基于EMD结合Choi-Williams分布的暂态电能质量扰动检测

W. Liu, Xiaoting Guo
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引用次数: 2

摘要

为了抑制Cohen类二次时频分布中的交叉项干扰,提出了一种基于经验模态分解(EMD)和Choi-Williams分布的方法。该方法在频域通过EMD将时域信号分解为固有模态函数(IMFs)。该算法剔除EMD产生的假分量后计算Cohen类分布,然后将IMFs的结果与原始信号线性叠加,重构原始信号的Cohen类分布。仿真结果表明,该方法能有效抑制Cohen类分布的交叉项,保证Cohen类分布时频集中,提取干扰特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of transient power quality disturbances based EMD combined with Choi-Williams distribution
To suppress the cross terms interference in the Cohen class quadratic time-frequency distribution, a method based on empirical mode decomposition (EMD) and Choi-Williams distribution is proposed. In this method, the time domain signal is decomposed into intrinsic mode functions (IMFs) by EMD in frequency domain. It calculates Cohen class distribution after deleting the false components generated by EMD, and then the Cohen class distribution of original signal is reconstructed by superposing the results of IMFs to the original signal linearly. The simulation results show that the method is effective to suppress the cross terms of Cohen class Distribution, ensure Cohen class Distribution time-frequency concentration, and extract features of disturbance.
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