Parameter estimation for load-sharing systems with degrading components

B. Liu, J. Xu, X. Zhao
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引用次数: 3

Abstract

This paper aims to develop a parameter estimation approach for load-sharing systems subject to continuous degradation. The system consists of multiple components in parallel structure. The components of the system suffer a degradation process, characterized respectively by Wiener process and Inverse Gaussian process. When components fail one by one, the total workload is redistributed among the remaining components, which accelerates the degradation process of the surviving components, which is referred to as a load-sharing system. Maximum likelihood estimation (MLE) is used to estimate the parameters for a load-sharing system. The available data are the failure times of the components and the degradation level of the remaining components at failure time. For Wiener process, a close-form MLE is derived and an analytical solution is achieved. For inverse Gaussian process, however, it is difficult to obtain a close-form MLE and numerical method is adopted instead. Finally, numerical studies are conducted to illustrate the estimation procedure.
具有退化部件的负载共享系统的参数估计
本文旨在发展一种持续退化的负荷共享系统参数估计方法。该系统由多个部件并联构成。系统的组成部分经历了一个退化过程,分别用维纳过程和逆高斯过程来表征。当组件一个接一个失效时,总工作负载被重新分配到剩余的组件中,这加速了幸存组件的退化过程,这被称为负载共享系统。最大似然估计(MLE)用于负荷共享系统的参数估计。可用的数据是组件的故障时间和故障时剩余组件的退化程度。对于维纳过程,导出了一个接近形式的最大似然方程,并得到了解析解。然而,对于逆高斯过程,难以获得接近形式的最大似然,采用数值方法代替。最后,通过数值研究来说明估计过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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