Bearing Fault Diagnosis Based on Dual-Tree Complex Wavelet Transform

Abstract:

A novel method of bearing fault diagnosis based on demodulation technique of dual-tree complex wavelet transform (DTCWT) is proposed. It is demonstrated that the proposed dual-tree complex wavelet transform has better shift invariance, reduced frequency aliasing effect and de-noising ability. The bearing fault vibration signal is firstly decomposed and reconstructed using dual-tree complex wavelet transform. Then the real and imaginary parts are obtained and the vibration signal is amplitude demodulated. In the end, the amplitude envelope and wavelet envelope spectrum are computed. Therefore, the character of the bearing fault can be recognized according to the wavelet envelope spectrum. The experimental results show that dual-tree complex wavelet transform can effectively reduce spectral aliasing and fault diagnosis based on dual-tree complex wavelet transform can effectively diagnose bearing inner and outer race fault under strong background noise condition.

• Periodical: Advanced Materials Research (Volumes 490-495)
• Pages: 128-132
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.490-495.128
• Online since: March 2012
• Authors: Hui Li
• Keywords: Amplitude Demodulation, Bearing, Dual-Tree Complex Wavelet Transform, Fault Diagnosis, Signal Processing

References

[1] J. Lin and L. Qu: Feature extraction based on Morlet wavelet and its application for mechanical fault diagnosis, Journal of Sound and Vibration, Vol. 234, No. 1, (2000), pp.135-148.

DOI: 10.1006/jsvi.2000.2864

[2] W.J. Wang, P.D. McFadden: Application of wavelets to gearbox vibration signals for fault detection, Journal of Sound and Vibration, Vol. 192, no. 5, (1996), p.927–939.

DOI: 10.1006/jsvi.1996.0226

[3] Hui Li, Haiqi Zheng, Liwei Tang: Bearing Fault Detection and Diagnosis Based on Teager-Huang Transform. International Journal of Wavelets, Multiresolution and Information Processing, Vol. 7, No. 5, (2009), pp.643-663.

DOI: 10.1142/s0219691309003173

[4] Hui Li, Haiqi Zheng, Liwei Tang: Bearing Fault Detection and Diagnosis Based on Order Tracking and Teager-Huang Transform. Journal of Mechanical Science and Technology, Vol. 24, No. 3, (2010), pp.811-822.

DOI: 10.1007/s12206-009-1211-9

[5] Hui Li, Haiqi Zheng, Liwei Tang: Bearing Fault Diagnosis Based on Amplitude and Phase Map of Hermitian Wavelet Transform. Journal of Mechanical Science and Technology, Vol. 25, No. 11, (2011), pp.2731-2740.

DOI: 10.1007/s12206-011-0717-0

[6] N.G. Kingsbury: The dual-tree complex wavelet transform: a new technique for shift invariance and directional filters, IEEE Digital Signal Processing Workshop, (1998).

[7] I.W. Selesnick, R.G. Baraniuk, N.G. Kingsbury: The dual-tree complex wavelet transform, IEEE Signal Processing Magazine, Vol. 22, No. 6, (2005), p.123–151.

DOI: 10.1109/msp.2005.1550194