SVM-PHM : A Novel Method for Remaining Useful Life Prediction

摘要：

The Remaining Useful Life(RUL) prediction of the equipment plays a significant role in maintenance management The accurate RUL prediction based on the current and previous health condition of the equipment is essential to make a timely maintenance decision for failure avoidance. In this paper, we presented a novel RUL forecasting method of Proportional Hazards Model(PHM) assembled with Support Vector Machine(SVM).In this method, we employed SVM to identify abnormal data and regress raw data. A case study is presented, and the performances of RUL prediction of PHM and SVM-PHM are examined.

关键词： proportional hazards model support vector machine remaining useful life outlier detection prediction

作者: Feng Tianle Zhao Jianmin

作者单位: Department of Equipment Command and Management Mechanical Engineering College Shijiazhuang, China

会议类型: 国际会议

会议名称: 2010 International Conference of Informationa Science and Management Engineering(2010年信息科学与管理工程国际学术会议 ISME 2010)

会议地点: 西安

会议语种:英文

页码: 369-372

在线出版日期: 2010-08-07（万方平台首次上网日期，不代表论文的发表时间）