基于DT-CWT自适应Teager能量谱的轴承早期故障诊断

发布时间：2018-01-31 04:46

本文关键词： 滚动轴承双树复小波频带幅值熵 Teager能量谱自适应共振带提取故障诊断　出处：《振动.测试与诊断》2017年04期 　论文类型：期刊论文

【摘要】：针对滚动轴承早期故障特征信息难以识别以及带通滤波器参数设置依赖使用者经验等造成共振带不能有效确定并自适应提取的问题,提出了频带幅值熵的概念。在此基础上,将双树复小波变换和Teager能量谱结合,提出了基于双树复小波自适应Teager能量谱的早期故障诊断方法。首先,利用双树复小波将采集到的振动信号分解为不同频带的子信号,并计算各子带的频带幅值熵;然后,将熵值按升序排列后依次作为阈值,提取频带幅值熵大于阈值的子带,依据峭度指标确定最佳阈值,从而自适应并且有效地提取出共振带;最后,对共振带进行Teager能量谱分析,即可从中准确地识别出轴承的故障特征频率。通过信号仿真与实验数据分析验证了该方法的有效性。
[Abstract]:Due to the difficulty of identifying the early fault feature information of rolling bearing and the dependence of user experience on the parameter setting of band-pass filter, the resonance band can not be effectively determined and self-adaptively extracted. The concept of frequency band amplitude entropy is put forward, and on this basis, the dual tree complex wavelet transform and Teager energy spectrum are combined. An early fault diagnosis method based on bitree complex wavelet adaptive Teager energy spectrum is proposed. Firstly, the collected vibration signal is decomposed into sub-signals in different frequency bands by using bitree complex wavelet. The amplitude entropy of each sub-band is calculated. Then, the entropy value is arranged in ascending order as the threshold value, the sub-band whose amplitude entropy is larger than the threshold value is extracted, and the optimal threshold is determined according to the kurtosis index, and the resonance band is extracted adaptively and effectively. Finally, the fault characteristic frequency of the bearing can be accurately identified by the Teager energy spectrum analysis of the resonance band, and the effectiveness of the method is verified by signal simulation and experimental data analysis.
【作者单位】：内蒙古科技大学机械工程学院;
【基金】：国家自然科学基金资助项目(21366017) 内蒙古自治区自然科学基金资助项目(2012MS0717)
【分类号】：TH133.33
【正文快照】： 引言滚动轴承在各种工业现场中被广泛应用,当轴承出现故障时,设备及其他零件很容易受到毁坏,这会导致人员和经济遭受巨大损失。因此,在故障刚刚萌发、程度尚轻微时就能够准确、有效地检测出轴承元件故障对预防事故的发生具有重要意义[1]。当滚动轴承出现点蚀、剥落和裂纹等局

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