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• W4244488411 abstract "In this paper, a new approach to fault detection and diagnosis that is based on correspondence analysis (CA) is proposed. CA is a powerful multivariate technique based on the generalized singular value decomposition. The merits of using CA lie in its ability to depict rows as well as columns as points in the dual lower dimensional vector space. CA has been shown to capture association between various features and events quite effectively. The key strengths of CA, for fault detection and diagnosis, are validated on data involving simulations as well as experimental data obtained from a laboratory-scale setup." @default.
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• W4244488411 date "2005-12-03" @default.
• W4244488411 modified "2023-09-27" @default.
• W4244488411 title "Fault Detection and Isolation Using Correspondence Analysis" @default.
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• W4244488411 doi "https://doi.org/10.1021/ie058033g" @default.
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