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《中国化学工程学报(英文版)》 2012-06
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Phase Transition Analysis Based Quality Prediction for Multi-phase Batch Processes

ZHAO Luping 1,2 , ZHAO Chunhui 1, ** and GAO Furong 1,2 1 State Key Laboratory of Industrial Control Technology, Department of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China 2 Department of Chemical and Biomolecular Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China  
Batch processes are usually involved with multiple phases in the time domain and many researches on process monitoring as well as quality prediction have been done using phase information. However, few of them consider phase transitions, though they exit widely in batch processes and have non-ignorable impacts on product qualities. In the present work, a phase-based partial least squares (PLS) method utilizing transition information is proposed to give both online and offline quality predictions. First, batch processes are divided into several phases using regression parameters other than prior process knowledge. Then both steady phases and transitions which have great influences on qualities are identified as critical-to-quality phases using statistical methods. Finally, based on the analysis of different characteristics of transitions and steady phases, an integrated algorithm is developed for quality prediction. The application to an injection molding process shows the effectiveness of the proposed algorithm in comparison with the traditional MPLS method and the phase-based PLS method.
【Fund】: Supported by Guangzhou Nansha District Bureau of Economy & Trade Science & Technology Information Project (201103003);; the Fundamental Research Funds for the Central Universities (2012QNA5012);; Project of Education Department of Zhejiang Province (Y201223159);; Technology Foundation for Selected Overseas Chinese Scholar of Zhejiang Province (J20120561)
【CateGory Index】: TP274
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