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Innovative Sound Processing Techniques for Secure Product Maintenance

Richard SmithNorth-South-East-West

4 Nottingham Way NorthClifton Park, New York 12065

Phone (518) 877-6085E-mail: [email protected]

ABSTRACT

“Bird Watchers” identify concealed birds by the songs they sing. [Reference 1] Identification of birds by “ear” is similar to recognizing defective bearings by the noise they make. In the rail industry railroad maintenance workers can hear and identify the locations of defective roller bearings in rail cars traveling at speeds of 20 to 50 MPH. [Ref. 2]

Features of sounds commonly produced by biological and mechanical systems can provide us with opportunities for creating unique acoustic based diagnostic systems [Ref. 3]. Although we will probably never make electronic systems that have the diagnostic sophistication of our human brain, we can build computerize detection systems that take advantage of some of the ways we identify common everyday sounds. This presentation and associated documentation presents some of the acoustic diagnostic techniques in use today.

This presentation also reviews sounds from a dozen different applications with an “ear” on how the various acoustic processing methods can be used to identify faulty operation of common mechanical products. The review includes acoustic examples from Nature, Freight & Transit Rail Systems, the Heating Industry, the Highway Trucking Industry and Scientific Research Laboratories.

INTRODUCTION

The sounds you hear in the background are derived from several files that will be reviewed in more depth during this talk. Nature provides many examples of biological species that use audio diagnostics. Animals are particularly adept at processing and responding to audible inputs. A few examples are discussed in [Ref. 3], a paper on acoustic bearing defect detection, which discusses the way bats use acoustics in finding food in total darkness. Bats use sophisticated ultra-sonic real-time processing of echoes to locate and gather daily food on-the-fly. Some of today's machinery monitoring systems make use of a few of the techniques that bats have used for thousands (or millions) of years.

With today’s computer displays it is said that “What You See Is What You Get”; but with acoustics, “What you hear may not be so clear”. Acoustic signatures can be confusing to the uninitiated and often times require

extensive processing before they reveal their diagnostic information. To illustrate this, let's take a look at some graphics of the sounds you heard a moment ago and review the acoustics which enables engineers to protect everyday products we are all familiar with.

REAL-TIME RAILROAD BEARING DIAGNOSTICS

Early studies from 1977 [Refs. 4 & 5] of railroad roller bearings provided evidence that as many as 20 percent of the bearing population contained some type of structural defect. Early in 1986 Frarey & Smith presented an invited paper [Ref. 6] which described methods for screening bearings with microphones in order to find internal flaws that showed up during operation. The paper was given at a roller bearing conference sponsored by the AAR. At that time the process of detecting bearing defects with the aid of microphones was in its infancy. Soon after the paper presentation a Patented [Ref. 7] prototype wayside acoustic detector was developed to augment the information normally collected with hotbox detectors throughout the United States. A review the earliest acoustic information from acoustic roller bearing detection systems can be found in References 6, 7, 8 & 9.

The earliest prototype deployment of a wayside acoustic detector was ahead of its time. It soon became apparent, that if wayside acoustic detectors were to be success-fully implemented, then a comprehensive study which included both laboratory testing, as well as, controlled field studies would have to be carried out. In the early 1990s those studies were initiated by the Association of American Railroads (AAR) at its Transportation Technology Center (TTC, Inc) in Pueblo, Colorado.

A graphic representation of passing train sounds, similar to those you heard a while ago, is shown in Figure 1. This plot is taken from [Ref. 10] and is from a microphone signature contained on an American Association of Railroads (AAR) Data CD (i.e., disk file 24AP1N30.001). See [Ref. 11] for a description of the AAR Data CD. This time based display contains 1.65 million acoustic data points and is derived from a preliminary wayside acoustic detection field test.

