493 2020

[9] H Y Wang J Ma G D Wang et al ldquoResearch on AE sourcelocation of linear and plane rock massrdquo Shock and Vibrationvol 2020 Article ID 8846582 18 pages 2020

[10] V A Mansurov ldquoPrediction of rockbursts by analysis ofinduced seismicity datardquo International Journal of Rock Me-chanics and Mining Sciences vol 38 no 6 pp 893ndash901 2001

[11] M C He J L Miao and J L Feng ldquoRock burst process oflimestone and its acoustic emission characteristics under true-triaxial unloading conditionsrdquo International Journal of RockMechanics and Mining Sciences vol 47 no 2 pp 286ndash2982010

[12] F Gong J Yan X Li and S Luo ldquoA peak-strength strainenergy storage index for rock burst proneness of rock ma-terialsrdquo International Journal of Rock Mechanics and MiningSciences vol 117 pp 76ndash89 2019

[13] F Du and KWang ldquoUnstable failure of gas-bearing coal-rockcombination bodies insights from physical experiments andnumerical simulationsrdquo Process Safety and EnvironmentalProtection vol 129 pp 264ndash279 2019

[14] S D Butt C Mukherjee and G Lebans ldquoEvaluation ofacoustic attenuation as an indicator of roof stability in ad-vancing headingsrdquo International Journal of Rock Mechanicsand Mining Sciences vol 37 no 7 pp 1123ndash1131 2000

[15] M Cai H Morioka P K Kaiser et al ldquoBack-analysis of rockmass strength parameters using ae monitoring datardquo Inter-national Journal of Rock Mechanics and Mining Sciencesvol 44 no 4 pp 538ndash549 2007

[16] D P Jansen S R Carlson R P Young and D A HutchinsldquoUltrasonic imaging and acoustic emission monitoring ofthermally induced microcracks in Lac du Bonnet graniterdquoJournal of Geophysical Research Solid Earth vol 98 no B12pp 22231ndash22243 1993

[17] U Bismayer ldquoEarly warning signs for mining accidentsdetecting crackling noiserdquo American Mineralogist vol 102no 1 pp 3-4 2017

[18] X Kong E Wang S Li H Lin P Xiao and K ZhangldquoFractals and chaos characteristics of acoustic emission energyabout gas-bearing coal during loaded failurerdquo Fractals vol 27no 5 Article ID 195072 2019

[19] F Du K Wang G Wang Y Jiang C Xin and X ZhangldquoInvestigation of the acoustic emission characteristics duringdeformation and failure of gas-bearing coal-rock combinedbodiesrdquo Journal of Loss Prevention in the Process Industriesvol 55 pp 253ndash266 2018

[20] R P Young D A Hutchins S Talebi et al ldquoLaboratory andfield investigations of rockburst phenomena using concurrentgeotomographic imaging and acoustic emissionmicroseismictechniquesrdquo Seismicity in Mines vol 129 no 3-4pp 647ndash659 1989

[21] X Jansen H Xu M He and F Zhang ldquoExperimental in-vestigation of the occurrence of rockburst in a rock specimenthrough infrared thermography and acoustic emissionrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 93 pp 250ndash259 2017

[22] R E Goodman and E Richard ldquoSubaudible noise duringcompression of rocksrdquo Geological Society of America Bulletinvol 74 no 4 pp 487ndash490 1963

[23] M Cai P K Kaiser H Morioka et al ldquoFLACPFC couplednumerical simulation of AE in large-scale underground

excavationsrdquo International Journal of Rock Mechanics andMining Sciences vol 44 no 4 pp 550ndash564 2007

[24] V Saltas F Vallianatos D Triantis T Koumoudeli andI Stavrakas ldquoNon-extensive statistical analysis of acousticemissions series recorded during the uniaxial compression ofbrittle rocksrdquo Physica A Statistical Mechanics and Its Ap-plications vol 528 Article ID 121498 2019

[25] V Saltas I Fitilis and F Vallianatos ldquoA combined complexelectrical impedance and acoustic emission study in limestonesamples under uniaxial loadingrdquo Tectonophysics vol 637pp 198ndash206 2014

[26] G Qi ldquoWavelet-based AE characterization of compositematerialsrdquo NDTamp E International vol 33 no 3 pp 133ndash1442000

[27] G Manthei J Eisenblatter and T Dahm ldquoMoment tensorevaluation of acoustic emission sources in salt rockrdquo Con-struction and Building Materials vol 15 no 5-6 pp 297ndash3092001

[28] H Jeong and Y-S Jang ldquoWavelet analysis of plate wavepropagation in composite laminatesrdquo Composite Structuresvol 49 no 4 pp 443ndash450 2000

[29] S-H Chang and C-I Lee ldquoEstimation of cracking anddamage mechanisms in rock under triaxial compression bymoment tensor analysis of acoustic emissionrdquo InternationalJournal of Rock Mechanics and Mining Sciences vol 41 no 7pp 1069ndash1086 2004

[30] T Hirata T Satoh and K Ito ldquoFractal structure of spatialdistribution of microfracturing in rockrdquo Geophysical JournalInternational vol 90 no 2 pp 369ndash374 1987

[31] X Lei K Masuda O Nishizawa et al ldquoDetailed analysis ofacoustic emission activity during catastrophic fracture offaults in rockrdquo Journal of Structural Geology vol 26 no 2pp 247ndash258 2004

[32] J Jouniaux J Pei J Liu et al ldquoInvestigation on acousticemission behavior and its time-space evolution mechanism infailure process of coalndashrock combined bodyrdquo Chinese Journalof Rock Mechanics and Engineering vol 30 pp 1564ndash15702011

[33] E Townend B D ompson P M Benson PG MeredithP Baud and R P Young ldquoImaging compaction bandpropagation in Diemelstadt sandstone using acoustic emis-sion locationsrdquo Geophysical Research Letters vol 35 no 15pp 189ndash193 2008

[34] M Naderloo M Moosavi and M Ahmadi ldquoUsing acousticemission technique tomonitor damage progress around jointsin brittle materialsrdquo Deoretical and Applied Fracture Me-chanics vol 104 Article ID 102368 2019

[35] GBT Unified Number of Natural Stone China StandardsPress Beijing China 2009

[36] G Shen Acoustic Emission Detection Technology and Appli-cation Science Press Beijing China 2015

[37] Y Guo Research on Wavelet Base Selection for VibrationSignal Processing Hefei University of Technology HefeiChina 2003

[38] F Xu E Wang and D Song ldquoLong-range correlation andmultifractal distribution of acoustic emission of coal-rockrdquoRock and Soil Mechanics vol 32 no 7 pp 2111ndash2116 2011

Advances in Civil Engineering 19

granite From Figure 11 it can be observed that the energy ofthe original pulse signal is concentrated in the range of9475ndash16506 kHz and 2185 of the energy existed in thefrequency band of 28225ndash35256 kHz For GAMmarble themain dominant energy distribution of the initial signal wasvery wide and was distributed in the frequency band of0ndash36428 kHz Among them the dominant energy wasdistributed within the 10647ndash12991 kHz range accountingfor 3213 of the total energy Similar attenuation charac-teristics as granite were presented with the increase of elasticwave propagation distance In general for GAM the exci-tation energy of the AE signal generated by pulse excitationwas the weakest and the attenuation was the fastest with theincrease of distancee initial excitation energy of the threegroups of granite was partially concentrated in the frequency

band of 23538ndash35256 kHz of which the performance ofG3561 was the most obvious

e pulse AE signal was very complex for 2 groups of theplate-shaped rocks (Figure 12) erefore the initial energyof the M1 measuring point in each direction was also quitedifferent In the direction of 0deg the dominant energy of theoriginal pulse signal in G3761-L was concentrated in thefrequency band of 0ndash17678 kHz which accounted for8904 of the total energy Meanwhile about 628 of theenergy was distributed in the frequency band of29397ndash32913 kHz e same law was also shown in GAM-L but the main dominant frequency in GAM-L was rela-tively concentrated in the short frequency band of10647ndash17678 kHz which accounted for 6357 of the totalenergy With the spread of the elastic wave the energy in

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 50002468

10121416

M3

(c)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5001000150020002500300035004000

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40

50

M2

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

5

10

15

20

25

30

M3

(d)

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

0 100 200 300 400 5000

100

200

300

400

500

M1

Ener

gy (m

Vlowast

mS)

Frequency (KHZ)

M2

0 100 200 300 400 5000

2

4

6

8En

ergy

(mVlowast

mS)

Frequency (KHZ)

M3

0 100 200 300 400 500012345678

(e)

Figure 11e energy distribution of acoustic emission signal frequency band of rod-shaped rock (a) G3768 (b) G3561 (c) TBG (d) AAM(e) GAM

Advances in Civil Engineering 15

0 100 200 300 400 5000

200400600800

100012001400

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

M2

0 100 200 300 400 5000005101520253035

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

M3

0 100 200 300 400 50000020406081012

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

(a)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40En

ergy

(mVlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 5000

2

4

6

8

Ener

gy (m

Vlowast

mS)

(b)

M1

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

1020304050607080

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50002468

1012141618

Ener

gy (m

Vlowast

mS)

(c)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700800

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 50005

101520253035

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

Ener

gy (m

Vlowast

mS)

(d)

