基于独立分量分析的EMD模态混叠消除方法研究

针对经验模态分解(empirical mode decomposition,EMD)算法中存在的模态混叠现象,提出一种应用独立分量分析进行模态混叠消除的新方法.首先应用形态学滤波方法将信号中的噪声予以消除,减少由于噪声因素造成的模态混叠现象.然后将信号进行EMD分解,获得不同的IMF分量,将存在模态混叠成分的IMF分量进行相空间重构,利用基于峭度最大化的独立分量分解算法实现混叠成分的分离,仿真分析和工程应用的结果表明,所提方法能有效地消除EMD分解过程中的模态混叠现象.

Study on the method for eliminating mode mixing of empirical mode decomposition based on independent component analysis

Aiming at the existing problem of mode mixing in empirical mode decomposition(EMD),a new method based on independent component analysis(ICA) is proposed.Firstly,the morphological filtering method is used to remove noise and reduce the mode mixing caused by noise factor.Then,the EMD algorithm is used to decompose the signal into different IMF components,and the IMF components that have the problem of mode mixing are selected and reconstructed in the phase space.Finally,the ICA algorithm based on the kurtosis maximization is adopted to assume the independence among the sources and achieve the separation of the overlapped components.The results of simulation analysis and engineering application show that the proposed method can effectively eliminate the mode mixing in EMD.