Fault Feature Extraction of Rolling Bearings Based on Variational Mode Decomposition and Singular Value Entropy

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	Fault Feature Extraction of Rolling Bearings Based on Variational Mode Decomposition and Singular Value Entropy
	Zhang, Chen; Zhao, Rongzhen; Deng, Linfeng
	2017
页码	296-300
英文摘要	In order to solve the problem that the fault characteristic signals of rolling bearings are weak and the fault identification is relatively difficult, a fault feature extraction method for rolling bearings based on variational mode decomposition singular value entropy is proposed. The original signals are decomposed by variational mode decomposition, and some intrinsic modal functions are obtained to form the initial characteristic matrix. Then, the singular value decomposition technique is used to process the initial characteristic matrix and the singular value entropy is obtained by combining the information entropy theory. Finally, according to the magnitude of the singular value entropy, the working states and fault types of rolling bearings are distinguished. The results show that this method can classify the weak faults of rolling bearings more clearly and has higher fault identification accuracy.
会议录	2ND INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND INDUSTRIAL AUTOMATION (ICITIA 2017)
会议录出版者	DESTECH PUBLICATIONS, INC
会议录出版地	439 DUKE STREET, LANCASTER, PA 17602-4967 USA
语种	英语
WOS研究方向	Automation & Control Systems ; Computer Science ; Engineering ; Robotics
WOS记录号	WOS:000426968200043
内容类型	会议论文
源URL	[http://119.78.100.223/handle/2XXMBERH/36259]
专题	机电工程学院
通讯作者	Zhang, Chen
作者单位	Lanzhou Univ Technol, Lanzhou 730050, Gansu, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Chen,Zhao, Rongzhen,Deng, Linfeng. Fault Feature Extraction of Rolling Bearings Based on Variational Mode Decomposition and Singular Value Entropy[C]. 见:.