Phase Transition Analysis Based Quality Prediction for Multi-phase Batch Processes*

Chinese Journal of Chemical Engineering ›› 2012, Vol. 20 ›› Issue (6): 1191-1197.

Phase Transition Analysis Based Quality Prediction for Multi-phase Batch Processes^*

赵露平^1,2, 赵春晖¹, 高福荣^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

收稿日期:2012-05-31 修回日期:2012-07-30 出版日期:2012-12-28 发布日期:2012-12-28
通讯作者: ZHAO Chunhui,E-mail:chhzhao@zju.edu.cn
基金资助:
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)

Phase Transition Analysis Based Quality Prediction for Multi-phase Batch Processes^*

ZHAO Luping^1,2, ZHAO Chunhui¹, 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

Received:2012-05-31 Revised:2012-07-30 Online:2012-12-28 Published:2012-12-28
Supported by:
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/Abstract

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

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.

Key words: multi-phase, transition, partial least squares, quality prediction, batch process

赵露平, 赵春晖, 高福荣. Phase Transition Analysis Based Quality Prediction for Multi-phase Batch Processes^*[J]. Chinese Journal of Chemical Engineering, 2012, 20(6): 1191-1197.

ZHAO Luping, ZHAO Chunhui, GAO Furong. Phase Transition Analysis Based Quality Prediction for Multi-phase Batch Processes^*[J]. Chin.J.Chem.Eng., 2012, 20(6): 1191-1197.

参考文献

1 Nomikos,P.,MacGregor,J.F.,"Monitoring batch processes using multiway principal component analysis",AIChE J.,40,1361-1375 (1994).
2 Nomikos,P.,MacGregor,J.F.,"Multi-way partial least squares in monitoring batch processes",Chemom.Intell.Lab.Syst.,30,97-108 (1995).
3 Venkatasubramanian,V.,Rengaswamy,R.,Kavuri,S.N.,Yin,K.,"A review of process fault detection and diagnosis Part III: Process history based methods",Comput.Chem.Eng.,27,327-346 (2003).
4 Wold,S.,Kettaneh,N.,Tjessem,K.,"Hierarchical multiblock PLS and PC models for easier model interpretation and as an alternative to variable selection",J.Chemom.,10,463-482 (1996).
5 Westerhuis,J.A.,Kourti,T.,MacGregor,J.F.,"Analysis of multiblock and hierarchical PCA and PLS models",J.Chemom.,12,301-321 (1998).
6 Choi,S.W.,Lee,I.B.,"Multiblock PLS-based localized process diagnosis",J.Process Control,15,295-306 (2005).
7 Duchesne,C.,MacGregor,C.D.,"Multivariate analysis and optimization of process variable trajectories for batch processes",Chemom.Intell.Lab.Syst.,5,125-137 (2000).
8 Chu,Y.H.,Lee,Y.H.,Han,C.,"Improved quality estimation and knowledge extraction in a batch process by bootstrapping-based generalized variable selection",Ind.Eng.Chem.Res.,43,2680-2690 (2004).
9 Lu,N.Y.,Wang,F.L.,Gao,F.R.,"Sub-PCA modeling and on-line monitoring strategy for batch processes",AIChE J.,50,255-259 (2004).
10 Lu,N.Y.,Gao,F.R.,"Stage-based process analysis and quality prediction for batch processes",Ind.Eng.Chem.Res.,44,3547-3555 (2005).
11 黱dey,C.,Cinar,A.,"Statistical monitoring of multistage,multiphase batch processes",IEEE Control Syst.Mag.,22,40-52 (2002).
12 Gabrielsson,J.,Jonsson,H.,Airiau,C.,Schmidt,B.,Escott,R.,Trygg,T.,"The OPLS methodology for analysis of multi-block batch process data",J.Chemom.,20,362-369 (2006).
13 Zhao,C.H.,Wang,F.L.,Gao,F.R.,Lu,N.Y.,Jia,M.X.,"Improved knowledge extraction and phase-based quality prediction for batch processes",Ind.Eng.Chem.Res.,47,825-834 (2008).
14 Zhao,C.H.,Wang,F.L.,Mao,Z.Z.,Lu,N.Y.,Jia,M.X.,"Quality prediction based on phase-specific average trajectory for batch processes",AIChE J.,54,693-705 (2008).
15 Zhao,C.H.,Lu,N.Y.,Wang,F.L.,Jia,M.X.,"Stage-based soft-transition multiple PCA modeling and on-line monitoring strategy for batch processes",J.Process Control,17,728-741 (2007).
16 Yao,Y.,Gao,F.R.,"Phase and transition based batch process modeling and online monitoring",J.Process Control,19,816-826 (2009).
17 Yao,Y.,Gao,F.R.,"A survey on multistage/multiphase statistical modeling methods for batch processes",Annual Reviews in Control,33,172-183 (2009).
18 Johnson,R.,Wichern,D.,Applied Multivariate Statistical Analysis,5th edition,Prentice Hall,Upper Saddle River,NJ,354-383 (2002).
19 Montgomery,D.C.,Peck,E.A.,Vining,G.,Introduction to Linear Regression Analysis,4th edition,John Wiley & Sons,New York,22-28 (2004).
20 Yang,Y.,Gao,F.R.,"Cycle-to-cycle and within-cycle adaptive control of nozzle pressures during packing-holding for thermoplastic injection molding",Polym.Eng.Sci.,39,2042-2064 (1999).
21 Yang,Y.,Gao,F.R.,"Adaptive control of the filling velocity of thermoplastics injection molding",Control Eng.Practice,8,1285-1296 (2000).
22 Lu,N.Y.,Gao,F.R.,"Stage-based online quality control for batch processes",Ind.Eng.Chem.Res.,45,2272-2280 (2006).
23 Yang,Y.,"Injection molding: from process to quality control",Ph.D.Thesis,The Hong Kong University of Science & Technology,Hong Kong (2004).

