A Copula Function Based Evidence Theory Model For Correlation Analysis and Corresponding Structural Reliability Method

doi:10.3901/JME.2017.16.199

Abstract

Abstract: A Copula function based evidence theory model for correlation analysis and corresponding structural reliability method is proposed to deal with reliability design problems with dependent evidence variables. The Copula function is used to describe the correlation between evidence variables, and to identify the best copula, a Bayesian method which is usually used in probabilistic problem is expanded to evidence theory, the empirical distribution is used to convert the evidence variables to standard uniform variables, and the weight is calculated from the samples to identify the best copula function. The joint basic probability assignment (BPA) is gained by making the difference between the marginal BPAs using copula function. Then the reliability interval is gained by calculating the cumulative BPA of the focal elements in the reliable domain. Three examples are investigated to verify the effectiveness of the proposed method, the results show that the correlation between evidence variables may influence the reliability results significantly, and the commonly used independence assumption may lead to big error of the reliability result.

Key words: Bayesian method, Copula, evidence theory, parameter correlation, structural reliability

CLC Number:

TH122

JIANG Chao, ZHANG Wang, HAN Xu. A Copula Function Based Evidence Theory Model For Correlation Analysis and Corresponding Structural Reliability Method[J]. Journal of Mechanical Engineering, 2017, 53(16): 199-209.

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