The first derivative of the time based data is displayed in Figure 2. It is essentially the same as Figure 1, except it has no bias offset on the vertical axis. Note there are also

Presented at the 2nd Annual Tech Valley Symposium, April 18, 2006, Albany, NY 1

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32 spiked wheel markers in a line trace at the bottom of Figure 2. These graphic wheel markers illustrate the electronic provision for finding the center location of each of the train’s wheel axles as they pass the acoustic detector. Knowing where each wheel is located, relative to the sensing microphone, is required for pinpointing the actual position of each bearing in the train – particularly if the observed bearing is defective.

The two plots just reviewed illustrate the raw acoustic data obtained from a passing train. When properly processed this type of acoustic information quickly reveals the presence (or absence) of bearing defects in passing trains. These displays are presented here to illustrate the type of wave information that is commonly gathered by railroad wayside acoustic bearing protection systems. Today’s acoustic roller bearing protection systems automatically recognize bearing defects and allow for their removal long before a mechanical bearing failure might occur. Acoustic detection systems are nearly 100 percent effective [Refs. 12 & 13]. A quote from [Ref. 12] states the following:

“Even the most robust bearings like the Class K wear over time, which is why Burlington Northern and Santa Fe, Union Pacific, CSX Transportation, Norfolk Southern, and Canadian Pacific are now installing Trackside Acoustic Detection Systems (TADS™) [Ref. 14] in high traffic areas. "The systems are intended to be preventative maintenance tools," says Gerald Anderson, senior principal investigator at the Transportation Technology Center, Inc. "We want to find defects before bearings overheat and well before they set off a hotbox alarm. The systems have been trained to not only detect the presence of defects, but to identify defective components and evaluate defect severity for maintenance prioritization purposes."

Developed with South Africa's Spoornet, Australia's Queensland Rail, BNSF, NS, and CSXT, TTCI testing found that 97% of the detected bearings had an AAR shop-condemnable defect (38% had multiple defects involving more than one component). Defects included cup, cone, and roller spalls, water-etched or cracked components, brinells, and loose cones.” Copyright 2001 Simmons-Boardman Publishing Corporation.

Everyday, in the U.S., Trackside Acoustic Detection Systems (TADS™) made by the Transportation Technology Center, inc. in Pueblo CO. collectively scan over a quarter of a million rail car roller bearings. To date approximately $15 million worth of acoustic detection systems have been installed worldwide. Depending on the number of accidents these systems have helped prevent, each installation could be worth 10 to 100 times its actual cost of installation for every year it’s in service. Is it possible that an acoustic detection system or its acoustic processing techniques could be implemented to scan and protect your own company's products?

What types of roller bearing defects can an acoustic wayside detector find in a passing train? Gerald Anderson from the TTCI put it this way in [Ref.15], a Railway Age Article released in 2001:

“The trackside acoustic detection system (TADS™) is structured to detect the following condemnable bearing defects per the AAR Manual of Standards and Recommended Practices (Section H-II):

* Cup spalls.* Cone spalls.* Spalled, etched, or seamed rollers.* Water-etched raceways.* Spun or loose cones.

Several TTC,Inc. developed research grade acoustic bearing detection systems are now operating in North America, South Africa, and Australia. The data these systems are generating is expected to lead to the final release of a production system, available for implementation throughout the world in late 2002. Cooperative research programs sponsored by the Federal Railroad Administration and the Association of American Railroads provided data with acoustic characterizations of deflection bearings to all potential suppliers.

Bearing flaws are selected at TTC,Inc. during the initial evaluation or training period, and bearing defect inspection requests are sent to the operating railroads. Many of these bearings are scheduled for removal and inspection to further build the TADS™ training database. The system is also being developed to have the capability of detecting severity in addition to flaw presence. The severity capability will be integrated into the system as the bearing flaw training database matures.” Copyright 2001 Simmons-Boardman Publishing Corporation.

To get an idea of what internal roller bearing defects look like and what the acoustic signatures sound like, let's return once more to the information presented in Reference 9. Figures 3 and 4 contain photos of the internal bearing defects from field test bearings number 4 and 19. Bearing No. 4 has an outer race or so-called "cup" defect, whereas, bearing number 19 contains spalls on its inner raceway surface.

