slow speed rolling element bearing

8/3/2019 Slow Speed Rolling Element Bearing

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M. Elforjanie-mail: [email protected]

D. Mbae-mail: [email protected]

School of Engineering,Craneld University,

Craneld,Bedfordshire MK43 0AL, UK

Monitoring the Onset andPropagation of NaturalDegradation Process in a SlowSpeed Rolling Element BearingWith Acoustic EmissionThe monitoring and diagnosis of rolling element bearings with the high frequency acous-tic emission (AE) technology has been ongoing since the late 1960s. This paper demon-strates the use of AE measurements to detect, locate, and monitor natural defect initiationand propagation in a conventional rolling element bearing. To facilitate the investigationa special purpose test rig was built to allow for accelerated natural degradation of abearing race. It is concluded that subsurface initiation and subsequent crack propagationcan be detected with the AE technology. The paper also presents comparative resultsbetween AE and vibration diagnosis. DOI: 10.1115/1.2948413

1 IntroductionSlow speed rotating machines are the mainstay of several in-

dustrial applications worldwide. They can be found in paper andsteel mills, water industry, wind turbines, etc. The operationalexperience of such machinery has not only revealed challengingdesign issues but has also presented opportunities for further sig-nicant improvements in the technology and economics of suchmachines. Failures associated with bearings represent the cause of extended outages and are typically caused by gradual deteriorationand wear 1 . Such slow degradation processes can be identied if a robust online monitoring and predictive maintenance technologyis used to detect impending problems with obvious economicadvantages.

Slow speed rotating machinery generates relatively reduced en-

ergy loss rates from damage related processes, and therefore con-ventional condition monitoring technologies e.g., vibration analy-sis tend to be more difcult to apply. Jamaludin et al. 2summarized the limitations in applying vibration to slow rotatingmachines. However, this is not the case for the acoustic emissionAE technology, which is well suited to detecting very small

energy release rates. As a result AE is able to detect subtle defectrelated activity from machinery 3,4 . To date most publishedworks on the application of the AE to monitoring bearing me-chanical integrity have been on articially or seeded damage,which is generally induced with an electrical discharge system andengraving machine or by introducing debris into the lubricant 4 .This paper presents the experimental results of an evaluation of AE technology in detecting and diagnosing the onset of subsur-face cracks and their propagation to spalls. Comparisons betweensimple AE and vibration parameters are presented for all tests.

AE can be dened as the class of phenomena whereby transientelastic waves are generated by the rapid release of energy fromlocalized sources within a material. A tremendous amount of work has been undertaken over the last 20 years in developing the ap-plication of the AE technology for bearing health monitoring 4 .Jamaludin et al. 2 conducted an investigation into the applica-bility of stress wave analysis for detecting early stages of bearing

damage at a rotational speed of 1.12 rpm 0.0187 Hz . Attemptshad been made to generate a natural defect on the bearing com-ponents by fatiguing. However, after allowing the test bearing tooperate for a period of 800 h under conditions of grease starva-tion, no defect and/or wear was visually detectable on any of thebearing components. In a further study, Morhain and Mba 5examined the application of standard AE characteristic parameterson a radially loaded bearing. The use of typical AE parameterssuch as root mean square rms and count values was validated asa robust technique for detecting bearing damage and was shown tocorrelate with increasing speed, load, and defect size. Al-Ghamdiand Mba 6 conducted a comparative experimental study on theuse of AE and vibration analysis for bearing defect identicationand estimation of defect size. It was concluded that AE offeredearlier fault detection and improved identication capabilities thanvibration analysis. Furthermore, the AE technology also providedan indication of the defect size, allowing the user to monitor therate of degradation on the bearing, unachievable with vibrationanalysis.

