The Statistical Data-driven Remaining Useful Life Prediction-A Review on the Wiener Process-based Method

被引:3
|
作者
Guan, Qingluan [1 ]
Wei, Xiukun [2 ]
机构
[1] Beijing Jiaotong Univ, Sch Traff & Transportat, Beijing, Peoples R China
[2] Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing, Peoples R China
基金
国家重点研发计划;
关键词
remaining useful life; reliability; uncertainty; Wiener process; HEALTH MANAGEMENT; DEGRADATION; GAMMA; MODEL; DISTRIBUTIONS; PROGNOSTICS;
D O I
10.1109/PHM58589.2023.00020
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Prognostics and health management (PHM) is a core technology in the domain of reliability, and it has got extensive acclamation and application. The statistical data-driven method prediction method has become a popular hotspot of research in recent years since it only considers the condition monitoring data and relevant degradation information. As one of the data-driven remaining useful life (RUL) prediction methods, the Wiener process-based method is commonly used. Considering the uncertainty existing in the degradation process for the equipment or device, this paper summarizes the statistical data-driven method and focuses on the Wiener process-based method. Finally, some urgent issues to be addressed in the future are discussed.
引用
收藏
页码:64 / 68
页数:5
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