Belief Universal Generating Function Analysis of Multi-State Systems Under Epistemic Uncertainty and Common Cause Failures
Belief Universal Generating Function Analysis of Multi-State Systems Under Epistemic Uncertainty and Common Cause Failures
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DOI：
10.1109/tr.2015.2419620
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发表时间：
2015-04
影响因子：
5.9
通讯作者：
J. Mi;Yanfeng Li;Yu Liu;Yuanjian Yang;Hongzhong Huang
中科院分区：
文献类型：
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作者：
J. Mi;Yanfeng Li;Yu Liu;Yuanjian Yang;Hongzhong Huang
针对工程系统的复杂性，以及现有可靠性分析数据不足以获得元件精确状态概率的情况，提出了一种基于信度函数理论的扩展泛母函数（UGF），用于分析具有认知不确定性的多状态系统（MSS）的可靠性。共因故障（CCF）的行为进一步纳入，共因故障的发生概率使用加权影响向量法进行评估。数值例子来说明所提出的方法是如何工作的。此外，本文还采用全局优化方法求出了系统可靠度的真值区间，并将所得结果与现有方法的结果进行了比较。算例表明，置信UGF方法可以有效避免区间UGF方法中的区间扩张问题和高估问题，为区间数据和CCF的MSS可靠性评估提供了可靠的方法.
Because of the complexity of engineering systems, and the fact that insufficient data are only available to obtain the precise state probability of components, an extended universal generating function (UGF) based on belief function theory is introduced in this paper to conduct the reliability analysis of multi-state systems (MSSs) with epistemic uncertainty. The behavior of common cause failures (CCFs) is further incorporated, and the occurrence probability of CCFs is evaluated using a weighted impact vector method. A numerical example is used to illustrate how the proposed method works. In addition, a global optimization method is used to obtain the truth interval of the system reliability, and the results are compared with those obtained by using some existing methods. The case study shows that the belief UGF method can effectively avoid the interval expansion problem and the overestimation problem involved in the interval UGF method, and the proposed method can be used to provide a reliable way to evaluate the reliability of MSSs with interval data and CCFs.