Figure 12 Continued

16 Advances in Civil Engineering

G3761-L showed a trend of attenuation and the energy intheM2measuring point was still distributed in the frequencyband of 0ndash17678 kHz e energy distribution at the M3measuring point was relatively concentrated and was locatedin the frequency band of 0ndash10647 kHz accounting for8340 of the total energy e energy at the measuringpoint M3 of GAM-L was more extensive in the frequencydomain and the energy value changed dramatically dem-onstrating the abnormal phenomenon that the maindominant energy increased e frequency range of thismeasuring point was 0ndash1885 kHz accounting for 8589 ofthe total energyere was also residual energy concentratedin the frequency band of 29397ndash32913 kHz e AE signalat M3 was superposed by the boundary reflection wave andthe energy was enhanced because of the high homogeneityand good ductility of GAM-L For G3761-L the dominantenergy of the elastic wave almost dissipated at the M3measuring point In the direction of 45deg the dominantenergy band of the original signal in G3761-L was distributedwithin 0ndash17678 kHz and 28225ndash35256 kHz respectivelyaccounting for 6415 and 3278 of the total energyMoreover it can be observed that the distribution of thedominant energy band was from distribution to concen-tration which was distributed in the frequency band of7131ndash17678 kHz at M2 With the increase of distance theenergy frequency band of the M3 measuring point near theedge of the plate was spread again and it was restored to theenergy frequency band range of the initial signal Howeverthe energy value was attenuated to a very small value at this

moment e energies of GAM-L in the measuring pointsM1 M2 and M3 were all distributed in the frequency bandof 0ndash36428 kHz In the direction of 90deg the primarydominant energy frequency bands of the two plate-shapedrocks were concentrated in 9475ndash1885 kHz e differenceis that the energy distribution of GAM-L was still con-centrated and the energy variation was much smaller thanG3761-L at the M2 measuring point In general the energyfrequency band of the two plate-shaped rocks with differentlithologies was the same as that of the rod-shape rock whichis mainly distributed in the range of 0ndash36428 kHz More-over they also exhibited the characteristics that the maindominant energy was distributed in the range of0ndash17678 kHz and the residual energy was distributed in therange of 28225ndash35256 kHz

4 Discussion

e purpose of this work was to study the propagationcharacteristics of elastic wave in lithological rock materialsrough the above research and analysis a preliminaryunderstanding was obtained Based on the deep waveletpacket analysis of amplitude energy characteristic param-eters and AE waveform the frequency band characteristicsof the local energy distribution of elastic wave with itspropagation were summarized However its propagationcharacteristics are difficult to be regularly grasped becausethe elastic wave itself is extremely complex Furthermore AEtechnology is mostly used in the damage detection and

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

20406080

100120140160

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

10

20

30

40

50

(e)

M1

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

200400600800

10001200140016001800

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

50

100

150

200

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 50005

101520253035

(f )

Figure 12e energy distribution of acoustic emission signal frequency band of plate-shaped rock (a) G3761-L (00) (b) G3761-L (450) (c)G3761-L (900) (d) GAM-L (00) (e) GAM-L (450) (f ) GAM-L (900)

Advances in Civil Engineering 17

defect location of metal or related materials with goodcompactness ductility and within the same medium ereare many uncertain interference factors in the experimentsIn some aspects the analysis of this paper only stays at thelevel of the apparent phenomenon and there are still manydeficiencies and areas worthy of improvement For instancethe density wave velocity and wave impedance of the rod-shaped rock samples should be tested and the micro-structure imaging experiments of the rock samples should beconducted e quality factor Q of different rock samplesshould be calculated Moreover the correlation between thequality factor and wave impedance should be studied andthe influence of different microcompositions of rod-shapedrocks on elastic wave attenuation should be deeply analyzedBased on the modal AE theory the influence of Lamb wavein plate-shaped rocks should be studied and the propagationmodel of two-dimensional AE should be constructed eGabor wavelet should be introduced to analyze the AE signalby time-frequency analysis e influence of differentwavelets based on the propagation effect of AE will becompared and analyzed and the time of the same mode ofthe AE wave arriving at the sensor will be determined tofurther optimize the plane location algorithm However theresearch in this work is still useful for studying large-scalerock samples in the future and provides effective researchmethods and ideas for the study of elastic wave propagationcharacteristics of different rock materials and compositematerials

5 Conclusions

In this work the characteristic parameter analysis andwaveform analysis of the AE signals obtained from differentexperimental schemes in 5 groups of rod-shaped rocks and 2groups of plate-shaped rocks were carried out e con-clusions are as follows

(1) e amplitude and energy of the rod-shaped rocksgradually attenuated with the increase of distancee amplitude can directly reflect the intensity of theAE counts at different measuring areas In theprocess of elastic wave propagation of the rod-sha-ped rock the P-wave preceded the S-wave andchanged violently e elastic wave of marble at-tenuated faster and the elastic wave of the threekinds of granite decayed attenuated closely Amongthem the elastic wave of TBG exhibited the fastestattenuation

(2) In flat plate-shaped rocks the amplitude exhibited anapproximate exponential attenuation characteristicwith the increase of the propagation distanceGranite exhibited a stronger elastic wave attenuationin the 0deg direction than the marble and the marblepresented fast attenuations in the 45deg and 90deg di-rections e energy change of marble was dramaticand the energy value in the interval of 45ndash55 cm atthe direction of 0deg showed the abnormal step phe-nomenon e energy value of the marble increasedafter 55 cm in the 45deg direction e energy value of

granite from the back to the end of the plate wasalmost maintained and tended to be stable at20ndash50mVms

(3) e frequency range of the energy distribution ofsamples in this work was within 0ndash36428 kHz Withthe increase of distance the main dominant energydistribution of the 5 groups of rod-shaped rocks inthe frequency range was characterized by distribu-tion to relative concentration and rapid energy at-tenuationemain dominant energy distribution ofthe 2 groups of plate-shaped rocks was distributed inthe range of 0ndash17678 kHz All rod-shaped rocks andplate-shaped rocks exhibited the characteristics ofresidual energy distribution in the frequency band of28225ndash35256 kHz

Data Availability

e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

e authors certify that they have no conflicts of interest

Acknowledgments

is research was funded by the National Natural ScienceFoundation of China (51804161 52074156 and 52004291)the Chinese Postdoctoral Science Foundation(2019M660861) and the State Key Laboratory CultivationBase for Gas Geology and Gas Control (Henan PolytechnicUniversity) (WS2020A04)

References

[1] J T Chen J H Zhao S C Zhang Y Zhang F Yang andM Li ldquoAn experimental and analytical research on theevolution of mining cracks in deep floor rock massrdquo Pure andApplied Geophysics vol 177 no 11 pp 5325ndash5348 2020

[2] K Wang and F Du ldquoCoal-gas compound dynamic disastersin China a reviewrdquo Process Safety and Environmental Pro-tection vol 133 pp 1ndash17 2020

[3] C Zhu M He M Karakus X Cui and Z Tao ldquoInvestigatingtoppling failure mechanism of anti-dip layered slope due toexcavation by physical modellingrdquo Rock Mechanics and RockEngineering vol 53 no 11 pp 5029ndash5050 2020

[4] X Wang C Liu S Chen L Chen K Li and N Liu ldquoImpactof coal sectorrsquos de-capacity policy on coal pricerdquo AppliedEnergy vol 265 Article ID 114802 2020

[5] D Liu Z Gu R Liang et al ldquoImpacts of pore-throat systemon fractal characterization of tight sandstonesrdquo Geofluidsvol 2020 no 9 17 pages Article ID 4941501 2020

[6] J Wang Y Zhang Z Qin S Song and P Lin ldquoAnalysismethod of water inrush for tunnels with damaged water-resisting rock mass based on finite element method-smoothparticle hydrodynamics couplingrdquo Computers and Geo-technics vol 126 Article ID 103725 2020

[7] B Chen S C Zhang Y Y Li Z K Li and H J ZhouldquoPhysical simulation study of crack propagation and insta-bility information discrimination of rock-like materials withfaultsrdquo Arabian Journal of Geosciences vol 13 p 966 2020

18 Advances in Civil Engineering

[8] F Du K Wang X Zhang C Xin and G Wang ldquoExperi-mental study of coal-gas outburst insights from coal-rockstructure gas pressure and adsorptivityrdquo Natural ResourcesResearch vol 29 no 4 pp 2481ndash2493 2020

[9] H Y Wang J Ma G D Wang et al ldquoResearch on AE sourcelocation of linear and plane rock massrdquo Shock and Vibrationvol 2020 Article ID 8846582 18 pages 2020

[10] V A Mansurov ldquoPrediction of rockbursts by analysis ofinduced seismicity datardquo International Journal of Rock Me-chanics and Mining Sciences vol 38 no 6 pp 893ndash901 2001

[11] M C He J L Miao and J L Feng ldquoRock burst process oflimestone and its acoustic emission characteristics under true-triaxial unloading conditionsrdquo International Journal of RockMechanics and Mining Sciences vol 47 no 2 pp 286ndash2982010

[12] F Gong J Yan X Li and S Luo ldquoA peak-strength strainenergy storage index for rock burst proneness of rock ma-terialsrdquo International Journal of Rock Mechanics and MiningSciences vol 117 pp 76ndash89 2019

