【摘要】 为了提取轨道列车轮对振动特征信息,提出一种基于频率切片小波变换的故障特征提取方法。首先,利用频率切片小波变换获取振动信号在全频带的时频分布;然后,依据得到的振动信号能量分布特点选择时频目标区域;接着,分割出含有故障特征的时频区域;最后,通过逆变换对目标区域的信号分量进行重构,分离出有效的信号时频特征。仿真结果表明,利用频率切片小波变换分离轮对振动信号时频特征效果较好,为轨道列车轮对振动信号时频特征精确提取提供一种新的方法。更多还原

【Abstract】 In order to extract the features of wheel-rail vibration,a novel fault diagnosis approach using time-frequency slice analysis is proposed.Firstly,wheel-rail vibration signal was transformed by frequency sliced wavelet transform(FSWT)to get the timefrequency characteristic figures of wheel-rail impact.Secondly,the time-frequency region was selected on the basis of the characteristic of the signal energy distribution.Thirdly,the chosen time-frequency region is further refining analyzed to highlight the hidden time-frequency characteristics.Finally,the time-frequency region which contains fault feature is separated.Through inverse FSWT transformation,the signal component was reconstructed to separate the time-frequency characteristics of effective signals.The effectiveness of this approach has been proved through the dynamics simulation data,gives a new and efficient method to extracting the features of wheelrail vibration.更多还原