Korbicz, Józef - ed. ; Sauter, Dominique - ed.
Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA, which is based on the estimation of the sample mean and covariance matrix of the data, is very sensitive to outliers in the training data set. Usually robust principal component analysis is applied to remove the effect of outliers on the PCA model. In this paper, a fast two-step algorithm is proposed. ; First, the objective was to find an accurate estimate of the covariance matrix of the data so that a PCA model might be developed that could then be used for fault detection and isolation. A very simple estimate derived from a one-step weighted variance-covariance estimate is used (Ruiz-Gazen, 1996). This is a "local" matrix of variance which tends to emphasize the contribution of close observations in comparison with distant observations (outliers). ; Second, structured residuals are used for multiple fault detection and isolation. These structured residuals are based on the reconstruction principle, and the existence condition of such residuals is used to determine the detectable faults and the isolable faults. The proposed scheme avoids the combinatorial explosion of faulty scenarios related to multiple faults to be considered. Then, this procedure for outliers detection and isolation is successfully applied to an example with multiple faults.
Zielona Góra: Uniwersytet Zielonogórski
AMCS, volume 18, number 4 (2008) ; click here to follow the link
Biblioteka Uniwersytetu Zielonogórskiego
Apr 8, 2024
Apr 8, 2024
30
https://zbc.uz.zgora.pl/publication/88503
Edition name | Date |
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Fault detection and isolation with robust principal component analysis | Apr 8, 2024 |
Puig, Vicenç Korbicz, Józef - red. Uciński, Dariusz - red.
Gangl, Simon Mongus, Domen Žalik, Borut Kowal, Marek - red. Korbicz, Józef - red.
Ichalal, Dalil Marx, Benoît Ragot, José Maquin, Didier Korbicz, Józef - red. Uciński, Dariusz - red.
Orjuela, Rodolfo Marx, Benoît Ragot, José Maquin, Didier Korbicz, Józef - red. Uciński, Dariusz - red.
Yoshizawa, Shintaro Helmke, Uwe Starkov, Konstantin Fliess, Michel - ed. Jai, Abdelhaq El - ed.
Borowiak, Klaudia Zbierska, Janina Budka, Anna Kayzer, Dariusz Kuczyński, Tadeusz - red.
Yang, Hao Jiang, Bin Cocquempot, Vincent Lu, Lingli Korbicz, Józef - red. Uciński, Dariusz - red.
Bonfé, Marcello Castaldi, Paolo Mimmo, Nicola Simani, Silvio Korbicz, Józef - red. Uciński, Dariusz - red.