The research on detection power quality sensitive to noise characteristics , EEMD in the power quality disturbance signal noise inherent in the process IMF , components select the issue .This paper put the issue named MEEMD that can detection of power quality disturbance signal. First , the signal characteristics of the adaptive selection of white noise amplitude K and the overall average value M. the white noise is added to the original signal to form a new signal to be decomposed. Then using the EMD new signal obtained IMF. IMF calculated correlation function , according to the correlation coefficient of IMF select the appropriate component of the reconstructed signal. Use Hilbert transform the original purpose of the detected signal. The simulation results show the effectiveness and feasibility of this method and existing EMD, comparative results EEMD parameter selection methods show the advantages of the method.%针对电能质量检测对噪声敏感的特点,集合经验模态分解(Ensemble Empirical Mode Decom-position,EEMD)对电能质量扰动信号检测过程中存在模态混叠,以及EEMD对固有模式函数(In-trinsic Mode Functions,IMF)分量的选取问题,提出了一种改进集合经验模态分解(Ensemble Empiri-cal Mode Decomposition,EEMD)的电能质量扰动信号检测方法.根据信号特点自适应的选取信号白噪声系数C值及总体平均数N值,将白噪声加入到原始信号形成新的待分解信号,再采用EMD分解新信号,计算各IMF分量的相关系数,根据相关系数选择相应的IMF分量重构信号,对其进行希尔伯特变换(Hilbert-Hang Transform,HHT),最终达到对原信号检测的目的.仿真结果验证了该方法的有效性和可行性与现有EMD、EEMD参数选取方法的对比结果表明了该方法的优势.
展开▼