Separation of fault features from a single-channel mechanical signal mixture using wavelet decomposition

Mechanical Systems and Signal Processing

Volumn 21, Issue 5, 2007, Pages 2025-2040

  Hong, Hoonbin ^a   Liang, Ming ^a  

^a UNIVERSITY OF OTTAWA   (Canada)

Author keywords

Mechanical fault feature extraction; Single channel signal separation; Wavelet transform

Indexed keywords

FEATURE EXTRACTION; FOURIER TRANSFORMS; MECHANICAL PROPERTIES; SIGNAL RECONSTRUCTION; WAVELET TRANSFORMS;

MECHANICAL FAULT FEATURE EXTRACTION; MECHANICAL SOURCE SIGNALS; SIGNAL SEPARATION; SINGLE CHANNEL SIGNAL SEPARATION;

FAULT DETECTION;

EID: 34047260285     PISSN: 08883270     EISSN: 10961216     Source Type: Journal    
DOI: 10.1016/j.ymssp.2006.11.001     Document Type: Article

References (26)

1. Gelle G., Colas M., and Delaunay G. Blind sources separation applied to rotating machines monitoring by acoustical and vibrations analysis. Mechanical Systems and Signal Processing 14 (2000) 427-442
2. Li W., Gu F., Ball A., Leung A., and Phipps C. A study of the noise from diesel engines using the independent component analysis. Mechanical Systems and Signal Processing 15 (2001) 1165-1184
3. Cao X., and Liu R. General approach to blind source separation. IEEE Transactions on Signal Processing 44 (1996) 562-571
4. Cichocki A., Thawonmas R., and Amari S. Sequential blind signal extraction in order specified by stochastic properties. Electronics Letters 33 (1997) 64-65
5. Li Y., and Wang J. Sequential blind extraction of instantaneously mixed sources. IEEE Transactions on Signal Processing 50 (2002) 997-1006
6. Antoni J., and Braun S. Editorial. Mechanical Systems and Signal Processing 19 6 (2005) 1163-1165
7. Antoni J. Blind separation of vibration components: principles and demonstrations. Mechanical Systems and Signal Processing 19 6 (2005) 1166-1180
8. Peled R., Braun S., and Zacksenhouse M. A blind deconvolution separation of multiple sources, with application to bearing diagnostics. Mechanical Systems and Signal Processing 19 6 (2005) 1181-1195
9. Bonnardot F., Randall R.B., and Guillet F. Extraction of second-order cyclostationary sources-application to vibration analysis. Mechanical Systems and Signal Processing 19 6 (2005) 1230-1244
10. Boustany R., and Antoni J. A subspace method for the blind extraction of a cyclostationary source: application to rolling element bearing diagnostics. Mechanical Systems and Signal Processing 19 6 (2005) 1245-1259
11. Bouguerriou N., Haritopoulos M., Capdessus C., and Allam L. Novel cyclostationarity-based blind source separation algorithm using second order statistical properties: theory and application to the bearing defect diagnosis. Mechanical Systems and Signal Processing 19 6 (2005) 1260-1281
12. Puigt M., and Deville Y. Time-frequency ratio-based blind separation methods for attenuated and time-delayed sources. Mechanical Systems and Signal Processing 19 6 (2005) 1348-1379
13. Servière C., and Fabry P. Blind source separation of noisy harmonic signals for rotating machine diagnosis. Journal of Sound and Vibration 272 (2004) 317-339
14. Servière C., and Fabry P. Principal component analysis and blind source separation of modulated sources for electro-mechanical systems diagnostic. Mechanical Systems and Signal Processing 19 6 (2005) 1293-1311
15. Roweis S. One microphone source separation. Advances in Neural Information Processing Systems 13 (2001) 793-799
16. Jang G., and Lee T. A maximum likelihood approach to single-channel source separation. Journal of Machine Learning Research 4 (2003) 1365-1392
17. Ertunc H.M., Loparo K.A., and Ocak H. Tool wear condition monitoring in drilling operations using hidden Markov models. International Journal of Machine Tools and Manufacture 41 (2001) 1363-1384
18. Ye J., Zhu X., and Zhang X. Adaptive blind separation with an unknown number of sources. Neural Computation 16 (2004) 1641-1660
19. Goupillaud P., Grossmann A., and Morlet J. Cycle-octave and related transforms in seismic signal analysis. Geoexploration 23 (1984) 85-102
20. Lin J., Zuo M., and Fyfe K. Mechanical fault detection based on the wavelet de-noising technique. Transactions of the ASME Journal of Vibration and Acoustics 126 (2004) 9-16
21. Mathworks, MATLAB Help, 2005.
22. Rioul O., and Duhamel P. Fast algorithms for discrete and continuous wavelet transforms. IEEE Transactions on Information Theory 38 (1992) 569-586
23. Case Western Reserve University bearing data center, 〈http://www.eecs.cwru.edu/laboratory/bearing/welcome_overview.htm〉, 2006.
24. Harris C., and Piersol A. Harris' Shock and Vibration Handbook. fifth ed. (2002), McGraw-Hill, New York, USA
25. Ho D., and Randall R.B. Optimisation of bearing diagnostic techniques using simulated and actual bearing fault signals. Mechanical Systems and Signal Processing 14 5 (2000) 763-788
26. Randall R.B., Antoni J., and Chosbaard S. The relationship between special correlation and envelope analysis in the diagnostics of bearing faults and other cyclostationary machine signals. Mechanical Systems and Signal Processing 15 5 (2001) 945-962