Miettinen and Pataniitty 7 described the use of the AE in themonitoring of faults in an extremely slow rotating rolling bearing5 rpm . Prior to testing the test bearing had been naturally dam-

aged on its outer race. It was concluded that the AE measurementwas a very sensitive method for fault detection in an extremelyslowly rotating bearing. Choudhury and Tandon 8 applied thespark erosion method for seeding defects in bearings. AE mea-surements from bearings without defect and with defects of dif-ferent sizes were undertaken. It was shown that the use of AEparameters such as ring-down counts and peak amplitudes couldidentify bearing defects. Price et al. 9 employed a four-ball lu-bricant test machine to simulate pitting fatigue and scufng wearcommonly experienced by gear and bearing components. Theprincipal monitoring technique utilized in this investigation wasAE. The study concluded that scufng wear and pitting was de-tectable with AE. To date the only investigation on the identica-tion of the onset of natural degradation in bearings involves thework presented by Yoshioka 10 . This focused on the detection of a rolling contact subsurface fatigue crack using AE technology.An AE source locating system was developed, and it was reportedthat the system was able to locate the AE source based on ananalysis of the time delay associated with AE events acquiredsimultaneously from different sensors. Yoshioka stated that cracks

Contributed by the Technical Committee on Vibration and Sound of ASME forpublication in the J OURNAL OF VIBRATION AND ACOUSTICS . Manuscript received October23, 2007; nal manuscript received April 30, 2008; published online July 15, 2008.Review conducted by Michael Brennan.

Journal of Vibration and Acoustics AUGUST 2008, Vol. 130 / 041013-1Copyright 2008 by ASME

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were identied parallel to the surface maximum length of ap-proximately 200 m in the rolling direction of ball and were dis-tributed between 50 m and 200 m below the surface. It mustbe noted that the tests undertaken by Yoshioka were on a bearingwith only three rolling elements, which is not representative of a

typical operational bearing. Furthermore, tests were terminatedonce AE activity increased such that the propagation of identiedsubsurface defects to surface defects was not monitored. Thiswork builds further on the work of Yoshioka by monitoring notonly the initiation of cracks, but also its propagation to spalls orsurface defects on a conventional bearing with the complete set of rolling elements. Furthermore, the location of the AE source wasalso monitored throughout the test sequence in order to validatethat the AEs generated throughout the test period can be eventu-ally attributed to the surface defect noted at the end of the test;this study is the rst of its kind to date.

2 Test-Rig Design and LayoutA specially designed test rig that encouraged the natural dam-

age condition of a test bearing was employed. To speed up crack initiation, a combination of a thrust ball bearing and a thrust rollerbearing was selected. One race of ball bearing SKF 51210 wasreplaced with a at race taken from the roller bearing SKF 81210TN of the same size, as shown in Fig. 1.

A consequence of this arrangement is that the rolling elementson the at track caused higher contact pressure relative to thegrooved race due to the reduced contact area between the ballelements and the at race. For the purpose of this experiment thefollowing procedure was undertaken to determine the subsurfacestresses on the test bearing and thereby estimate the time, or num-ber of cycles, toward surface fatigue on a track. Theories em-ployed for this procedure, particularly for the at race, includedthe Hertzian theory for determining surface stresses and deforma-tions, the Thomas and Hoersh theory for subsurface stress, and the

Lundberg and Palmgren theory for fatigue evaluation. For thegrooved race the standard procedure, as described by BS 5512,1991, was employed for determining dynamic load rating. Finallythe anticipated life for dened stresses was computed for both thegrooved and at races see Tables 1 and 2 . Results clearly illus-trated that surface fatigue, such as aking, could be initiated onthe at race within a few days depending on the load condition,thereby authenticating the test-rig design. It should be noted thatthe theoretical estimation of rolling contact fatigue is known to besubject to variability or scatter when compared to experimentalresults, and this has been attributed to the probability of inclusionsin the steel material located in the highest load zones of the race11 .

