Abstract

The time-dependent mechanism reliability and sensitivity analysis with imprecise probability distributions is investigated in this article. First, the interval model is employed to describe the uncertainty of the parameters of input variables due to the lack of data and knowledge. Next, the form of time-dependent failure probability and global reliability sensitivity (GRS) main effect index in the case of interval distribution parameters is analyzed. Then, the calculation methods of failure probability and GRS main effect index under the above circumstance are discussed. Finally, combined with the optimization algorithm, the Monte Carlo simulation (MCS) method and the method based on envelope function (MEVF) are proposed. By comparing with the MCS results, several numerical and engineering examples are analyzed to demonstrate the significance as well as the effectiveness of MEVF.

摘要

本文研究了时间分布不精确的概率分布机制的可靠性和敏感性分析。首先，采用区间模型来描述由于缺乏数据和知识而导致的输入变量参数的不确定性。接下来，分析了时间间隔分布参数情况下与时间有关的故障概率和全局可靠性灵敏度（GRS）主要影响指标的形式。然后讨论了在上述情况下的失效概率和GRS主效应指标的计算方法。最后，结合优化算法，提出了蒙特卡罗模拟（MCS）方法和基于包络函数的方法（MEVF）。通过与MCS结果进行比较，