The phenomenon of Doppler shift in the acoustic signal acquired by a microphone amounted beside the railway leads to the difficulty for fault diagnosis of train bearings with a high moving speed. To enhance the condition monitoring performance of the bearings on a passing train using stationary microphones, the elimination of the Doppler shift should be implemented firstly to correct the severe frequency-domain distortion of the acoustic signal recorded in these conditions. In this paper, a Doppler shift removal method is proposed based on instantaneous frequency (IF) estimation (IFE) for analyzing acoustic signals from train bearings with a high speed. Specifically, the IFE based on short-time Fourier transform is firstly applied to attain the IF vector. According to the acoustic theory of Morse, the data fitting is then carried out to achieve the fitting IFs with which the resampling sequence can be established as the resampling vector in time domain. The resampled signal can be finally reconstructed to realize fault diagnosis of train bearings. To demonstrate the effectiveness of this method, two simulations and an experiment with practical acoustic signals of train bearings with a crack on the outer raceway and the inner raceway have been carried out, and the comparison results have been presented in this paper.

References

References
1.
Xavier
,
C.
,
Fabrice
,
B.
, and
Jean
,
P. D.
,
2007
, “
Early Detection of Fatigue Damage on Rolling Element Bearings Using Adapted Wavelet
,”
ASME J. Vib. Acoust.
,
129
(
4
), pp.
495
506
.10.1115/1.2748475
2.
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
3.
Yan
,
R.
, and
Gao
,
R. X.
,
2008
, “
Rotary Machine Health Diagnosis Based on Empirical Mode Decomposition
,”
ASME J. Vib. Acoust.
,
130
(
3
), p.
021007
.10.1115/1.2827360
4.
Choe
,
H. C.
,
Wan
,
Y.
, and
Chan
,
A. K.
,
1997
, “
Neural Pattern Identification of Railroad Wheel-Bearing Faults From Audible Acoustic Signals: Comparison of FFT, CWT and DWT Features
,”
SPIE Proc. Wavelet App.
,
3087
, pp.
480
496
.10.1117/12.271772
5.
Irani
,
F. D.
,
2002
, “
Development and Deployment of Advanced Wayside Condition Monitoring Systems
,”
Foreign Rolling Stock
,
39
(
2
), pp.
39
45
.
6.
Barke
,
D.
, and
Chiu
,
W. K.
,
2005
, “
Structural Health Monitoring in the Railway Industry: A Review
,”
Struct. Health Monit.
,
4
, pp.
81
93
.10.1177/1475921705049764
7.
Cline
,
J. E.
, and
Bilodeau
,
J. R.
,
1998
, “
Acoustic Wayside Identification of Freight Car Roller Bearing Defects
,”
ASME/IEEE Joint Railroad Conference
,
Philadelphia, PA
, April 15–16, pp.
79
83
.10.1109/RRCON.1998.668083
8.
Dybała
,
J.
,
Gałęzia
,
A.
, and
Mączak
,
J.
,
2008
, “
Verification of Doppler Effect Removal Method for the Needs of Pass-By Railway Condition Monitoring System
,”
Diagnostyka
,
4
(
48
), pp.
5
8
.
9.
Dybala
,
J.
, and
Radkowski
,
S.
,
2013
, “
Reduction of Doppler Effect for the Needs of Wayside Condition Monitoring System of Railway Vehicles
,”
Mech. Syst. Signal Process
,
38
(
1
), pp.
125
136
.10.1016/j.ymssp.2012.03.003
10.
Yang
,
D.
,
Luo
,
Y.
,
Li
,
B.
,
Li
,
K.
, and
Li
,
X.
,
2010
, “
Acoustic Holography Method for Measuring Moving Sound Source With Correction for Doppler Effect in Time-Domain
,”
Acta Physica Sinica
,
59
(
7
), pp.
4738
4747
.
11.
Morse
,
P. M.
, and
Ingard
,
K. U.
,
1986
,
Theoretical Acoustics (Section 2)
,
Science Press
,
Beijing
, pp.
822
850
.
12.
Xie
,
H.
, and
Wang
,
Z.
,
2006
, “
Mean Frequency Derived Via Hilbert-Huang Transform With Application to Fatigue EMG Signal Analysis
,”
Comput. Methods Prog. Biomed.
,
82
(
2
), pp.
114
120
.10.1016/j.cmpb.2006.02.009
13.
Wang
,
Y.
,
He
,
Z.
, and
Zi
,
Y.
,
2010
, “
A Comparative Study on the Local Mean Decomposition and Empirical Mode Decomposition and Their Applications to Rotating Machinery Health Diagnosis
,”
ASME J. Vib. Acoust.
,
132
(
2
), p.
021010
.10.1115/1.4000770
14.
Beex
,
A. A.
, and
Shan
P.
,
1999
, “
A Time-Varying Prony Method for Instantaneous Frequency Estimation at Low SNR
,”
IEEE International Symposium on Circuits and Systems
(
ISCAS '99
), Orlando, FL, May 30–June 2, Vol.
3
, pp.
5–8
.10.1109/ISCAS.1999.778771
15.
Huang
,
N. E.
,
Wu
,
Z.
,
Long
,
S. R.
,
Arnold
,
K. C
.
,
Chen
,
X.
, and
Blank
,
K.
,
2009
, “
On Instantaneous Frequency
,”
Adv. Adapt. Data Anal.
,
1
(
02
), pp.
177
229
.10.1142/S1793536909000096
16.
Qian
,
S.
,
2005
,
Introduction to Time–Frequency and Wavelet Transforms
,
China Machine Press
,
Beijing
.
17.
Brown
,
D. N.
,
1989
, “
Envelope Analysis Detects Bearing Faults Before Major Damage Occurs
,”
Pulp and Paper
,
63
, pp.
113
117
.
18.
Tse
,
P. W.
,
Peng
,
Y. H.
, and
Yam
,
R.
,
2001
, “
Wavelet Analysis and Envelope Detection for Rolling Element Bearing Fault Diagnosis—Their Effectiveness and Flexibilities
,”
ASME J. Vib. Acoust.
,
123
, pp.
303
310
.10.1115/1.1379745
You do not currently have access to this content.