condition monitoring of blade in turbomachinery a review

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Review ArticleCondition Monitoring of Blade in Turbomachinery: A Review

Ahmed M. Abdelrhman,1 Lim Meng Hee,2 M. S. Leong,1 and Salah Al-Obaidi1

Institute of Noise and Vibration, Universiti eknologi Malaysia, International Campus, Jalan Semarak, Kuala Lumpur, Malaysia

Razak School of Engineering and Advanced echnology, Universiti eknologi Malaysia, Kuala Lumpur, Malaysia

Correspondence should be addressed to Ahmed M. Abdelrhman; [email protected]

Received July ; Revised January ; Accepted January ; Published March

Academic Editor: Mario L. Ferrari

Copyright Ahmed M. Abdelrhman et al. Tis is an open access article distributed under the Creative Commons AttributionLicense, whichpermits unrestricted use, distribution, andreproduction in anymedium, providedthe original workis properlycited.

Blade aults and blade ailures are ranked among the most requent causes o ailures in turbomachinery. Tis paper provides areview on the condition monitoring techniques and the most suitable signal analysis methods to detect and diagnose the healthcondition o blades in turbomachinery. In this paper, blade aultsare categorised into ve types in accordance with their nature andcharacteristics, namely, blade rubbing, blade atigue ailure, blade deormations (twisting, creeping, corrosion, and erosion), bladeouling, and loose blade. Reviews on characteristics and the specic diagnostic methods to detect each type o blade aults are alsopresented. Tis paper also aims to provide a reerence in selecting the most suitable approaches to monitor the health condition oblades in turbomachinery.

1. Introduction

Blades are extensively used in power generation turboma-chinery such as the compressors and gas turbines. In thesemachines, there could be more than a thousand bladeslocated in both the turbine and compressor sections to trans-er energy between the rotor and fluid. Tus, the operationo these machines is largely dependent on the condition othese blades. Blades ofen operate in hostile and high stressenvironment that can potentially lead to blade ailures. Teailure o a single blade can potentially compromise the total

integrity o the machine. In such instances, even a bladeailure rate o in is not acceptable. According to Farrahietal.[] and Poursaeidi et al. [], blade ailures in gas turbinesand compressors mostly originate rom some orm o initialdamage or deect o the blades caused by Foreign ObjectDamage (FOD), ingested debris, or manuacturing deects.Tese minor deects or damage can propagate over time andeventually lead to total blade ailures. Common types o bladeaults and blade ailures in turbomachinery include bladerubbing, low and high cycle atigue ailures, creep, ouledblade, loose blade, and blade induced FOD. A review on themost common ailure mechanisms in gas turbine blades wasprovided by Carter [].

Tis paper provides a review on the strategy or monitor-ing the condition o blades as well as the specic techniquesapplicable to monitoring different types o blade aults com-monly ound in turbomachinery.

2. Strategies for ConditionMonitoring of Blade

wo different types o strategies can be employed to monitorthe condition o a blade: monitoring machines operat-ing parameters (e.g., vibration, pressure, temperature) andperorming signal analysis (e.g., Fouriers analysis, waveletanalysis, articial intelligence). In most instances, bothstrategies are deployed concurrently to obtain the mostimportant inormation rom the signal at hand. In thispaper, the literature review on each o these two strategies ispresented.

.. Monitoring of Machines Operating Parameters

... Vibration Measurements. Vibration analysis has beenthe most widely used blade condition monitoring method

Hindawi Publishing CorporationAdvances in Mechanical EngineeringVolume 2014, Article ID 210717, 10 pageshttp://dx.doi.org/10.1155/2014/210717
http://dx.doi.org/10.1155/2014/210717http://dx.doi.org/10.1155/2014/210717


