Online Batch Process Monitoring Based on Just-in-Time Learning and Independent Component Analysis

A new method was developed for batch process monitoring in this paper.In the developed method,just-in-time learning(J1TL) and independent component analysis(ICA) were integrated to build JITL-ICA monitoring scheme.JITL was employed to tackle with the characteristics of batch process such as inherent timevarying dynamics,multiple operating phases,and especially the case of uneven length stage.According to new coming test data,the most correlated segmentation was obtained from batch-wise unfolded training data by JITL.Then,ICA served as the principal components extraction approach.Therefore,the non-Gaussian distributed data can also be addressed under this modeling framework.The effectiveness and superiority of JITL-ICA based monitoring method was demonstrated by fed-batch penicillin fermentation.

A new method was developed for batch process monitoring in this paper. In the devdopad method, just-in-time learning （ JITL ） and independent component analysis （ICA） were integrated to build JITL-ICA monitoring scheme. JITL was employed to tackle with the characteristics of batch process such as inherent time- varying dynamics, multiple operating phases, and especially the case of uneven length stage. According to new coming test data, the most correlated segmentation was obtained from batch-wise unfolded training data by JITL. Then, ICA served as the principal components extraction approach. Therefore, the non.Gaussian distributed data can also be addressed under this modeling framework. The effectiveness and superiority of JITL-ICA based monitoring method was demonstrated by fed-batch penicillin fermentation.