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Shock and Vibration
Volume 2017 (2017), Article ID 6106103, 9 pages
https://doi.org/10.1155/2017/6106103
Research Article

A Spectrum Detection Approach for Bearing Fault Signal Based on Spectral Kurtosis

School of Mechanical Engineering, Harbin Institute of Technology, Harbin, China

Correspondence should be addressed to Liqin Wang; nc.ude.tih@gnawql

Received 2 August 2016; Revised 9 November 2016; Accepted 4 December 2016; Published 19 February 2017

Academic Editor: Angelo M. Tusset

Copyright © 2017 Yunfeng Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

According to the similarity between Morlet wavelet and fault signal and the sensitive characteristics of spectral kurtosis for the impact signal, a new wavelet spectrum detection approach based on spectral kurtosis for bearing fault signal is proposed. This method decreased the band-pass filter range and reduced the wavelet window width significantly. As a consequence, the bearing fault signal was detected adaptively, and time-frequency characteristics of the fault signal can be extracted accurately. The validity of this method was verified by the identifications of simulated shock signal and test bearing fault signal. The method provides a new understanding of wavelet spectrum detection based on spectral kurtosis for rolling element bearing fault signal.