Process monitoring for chemical process based on semi-supervised principal component analysis

Abstract

The performances of methods based on principal component analysis (PCA) for process monitoring can degrade quickly when the abnormal samples included in samples for modeling. However, the labels of the process samples are difficult to obtain. Usually, we have many unlabelled samples and small labeled samples. In this paper, the semi-supervised PCA (SSPCA… (More)

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