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Fault detection in industrial processes using canonical variate analysis and dynamic principal component analysis

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, no. 1 (2000): 81-93

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Principal component analysis (PCA) is a well-known data dimensionality technique that has been used to detect faults during the operation of industrial processes. Dynamic principal component analysis (DPCA) and canonical variate analysis (CVA) are data dimensionality techniques which take into account serial correlations, but their effect...更多

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