Copula-based reliability analysis of degrading systems with dependent failures

被引:114
作者
Fang, Guanqi [1 ]
Pan, Rong [1 ]
Hong, Yili [2 ]
机构
[1] Arizona State Univ, Sch Comp Informat & Decis Syst Engn, Tempe, AZ 85281 USA
[2] Virginia Tech, Dept Stat, Blacksburg, VA 24061 USA
基金
美国国家科学基金会;
关键词
Accelerated degradation test; Bayesian inference; Copula function; Hamiltonian Monte Carlo; Multivariate model; System reliability; INVERSE GAUSSIAN PROCESS; ACCELERATED DEGRADATION; WIENER-PROCESSES; MODEL; PERFORMANCE; PRODUCTS; DESIGN; TESTS;
D O I
10.1016/j.ress.2019.106618
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Consider a coherent system, in which the degradation processes of its performance characteristics are positively correlated, this paper systematically investigates a bivariate degradation model of such a system. To analyze the accelerated degradation data, a flexible class of bivariate stochastic processes are proposed to incorporate the effects of environmental stress variables and the dependency between two degradation processes is modeled by a copula function. A two-step system reliability analysis approach is developed and it is implemented with the Hamiltonian Monte Carlo algorithm. Simulation studies validate this approach and the consequences of model misspecification are evaluated too, Furthermore, two real-world examples are presented to demonstrate the applicability of the proposed modeling framework of system reliability on correlated degradation processes.
引用
收藏
页数:19
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