INSIGHT-UsingAcousticEmissiontoMonitorSlidingWear

8/7/2019 INSIGHT-UsingAcousticEmissiontoMonitorSlidingWear

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Insight Vol 44 No 8 August 2002 1

C K Mechefske, G Sun and J Sheasby

AE

1. IntroductionAcoustic emission is generated at the sites of mate rial wear andso is an attractive possibility for continuously monitoring wearand for basic studies of the wear process. In order to determinewhether effective boundary lubrication can be distinguished frompoor boundary lubrication using acoustic emission measurements,a unique tribometer was used in which the conditions of lubricationcould be rapidly and reliably changed from good to bad. Vibrationmeasurements were made close to the interacting surfaces usinga laser vibrometer. Changes in wear rate and acoustic emissionactivity were measured across the mild-severe wear transition insliding wear. The intent was to characterise these changes in wearbehaviour in terms of acoustic emission characteristics and todetermine the usefulness of acoustic emission measurements forthe study of wear. Successful discrimination would have signi cantpotential for machine condition monitoring applications and forlubricant evaluation.

2. Literature reviewAcoustic emission (AE) in the sense used here refers to elasticwaves produced by microscopic deformations occurring in materialsas they are stressed and which comprise part of the elasticenergy released during deformation. Sometimes called stress wave

emissions , acoustic emissions are associated with dislocationmovements, with crack growth, with deformation of inclusions andwith other mechanisms. Detectable emission may be observed in awide variety of materials, in different modes of deformation, and canbe detected at solid surfaces with appropriate instrumentation [1].

Acoustic emission activity levels can be determined in real timeand utilised for the evaluation of a structure or component. SinceAE signals can travel over a long distance, an entire structurecan be examined in a single test sequence. Acoustic emission canbe used to continuously monitor the integrity of a structure inservice under favourable conditions. Wear research is another areawhere AE could be useful because of its sensitivity to dynamicmicroscopic processes. Unlike ultrasonic test methods, acousticemission is a passive test method in that no direct excitation isapplied. However, AE testing requires the application of a certainstimulus to a test-piece [2].

The literature on the subject reveals that there exists a goodunderstanding of the mechanisms of wear in sliding contacts andhow these mechanisms are affected by variation of operatingconditions. It is recognised that, under moderate load and slidingspeed conditions, ceramics exhibit mild wear, characterised byessentially micro-cracking of the sub-surface. In some situations,changing the contact parameters can produce severe wear regimeswith a corresponding increase of the wear rate [3]. Alternatively,layers of low mechanical strength formed from compacted smallerfragments and particles [4] or more coherent thin layers of enhancedmechanical parties can protect the rubbing surfaces.

Kholodilov and Rapoport [5] studied both friction and wear of polymers sliding on steel using AE measurements. As specimensurface roughness was increased and adhesion and fatigue wearmechanisms gave way to abrasion, the AE count rate increased.Results showing a linear relation between total AE counts and theamount of wear were also presented. This result is explained interms of the volume of wear being related to wear particle surfacearea as in an Archard-type wear model and the amount of AEdepends on surface area since new surface formation generatesAE.

It has also been found that tribological interactions betweenfibrous networks and polymer surfaces result in the generation of

AE signals. The intensity of such signals was found to dependupon transducer contact pressure and rubbing velocity as well as onspecimen material mechanical behaviour [6][7] .

Rapports [8] studied AE generated in friction and wear. Resultssimilar to those described above were obtained for relationshipsbetween coefficient of friction, wear and AE. Filatov [6] limited theactive wear mechanisms to only abrasion by studying the slidingof metals on bonded abrasive surfaces. By varying the abrasive gritsize, the wear particle size was controlled and results showing AEcounts proportional to wear particle surface area were produced.

