地铁车辆转向架轴承状态对车辆的安全运行至关重要。现有地铁车辆转向架轴承的监测与诊断存在智能化程度低、准确性差等不足。针对此不足，对地铁车辆转向架轴承故障模型进行推导，提出一种地铁车辆转向架轴承故障智能诊断方法。该方法根据转向架轴承径向振动加速度信号，采用小波包-包络分析和故障识别搜索算法，诊断轴承故障及故障类型。为了验证所提出方法的有效性，设计并搭建了轴承故障诊断试验台，基于此试验台对广州地铁车辆转向架故障轴承进行了测试。试验结果表明：所提出的转向架轴承故障诊断方法能够准确识别轴承故障，为地铁车辆转向架轴承故障诊断的自动化、智能化提供了新思路。%The condition of bogie bearings of metro vehicle is highly important to the safe and normal operation of metro vehicles.However,shortcomings,such as a low level of intelligence and poor accuracy,exist in cur-rent monitoring and diagnosis methods for bogie bearings of metro vehicle.To solve this problem,a fault mod-el for bogie bearings of metro vehicle is derived and an intelligent fault diagnosis method for bogie bearings of metro vehicle is proposed.This method,based on the radial vibration acceleration signal of bogie bearings,u-sing the wavelet packet-envelopment analysis and the search algorithm for fault identification,diagnoses bear-ing faults and finds out the fault type.In order to verify the effectiveness of the proposed method,a test plat-form for bearing fault diagnosis was designed and built,and the fault bogie bearings used in Guangzhou Metro were tested on this test platform.Test results show that the proposed fault diagnosis method for bogie bearings can accurately identify bearing faults,and provide a new idea for automatic and intelligent fault diagnosis on bo-gie bearings.
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