Title :
Process monitoring based on canonical variate analysis
Author :
Yi Wang ; Seborg, Dale E. ; Larimore, Wallace E.
Author_Institution :
Dept. of Chem. Eng., Univ. of California, Santa Barbara, Santa Barbara, CA, USA
Abstract :
A new process monitoring strategy is proposed based on canonical variate analysis (CVA). State-space models are identified from input/output data collected over different time periods, and then an optimal test of hypothesis concerning process change is computed by comparing the respective model fits, using the Akaike Information Criterion. The new process monitoring strategy is illustrated in a simulation example, a continuous tank reactor (CSTR) problem.
Keywords :
chemical reactors; process monitoring; state-space methods; statistical testing; Akaike information criterion; CSTR problem; CVA; State-space models identified; canonical variate analysis; continuous tank reactor problem; input/output data collection; optimal hypothesis testing; process change; process monitoring; process monitoring strategy; time periods; Chemical reactors; Computational modeling; Data models; Monitoring; Noise; Standards; State-space methods; Canonical Variate Analysis; Process Monitoring;
Conference_Titel :
Control Conference (ECC), 1997 European
Conference_Location :
Brussels
Print_ISBN :
978-3-9524269-0-6
