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Principal component analysis (PCA) has been effectively applied in fault detection and in diagnosis of industrial processes to deal with a large number of variables with high correlations. However, normal changes often occur in real process, which always result in false alarms for a fixed-model approach. The authors' research is focused on the traits of normal process changes, which are classified...
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