Abstract
Canonical correlation analysis(CCA) could be utilized for analyzing a linear static process when the input-output relationship is explicitly existing. Based on the canonical variates obtained by the CCA method, a novel fault detection approach can be designed by resembling the principal component analysis (PCA) and the partial least squares (PLS) approaches. However, in this paper, the traditional CCA approach will be shown insensitive to one kind of fault, i.e., multiplicative fault (change). Based on this motivation, a modified statistic based on the local approach is introduced to help CCA approach further improve its acceptance for detecting multiplicative changes in the static processes. The new method will be verified through its application to a continuous stirred tank heater (CSTH).
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