A compound fault feature separation method of rolling bearings based on VMD optimized by the bat algorithm

被引：0
|
作者：
Zhang W. [1 ,2 ]
Ll J. [1 ,2 ]
Chen W. [1 ,2 ]
机构：
[1] College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Taiyuan
[2] National-Joint Engineering Laboratory of Mining Fluid Control, Taiyuan University of Technology, Taiyuan
来源：
Zhendong yu Chongji/Journal of Vibration and Shock | 2022年 / 41卷 / 20期
关键词：
bat algorithm; composite impact index; compound fault diagnosis; variational modal decomposition (VMD);
D O I：
10.13465/j.cnki.jvs.2022.20.017
中图分类号：
学科分类号：
摘要：
Aiming at the problems that the composite fault feature information of a rolling bearing under the interference of strong background noise is difficult to extract, and the parameters in the variational modal decomposition (VMD) need to be determined in advance, a composite fault separation method for a rolling bearing based on VMD optimized by the bat algorithm was proposed. First, a new comprehensive impact index was proposed and compared with existing indicators. The results show that it has increased by 29. 6% to the sensitivity of the fault signal. Then, the minimum average comprehensive influence index was proposed as the objective function, the bat algorithm was used to adaptively search the optimal parameters of VMD, and the signal was decomposed by VMD. Finally, the decomposed modal components were subjected to envelope demodulation analysis, and the fault type of the bearing was judged through the envelope spectrum. The simulation and experimental results show that the method can effectively separate the information of a single fault from the composite fault signal under noise interference, and determine the type of bearing fault, thus the effectiveness of the method is verified. © 2022 Chinese Vibration Engineering Society. All rights reserved.
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页码：133 / 141
页数：8
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