Parameter estimation for load-sharing system subject to Wiener degradation process using the expectation-maximization algorithm
Xu, Jianyu and Liu, Bin and Zhao, Xiujie (2019) Parameter estimation for load-sharing system subject to Wiener degradation process using the expectation-maximization algorithm. Quality and Reliability Engineering International, 35 (4). pp. 1010-1024. ISSN 0748-8017 (https://doi.org/10.1002/qre.2442)
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Abstract
In practice, many systems exhibit load-sharing behavior, where the surviving components share the total load imposed on the system. Different from general systems, the components of load-sharing systems are interdependent in nature, in such a way that when one component fails, the system load has to be shared by the remaining components, which increases the failure rate or degradation rate of the remaining components. Because of the load-sharing mechanism among components, parameter estimation and reliability assessment are usually complicated for load-sharing systems. Although load-sharing systems with components subject to sudden failures have been intensely studied in literatures with detailed estimation and analysis approaches, those with components subject to degradation are rarely investigated. In this paper, we propose the parameter estimation method for load-sharing systems subject to continuous degradation with a constant load. Likelihood function based on the degradation data of components is established as a first step. The maximum likelihood estimators for unknown parameters are deduced and obtained via expectation-maximization (EM) algorithm considering the nonclosed form of the likelihood function. Numerical examples are used to illustrate the effectiveness of the proposed method.
ORCID iDs
Xu, Jianyu, Liu, Bin ORCID: https://orcid.org/0000-0002-3946-8124 and Zhao, Xiujie;-
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Item type: Article ID code: 68943 Dates: DateEvent30 June 2019Published21 December 2018Published Online20 November 2018AcceptedSubjects: Technology > Engineering (General). Civil engineering (General) Department: Strathclyde Business School > Management Science Depositing user: Pure Administrator Date deposited: 22 Jul 2019 08:18 Last modified: 12 Dec 2024 08:19 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/68943