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Combinatorial Reliability Analysis of Imperfect Coverage Systems Subject to Functional Dependence

机译:具有功能依赖性的不完全覆盖系统的组合可靠性分析

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Functional dependence occurs when the failure of one component causes other components within the same system to become inaccessible or unusable. It is one of the dynamic behaviors that have been recognized in the dynamic fault tree analysis, where a dynamic gate called FDEP was designed to model such behavior. Traditional approaches to handling functional dependence in the reliability analysis of fault-tolerant systems with imperfect fault coverage are mainly based on Markov models, which are often computationally intensive, and even intractable due to the well-known state space explosion problem. In addition, the Markov-based approaches are typically restricted to exponential time-to-failure distributions for system components. In this paper, a combinatorial, separable method based on the divide-and-conquer paradigm and total probability theorem is proposed for addressing the above problems. The proposed method obviates the use of inefficient Markov models, offering exact, computationally-efficient solutions to the reliability analysis of imperfect coverage systems subject to functional dependencies. The proposed method is applicable to the analysis of large systems with any arbitrary time-to-failure distributions. Several case studies are given to illustrate the application and advantages of the proposed method.
机译:当一个组件的故障导致同一系统中的其他组件变得不可访问或无法使用时,就会发生功能依赖性。这是在动态故障树分析中已经认识到的动态行为之一,其中设计了称为FDEP的动态门来对这种行为进行建模。在故障覆盖范围不完善的容错系统的可靠性分析中,处理功能依赖性的传统方法主要基于马尔可夫模型,由于众所周知的状态空间爆炸问题,该模型通常计算量大,甚至难以处理。此外,基于马尔可夫的方法通常仅限于系统组件的指数失效时间分布。针对上述问题,本文提出了一种基于分而治之范式和总概率定理的组合可分离方法。所提出的方法消除了效率低下的马尔可夫模型的使用,为功能受限的不完善覆盖系统的可靠性分析提供了精确,计算有效的解决方案。该方法适用于具有任意失效时间分布的大型系统的分析。给出了几个案例研究,以说明该方法的应用和优点。

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