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

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 informati...

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Vydané v:European journal of operational research Ročník 213; číslo 1; s. 1 - 14
Hlavní autori: Si, Xiao-Sheng, Wang, Wenbin, Hu, Chang-Hua, Zhou, Dong-Hua
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Amsterdam Elsevier B.V 16.08.2011
Elsevier
Elsevier Sequoia S.A
Edícia:European Journal of Operational Research
Predmet:
Applied sciences
Brown motion
Distribution theory
Estimates
Estimating
Estimating techniques
Exact sciences and technology
Health
Industrial metrology. Testing
Information
Linear inference, regression
Maintenance
Maintenance Remaining useful life Brown motion Stochastic filtering Proportional hazards model Markov
Markov
Mathematical models
Mathematics
Mechanical engineering. Machine design
Operational research
Operations research
Probability and statistics
Proportional hazards model
Remaining useful life
Sciences and techniques of general use
Statistical analysis
Statistical methods
Statistics
Stochastic filtering
Studies
Useful life
Maintenance
Stochastic filtering
Remaining useful life
Markov
Brown motion
Proportional hazards model
Markov process
Probabilistic approach
Statistical distribution
Health
Durability
Data driven modelling
Modeling
Cox model
Information source
Filtering theory
System identification
Monitoring
ISSN:0377-2217, 1872-6860
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Popis
Shrnutí: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.
Bibliografia:ObjectType-Article-2
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ObjectType-Literature Review-3
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ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2010.11.018