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Reliability calculation method based on the Copula function for mechanical systems with dependent failure

  • Ying-Kui GuEmail author
  • Chao-Jun Fan
  • Ling-Qiang Liang
  • Jun Zhang
S.I.: Reliability Modeling with Applications Based on Big Data

Abstract

In order to accurately calculate the reliability of mechanical components and systems with multiple correlated failure modes and to reduce the computational complexity of these calculations, the Copula function is used to represent related structures among failure modes. Based on a correlation analysis of the failure modes of parts of a system, a life distribution model of components is constructed using the Copula function. The type of Copula model was initially selected using a binary frequency histogram of the life empirical distribution between the two components. The unknown parameters in the Copula model were estimated using the maximum likelihood estimation method and the most suitable Copula model was determined by calculating the square Euclidean distance. The reliability of series, parallel, and series–parallel systems was analyzed based on the Copula function, where life was used as a variable to measure the correlation between components. Thus, a reliability model of a system with life correlations was established. Reliability calculation of a particular diesel crank and connecting rod mechanism was taken as a practical example to illustrate the feasibility of the proposed method.

Keywords

Reliability Life distribution Copula function Multiple failure modes Parameter estimation Crank and connecting rod mechanism 

Notes

Acknowledgements

This research was partially supported by the National Natural Science Foundation of China under the Contract Number 61463021, the Natural Science Foundation of Jiangxi Province under the Contract Number 20181BAB202020, and the Young Scientists Object Program of Jiangxi Province, China under the Contract Number 20144BCB23037.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Mechanical and Electrical EngineeringJiangxi University of Science and TechnologyGanzhouPeople’s Republic of China

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