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Advances in Mechanical Engineering

or decades. ime domain waveorm signals are typicallytransormed into the requency domain using Fourierstransormations. Afer that, interpretation o the vibrationspectrum is perormed to extract useul inormation aboutthe health o the machine. Detailed monitoring o a bladeusing vibration analysis is commonly achieved by monitoring

the relative changes o its blade pass requency (BPF) and itsharmonics as presented by Mitchell []. Te use o vibrationanalysis or blade aults diagnosis has also been studiedby Simmons [, ], Parge et al. [], and Parge et al. [].Tey have observed that the relative changes in the BPFand its harmonics amplitude can provide useul inormationabout the occurrence o blade rubbing. Al-Badour et al.[] studied the vibration signals caused by stator-to-bladerubbing during the machine runup and coast-down andthey ound that this method is effective in detecting bladerubbing. Te authors Abdelrhman et al. [] also investigatedthe effectiveness o vibration analysis or blade rubbing inmultistage rotor system at different rotor stages and different

rubbing severities. Satyam et al. [] used Cepstrum analysisto analyze the vibration signal in order to detect blade aults.It was shown that the conventional requency analysis inmachinery vibration is incapable o accurately determiningthe deects in blades. On the other hand, Cepstrum analysiscan accurately identiy the harmonics and sideband amilieso BPF. It is thereore a better technique or blade aultsdetection especially in ship and submarine applications. Inaddition, Randall and Sawalhi [] also employed the sametechnique to remove unwanted requency components romthe BPF components o interest. Tis allows or a betteridentication o blade ault based on the BPF monitoringapproach. Mathioudakis et al. [] conducted an experi-

mental study to correlate between the compressor casingvibration and the pressure eld around the compressorblades. Tey ound that the casing vibration can be correlatedwith unsteady pressure eld around blades and thus providea clearer picture o the blade in the interior o the casingas compared to conventional vibration signals. Barragan []reported that through a detailed comparison o vibrationspectrum against a vibration spectrum library o severe aultssuch as FOD, blade loss part, blade rub, and loose joints,blade ault could be detected. Chang and Chen [] studiedthe detection o cracked blades by analyzing vibration signalswith a spatial wavelet analysis method. Tey ound that theposition o the cracked blade can be identied based on

the proposed method. Zielinski and Ziller [] presented anoncontact blade vibration measurement method on axialflow turbine compressor blades. Tis method offered a bettermeans o detecting cracks in rotor blades. Nevertheless, itis highlighted by Baines [] that vibration analysis couldonly detect the blade aults i severe damage occurs atthe blade. A minor deormation o a ew blades, such asrubbing, will not be detected. Hee and Leong [] used

vibration signal to generate operational deflection shape(ODS) o rotor casing to detect blade rub. A comprehensivereview on the use o vibration as a diagnostic tool or bladeault has been done by the authors and can be ound in[].

... Strain Gauge Measurements. Strain gauges are typicallyused to measure the amount o deormation on the suraceo a turbine blade. Scalzo et al. [] employed the straingauge method to monitor the stress prole o blades o anindustrial gas turbine. It is reported that this method enablesthe monitoring o blade atigue ailures by studying the

characteristic o flow-induced resonant vibration. It is wellunderstood that a crack presence in a turbine blade will alteritsnatural requency anda cracked blade maythus experienceresonance conditions even at its normal operating condition.Mercadal et al. [] proposed the use o noncontacting stressmonitoring system (NSMS) to monitor blades resonancewhereby a damaged blade is ound to have shifed in itsresonant requencies. A method o using strain gauge tomonitor low cycle atigue aults in turbine blade was alsoproposed by Kumar et al. []. Barschdorff and Korthauer[] commented that the deployment o this method inoperational gas turbine mayace some challenges as the straingauge device may ail due to the extremely high temperaturein the gas turbine.

... Pressure Measurements. Te use o pressureeld distor-tion around rotating blades was proposed by Mathioudakiset al. [] to diagnose blade deormation aults. It was shownthat the pressure transducer signals mounted in the innercasing o the industrialgas turbine provide better inormationabout the condition o ouled and twisted blades than the

vibration analysis. Tis method has also been studied byBarschdor and Korthauer [] and Valero and Esquiza [].However, it is reckoned that this method is difficult to employor operational gas turbines due to the difficulty o mountingpressure sensors at the surace o turbine blades.