A specically designed test rig, as shown in Fig. 2, was em-ployed for this investigation. It consisted of a hydraulic loadingdevice, a geared electrical motor Motovario-Type HA52 B3-B6-B7 j20,46-lubricated: AGIP , a coupling, and a supporting

Fig. 1 Test bearing

Table 1 Bearing life calculations for Case I

Input data

Load applied N 50000Number of balls 14Ball radius mm 5.75Race groove radius mm 5.8Mean bearing diameter mm 64Rotational speed rpm 72

Auxiliary quantities

Flat race Groove raceLoad on single ball N 3571 3571Curvature sum mm 0.35 0.18Curvature difference mm 0.00 0.98Dimensionless semimajor axis of contact ellipse a *

1.00 6.31

Dimensionless semiminor axis of contact ellipse b*

1.00 0.32

Dimensionless contact deformation d * 1.00 0.44

Surface stress and deformation

Flat race Groove raceSemimajor axis of the ellipsecontact mm

0.513 4.063

Semiminor axis of the ellipsecontact mm

0.513 0.206

Deformation mm 0.046 0.016Maximum pressure stress N / mm 2 6484 2042Permanent deformation mm 0.0044 00.0001 D mm 0.0012 0.0012Permanent deformation/0.0001 D % 379 3.4Plastic/elastic deformation % 9.5 0.24

Subsurface stresses

Thomas and Hoersh theoryFlat race Groove race

Maximum shear stress N / mm 2 2215 628Shear-pressure stress ratio % 34.16 30.76Depth below the surface mm 0.241 0.158Depth/semiminor axis of ellipsecontact %

47.00 77.00

Lundeberg and Palmgren theoryFlat race Groove race

Maximum amplitude orthogonalshear stress N / mm 2

2774 1018

Shear-pressure stress ratio % 42.78 49.88Depth below the surface mm 0.180 0.102Depth/semiminor axis of ellipsecontact %

35.09 49.63

von Mises distortion energy theoryFlat race Groove race

Maximum octahedral shear stressN / mm 2

3696 1164

Shearpressure stress ratio % 57 57Depth below the surface mm 0.385 0.154Depth/semiminor axis of ellipsecontact %

75 75

Race life prediction

Flat race Groove raceBasic dynamic load rating N 23,556 61,874L10 day 1 18

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structure. The test bearing was positioned between the stationarythrust loading shaft and the rotating disk, which housed thegrooved race. The at race was tted onto the loading shaft in aspecically designed housing. This housing was constructed to

allow for the placement of AE sensors and thermocouples directlyonto the race see Fig. 4 . The thrust shaft was driven by a hy-draulic cylinder Hi-Force Hydraulics Model No. HP110-HANDpump-single speed-working pressure: 700 bars , which movedforward to load the bearing and backward to allow periodicalinspections of the test bearing face. The rotating disk was drivenby a shaft attached to a geared motor with an output speed of

72 rpm. A thrust bearing SKF 81214 TN was placed between thecoupling and the test bearing to react the axial load. A exiblecoupling was employed between the shaft and the geared motor.

3 InstrumentationA schematic of the data acquisition process is detailed in Fig. 3.

The AE acquisition system employed commercially available pi-ezoelectric sensors Physical Acoustic Corporation type PICOwith an operating range of 200750 kHz at temperatures rangingfrom 65C to 177C. Four acoustic sensors, together with twothermocouples RoHS type: J 1 M 455-4371 , were attached tothe back of the at raceway using superglue. One accelerometerEndevco-236-M-ISOEASE-PF44 , attached to the housing of the

at race, was used to measure the vibration in the axial direction.

The acoustic sensors were connected to a data acquisition systemthrough a preamplier, set at 40 dB gain see Figs. 3 and 4 . Thesystem was continuously set to acquire AE wave forms at 2 MHzsampling rate, while AE parameters such as counts, rms, averagesignal level ASL in decibels, maximum amplitude, and absoluteenergy joules were recorded over a time constant of 10 ms and asampling rate of 100 Hz.

4 Experimental Results Observations and Discussions

4.1 Acquisition System Calibration. Prior to testing, calibra-tion tests were undertaken to understand the attenuation propertiesof the test bearing. Attenuation can be described as any reductionor loss in the AE signal strength in the form of amplitude or

intensity , and it is expressed in decibels 12 . In AE applications,attenuation is a very important property because it determines thesignal strength as a function of distance; therefore, it plays a sig-nicant role in specifying locations of AE sensors for purposes of identifying sources of AE events.

