期刊
RELIABILITY ENGINEERING & SYSTEM SAFETY
卷 193, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2019.106618
关键词
Accelerated degradation test; Bayesian inference; Copula function; Hamiltonian Monte Carlo; Multivariate model; System reliability
资金
- NSF [1838271, 1726445]
- Division Of Computer and Network Systems
- Direct For Computer & Info Scie & Enginr [1838271] Funding Source: National Science Foundation
- Div Of Civil, Mechanical, & Manufact Inn
- Directorate For Engineering [1726445] Funding Source: National Science Foundation
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.
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