[13] F Du and KWang ldquoUnstable failure of gas-bearing coal-rockcombination bodies insights from physical experiments andnumerical simulationsrdquo Process Safety and EnvironmentalProtection vol 129 pp 264ndash279 2019

[14] S D Butt C Mukherjee and G Lebans ldquoEvaluation ofacoustic attenuation as an indicator of roof stability in ad-vancing headingsrdquo International Journal of Rock Mechanicsand Mining Sciences vol 37 no 7 pp 1123ndash1131 2000

[15] M Cai H Morioka P K Kaiser et al ldquoBack-analysis of rockmass strength parameters using ae monitoring datardquo Inter-national Journal of Rock Mechanics and Mining Sciencesvol 44 no 4 pp 538ndash549 2007

[16] D P Jansen S R Carlson R P Young and D A HutchinsldquoUltrasonic imaging and acoustic emission monitoring ofthermally induced microcracks in Lac du Bonnet graniterdquoJournal of Geophysical Research Solid Earth vol 98 no B12pp 22231ndash22243 1993

[17] U Bismayer ldquoEarly warning signs for mining accidentsdetecting crackling noiserdquo American Mineralogist vol 102no 1 pp 3-4 2017

[18] X Kong E Wang S Li H Lin P Xiao and K ZhangldquoFractals and chaos characteristics of acoustic emission energyabout gas-bearing coal during loaded failurerdquo Fractals vol 27no 5 Article ID 195072 2019

[19] F Du K Wang G Wang Y Jiang C Xin and X ZhangldquoInvestigation of the acoustic emission characteristics duringdeformation and failure of gas-bearing coal-rock combinedbodiesrdquo Journal of Loss Prevention in the Process Industriesvol 55 pp 253ndash266 2018

[20] R P Young D A Hutchins S Talebi et al ldquoLaboratory andfield investigations of rockburst phenomena using concurrentgeotomographic imaging and acoustic emissionmicroseismictechniquesrdquo Seismicity in Mines vol 129 no 3-4pp 647ndash659 1989

[21] X Jansen H Xu M He and F Zhang ldquoExperimental in-vestigation of the occurrence of rockburst in a rock specimenthrough infrared thermography and acoustic emissionrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 93 pp 250ndash259 2017

[22] R E Goodman and E Richard ldquoSubaudible noise duringcompression of rocksrdquo Geological Society of America Bulletinvol 74 no 4 pp 487ndash490 1963

[23] M Cai P K Kaiser H Morioka et al ldquoFLACPFC couplednumerical simulation of AE in large-scale underground

excavationsrdquo International Journal of Rock Mechanics andMining Sciences vol 44 no 4 pp 550ndash564 2007

[24] V Saltas F Vallianatos D Triantis T Koumoudeli andI Stavrakas ldquoNon-extensive statistical analysis of acousticemissions series recorded during the uniaxial compression ofbrittle rocksrdquo Physica A Statistical Mechanics and Its Ap-plications vol 528 Article ID 121498 2019

[25] V Saltas I Fitilis and F Vallianatos ldquoA combined complexelectrical impedance and acoustic emission study in limestonesamples under uniaxial loadingrdquo Tectonophysics vol 637pp 198ndash206 2014

[26] G Qi ldquoWavelet-based AE characterization of compositematerialsrdquo NDTamp E International vol 33 no 3 pp 133ndash1442000

[27] G Manthei J Eisenblatter and T Dahm ldquoMoment tensorevaluation of acoustic emission sources in salt rockrdquo Con-struction and Building Materials vol 15 no 5-6 pp 297ndash3092001

[28] H Jeong and Y-S Jang ldquoWavelet analysis of plate wavepropagation in composite laminatesrdquo Composite Structuresvol 49 no 4 pp 443ndash450 2000

[29] S-H Chang and C-I Lee ldquoEstimation of cracking anddamage mechanisms in rock under triaxial compression bymoment tensor analysis of acoustic emissionrdquo InternationalJournal of Rock Mechanics and Mining Sciences vol 41 no 7pp 1069ndash1086 2004

[30] T Hirata T Satoh and K Ito ldquoFractal structure of spatialdistribution of microfracturing in rockrdquo Geophysical JournalInternational vol 90 no 2 pp 369ndash374 1987

[31] X Lei K Masuda O Nishizawa et al ldquoDetailed analysis ofacoustic emission activity during catastrophic fracture offaults in rockrdquo Journal of Structural Geology vol 26 no 2pp 247ndash258 2004

[32] J Jouniaux J Pei J Liu et al ldquoInvestigation on acousticemission behavior and its time-space evolution mechanism infailure process of coalndashrock combined bodyrdquo Chinese Journalof Rock Mechanics and Engineering vol 30 pp 1564ndash15702011

[33] E Townend B D ompson P M Benson PG MeredithP Baud and R P Young ldquoImaging compaction bandpropagation in Diemelstadt sandstone using acoustic emis-sion locationsrdquo Geophysical Research Letters vol 35 no 15pp 189ndash193 2008

[34] M Naderloo M Moosavi and M Ahmadi ldquoUsing acousticemission technique tomonitor damage progress around jointsin brittle materialsrdquo Deoretical and Applied Fracture Me-chanics vol 104 Article ID 102368 2019

[35] GBT Unified Number of Natural Stone China StandardsPress Beijing China 2009

[36] G Shen Acoustic Emission Detection Technology and Appli-cation Science Press Beijing China 2015

[37] Y Guo Research on Wavelet Base Selection for VibrationSignal Processing Hefei University of Technology HefeiChina 2003

[38] F Xu E Wang and D Song ldquoLong-range correlation andmultifractal distribution of acoustic emission of coal-rockrdquoRock and Soil Mechanics vol 32 no 7 pp 2111ndash2116 2011

Advances in Civil Engineering 19

0 100 200 300 400 5000

200400600800

100012001400

Frequency (KHZ)

M1

Ener

gy (m

Vlowast

mS)

M2

0 100 200 300 400 5000005101520253035

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

M3

0 100 200 300 400 50000020406081012

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

(a)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

10

20

30

40En

ergy

(mVlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 5000

2

4

6

8

Ener

gy (m

Vlowast

mS)

(b)

M1

Frequency (KHZ)

0 100 200 300 400 5000

500100015002000250030003500

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 5000

1020304050607080

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50002468

1012141618

Ener

gy (m

Vlowast

mS)

(c)

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700800

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

0 100 200 300 400 50005

101520253035

Ener

gy (m

Vlowast

mS)

M3

Frequency (KHZ)

0 100 200 300 400 50005

10152025303540

Ener

gy (m

Vlowast

mS)

(d)

Figure 12 Continued

16 Advances in Civil Engineering

G3761-L showed a trend of attenuation and the energy intheM2measuring point was still distributed in the frequencyband of 0ndash17678 kHz e energy distribution at the M3measuring point was relatively concentrated and was locatedin the frequency band of 0ndash10647 kHz accounting for8340 of the total energy e energy at the measuringpoint M3 of GAM-L was more extensive in the frequencydomain and the energy value changed dramatically dem-onstrating the abnormal phenomenon that the maindominant energy increased e frequency range of thismeasuring point was 0ndash1885 kHz accounting for 8589 ofthe total energyere was also residual energy concentratedin the frequency band of 29397ndash32913 kHz e AE signalat M3 was superposed by the boundary reflection wave andthe energy was enhanced because of the high homogeneityand good ductility of GAM-L For G3761-L the dominantenergy of the elastic wave almost dissipated at the M3measuring point In the direction of 45deg the dominantenergy band of the original signal in G3761-L was distributedwithin 0ndash17678 kHz and 28225ndash35256 kHz respectivelyaccounting for 6415 and 3278 of the total energyMoreover it can be observed that the distribution of thedominant energy band was from distribution to concen-tration which was distributed in the frequency band of7131ndash17678 kHz at M2 With the increase of distance theenergy frequency band of the M3 measuring point near theedge of the plate was spread again and it was restored to theenergy frequency band range of the initial signal Howeverthe energy value was attenuated to a very small value at this

moment e energies of GAM-L in the measuring pointsM1 M2 and M3 were all distributed in the frequency bandof 0ndash36428 kHz In the direction of 90deg the primarydominant energy frequency bands of the two plate-shapedrocks were concentrated in 9475ndash1885 kHz e differenceis that the energy distribution of GAM-L was still con-centrated and the energy variation was much smaller thanG3761-L at the M2 measuring point In general the energyfrequency band of the two plate-shaped rocks with differentlithologies was the same as that of the rod-shape rock whichis mainly distributed in the range of 0ndash36428 kHz More-over they also exhibited the characteristics that the maindominant energy was distributed in the range of0ndash17678 kHz and the residual energy was distributed in therange of 28225ndash35256 kHz

4 Discussion

e purpose of this work was to study the propagationcharacteristics of elastic wave in lithological rock materialsrough the above research and analysis a preliminaryunderstanding was obtained Based on the deep waveletpacket analysis of amplitude energy characteristic param-eters and AE waveform the frequency band characteristicsof the local energy distribution of elastic wave with itspropagation were summarized However its propagationcharacteristics are difficult to be regularly grasped becausethe elastic wave itself is extremely complex Furthermore AEtechnology is mostly used in the damage detection and

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

20406080

100120140160

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

10

20

30

40

50

(e)

