Research On The Optimization Of Preventive Maintenance Model For Urban Rail Transit Trains Bogie

With the rapid development of China’s urban rail transit industry,the number of domestic urban rail trains has risen sharply,and there is also a huge demand for train maintenance work.Effective maintenance work can ensure the safety and reliability of train operation,improve train operation efficiency and maintenance economy.Therefore,it is of great significance to study advanced and improved train maintenance strategies and improve train maintenance level to ensure train operation safety and control maintenance costs.Firstly,based on the traditional opportunity maintenance strategy based on time threshold,this paper considers component fault risk level and profit-loss ratio,and establishes the opportunity maintenance strategy optimization model based on global optimization threshold.This model takes the lowest average maintenance expense ratio as the optimization goal,and takes into account the condition of the starting opportunity maintenance of each part of the train travel department from four aspects of the position,timing,mode and judgment standard of opportunity maintenance.Secondly,the model will be the opportunity to maintain subdivision for the chance to repair and replacement,and uses the recursion back factor for different maintenance methods described,quantitative decision method is given the opportunity to maintain way at the same time,from the Angle of global optimization direction of parts chance to maintain recursion and optimize the level of risk,to determine the optimal maintenance policy.Comparative analysis shows that this model can control the oversupply problem of traditional opportunity maintenance and effectively reduce operation and maintenance costs.Then,in view of the traditional preventive maintenance model estimate of the failure rate index often appear incorrect failure distribution model of the problem.In this paper,the artificial neural network is used to replace the empirically based failure rate distribution display expression method in the traditional model to predict the urban rail train.The failure rate of the ministry has established the IPSO-BP neural network prediction model,and compared with the BP and PSO-BP neural network models,the superiority of the IPSO-BP neural network failure rate prediction model is verified.Finally,according to the condition monitoring needs of each train system and the development trend of intelligent maintenance,the state monitoring and intelligent maintenance system of urban rail train based on B/S architecture is designed and developed,which can provide technical support for the realization of state maintenance and intelligent maintenance decision-making of the train.