频移经验模态分解在低频振荡参数提取中的应用

Frequency Shift Empirical Mode Decomposition for Extracting Low Frequency Oscillation Parameters

当信号中2个单频分量的频率在2倍频内时,经验模态分解(EMD)无法将2个分量分解开。为提高EMD的频率分辨率,提出了基于信号调制的频移EMD算法。此方法增大了信号中组成分量的频率比,使之达到EMD可分的程度。将该方法应用于电力系统低频振荡模态参数的提取,能较好地提取2倍频范围内的低频振荡模态分量的瞬时频率、瞬时幅值、相位及阻尼比等参数,数值仿真和实例分析均表明了该方法的有效性。

As two individual components in a signal with frequencies within an octave is usually indecomposable by the normal empirical mode decomposition（EMD） method,to improve the frequency resolution,a method based on frequency shift EMD capable of enlarging the component frequency difference to reach the EMD identifying level is presented.In its application to extracting model parameters of low frequency oscillation in the power system,this method proves fairly effective in extracting model parameters in a signal with frequencies within an octave,such as,instantaneous frequency,instantaneous amplitude,phase and damping ratio,etc,as shown by numerical simulation and case analysis results.