M1

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

200400600800

10001200140016001800

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

50

100

150

200

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 50005

101520253035

(f )

Figure 12e energy distribution of acoustic emission signal frequency band of plate-shaped rock (a) G3761-L (00) (b) G3761-L (450) (c)G3761-L (900) (d) GAM-L (00) (e) GAM-L (450) (f ) GAM-L (900)

Advances in Civil Engineering 17

defect location of metal or related materials with goodcompactness ductility and within the same medium ereare many uncertain interference factors in the experimentsIn some aspects the analysis of this paper only stays at thelevel of the apparent phenomenon and there are still manydeficiencies and areas worthy of improvement For instancethe density wave velocity and wave impedance of the rod-shaped rock samples should be tested and the micro-structure imaging experiments of the rock samples should beconducted e quality factor Q of different rock samplesshould be calculated Moreover the correlation between thequality factor and wave impedance should be studied andthe influence of different microcompositions of rod-shapedrocks on elastic wave attenuation should be deeply analyzedBased on the modal AE theory the influence of Lamb wavein plate-shaped rocks should be studied and the propagationmodel of two-dimensional AE should be constructed eGabor wavelet should be introduced to analyze the AE signalby time-frequency analysis e influence of differentwavelets based on the propagation effect of AE will becompared and analyzed and the time of the same mode ofthe AE wave arriving at the sensor will be determined tofurther optimize the plane location algorithm However theresearch in this work is still useful for studying large-scalerock samples in the future and provides effective researchmethods and ideas for the study of elastic wave propagationcharacteristics of different rock materials and compositematerials

5 Conclusions

In this work the characteristic parameter analysis andwaveform analysis of the AE signals obtained from differentexperimental schemes in 5 groups of rod-shaped rocks and 2groups of plate-shaped rocks were carried out e con-clusions are as follows

(1) e amplitude and energy of the rod-shaped rocksgradually attenuated with the increase of distancee amplitude can directly reflect the intensity of theAE counts at different measuring areas In theprocess of elastic wave propagation of the rod-sha-ped rock the P-wave preceded the S-wave andchanged violently e elastic wave of marble at-tenuated faster and the elastic wave of the threekinds of granite decayed attenuated closely Amongthem the elastic wave of TBG exhibited the fastestattenuation

(2) In flat plate-shaped rocks the amplitude exhibited anapproximate exponential attenuation characteristicwith the increase of the propagation distanceGranite exhibited a stronger elastic wave attenuationin the 0deg direction than the marble and the marblepresented fast attenuations in the 45deg and 90deg di-rections e energy change of marble was dramaticand the energy value in the interval of 45ndash55 cm atthe direction of 0deg showed the abnormal step phe-nomenon e energy value of the marble increasedafter 55 cm in the 45deg direction e energy value of

granite from the back to the end of the plate wasalmost maintained and tended to be stable at20ndash50mVms

(3) e frequency range of the energy distribution ofsamples in this work was within 0ndash36428 kHz Withthe increase of distance the main dominant energydistribution of the 5 groups of rod-shaped rocks inthe frequency range was characterized by distribu-tion to relative concentration and rapid energy at-tenuationemain dominant energy distribution ofthe 2 groups of plate-shaped rocks was distributed inthe range of 0ndash17678 kHz All rod-shaped rocks andplate-shaped rocks exhibited the characteristics ofresidual energy distribution in the frequency band of28225ndash35256 kHz

Data Availability

e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

e authors certify that they have no conflicts of interest

Acknowledgments

is research was funded by the National Natural ScienceFoundation of China (51804161 52074156 and 52004291)the Chinese Postdoctoral Science Foundation(2019M660861) and the State Key Laboratory CultivationBase for Gas Geology and Gas Control (Henan PolytechnicUniversity) (WS2020A04)

References

[1] J T Chen J H Zhao S C Zhang Y Zhang F Yang andM Li ldquoAn experimental and analytical research on theevolution of mining cracks in deep floor rock massrdquo Pure andApplied Geophysics vol 177 no 11 pp 5325ndash5348 2020

[2] K Wang and F Du ldquoCoal-gas compound dynamic disastersin China a reviewrdquo Process Safety and Environmental Pro-tection vol 133 pp 1ndash17 2020

[3] C Zhu M He M Karakus X Cui and Z Tao ldquoInvestigatingtoppling failure mechanism of anti-dip layered slope due toexcavation by physical modellingrdquo Rock Mechanics and RockEngineering vol 53 no 11 pp 5029ndash5050 2020

[4] X Wang C Liu S Chen L Chen K Li and N Liu ldquoImpactof coal sectorrsquos de-capacity policy on coal pricerdquo AppliedEnergy vol 265 Article ID 114802 2020

[5] D Liu Z Gu R Liang et al ldquoImpacts of pore-throat systemon fractal characterization of tight sandstonesrdquo Geofluidsvol 2020 no 9 17 pages Article ID 4941501 2020

[6] J Wang Y Zhang Z Qin S Song and P Lin ldquoAnalysismethod of water inrush for tunnels with damaged water-resisting rock mass based on finite element method-smoothparticle hydrodynamics couplingrdquo Computers and Geo-technics vol 126 Article ID 103725 2020

[7] B Chen S C Zhang Y Y Li Z K Li and H J ZhouldquoPhysical simulation study of crack propagation and insta-bility information discrimination of rock-like materials withfaultsrdquo Arabian Journal of Geosciences vol 13 p 966 2020

18 Advances in Civil Engineering

[8] F Du K Wang X Zhang C Xin and G Wang ldquoExperi-mental study of coal-gas outburst insights from coal-rockstructure gas pressure and adsorptivityrdquo Natural ResourcesResearch vol 29 no 4 pp 2481ndash2493 2020

[9] H Y Wang J Ma G D Wang et al ldquoResearch on AE sourcelocation of linear and plane rock massrdquo Shock and Vibrationvol 2020 Article ID 8846582 18 pages 2020

[10] V A Mansurov ldquoPrediction of rockbursts by analysis ofinduced seismicity datardquo International Journal of Rock Me-chanics and Mining Sciences vol 38 no 6 pp 893ndash901 2001

[11] M C He J L Miao and J L Feng ldquoRock burst process oflimestone and its acoustic emission characteristics under true-triaxial unloading conditionsrdquo International Journal of RockMechanics and Mining Sciences vol 47 no 2 pp 286ndash2982010

[12] F Gong J Yan X Li and S Luo ldquoA peak-strength strainenergy storage index for rock burst proneness of rock ma-terialsrdquo International Journal of Rock Mechanics and MiningSciences vol 117 pp 76ndash89 2019

[13] F Du and KWang ldquoUnstable failure of gas-bearing coal-rockcombination bodies insights from physical experiments andnumerical simulationsrdquo Process Safety and EnvironmentalProtection vol 129 pp 264ndash279 2019

[14] S D Butt C Mukherjee and G Lebans ldquoEvaluation ofacoustic attenuation as an indicator of roof stability in ad-vancing headingsrdquo International Journal of Rock Mechanicsand Mining Sciences vol 37 no 7 pp 1123ndash1131 2000

[15] M Cai H Morioka P K Kaiser et al ldquoBack-analysis of rockmass strength parameters using ae monitoring datardquo Inter-national Journal of Rock Mechanics and Mining Sciencesvol 44 no 4 pp 538ndash549 2007

[16] D P Jansen S R Carlson R P Young and D A HutchinsldquoUltrasonic imaging and acoustic emission monitoring ofthermally induced microcracks in Lac du Bonnet graniterdquoJournal of Geophysical Research Solid Earth vol 98 no B12pp 22231ndash22243 1993

[17] U Bismayer ldquoEarly warning signs for mining accidentsdetecting crackling noiserdquo American Mineralogist vol 102no 1 pp 3-4 2017

[18] X Kong E Wang S Li H Lin P Xiao and K ZhangldquoFractals and chaos characteristics of acoustic emission energyabout gas-bearing coal during loaded failurerdquo Fractals vol 27no 5 Article ID 195072 2019

[19] F Du K Wang G Wang Y Jiang C Xin and X ZhangldquoInvestigation of the acoustic emission characteristics duringdeformation and failure of gas-bearing coal-rock combinedbodiesrdquo Journal of Loss Prevention in the Process Industriesvol 55 pp 253ndash266 2018

[20] R P Young D A Hutchins S Talebi et al ldquoLaboratory andfield investigations of rockburst phenomena using concurrentgeotomographic imaging and acoustic emissionmicroseismictechniquesrdquo Seismicity in Mines vol 129 no 3-4pp 647ndash659 1989

[21] X Jansen H Xu M He and F Zhang ldquoExperimental in-vestigation of the occurrence of rockburst in a rock specimenthrough infrared thermography and acoustic emissionrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 93 pp 250ndash259 2017

[22] R E Goodman and E Richard ldquoSubaudible noise duringcompression of rocksrdquo Geological Society of America Bulletinvol 74 no 4 pp 487ndash490 1963

[23] M Cai P K Kaiser H Morioka et al ldquoFLACPFC couplednumerical simulation of AE in large-scale underground

excavationsrdquo International Journal of Rock Mechanics andMining Sciences vol 44 no 4 pp 550ndash564 2007