The acoustic signatures from the two bearings are highlighted in envelope form in Figure 5. The time expansion of the signal from bearing 4 is shown in Figure 6. Note the periodic peak structure which is a result of the roller and race-way mechanical interactions as the bearing goes by the microphone. This periodic peak response over time is a typical dominant feature of a spalled cup defect in roller bearings. If you observed one of these coming from your acoustic wayside detection system you should probably take it out of service. This acoustic signature represents a potential accident “just waiting to happen”. Much more has recently been published on the attributes of the commercially available Trackside Acoustic Detection System (TADS™) and the reviews can be found in References 16 through 20.


ACOUSTIC MONITORING OF A GAS FIRED HOT AIR FURNACE WITH AUXILLARY STACK GAS EXHAUST BLOWERS

Our next acoustic monitoring example is from a furnace with auxiliary blowers. The author got involved with this furnace blower system after repair personnel had visited this unit on several occasions.

This unit would always begin acting up when the outdoor temperature would drop near zero during the late night hours. The unit under discussion was located in a crawlspace underneath the facility it was responsible for heating. Temperatures under the crawlspace did not reach the outdoor temperatures of the night but they were cooler than the heated area of the overhead facility.

Maintenance repair personnel had made adjustments to the high low cut off levels of the furnace heater blower and the stack gas high low cutoff sensors on several different occasions.

The assumption was that this furnace unit was somehow unique was not operating properly because the temperature of the gases were slightly higher or lower than they should be when the fans started or stopped cycling on or off.

The owner commented that this furnace continually performed inefficiently and improperly when the outdoor temperature would approach zero degrees Fahrenheit or below.

The owner asked the author to take a look at the problem furnace after several repair visits provided no improvement to the unit's operation. Without knowing too much about the problem the author decided to make a survey acoustic recording of the furnace cycles during a full night when the outdoor temperature was to dip into the teens. Several on and off cycles of this furnace with its auxiliary heater and stack blowers would need to be recorded for review. This project required an extended period recorder, so the author chose a digital solid-state device that could store several unattended hours of continuous acoustic data (~10 to 18 hours).

Several types of these solid-state recording devices are on the market today. These handheld recorders can collect acoustic data for up to 40 hours or more at very high data rates and the bit levels of resolutions. See Figure 7 for a graphic view of the acoustic time based signature from the furnace.

The problem of the unit being discussed is displayed directly in the time based signatures of the acoustic recording. Sometimes acoustic information does not have to be fully analyzed for its frequency content to reveal the problem of a unit under surveillance. The timing and length of the acoustic recordings themselves revealed an overall pattern which was ignored during the repair process. Since the problem would not show up until it was

cold outside, making adjustments in the units cutoff sensors did not address the actual problem that existed in the unit. Furthermore, no extensive testing of the examined unit could be made under the exact conditions that initiated the inherent problem.

During the next visit after the acoustic recording was taken, the repair personnel were presented with the evidence of the recording itself. No adjustment of stack gas sensor’s on (or off) settings would ever fix the problem that was inherently in the unit. They had to agree that they were not addressing the source of this unit’s problem. Although the author had no idea at the time, what the source problem was, the recording shown in Figure 7 provided enough information for the repair personnel to look in greater depth at the hardware they had been ignoring.

It turns out this furnace had a faulty (sticky) gas line pressure valve that feeds the furnace. Sticky gas valves rarely occur, so repair personnel did not address it. This particular furnace only acted up when the surrounding temperature of the unit, plus the flowing gas, cooled off the body of the valve itself. Operation of the valve was marginal enough to keep it operating whenever the surrounding temperatures were warm. Warmer outdoor temperatures also meant that the gas flow through the valve was reduced, which allowed the valve to remain warmer.