... Acoustic and Acoustic Emission Measurements. Acous-tic emission techniques have proven to be an effective toolor early ault detection in rotating machinery []. Leonand rainor [] presented an online blade ault diagnosticmethod based on acoustic signals. Tis method utilized inter-nal mounted acoustic sensors to identiy the occurrence andlocation o propagating bladecracks, bladerow damage, bladeflutter, and aerodynamic events such as condensation shock.Willsch et al. [] introduced a new technique or onlinemonitoring o blade cracks and spalling. Tis techniqueinvolves the use o acoustical waveguides, optical waveguides,and millimeter waves. Nonlinear acoustics measurements

techniques were then employed to evaluate atigue in tur-bine blades. Nonlinear acoustics measurements techniqueswere also applied by Hinton et al. [] to monitor bladesatigue. Randall and Rocketdyne [] and Graham et al. []introduced blade aults diagnostic method based on acousticemission monitoring to detect aults such as blade-to-statorrubbing, loose turbine disks, and blade cracking. Te use oacoustic emission (AE) in monitoring gas turbine operatingparameters is also investigated by Douglas et al. []. Anexperimental study done by Banov et al. [] and Urbach et al.[] showed that when atigue crack has become sufficientlylong, AE techniques can be used to effectively detect crackso blades at a much more early stage than vibration analysis.


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... Debris Monitoring. Debris monitoring can be used tomonitor the electrostatic and debris caused by blade rubbing.Tis method has been studied by Cartwright and Fisher[] and Fisher []. In this technique, electrostatic sensorsmounted in the turbine gas path were used to monitor theelectrostatic charge that grows with blade rubbing. Besides,

Powrie and McNicholas [] also used this method tomonitor the electrostatic charge and debris in the exhaust gasstream in order to detect blade rub and combustion chamberdeterioration.

... Blade ip Monitoring. Optical measurement o bladevibration has been used or blade tip clearance monitoringby Simmons et al. []. Tis is done by installing an opticalblade tip sensor at a spot on the blade surace. Te probeo the ber optic bundle will then image the spot. Anychange in the distance between the blades tip and probewould cause the images spot on the ber optic to moveacross the ace o the bundle, and the distance is directly

related to the change in blade to the probe. Tis methodhas been tested on an experiment rig and could be usedto monitor blade tip clearance. Tis method can thereorebe used to provide early detection o blade rubbing in gasturbine. Von Flotow et al. [] used capacitance blade tipsensor to detect parameters such as the time o arrivaland angle o arrival and thus provide inormation to detect

various types o blade aults such as loss o blade, crack,rubbing, and bend blade. A powerul and reliable techniqueor blade tip clearance measurements that can be used underextremely harsh environments is presented by Steiner [].Tis method utilizes a heavy duty blade tip probe to detectshaf eccentricity or blade oscillations and thus provides

inormation on the condition o blade. Tis method has alsobeen studied by Sheard [] among others.

... emperature Monitoring. In this method, blades run-ning hotter than other blades can be detected and thusprovide useul inormation or the prediction o creep. Ablade temperature measurement system was also developedby Land Inrared Inc. Tis system is claimed to be capableo giving early warning o potential blade ailures caused byoverheating, such as creep. Annereldt et al. [] presenteda thermocrystal technique or monitoring the temperatureo turbine blades and vanes. Te technique was shownto be reliable and to have good accuracy in temperature

gradients measurements. Te study o heat transer and stressdistributions on a gas turbine blade was investigated by Kimet al. []. It was reported that the highest temperatureon a turbine blade is located at the stagnation point othe blade leading edge. Te point o maximum stress ona turbine blade is at its root. urbine blade ailures couldthereore be estimated by monitoring the total stress resultingrom combination o thermal load and cooling effects. Acommercial online Termal Barrier Coating (BC) blademonitoring system has also been developed by SiemensWestinghouse Power Corporation Engineering in collabora-tion with Siemens Corporate Research []. Te techniquecombines innovative access port design, high-speed inrared

imagery, a tailor-made overall control and image evaluationsystem, and related BC lifing models. Te presented onlinetechnique is able to capture two-dimensional quantitativeinrared images o row- blades during ull engine operationand can help in not only ensuring the sae blades operationbut also extending the blades lie.

