Failure Importance Analysis and Adjustment Based on Bayesian Networks

摘要：

Importance measures in reliability engineering are used to find the weak areas of a system. Traditional importance measures for binary systems and multistate systems mainly concern reliability importance of an individual component, and seldom consider the reliability importance of the causal components. This paper constructs the failure importance analysis Bayesian networks (FIABN) to describe the causality system firstly. Then we present the failure importance measures models for binary and multi-state systems based on FIABN. Finally, the adjustment methods of the failure importance are given. The numerical simulations show failure importance measures models and adjustment methods are effective.

关键词： failure importance measure Bayesian networks failure importance adjustment model causal system

作者: Shubin Si Wei Hu Zhiqiang Cai

作者单位: Department of Industrial Engineering, School of Mechatronics,Northwestern Polytechnical University, Department of Industrial Engineering, School of Mechatronics, Northwestern Polytechnical University, Department of Industrial Engineering,School of Mechatronics, Northwestern Polytechnical University,

会议类型: 国际会议

会议名称: Second International Symposium on Information Science and Engineering(第二届信息科学与工程国际会议)

会议地点: 上海

会议语种:英文

页码: 303-308

在线出版日期: 2009-12-26（万方平台首次上网日期，不代表论文的发表时间）