Improved multi-stage online monitoring strategy for batch process

• Main Authors: Li, Chunlei, Wang, Pu, Gao, Xuejin
• Format: Conference Proceeding
• Language: English
• Subjects: batch process; Batch production systems; Computer simulation; Conferences; Criteria; Data models; Fermentation; Load modeling; Monitoring; operation stage separation; Principal component analysis; principal component analysis (PCA); Separation; Similarity; Solid modeling; Strategy
• ISSN: 2161-2927; 1934-1768
• DOI: 10.1109/ChiCC.2016.7554432

In order to accurately divide the stages and improve the sensitivity of fault diagnosis, a new method is proposed for the sub-stage separation of batch process. First, based on the changes in the load matrices, which reveal the change of data direction, rough separation of operation sub-stage is executed. According to the criterion of minimum similarity distances, time-slice matrices are sorted to realize separation of operation sub-stage more particularly for batch process. The two-step separation method considers evolvement of the underlying process behavior. Therefore, the method can accurately divide the stages. Finally, multi-way principal component analysis (MPCA) model is established for each phase and applied to on-line monitoring for batch process. The proposed method is applied to penicillin fermentation process, the simulation results show that the multistage-based MPCA method has better performance, compared with the traditional MPCA.