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A novel method for the optimal band selection for vibration signal demodulation and comparison with the Kurtogram

机译:一种用于振动信号解调的最佳频带选择的新方法,并与Kurtogram比较

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The narrowband amplitude demodulation of a vibration signal enables the extraction of components carrying information about rotating machine faults. However, the quality of the demodulated signal depends on the frequency band selected for the demodulation. The spectral kurtosis (SK) was proved to be a very efficient method for detection of such faults, including defective rolling element bearings and gears [1]. Although there are conditions, under which SK yields valid results, there are also cases, when it fails, e.g. in the presence of a relatively strong, non-Gaussian noise containing high peaks or for a relatively high repetition rate of fault impulses.rnIn this paper, a novel method for selection of the optimal frequency band, which attempts to overcome the aforementioned drawbacks, is presented. Subsequently, a new tool for presentation of results of the method, called the Protrugram, is proposed. The method is based on the kurtosis of the envelope spectrum amplitudes of the demodulated signal, rather than on the kurtosis of the filtered time signal. The advantage of the method is the ability to detect transients with smaller signal-to-noise ratio comparing to the SK-based Fast Kurtogram. The application of the proposed method is validated on simulated and real data, including a test rig, a simulated signal, and a jet engine vibration signal.
机译:振动信号的窄带幅度解调使得能够提取承载有关旋转机械故障信息的组件。但是,解调信号的质量取决于为解调选择的频带。光谱峰度(SK)被证明是检测此类故障(包括有缺陷的滚动元件轴承和齿轮)的一种非常有效的方法[1]。尽管在某些情况下,SK可以得出有效的结果,但在某些情况下,它会失败,例如。在存在较高峰值的较高非噪声噪声或较高的故障脉冲重复率的情况下。本文提出了一种用于选择最佳频带的新颖方法,该方法试图克服上述缺点。提出了。随后,提出了一种用于表示方法结果的新工具,称为Protrugram。该方法是基于解调信号的包络频谱幅度的峰度,而不是基于滤波后的时间信号的峰度。与基于SK的快速Kurtogram相比,该方法的优势在于能够以较小的信噪比检测瞬态。该方法在模拟和真实数据上得到了验证,包括试验台,模拟信号和喷气发动机振动信号。

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