摘要
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.
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 resalos. demonstrate the feasibility of the proposed approach.
出处
《控制与决策》
EI
CSCD
北大核心
2005年第12期1429-1433,共5页
Control and Decision
关键词
独立源分析
协方差
振荡检测与诊断
故障诊断
Independent component analysis
Auto-covariance
Oscillation detection and diagnosis
Fault diagnosis
