Detection of Bearing Outer Race Fault in Induction Motors using Motor Current Signature Analysis

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	Detection of Bearing Outer Race Fault in Induction Motors using Motor Current Signature Analysis
	Song XJ(宋向金)2; Wang ZW(王照伟)2; Hu JT(胡静涛)1
	2019
会议日期	August 11-14, 2019
会议地点	Harbin, China
关键词	induction motor bearing fault stator current signature analysis CEEMDAN
页码	1-5
英文摘要	Bearing damage is the most common fault type in induction motors. In recent years, bearing fault detection based on motor current signature analysis (MCSA) has been gained extensive attention. However, the changes in the stator current signal which is caused by the bearing fault are usually very weak. In order to detect bearing fault effectively, a method for bearing fault detection based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) analysis of motor current signals is proposed. The CEEMDAN is used to decompose the stator current signal into several independent intrinsic mode functions (IMF), then the most sensitive IMF can be extracted. The experimental results show that the proposed approach is effective for bearing outer race fault detection. © 2019 IEEE.
产权排序	2
会议录	2019 22nd International Conference on Electrical Machines and Systems, ICEMS 2019
会议录出版者	IEEE
会议录出版地	New York
语种	英语
ISBN号	978-1-7281-3398-0
WOS记录号	WOS:000537504802029
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/26173]
专题	沈阳自动化研究所_数字工厂研究室
通讯作者	Song XJ(宋向金)
作者单位	1.Chinese Academy of Sciences, Shenyang Institute of Automation, Shenyang 110016, China 2.Jiangsu University, School of Electrical and Information Engineering, Zhenjiang 212013, China
推荐引用方式 GB/T 7714	Song XJ,Wang ZW,Hu JT. Detection of Bearing Outer Race Fault in Induction Motors using Motor Current Signature Analysis[C]. 见:. Harbin, China. August 11-14, 2019.