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Time-varying waveform analysis for power transformer protection using frequency shift Empirical mode decomposition

机译:基于频移的电力变压器保护时变波形分析经验模态分解

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Empirical mode decomposition (EMD) method is a novel time-frequency analysis tool to analyse non-stationary signals, which decomposes the signal concerned into intrinsic mode functions (IMFs) modulated in terms of both amplitude and frequency. The original version of EMD, however, suffers from an algorithm difficulty to separate two individual components, frequencies of which are within an octave. To improve the frequency resolution, a signal pre-processing method is used to shift the frequencies apart based on signal communication theory. This proposed frequency shift EMD has been successfully applied to extract modal parameters of low frequency oscillations for power systems. In this paper, this method is used to analyse the transient signals (inrush current) in the field of power transformer protection. Comparing with low frequency oscillation signals, these signals include more frequency components with faster dynamics. Numerical simulations are conducted to verify the frequency shift EMD. The results show that this method is adequate for time-varying waveform analysis for power transformer protection, and with the information provided by this frequency shift EMD, more robust protection schemes for power transformer could be proposed.
机译:经验模态分解(EMD)方法是一种新颖的时频分析工具,用于分析非平稳信号,该信号将相关信号分解为根据振幅和频率进行调制的固有模式函数(IMF)。但是,EMD的原始版本在算法上难以分离两个单独的分量,其频率在一个八度音程内。为了提高频率分辨率,基于信号通信理论,使用信号预处理方法将频率分开。提出的移频EMD已成功应用于提取电力系统低频振荡的模态参数。在本文中,该方法用于分析电力变压器保护领域中的瞬态信号(浪涌电流)。与低频振荡信号相比,这些信号包含更多具有更快动态特性的频率分量。进行数值模拟以验证频移EMD。结果表明,该方法适用于电力变压器保护的时变波形分析,利用该频移EMD提供的信息,可以提出更鲁棒的电力变压器保护方案。

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