Window-Based Stepwise Sequential Phase Partition for Nonlinear Batch Process Monitoring

作者：Liu, Jingxiang; Liu, Tao^*; Zhang, Jie

来源：Industrial & Engineering Chemistry Research, 2016, 55(34): 9229-9243.

DOI：10.1021/acs.iecr.6b01257

• PRINCIPAL COMPONENT ANALYSIS
• QUALITY PREDICTION
• FAULT-DETECTION
• PCA
• IDENTIFICATION
• FERMENTATION
• MODEL
• STRATEGY
• MPCA

In this paper, a window,based stepwise sequential phase partition method is proposed to improve monitoring performance for nonlinear batch processes with multiphase operations. The three-dimensional information matrix Of batch operation is unfolded and normalized in the batch-wise direction to facilitate establishing the kernel principal component analysis (KPCA) models for phase partition. A moving window is introduced to improve the partition performance, with respect to the process dynamics and time sequence for operation. Consequently, phase partition algorithms are developed for even- and uneven-length batch processes, respectively. Moreover, a traversal algorithm is given to determine the optimal choice of the KPCA parameters and the window size for phase partition. A numerical case and two industrial multiphase processes of injection molding and penicillin fermentation are used to demonstrate the effectiveness and merit of the proposed phase partition method.

• 出版日期2016-8-31
• 单位大连理工大学