Several techniques have been developed to analyse AE signals.The most common techniques are: the count rate method, inwhich a threshold signal value (usually above the noise level) isselected and the number of threshold crossings per unit time is

determined; the amplitude distribution analysis, in which severaldiscrete thresholds are chosen and the relative number of eventsoccurring within each threshold interval is obtained; frequency

Using acoustic emission to monitor sliding wear

In this study, acoustic emission (AE) was used to monitorthe wear process and wear situations with a tribometerconsisting of a steel ball sliding on a sapphire disk and ona steel disk, with and without zinc dialkyldithiophosphate(ZDDP) additive in the lubricant. The paper discusses thecharacteristics of the stress waves generated and theirvariation with test conditions. Changes in test conditionsand acoustic emission activity were measured across themild-to-severe wear transition using sapphire and steel sliding disks. The intent was to characterise these changes inwear behaviour in terms of acoustic emission characteristicsand to determine the usefulness of acoustic emissionmeasurements for the study of wear. It is shown that thereis a systematic relationship between acoustic emission and wear rate. In the time domain signals, the AE counts weresmall when the wear rate was mild and large when thewear rate was severe. In the frequency domain signals, theAE variation is low when the wear rate is mild and highwhen the wear rate is severe. The ZDDP anti-wear additivecan reduce AE activity. It appears that the energy released is primarily in the frequency range of 100-500 kHz. Thedifference between mild and severe wear rates is clearlyobservable in both the time domain and the frequencydomain. These results suggest that AE has the potential tobecome a useful wear rate monitoring technique.

Chris K Mechefske is in the Department of Mechanical Engineering,Queens University, Kingston, Ontario, Canada, K7L 3N6.

George Sun and John Sheasby are in the Department of Mechanical &Materials Engineering, University of Western Ontario, London, Ontario,Canada, N6A 5B9.


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2 Insight Vol 44 No 8 August 2002

spectral analysis, which yields the frequency components of therecorded AE signal; autocorrelation analysis, which is used toidentify the periodic components of the signal; and root-mean-square (RMS) analysis, in which the RMS of the AE signal(AE-RMS) is used as an indicator of the energy released [9].

3. Experimental equipment and methodThe tests reported on here were carried out on a ball-on-disk

tribometer under conditions of pure sliding, ie a stationary ballbeing loaded against a rotating disk (see Figure 1(a)). The ball-on-disc tribometer system is powered by an electric motor thatprovides the rotating movement and torque to a sapphire discthrough a exible coupling. The coupling helps prevent vibrationsoriginating in the motor bearings and/or speed reduction gearboxfrom being transmitted to the vibration measurement point. Slidingspeeds varying between 0 to 800 mm/s can be obtained. Theball (sample) holder is attached to a rigid arm which is linked tothe rig support by a horizontal pivot. The arm is balanced by acounterweight.

Care was taken to ensure that the arm was perfectly horizontalat the beginning of each test. Force sensors were used to measurethe normal load and the friction load with a resolution of atleast 0.01 kg. Vibration signals were detected at the ball holderusing a Polytec laser vibrometer. The output signals from the laservibrometer were collected using a Hewlett-Packard 54645 deepstorage oscilloscope. Matlab was the principal softwear used forsignal analysis.

The wear behaviour was observed through the sapphire discusing a microscope and a CCD video camera. Superimposed onthe video picture was the elapsed time, the oil temperature, loadon the ball and friction force. Figure 1(b) shows a schematic of theexperimental set-up.

The base oil used in the study was Solvent 50N (kinematicviscosity 28.31 cSt at 40C). The antiwear additive used in the oilare based on zinc dialkyldithiophosphate (ZDDP). The material of the test ball is 52100 stainless steel. The Rockwell C hardness is64 and the surface roughness is 0.1 m. Specimen preparation was

completed by degreasing with hexane and 5 min ultrasonic bath indetergent solution and IPA alcohol degreaser.

4. Wear propertiesWear protection in motor oils is usually achieved by theuse of antiwear additives in the oil that are based on zincdialkyldithiophosphate (ZDDP). Wear protection by ZDDPs hasbeen associated with the formation of lms largely composed of

inorganic, amorphous phosphates [10] . When the additive is workingoptimally the wear rate is less than 1 mm 3/Nm. Wear surfacesare coated by uneven glassy lms averaging 0.3 mm thick withload-carrying asperities, typically 20 mm in diameter, that formand decay with a half life of about two minutes (see Figure 2(e)).Additive debris appears to be ne granular particles of about 50 nmand of essentially the same composition as the thick glassy antiwear

lms [11] . When the additive is performing less satisfactorily, wearrates can be greater than 25 m3/N.m, which is the maximum rateallowable to pass a Sequence V test. At such rates the wearingsurfaces have a sparse antiwear lm with metal being lost by achemical wear process (see Figure 3(a)).

