Rolling Bearing Fault Diagnosis Using Improved Lifting Scheme

Abstract:

Vibration signal carries dynamic information of rotating machinery and the useful information often is corrupted by noise. Effective signal de-noising and feature extraction methods are necessary to analyze these signals. In this paper, an improved lifting scheme is proposed for such vibration signal analysis. The auto-correlation factor of scale decomposition vibration signal is used as to optimize the prediction operator and update operator at each sample point, which can adapt to the vibration signal characteristic. Improved lifting scheme decomposition and reconstruction procedures are designed. Experimental results confirm the advantage of the proposed method over redundant wavelet transform for rolling bearing fault diagnosis, and the typical fault features in time domain are desirably extracted by improved lifting scheme.

• Periodical: Advanced Materials Research (Volumes 518-523)
• Pages: 3780-3783
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.518-523.3780
• Online since: May 2012
• Authors: Hong Kai Jiang, Yi Na He, Chen Dong Duan
• Keywords: Auto-Correlation Factor, Fault Diagnosis, Improved Lifting Scheme, Rolling Bearing, Signal De-Noising

References

[1] Z.J. He, Y.Y. Zi, Q.F. Meng, et al. Fault diagnosis principle of non-stationary signal and applications to mechanical equipment (In Chinese), Higher Education Press, Beijing, (2001).

[2] Y.G. Lei, J. Lin, Z.J He, et al. Application of an improved kurtogram method for fault diagnosis of rolling element bearings, Mechanical Systems and Signal Processing 25 (2011) 1738-1749.

DOI: 10.1016/j.ymssp.2010.12.011

[3] H.Y. Yang, J. Mathew, L. Ma, Fault diagnosis of rolling element bearings using basis pursuit, Mechanical Systems and Signal Processing 19 (2005) 341-356.

DOI: 10.1016/j.ymssp.2004.03.008

[4] W. Sweldens, The lifting scheme: a custom-design construction of biorthogonal wavelets, Applied Computer Harmonic Analysis 3 (2) (1996) 186-200.

DOI: 10.1006/acha.1996.0015

[5] W. Sweldens, The lifting scheme: A construction of second generation wavelets, SIAM Journal of Mathematical Analysis 29 (2) (1997) 511-546.

DOI: 10.1137/s0036141095289051

[6] I. Daubechies and W. Sweldens, Factoring wavelet transform into lifting steps, Journal of Fourier Analysis and Applications 4 (3) (1998) 247-269.

DOI: 10.1007/bf02476026

[7] Z. Li, Z.J. He, Y.Y. Zi, et al, Customized wavelet denoising using intra- and inter-scale dependency for bearing fault detection, Journal of Sound and Vibration 313 (2008) 342-359.

DOI: 10.1016/j.jsv.2007.11.039

[8] C.D. Duan, Z.J. He, H.K. Jiang, A sliding window feature extraction method for rotating machinery based on the lifting scheme, Journal of Sound and Vibration 299 (2007) 774-785.

DOI: 10.1016/j.jsv.2006.07.037

[9] H.K. Jiang, Z.J. He, C.D. Duan, P. Chen. Gearbox Fault Diagnosis Using Adaptive Redundant Lifting Scheme. Mechanical Systems and Signal Processing, 20 (2006): 1992-2006.

DOI: 10.1016/j.ymssp.2005.06.001

[10] G.C.K. Abhayaratne, D.M. Monro, Embedded-to-lossless coding of motion-compensated prediction residuals in lossless video coding, in: Proceedings of Visual Communications and Image Processing, 2001, pp.175-185.

DOI: 10.1117/12.411795

[11] C. Xu, R. Zhao, X. Gan, Wavelet analysis applied algorithm, Science Press, Beijing, (2004).