Online Monitoring of Batch Process using Sub-phase based Principal Component Analysis

摘要：

　　Methods based on multivariate statistical projection analysis have been widely applied for batch processes monitoring.However,conventional methods are linear ones that can only model linear combinations of variables and most batch processes are non-linearity.Traditionally,in process modeling,two solutions for non-linearity have been implemented: non-linear models and local linear models.In this paper,a novel methodology named Sub-phase based Principal Component Analysis(SPPCA),which integrates methods of operation phase detection and a novel multi-way principal component analysis(MPCA),is approached.A case study from a simulated fed-batch penicillin cultivation process indicates the efficacy of approach.

关键词： Batch process monitoring principal component analysis AP clustering sub-phase modelling

作者: LIU Xin WANG Pu GAO Xuejin QI Yongsheng

作者单位: College of Electronic Information and Control Engineering,Beijing University of Technology,Beijing 1 College of Electric Power,Inner Mongolia University of Technology,Huhhot 010051,China

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 5150-5155

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）