title: [Fermentation process monitoring and fault detection based on dynamic MPCA].
abstract: A dynamic multiway principle component analysis for on-line batch process monitoring and fault detection was proposed. It integrates the time-lagged windows of process dynamic behavior with the multiway principle component analysis (MPCA). Using multi-model instead of single model, the dynamic MPCA approach emphasizes particularly on-line process performance monitoring and fault defecting. On-line process monitoring of cephalosporin C fermentation was studied, the results demonstrate that the dynamic MPCA method is able to efficiently monitor performance of the fermentation process and exactly detect faults which results in extraordinary behavior of processes.
authors.affiliation: Department of Automation, Shanghai Second Polytechnic University, Shanghai 201209, China. zhifeng.wang@163.com
authors.forename: Zhi-Feng
authors.initials: ZF
authors.lastname: Wang
authors.forename: Jing-Qi
authors.initials: JQ
authors.lastname: Yuan
mesh_terms: D002511:Cephalosporins / Q000096:biosynthesis*; D005285:Fermentation; D005544:Forecasting; D017711:Nonlinear Dynamics; D025341:Principal Component Analysis / Q000379:methods*
chemical_list: D002511:Cephalosporins; C025163:cephalosporin C