With the increase of subway operating time and mileage,subway vehicles are gradually approaching their theoretical life.In order to ensure the safety of vehicle operation,it is necessary to evaluate the health status and remaining life of its important subsystems.This paper selects the vehicle bogie system as the research object,a combined model of Seasonal Auto-Regression Integrated Moving Average(SARIMA)and Support Vector Regression(SVR)is proposed based on the covariance optimization method to evaluate the life of the bogie.Firstly,the historical failure rate of the vehicle bogie system is converted into health index.Then SARIMA and SVR are weighted and combined based on the covariance optimization method,and prediction is made based on the historical health index of the bogie system.Finally,a mathematical model of historical and predicted health index and running time are established,and the remaining life of the bogie system is obtained by analysis.Taking the bogie system of a metro vehicle as an example,the example analysis and verification are carried out.The results show that the combined model can more accurately predict its health status and provide a theoretical basis for relevant maintenance departments to carry out maintenance strategies.In addition,the proposed model can estimate the remaining life of the vehicle,and provide theoretical data analysis support for vehicle retirement and life extension decision-making in the later stage of vehicle life.
bogie system/life prediction/Seasonal Auto-Regression Integrated Moving Average and Support Vector Regression(SARIMA and SVR)/combined model/covariance optimization method
维普
万方数据