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基于时段过渡分析的多时段间歇过程质量预测(英文)
引用本文:赵露平,赵春晖,高福荣. 基于时段过渡分析的多时段间歇过程质量预测(英文)[J]. 中国化学工程学报, 2012, 20(6): 1191-1197. DOI: 10.1016/S1004-9541(12)60607-7
作者姓名:赵露平  赵春晖  高福荣
作者单位: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
基金项目: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)
摘    要: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.

关 键 词:multi-phase  transition  partial least squares  quality prediction  batch process  
收稿时间:2012-05-31

Phase Transition Analysis Based Quality Prediction for Multi-phase Batch Processes
ZHAO Luping,ZHAO Chunhui, and GAO Furong. Phase Transition Analysis Based Quality Prediction for Multi-phase Batch Processes[J]. Chinese Journal of Chemical Engineering, 2012, 20(6): 1191-1197. DOI: 10.1016/S1004-9541(12)60607-7
Authors:ZHAO Luping  ZHAO Chunhui    GAO Furong
Affiliation: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
Abstract: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.
Keywords:
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