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• W2023659835 abstract "A novel method which integrates mutual information (MI) with weighted independent component analysis (MI-WICA) is proposed to highlight useful information for non-Gaussian process monitoring. Since the traditional independent component analysis (ICA) may not function well for non-Gaussian process monitoring, the MI-WICA uses MI technology to evaluate the importance of each independent component (IC) within a moving window, and then set different weighting values on the selected ICs to highlight the fault information for fault detection. The proposed method is applied to a simple multivariate process and the Tennessee Eastman benchmark process, and process simulation results demonstrate that the method is superior to those of the regular principal component analysis, ICA methods." @default.
• W2023659835 created "2016-06-24" @default.
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• W2023659835 date "2014-01-01" @default.
• W2023659835 modified "2023-09-23" @default.
• W2023659835 title "Fault Detection in Non-Gaussian Processes Based on Mutual Information Weighted Independent Component Analysis" @default.
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• W2023659835 doi "https://doi.org/10.1252/jcej.13we180" @default.
• W2023659835 hasPublicationYear "2014" @default.
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