发明名称 Fault Prediction and Condition-based Repair Method of Urban Rail Train Bogie
摘要 The present invention provides a fault prediction and condition-based repair method of an urban rail train bogie. An optimum service life distribution model of a framework, a spring device, a connecting device, a wheel set and axle box, a driving mechanism, and a basic brake device of a bogie is determined by adopting a method based on survival analysis; a reliability characteristic function of each subsystem is obtained; then, a failure rate of each subsystem of the bogie is calculated by adopting a neural network model optimized by an evolutionary algorithm; and finally, proportional risk modelling is conducted by taking the failure rate and safe operation days of each subsystem of the bogie as concomitant variables; and on the basis of cost optimization, thresholds and control limits for condition-based repair of a bogie system are obtained.
申请公布号 US2016282229(A1) 申请公布日期 2016.09.29
申请号 US201414890167 申请日期 2014.12.05
申请人 BEIJING JIAOTONG UNIVERSITY 发明人 QIN Yong;JIA Limin;SHI Jingxuan;CHENG Xiaoqing;ZHANG Yuan;YU Shan;KOU Linlin;ZHANG Zhenyu
分类号 G01M17/10 主分类号 G01M17/10
代理机构 代理人
主权项 1. A fault prediction and condition-based repair method of an urban rail train bogie, wherein the bogie comprises six subsystems, that is a framework, a spring device, a connecting device, a wheel set and axle box, a driving mechanism, and a basic brake device, and the method sequentially comprises steps as follows: S1 performing a censored processing based on a collected history failure data, determining a distribution model of each subsystem of the bogie based on a survival analysis method, obtaining a reliability characteristic function of each subsystem, calculating a reliability of each subsystem, and determining a subsystem with a lowest reliability as a most fragile part in the bogie; S2 calculating a failure rate of each subsystem of the bogie by adopting a neural network model optimized by an evolutionary algorithm; S3 conducting a proportional risk modeling by taking safe operation days and the calculated failure rate of each subsystem of the bogie as concomitant variables, and obtaining thresholds and control limits for condition-based repair of a bogie system, wherein an upper control limit is a failure threshold, and during a running process, once a system status value is found to exceed the upper control limit, the system is in an unusable status at this time, and based on regulations, a corrective maintenance or replacement shall be performed before the system is reused; a lower control limit is a preventive maintenance or replacement threshold, and indicates that a potential failure of the system starts to appear, and once a system status value exceeds the lower control limit, a corresponding troubleshooting or preventive maintenance shall be performed on a corresponding part, and if the system status value is lower than the lower control limit, the system does not need to be repaired.
地址 Beijing CN