Rolling Bearing Fault Diagnosis Method based on EEMD Permutation Entropy and Fuzzy Clustering

摘要：

　　In order to improve the precision of rolling bearing fault diagnosis,this paper puts forward a method for rolling bearing fault diagnosis based on EEMD permutation entropy and fuzzy clustering.Firstly,it sets normal and damage acoustic emission signals of rolling bearing inner ring by using EEMD algorithm,to obtain several intrinsic mode function(IMF) components,and then extracts the permutation entropy as the signal eigenvalue in sensitive IMF of reflecting signal characteristic,then it can conduct the fault identification and classification in fuzzy clustering analysis.The experimental results show that the method can be effectively applied to rolling bearing fault diagnosis,and it has higher diagnosis accuracy.

关键词： rolling bearing fault diagnosis,EEMD permutation entropy fuzzy clustering

作者: Long Han Chengwei Li Liwei Zhan Xiaoli Li

作者单位: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin,HeiLongJiang School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin,HeiLongJiang

会议类型: 国际会议

会议名称: 2015 Fifth International Conference on Instrumentation and Measurement,Computer,Communication and Control (IMCCC2015)(第五届仪器测量、计算机通信与控制国际会议)

会议地点: 秦皇岛

会议语种:英文

页码: 470-474

在线出版日期: 2015-09-18（万方平台首次上网日期，不代表论文的发表时间）