Detailed measurements of the inlet and out-let pressures provided by the valve when the furnace was operating revealed that this valve might abnormally choke the gas flow to the furnace under certain conditions. Reduced gas flow to the furnace would, of course, immediately drop the plenum temperature and cause the heater fan to show off prematurely. The reduced amount of gas feeding the furnace would also shut the heater blower down sooner than it should during any heat circulating cycle that might take place.

Once the gas line feed valve of this unit was changed, all the faulty heating and blower problems went away.

ACOUSTIC EVALUATION OF RAIL LUBRICATION

The transit industry has an inherent noise problem. The industries cars operate on steel wheels. In addition, pairs of these steel wheels are mounted on a single solid axle. Since these axles are solid, there is no speed differential inherent to the wheel pairs as the transit cars go around curves. Consequently, all transit cars make noise (typically squeals) as the cars navigate around curves. In some cases, the curves do not have to be sharp at all and still the car wheels will squeal wildly. When this occurs, the transit car facilities receive numerous telephone calls (i.e., people who live nearby call to complain about the excessive noise!).

The industry has learned that lubrication can alleviate some of these problems. A small amount of lubricant placed on rails significantly reduces the squealing that a transit car produces. Tests to evaluate the noise reduction character of various types of lubricant have been undertaken by the transit industry.


One of the acoustic reviews undertaken by the transit industry is discussed next.

Refer to Figures 8 through 12 for information related to a single noise evaluation test made for the transit industry. The discussed noise evaluation test took place over a two-week period. Every nine minutes throughout each day a transit car passed the test site during the study. The sounds from four hundred and thirty-four car units (a typical car unit is a pair of cars called a "consist") were recorded duing the test period. Only 10% of the recorded car passes were from single cars.

A typical passing “consist” is shown in Figure 8. The test site is displayed in photo of Figure 9, which is a fisheye view of the double track near the location where the acoustic sensors were placed throughout the test.

Two sample time based acoustic signatures from passing transit cars are shown in Figures 10 and 11. The first time trace (Fig.10) was collected when the rails were totally dry and free of lubricant. Figure 11 shows the typical noise output when the track is fully lubricated. Note the amplitude difference between these two separate time based plots. The largest amplitudes were, of course, recorded whenever the rails were dry.

Figure 12 is a summary display of all the acoustic noise data collected during the study. The plot displays two separate average spectral based sets of information. The figure reveals that the highest reduction in noise occurs when the generated noise frequency is high (above 3000 Hz). When lubricant is on the rails, low-frequency noise is is still significantly reduced in magnitude but not as much as the high frequencies are. So, whenever lubricant is between the rail-wheel contacts it is difficult to generate loud squealing noise since the tangential frictional force across the interface is low and/or highly damped.

Single Point - Top of Rail Lubricator Facts:

1) Lubricators Help Control Friction And/Or Wear

2) Lubricators Reduce Energy Loss

3) Lubricators Reduce Transit Wheel Noise

4) The Top of Rail Lubrication Approach Is Useful

on Short Rail Sections And/Or Single Curves

5) The Method Uses Small Amounts of Lubricant

6) The Scheme Is Compatible With Foot And

Automobile Traffic

7) Applied Lubricant Can Be Carefully Controlled

8) The Method Viable for Closed Subway Systems

See Refs. 21-23 for more details on this topic.

ACOUSTIC MONITORING AND INTRUSION SECURITY

A local company International Electronic Machines, Inc. (-IEM-) is presently developing an acoustic intrusion monitoring system. See Ref. 24 (a previous related completed study). Subsequently, IEM has obtained a second phase SBIR contract which includes at least one task for implementing new acoustic monitoring schemes. This new acoustic monitoring approach under development at, IEM is part of an overall larger monitoring system which includes video surveillance and pattern recognition. The acoustic portion of this project is intended to enhance the video actuation capabilities of the intrusion detection package.

Although there are many ways to implement intrusion detection, the use of acoustics is an inexpensive approach which can be coupled with many other monitoring techniques. A modular arrangement of microphone array elements is presently being tested in the IEM facility in Albany, NY. The acoustic detector under development is focused on early warning schemes which will be activated whenever sounds such as the following are observed:

1. sounds from people talking,2. sounds from people walking,3. noises generated by cars & trucks, and4. other extreme noises such as, gunshots.