[24] V Saltas F Vallianatos D Triantis T Koumoudeli andI Stavrakas ldquoNon-extensive statistical analysis of acousticemissions series recorded during the uniaxial compression ofbrittle rocksrdquo Physica A Statistical Mechanics and Its Ap-plications vol 528 Article ID 121498 2019

[25] V Saltas I Fitilis and F Vallianatos ldquoA combined complexelectrical impedance and acoustic emission study in limestonesamples under uniaxial loadingrdquo Tectonophysics vol 637pp 198ndash206 2014

[26] G Qi ldquoWavelet-based AE characterization of compositematerialsrdquo NDTamp E International vol 33 no 3 pp 133ndash1442000

[27] G Manthei J Eisenblatter and T Dahm ldquoMoment tensorevaluation of acoustic emission sources in salt rockrdquo Con-struction and Building Materials vol 15 no 5-6 pp 297ndash3092001

[28] H Jeong and Y-S Jang ldquoWavelet analysis of plate wavepropagation in composite laminatesrdquo Composite Structuresvol 49 no 4 pp 443ndash450 2000

[29] S-H Chang and C-I Lee ldquoEstimation of cracking anddamage mechanisms in rock under triaxial compression bymoment tensor analysis of acoustic emissionrdquo InternationalJournal of Rock Mechanics and Mining Sciences vol 41 no 7pp 1069ndash1086 2004

[30] T Hirata T Satoh and K Ito ldquoFractal structure of spatialdistribution of microfracturing in rockrdquo Geophysical JournalInternational vol 90 no 2 pp 369ndash374 1987

[31] X Lei K Masuda O Nishizawa et al ldquoDetailed analysis ofacoustic emission activity during catastrophic fracture offaults in rockrdquo Journal of Structural Geology vol 26 no 2pp 247ndash258 2004

[32] J Jouniaux J Pei J Liu et al ldquoInvestigation on acousticemission behavior and its time-space evolution mechanism infailure process of coalndashrock combined bodyrdquo Chinese Journalof Rock Mechanics and Engineering vol 30 pp 1564ndash15702011

[33] E Townend B D ompson P M Benson PG MeredithP Baud and R P Young ldquoImaging compaction bandpropagation in Diemelstadt sandstone using acoustic emis-sion locationsrdquo Geophysical Research Letters vol 35 no 15pp 189ndash193 2008

[34] M Naderloo M Moosavi and M Ahmadi ldquoUsing acousticemission technique tomonitor damage progress around jointsin brittle materialsrdquo Deoretical and Applied Fracture Me-chanics vol 104 Article ID 102368 2019

[35] GBT Unified Number of Natural Stone China StandardsPress Beijing China 2009

[36] G Shen Acoustic Emission Detection Technology and Appli-cation Science Press Beijing China 2015

[37] Y Guo Research on Wavelet Base Selection for VibrationSignal Processing Hefei University of Technology HefeiChina 2003

[38] F Xu E Wang and D Song ldquoLong-range correlation andmultifractal distribution of acoustic emission of coal-rockrdquoRock and Soil Mechanics vol 32 no 7 pp 2111ndash2116 2011

Advances in Civil Engineering 19

G3761-L showed a trend of attenuation and the energy intheM2measuring point was still distributed in the frequencyband of 0ndash17678 kHz e energy distribution at the M3measuring point was relatively concentrated and was locatedin the frequency band of 0ndash10647 kHz accounting for8340 of the total energy e energy at the measuringpoint M3 of GAM-L was more extensive in the frequencydomain and the energy value changed dramatically dem-onstrating the abnormal phenomenon that the maindominant energy increased e frequency range of thismeasuring point was 0ndash1885 kHz accounting for 8589 ofthe total energyere was also residual energy concentratedin the frequency band of 29397ndash32913 kHz e AE signalat M3 was superposed by the boundary reflection wave andthe energy was enhanced because of the high homogeneityand good ductility of GAM-L For G3761-L the dominantenergy of the elastic wave almost dissipated at the M3measuring point In the direction of 45deg the dominantenergy band of the original signal in G3761-L was distributedwithin 0ndash17678 kHz and 28225ndash35256 kHz respectivelyaccounting for 6415 and 3278 of the total energyMoreover it can be observed that the distribution of thedominant energy band was from distribution to concen-tration which was distributed in the frequency band of7131ndash17678 kHz at M2 With the increase of distance theenergy frequency band of the M3 measuring point near theedge of the plate was spread again and it was restored to theenergy frequency band range of the initial signal Howeverthe energy value was attenuated to a very small value at this

moment e energies of GAM-L in the measuring pointsM1 M2 and M3 were all distributed in the frequency bandof 0ndash36428 kHz In the direction of 90deg the primarydominant energy frequency bands of the two plate-shapedrocks were concentrated in 9475ndash1885 kHz e differenceis that the energy distribution of GAM-L was still con-centrated and the energy variation was much smaller thanG3761-L at the M2 measuring point In general the energyfrequency band of the two plate-shaped rocks with differentlithologies was the same as that of the rod-shape rock whichis mainly distributed in the range of 0ndash36428 kHz More-over they also exhibited the characteristics that the maindominant energy was distributed in the range of0ndash17678 kHz and the residual energy was distributed in therange of 28225ndash35256 kHz

4 Discussion

e purpose of this work was to study the propagationcharacteristics of elastic wave in lithological rock materialsrough the above research and analysis a preliminaryunderstanding was obtained Based on the deep waveletpacket analysis of amplitude energy characteristic param-eters and AE waveform the frequency band characteristicsof the local energy distribution of elastic wave with itspropagation were summarized However its propagationcharacteristics are difficult to be regularly grasped becausethe elastic wave itself is extremely complex Furthermore AEtechnology is mostly used in the damage detection and

M1

Frequency (KHZ)

0 100 200 300 400 5000

100200300400500600700

Ener

gy (m

Vlowast

mS)

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

20406080

100120140160

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

10

20

30

40

50

(e)

M1

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

200400600800

10001200140016001800

M2

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 5000

50

100

150

200

M3

Frequency (KHZ)

Ener

gy (m

Vlowast

mS)

0 100 200 300 400 50005

101520253035

(f )

Figure 12e energy distribution of acoustic emission signal frequency band of plate-shaped rock (a) G3761-L (00) (b) G3761-L (450) (c)G3761-L (900) (d) GAM-L (00) (e) GAM-L (450) (f ) GAM-L (900)

Advances in Civil Engineering 17

defect location of metal or related materials with goodcompactness ductility and within the same medium ereare many uncertain interference factors in the experimentsIn some aspects the analysis of this paper only stays at thelevel of the apparent phenomenon and there are still manydeficiencies and areas worthy of improvement For instancethe density wave velocity and wave impedance of the rod-shaped rock samples should be tested and the micro-structure imaging experiments of the rock samples should beconducted e quality factor Q of different rock samplesshould be calculated Moreover the correlation between thequality factor and wave impedance should be studied andthe influence of different microcompositions of rod-shapedrocks on elastic wave attenuation should be deeply analyzedBased on the modal AE theory the influence of Lamb wavein plate-shaped rocks should be studied and the propagationmodel of two-dimensional AE should be constructed eGabor wavelet should be introduced to analyze the AE signalby time-frequency analysis e influence of differentwavelets based on the propagation effect of AE will becompared and analyzed and the time of the same mode ofthe AE wave arriving at the sensor will be determined tofurther optimize the plane location algorithm However theresearch in this work is still useful for studying large-scalerock samples in the future and provides effective researchmethods and ideas for the study of elastic wave propagationcharacteristics of different rock materials and compositematerials

5 Conclusions

In this work the characteristic parameter analysis andwaveform analysis of the AE signals obtained from differentexperimental schemes in 5 groups of rod-shaped rocks and 2groups of plate-shaped rocks were carried out e con-clusions are as follows

(1) e amplitude and energy of the rod-shaped rocksgradually attenuated with the increase of distancee amplitude can directly reflect the intensity of theAE counts at different measuring areas In theprocess of elastic wave propagation of the rod-sha-ped rock the P-wave preceded the S-wave andchanged violently e elastic wave of marble at-tenuated faster and the elastic wave of the threekinds of granite decayed attenuated closely Amongthem the elastic wave of TBG exhibited the fastestattenuation

(2) In flat plate-shaped rocks the amplitude exhibited anapproximate exponential attenuation characteristicwith the increase of the propagation distanceGranite exhibited a stronger elastic wave attenuationin the 0deg direction than the marble and the marblepresented fast attenuations in the 45deg and 90deg di-rections e energy change of marble was dramaticand the energy value in the interval of 45ndash55 cm atthe direction of 0deg showed the abnormal step phe-nomenon e energy value of the marble increasedafter 55 cm in the 45deg direction e energy value of

granite from the back to the end of the plate wasalmost maintained and tended to be stable at20ndash50mVms

(3) e frequency range of the energy distribution ofsamples in this work was within 0ndash36428 kHz Withthe increase of distance the main dominant energydistribution of the 5 groups of rod-shaped rocks inthe frequency range was characterized by distribu-tion to relative concentration and rapid energy at-tenuationemain dominant energy distribution ofthe 2 groups of plate-shaped rocks was distributed inthe range of 0ndash17678 kHz All rod-shaped rocks andplate-shaped rocks exhibited the characteristics ofresidual energy distribution in the frequency band of28225ndash35256 kHz