The two different wear situations representing effective andineffective additive performance , as described in the introduction,were achieved by changing the rotating speed of the disk. Thetemperature (room) and load (4 kg) were held constant. In thisexperiment sliding speeds of 5, 10, 20 40 mm/s are considered low.Figure 2(a) shows the wear surface situation during low slidingspeeds. Figure 2 (b), (c) and (d) show the wear surface of test ball atfaster sliding speeds: 50 mm/s, 60 mm/s and 70 mm/s. It was foundthat the ZDDP additive started to be effective at a sliding speed of 50 mm/s, when the protection film started to appear on the wearsurface. The lubricant protection film covered area increases withsliding speed. This stage can be considered as a transition stagefrom poor to effective lubrication. Figure 2(e) shows the surfacesituation of sliding speeds 80, 120, 240, 480 mm/s, which areconsidered high sliding speeds. At a high sliding speed the additivewas effective, whereas at low sliding speed severe wear occurred.

5. Acoustic emission in wearThe investigation of wear phenomena by AE monitoring has severalattractions. Acoustic emissions are generated in a deforming bodyby the deformation process and so are direct indications of theactual wear event. They can be viewed as a description of theprocess, which is more closely linked to the process than materialstructure or geometry features. The characteristics of the AE signalsuch as frequency, amplitude, duration, growth and decay rates aredetermined by material properties. These signal characteristics aredistinct from phenomena generated by test or production machinesand their components.

The changes in the plastic deformation state of a body result inthe generation of stress waves or acoustic emissions. When thesestress waves are detected by the laser vibrometer, an electricalsignal is generated. Such signals are referred to as AE signals.Two types of AE signal analysis are usually recognised: frequencydomain analysis and time domain analysis.

In real- time monitoring applications of AE, the use of timedomain analysis is common. Measured AE parameters in timedomain analysis include (see Figure 3): (a) AE events , which canbe defined as a detected AE signal; (b) AE counts , or the numberof times an acoustic emission signal exceeds a pre-set thresholdvoltage (usually above the background noise level) during a test;(c) AE count rate , or the rate at which AE counts occur; (d) AE peak amplitude , or the peak voltage of the largest excursion attained

by the signal waveform during an AE event; and (e) AE energy ,defined as the electrical energy in an AE signal which is believed tocorrespond to the energy released by an AE source [12] .

(b)

Figure 1. Schematic diagram of (a) ball-on-disk tribometer and(b) experimental set-up for AE signal acquisition andprocessing

(a)


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Two main types of acoustic emission a re usually recognised.For a discrete short-term event such as an increment of crackpropagation in a brittle material, an emission burst lasting typicallytens of microseconds can be identified. For deformation proceedingsteadily at a lower level, as in large-scale yielding of a ductilematerial, multiple individual emission waves of low amplitudeare thought to merge and overlap producing continuous emissionthat appears on initial observation similar to electronic noise. Acontinuous AE signal can be defined as one in which the averagetime between emissions of similar amplitude is less than theduration of the emission. Quantitative data are most frequentlyexpressed in terms of the root mean square (rms) value of the signalor in terms of measurements known as ring-down counts which

record the number of times the acoustic emission signal exceedsa pre-set trigger voltage level (or a weighted count based on a

number of pre-set trigger voltage levels). The former is held tobe more appropriate for continuous emissions and the latter moresuited to burst emissions. In each case, the measurement is closelyrelated to the energy of AE activity [13,14,15] .