In summary the acoustic work underway at IEM can be stated as follows:

1. Proof of Concept Trial Tests Were Initiated With Commercially Available Microphones Coupled with Solid-state Handheld Recording Devices

2. Laboratory Tests Proved Sound Source Location Can Be Performed with Simple Set-Up Microphone Units & Arrangements

3. Initial Simplified Sound Character Analyses Show that Sound Sources Could Be Classified into Identifiable Security Based Categories

See Figure 13 through 16 for a few graphics related to the IEM work and this part of our discussion.

Figure 13 shows two stereo microphones arranged for few simple acoustic evaluation tests. With this arrangement a sound source location positioning method was reviewed. With this arrangement, source sound positions could be calculated in a large test room to an accuracy of about 1 foot.

Figure 14 is a sonogram of a walker traversing through a wooded area. No simple specific frequency can be identified however, the repetitive motion of the person’s feet touching the ground created an identifiable repetitive acoustic pattern.

Figures 15 and 16 are derived from the sounds created by a passing truck, as it first approached and then passed by the microphone arrangement set up to monitor these sounds. In


this case there are specific dominant frequencies evident throughout the time the truck first approached and then left the site.

Time and frequency based responses from source sounds are sometimes useful in characterizing the nature of the source sounds themselves. In the absence of full char-acterization of the sounds through pattern recognition, the fact that the sound is heard is evidence that something is making noise. From a security standpoint it may be most important to direct attention to the source of the sounds regardless of their acoustic character.

TRUCKING INDUSTRY TIRE BLOWOUT AVOIDANCE SYSTEM

Every U.S. truck should be outfitted with an acoustic based T-BAM. T-BAM is an acronym for Tire Blowout Avoidance Monitor.

Acoustic based tire blowout avoidance monitoring is not offered by today’s security based manufacturers. In the author's opinion it should be, but for now it is just a dream.

If you travel our U.S. highways you may be aware that there is a need for tire blowout avoidance monitoring. Today's U.S. highways are littered with truck tire debris.

Some truck tire debris lying in the center of one of our major U.S. highways is shown in Figure 17. Figure 18 is a photo of a typical truck that runs on our highways. As shown in the photo, most truck axles have four tires. Any single loss of a truck tire from overheating and blowing out may not cause the truck itself to have an accident but the debris flying from the blow out itself is a potential danger to anyone following that truck.

If you have driven our highways recently, you know that some truck tire debris can be spotted on the average about every one to five miles. This is consistent throughout the major U.S. highway system in those states that DO NOT pick the debris. If we assume that every couple of years all this debris is replaced over and over again this scattered highway material represents a lot of potential automobile accidents, just waiting to happen.

With approximately 1,000 miles of highway in each of our states, this debris represents somewhere between 200 and 1000 tire blowout's. Multiply these average number of blowout's by the 50 states and you’re witness to the remains of some 10,000 to 50,000 potential accidents every year or two.

Whether a given blowout tire causes an accident will never be established in advance. But on the average, some of these blowouts will (and do) cause serious accidents involving innocent vehicle passengers. The author knows personally of at least four individuals who were killed from flying truck tire debris.

In another incident, a friend of the author had his car totaled and his wife's arm broken when flying truck tire debris struck the front of their automobile. In this instance, the the cop who arrived at the site of the accident, told a couple that this happens all the time, and that they were just lucky they weren’t killed. The truck they were following had continued on its way, unaware that anything happened, and was never seen by the people whose car was totaled or the policeman who visited the accident.

Furthermore, the author himself has personally witnessed two truck tire blowouts while driving behind two highway trucks in his own lifetime. In one case, the debris itself just missed his vehicle, while a tire ripped itself to shreds in front of his eyes.