Data Availability

e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

e authors certify that they have no conflicts of interest

Acknowledgments

is research was funded by the National Natural ScienceFoundation of China (51804161 52074156 and 52004291)the Chinese Postdoctoral Science Foundation(2019M660861) and the State Key Laboratory CultivationBase for Gas Geology and Gas Control (Henan PolytechnicUniversity) (WS2020A04)

References

[1] J T Chen J H Zhao S C Zhang Y Zhang F Yang andM Li ldquoAn experimental and analytical research on theevolution of mining cracks in deep floor rock massrdquo Pure andApplied Geophysics vol 177 no 11 pp 5325ndash5348 2020

[2] K Wang and F Du ldquoCoal-gas compound dynamic disastersin China a reviewrdquo Process Safety and Environmental Pro-tection vol 133 pp 1ndash17 2020

[3] C Zhu M He M Karakus X Cui and Z Tao ldquoInvestigatingtoppling failure mechanism of anti-dip layered slope due toexcavation by physical modellingrdquo Rock Mechanics and RockEngineering vol 53 no 11 pp 5029ndash5050 2020

[4] X Wang C Liu S Chen L Chen K Li and N Liu ldquoImpactof coal sectorrsquos de-capacity policy on coal pricerdquo AppliedEnergy vol 265 Article ID 114802 2020

[5] D Liu Z Gu R Liang et al ldquoImpacts of pore-throat systemon fractal characterization of tight sandstonesrdquo Geofluidsvol 2020 no 9 17 pages Article ID 4941501 2020

[6] J Wang Y Zhang Z Qin S Song and P Lin ldquoAnalysismethod of water inrush for tunnels with damaged water-resisting rock mass based on finite element method-smoothparticle hydrodynamics couplingrdquo Computers and Geo-technics vol 126 Article ID 103725 2020

[7] B Chen S C Zhang Y Y Li Z K Li and H J ZhouldquoPhysical simulation study of crack propagation and insta-bility information discrimination of rock-like materials withfaultsrdquo Arabian Journal of Geosciences vol 13 p 966 2020

18 Advances in Civil Engineering

[8] F Du K Wang X Zhang C Xin and G Wang ldquoExperi-mental study of coal-gas outburst insights from coal-rockstructure gas pressure and adsorptivityrdquo Natural ResourcesResearch vol 29 no 4 pp 2481ndash2493 2020

[9] H Y Wang J Ma G D Wang et al ldquoResearch on AE sourcelocation of linear and plane rock massrdquo Shock and Vibrationvol 2020 Article ID 8846582 18 pages 2020

[10] V A Mansurov ldquoPrediction of rockbursts by analysis ofinduced seismicity datardquo International Journal of Rock Me-chanics and Mining Sciences vol 38 no 6 pp 893ndash901 2001

[11] M C He J L Miao and J L Feng ldquoRock burst process oflimestone and its acoustic emission characteristics under true-triaxial unloading conditionsrdquo International Journal of RockMechanics and Mining Sciences vol 47 no 2 pp 286ndash2982010

[12] F Gong J Yan X Li and S Luo ldquoA peak-strength strainenergy storage index for rock burst proneness of rock ma-terialsrdquo International Journal of Rock Mechanics and MiningSciences vol 117 pp 76ndash89 2019

[13] F Du and KWang ldquoUnstable failure of gas-bearing coal-rockcombination bodies insights from physical experiments andnumerical simulationsrdquo Process Safety and EnvironmentalProtection vol 129 pp 264ndash279 2019

[14] S D Butt C Mukherjee and G Lebans ldquoEvaluation ofacoustic attenuation as an indicator of roof stability in ad-vancing headingsrdquo International Journal of Rock Mechanicsand Mining Sciences vol 37 no 7 pp 1123ndash1131 2000

[15] M Cai H Morioka P K Kaiser et al ldquoBack-analysis of rockmass strength parameters using ae monitoring datardquo Inter-national Journal of Rock Mechanics and Mining Sciencesvol 44 no 4 pp 538ndash549 2007

[16] D P Jansen S R Carlson R P Young and D A HutchinsldquoUltrasonic imaging and acoustic emission monitoring ofthermally induced microcracks in Lac du Bonnet graniterdquoJournal of Geophysical Research Solid Earth vol 98 no B12pp 22231ndash22243 1993

[17] U Bismayer ldquoEarly warning signs for mining accidentsdetecting crackling noiserdquo American Mineralogist vol 102no 1 pp 3-4 2017

[18] X Kong E Wang S Li H Lin P Xiao and K ZhangldquoFractals and chaos characteristics of acoustic emission energyabout gas-bearing coal during loaded failurerdquo Fractals vol 27no 5 Article ID 195072 2019

[19] F Du K Wang G Wang Y Jiang C Xin and X ZhangldquoInvestigation of the acoustic emission characteristics duringdeformation and failure of gas-bearing coal-rock combinedbodiesrdquo Journal of Loss Prevention in the Process Industriesvol 55 pp 253ndash266 2018

[20] R P Young D A Hutchins S Talebi et al ldquoLaboratory andfield investigations of rockburst phenomena using concurrentgeotomographic imaging and acoustic emissionmicroseismictechniquesrdquo Seismicity in Mines vol 129 no 3-4pp 647ndash659 1989

[21] X Jansen H Xu M He and F Zhang ldquoExperimental in-vestigation of the occurrence of rockburst in a rock specimenthrough infrared thermography and acoustic emissionrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 93 pp 250ndash259 2017

[22] R E Goodman and E Richard ldquoSubaudible noise duringcompression of rocksrdquo Geological Society of America Bulletinvol 74 no 4 pp 487ndash490 1963

[23] M Cai P K Kaiser H Morioka et al ldquoFLACPFC couplednumerical simulation of AE in large-scale underground

excavationsrdquo International Journal of Rock Mechanics andMining Sciences vol 44 no 4 pp 550ndash564 2007

[24] V Saltas F Vallianatos D Triantis T Koumoudeli andI Stavrakas ldquoNon-extensive statistical analysis of acousticemissions series recorded during the uniaxial compression ofbrittle rocksrdquo Physica A Statistical Mechanics and Its Ap-plications vol 528 Article ID 121498 2019

[25] V Saltas I Fitilis and F Vallianatos ldquoA combined complexelectrical impedance and acoustic emission study in limestonesamples under uniaxial loadingrdquo Tectonophysics vol 637pp 198ndash206 2014

[26] G Qi ldquoWavelet-based AE characterization of compositematerialsrdquo NDTamp E International vol 33 no 3 pp 133ndash1442000

[27] G Manthei J Eisenblatter and T Dahm ldquoMoment tensorevaluation of acoustic emission sources in salt rockrdquo Con-struction and Building Materials vol 15 no 5-6 pp 297ndash3092001

[28] H Jeong and Y-S Jang ldquoWavelet analysis of plate wavepropagation in composite laminatesrdquo Composite Structuresvol 49 no 4 pp 443ndash450 2000

[29] S-H Chang and C-I Lee ldquoEstimation of cracking anddamage mechanisms in rock under triaxial compression bymoment tensor analysis of acoustic emissionrdquo InternationalJournal of Rock Mechanics and Mining Sciences vol 41 no 7pp 1069ndash1086 2004

[30] T Hirata T Satoh and K Ito ldquoFractal structure of spatialdistribution of microfracturing in rockrdquo Geophysical JournalInternational vol 90 no 2 pp 369ndash374 1987

[31] X Lei K Masuda O Nishizawa et al ldquoDetailed analysis ofacoustic emission activity during catastrophic fracture offaults in rockrdquo Journal of Structural Geology vol 26 no 2pp 247ndash258 2004

[32] J Jouniaux J Pei J Liu et al ldquoInvestigation on acousticemission behavior and its time-space evolution mechanism infailure process of coalndashrock combined bodyrdquo Chinese Journalof Rock Mechanics and Engineering vol 30 pp 1564ndash15702011

[33] E Townend B D ompson P M Benson PG MeredithP Baud and R P Young ldquoImaging compaction bandpropagation in Diemelstadt sandstone using acoustic emis-sion locationsrdquo Geophysical Research Letters vol 35 no 15pp 189ndash193 2008

[34] M Naderloo M Moosavi and M Ahmadi ldquoUsing acousticemission technique tomonitor damage progress around jointsin brittle materialsrdquo Deoretical and Applied Fracture Me-chanics vol 104 Article ID 102368 2019

[35] GBT Unified Number of Natural Stone China StandardsPress Beijing China 2009

[36] G Shen Acoustic Emission Detection Technology and Appli-cation Science Press Beijing China 2015

[37] Y Guo Research on Wavelet Base Selection for VibrationSignal Processing Hefei University of Technology HefeiChina 2003

[38] F Xu E Wang and D Song ldquoLong-range correlation andmultifractal distribution of acoustic emission of coal-rockrdquoRock and Soil Mechanics vol 32 no 7 pp 2111ndash2116 2011

