Remaining Useful Life Prediction of Rolling Element Bearings Based on Different Degradation Stages and Particle Filter

被引：0

作者：

Li Q. ^{[1
]}

Ma B. ^{[1
]}

Liu J. ^{[1
]}

机构：

[1] Beijing Key Laboratory of High End Mechanical Equipment Health Monitoring and Self recovery, Beijing University of Chemical Technology, Beijing

来源：

Transactions of Nanjing University of Aeronautics and Astronautics | 2019年 / 36卷 / 03期

关键词：

Different life stages of state space model; Particle filter; Remaining useful life prediction of rolling element bearing;

D O I：

10.16356/j.1005-1120.2019.03.007

中图分类号：

学科分类号：

摘要：

A method is proposed to improve the accuracy of remaining useful life prediction for rolling element bearings, based on a state space model (SSM) with different degradation stages and a particle filter. The model is improved by a method based on the Paris formula and the Foreman formula allowing the establishment of different degradation stages. The remaining useful life of rolling element bearings can be predicted by the adjusted model with inputs of physical data and operating status information. The late operating trend is predicted by the use of the particle filter algorithm. The rolling bearing full life experimental data validate the proposed method. Further, the prediction result is compared with the single SSM and the Gamma model, and the results indicate that the predicted accuracy of the proposed method is higher with better practicability. © 2019, Editorial Department of Transactions of NUAA. All right reserved.

引用

页码：432 / 441

页数：9