## Journal of Central South University

 第49卷    第11期    总第291期    2018年11月

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(1. 中国科学院 微电子研究所，北京，100029；
2. 中国科学院大学，北京，100049
)

Fault tree analysis of automobile drive axle system based on fuzzy grey correlation theory

1. Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China

Abstract:To solve the problem that the classical fault tree analysis can not obtain complete fault information and accurate fault probability in the analysis of large and complex systems, an improved fault tree analysis based on fuzzy set theory and grey correlation theory was proposed. Firstly, all minimal cut sets were determined via fault tree analysis. The triangular fuzzy number was employed to describe the fault probability. The fuzzy probability of the top event and the fuzzy significances of bottom events were calculated according to the fuzzy operators. Secondly, a grey correlation model was established, in which the fuzzy significances of bottom events were regarded as sub-sequences and the characteristic matrix composed of minimal cut sets as primary-sequences. The grey correlation degrees between the top event and minimal cut sets were calculated to find the key direction of improving system reliability quickly and accurately. Finally, the method was applied to analyze the probability of the automobile drive axle system. The results show that the bearing fatigue pitting is the key failure event. To a certain extent, the reliability analysis of the drive axle system is finished with the lack of failure probability information, and this improved method can provide reference for improving the reliability and safety of the system and formulating relevant safety measures.

Key words: reliability analysis; fault tree analysis; triangular fuzzy number; grey correlation degree; drive axle system

 中南大学学报（自然科学版） ISSN 1672-7207 CN 43-1426/NZDXZAC 中南大学学报（英文版） ISSN 2095-2899 CN 43-1516/TBJCSTFT