[1]	Chenyang Zhao, Yinhan Cheng, Guangfei Qu, Yongheng Yuan, Fenghui Wu, Ye Liu, Shan Liu, Junyan Li, Ping Ning. High-performance liquid-phase catalytic purification of phosphine in tail gas using Pd(II)/Cu(II) composite[J]. 中国化学工程学报, 2023, 57(5): 98-108.
[2]	Baodong Zhao, Yinglei Wang, Fulei Gao, Yajing Liu, Weixiao Liu, Feng Ding. Understanding the alkyl effect of geminal dinitropropyl ester energetic plasticizers on hydroxyl terminated polybutadiene (HTPB): Simultaneous tuning on low temperature behavior and processability[J]. 中国化学工程学报, 2023, 54(2): 364-371.
[3]	Mi Feng, Bin He, Xinyan Chen, Junli Xu, Xingmei Lu, Cai Jia, Jian Sun. Separation of chitin from shrimp shells enabled by transition metal salt aqueous solution and ionic liquid[J]. 中国化学工程学报, 2023, 53(1): 133-141.
[4]	Yuanjie Li, Qiuxiang Yin, Meijing Zhang, Ying Bao, Baohong Hou, Jingkang Wang, Jiting Huang, Ling Zhou. Characterization and structure analysis of the heterosolvate of erythromycin thiocyanate[J]. 中国化学工程学报, 2022, 44(4): 268-274.
[5]	Yichao Wu, Zhiwei Xie, Xiaofeng Gao, Xian Zhou, Yangzhi Xu, Shurui Fan, Siyu Yao, Xiaonian Li, Lili Lin. The highly selective catalytic hydrogenation of CO₂ to CO over transition metal nitrides[J]. 中国化学工程学报, 2022, 43(3): 248-254.
[6]	Shan Ni, Hongnan Qu, Huifang Xing, Zihao Xu, Xiangyang Zhu, Menglei Yuan, Meng Rong, Li Wang, Jiemiao Yu, Yanqing Li, Liangrong Yang, Huizhou Liu. Interfacial engineering of transition-metal sulfides heterostructures with built-in electric-field effects for enhanced oxygen evolution reaction[J]. 中国化学工程学报, 2022, 41(1): 320-328.
[7]	Yongqi Liu, Qiuxiang Yao, Ming Sun, Xiaoxun Ma. Selective preparation of light aromatic hydrocarbons from catalytic fast pyrolysis vapors of coal tar asphaltene over transition metal ion modified zeolites[J]. 中国化学工程学报, 2021, 35(7): 275-287.
[8]	Racheal Aigbe, Doga Kavaz. Unravel the potential of zinc oxide nanoparticle-carbonized sawdust matrix for removal of lead (II) ions from aqueous solution[J]. 中国化学工程学报, 2021, 29(1): 92-102.
[9]	Shutian Chen, Qingchao Jiang, Xuefeng Yan. Multimodal process monitoring based on transition-constrained Gaussian mixture model[J]. 中国化学工程学报, 2020, 28(12): 3070-3078.
[10]	Zhiqiang Liu, Yunxiao Lu, Jiuhui Cheng, Qiang Han, Zunjing Hu, Linlin Wang. Geomechanics involved in gas hydrate recovery[J]. 中国化学工程学报, 2019, 27(9): 2099-2106.
[11]	Quanhong Zhu, Hang Xiao, Aqiang Chen, Shujun Geng, Qingshan Huang. CFD study on double-to single-loop flow pattern transition and its influence on macro mixing efficiency in fully baffled tank stirred by a Rushton turbine[J]. 中国化学工程学报, 2019, 27(5): 993-1000.
[12]	Aihong Li, Changzhan Liu, Zhiyong Liu. A heuristic design method for batch water-using networks of multiple contaminants with regeneration unit[J]. 中国化学工程学报, 2019, 27(5): 1103-1112.
[13]	Rasheeda M. Ansari, Lolakshi K. Mahesh, Badekai Ramachandra Bhat . Cobalt Schiff base complexes: Synthesis characterization and catalytic application in Suzuki–Miyaura reaction[J]. 中国化学工程学报, 2019, 27(3): 556-563.
[14]	Li Jia, Wendan Tan. Just-in-time learning based integrated MPC-ILC control for batch processes[J]. Chinese Journal of Chemical Engineering, 2018, 26(8): 1713-1720.
[15]	Yongyong Hui, Xiaoqiang Zhao. Batch process monitoring based on WGNPE-GSVDD related and independent variables[J]. Chinese Journal of Chemical Engineering, 2018, 26(12): 2549-2561.

Phase Transition Analysis Based Quality Prediction for Multi-phase Batch Processes^*

Phase Transition Analysis Based Quality Prediction for Multi-phase Batch Processes^*

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价