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An Improved HHT Method and Its Application in Fault Diagnosis of Roller Bearing

机译:一种改进的HHT方法及其在滚子轴承故障诊断中的应用

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Hilbert-Huang transform (HHT) is a very effective time-frequency analysis method, but it has some disadvantages. For example, the dense modal signal cannot be decomposed completely, and redundancy intrinsic mode functions (IMFs) are easy emerging at low frequency, which will cause the distortion of the processing results. In view of the above questions, this study applies the wavelet packet transform for denoising before HHT for improving the dense modal problem, and applies the correlation coefficient method to eliminate the redundancy IMF. The fault diagnostic case of roller bearing shows the effectiveness of the proposed method.
机译:Hilbert-Huang变换(HHT)是一种非常有效的时频分析方法,但它有一些缺点。例如,密集模态信号不能完全分解,并且冗余的内在模式功能(IMF)在低频时易于出现,这将导致处理结果的失真。鉴于上述问题,本研究将小波包变换应用于HHT之前用于改善密集模态问题,并应用相关系数方法来消除冗余IMF。滚子轴承的故障诊断情况显示了该方法的有效性。

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