... Performance Monitoring. Perormance monitoringinvolves the acquisition o a variety o data (temperature,pressure, and speed) located along the gas turbine and thencalculating the perormance o the parameters such as massflow rate and compressor and turbine operating efficiency.Perormance monitoring methods are a valuable tool todetect blade ouling and rotating stall. Tese aults usuallywill cause some aerodynamics distortion on blades andaffect the overall perormance o the machine. Tis methodhas been studied by Dundas [], Dundas et al. [], andMeher-Homji and Boyce [] amongst others. An algorithmor blade ault diagnosis using hybrid method (perormance

and vibration monitoring) was developed by Kubiak et al.[]. It is shown that by using this hybrid algorithm, bladeaults such as the wearing-out effects o the blade and bladeouling could be detected. able provides a summary othe blade condition monitoring methods discussed in theproceeding section.

.. Advanced Signal Analysis echniques

... Wavelet Analysis. Aretakis and Mathioudakis [] pro-posed a blade ault diagnostic method based on waveletanalysis. Wavelet analysis is perormed on the time signalso the casing vibration, unsteady pressure, and acousticmeasurements taken rom commercial gas turbines. Teyhighlighted that a distinctive difference could be seen romthe wavelet map o healthy and aulty signals around BPFlevel. Tey have also demonstrated that each type o bladeaults(ouled blade, twisted blade, andmistuned stator blade)could generate a unique signature o wavelet pattern based onthe pressure signals. Te authors investigated the easibilityo wavelet analysis or multistage blade aults diagnosis [].In another research paper [] the current authors havealso explored the usage o wavelet analysis or loose bladedetection. Loose blade was ound to be only detectableduringthe rotor coast-down process. Application o wavelet analysisin monitoring the different types o blade aults such as rub

due to rotor eccentricity or creep has also been presented bythe authors o []. It was showed that wavelet analysis can beused to reveal useul inormation about the blade conditionand also to diagnose root cause o blade aults. Yuan et al. []used the wavelet analysis method to detect cracked turbineblades. It was demonstrated that both the Short ime Fourierransorm (SF) and Mallats wavelet transorm could beused to obtain the characteristics o a cracked blade based onthe high requency impacts signals ound on the SF andMallats wavelet. Peng et al. [,] reported on applicationo wavelet scalogram and wavelet phase spectrum to detectblade rubbing and rubbing-caused impacts. Tey have oundthat these techniques can be used to better detect rub impact


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: Summary o blade condition monitoring methods.

Blade monitoring methods Monitoring parameters Characteristics and applications

Vibration Blade pass requency (BPF)

(i) Easy to implement(ii) Suitable or blade rubbing detection(iii) Not sensitive to detect minor aults such as blade geometryalterations

Pressure Pressure distortion around

blades(i) Suitable or blade deormation and ouling detection(ii) Difficult to deploy under operating conditions

Acoustic Acoustic signal (i) Suitable or blade rubbing detection

(ii) Sensitive to noise

Debris Particle in oil and charges Suitable or blade rubbing and FOD detection

Strain gauge Displacement Suitable or blade deormation and blade atigue detection

emperature emperature(i) Suitable or blade creep monitoring(ii) Can provide early warning(iii) Embedded temperature sensors are required

PerormancePerormance (efficiency,output, uel consumption,etc.)

(i) Suitable or blade ouling and rotating stall detection(ii) Large number o sensors required(iii) Large number o data and calculation required

signal as compared to FF analysis. A blade ault diagnosisapproach is also proposed by Qing-Yang et al. [] by usingthe combination o the Morlet wavelet transorm and neuralnetwork or eature recognition purpose. Wang et al. [] alsoapplied lifing wavelet transormation to detect blade aults.Te current authors also studied the various applications owavelet analysis technique [, ] to analyze vibration signalor blade rubbing detection.

