Method of Bearing Fault Identification Based On SVM Decision Tree

摘要：

　　This paper has put forward one method, combining with theory of decision tree and method of voting, and established one kind of multi-failure classifier of SVM, which could finish cross training, repeated classification and accumulative voting.This classifier could accomplish classification of failure bearings and do classification experiments among failures of kinds of beatings.The results have shown that this method could identify states of breakdown equipment for the purpose of diagnosis of failures of mechanical system accurately.

关键词： Support vector machine bearing multi-failure classifier decision tree

作者: Cheng Hang Li Xi Qin Zheng-bo Huang Chao-young

作者单位: Research Institute of Mechatronic Engineering Taiyuan University of Technology,Taiyuan Shanxi 030024 China

会议类型: 国际会议

会议名称: the 3nd International Conference on Digital Manufacturing & Automation (第三届数字制造与自动化国际会议(ICDMA 2012))

会议地点: 桂林

会议语种:英文

页码: 1010-1015

在线出版日期: 2012-08-01（万方平台首次上网日期，不代表论文的发表时间）