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Variance-based importance analysis measure for mission reliability of phased mission system

机译:基于方差的分阶段任务系统任务可靠性重要性分析方法

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Importance measures are used to estimate the relative importance of components to system reliability. Phased mission systems (PMS) have many components working in several phases with different success criteria, and their component structural importance is distinct in different phases. Additionally, reliability parameters of components in PMS always have uncertainty in practice. Therefore, existing component importance measures based on either the partial derivative of system structure function or component structural importance may have difficulties in PMS importance analysis. This paper presents a simulation method to evaluate the component global importance for PMS based on the variance-based method and the Monte-Carlo method. To facilitate the practical use, we further discuss the correlation relationship between the component global importance and its possible influence factors, and present here a fitting model for evaluating component global importance. Finally, two examples are given to show that the fitting model displays quite reasonable component importance.
机译:重要性度量用于估计组件对系统可靠性的相对重要性。分阶段任务系统(PMS)的许多组件在多个阶段中都有不同的成功标准,并且它们的组件结构重要性在不同的阶段中也不同。另外,PMS中组件的可靠性参数在实践中始终具有不确定性。因此,基于系统结构功能的偏导数或组件结构重要性的现有组件重要性度量可能会在PMS重要性分析中遇到困难。本文提出了一种基于方差和蒙特卡洛方法的评估PMS组件全局重要性的仿真方法。为了便于实际使用,我们进一步讨论了组件全局重要性与其可能的影响因素之间的相关关系,并在此处提出了一种用于评估组件全局重要性的拟合模型。最后,通过两个例子说明拟合模型显示了相当合理的组件重要性。

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