Performance Monitoring Based on Characteristic Subspace

Abstract

In the operation and control of chemical process, automatic data logging systems produce large volumes of data. It is important for supervising daily operation that how to exploit the valuable information about normal and abnormal operation, significant disturbance and changes in operational and control strategies. In this paper, principal component analysis (PCA) is clarified its essence from the view of space, and every different subspace represents different operational mode and process performance. Based on that, distance between two subspaces is calculated to evaluate the difference between them. The method is illustrated by a case study of a fluid catalytic cracking unit (FCCU) reactor-regenerator system.