Research on Advanced Maintenance Plan Model of emu Based on Particle Swarm Optimization Algorithm

With the increase of high-speed emu operation mileage, the complexity and the cost to maintenance the emu is also increasing, so a scientific and comprehensive maintenance plan model for reducing excessive repair and improving maintenance efficiency is of great importance. A comprehensive analysis of the establishment of the emu maintenance plan needs to consider such factors as the mileage of the emu vehicles in service, the maintenance capacity of the base, the peak of passenger flow in holidays, and the maintenance of the normal transportation capacity of the road bureau, we propose to use these parameters such as the remaining mileage, whether more than maintenance ability and the number of hot standby as the evaluation index of the emu advanced maintenance plan model. And by using the particle swarm optimization (PSO) algorithm solving process control, advanced maintenance plan model parameter tuning, strong ability of global optimization can be obtained, thus obtains the optimal base maintenance plan, to achieve the purpose of enhance maintenance efficiency.