Bearing attenuation test was carried out prior to laboratorytests. HsuNielsen sources were used for attenuation tests. Thistest consists of breaking a 0.5 mm diameter pencil lead approxi-mately 3 mm 0.5 mm from its tip by pressing it against thesurface of the piece. Two different approaches to ascertaining at-tenuation were undertaken. The rst involved breaking a 0.5 mmdiameter lead pencil of hardness 2H onto the at raceway directlyadjacent to AE sensors labeled channels 1, 2, 3, and 4 see Fig. 5 .

Table 2 Bearing life calculations for Case II

Input data

Load applied N 35000Number of balls 14Ball radius mm 5.75Race groove radius mm 5.8Mean bearing diameter mm 64Rotational speed rpm 72

Auxiliary quantities

Flat race Groove raceLoad on single ball N 2500 2500Curvature sum mm 0.35 0.18Curvature difference mm 0.00 0.98Dimensionless semimajor axis of contact ellipse a *

1.00 6.31

Dimensionless semiminor axis of contact ellipse b*

1.00 0.32

Dimensionless contact deformation d * 1.00 0.44

Surface stress and deformation

Flat race Groove raceSemimajor axis of the ellipsecontact mm

0.455 3.608

Semiminor axis of the ellipsecontact mm

0.455 0.183

Deformation mm 0.036 0.013Maximum pressure stress N / mm 2 5757 1813Permanent deformation mm 0.0021 0.00000.0001 D mm 0.0012 0.0012Permanent deformation/0.0001 D % 186 2Plastic/elastic deformation % 6 0.1

Subsurface stresses

Thomas and Hoersh theoryFlat race Groove race

Maximum shear stress N / mm 2 1967 558Shear-pressure stress ratio % 34.16 30.76Depth below the surface mm 0.214 0.141Depth/semiminor axis of ellipsecontact %

47 77

Lundeberg and Palmgren theoryFlat race Groove race

Maximum amplitude orthogonalshear stress N / mm 2

2463 904

Shear-pressure stress ratio % 42.78 49.88Depth below the surface mm 0.160 0.091Depth/semiminor axis of ellipsecontact %

35.09 49.63

von Mises distortion energy theoryFlat race Groove race

Maximum octahedral shear stressN / mm 2

3282 1033

Shearpressure stress ratio % 57 57Depth below the surface mm 0.342 0.137Depth/semiminor axis of ellipsecontact %

75 75

Race life prediction

Flat race Groove raceBasic dynamic load rating N 23556 61,874L10 day 3 53

Fig. 2 Test-rig layout

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bearing ring involved breaking lead at another three positions la-beled as midpoints between channels 2 and 3, and channels 3 and4. In-plane tests were also undertaken midpoint between channels

2 and 3. The experimental settings were kept the same as theprevious attenuation test. For these tests, ten lead breaks at eachposition were again performed and the average maximum signalamplitudes and attenuation rate, as described in the rst part, arepresented in Fig. 7. During the test, where the source location wasat the midpoint between channels 2 and 3, channel 2 recorded themaximum signal strength of 0.209 V, while highest attenuationsof 3.13 dB and 3.44 dB were observed at channels 1 and 4, re-spectively see Fig. 7 . It should be noted that the position 3 inFig. 7 is not channel 3 but the midpoint between channels 2 and 3see the gure legend .

4.2 AE Source Location. The capability of AE to determinesource locations of signals emanating in real time from materialsunder load is one of the signicant advantages over other nonde-

structive test NDT technologies. In AE applications, AE signalstraveling through the medium are attenuated and arrive at differentsensors with certain time delay. This delay can be attributed to thedistance between the source defect and AE sensors, and withknowledge of the signal velocity the location of the AE source canbe identied. For this particular investigation efforts were made toidentify the defect location AE source location in real time. Thiswas accomplished by identifying the wave velocity on the ringexperimentally. At a threshold of 52 dB and with known distancesbetween the AE sensors, the velocity of the AE wave form undersuch conditions was calculated at 4000 m / s. This velocity was

Fig. 5 Breaking lead pencil at four different positions

Fig. 6 Relative attenuation at four different positions




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used for all future source locations, and prior to the onset of testing several lead breaks were made at various positions on thesurface to establish the accuracy at this velocity and specicthreshold level. Results were within 4% of the exact geometriclocation of the lead break. Figure 8 shows the source locationlayout used, which essentially unwrapped the bearing race for alinear location

4.3 Bearing Tests. Under normal conditions of load, rota-tional speed, and good alignment, surface damage begins withsubsurface initiation, which gradually propagates to the surface,creating pits and spalls.