In these experiments, acoustic emission frequencies up to1.5 MHz have been recorded. The focus is therefore on theultrasonic regime of wave transmission as distinct from relativelylow frequency noise. The associated acoustic emission is likelyto be high frequency transient elastic stress waves (100 kHz to1 MHz) generated by the rapid release of strain energy within the

(a) Poor lubrication (Sliding speeds 50 mm/s)Figure 2. Wear surface situations

Figure 3. Schematic representation of an AE signal


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material. The waves can travel as compression, shear or surfacewaves. The frequency range under investigation in this study istherefore well above the frequency range normally used to detectand diagnose mechanical deterioration in machinery. Most machinecondition monitoring approaches use frequencies at only a fewtimes the rotating or reciprocating speed of the machine. Only incases of high-speed turbomachinery, that incorporate gear boxes,would the defect frequencies of interest exceed 20-25 kHz.

An advantage of using these high frequency stress waves is to

avoid background noise in the signal. It is possible to filter outthe traditional frequencies of interest ( < 25 kHz) associated withmoving mechanical components. The characteristic time and/orfrequency domain features can then be identified.

6. Results and discussionTime domain signals analysis

All time domain signals in these experiments were l tered usinga 100-1000 kHz band-pass lter. The sampling frequency was4 MHz and signal processing involved using blocks of 4000 datapoints collected over sampling intervals of 1 ms.

6.1 Time domain AE signal at different sliding speeds and lubrication conditions

Figure 4 shows a typical time domain AE signal while monitoringthe wear behaviour of the test ball on the sapphire disk underdifferent sliding speeds. The lubricant is base lubricant with noZDDP additive. The load on the test ball was 4 kg. Figure 4indicates the AE signals of wear in a poor lubricant situation (therewas no lubricant lm on the wear surface). This response wastypical of all sliding speeds.

Figure 5 shows the time domain AE signal while monitoring thewear behaviour of test ball on the sapphire disk. The lubricant hasZDDP additive. Figure 5(a) indicates the AE signal representinga poor lubricant situation (there is no lubricant film on the wearsurface). Figure 5(b) indicates that the wear surfaces are partly

covered by lubricant film. Figure 5(c) indicates that the AE signalrepresents wear behaviour in an effective lubricant situation (there

is lubricant film on the wear surface). It was found that there wasmore AE activity during the poor lubricant situation.

Figure 6 shows a typical time domain AE signals whilemonitoring the wear behaviour of the test ball on the steel disk. Thelubricant was base lubricant with no ZDDP additive. This figureshows continuous AE activity indicating poor lubricant conditions.This signal is typical of all sliding speeds. Figure 7 shows thetime domain AE signal while monitoring the wear behaviour of the test ball on the steel disk. The lubricant has ZDDP additive.

The wear occurring on the surface cannot be seen directly in thiscase. However, it is clear that there was more AE activity duringlow sliding speed than during high sliding speed indicating poorlubricant conditions at low speeds and good lubricant conditions athigh sliding speeds.

6.2 The comparison of wear rate and AE signals

It is generally accepted that the plastic deformation generatescontinuous AE signals, whereas AE signals resulting from crackingprocesses are characterised by bursts. The large amplitude burstsignals can also be generated from small metal piece breakage.The peak level of AE signals are considered to be created by burstsignal emission. In this section, the peak level, RMS level, countrate of AE signals and the percentage quiet time are examined inthe time domain signals in order to establish correlation betweenthe wear process and associated AE signals.

Figure 8 shows the variation of the different AE signalcharacteristics during the monitoring of the wear behaviour of testball on a sapphire and a steel disk. The sliding speed changesfrom 5 mm/s to 480 mm/s. Load added on the test ball was 4 kg.Figure 8(a) shows the variation of the peak level for differentsliding speeds and wear situations. It can be found that fastersliding speeds lead to higher AE peak levels. Figure 8(b) showsthe variation of RMS level at different sliding speeds and wearssituations. The results indicate that faster sliding speed leads tohigher RMS levels, and the ZDDP additive can reduce the overall

RMS level. AE signal intensity is proportional to strain rate andtherefore it is reasonable to find that higher energy AE signals aregenerated at higher sliding speeds.

