A Fine Spectral Negentropy Method and Its Application to Fault Diagnosis of Rolling Bearing

被引：0
|
作者：
Xu Y. [1 ]
Tian W. [1 ]
Cao J. [1 ]
Ma C. [1 ]
机构：
[1] Institute of Intelligent Monitoring and Diagnosis, Beijing University of Technology, Beijing
来源：
Hsi-An Chiao Tung Ta Hsueh/Journal of Xi'an Jiaotong University | 2019年 / 53卷 / 08期
关键词：
Empirical wavelet transform; Fault feature extraction; Resonant side band; Rolling bearing; Spectral negentropy;
D O I：
10.7652/xjtuxb201908005
中图分类号：
学科分类号：
摘要：
A fine spectral negentropy (ASNE) method based on empirical wavelet transform (EWT) is proposed to solve the problems that it is difficult to determine the central frequency of the resonance sideband and the determination of the bandwidth is susceptible to noise when extracting fault features of rolling bearings. The proposed method constructs a filter bank by using the characteristics of empirical wavelet filter to realize the scanning filter in frequency domain. Then, the filtered components are screened by combining the feature of spectral negentropy in time domain, and it is easier to detect periodic impulse components in signals. The accurate central frequency and bandwidth are obtained after two scanning cycles. Then the optimum fault feature components are extracted through EWT, and the fault feature information of the bearing is finally obtained through envelope demodulation. The method is validated by the experimental signals of inner and outer races of rolling bearing. The results show that the method quickly and accurately determines the central frequency and bandwidth of resonance sideband, and effectively extracts the fault feature information of inner and outer races. The performance is better than that of the Infogram method. The proposed method overcomes the limitation of traditional method in frequency band division and immunity to noise, and extracts the central frequency and bandwidth more accurately. © 2019, Editorial Office of Journal of Xi'an Jiaotong University. All right reserved.
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页码：31 / 39and128
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