... Articial Intelligence and Pattern Recognition ech-niques. Probabilistic neural networks method was presentedby Kyriazis et al. [] to diagnose various types o bladeaults. Angelakis et al. [] proposed a method o usingneural networks to diagnose blade aults in gas turbines. Inhis study, neural network-based ault diagnosis was used aspattern recognition tool to discriminate the patterns o aultyrom healthy blades using signals measured rom twelvedifferent sensors or signals such as vibration and pressuresignals. Loukis et al. [] presented an automated bladeaults detection method based on spectral pattern analysistechnique. Tey have incorporated an innovative eatureinto a computer expert system to automatically detect andidentiy the type o ault in gas turbine by deriving the

values o discriminants calculated rom spectral patterns oast response measurement signals such as casing vibration,

internal pressure, and acoustic emission. It was ound thatblade ouling, blade twisting, and stator blade restaggeringcould be detected automatically based on this method.Aretakis et al. [] presented a hybrid method to diagnosecompressor blade ouling aults based on the combinationo pattern recognition techniques known as the geometricand statistical pattern recognition technique. Tese patternrecognition techniques were shown to be viable to diagnoseminor blade aults. Dedoussis et al. [] presented a methodbased on the numerical simulation o blade ault signaturesrom unsteady wall pressure signals. Tis method producedthe blade ault signatures o gas turbine using only theoreticalcomputations. Tey employed a panel technique or the

calculation o the flow eld around blade cascades. From thecalculation, time waveorm o the pressure signal at a locationon the casing wall acing the rotating blades is developed. Byprocessing the aulty time, waveorm signal will enable theconstruction o the aulty spectra signatures. Tis methodgives rise to the possibility o establishing the blade aultsignatures without having to perorm any experiments at all.

... Computational Fluid Dynamics (CFD). Aretakis et al.[] demonstrated the application o CFD to derive bladeaults signatures. It was reported that this method can thus

provide a basis or blade aults identication in gas turbineand compressors. Stamatis et al. [] presented a study oblade aults diagnosis in gas turbine based on the CFDmethod. In this paper, a measured quantity was used as aninput or physical modeling and the physical blade congu-ration is produced as the nal output. Tis method providesa direct geometrical picture o the blade aults and does notrely on the interpretation o conventional ault signatures.Besides, Koubogiannis et al. [] also used CFD method tocreate a database or gas turbine blade ault diagnosis solelybased on signal modeling approach. Tey have shown thatblade ault signature databases could be created without theneed to conduct any costly experiments by using the method

o unstructured and parallel CFD processing. CFD methodwas also investigated by Yokoyama et al. []. Hameed andManarvi [] also used CFD to predict crack locations atturbine blades surace.

... Statistical Analysis. Romessis et al. [] proposed theuse o probabilistic reasoning to derive statistical inorma-tion. It was showed that this method could be used to detectcomponent aults (i.e., blade related aults) o jet engine.Loukis et al. [] developed an automated method or gasturbine blade ault diagnosis based on the principals ostatistical pattern recognition. Te decision-making eatureis based on the derivation o spectral patterns rom dynamic


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F : Marks o blade rubbing on compressor rotor.

measurement data. Te calculations o discriminate coe-cients with respect to the reerence spectral patterns othe aults were done by taking into account their statisticalproperties. In this method, the success rate o automated

decision making is urther improved, and the need orintuitive discriminate selection is eliminated. Zhang et al.[] presented a signal recognition method to recognize theblade ault based on the symmetry and similarity principalby making use o the means, variance, and means o varianceto eliminate the effect caused by the parameter differencesbetween blades. Te plotting o means o variances showedthat it can be used to distinguish the aulty rom the healthyblade.

3. Condition Monitoring of DifferentTypes of Blade Faults

In this section, the most requently occurring blade aults inturbomachinery are categorized into ve types, namely, bladerubbing, blade atigue ailure, blade deormation (twisting,creeping, corrosion, and erosion), blade ouling, and looseblade. A review o the most suitable method to detect eachtype o blade aults is presented in the ollowing section.

