Health stages division and remaining useful life prediction of rolling element bearings based on hidden semi-Markov model

被引：2

作者：

Wu, Hongwei ^{[1
,2
]}

Liu, Zhenxing ^{[1
,2
]}

Zhang, Yong ^{[1
,2
]}

Zheng, Ying ^{[3
]}

Tang, Cong ^{[1
,2
]}

机构：

[1] Wuhan Univ Sci & Technol, Sch Informat Sci & Engn, Wuhan 430081, Peoples R China

[2] Minist Educ, Engn Res Ctr Met Automat & Measurement Technol, Wuhan 430081, Peoples R China

[3] Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Wuhan 430074, Peoples R China

来源：

PROCEEDINGS OF THE 33RD CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2021) | 2021年

基金：

中国国家自然科学基金;

关键词：

Health stages division; Fault occurrence time detection; Remaining useful life prediction; Hidden semi-Markov model; PROGNOSTICS;

D O I：

10.1109/CCDC52312.2021.9601903

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Health stages division and Remaining Useful Life (RUL) prediction are two important parts in safety study of rolling element bearings. In this paper, the Hidden Semi-Markov Model (HSMM) is proposed to divide the degradation stages of rolling element bearings. Firstly, we extract the root mean square feature from the original vibration signal, then utilize Viterbi algorithm to divide the degradation stages. Secondly, Fault occurrence time is determined according to the degradation stage and RUL is predicted with HSMM. In order to verify the effectiveness of this method, IEE-PHM-2012 challenge data sets are adopted and the comparison with the existing methods is carried out.

引用

页码：311 / 316

页数：6

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