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A Stochastic Approach for Evaluating the Reliability of Multi-stated Phased-Mission Systems with Imperfect Fault Coverage

机译:一种评估多完全故障覆盖的多表相控使系统可靠性的随机方法

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A phased-mission system (PMS) is usually consisting of a number of non-overlapping phases, and the phases should be completed sequentially to achieve a successful mission. In practice, imperfect fault coverage (IPC) plays an important effect on the system reliability. In this paper, stochastic multi-value (SMV) models are proposed to predict the system reliability of a multi-stated PMS consisting of non-repairable components; during the evaluating process, three different imperfect fault coverage conditions (listed as Element Level Coverage, Fault Level Coverage, and Performance dependent Coverage) are incorporated. In the stochastic analysis, performance values and their corresponding probabilities of elements are simultaneously encoded in random sequences consisting of permutation of fixed numbers of multi-value numbers. Thus, the types of components' failure distributions are not limited for the proposed approach. By feeding the obtained stochastic sequences into the proposed system structure, reliability of a PMS can be efficiently determined which avoids cumbersome analyzing process. The efficiency of the SMV approach is verified by several case studies compared to universal generating function (UGF).
机译:分阶段任务系统(PMS)通常由许多非重叠阶段组成,并且阶段应按顺序完成以实现成功的使命。在实践中,不完美的故障覆盖(IPC)对系统可靠性起着重要影响。在本文中,提出了随机多值(SMV)模型来预测由不可修复部件组成的多表PM的系统可靠性;在评估过程中,结合了三种不同的不完美故障覆盖条件(列为元素级覆盖,故障级别覆盖以及性能相关覆盖率)。在随机分析中,性能值及其对应的元素的概率同时编码,其随机序列编码,该随机序列由多值数的固定数量的置换组成。因此,组件的故障分布类型不限于所提出的方法。通过将所获得的随机序列送入所提出的系统结构中,可以有效地确定PMS的可靠性,这避免了繁琐的分析过程。与通用生成功能(UGF)相比,几种情况研究验证了SMV方法的效率。

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