基于双树复小波包变换和1.5维谱的轴承故障诊断方法

发布时间：2018-04-19 20:51

本文选题：双树复小波包变换 + .维谱　；参考：《河南理工大学学报(自然科学版)》2016年06期

【摘要】：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。
[Abstract]:Aiming at the difficulty of fault identification of rolling bearing, a diagnosis method based on double tree complex wavelet packet transform and 1.5 dimension spectrum is proposed. Firstly, the complex and non-stationary original fault signals are decomposed into several different sub-band signal components by the double tree complex wavelet packet transform. Then the kurtosis evaluation index is used to select the subband signal component which contains rich characteristic information from the decomposition result, which is regarded as the best component and further envelope demodulation operation. Finally, the 1.5 dimension spectrum of the envelope signal is calculated. The bearing fault feature information is extracted from it. The analysis results of measured signals show that the diagnosis method based on double tree complex wavelet packet transform and 1.5 dimensional spectrum can effectively judge the fault type of rolling bearing and has certain engineering application value.
【作者单位】：河北金融学院信息管理与工程系;燕山大学经济管理学院;
【基金】：河北省自然科学基金资助项目(E2015502056)
【分类号】：TH133.33

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