Multi-component system maintenance optimization of a rail transit train based on opportunistic correlations

作     者：Jisheng Dai Rongjun Ding Yong Fu Yong Qin Jisheng Dai;Rongjun Ding;Yong Fu;Yong Qin

作者机构：College of Mechanical and Vechicle EngineeringHunan UniversityYuelu DistrictChangshaHunan 410082China Zhuzhou CRRC Times Electric Co.Ltd.Shifeng DistrictZhuzhouHunan 412001China State Key Lab of Rail Traffic Control&SafetyBeijing Jiaotong UniversityHaidian DistrictBeijing 100044China 

出 版 物：《Transportation Safety and Environment》 (交通安全与环境（英文）)

年 卷 期：2023年第5卷第4期

页      面：182-191页

学科分类：082304[工学-载运工具运用工程] 08[工学] 080204[工学-车辆工程] 0802[工学-机械工程] 0823[工学-交通运输工程] 

基　　金：funded by the Hunan Science and Technology‘Lotus Bud’Talent Support Program(Gr ant No.2022TJ-XH-009) 

主　　题：multi-component system maintenance optimization rail transit train opportunistic correlation modified particle swarm optimization(PSO) 

摘      要：ln order to deal with the problems of insufficient or excessive maintenance in the current maintenance activities of China transit trains,this paper develops a novel multi-component system maintenance optimization approach based on an opportunistic correlation *** on the minimal reliability and failure rate change rule of each train component,the novel proposed maintenance optimization benefits from an improved opportunistic maintenance model with system structure correlation,fault correlation and reliability correlation under imperfect ***,different maintenance modes can be determined by a proposed mainte-nance factor under the different conditions of ***,the reliability threshold of each component is also considered to optimize the maintenance cost by the system reliability and operational availability of the ***,as the mentioned problem belongs to the NP-Hard optimization problems,a modified particle swarm optimization(PSO)with the improvement of inertia weight is proposed to cope with the optimization *** on a specific case under the practical recorded failure data,the analysis shows that the proposed model and approach can effectively cut the maintenance cost.