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.