针对滚动轴承故障识别困难这一问题,提出了基于双树复小波包变换和1.5维谱的诊断方法.首先通过双树复小波包变换将复杂的、非平稳的原始故障信号分解为若干个不同子带信号分量,继而利用峭度评价指标从分解所得结果中筛选出蕴含丰富特征信息的子带信号分量,将其视为最佳分量并做进一步包络解调运算,最后计算所得包络信号的1.5维谱,从中提取出轴承故障特征信息.实测信号分析结果表明,基于双树复小波包变换和1.5维谱的诊断方法能够实现滚动轴承故障类型的有效判定,具有一定工程应用价值.%To overcome the difficulty of fault diagnosis for rolling bearing,a diagnosis method based on dual tree complex wavelet packet transform and 1.5 dimension spectrum was proposed.Firstly,the complex and non-stationary original fault signal was decomposed into several different sub-band signal components using the dual tree complex wavelet packet transform,then the sub-band signal component containing the rich characteristic information was selected through the kurtosis evaluation index,and this signal component was regarded as the optimal component,then the envelope demodulation operation was performed on the optimal component.Finally,the 1.5 dimension spectrum of the obtained envelope signal was calculated and fault characteristic information of the bearing could be extracted.The analysis results of the measured signal showed that the diagnosis method based on dual tree complex wavelet packet transform and 1.5 dimension spectrum could effectively judge the fault type of the rolling bearing,and had a certain value for engineering application.
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