| In reliability engineering,many systems with high reliability requirements are usually designed with k-out-of-n:G structure.However,the reliability optimization for k-out-of-n systems is a rather difficult problem.Therefore,it is necessary to study the reliability optimization problem for k-out-of-n:G system,which is extremely instructive for system design.Firstly,introduced the mixed redundancy strategy and semi-component mixing-redundancy strategy in the reliability optimization design of k-out-of-n:G system for the first time.Based on the continuous time markov chain,the system reliability mathematical models are established for k-out-of-n:G with different redundancy strategies.To evaluate the performance of the proposed reliability mathematical models,propose two reliability optimization problems,A pseudo-parallel genetic algorithm is designed to solve the problems.Then,several typical reliability optimization problems and an engineering case problem are numerically analyzed.The experimental results show that the two new models have higher system reliability and better performance than previous model studies.The new model based on markov chain and mixed redundancy strategy was applied to 33 commonly used redundancy allocation subproblem test sets,and the system reliability obtained by the model based on lower bound formulation and a choice of redundancy strategy was analyzed,and an average error rate is 0.7379%.The experimental results show that the reliability mathematical model established by using continuous time markov chain for k-out-of-n:G system is more precise.By adjusting several key parameters,the sensitivity of different redundancy strategies are analyzed,and the influence of key parameters such as component and switching system reliability on different redundancy strategies isobtained.Reveals the significant influence of the failure rate of switching system on the optimal system configuration at the same time.The article has 33 figures,18 tables and 64 references. |
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