To be sure that a tire blowout avoidance monitor can be viable using acoustics, take a look at Figs. 19 and 20. These figures compare two types of sounds, 1) noise from a typical truck tire on the highway, and also 2) sounds emanating from a truck tire which has an inherent problem. The second signal is from a truck tire that is in the process of overheating and will ultimately blowout. Note the amount of modulation present in the defective tire represented in Fig. 20. A simple microphone mounted on each highway truck could be used to activate WARNING LIGHTS or produce an acoustic output which would warn the driver of the impending danger. It is estimated that such a device could be produced and mounted in any truck for around $25.

Maybe in the past, you witnessed truck tire debris flying past your own vehicle. An acoustic based tire blowout avoidance monitoring device which might be used to avoid this from happening in the future is well within our technical grasp today. The author is ready and willing to develop the needed T-BAM whenever you are. Let's say we start today, shall we?

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1. Kroodsma, Donald, “The Singing Life Of Birds: The Heart And Science Of Listening To Birdsong", Houghton Mifflin Publisher's, New York, 2005.

2. Florom, R. L., Hiatt A. R., Bambara J. E., & Smith R. L., "Wayside Acoustic Detection of Railroad Roller Bearing Defects", ASME Paper No. 87-WA/RT-11, December 1987.

3. Smith, R. L., “Acoustic Signatures of Birds, Bats, Bells, and Bearings”, Vibration Institute Paper Presented at the Annual Meeting, Dearborn, MI, June 1998.

4. Frarey, J. L., Smith, R. L. and Krauter, A. I., "Wayside Derailment Inspection Requirements Study for Railroad Vehicle Equipment", DOT Final Report No. FRA/ORD-77/18, May 1977.

5. McGrew, J. M., and Smith, R. L., "Railroad Roller Bearing Defect Study", Contract DOT-TSC-1505 Final Report, August 1978.

6. Frarey, J. L. and Smith, R. L., "Acoustic Signatures of Various Roller Bearing Defects", AAR/University of Illinois Conference on Railroad Bearing Failure Detection and Diagnosis, April 15-16, 1986.

7. Bambara, Joseph E., Frarey, John L., Smith, Richard L., “On-line Acoustic Detection of Bearing Defects”, United States Patent 4,790,190, December 13, 1988.

8. Smith, R. L. and Bambara, J.E., "Acoustic Detection of Defective Rolling Element Bearings", Paper presented at the 43rd MFPG Meeting in San Diego, Ca., October 1988.

9. Smith R. L., Bambara J. E., & Florom, R. L., "Railcar Bearing End-Life Failure Distances and Acoustical Defect Censuring Methods", ASME Paper Presented at the Winter Annual Meeting in Chicago, Ill., November 1988.

10. Gerald B. Anderson, James E. Cline, Transportation Technology Center, Inc. (TTCI) and Richard L. Smith, North-South-East-West (NSEW), “Acoustic Detection Of Roller Bearing Defects: Phase II, Field Test”, Report DOT/FRA/ORD-00/06.II, Funding DTFR53-93-C-00001, Task Order 111, Office of Research and Development, Washington, D.C. 20590, August 2003.

11. Smith, R. L., "A Review of the Defective Roller Bearing Vibration CD Data Sets Collected by the Association of American Railroads," Vibration Institute Paper Presented at the Annual Meeting, New Orleans, LA, June 1997.

12. Luczak, Marybeth, “Don't Fret. These Bearings Are Tough: The Class K Bearing Continues To Make The Grade In Today's Harsh, Heavy-Axle Load Environment”, Railway Age, Feb, 2004.

13. Hawthorne, Keith L., “TTCI weighs in on TADS and TPDS”, Railway Age, April, 2004.

14. The TADS Acronym has many commercial and government meanings. See: http://acronyms.thefreedictionary.com/TADS. The one defined in this paper and used by the TTC is not contained in the above web site’s free dictionary.

