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Imprecise sensitivity analysis of system reliability based on the Bayesian network and probability box
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School of Automation Engineering, University of Electronic Science and Technology of China, No.2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, Sichuan, 611731, P.R. China
School of Automation Engineering, Center for System Reliability and Safety, University of Electronic Science and Technology of China, No.2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, Sichuan, 611731, P.R. China
Publication date: 2020-09-30
Eksploatacja i Niezawodność – Maintenance and Reliability 2020;22(3):508-519
Sensitivity analysis measures how changes in system inputs affect outputs. Previously, a large amount of sensitivity analysis research was relevant to the precise probability that is regarded as an ideal condition of engineering. Due to insufficient test samples and the low accuracy of test data, system reliability with hybrid uncertainty is difficult to be described as a precise value. As a profusion of highly integrated electromechanical equipment is applied in modern life, it is impossible to apply sufficient resources to eliminate the stochastic property of every component, which necessitates the identification of highly sensitive components to efficiently reduce imprecision. Hence, based on the theory of imprecise probability, imprecise sensitivity analysis has become a popular research topic in the last decade. In this paper, a method for uncertain system reliability and imprecise sensitivity analysis is proposed based on a Bayesian network, a probability box and the pinching method. The feasibility and accuracy of the combined method are fully verified through the evaluation and analysis of a numerical example and a case study of an electromechanical system, and the highly sensitive components that heavily influence the imprecision of system outputs are accurately identified.
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