Adaptive Monitoring Based on Independent Component Analysis for Multiphase Batch Processes with Limited Modeling Data

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• 作者：Chunhui Zhao ; Fuli Wang ; Zhizhong Mao ; Ningyun Lu ; Mingxing Jia
• 刊名：Industrial & Engineering Chemistry Research
• 出版年：2008
• 出版时间：May 7, 2008
• 年：2008
• 卷：47
• 期：9
• 页码：3104 - 3113
• 全文大小：166K
• 年卷期：v.47,no.9(May 7, 2008)
• ISSN：1520-5045

文摘

An adaptive monitoring method based on multiphase independent component analysis (ICA), termed AMPICA,is proposed for batch processes of long duration. Starting from limited modeling batches, the local processcorrelation structures are explored and thus multiple phase-specific models are developed, where each phasepattern can be faithfully approximated by different sub-ICA models. Then an adaptive updating strategy isadopted to accommodate more underlying process information and normal batch-to-batch slow-varyingbehaviors with the accumulation of new batch data. The idea and algorithm are illustrated with respect to thetypical data collected from a benchmark simulation of fed-batch penicillin fermentation production. Thesimulation results show that the proposed method provides a new feasible statistical analysis solution formodeling and monitoring problems with limited data in long-cycle batch processes.