一种城市轨道车辆轴箱轴承故障特征提取方法

针对城市轨道车辆轴箱轴承结构特点及轴承故障时产生振动信号的特征，提出了一种新的轴箱轴承故障特征提取方法。引入卷积滤波，对采集的轴箱轴承振动信号进行分频、滤波、重构，提取轴承故障特征。在故障特征提取的基础上，进行轴承故障识别及定位。结果表明：该方法对振动信号进行分析，具有不压缩、任意分频和减少截断误差的性质；可以更好地获得故障特征；能够有效地应用于轴箱轴承的故障诊断。

An Approach to Fault Feature Extraction of Urban Rail Vehicle Axle Box Bearing

A new approach for extracting features of axle box bearing fault vibration signals is proposed based on the characteristics of the urban rail vehicle axle box bearing structure and the features of bearing fault vibration signals.Convolution filter is introduced for frequency dividing,filtering and reconfiguration processing on axle box bearing vibration signals,then the bearing fault features are extracted.On the basis of fault feature extraction,the fault is identified and located.It is shown that using the method to analyze vibration signals has natures that no compression,arbitrary frequency division and reduced truncation error,which can get a better fault feature and effectively be applied to fault diagnosis of axle box bearing.