The count rate has been adapted to analyse AE signals usingthreshold values above the noise level. Since the amplitude of a

Figure 4. Time domain AE during wear on the sapphire disk withbase lubricant only

(a) Sliding speed of 40 mm/s (b) Sliding speed of 60 mm/s (c) Sliding speed of 80 mm/sFigure 5. Time domain AE signals during wear on the sapphire disk with ZDDP lubricant

Figure 6. Time domain AE during wear on the steel disk withbase lubricant only


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continuous signal increases gradually with sliding speeds, the countrate obtained for a fixed threshold value is affected by both continuous

and burst signals. If a threshold value is set above the dominantamplitude, the variation of burst signals with sliding distance can beexamined by observing the variation of the count rate.

Figure 8(c) shows the variation of the AE count rate in differentsliding speeds. For wear on sapphire with base lubricant, all wearsituations were poor lubrication. For wear with ZDDP lubricant,the ZDDP additive started to be effective at 50 mm/s when thelubricant films first appear on the wear surface (see Figure 2(b)).The results show the AE count rates of wear with ZDDP lubricantare smaller than those wear with base lubricant when sliding speedswere faster than 50 mm/s (Figure 8(c)). This indicates that thelubricant protection film can reduce the AE count rate. Theseresults also demonstrate that AE is sensitive to sudden changes inwear behaviour.

The wear situations could not be seen directly when the wearon steel was occurring. It can be found that faster sliding speedlead to higher AE peak and RMS level. The RMS levels of wearwith ZDDP lubricant are lower than those with base lubricant.Figure 8(c) also shows the variation of the AE count rate in differentsliding speeds. It shows the ZDDP can reduce AE counts rates

(a) Sliding speed of 40 mm/s (b) Sliding speed of 60 mm/s (c) Sliding speed of 80 mm/sFigure 7. Typical time domain AE signals during wear on the steel disk with ZDDP lubricant

(a) Peak level vs wear on sapphire and steel disk (b) RMS level vs wear (sapphire and steel)

(c) AE count rate vs wear (sapphire and steel) (d) Percentage of AE quiet time

(e) Wear rate of different sliding speeds

Figure 8. AE comparison and wear rate


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when sliding speeds are faster than 50 mm/s for steel on sapphireand for steel on steel.

Figure 8(d) shows the percentage of the time that the AE signalwas quiet. Here a quiet period if defined as a period of time whenthe AE signal is continuously below the AE count rate thresholdlevel for at least 1 s (1% of the sample length). The result showsthat the AE quiet periods during ineffective lubrication are stable ataround 2-5% of the total signal. With more and more film coveragethe quiet periods increase. The AE quiet periods are stable around25-29% of the total signal when the surface was fully covered by

film.Sheasby [11] investigated the wear rate of a ball on rotating disk

with ZDDP additive at constant load and temperature. Figure 8(e)shows the result that wear rate decreases as sliding speeds go up.The test results show that AE peak and RMS levels increase aswear rate decreases. Comparing the wear rate and AE count rate(Figure 8(c)) it is seen that the AE count rate and wear rate bothdecrease as sliding speed increases. This result shows that AE countrate and percentage quiet time could be useful in detecting wearconditions and distinguishing between effective and poor lubricantsituations.

6.3 The effects of ZDDP on wear behaviour

Figure 9(a) shows the time domain AE signal during wear on thesapphire disk at high sliding speed and with base lubricant only.Figure 9(b) shows the time domain AE signal after ZDDP additivewas added into the base lubricant. Figure 10(a) shows the AE

counts comparison of Figure 9(a) and Figure 9(b). It is clear thatZDDP additive reduces the AE count as well as the wear rate.

Figure 9(c) shows the time domain AE signal during wear onthe steel disk at high sliding speed and with base lubricant only.Figure 9(d) shows the time domain AE signal after ZDDP additivewas added into the base lubricant. Figure 10(b) shows the AE countcomparison of Figure 9(c) and Figure 9(d). It is clear that ZDDPadditive reduces the AE count as well as the wear rate in bothsituations. The results also indicate that the wear on the steel diskcreates more AE activity than wear on the sapphire disk.

6.4 The effects of load on AE signals

It is known that as the load increases the wear rate tends toincrease [11] . In order to investigate the effects of load on wearbehaviour and AE signals some tests were carried out involvingwear on a sapphire disk for different applied loads at constantsliding speed. The loads added on the test ball were 3 kg, 4 kg, 7 kgand 10 kg at sliding speed of 10 mm/s.

