考虑维修力量影响及载荷动态分配的k/n系统模糊可靠性分析

doi:10.7527/S1000-6893.2017.21718

Abstract

Abstract: In engineering practice, the preparation period usually exists before maintenance activities. Because of external environment and deterioration of the system after a long period of operation, the state performance level of the components is uncertain, making the system reliability modeling more difficult. Therefore, the failure transfer rate, repair transfer rate and state performance level of components are regarded as fuzzy numbers. By using Power Law rule, the failure-correlation between components is characterized, and the failure-correlation phenomena is found to occur when the load on the component exceeds a threshold. The influence of the quantitative relationship between repairmen and fault components on system reliability is considered. A model for the k-out-of-n system with dynamic load distribution and maintenance preparation period is analyzed, and the state transfer differential equations are established. The inverse hierarchical analysis method is put forward to present the recursive relation of the steady-state probability coefficient of the system. By using the α-cut level set and the Zadeh-expansion principle, the level set internal of the fuzzy state probability is determined. The steady measures of the system are obtained and the influence of the fuzzy degree of the repairman number and component parameters on steady measures is presented by a numerical simulation, proving the applicability of the model.

Key words: maintenance preparation period, fuzzy multiple-state, failure-correlation threshold, dynamic load distribution, steady state availability, maintenance busy period, reliability analysis

CLC Number:

V211

LI Fang, HE Youchen, DI Peng, CHEN Tong, YIN Dongliang. Reliability analysis of fuzzy k-out-of-n system considering maintenance influence and dynamic load distribution mechanism[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2018, 39(4): 221718-221718.

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Reliability analysis of fuzzy k-out-of-n system considering maintenance influence and dynamic load distribution mechanism

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