基于协方差ICA分析的多重振荡源分离方法

提出一种新的基于协方差独立源分析（ICA）的多重振荡源分离定位方法.把控制系统中受到振荡干扰的过程数据变换到协方差函数,利用ICA分析的方法进行多重振荡源分离.通过仿真实验对比分析,指出其他时域主元分析（PCA） 、时域ICA、协方差PCA等方法的不足,而协方差ICA分析能够准确地分离并定位多重振荡干扰源.仿真结果表明该方法是可行的.

ICA on Auto-covariance Approach to Multi-oscillation Isolation

A novel method based on auto-covariance independent component analysis(ICA) for multi-oscillation isolation and localization is proposed.The auto-covariance dataset,calculated from perturbed oscillatory operation data in process control system,is analyzed for the aimed tasks.Simulation test and comparison analysis between simulated sources and analysis results show that ICA on auto-covariance is capable of isolating and localizing multiple oscillatory sources accurately,whilst other approaches,such as those based on time-domain principal component analysis(PCA),time-domain ICA or PCA on auto-covariance,are lack of such capabilities. Simulation results demonstrate the feasibility of the proposed approach.