蒋玮

个人信息Personal Information

教授

博士生导师

硕士生导师

性别:女

毕业院校:英国Wolverhampton大学

学位:博士

所在单位:机械工程学院

学科:机械设计及理论. 机械制造及其自动化

办公地点:机械大方楼9017

电子邮箱:jiangwei@dlut.edu.cn

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A Weighted Saddlepoint Approximation Method for System Reliability Analysis

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论文类型:期刊论文

发表时间:2016-08-01

发表刊物:International Journal of Reliability, Quality and Safety Engineering

收录刊物:EI、Scopus

卷号:23

期号:4

ISSN号:02185393

摘要:The relationship between the reliability probabilities of the component and the system is hard to get. If this relationship can be obtained easily, the reliability of the system can be calculated by using the reliability structures of the components. The common method to express this relationship is using the linear correlation index, which only shows the linear correlation between the components failure rather than the relationship between high nonlinear functions. In order to describe this relationship accurately and calculate the system reliability using the component reliability structures, a Uniform Design (UD)-Saddlepoint Approximation (SA)-based system reliability analysis method is proposed. The system reliability analysis method is decomposed to three simple steps: (1) calculating the weight coefficient which represents the contribution rate of each component to system reliability, (2) approximating Cumulant Generation Function (CGF) of each component, (3) calculating CGF of the system and approximating the system reliability with SA method. The weight coefficient of each component is derived from UD method, and a variable interval selection method is developed to decrease the required number of samples and increase the accuracy of the weight coefficients. First-Order Saddlepoint Approximation (FOSA) method or Mean-Value First-Order Saddlepoint Approximation (MVFOSA) method is used to analyze the CGF of a component performance function. Then the CGF of the system can be obtained by the weighted addition law by combining the CGFs of components performance functions with the weight coefficients. Finally, the system reliability can be approximated by SA method. Four examples are employed to demonstrate that the new method outperforms other methods for system reliability analysis in terms of efficiency and accuracy. ? 2016 World Scientific Publishing Company.