Advances in Civil Engineering 19

defect location of metal or related materials with goodcompactness ductility and within the same medium ereare many uncertain interference factors in the experimentsIn some aspects the analysis of this paper only stays at thelevel of the apparent phenomenon and there are still manydeficiencies and areas worthy of improvement For instancethe density wave velocity and wave impedance of the rod-shaped rock samples should be tested and the micro-structure imaging experiments of the rock samples should beconducted e quality factor Q of different rock samplesshould be calculated Moreover the correlation between thequality factor and wave impedance should be studied andthe influence of different microcompositions of rod-shapedrocks on elastic wave attenuation should be deeply analyzedBased on the modal AE theory the influence of Lamb wavein plate-shaped rocks should be studied and the propagationmodel of two-dimensional AE should be constructed eGabor wavelet should be introduced to analyze the AE signalby time-frequency analysis e influence of differentwavelets based on the propagation effect of AE will becompared and analyzed and the time of the same mode ofthe AE wave arriving at the sensor will be determined tofurther optimize the plane location algorithm However theresearch in this work is still useful for studying large-scalerock samples in the future and provides effective researchmethods and ideas for the study of elastic wave propagationcharacteristics of different rock materials and compositematerials

5 Conclusions

In this work the characteristic parameter analysis andwaveform analysis of the AE signals obtained from differentexperimental schemes in 5 groups of rod-shaped rocks and 2groups of plate-shaped rocks were carried out e con-clusions are as follows

(1) e amplitude and energy of the rod-shaped rocksgradually attenuated with the increase of distancee amplitude can directly reflect the intensity of theAE counts at different measuring areas In theprocess of elastic wave propagation of the rod-sha-ped rock the P-wave preceded the S-wave andchanged violently e elastic wave of marble at-tenuated faster and the elastic wave of the threekinds of granite decayed attenuated closely Amongthem the elastic wave of TBG exhibited the fastestattenuation

(2) In flat plate-shaped rocks the amplitude exhibited anapproximate exponential attenuation characteristicwith the increase of the propagation distanceGranite exhibited a stronger elastic wave attenuationin the 0deg direction than the marble and the marblepresented fast attenuations in the 45deg and 90deg di-rections e energy change of marble was dramaticand the energy value in the interval of 45ndash55 cm atthe direction of 0deg showed the abnormal step phe-nomenon e energy value of the marble increasedafter 55 cm in the 45deg direction e energy value of

granite from the back to the end of the plate wasalmost maintained and tended to be stable at20ndash50mVms

(3) e frequency range of the energy distribution ofsamples in this work was within 0ndash36428 kHz Withthe increase of distance the main dominant energydistribution of the 5 groups of rod-shaped rocks inthe frequency range was characterized by distribu-tion to relative concentration and rapid energy at-tenuationemain dominant energy distribution ofthe 2 groups of plate-shaped rocks was distributed inthe range of 0ndash17678 kHz All rod-shaped rocks andplate-shaped rocks exhibited the characteristics ofresidual energy distribution in the frequency band of28225ndash35256 kHz

Data Availability

e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

e authors certify that they have no conflicts of interest

Acknowledgments

is research was funded by the National Natural ScienceFoundation of China (51804161 52074156 and 52004291)the Chinese Postdoctoral Science Foundation(2019M660861) and the State Key Laboratory CultivationBase for Gas Geology and Gas Control (Henan PolytechnicUniversity) (WS2020A04)

References

[1] J T Chen J H Zhao S C Zhang Y Zhang F Yang andM Li ldquoAn experimental and analytical research on theevolution of mining cracks in deep floor rock massrdquo Pure andApplied Geophysics vol 177 no 11 pp 5325ndash5348 2020

[2] K Wang and F Du ldquoCoal-gas compound dynamic disastersin China a reviewrdquo Process Safety and Environmental Pro-tection vol 133 pp 1ndash17 2020

[3] C Zhu M He M Karakus X Cui and Z Tao ldquoInvestigatingtoppling failure mechanism of anti-dip layered slope due toexcavation by physical modellingrdquo Rock Mechanics and RockEngineering vol 53 no 11 pp 5029ndash5050 2020

[4] X Wang C Liu S Chen L Chen K Li and N Liu ldquoImpactof coal sectorrsquos de-capacity policy on coal pricerdquo AppliedEnergy vol 265 Article ID 114802 2020

[5] D Liu Z Gu R Liang et al ldquoImpacts of pore-throat systemon fractal characterization of tight sandstonesrdquo Geofluidsvol 2020 no 9 17 pages Article ID 4941501 2020

[6] J Wang Y Zhang Z Qin S Song and P Lin ldquoAnalysismethod of water inrush for tunnels with damaged water-resisting rock mass based on finite element method-smoothparticle hydrodynamics couplingrdquo Computers and Geo-technics vol 126 Article ID 103725 2020

[7] B Chen S C Zhang Y Y Li Z K Li and H J ZhouldquoPhysical simulation study of crack propagation and insta-bility information discrimination of rock-like materials withfaultsrdquo Arabian Journal of Geosciences vol 13 p 966 2020

18 Advances in Civil Engineering

[8] F Du K Wang X Zhang C Xin and G Wang ldquoExperi-mental study of coal-gas outburst insights from coal-rockstructure gas pressure and adsorptivityrdquo Natural ResourcesResearch vol 29 no 4 pp 2481ndash2493 2020

[9] H Y Wang J Ma G D Wang et al ldquoResearch on AE sourcelocation of linear and plane rock massrdquo Shock and Vibrationvol 2020 Article ID 8846582 18 pages 2020

[10] V A Mansurov ldquoPrediction of rockbursts by analysis ofinduced seismicity datardquo International Journal of Rock Me-chanics and Mining Sciences vol 38 no 6 pp 893ndash901 2001

[11] M C He J L Miao and J L Feng ldquoRock burst process oflimestone and its acoustic emission characteristics under true-triaxial unloading conditionsrdquo International Journal of RockMechanics and Mining Sciences vol 47 no 2 pp 286ndash2982010

[12] F Gong J Yan X Li and S Luo ldquoA peak-strength strainenergy storage index for rock burst proneness of rock ma-terialsrdquo International Journal of Rock Mechanics and MiningSciences vol 117 pp 76ndash89 2019

[13] F Du and KWang ldquoUnstable failure of gas-bearing coal-rockcombination bodies insights from physical experiments andnumerical simulationsrdquo Process Safety and EnvironmentalProtection vol 129 pp 264ndash279 2019

[14] S D Butt C Mukherjee and G Lebans ldquoEvaluation ofacoustic attenuation as an indicator of roof stability in ad-vancing headingsrdquo International Journal of Rock Mechanicsand Mining Sciences vol 37 no 7 pp 1123ndash1131 2000

[15] M Cai H Morioka P K Kaiser et al ldquoBack-analysis of rockmass strength parameters using ae monitoring datardquo Inter-national Journal of Rock Mechanics and Mining Sciencesvol 44 no 4 pp 538ndash549 2007

[16] D P Jansen S R Carlson R P Young and D A HutchinsldquoUltrasonic imaging and acoustic emission monitoring ofthermally induced microcracks in Lac du Bonnet graniterdquoJournal of Geophysical Research Solid Earth vol 98 no B12pp 22231ndash22243 1993

[17] U Bismayer ldquoEarly warning signs for mining accidentsdetecting crackling noiserdquo American Mineralogist vol 102no 1 pp 3-4 2017

[18] X Kong E Wang S Li H Lin P Xiao and K ZhangldquoFractals and chaos characteristics of acoustic emission energyabout gas-bearing coal during loaded failurerdquo Fractals vol 27no 5 Article ID 195072 2019

[19] F Du K Wang G Wang Y Jiang C Xin and X ZhangldquoInvestigation of the acoustic emission characteristics duringdeformation and failure of gas-bearing coal-rock combinedbodiesrdquo Journal of Loss Prevention in the Process Industriesvol 55 pp 253ndash266 2018

[20] R P Young D A Hutchins S Talebi et al ldquoLaboratory andfield investigations of rockburst phenomena using concurrentgeotomographic imaging and acoustic emissionmicroseismictechniquesrdquo Seismicity in Mines vol 129 no 3-4pp 647ndash659 1989

[21] X Jansen H Xu M He and F Zhang ldquoExperimental in-vestigation of the occurrence of rockburst in a rock specimenthrough infrared thermography and acoustic emissionrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 93 pp 250ndash259 2017

[22] R E Goodman and E Richard ldquoSubaudible noise duringcompression of rocksrdquo Geological Society of America Bulletinvol 74 no 4 pp 487ndash490 1963

[23] M Cai P K Kaiser H Morioka et al ldquoFLACPFC couplednumerical simulation of AE in large-scale underground

excavationsrdquo International Journal of Rock Mechanics andMining Sciences vol 44 no 4 pp 550ndash564 2007

[24] V Saltas F Vallianatos D Triantis T Koumoudeli andI Stavrakas ldquoNon-extensive statistical analysis of acousticemissions series recorded during the uniaxial compression ofbrittle rocksrdquo Physica A Statistical Mechanics and Its Ap-plications vol 528 Article ID 121498 2019

[25] V Saltas I Fitilis and F Vallianatos ldquoA combined complexelectrical impedance and acoustic emission study in limestonesamples under uniaxial loadingrdquo Tectonophysics vol 637pp 198ndash206 2014

[26] G Qi ldquoWavelet-based AE characterization of compositematerialsrdquo NDTamp E International vol 33 no 3 pp 133ndash1442000

