Variance-based importance analysis measure for mission reliability of phased mission system

被引:2
|
作者
Wu, Xinyang [1 ]
Wu, Xiaoyue [1 ]
Balakrishnan, Narayanaswamy [2 ]
机构
[1] Natl Univ Def Technol, Coll Syst Engn, Changsha, Hunan, Peoples R China
[2] McMaster Univ, Dept Math & Stat, Hamilton, ON, Canada
基金
中国国家自然科学基金;
关键词
Component importance analysis; phased mission system (PMS); variance-based; Monte-Carlo simulation; fitting; UNCERTAINTY IMPORTANCE MEASURE; GLOBAL SENSITIVITY-ANALYSIS; BIRNBAUM IMPORTANCE; COHERENT SYSTEMS; INDEXES; SIMULATION; ALLOCATION; COMPONENTS; MODEL; PERFORMANCE;
D O I
10.1080/00949655.2017.1407936
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Importance measures are used to estimate the relative importance of components to system reliability. Phased mission systems (PMS) have many components working in several phases with different success criteria, and their component structural importance is distinct in different phases. Additionally, reliability parameters of components in PMS always have uncertainty in practice. Therefore, existing component importance measures based on either the partial derivative of system structure function or component structural importance may have difficulties in PMS importance analysis. This paper presents a simulation method to evaluate the component global importance for PMS based on the variance-based method and the Monte-Carlo method. To facilitate the practical use, we further discuss the correlation relationship between the component global importance and its possible influence factors, and present here a fitting model for evaluating component global importance. Finally, two examples are given to show that the fitting model displays quite reasonable component importance.
引用
收藏
页码:841 / 868
页数:28
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