考虑认知不确定性的多状态系统Birnbaum重要度分析方法

doi:10.3901/JME.2018.08.223

机械工程学报 ›› 2018, Vol. 54 ›› Issue (8): 223-232.doi: 10.3901/JME.2018.08.223

• 交叉与前沿 • 上一篇

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考虑认知不确定性的多状态系统Birnbaum重要度分析方法

夏侯唐凡¹, 刘宇¹, 张皓冬¹, 张成林²

1. 电子科技大学机械与电气工程学院成都 611731;
2. 中国科学技术大学工程科学学院合肥 230026

收稿日期:2017-05-09 修回日期:2017-11-05 出版日期:2018-04-20 发布日期:2018-04-20
通讯作者: 刘宇(通信作者),男,1982年出生,教授,博士研究生导师。主要研究方向为复杂系统可靠性建模和评估、维修决策、故障预测和健康管理、不确定性下的设计。E-mail:yuliu@uestc.edu.cn
基金资助:
国家自然科学基金（71371042）和四川省杰出青年学术技术带头人培育基金（2016JQ0006）资助项目。

Birnbaum Importance Measure of Multi-state Systems under Epistemic Uncertainty

XIAHOU Tangfan¹, LIU Yu¹, ZHANG Haodong¹, ZHANG Chenglin²

1. School of Mechatronics Engineering, University of Electronic Science and Technology of China, Chengdu 611731;
2. School of Mechanical and Electrical Science, University of Science and Technology of China, Hefei 230026

Received:2017-05-09 Revised:2017-11-05 Online:2018-04-20 Published:2018-04-20

摘要/Abstract

摘要： 重要度分析是辨识复杂系统可靠性薄弱环节的有效手段。但现有的重要度分析方法均假设系统及组成部件的退化规律是完全精确已知的，即系统和部件的退化或失效模型是可以被精确估计的。针对实际工程中由于小样本、失效数据不足且难以获取、失效或退化机理不明确等因素所产生的退化模型参数认知不确定性，提出一种考虑认知不确定性的多状态系统Birnbaum重要度分析新方法，利用证据理论和马尔科夫模型分别开展认知不确定性量化和多状态系统可靠性建模，从而有效地量化部件退化参数的认知不确定性对系统可靠度和重要度的影响。该方法被应用在重型数控车床的刀具进给控制系统的可靠性分析中，以阐明认知不确定性对部件重要度分析和排序的作用与影响。

关键词: Dempster-Shafer证据理论, 多状态系统, 马尔科夫模型, 认知不确定性, 重要度分析

Abstract: Importance measures are effective tools to identify the weak components of multi-state systems from a reliability perspective. Nevertheless, the most reported works on importance measures were based on the premise that the deteriorating processes of systems and its components can be precisely known. In many engineering practices, due to limited data, imprecise information, and unknown failure/degradation mechanisms, it is inevitable that the estimated parameters may contain the epistemic uncertainty. By taking account of the epistemic uncertainty associated with the parameters of multi-state system degradation models, a new Birnbaum importance measure of multi-state systems under epistemic uncertainty is put forth. In the proposed method, the Dempster-Shafer evidence theory is used to quantify the epistemic uncertainty, while the Markov model is utilized to characterize the degradation process of multi-state systems. An illustrative example of a cutter feeding control system of machining tools is presented to demonstrate the impact of the epistemic uncertainty on the importance analysis and ranking of components.

Key words: Dempster-Shafer evidence theory, epistemic uncertainty, importance measure, Markov model, multi-state systems

中图分类号:

TB114

夏侯唐凡, 刘宇, 张皓冬, 张成林. 考虑认知不确定性的多状态系统Birnbaum重要度分析方法[J]. 机械工程学报, 2018, 54(8): 223-232.

XIAHOU Tangfan, LIU Yu, ZHANG Haodong, ZHANG Chenglin. Birnbaum Importance Measure of Multi-state Systems under Epistemic Uncertainty[J]. Journal of Mechanical Engineering, 2018, 54(8): 223-232.

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考虑认知不确定性的多状态系统Birnbaum重要度分析方法

Birnbaum Importance Measure of Multi-state Systems under Epistemic Uncertainty

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