Reliability Analysis And Optimization Of Fuzzy Multi-State System With Common Cause Failure

The rapid development of modern industry,while improving the versatility of engineering systems,makes these engineering systems gradually larger and more complex.Once a failure occurs,it would cause huge losses.Therefore,system reliability has always been a hot issue of social concern.Only a system with favorable reliability can exert advantages.The complex systems in the real world mostly have the characteristics of multi-state,fuzzy failure probability and common cause failure.The traditional reliability analysis method based on the "two-state"assumption has been unable to adapt to the changes in demand brought about by these characteristics of complex systems.The existing reliability analysis methods mostly have problems such as high computational complexity and "state space explosion".Therefore,this paper takes complex systems with characteristics of multi-state,fuzzy and common-cause failure as the research object,and conducts research on its reliability analysis and optimization.First,this paper proposes a stochastic fuzzy multi-state model for fuzzy multi-state systems without considering common cause failures,based on fuzzy universal generating functions and multi-valued stochastic computation methods.The model combines the advantages of fuzzy universal generating functions for modeling of the performance and the probability of components and systems and the characteristics of rapid calculation of stochastic computation,thereby improving the efficiency of reliability analysis of complex systems.In this paper,the fuzzy universal generating function and Monte Carlo simulation method are established as experimental comparison models.The experimental results of each model can show that the stochastic fuzzy multi-state model can correctly evaluate the reliability of the fuzzy multi-state model and has high analysis efficiency.Secondly,this paper proposes a stochastic common-cause fuzzy multi-state model for fuzzy multi-state systems that consider common cause failures.The model uses implicit analysis to analyze the common cause failure and independent failure of the system separately.The common cause failure is analyzed based on the ? factor model;the independent failure is analyzed based on the stochastic fuzzy multi-state model.The stochastic common-cause unit combine the common-cause failure and the independent failure,and the reliability of the fuzzy multi-state system considering the common-cause failure is obtained through availability analysis.Finally,this paper uses the extended Risk Achievement Worth importance method to rank the importance of each component of the fuzzy polymorphic model with common cause failure,and obtains the component ranking from high to low contribution to the system reliability,so as to providing corresponding decisions for the optimization of the system to improve the reliability of the system.