Research On Dynamic Characteristics And Fault Analysis Of The Axle Box Roller Bearing For High-speed Railway

With the rapid development of high-speed trains,train safety in traffic process is being taken more and more seriously.Axle box bearing,a key component of the running gear,is key to ensuring the safe operation.Studies about stress conditions, vibration, temperature dynamics under typical malfunction or different conditions for understanding reasons of damage and predicting malfunction, provide theoretical basis for bearing fault diagnosis,and be a guide to improve the bearing structure.In this paper, double row tapered roller bearings is the object of study.In consideration of frictional contact, centrifugal and gyroscopic, the finite element model is built by ANSYS / LS-DYNA analysis software.The simulation results of revolution and rotation speeds show theoretical values are consistent with the simulation, and the model can reflect the dynamic characteristics of the bearing.Internal stress is simulated by the display dynamics,which obtains stress distribution in different conditions,and the impact of factors on stress are analyzed.Inner ring raceway surface pitting, outer ring raceway surface gluing, rolling scratches, cage fracture failure are simulated for vibration acceleration.The wavelet decomposition and Hibert envelope demodulation of vibration signal is done to extract characteristic signal of different fault.Steady temperature field is analyzed by ANASYS and thermal network method in simulation and theoretical,learning temperature distribution from macro and micro. The orthogonal experiment is established to explore factors affecting temperature and determine failures caused by surface imperfections unable diagnosed.Finally, vibration of high-speed train axle box bearings under different conditions are studied in experiment.The comparison of experimental and simulated values is done to verify the feasibility of the simulation method,which provide a basis for the development of subsequent bearing line monitoring system.