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RESEARCH PAPER
Reliability-based design optimization under fuzzy and interval variables based on entropy theory
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School of Automobile and Transportation Xihua University No. 999, Jinzhou Road, Jinniu Zone, Chengdu 610039, China
 
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Institute of Electronic Engineering China Academy of Engineering Physics No. 64, Mianshan Road, Youxian Zone, Mianyang 621900, China
 
 
Publication date: 2019-09-30
 
 
Eksploatacja i Niezawodność – Maintenance and Reliability 2019;21(3):430-439
 
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ABSTRACT
Reliability-based design optimization under fuzzy and interval variables is important in engineering practice. The interval Monte Carlo simulation (IMCS), extremum method, and saddlepoint approximation (SPA) can be used for reliability optimization issues contain only interval variables. Thus, how to deal with the fuzzy variables is critical for system reliability analysis and optimization design. The α-level cut method can be applied to deal with fuzzy variables but it is complex and computationally expensive. Therefore, an equivalent conversion method based on entropy theory is proposed in this paper, which can convert the fuzzy variables to the normal random variables to avoid the complex integral process. According to the equivalent conversion method, the entropybased sequential optimization and reliability assessment (E-SORA) is developed in combination with the worst case analysis (WCA) for reliability-based design optimization under fuzzy and interval variables. A numerical example about the reliability design of the crank-link mechanism under fuzzy and interval variables is solved by the E-SORA, double-loops method, and α-level cut algorithm, respectively, is used to demonstrate the accuracy and efficiency, and the results show that the proposed method is feasible for reliability-based design optimization under fuzzy and interval variables
 
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Eksploatacja i Niezawodność – Maintenance and Reliability
 
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ISSN:1507-2711
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