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Fault Diagnosis of Rolling Bearing based on EMD Combined with HHT Envelope and Wavelet Spectrum Transform

机译:基于EMD结合HHT信封和小波谱变换的滚动轴承故障诊断

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摘要

A novel method based on Hilbert Transform (HT) and Empirical Mode Decomposition (EMD) algorithm is proposed in this paper, which separates time series into intrinsic mode functions (IMFs) with different time scales and applies the Hilbert transformation for every IMF to obtain the Hilbert spectrum. Firstly, relevant theories of the proposed method are introduced. Then, based on these theoretical introductions, the fault vibration signals of rolling bearing are dealt with related algorithm. The research results demonstrate that the characteristic frequency of bearing fault can be obtained by proposed method, which is more effective compared with existing algorithm.
机译:本文提出了一种基于Hilbert变换(HT)和经验模式分解(EMD)算法的新方法,其将时间序列分开到具有不同时间尺度的内在模式功能(IMF),并为每个IMF应用HILBERT转换以获得希尔伯特光谱。首先,介绍了所提出的方法的相关理论。然后,基于这些理论介绍,滚动轴承的故障振动信号与相关算法进行了处理。研究结果表明,通过所提出的方法可以获得轴承故障的特征频率,与现有算法相比更有效。

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