Time-Dependent Reliability Analysis of Deteriorating Structures Based on Phase-Type Distributions

• Published in: IEEE transactions on reliability Vol. 69; no. 2; pp. 545 - 557
• Main Authors: Li, Junxiang, Chen, Jianqiao, Zhang, Xiaosheng
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Computer simulation; Convolution; Convolutions; Datasets; Degradation; deteriorating structures; Deterioration; Electric shock; Fitting; Model accuracy; Monte Carlo simulation; Numerical models; PH fitting; phase-type (PH) distributions; Random variables; Reliability; Reliability analysis; Reliability engineering; shock threshold; Structural reliability; Time dependence; time-dependent reliability analysis; Transient analysis
• ISSN: 0018-9529; 1558-1721
• DOI: 10.1109/TR.2019.2907307

This paper develops a method for the time-dependent reliability analysis of deteriorating structures using phase-type (PH) distributions. The deteriorating model consists of two aspects: the progressive deterioration posed by aging effects, and the shock deterioration caused by random shocks. Evaluating the distribution of the sum of random variables is a tough work in the model. For simplified problems that random variables follow specific distributions with the convolutions being derived analytically, it is effective to utilize semianalytical methods for the time-dependent reliability analysis. For other general problems (the distribution does not have additivity or is even unknown, only with limited datasets), the semianalytical method will no longer be applicable. In dealing with such problems, PH fitting is utilized in the proposed model, i.e., any distribution or general datasets are approximated as PH distributions using Expectation Maximization algorithms. Owing to the good properties in convolution of PH distributions, the time-dependent reliability can be evaluated conveniently. Numerical examples are given to demonstrate the efficiency of the model proposed, and its accuracy is verified by comparing the model results with those of Monte Carlo simulation. The interaction between the degradation process and the shock process is also modeled and displayed with an example and discussion.