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A stochastic hybrid systems model of common-cause failures of degrading components

机译:退化组件常见原因的随机混合系统模型

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Common-Cause Failures (CCFs) are an important threat to safety critical systems. Most existing CCF models assume that the component failure behavior does not vary over time. Such an assumption is often challenged in practice due to the influence of various degradation mechanisms, e.g., wear, corrosion, fatigue, etc. In this paper, we develop a new model for CCFs considering components degradation. The model is developed in the mathematical framework of Stochastic Hybrid Systems (SHS). The CCFs are modeled as random shock processes that affect a group of components simultaneously and the components degradation processes are modeled by stochastic differential equations derived from physics-of-failures. The benefit of using the SHS model for CCFs is that the developed model is analytically solvable. The system reliability can, then, also be solved analytically in closed form. The proposed CCF modelling framework is demonstrated by a numerical example of a three unit redundant system and, then, applied to an Auxiliary Feedwater Pump (AFP) system of a Nuclear Power Plant (NPP). A comparison to the Binomial Failure Rate (BFR) model of literature shows that by considering the components degradation processes, the proposed model can accurately describe the CCF effect on the reliability of a system with degrading components. (C) 2017 Elsevier Ltd. All rights reserved.
机译:常见原因故障(CCF)是对安全关键系统的重要威胁。大多数现有的CCF模型都假定组件故障行为不会随时间变化。由于各种降解机制(例如,磨损,腐蚀,疲劳等)的影响,这种假设在实践中通常会受到挑战。在本文中,我们开发了一种考虑部件降解的CCF新模型。该模型是在随机混合系统(SHS)的数学框架中开发的。 CCF被建模为同时影响一组组件的随机冲击过程,而组件的退化过程则通过从失效物理原理导出的随机微分方程建模。将SHS模型用于CCF的好处是开发的模型在分析上可以解决。这样,系统的可靠性也可以用封闭形式解析地解决。通过一个三单元冗余系统的数值示例演示了提出的CCF建模框架,然后将其应用于核电厂(NPP)的辅助给水泵(AFP)系统。与文献的二项式故障率(BFR)模型的比较表明,通过考虑组件退化过程,所提出的模型可以准确地描述CCF对具有退化组件的系统的可靠性的影响。 (C)2017 Elsevier Ltd.保留所有权利。

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