Fault feature extraction of rolling element bearings based on TVD and MSB

被引：0
|
作者：
Zhu D. [1 ]
Zhang Y. [1 ]
Zhao L. [1 ]
Zhu Q. [1 ]
机构：
[1] School of Power Engineering, Naval University of Engineering, Wuhan
来源：
Zhendong yu Chongji/Journal of Vibration and Shock | 2019年 / 38卷 / 08期
关键词：
Fault diagnosis; Modulation signal bispectrum(MSB); Rolling element bearing; Total variation denoising(TVD);
D O I：
10.13465/j.cnki.jvs.2019.08.016
中图分类号：
学科分类号：
摘要：
To solve the problem that the fault features of rolling element bearings are periodic but weak which usually are submerged in strong background noise, a fault diagnosis method based on the second order total variation denoising and modulation signal bispectrum was proposed. Firstly, TVD was applied to original vibration signal while the correlation kurtosis based on envelope spectrum was used as an index to select the optimal parameter λ. Then, the MSB was used to analyze the filtered signal to further suppress the interference of noise, the compound slice spectrum was composed by five selected slices based on index p. Finally, by analyzing the compound slice, the type of bearing fault was determined. The proposed method was applied in simulated and experimental fault signals of rolling element bearings. The results show that the method can reduce the effect of noise to realize accurate diagnosis of bearings' faults. © 2019, Editorial Office of Journal of Vibration and Shock. All right reserved.
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页码：103 / 109and125
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