A single-loop time-variant reliability evaluation via a decoupling strategy and probability distribution reconstruction

verfasst von

Yang Zhang, Jun Xu, Michael Beer

Abstract

In this paper, a single-loop approach for time-variant reliability evaluation is proposed based on a decoupling strategy and probability distribution reconstruction. The most attractive feature of the proposed method is that the reliability at a specified time instant can be captured by performing time-invariant reliability analysis only once. In this method, the expansion optimal linear estimation is first employed to discretize the loading stochastic process. Then, a decoupling strategy that decouples the loading stochastic process and degradation processes is developed to formulate a single-loop method for time-variant reliability analysis, where an equivalent extreme value limit state function (EEV-LSF) is obtained. To improve the accuracy and robustness, the Box–Cox transformation is applied to get a transformed EEV-LSF. The maximum entropy method with fractional exponential moments is employed to robustly derive the probability distribution of transformed EEV-LSF. Once the probability distribution is captured, the time-variant failure probability can be readily computed. To handle a large number of random variables, a weighted sampling method is applied for moment assessment to ensure an efficient solution. Numerical examples including a complex real-world case are studied to validate the proposed method, where pertinent Monte Carlo simulations and PHI2 method are conducted for comparisons.

Organisationseinheit(en)

Institut für Risiko und Zuverlässigkeit

Externe Organisation(en)

Hunan University
The University of Liverpool
Tongji University

Typ

Artikel

Journal

Reliability Engineering and System Safety

Band

232

ISSN

0951-8320

Publikationsdatum

04.2023

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Sicherheit, Risiko, Zuverlässigkeit und Qualität, Wirtschaftsingenieurwesen und Fertigungstechnik

Elektronische Version(en)

https://doi.org/10.1016/j.ress.2022.109031 (Zugang: Geschlossen)