15. Anderson, Gerald, “Now Hear This! - Transportation Technology Center Inc. New Trackside Acoustic Detection System May Detect Faulty Railroad Roller Bearings”, Railway Age, Oct, 2001.

16. Hawthorne, Keith and Irani, Firdausi, ” Reducing The Stress State Of The Railway: Integrating New Wayside Defect Detection And Condition Monitoring Systems Can Help Lower The Load Or Stress State Of The Railway, Improve Safety, And Increase Operating Efficiency - Research & Development”, International Railway Journal, Sept, 2003

17. “TADS - Preventing Railroad Accidents”, Brüel & Kjær Magazine Issue No. 1, 2004.

18. “China Acquires TADS™”, Railway Age, Nov, 2005.

19. “Canadian Pacific Railway (CPR) installs “smart” sound technology for predicting wheel bearing failure”, Calgary, Alberta, Canada, December 6, 2004

20. Anderson,Gerald B., Irani, Firdausi, D., Urban, Curtis L., from the Transportation Technology Center, Inc., Pueblo, Colorado, “USA Development and Deployment of Advanced Wayside Condition Monitoring Systems”, Conference proceedings of the 7th

INTERNATIONAL HEAVY HAUL CONFERENCE on ”Confronting the Barriers of Heavy Haul Rail Technology.” Brisbane, Australia, June 10 - 14, 2001.

21. Smith, R. L., “Rail Squeal Noise Evaluation Study Before & After Plasma Spray Coating”, Transit Authority of Portland, Oregon, July, 1999.

22. Smith, R. L., “Technical Report Acoustic Evaluation of Rail Lubrication”, TTC Contracted Report to the Transit Authority of Portland, Oregon, August, 2004.

23. Smith, R. L., "Roller Bearing Protection Cost Model Review", Final Report to a Major Railroad Supplier, Presented December 1995.

24. Smith, R. L., “Design of a Miniature Wireless Infrared & Acoustic Sensor, Test Result Supplement for an SBIR Report”, NSEW Review Report to IEM, Albany, NY, April, 1999.


http://acronyms.thefreedictionary.com/TADS

Figure 1 A graphic representation of passing train sounds.

Figure 2 The first derivative of the time based data previously shown in Figure 1


Figure 3 Large cup defect in bearing on axle 4 of run 24

Figure 4 Large cone defect in bearing from axle 19 of run 24.


Figure 5 Acoustic envelope signatures from the two bearings shown in the photos are highlighted with boxes

Figure 6 Time expansion view of the acoustic signal from bearing 4 which was highlighted in the previous figure


Figure 7 Acoustic display from a gas fired furnace showing a sequence of four on-off cycles over time


Figure 8 – View of one of transit cars while passing through an acoustic evaluation test site.

Figure 9 – Test site photo near acoustic sensing location. Note separate North & South bound tracks.


Figure 10 – Typical time based noise recordings taken when the rail was “Dry” i.e., lubricant free.

Figure 11 – Typical time based noise recordings taken during the time when the rail was lubricated.


Figure 12 – Image depicting average relative spectral noise levels under dry & lubricated conditions.


Figure 13 Simple 4 Microphone Test Evaluation Set-Up for IEM Acoustic Intrusion Study


Figure 14 Sonogram from a Single Walker collected by a Microphone for the IEM Acoustic Study.

Figure 15 IEM Test Microphone Recording from a Passing Truck.


Figure 16 IEM Test Sonogram from Sounds Generated by a Passing Truck.


Figure 17 Tire Debris from a Truck Tire Blow Out Lying on the Pavement of a Major Highway.

Figure 18 Highway Trucks Should be Outfitted with T-BAMs. Tire Blowout Avoidance Monitors


Presented at the 2nd Annual Tech Valley Symposium, April 18, 2006, Albany, NY

Figure 19 – Sounds from a Typical Truck TireNote: Very Little or NO Modulation while Traveling at 75 MPH

Figure 20 – Sounds from a Defective Truck TireNote: Constant 10 Hz Modulation while Traveling at 75 MPH

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