[27] G Manthei J Eisenblatter and T Dahm ldquoMoment tensorevaluation of acoustic emission sources in salt rockrdquo Con-struction and Building Materials vol 15 no 5-6 pp 297ndash3092001

[28] H Jeong and Y-S Jang ldquoWavelet analysis of plate wavepropagation in composite laminatesrdquo Composite Structuresvol 49 no 4 pp 443ndash450 2000

[29] S-H Chang and C-I Lee ldquoEstimation of cracking anddamage mechanisms in rock under triaxial compression bymoment tensor analysis of acoustic emissionrdquo InternationalJournal of Rock Mechanics and Mining Sciences vol 41 no 7pp 1069ndash1086 2004

[30] T Hirata T Satoh and K Ito ldquoFractal structure of spatialdistribution of microfracturing in rockrdquo Geophysical JournalInternational vol 90 no 2 pp 369ndash374 1987

[31] X Lei K Masuda O Nishizawa et al ldquoDetailed analysis ofacoustic emission activity during catastrophic fracture offaults in rockrdquo Journal of Structural Geology vol 26 no 2pp 247ndash258 2004

[32] J Jouniaux J Pei J Liu et al ldquoInvestigation on acousticemission behavior and its time-space evolution mechanism infailure process of coalndashrock combined bodyrdquo Chinese Journalof Rock Mechanics and Engineering vol 30 pp 1564ndash15702011

[33] E Townend B D ompson P M Benson PG MeredithP Baud and R P Young ldquoImaging compaction bandpropagation in Diemelstadt sandstone using acoustic emis-sion locationsrdquo Geophysical Research Letters vol 35 no 15pp 189ndash193 2008

[34] M Naderloo M Moosavi and M Ahmadi ldquoUsing acousticemission technique tomonitor damage progress around jointsin brittle materialsrdquo Deoretical and Applied Fracture Me-chanics vol 104 Article ID 102368 2019

[35] GBT Unified Number of Natural Stone China StandardsPress Beijing China 2009

[36] G Shen Acoustic Emission Detection Technology and Appli-cation Science Press Beijing China 2015

[37] Y Guo Research on Wavelet Base Selection for VibrationSignal Processing Hefei University of Technology HefeiChina 2003

[38] F Xu E Wang and D Song ldquoLong-range correlation andmultifractal distribution of acoustic emission of coal-rockrdquoRock and Soil Mechanics vol 32 no 7 pp 2111ndash2116 2011

Advances in Civil Engineering 19

[8] F Du K Wang X Zhang C Xin and G Wang ldquoExperi-mental study of coal-gas outburst insights from coal-rockstructure gas pressure and adsorptivityrdquo Natural ResourcesResearch vol 29 no 4 pp 2481ndash2493 2020

[9] H Y Wang J Ma G D Wang et al ldquoResearch on AE sourcelocation of linear and plane rock massrdquo Shock and Vibrationvol 2020 Article ID 8846582 18 pages 2020

[10] V A Mansurov ldquoPrediction of rockbursts by analysis ofinduced seismicity datardquo International Journal of Rock Me-chanics and Mining Sciences vol 38 no 6 pp 893ndash901 2001

[11] M C He J L Miao and J L Feng ldquoRock burst process oflimestone and its acoustic emission characteristics under true-triaxial unloading conditionsrdquo International Journal of RockMechanics and Mining Sciences vol 47 no 2 pp 286ndash2982010

[12] F Gong J Yan X Li and S Luo ldquoA peak-strength strainenergy storage index for rock burst proneness of rock ma-terialsrdquo International Journal of Rock Mechanics and MiningSciences vol 117 pp 76ndash89 2019

[13] F Du and KWang ldquoUnstable failure of gas-bearing coal-rockcombination bodies insights from physical experiments andnumerical simulationsrdquo Process Safety and EnvironmentalProtection vol 129 pp 264ndash279 2019

[14] S D Butt C Mukherjee and G Lebans ldquoEvaluation ofacoustic attenuation as an indicator of roof stability in ad-vancing headingsrdquo International Journal of Rock Mechanicsand Mining Sciences vol 37 no 7 pp 1123ndash1131 2000

[15] M Cai H Morioka P K Kaiser et al ldquoBack-analysis of rockmass strength parameters using ae monitoring datardquo Inter-national Journal of Rock Mechanics and Mining Sciencesvol 44 no 4 pp 538ndash549 2007

[16] D P Jansen S R Carlson R P Young and D A HutchinsldquoUltrasonic imaging and acoustic emission monitoring ofthermally induced microcracks in Lac du Bonnet graniterdquoJournal of Geophysical Research Solid Earth vol 98 no B12pp 22231ndash22243 1993

[17] U Bismayer ldquoEarly warning signs for mining accidentsdetecting crackling noiserdquo American Mineralogist vol 102no 1 pp 3-4 2017

[18] X Kong E Wang S Li H Lin P Xiao and K ZhangldquoFractals and chaos characteristics of acoustic emission energyabout gas-bearing coal during loaded failurerdquo Fractals vol 27no 5 Article ID 195072 2019

[19] F Du K Wang G Wang Y Jiang C Xin and X ZhangldquoInvestigation of the acoustic emission characteristics duringdeformation and failure of gas-bearing coal-rock combinedbodiesrdquo Journal of Loss Prevention in the Process Industriesvol 55 pp 253ndash266 2018

[20] R P Young D A Hutchins S Talebi et al ldquoLaboratory andfield investigations of rockburst phenomena using concurrentgeotomographic imaging and acoustic emissionmicroseismictechniquesrdquo Seismicity in Mines vol 129 no 3-4pp 647ndash659 1989

[21] X Jansen H Xu M He and F Zhang ldquoExperimental in-vestigation of the occurrence of rockburst in a rock specimenthrough infrared thermography and acoustic emissionrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 93 pp 250ndash259 2017

[22] R E Goodman and E Richard ldquoSubaudible noise duringcompression of rocksrdquo Geological Society of America Bulletinvol 74 no 4 pp 487ndash490 1963

[23] M Cai P K Kaiser H Morioka et al ldquoFLACPFC couplednumerical simulation of AE in large-scale underground

excavationsrdquo International Journal of Rock Mechanics andMining Sciences vol 44 no 4 pp 550ndash564 2007

[24] V Saltas F Vallianatos D Triantis T Koumoudeli andI Stavrakas ldquoNon-extensive statistical analysis of acousticemissions series recorded during the uniaxial compression ofbrittle rocksrdquo Physica A Statistical Mechanics and Its Ap-plications vol 528 Article ID 121498 2019

[25] V Saltas I Fitilis and F Vallianatos ldquoA combined complexelectrical impedance and acoustic emission study in limestonesamples under uniaxial loadingrdquo Tectonophysics vol 637pp 198ndash206 2014

[26] G Qi ldquoWavelet-based AE characterization of compositematerialsrdquo NDTamp E International vol 33 no 3 pp 133ndash1442000

[27] G Manthei J Eisenblatter and T Dahm ldquoMoment tensorevaluation of acoustic emission sources in salt rockrdquo Con-struction and Building Materials vol 15 no 5-6 pp 297ndash3092001

[28] H Jeong and Y-S Jang ldquoWavelet analysis of plate wavepropagation in composite laminatesrdquo Composite Structuresvol 49 no 4 pp 443ndash450 2000

[29] S-H Chang and C-I Lee ldquoEstimation of cracking anddamage mechanisms in rock under triaxial compression bymoment tensor analysis of acoustic emissionrdquo InternationalJournal of Rock Mechanics and Mining Sciences vol 41 no 7pp 1069ndash1086 2004

[30] T Hirata T Satoh and K Ito ldquoFractal structure of spatialdistribution of microfracturing in rockrdquo Geophysical JournalInternational vol 90 no 2 pp 369ndash374 1987

[31] X Lei K Masuda O Nishizawa et al ldquoDetailed analysis ofacoustic emission activity during catastrophic fracture offaults in rockrdquo Journal of Structural Geology vol 26 no 2pp 247ndash258 2004

[32] J Jouniaux J Pei J Liu et al ldquoInvestigation on acousticemission behavior and its time-space evolution mechanism infailure process of coalndashrock combined bodyrdquo Chinese Journalof Rock Mechanics and Engineering vol 30 pp 1564ndash15702011

[33] E Townend B D ompson P M Benson PG MeredithP Baud and R P Young ldquoImaging compaction bandpropagation in Diemelstadt sandstone using acoustic emis-sion locationsrdquo Geophysical Research Letters vol 35 no 15pp 189ndash193 2008

[34] M Naderloo M Moosavi and M Ahmadi ldquoUsing acousticemission technique tomonitor damage progress around jointsin brittle materialsrdquo Deoretical and Applied Fracture Me-chanics vol 104 Article ID 102368 2019

[35] GBT Unified Number of Natural Stone China StandardsPress Beijing China 2009

[36] G Shen Acoustic Emission Detection Technology and Appli-cation Science Press Beijing China 2015

[37] Y Guo Research on Wavelet Base Selection for VibrationSignal Processing Hefei University of Technology HefeiChina 2003

[38] F Xu E Wang and D Song ldquoLong-range correlation andmultifractal distribution of acoustic emission of coal-rockrdquoRock and Soil Mechanics vol 32 no 7 pp 2111ndash2116 2011

Advances in Civil Engineering 19