For years, vibration analysis has been the industry standard for bearing fault diagnosis. However, due to the various advantages over vibration based techniques, the quantification of acoustic emission (AE) for bearing health diagnosis has been an area of interest for recent years. Additionally, most AE based methodologies to date utilize data mining technologies. Presented in this paper is a new approach, combining a heterodyne based frequency reduction technique, time synchronous resampling, and spectral averaging to process AE signals and compute condition indicators (CIs) for bearing fault diagnostics. First, the heterodyne based frequency reduction technique allows the AE signal frequency to be down shifted from several MHz to less than 50 kHz, which approaches that of vibration based methodologies. Next, the sampled AE signals are band pass filtered to retain the useful information related to the bearing defects. Last, a trigger signal is utilized to time synchronously resample the AE signals to allow the calculation of a spectral average and the extraction and evaluation of CIs for bearing fault diagnosis. The technique presented in this paper is validated using the AE signals of seeded fault steel bearings on a bearing test rig. Presented is an effective AE based approach validated to diagnose all four fault types: inner race, outer race, ball, and cage. Moreover, the effectiveness of the presented approach is established through the comparison of both AE and vibration data.

References

References
1.
Applied Industrial Technologies
,
2009
, “
Lubricant Failure = Bearing Failure
,” Machinery Lubrication, January, http://www.machinerylubrication.com/Read/1863/lubricant-failure
2.
Tse
,
P.
,
Peng
,
Y.
, and
Yam
,
R.
,
2001
, “
Wavelet Analysis and Envelope Detection for Rolling Element Bearing Fault Diagnosis—Their Effectiveness and Flexibilities
,”
ASME J. Vib. Acoust.
,
123
(
3
), pp.
303
310
.10.1115/1.1379745
3.
Yan
,
R.
,
Gao
,
R.
, and
Wang
,
C.
,
2009
, “
Experimental Evaluation of a Unified Time-Scale-Frequency Technique for Bearing Defect Feature Extraction
,”
ASME J. Vib. Acoust.
,
131
(
4
), p.
041012
.10.1115/1.3147125
4.
Lei
,
Y.
,
He
,
Z.
, and
Zi
,
Y.
,
2008
, “
Application of a Novel Hybrid Intelligent Method to Compound Fault Diagnosis of Locomotive Roller Bearings
,”
ASME J. Vib. Acoust.
,
130
(
3
), p.
034501
.10.1115/1.2890396
5.
He
,
Q.
,
Li
,
P.
, and
Kong
,
F.
,
2012
, “
Rolling Bearing Localized Defect Evaluation by Multiscale Signature Via Empirical Mode Decomposition
,”
ASME J. Vib. Acoust.
,
134
(
6
), p.
061013
.10.1115/1.4006754
6.
Wei
,
D.
, and
Zhan-Sheng
,
L.
,
2009
, “
Genetic Integration of Different Diagnosis Methods and/or Fault Features for Improvement of Diagnosis Accuracy
,”
ASME J. Vib. Acoust.
,
131
(
1
), p.
011002
.10.1115/1.2980379
7.
Kappaganthu
,
K.
, and
Nataraj
,
C.
,
2011
, “
Feature Selection for Fault Detection in Rolling Element Bearings Using Mutual Information
,”
ASME J. Vib. Acoust.
,
133
(
6
), p.
061001
.10.1115/1.4003400
8.
Zhang
,
Y.
,
Liang
,
M.
,
Li
,
C.
, and
Hou
,
S.
,
2013
, “
A Joint Kurtosis-Based Adaptive Bandstop Filtering and Iterative Autocorrelation Approach to Bearing Fault Detection
,”
ASME J. Vib. Acoust.
,
135
(
5
), p.
051026
.10.1115/1.4024610
9.
Hou
,
S.
,
Li
,
Y.
,
Wang
,
Z.
, and
Liang
,
M.
,
2010
, “
A New Low-Frequency Resonance Sensor for Low Speed Roller Bearing Monitoring
,”
ASME J. Vib. Acoust.