.. Blade Rubbing. Te occurrence o blade rubbing inturbomachinery has become more prevalent with the advento high perormance turbomachinery design. Tis is becausethe primary design consideration o these machines is tominimize the operational clearances between rotating blades

and casing in order to increase cycle efficiencies and thusreduce the overall uel consumption []. According toBarschdorff and Korthauer [], blade rubbing and bladeatigue ailure were reckoned to be the most prevalent bladeaults in gas turbine with % o total blade ailures in gasturbines contributed by rubbing whist .% by blade atigueailure (i.e., crack, loss o part, and FOD). Te consequenceso blade rubbing could be very serious as it can lead to othermore destructive ailures in machinery such as FOD dueto broken blade parts.Figure illustrates the effect o bladerubbing on the surace o compressor rotor.

o date, abundance o studies have been conducted tounderstand the effects and mechanisms o blade rubbing

in turbomachinery. Choy and Padovan [] investigated thecharacteristicso the nonlineardynamicso rubbing andhaveestablished the relationship o various parameters o rubbingexcitation such as the relationship o rub orce and energylevels with rubbing duration and incidence separation angles.Laverty [] studied the mechanics o rubbing between a

compressor blade tip seals and rotor casing. He ound thatthe total energy o rubbing is mainly contributed by theincursion rate o the rubbing as compared to rubbing velocityand the thickness o the blade. He concluded that the overallrubbing energy increased in proportion to the quantity oblades that are involved in the process o rubbing. Sawicki etal. [] studied the dynamic behavior o rotors rubbing andound that the vibration spectrum o rubbing is mainly dom-inated by subharmonic, quasiperiodic, and chaotic vibrationcomponents. Ahrens et al. [] conducted an experimentalstudy to investigate the resulting contact orces (in radial andtangential direction) during the process o rubbing. Roqueset al. [] ormulated a mathematical rotor-stator modelo a turbogenerator in order to study the speed transientsand angular deceleration associated with rubbing. Tesereports, amongst others, have provided a deeper understand-ing o the mechanics and mechanisms o rubbing and thusenabled a better interpretation o rub related observationsand signals in relation to their actual physical conditionthat occurred. Blade rubbing detection in turbomachinery isofen accomplished by establishing the vibration symptomso rubbing rom time domain (i.e., vibration waveorm, orbitplot), requency domain (i.e., FF), and also time-requencydomain (i.e., wavelet and SF) signal analysis. A literaturereview by Muszynska [] provided exhaustive inormationrelated to vibration, rotor dynamics, and the resulting rotororbit during rubbing. Tis inormation could be used as areerence to detect blade rubbing in turbomachinery. Kubiaket al. [] highlighted that blade rubbing could be detectedi the blade passing requency (BPF) amplitude is ound tobe exceptionally high in the vibration spectrum. Beside this,the presence o the abnormal requency harmonics peaks(x, x, x, etc.) o the operating speed in the vibrationspectrum could also indicate theoccurrence o blade rubbing.A drastic escalation in rotor subharmonic peaks in the

vibration spectrum could also iner the presence o bladerubbing as reported by Meher-Homji []. Patel and Darpe[] studied the early detection o rubbing in turbomachinerybased on the vibration signal measured during a coast-up o amachine. Tey ound that the Hilbert-Huang signal analysis

could be applied to detect early rubbing in a rotor systembased on the vibration signal measured during the coast-up o a machine. Wavelet analysis method was also widelyused to detect rubbing in turbomachinery. For instance, Penget al. [] conducted a study to determine the effectivenesso using the conventional scalograms as compared to thereassigned scalograms or the detection o rubbing. Teyound that when rubbing occurred, its rubbing impacts couldlead to an increase in vibration amplitude at high requencyregion. Tey concluded that the vibration amplitude peakso high requencies region increase in correspondence withthe increase o severity o rubbing. Wang and Chu []proposed a method to determine the location o rubbing


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in a rotor bearing system based on acoustics emission andwavelet analysis. Peng et al. [] used wavelet analysis asa means or eature extraction o rubbing impact signal ina rotor system. Hee and Leong [] conducted an experi-mental study to understand the dynamic responses o casingdeflection prole due to different congurations o blade

rubbing and ound that the detailed analysis o amplitudeand phase angle o the casing vibration could be used orblade rubbing classication. Leong and Lim [] proposeda method that involved wavelet analysis technique to detectblade looseness and monitoring blade pass requency signalsor blade rubbing and cracks identication. Cong et al. []reported the use o an impact energy model or the evaluationo rotor rub impact ault where spectrum analysis can showa distinctive pattern or different severity states o the bladerub.

