Fault diagnosis method for rolling bearings based on EEMD and autocorrelation function kurtosis

被引：0
|
作者：
Liu Y. [1 ,3 ]
Li C. [1 ]
Liao Y. [2 ,3 ]
机构：
[1] School of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang
[2] School of Civil Engineering, Shijiazhuang Tiedao University, Shijiazhuang
[3] Key Laboratory of Traffic Safety and Control in Heibei, Shijiazhuang
来源：
Zhendong yu Chongji/Journal of Vibration and Shock | 2017年 / 36卷 / 02期
关键词：
Autocorrelation function; Bearing; Coefficient of kurtosis; Fault diagnosis;
D O I：
10.13465/j.cnki.jvs.2017.02.018
中图分类号：
学科分类号：
摘要：
Considering that fault shock signals of rolling bearings have the features of periodicity and easily immerging in background noise, a fault diagnosis method based on the EEMD and autocorrelation function kurtosis was proposed. Bearing fault signal was decomposed by EEMD method, and according to the autocorrelation function kurtosis and the kurtosis criterion, the IMF components, which contain much more fault information, were chosen to reconstruct a new composite signal. By virtue of the spectral kurtosis analysis of the new composite signal, a band-pass filter was designed. The new composite signal was filtered by the band-pass filter, further envelope demodulated and then compared with the theoretical failure frequency. A case study on bearing faults simulations and experiments verifies the effectiveness and feasibility of the method proposed. © 2017, Editorial Office of Journal of Vibration and Shock. All right reserved.
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页码：111 / 116
页数：5
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