,
132
(
1
), p.
014502
.10.1115/1.4000773
10.
Morhain
,
A.
, and
Mba
,
D.
,
2003
, “
Bearing Defect Diagnosis and Acoustic Emission
,”
Proc. Inst. Mech. Eng., Part J.
,
217
(
4
), pp.
257
272
.10.1243/135065003768618614
11.
Mba
,
D.
,
2008
, “
The Use of Acoustic Emission for Estimation of Bearing Defect Size
,”
J. Failure Anal. Prev.
,
8
(
2
), pp.
188
192
.10.1007/s11668-008-9119-8
12.
Nienhaus
,
K.
,
Boos
,
F. D.
,
Garate
,
K.
, and
Baltes
,
R.
,
2012
, “
Development of Acoustic Emission (AE) Based Defect Parameters for Slow Rotating Roller Bearings
,”
J. Phys.: Conf. Ser.
,
364
(
1
), p.
012034
.10.1088/1742-6596/364/1/012034
13.
He
,
Y.
, and
Zhang
,
X.
,
2012
, “
Approximate Entropy Analysis of the Acoustic Emission From Defects in Rolling Element Bearings
,”
ASME J. Vib. Acoust.
,
134
(
6
), p.
061012
.10.1115/1.4007240
14.
Yoshioka
,
T.
, and
Fujiwara
,
T.
,
1982
, “
A New Acoustic Emission Source Locating System for the Study of Rolling Contact Fatigue
,”
Wear
,
81
(
1
), pp.
183
186
.10.1016/0043-1648(82)90314-3
15.
Mba
,
D.
, and
Rao
,
R.
,
2006
, “
Development of Acoustic Emission Technology for Condition Monitoring and Diagnosis of Rotating Machines; Bearings, Pumps, Gearboxes, Engines and Rotating Structures
,”
Shock Vib. Dig.
,
38
(
1
), pp.
3
16
.
16.
He
,
Y.
,
Zhang
,
X.
, and
Friswell
,
M.
,
2009
, “
Defect Diagnosis for Rolling Element Bearings Using Acoustic Emission
,”
ASME J. Vib. Acoust.
,
131
(
6
), p.
061012
.10.1115/1.4000480
17.
Qu
,
Y.
,
He
,
D.
,
Yoon
,
J.
,
Van Hecke
,
B.
,
Bechhoefer
,
E.
, and
Zhu
,
J.
,
2014
, “
Gearbox Tooth Cut Fault Diagnostics Using Acoustic Emission and Vibration Sensors—A Comparative Study
,”
Sensors
,
14
(
1
), pp.
1372
1393
.10.3390/s140101372
18.
Shiroishi
,
J.
,
Li
,
Y.
,
Liang
,
S.
,
Kurfess
,
T.
, and
Danyluk
,
S.
,
1997
, “
Bearing Condition Diagnosis Via Vibration and Acoustic Emission Measurements
,”
Mech. Syst. Signal Process.
,
11
(
5
), pp.
693
705
.10.1006/mssp.1997.0113
19.
Felten
,
D.
,
2003
, “
Understanding Bearing Vibration Frequencies
,”
Electrical Apparatus Service Association (EASA), St. Louis, MO
.
20.
McFadden
,
P. D.
,
1987
, “
A Revised Model for the Extraction of Periodic Waveforms by Time Domain Averaging
,”
Mech. Syst. Signal Process.
,
1
(
1
), pp.
83
95
.10.1016/0888-3270(87)90085-9
21.
McFadden
,
P. D.
,
1991
, “
A Technique for Calculating the Time Domain Averages of the Vibration of the Individual Planet Gears and the Sun Gear in an Epicyclic Gearbox
,”
J. Sound Vib.
,
144
(
1
), pp.
163
172
.10.1016/0022-460X(91)90739-7
22.
