Nonlinear partial least square (NPLS) methods with generalized likelihood ratio test (GLRT) for fault detection and diagnosis of chemical processes
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We presented the problem of fault detection using kernel partial least square (PLS) -based generalized likelihood ratio test (GLRT) and neural net partial least square (PLS) -based GLRT. TEP results demonstrate the effectiveness of the KPLS -based GLRT technique for detection of multiple faults with low false alarm rate and early fault detection KPLS regression model is used to predict concentration of the product from online process variable.