Remaining useful life estimation - A review on the statistical data driven approaches

被引:1436
|
作者
Si, Xiao-Sheng [1 ,3 ]
Wang, Wenbin [2 ,4 ,5 ]
Hu, Chang-Hua [1 ]
Zhou, Dong-Hua [3 ]
机构
[1] Xian Inst Hitech, Dept Automat, Xian 710025, Shaanxi, Peoples R China
[2] Univ Salford, Salford Business Sch, Salford M5 4WT, Lancs, England
[3] Tsinghua Univ, Dept Automat, TNLIST, Beijing 100084, Peoples R China
[4] Beijing Univ Sci & Technol, Sch Econ & Management, Beijing, Peoples R China
[5] City Univ Hong Kong, PHM Ctr, Hong Kong, Hong Kong, Peoples R China
基金
英国工程与自然科学研究理事会;
关键词
Maintenance; Remaining useful life; Brown motion; Stochastic filtering; Proportional hazards model; Markov; CONDITION-BASED MAINTENANCE; SEMI-MARKOV MODEL; PROPORTIONAL HAZARDS MODEL; INVERSE GAUSSIAN DISTRIBUTION; EQUIPMENT HEALTH DIAGNOSIS; OPTIMAL BURN-IN; RESIDUAL-LIFE; ACCELERATED DEGRADATION; THRESHOLD REGRESSION; PREVENTIVE MAINTENANCE;
D O I
10.1016/j.ejor.2010.11.018
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Remaining useful life (RUL) is the useful life left on an asset at a particular time of operation. Its estimation is central to condition based maintenance and prognostics and health management. RUL is typically random and unknown, and as such it must be estimated from available sources of information such as the information obtained in condition and health monitoring. The research on how to best estimate the RUL has gained popularity recently due to the rapid advances in condition and health monitoring techniques. However, due to its complicated relationship with observable health information, there is no such best approach which can be used universally to achieve the best estimate. As such this paper reviews the recent modeling developments for estimating the RUL. The review is centred on statistical data driven approaches which rely only on available past observed data and statistical models. The approaches are classified into two broad types of models, that is, models that rely on directly observed state information of the asset, and those do not. We systematically review the models and approaches reported in the literature and finally highlight future research challenges. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:1 / 14
页数:14
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