Fault diagnosis method of rolling bearing based on CLMD and CSES

被引：0
|
作者：
Huang C. [1 ]
Song H. [1 ]
Qin N. [2 ]
Chen X. [1 ]
Chai P. [1 ]
机构：
[1] School of Mechanical and Electrical Engineering, Zhengzhou Institute of Technology, Zhengzhou
[2] School of Electrical Engineering, Southwest Jiaotong University, Chengdu
来源：
Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2020年 / 40卷 / 08期
基金：
中国国家自然科学基金;
关键词：
Complex Fourier transform; Complex local mean decomposition; Complex signal envelope spectrum; Early failure; Fault diagnosis; Rolling bearing;
D O I：
10.16081/j.epae.202006016
中图分类号：
学科分类号：
摘要：
A novel fault diagnosis method of rolling bearing based on CLMD(Complex Local Mean Decomposition) and CSES(Complex Signal Envelope Spectrum) is proposed. Firstly, the vibration signals in two directions are collected by the acceleration sensors installed perpendicularly to each other and combined into a complex signal. Then the complex signals are adaptively decomposed by CLMD, and the real and imaginary envelope signals obtained from the complex signal are combined into a complex envelope signal. According to the amplitude enhancement and composite frequency feature of complex Fourier transform, the complex Fourier transform is directly applied to the complex envelope signal, and the extracted fault characteristic frequency is clearer. By the outer ring fault experiment in different position of rolling bearing, it is proved that the proposed method can enhance the fault feature and can be used to diagnose weak faults and compound faults of rolling bearing. © 2020, Electric Power Automation Equipment Press. All right reserved.
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页码：179 / 183
页数：4
相关论文
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