Besides vibration analysis, acoustic emission method wasalso proposed by Mba and Hall [] to detect blade rubbing.Tey ound that the stress waves and acoustic emission

produced during the rictional rubbing process can propagateacross the turbine surace and across the bearing interaceallowing measurement to be made by the sensor attachedto bearing housing. Meher-Homji [] commented that thesimple acoustic measurement could also be used to detectblade rubbing using stethoscopes during gas turbine startupand shutdown and this technique has already been adoptedby gas turbine operator. Fisher [] commented that manytechniques such as the perormance and vibration moni-toring are dependent on a secondary effect being producedby the rubbing ault. For instance, blade rubbing can onlybe detected by these techniques provided sufficient materialloss has occurred and results in an imbalance or loss operormance. He has adopted an engine distress monitoringsystem (EDMS) to monitor in real time the debris producedby the gas path component, such as blade rubbing andcombustor aults. He has ound that this method is capableo providing a more direct indicator o blade rubbing as themeasurement made based on the actual debris produced bythe ault probably beore remedial action is required, thusgiving a sufficient prognosis period. Simmons et al. []presented a method or blade tip clearance monitoring usingan optical probe and ound that this method could provideearly indication o a blade rubbing i the measured blade tipclearance has reduced considerably.

.. Blade Fatigue Failure (Crack, Loss of Part, and FOD).Blade atigue ailures in turbomachinery are generally causedby high and low cycle atigue o the blades. High cycle atiguein turbine blades is ofen caused by aerodynamic excitationsor sel-excited vibration (flutter). High cycle atigue damageoccurrs when stress levels are above its atigue strength. Incontrast, low cycle atigue occurs as a result o requentstart-stop cycle o a machine which can lead to crack inbores and bolt hole areas o compressor and turbine disksthat operate under high centriugal stress. In this situation,a minute flaw could grow into crack which upon attainingcritical size could result in total rupture o blade. In addition,crack can also be caused by resonant atigue in blade.

Resonant atigue is an important ailure mechanism whichariseswhen a periodic orce acts ata requency correspondingto a blade natural requency. I the damping is inadequate,crack will eventually develop and propagate and total bladeailure could occur as commented by Meher-Homji [].A nonintrusive measurement method or measurements o

torsional vibration signals or blade crack detection was alsostudied by Maynand and rethewey [].It is well understood that any damage in turbine blades,

including cracks, can cause shif in blades resonance re-quencies. Tereore the monitoring o the blade resonancecondition is ofen adopted to detect a crack in blade. Lackner[] presented a crack detection method or compressorblades in gas turbine engine using eddy current sensors. Heobserved that crack in blade was ound to lower the resonantrequency o the rst torsion mode o the blade. Mercadalet al. [] employed a method using a noncontacting stressmonitoring system to monitor blade resonance condition.Various methods o nondestructive testing such as eddycurrent and ultrasound were also ofen used to detect crack inturbine blades. elemetry measurement method to monitordirect blade vibration was also used and studied by Scalzoet al. [] and Mercadal et al. []. However, the methodso monitoring blade vibration using eddy current and straingauge seem to be only applicable during machinery outagecondition.

Vibration analysis is ofen employed in the eld to moni-tor health condition o turbomachinery. However, vibrationanalysis is only capable o detecting atigue blade ailurei there is massive loss o blade part that could cause thechanges in rotor dynamics characteristics o the machine.Meher-Homji [] presented a case study whereby severelydamaged rst-stage turbine blades could not even show up initsvibration spectrum. Dofman andMoroslav [] presentedin their paper that a crack at the turbine blade root could becaused by the atigue initiated by the rotor torsional vibra-tion. orsional vibration is generally a sporadic, transientphenomenon provoked by a sudden load change on the grid.Hence, the measurement and monitoring o the torsional

vibration could be used to provide early warning or crack atturbine blade root. Tis method was also studied by Maynardand rethewey [].