During testing, AE parameters were recorded in two modes; therst was a continuous recording of AE absolute energy and rmsacquired at a sampling rate of 100 Hz and over a time constant of

10 ms. The absolute energy is a measure of the true energy and isderived from the integral of the V 2 signal divided by the referenceresistance 10 k over the duration of the AE signal. In addition,traditional AE parameters such as counts, amplitude, and ASLwere also measured. The ASL is a measure of the continuouslyvarying and averaged value of the amplitude of the AE signal indecibels. The ASL is calculated from the rms measurement and isgiven as

ASL dB = 20 log 10 1.4 rms in mV / 100 2

The traditional parameters were calculated over an AE event du-ration of 1500 s and a threshold of 52 dB; the threshold of 52 dB was selected based on numerous rig commissioning tests;at this level a signicant amount of background noise was re-

Fig. 7 Relative attenuation at three different positions

Fig. 8 Source location layout for linear detection




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jected. With almost all tests it was noted that during the rst 2 hof each test AE activity was present, and this was attributed to arunning-in period as after this period 2 h all measured AE andvibration parameters remained constant. For this particular papertwo experimental cases are presented that reect the general ob-servations associated with over 18 experimental tests at loadsranging from 20 kN, 35 kN, and 50 kN. Case I is for a load con-dition of 50 kN, while Case II presents results for a test load of 35 kN.

Case I . Observations of continuous monitoring of the AE lev-els, in addition to traditional AE parameters, for 16 h of bearingoperation are presented in Figs. 9 and 10. At the end of the test16 h there was visible surface damage. It was observed that at

approximately 9 h into operation AE emission levels began to

increase steadily. This was not observed on the vibration measure-ments though vibration levels increased after 13.5 h of operation;much later that was detected by AE reinforcing the widely ac-knowledged view that AE is more sensitive than vibration forbearing defect identication 4 . The increase in AE energy levelsfrom earlier in the test run between 2 h and 6 h to the condition of surface damage was in the order of 10,000%. Figure 10 showstrends of traditional AE parameters all of which show a signicantincrease in AE activity from 9 h of operation.Also worth noting isa small increase in AE levels counts and amplitude at 4 h of operation.

Interestingly observations of the AE wave form, sampled at2 MHz, showed changing characteristics as a function of time.This is presented in Fig. 11 where a typical AE wave form asso-

Fig. 9 Test conditions run until visually observable surface damage, Case I

Fig. 10 Classical AE parameters associated with Case I




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ciated with spurious AE transient events is presented after 4 h of operation. The wave form at 10 h operations shows a periodicityof AE transient bursts at approximately 18 Hz , while at 16 hoperation signicant AE transient events associated with the de-fect frequency 9 Hz of the bearing are clearly noted see Fig.11 . It is particularly interesting to note that the frequency of thetransient event reduced from 18 Hz to 9 Hz from 10 h operationto the end of the test at 16 h . As surface defects, such as spalls,are continually developing, it is postulated that a newly formed

spall will contribute relatively higher AE events as the edges of this newly formed defect will be rougher in comparison to analready existing spall, which becomes smoothened with the pas-sage of time. As such at 16 h operation one of the spalls devel-oped was relatively less mature than others and resulted in highAE levels at the defect frequency. Hence the strong evidence of 9 Hz indicating one defect on the race. This also explains thesharp bursts of AE activity noted during observations of continu-ously monitored AE energy levels see Fig. 9 . Even though theoverall energy levels increase from 9 h operation, relatively largetransient rises were noted during the period from 10 h to 16 h. Itis postulated that these large transient bursts are attributed to re-gions that have newly developed surface damage; this is an evo-lutionary process giving rise to peaks and troughs in AE levels.On termination of the test 16 h a visual inspection revealed sur-face damage at three locations on the race see Fig. 12 .

