Gearbox fault diagnosis using independent component analysis in the frequency domain and wavelet filtering

We combine independent component analysis in the frequency domain (ICA-FD) and Morlet wavelet filtering for gearbox fault diagnosis. Collected vibration signals from a gearbox are separated into two components with ICA-FD. Morlet wavelet filtering is then applied to the separated components. The opt...

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Main Authors: Xinhao Tian, Jing Lin, Fyfe, K.R., Zuo, M.J.
Format: Conference Proceeding
Language:English
Subjects:
Blind source separation
Fault diagnosis
Filtering
Frequency domain analysis
Independent component analysis
Signal processing
Source separation
Vibrations
Wavelet analysis
Wavelet domain
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Jing Lin
Fyfe, K.R.
Zuo, M.J.
description We combine independent component analysis in the frequency domain (ICA-FD) and Morlet wavelet filtering for gearbox fault diagnosis. Collected vibration signals from a gearbox are separated into two components with ICA-FD. Morlet wavelet filtering is then applied to the separated components. The optimal shape parameter, /spl beta/, of the basic Morlet wavelet is obtained by minimizing the wavelet entropy. Better diagnosis results are obtained with this combination than using wavelet filtering alone.
doi_str_mv 10.1109/ICASSP.2003.1202340
format conference_proceeding
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identifier ISSN: 1520-6149
ispartof 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03), 2003, Vol.2, p.II-245
issn 1520-6149
2379-190X
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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Blind source separation
Fault diagnosis
Filtering
Frequency domain analysis
Independent component analysis
Signal processing
Source separation
Vibrations
Wavelet analysis
Wavelet domain
title Gearbox fault diagnosis using independent component analysis in the frequency domain and wavelet filtering
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