A Markov decision process framework for optimal operation of monitored multi-state systems

被引：10

作者：

Compare, Michele ^{[1
,2
]}

Marelli, Paolo ^{[1
]}

Baraldi, Piero ^{[1
]}

Zio, Enrico ^{[1
,2
,3
]}

机构：

[1] Politecn Milan, Dept Energy, Via La Masa 34, I-20137 Milan, Italy

[2] Aramis Srl, Milan, Italy

[3] Ecole Cent Supelec, Fdn Elect France, Chair Syst Sci & Energy Challenge, Gif Sur Yvette, France

来源：

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY | 2018年 / 232卷 / 06期

关键词：

Multi-component system; Markov decision process; optimal maintenance policy; optimal operation policy; prognostics and health management; condition-based maintenance; PLANNING STRUCTURAL INSPECTION; CONDITION-BASED MAINTENANCE; MULTICOMPONENT SYSTEMS; PROGNOSTICS; POLICIES; COMPONENTS;

D O I：

10.1177/1748006X18757077

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

We develop a decision support framework based on Markov decision processes to maximize the profit from the operation of a multi-state system. This framework enables a comprehensive management of the multi-state system, which considers the maintenance decisions together with those on the multi-state system operation setting, that is, its loading condition and configuration. The decisions are informed by a condition monitoring system, which estimates the health state of the multi-state system components. The approach is shown with reference to a mechanical system made up of components affected by fatigue.

引用

页码：677 / 689

页数：13

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