Early fault feature extraction of rolling bearing based on optimized VMD and improved threshold denoising

doi:10.13465/j.cnki.jvs.2021.13.019

	Early fault feature extraction of rolling bearing based on optimized VMD and improved threshold denoising
	Chen, Peng 1; Zhao, Xiaoqiang 1,2,3
刊名	Zhendong yu Chongji/Journal of Vibration and Shock
	2021-07-15
卷号	40 期号:13 页码:146-153
关键词	Extraction Feature extraction Signal processing Spectrum analysis Adaptive decomposition Correlation coefficient Fault feature extractions Mode decomposition Optimization algorithms Optimization method Teager energy operators Threshold de-noising
ISSN号	10003835
DOI	10.13465/j.cnki.jvs.2021.13.019
英文摘要	Aiming at the problem of early fault signals of rolling bearing being weak to cause fault feature extraction being difficult under complex working conditions and strong background noise interference, a method of rolling bearing fault feature extraction based on optimized variational mode decomposition (VMD) and improved threshold denoising was proposed. Firstly, VMD was optimized using the whale optimization algorithm (WOA) to realize the adaptive decomposition of vibration signal, and the optimal modal components selection criteria for L-kurtosis and correlation coefficient were established. Then, the improved threshold denoising was performed on the selected optimal components. Finally, Hilbert envelope spectral analysis was performed on the de-noised signals to realize fault feature frequency extraction. The proposed method was verified to adopt simulated signals and the engineering data set of University of Western Reserve in US. At the same time, the proposed method was compared with Teager energy operator denoising method and the optimization method based on envelope entropy criterion. The results showed that the effect of the proposed method is better. © 2021, Editorial Office of Journal of Vibration and Shock. All right reserved.
语种	中文
出版者	Chinese Vibration Engineering Society
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/150950]
专题	电气工程与信息工程学院
作者单位	1.College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou; 730050, China; 2.National Experimental Teaching Center of Electrical and Control Engineering, Lanzhou; 730050, China 3.Gansu Provincial Key Lab of Advanced Control for Industrial Processes, Lanzhou; 730050, China;
推荐引用方式 GB/T 7714	Chen, Peng,Zhao, Xiaoqiang. Early fault feature extraction of rolling bearing based on optimized VMD and improved threshold denoising[J]. Zhendong yu Chongji/Journal of Vibration and Shock,2021,40(13):146-153.
APA	Chen, Peng,&Zhao, Xiaoqiang.(2021).Early fault feature extraction of rolling bearing based on optimized VMD and improved threshold denoising.Zhendong yu Chongji/Journal of Vibration and Shock,40(13),146-153.
MLA	Chen, Peng,et al."Early fault feature extraction of rolling bearing based on optimized VMD and improved threshold denoising".Zhendong yu Chongji/Journal of Vibration and Shock 40.13(2021):146-153.