Bayesian modeling of multi-state hierarchical systems with multi-level information aggregation

被引:48
作者
Li, Mingyang [1 ]
Liu, Jian [1 ]
Li, Jing [2 ]
Kim, Byoung Uk [3 ]
机构
[1] Univ Arizona, Dept Syst & Ind Engn, Tucson, AZ 85721 USA
[2] Arizona State Univ, Sch Comp Informat & Decis Syst Engn, Tempe, AZ 85287 USA
[3] Air Force Res Lab, Autonomous Control Branch, Wright Patterson AFB, OH 45433 USA
基金
美国国家科学基金会;
关键词
System reliability; Multiple failure states; Hierarchical structure; Bayesian networks; Prior elicitation; COMMON-CAUSE FAILURES; RELIABILITY-ANALYSIS; NETWORKS;
D O I
10.1016/j.ress.2013.12.001
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Reliability modeling of multi-state hierarchical systems is challenging because of the complex system structures and imbalanced reliability information available at different system levels. This paper proposes a Bayesian multi-level information aggregation approach to model the reliability of multi-level hierarchical systems by utilizing all available reliability information throughout the system. Cascading failure dependency among components and/or sub-systems at the same level is explicitly considered. The proposed methodology can significantly improve the accuracy of system-level reliability modeling. A case study demonstrates the effectiveness of the proposed methodology. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:158 / 164
页数:7
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