Figure 11 summarises the AE results obtained from theexperiments of wear on sapphire disk with ZDDP lubricant. Thecomparison of the RMS level distributions in Figure 11(a) indicatesthat increasing load applied on the test ball could reduce the RMSlevel of AE. Figure 11(b) shows the AE count rate variation underdifferent loads. It is clear that with larger loads the AE count rateincreases. This indicates that as the load increases the AE activityalso increases. The increase in the AE count rate indicates thathigher applied loads can produce severe sliding wear.

(a) Sapphire disk, base lubricant (b) Sapphire disk, ZDDP lubricant

(c) Steel disk, base lubricant (d) Steel disk, ZDDP lubricantFigure 9. Time domain signals comparing sliding wear with and without ZDDP additive for steel and sapphire (sliding speed of 480 mm/s)


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Frequency domain signals analysis

6.5 The RMS of spectral difference at different sliding speeds

As in the previous section the AE signals used here were sampledat a frequency of 4 MHz during each of the tests. Each samplecontained 4000 data points (collected over 1 ms), which wereanalysed using a fast Fourier transform algorithm. Frequencyspectra generated from the AE signals that represent different wearsituations are shown in Figure 12 and Figure 13.

During different wear situations the frequency characteristicsof the acoustic emissions generated are quite distinct. Fromobservation it is clear that the frequency range of 100-500 kHzrepresents the range where there is the most significant differencebetween the two signals. While the overall amplitude of thefrequency spectra is higher for the effective wear situation theresponse is relatively flat and there is minimal variation. For thecase where there is a poor wear situation the overall amplitude of

the frequency spectra is slightly lower and the response at differentfrequencies is relatively variable.Figure 14 shows the RMS of Spectral Difference (Rdo) [16] of

AE signals from different sliding speeds. The RMS of spectraldifference is the root mean square of the difference between twospectra when the amplitude of the spectrum coefficients are givenlogarithmically. Comparing the RMS of Spectral Difference values,it was found that there was more variation in the spectra duringthe poor lubricant situation (sliding speed 5, 10, 20, 40 mm/s) thanduring the effective lubricant situation (sliding speed 80, 120, 240,480 mm/s).

In order to compare the root mean square of the differencebetween two frequency ranges within one frequency domain AEsignal, the RMS of Spectral Difference Ratio was applied to

compare the spectral difference of 100-300 KHz and 700-900 KHz(see Figure 15).

Figure 16 shows the Rdo Ratio comparison for different testmaterials and lubrication conditions. It shows a smaller Rdo ratiowhen wear was in an effective lubrication condition.

(a) AE count rate (sapphire disk, sliding speed 480 mm/s)

(b) AE count rate per (steel disk, sliding speed 480 mm/s)Figure 10. Effects of ZDDP on wear behaviour

(b) AE count rate of different loadsFigure 11. The effects of load to AE signals

(a) RMS level of different loads

Figure 12. Frequency spectra from AE signal during wear onsapphire disk under poor lubricant conditions (sliding speed20 mm/s)

Figure 13. Frequency spectra from AE signal during wear on

sapphire disk under effective lubricant conditions (sliding speed240 mm/s)


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7. ConclusionsAcoustic emission signals generated during the wear processinvolving a steel ball sliding over sapphire and steel disks wereanalysed in both time and frequency domain. The results obtainedfrom the experiments carried out show that AE has the potential tobecome a useful wear rate monitoring technique.

In time domain signals the increase of AE peak level and RMSvalue parallel the increase of sliding speed, this indicates that peak

level and RMS level are useful to represent the wear surface strainrate. However, peak level and RMS level are poor indicators of a changing wear rate. The variations of AE count rate and thepercentage of quiet time in the AE signal parallel the variationsof wear rate across the poor-effective lubrication transition. Ingeneral, AE count rate is low when lubrication is effective and highwhen lubrication is poor. The percentage of quiet time in the AEsignal is high when the lubrication is effective and low when thelubrication is poor.