Thus far the observations have shown AE to monitor the deg-radation of an accelerated test; the next phase of analysis involvedsource identication of AE activity throughout the test duration.Figures 1317 highlight the trends in source location throughoutthe test period; the regions where the surface damage occurredhave been highlighted. The location plots show cumulative energyover the test simulation. It is worth noting that only AE eventsabove a threshold of 52 dB contribute to the source location.Whenever the threshold is exceeded the location of the source iscomputed and identied. The AE energy is assigned to the geo-metric position source ; this is a cumulative process, and as sucha xed source will have the largest contributory energy in a cu-

mulative plot.Evident from these gures was that at the start of the tests Fig.

13 , a concentration of AE source from outside zone 3 195 mmwas noted; this is attributed to the running-in AE activity. At about4 h into operation, relatively early signs of concentrated AE ac-tivity from two of the highlighted zones began to appear see Fig.14 . After 1012 h operation the concentration of the AE sourcewas clearly located at the three highlighted regions see Figs. 15and 16 . At this stage the running-in AE related source opera-tional noise , as seen in Fig. 13, was relatively insignicant.Lastly at 16 h operation the location of the AE sources was lim-ited to the three regions where the actual surface damage hasoccurred see Fig. 17 . These results suggest that the onset of crack development could have been identied as early as 4 h intothe operation of the test bearing.

Case II . This case presents different trends to that noted earlierin Case I; the applied load on this test bearing was 35 kN. Obser-

Fig. 11 AE wave form associated with Case I

Fig. 12 Crack zones on at ring associated with Case I




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Fig. 13 Test running-in stage associated with Case I 1 h operation

Fig. 14 Crack onset stage associated with Case I 4 h operation

Fig. 15 Crack propagation stage associated with Case I 10 h operation




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Fig. 16 Crack propagation stage associated with Case I 12 h operation

Fig. 17 Surface damage locations associated with Case I 16 h operation

Fig. 18 Test conditions run until visually observable surface damage, Case II




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Fig. 19 Classical AE parameters associated with Case II

Fig. 20 AE wave form associated with Case II




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vations of continuous monitoring of the AE levels, in addition totraditional AE parameters, for 18 h of bearing operation are pre-sented in Figs. 18 and 19. At 4 h of operation relatively highlevels of AE activity were noted, particularly the activity associ-ated with AE counts. Also noted on the AE wave form at 4 hoperation was the high transient nature of the wave form. At 6 hoperation the level of AE is reduced to that prior to the increasedAE activity at 4 h see Fig. 18 . The exact reason for this is notknown, but the authors postulate that the generation of early sub-surface or surface damage resulted in AE activity, whichfollowing maturity of the defects worn smooth particularlyaround the edges overtime reduced the AE activity, as ex-plained earlier. This phenomenon had been noted by Al-Dossaryet al. 13 where protrusion at the edge of the articially seededdefects generated high transient AE bursts during the entry andexit only of the roller over the defect.

Again, as in the previous tests the wave form at the end of thetest highlighted a periodicity of AE transient events associated

Fig. 21 Crack zone on at ring associated with Case II

Fig. 22 Test running-in stage associated with Case II 1 h operation

Fig. 23 Crack onset stage associated with Case II 4 h operation




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with the defect frequency of the bearing 9 Hz see Fig. 20 .Interestingly no periodic AE transient event was noted at 10 h of operation; AE transient events remained random. At 18 h of op-eration the test was terminated and there was now visible evidenceof surface damage see Fig. 21 .

Source location deployment used in bearing tests provided an-other simple and rapid means to identify and locate the crack initiation and propagation. As in the previous case the source lo-cation over the duration of the tests is presented in Figs. 2226.Again, the start of the tests shown geometric concentrations of AEactivity that is attributed to the running in condition see Fig. 22 .The other gures show the growing concentration of AE energyfrom the defect location over time, again suggesting that the onsetof cracking could be ascertained as early as 4 h into operation.

It is worth noting that the actual test period leading to visual

damage on the race was much faster than the theoretical calcula-tions. This variation was random but always earlier than predicted.