.. Blade Deformation (Creep, wisting, Erosion, and Corro-sion). Bladedeormation in turbomachinery couldoccur due

to creep, erosion, corrosion, andFOD induced blade twisting.Figure depicts photographs o compressor blade deorma-tion. Generally, blade deormation could cause obstructionin the flow o a machine and thereore could be detected bymeasuring the pressure eld around the blades. Tis methodhas been proposed by Mathioudakis et al. [] and Dedoussiset al. []. As shown by Aretakis and Mathioudakis [], thedistortiono pressuresignals around the blades couldindicatethe occurrence o twisted blade. Beebe [] also commentedthat the erosion o the blade due to the solid particles couldalso be detected using the perormance monitoring methodwhen gas turbine efficiency has dropped substantially. Besidethis, a technology developed by GE power system known


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(a) (b)

F : Photographs o blade deormation.

as taggant coating system can be used to detect any bladecorrosion or erosion o blade. Any detection o the coated

material at exhaust collector can be used as the indication othe presence o corrosion and erosion o the Mann [].

.. Blade Fouling. Blade ouling is an important mechanismleading to perormancedeterioration in turbomachinery overtime.Kurzetal.[] explainedthat ouling is normally causedby the adherence o particles to airoils and annulus suraces.A case study o the causes and effects o ouling on gasturbine operation can be ound in Meher-Homji [, ].He ound that compressor blade ouling could be detectedbased on perormance monitoring method. Te solids orcondensing particles in the air and combusted gasses couldprecipitate on the rotating and stationary blade, thus causingsome changes to the aerodynamic prole and invariablydropping the compressor mass flow rate and affecting theturbine flow coefficient. Tereore the dropping o the overallpower output and thermal efficiency o the gas turbine couldindicate the presence o the ouled blade. Mathioudakiset al. [] presented that the measurement o the pressureeld around rotating blades in turbomachinery is a moresensitive method as compared to perormance monitoring todetect ouled blade. However, pressure monitoring method isdifficult to be applied or gas turbine and compressor duringactual operation.

.. Loose Blade. Loose blade in turbomachinery is a specialcondition whereby it usually involves not only the bladeitsel but also the mechanism o blade locking or bladeattachment design. Te authors Lim and Leong [] haveencountered a loose blade condition in one o the powerstations in Malaysia. An experimental study o loose bladeound that loose blade is not detectable under normaloperation condition due to centriugal orce. Instead, it canonly be detected during rotor coast-down stage by observingthe impactive signals caused by the loose blade. Beside this,Kuo [] also conducted a study on the diagnosis o the looseblade with Fouriers analysis method on vibration signal. Heused neural networks and uzzy logic methods to develop

a pattern recognition algorithm to enhance the detection oloose blade using vibration analysis.

4. Conclusion

Blade aults remain as one o the most elusive and requentlyoccurred aults in turbomachinery. Te selection o blademonitoring method depends largely on the characteristics oblade aults as well as the practicality o the measurementitsel. In summary, vibration analysis and BPF method can beused effectively or the detection o severe blade rubbing. Forminor or early blade aults detection, pressure measurements,blade tip monitoring, acoustic emission, and debris monitor-ing should be used in lieu o vibration measurements. For thedetection o bladeatigue ailures,strain gauge measurements

and blade vibration monitoring methods can be used tomonitor any change in blade resonance requency. For bladedeormation and bladeouling detections, perormancemon-itoring was ound to be the most effective method availableto date. Tis paper aims to provide an overview o the mosteasible approaches or condition monitoring o blade inturbomachinery.

Conflict of Interests

Te authors declare that there is no conflict o interestsregarding the publication o this paper.

Acknowledgment

Tis work is supported by the ERGS Grant(R.K..L) nanced by the Ministry oEducation o Malaysia.

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