基于有限元算法优化EEMD的直流信号纹波分解方法

DC signal ripple decomposition method based on EEMD⁃FEM

为解决直流电能计量时不能对直流中纹波信号进行准确计量的问题,文中提出利用有限元算法优化集合经验模态分解(EEMD⁃FEM)的方法对直流中的纹波信号进行分解。利用有限元法对直流电压信号进行预处理,根据信号变化量进行有限元划分并求积分均值点,以保存信号特征并降低极值点个数,提升EEMD算法分解的收敛速度和准确度。为提取直流电压信号,搭建直流电能算法验证平台对直流电压信号进行仿真,得出相比于EEMD的分解方法,EEMD⁃FEM算法分解出的直流分量变化量保持在0.01%,分解出的直流信号稳定;IMF分量的电压幅值总体维持在0.01~0.001 V。结果表明,有限元算法优化的EEMD算法对直流信号的分解效果更好,在分解有用IMF分量、分离直流分量以及减少IMF分量个数上更优,能够达到理想的分解效果。

In order to solve the problem that the ripple signal in DC cannot be accurately measured in the DC energy measurement,a method using finite element method to optimize the ensemble empirical mode decomposition(EEMD⁃FEM)is proposed to decompose the ripple signal in DC.The DC voltage signal is preprocessed by means of FEM,and the finite element division is performed according to the signal variation and the integral mean value point is calculated to save the signal characteristics and reduce the number of extreme points,which improves the convergence speed and accuracy of the EEMD algorithm decomposition.In order to extract the DC voltage signal,a verification platform of DC power algorithm is built to simulate the DC voltage signal.It can be seen that in comparison with the EEMD decomposition method,the variation of the DC component decomposed by the EEMD⁃FEM algorithm remains at 0.01%,and the decomposed DC signal is stable;the voltage amplitude of the IMF component is generally maintained at 0.01~0.001 V.The results show that the EEMD algorithm optimized by FEM has better decomposition effect on the DC signal,and is better in decomposing the useful IMF component,separating the DC component and reducing the number of IMF components,which can achieve the ideal decomposition effect.