This is attributed to issues such as misalignment and unbalance,which are not incorporated in theoretical estimates; however, bestefforts were undertaken to minimize this.

5 ConclusionBearing run-to-failure tests under natural damage conditions

were successfully performed. These tests demonstrated the appli-cability of AE in detecting and locating crack initiation and propa-gation on bearing races whilst in operation. The two cases pre-sented are representative of other tests performed in this study andshow that there is a clear correlation between increasing AE en-ergy levels and the natural propagation and formation of bearingdefects. The study demonstrated that AE parameters such as rms

and energy are more reliable, robust, and sensitive to the detectionof incipient cracks and surface spalls in slow speed bearing than

Fig. 24 Crack propagation stage associated with Case II 10 h operation

Fig. 25 Crack propagation stage associated with Case II 14 h operation




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vibration analysis. At the rotational speed on which these testswere employed, this is the rst known attempt at correlating AEand natural defect generation.

References1 Tandon, N., and Choudhury, A., 1999, A Review of Vibration and Acoustic

Measurement Methods for the Detection of Defects in Rolling Element Bear-ings, Tribol. Int., 32 8 , pp. 469480.

2 Jamaludin, N., Mba, D., and Bannister, R. H., 2001, Condition Monitoring of Slow-Speed Rolling Element Bearings Using Stress Waves, Proc. Inst. Mech.Eng., Part E: J. Process Mech. Eng., 215 4 , pp. 245271.

3 Holroyd, T. J., 2001, Condition Monitoring of Very Slowly Rotating Machin-ery Using AE Techniques, 14th International Congress on Condition Moni-toring and Diagnostic Engineering Management , COMADEM 2001 ,Manchester, UK, Sept. 46.

4 Mba, D., and Rao, R. B. K. N., 2006, Development of Acoustic EmissionTechnology for Condition Monitoring and Diagnosis of Rotating Machines:Bearings, Pumps, Gearboxes, Engines, and Rotating Structures, Shock Vib.

Dig., 38, pp. 316.5 Morhain, A., and Mba, D., 2003, Bearing Defect Diagnosis and AcousticEmission, Proc. Inst. Mech. Eng., Part J: J. Eng. Tribol., 217 4 , pp. 257272.

6 Al-Ghamdi, A. M., and Mba, D., 2005, A Comparative Experimental Study on

the Use of Acoustic Emission and Vibration Analysis for Bearing Defect Iden-tication and Estimation of Defect Size , Elsevier Science, New York.

7 Miettinen, J., and Pataniitty, P., 1999, Acoustic Emission in Monitoring Ex-tremely Slowly Rotating Rolling Bearing, Proceedings of 12th InternationalCongress on Condition Monitoring and Diagnostic Engineering Management ,COMADEM 99, England.

8 Choudhury, A., and Tandon, N., 2000, Application of Acoustic EmissionTechnique for the Detection of Defects in Rolling Element Bearings, Tribol.Int., 33 1 , pp. 3945.

9 Price, E. D., Lees, A. W., and Friswell, M. I., 2005, Detection of SevereSliding and Pitting Fatigue Wear Regimes Through the Use of BroadbandAcoustic Emission, Proc. Inst. Mech. Eng., Part J: J. Eng. Tribol., 219 2 , pp.8598.

10 Yoshioka, T., 1992, Detection of Rolling Contact Subsurface Fatigue CracksUsing Acoustic Emission Technique, Lubr. Eng. 49 4 , pp. 303308.

11 Voskamp, A. P., 1985, Material Response to Rolling Contact Loading, Trans.ASME, J. Tribol., 107 3 , pp. 359366.

12 Holroyd, T., 2000, The Acoustic Emission & Ultrasonic Monitoring, 1st ed.,Coxmoor, Oxford, UK.

13 Al-Dossary, S., Raja Hamzah, R. I., and Mba, D., Observations of Changes inAcoustic Emission Waveform for Varying Seeded Defect Sizes in a RollingElement Bearing, Appl. Acoust., in press. Available online March 24, 2008.

Fig. 26 Surface damage location associated with Case II 18 h operation


slow speed rolling element bearing

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