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A Denoising Method of Vortex Flowmeter Signal in Oscillatory Flow Based on Hilbert Huang Transformation

机译:基于希尔伯特·黄变换的涡街流量计涡流去噪方法

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Hilbert-Huang Transform (HHT) is a new and effective method of analysing nonlinear and nonstationary time series. With this new method any complicated signal could be decomposed into a finite number of Intrinsic Mode Functions (IMFs). In this paper, HHT is applied to the vortex flow signal in oscillatory flow. First, the vortex flow noisy signal is decomposed into several IMFs using the efficient and adaptive Empirical Mode Decomposition(EMD). Then the high-frequency components filtered by EMD-scale are used for de-noising. And finally, a signal is reconstructed with both the high-frequency components after EMD-scale filtering and the low-frequency components. The reconstruction signal is a de-noising signal. This signal simulation test showed that this method to deal with the vortex flow signal in oscillatory flow is easy and effective.
机译:Hilbert-Huang变换(HHT)是分析非线性和非平稳时间序列的一种新的有效方法。使用这种新方法,可以将任何复杂的信号分解为有限数量的本征函数(IMF)。本文将HHT应用于振荡流中的涡流信号。首先,使用高效和自适应的经验模态分解(EMD)将涡流噪声信号分解为几个IMF。然后,将经过EMD标度滤波的高频分量用于去噪。最后,信号经过EMD规模滤波后的高频分量和低频分量进行重构。重建信号是消噪信号。信号仿真测试表明,该方法处理振荡流中的涡流信号是简便有效的。

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