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Probabilistic competing failure analysis in phased-mission systems

机译：分阶段任务系统中的概率竞争故障分析

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摘要

Many real-world systems are classified as phased-mission systems (PMSs). These systems involve multiple, consecutive, non-overlapping phases of operations, where system configuration and component behavior can vary from phase to phase due to changing tasks and environmental conditions. In addition, statistical dependencies exist across phases for a given component. These dynamic, dependent behaviors make reliability analysis of PMSs more challenging than single-phase systems. Further complicating the PMS analysis is the probabilistic functional dependence behavior where operations of some system components (referred to as probabilistic-dependent components) rely on functions of other components (referred to as trigger components) with certain probabilities. Time-domain competitions exist between a trigger component failure and propagated failures of related probabilistic-dependent components; different occurrence sequences can cause distinct system statuses. This paper models effects of phase-dependent, probabilistic competing failures, and suggests a multiple-valued decision diagram-based combinatorial procedure for reliability analysis of non-repairable PMSs. The method is applicable to arbitrary types of time-to-failure distributions for system components and probabilistic isolation factors, as well as different statistical relationships between local and propagated failures of the same component. A case study is presented to illustrate applications and advantages of the proposed method. Correctness of the method is verified using Monte Carlo simulations.
机译：许多现实世界的系统被归类为相控系统（PMS）。这些系统涉及多个，连续的，不重叠的操作阶段，其中，由于任务和环境条件的变化，系统配置和组件行为可能会在各个阶段有所不同。此外，给定组件的各个阶段之间存在统计依赖性。这些动态的，相互依赖的行为使PMS的可靠性分析比单相系统更具挑战性。概率功能依赖行为使PMS分析更加复杂，其中某些系统组件（称为概率相关组件）的操作依赖于具有某些概率的其他组件（称为触发组件）的功能。触发组件故障和相关的概率相关组件的传播故障之间存在时域竞争；不同的发生顺序可能导致不同的系统状态。本文对阶段相关的概率竞争故障的影响进行建模，并提出了基于多值决策图的组合程序，用于不可修复的PMS的可靠性分析。该方法适用于系统组件的任意类型的故障前时间分布和概率隔离因子，以及同一组件的本地故障和传播故障之间的不同统计关系。案例研究表明了该方法的应用和优点。使用蒙特卡洛模拟验证了该方法的正确性。

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