The test results show the sensitivity of AE to the loadingconditions. The results indicate that under steady state the AE countrate increases with increasing applied load, however, the AE peakand RMS levels decrease with increasing applied load.

The time domain signal analysis also indicated that lubricant

film can reduce the AE count rate, such a correlation betweenwear and AE signal could be very useful in the characterisationof wear mechanisms since AE count rate measurements can bedirectly related to important physical parameters. It can be said thatin general the occurrence of poor wear situation is characterisedby the intensification of a wear mechanisms, the later resultingin high AE activity (as evidenced by high AE count rates andcorrespondingly low percentage quiet time).

The frequency analysis indicates that the AE signals in therelatively low frequency range (100-500 kHz) exhibit a strongdependence on the lubrication conditions. In frequency domainsignals the AE variation is low when the wear rate is low and highwhen the wear rate is high. The ZDDP anti-0wear additive canreduce AE activity. The results suggest that the energy released ismainly in a specific frequency range (100-500 kHz).

In general, the occurrence of severe wear is characterised by theintensification of wear mechanisms resulting in high AE activityas evidenced by high AE count rate in the time domain and highspectral variation in the frequency domain.

8. References

1. S Lingard, C W Yu and C F Yau, Sliding wear studies usingacoustic emission, Wear, 162-164(1993) 597-60.

2. Kanji Ono, Acoustic emission, Handbook of Acoustic, 1998,p641-653.

3. V A Belyi, O V Kholodilov and A I Sviridyonok, Acousticspectrometry as used for the evaluation of tribological systems,

Wear, 69(1981)309-319.4. L S Rapoport, Y S Petrov and V E Vainberg, An acousticemission study of the real polymer-metal frictional contactarea, Sov. J. Frict. Wear, 3 (1982) 30-33.

5. L S Rapoport, Y S Petrov and V E Vainberg, Study of thedynamics of metal friction processes by the acoustic emissionmethod, Sov. J. Prict. Wear, 2 (1981) 91-94.

6. S V Filatov, Acoustic emission in the abrasive wear of metals,Sov. J. Frict. Wear, 3 (1982) 138-140.

7. M K Tse, J Leifer and A F Lewis, AE of exible disk magneticmedia systems, J. Acoust. Emiss., 4 (2-3) (1985) 125-129.

8. S Lingard and K K Ng, An investigation of AE in slidingfriction and wear of metals, Wear, 130 (1989) 367-379.

9. S-S Cho and K Komvopoulos, Correlation Between Acoustic

Emission and Wear of Multi-Layer Ceramic Coated CarbideTools, Journal of manufacturing Science and Engineering,p238-246/ Vol. 119, May 1997.

10. P A Willermet, D P Dailey, R O Carter III, P J Schmitz,W Zhu, Mechanism of formation of antiwear lms from zincdialkyldithiophosphates, Tribology International 28 (1995)177-187.

11. J S Sheasby, T A Caughlin, S Terranova and A Cohen.An examination of oil debris to give insight into boundary

lubrication. Tribology Series 31: The Third Body Concept:Interpretation of Tribological Phenomena. Ed D Dowson, et al ,Elsevier 1996, p. 685-693.

12. A G Beattie, Acoustic emission, principles and instrumentation,J. Acoust. Emiss., 2 (1983) 95-128.

13. H S Benabdallah and R J Boness (1999). Tribological behaviourand acoustic emissions Material Science, No 34, pp1-10.

14. R J Boness and S L McBride: Adhesive and abrasive wearstudies using acoustic emission techniques Wear, 135 (1989)171-191.

15. J Hanchi and B E Klamecki: Acoustic emission monitoring of the wear process, Wear, 145 (1991) 1-27.

16. C K Mechefske and J Mathew, Fault Detection and Diagnosisin Low Speed Rolling Element Bearings, Part I: The use

of Parametric Spectra, Mechanical Systems and SignalProcessing, Vol. 6, No. 4, p297-307. 1992.

Figure 14. RMS of Spectral Difference at different slidingspeeds

Figure 15. Schematic representation of Rdo ratio

Figure 16. Rdo ratio for different sliding speeds

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