Impulse Response Wavelet Transform Based Bearing Fault Diagnosis

Hui Li

doi:10.4028/www.scientific.net/AMR.204-210.1018

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 204-210Impulse Response Wavelet Transform Based Bearing...

Impulse Response Wavelet Transform Based Bearing Fault Diagnosis

Abstract:

The continuous wavelet transform enables one to look at the evolution in the time frequency joint representation plane. This advantage makes it very suitable for the detection of singularity generated by localized defects in mechanical system. This gives a desirable ability to detect the singularity characteristic of a signal precisely. In this study, the impulse response wavelet time frequency joint representation is used in conjunction to detect and diagnose the bearing fault. The impulse response wavelet time frequency joint representation is found to show distinctive signatures in the presence of bearing inner race or outer race damage. The experimental results show that the impulse response wavelet time frequency representation can extract the transients from strong noise signals and can effectively diagnose bearing fault.

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Periodical:

Advanced Materials Research (Volumes 204-210)

Pages:

1018-1021

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.204-210.1018

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Online since:

February 2011

Authors:

Hui Li

Keywords:

Bearing, Fault Diagnosis, Impulse Response Wavelet, Signal Processing, Time Frequency Distribution

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References

[1] R. Rubini and U. Meneghetti: Mechanical Systems and Signal Processing, Vol. 15, No. 2 (2001), pp.287-302.

Google Scholar

[2] N.G. Nikolaou and I.A. Antoniadis: Mechanical Systems and Signal Processing, Vol. 16, No. 4 (2002), pp.677-694.

Google Scholar

[3] J. Lin and L. Qu: Journal of Sound and Vibration, Vol. 234, No. 1 (2000), pp.135-148.

Google Scholar

[4] W.J. Wang: Mechanical Systems and Signal Processing, Vol. 15, No. 4, (2001) p.685–696.

Google Scholar

[5] J. Lin and M.J. Zuo: Mechanical Systems and Signal Processing, Vol. 17, No. 6 (2003), p.1259–1269.

Google Scholar

[6] D. Moulahbal, M. farid Golnaraghi, F. Ismail: Mechanical Systems and Signal Processing, Vol. 13, No. 3 (1999), p.423–436.

Google Scholar

[7] W.J. Wang, P.D. McFadden: Mechanical Systems and Signal Processing, Vol. 9, No. 5 (1995), p.497–507.

Google Scholar

[8] W.J. Wang, P.D. McFadden: Journal of Sound and Vibration, Vol. 192, No. 5 (1996), p.927–939.

Google Scholar

[9] Hui Li, Yuping Zhang, Haiqi Zheng: Journal of Mechanical Science and Technology, Vol. 23, No. 2 (2009), pp.291-301.

Google Scholar

[10] Hui Li, Haiqi Zheng, Liwei Tang: International Journal of Wavelets, Multiresolution and Information Processing, Vol. 7, No. 5 (2009), pp.643-663.

Google Scholar

[11] Hui Li, Haiqi Zheng, Liwei Tang: Journal of Mechanical Science and Technology, Vol. 24, No. 3 (2010), pp.811-822.

Google Scholar