The fast kurtogram is one of the most commonly applied methods for detecting rolling element bearing faults, and has been proven to be to be effective in most cases. However, the shortcomings of the kurtosis index limit the robustness and universality of the method, in that the kurtosis index is sensitive to single impulses with large amplitudes, and the segmentation of the spectrum is not adaptive to different signals. Moreover, fast kurtogram segments the spectrum evenly, which makes the method less adaptive. Therefore, a new diagnosis method for denoising signals, known as the VMD-Scale Space Based hoyergram, is proposed in this paper. Firstly, parameter-optimized Variation Mode Decomposition (VMD) is applied to the signal to calculate the center frequency of each sub-signal, referred to as the Intrinsic Mode Function (IMF). Secondly, the spectrum of the vibration signal is smoothed by means of scale space theory, and the local minimum between each two center frequencies is d...

中文翻译：

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基于VMD尺度的空间Hoyergram及其在滚动轴承故障诊断中的应用

快速峰图是检测滚动轴承故障的最常用方法之一，并且已被证明在大多数情况下是有效的。然而，峰度指数的缺点限制了该方法的鲁棒性和通用性，因为峰度指数对具有大振幅的单个脉冲敏感，并且频谱的分段不适用于不同的信号。此外，快速峰图将频谱均匀分​​割，这使该方法的适应性较差。因此，本文提出了一种新的信号去噪诊断方法，即VMD-Scale Space Hoyergram。首先，将参数优化的变化模式分解（VMD）应用于信号以计算每个子信号的中心频率，称为本征模式函数（IMF）。其次，