Envelope Analysis of Gear Faults Based on Spectral Kurtosis

Abstract:

An improved envelope analysis approach based on spectral kurtosis (SK) and complex shifted Morlet wavelet in the diagnostics of local gear faults is proposed in this paper. For enhancing impact signals of gear faults, a prewhitting process is performed to the original signals by autoregressive (AR) models firstly in the approach. Then, the envelopes of signals are extracted by Morlet wavelet filter family and the optimal center frequency and bandwidth of the band-pass filters is determined by SK. In the improved approach, not only the optimal parameters of the band-pass filters in envelope analysis can be obtained adaptively by, but also the number of the required band-pass filters can be reduced dramatically. Simulation results verified the feasibility of the present scheme positively.

• Periodical: Key Engineering Materials (Volumes 474-476)
• Pages: 1626-1631
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.474-476.1626
• Online since: April 2011
• Authors: Ting Wei Liu, Yu Guo, Bin Li, Yan Chun Ding, Hua Wen Zheng
• Keywords: AR Modal, Complex Shifted Morlet Wavelet, Envelope Analysis, Gear Local Fault, Spectral Kurtosis

References

[1] Wenyi. Wang: Early detection of gear tooth cracking using the resonance demodulation technique. Mech. Syst. Sign. Proc. Vol. 15 (2001), pp.887-903.

DOI: 10.1006/mssp.2001.1416

[2] N.G. Nikolaou and I.A. Antoniadis: Demodulation of vibration signals generated by defects in rolling element bearings using complex shifted morlet wavelets. Mech. Syst. Sign. Proc., Vol. 16 (2002), pp.677-694.

DOI: 10.1006/mssp.2001.1459

[3] N. Sawalhi, R.B. Randall and H. Endo: The enhancement of fault detection and diagnosis in rolling element bearings using minimum entropy deconvolution combined with spectral kurtosis. Mech. Syst. Sign. Proc., Vol. 21 (2007), pp.2616-2633.

DOI: 10.1016/j.ymssp.2006.12.002

[4] H. Endo and R.B. Randall: Enhancement of autoregressive model based gear tooth fault detection technique by the use of minimum entropy deconvolution filter. Mech. Syst. Sign. Proc., Vol. 21 (2007), pp.906-919.

DOI: 10.1016/j.ymssp.2006.02.005

[5] F. Combet and L. Gelman: Optimal filtering of gear signals for early damage detection based on the spectral kurtosis. Mech. Syst. Sign. Proc., Vol. 23 (2009), pp.652-668.

DOI: 10.1016/j.ymssp.2008.08.002

[6] N. Sawalhi and R.B. Randall: Spectral kurtosis optimization for rolling element bearings. ISSPA Conference, Sydney, Australia, August (2005).

DOI: 10.1109/isspa.2005.1581069

[7] W. Wang and A.K. Wong: Autoregressive model-based gear fault diagnosis. J. Vibr. Acoust. Vol. 124 (2002), pp.172-179.