McFadden
,
P. D.
, and
Toozhy
,
M. M.
,
2000
, “
Application of Synchronous Averaging to Vibration Monitoring of Rolling Element Bearings
,”
Mech. Syst. Signal Process.
,
14
(
6
), pp.
891
906
.10.1006/mssp.2000.1290
23.
Siegel
,
D.
,
Al-Atat
,
H.
,
Shauche
,
V.
,
Liao
,
L.
,
Snyder
,
J.
, and
Lee
,
J.
,
2012
, “
Novel Method for Rolling Element Bearing Health Assessment—A Tachometer-Less Synchronously Averaged Envelope Feature Extraction Technique
,”
Mech. Syst. Signal Process.
,
29
(
1
), pp.
362
376
.10.1016/j.ymssp.2012.01.003
24.
Braun
,
S.
,
1975
, “
The Extraction of Periodic Waveforms by Time Domain Averaging
,”
Acustica
,
32
(2), pp.
69
77
.
25.
Bonnardot
,
F.
,
El Badaoui
,
M.
,
Randall
,
R. B.
,
Daniere
,
J.
, and
Guillet
,
F.
,
2005
, “
Use of the Acceleration Signal of a Gearbox in Order to Perform Angular Resampling (With Limited Speed Fluctuation)
,”
Mech. Syst. Signal Process.
,
19
(
4
), pp.
766
785
.10.1016/j.ymssp.2004.05.001
26.
Bechhoefer
,
E.
,
2013
, “
An Enhanced Time Synchronous Averaging for Rotating Equipment Analysis
,”
Joint Conference: Machinery Failure Prevention Technology 2013 and ISA's 59th International Instrumentation Symposium
, Cleveland, OH, May 13–17, pp. 149–158.
27.
Qu
,
Y.
,
Bechhoefer
,
E.
,
He
,
D.
, and
Zhu
,
J.
,
2013
, “
A New Acoustic Emission Sensor Based Gear Fault Detection Approach
,”
Int. J. Prognostics Health Manage.
,
4
(Sp. 2), pp.
1
14
.
28.
Christian
,
K. N.
,
Mureithi
,
N.
,
Lakis
,
A.
, and
Thomas
,
M.
,
2007
, “
On the Use of Synchronous Averaging, Independent Component Analysis and Support Vector Machines for Bearing Fault Diagnosis
,”
First International Conference on Industrial Risk Engineering
, Montreal, QC, Canada, Dec. 17–19, pp. 610–624.
29.
Bechhoefer
,
E.
, and
Kingsley
,
M.
,
2009
, “
A Review of Time Synchronous Average Algorithms
,”
Annual Conference of the Prognostics and Health Management Society
, San Diego, CA, Sept. 27–Oct. 1, pp. 24–33.
30.
Bechhoefer
,
E.
,
Van Hecke
,
B.
, and
He
,
D.
,
2013
, “
Processing for Improved Spectral Analysis
,”
Annual Conference of the Prognostics and Health Management Society
, New Orleans, LA, Oct. 14–17, pp.
33
38
.
31.
Welch
,
P.
,
1967
, “
The Use of Fast Fourier Transform for the Estimation of Power Spectra: A Method Based on Time Averaging Over Short, Modified Periodograms
,”
IEEE Trans. Audio Electroacoust.
,
15
(
2
), pp.
70
73
.10.1109/TAU.1967.1161901
32.
He
,
D.
,
Li
,
R.
,
Zhu
,
J.
, and
Zade
,
M.
,
2011
, “
Data Mining Based Full Ceramic Bearing Fault Diagnostic System Using AE Sensors
,”
IEEE Transactions on Neural Networks
,
22
(
12
), pp.
2022
2031
.10.1109/TNN.2011.2169087
33.
Teager
,
H. M.
, and
Teager
,
S. M.
,
1992
, “
Evidence for Nonlinear Sound Production Mechanisms in the Vocal Tract
,”
Speech Production and Speech Modeling
, Springer, Dordrecht, The Netherlands, pp. 241–261.
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