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Reliability modelling for multi-component systems subject to stochastic deterioration and generalized cumulative shock damages

机译:多组分系统的可靠性建模,但随机劣化和广义累积冲击损失

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For a complex system consisting of multiple components, it is often unrealistic that one type of environmental shocks affects all the components at the same time. Correspondingly, random shocks are categorized into several distinct sets according to their functions, attributes or sizes. This study develops generalized reliability models for multi-component systems, where each component is subject to two dependent competing failure processes, i.e., a soft failure process caused jointly by internal performance degradation and an incremental damage due to effective external shock sets, and a hard failure process caused by the same random shocks. A damage improvement coefficient and a damage aggravation coefficient are respectively introduced to extend the standard cumulative shock damage model into two more generalized shock cases. Analytical representations of system reliability for a series-parallel system and a parallel-series system are derived based on a gamma to normal distribution approximation approach. To quantitatively compare the effects of these two damage coefficients, a block replacement policy is further adopted by searching for the optimal replacement intervals with a Nelder-Mead downhill simplex method. Finally, an illustrative example of micro-electro-mechanical systems (MEMS) consisting of four silicon micro-mechanical resonators is provided to examine the effects of self-healing ability in the materials of polymer binder on system reliability and replacement period.
机译:对于由多个组件组成的复杂系统,一种环境冲击通常同时影响所有组件通常是不现实的。相应地,随机冲​​击根据其功能,属性或大小分为几个不同的组。该研究为多组分系统开发了广义可靠性模型,其中每个组件受到两个相关的竞争故障过程,即通过内部性能下降和由于有效的外部冲击集而引起的增量损失,以及难以造成的软件失败过程,以及难以造成的由相同随机冲击引起的故障过程。分别引入损伤改善系数和损坏的加重系数以将标准累积冲击损伤模型扩展为两个更广泛的震动盒。基于正常分布近似方法的伽马推导出串行并行系统和并联系列系统的系统可靠性的分析表示。为了定量比较这两个损伤系数的效果,通过使用Nelder-Mead Downhill Simplex方法搜索最佳替代间隔来进一步采用块更换策略。最后,提供了由四种硅微机械谐振器组成的微电机械系统(MEMS)的说明性示例,以检查高分子粘合剂材料中的自愈合能力对系统可靠性和更换时段的影响。

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