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Fault Detection and Isolation Based on MM- ICA with Application to High-speed Railway

机译:基于MM-ICA的故障检测与隔离在高速铁路中的应用

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In this paper, a new fault detection and isolation scheme based on multiple models independent component analysis (MM-ICA) is established for high-speed railway. The proposed method firstly uses independent component analysis (ICA) to extract the essential independent components (ICs). Then a novel idea, which is to construct multiple ICA models, is proposed to locate fault. The proposed method is applied to fault detection and identification in both a simple multivariate system and highspeed railway motor, and the results are compared with principal components analysis (PCA). The simulation results clearly show the power and advantages of the novel fault detection and identification method based on MM-ICA.
机译:本文提出了一种基于多模型独立分量分析(MM-ICA)的高速铁路故障检测与隔离方案。所提出的方法首先使用独立成分分析(ICA)提取必要的独立成分(IC)。然后提出了一种新颖的构想,即构造多个ICA模型来定位故障。将该方法应用于简单的多元系统和高速铁路电动机的故障检测和识别,并将结果与​​主成分分析(PCA)进行了比较。仿真结果清楚地表明了基于MM-ICA的新型故障检测与识别方法的强大功能和优势。

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