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 P(陈鹏)1; Zhao XQ(赵小强)1,2,3
	2021-07-15
发表期刊	Zhendong yu Chongji/Journal of Vibration and Shock
ISSN	10003835
卷号	40 期号:13 页码:146-153
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.
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
DOI	10.13465/j.cnki.jvs.2021.13.019
收录类别	EI
语种	中文
出版者	Chinese Vibration Engineering Society
EI入藏号	20213110707021
EI主题词	Roller bearings
EI分类号	601.2 Machine Components ; 716.1 Information Theory and Signal Processing ; 802.3 Chemical Operations
引用统计	无
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/150950
专题	电气工程与信息工程学院
通讯作者	Zhao XQ(赵小强)
作者单位	1.兰州理工大学电气工程与信息工程学院; 2.甘肃省工业过程先进控制重点实验室; 3.兰州理工大学国家级电气与控制工程实验教学中心
第一作者单位	电气工程与信息工程学院
通讯作者单位	电气工程与信息工程学院; 兰州理工大学
第一作者的第一单位	电气工程与信息工程学院
推荐引用方式 GB/T 7714	Chen P,Zhao XQ. 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	陈鹏,&赵小强.(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	陈鹏,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.