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As an effective nonlinear dynamic data analysis tool, kernel slow feature analysis (KSFA) has achieved great success in continuous process monitoring field during recent years. However, its application to batch process monitoring is unexploited, which is a more challenging task because of the complicated characteristics of batch process data. In this paper, we propose a novel batch process monitoring...
Locality preserving projection (LPP) is a newly emerging fault detection method which can discover local manifold structure of a data set to be analyzed, but its linear assumption may lead to monitoring performance degradation for complicated nonlinear industrial processes. In this paper, an improved LPP method, referred to as sparse kernel locality preserving projection (SKLPP) is proposed for nonlinear...
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