Monitoring and Quality Prediction of CPLS Batch Process Based on Kernel Entropy Projection

doi:10.3969/j.issn.1003-9015.2018.05.026

	Monitoring and Quality Prediction of CPLS Batch Process Based on Kernel Entropy Projection
	Zhao, Xiao-Qiang1,2,3 ; Zhou, Wen-Wei 1,2; Hui, Yong-Yong 1,2
	2018-10-01
发表期刊	Gao Xiao Hua Xue Gong Cheng Xue Bao/Journal of Chemical Engineering of Chinese Universities
ISSN	10039015
卷号	32 期号:5 页码:1186-1193
摘要	A "multi-way Gaussian mixture model-concurrent kernel entropy projection to latent structures" (MGMM-CKEPLS) algorithm was proposed to solve problems of nonlinearity, multimode and quality prediction of batch process. Low-dimension nonlinear data was first projected into high-dimensional kernel feature space by kernel entropy projection. Principal components were obtained by the size of Renyi entropy contribution, which can reduce principal component numbers and overcome the problem of computational complexity of traditional kernel methods. Data of each mode was then obtained by GMM, and CPLS models were established for different modes, which was more consistent with actual batch processes by considering the difference between each process. Finally, unified monitoring statistics were integrated to achieve online monitoring and quality prediction by modal weight coefficients. The model was verified in penicillin fermentation process and the results show that the proposed algorithm has better online monitoring effectiveness and higher accuracy in quality prediction than MKPLS algorithm. © 2018, Editorial Board of "Journal of Chemical Engineering of Chinese Universities". All right reserved.
关键词	Forecasting Gaussian distribution Partial discharges Batch process Gaussian Mixture Model Multimodes Penicillin fermentation process Principal Components Projection to latent structures Quality prediction Weight coefficients
DOI	10.3969/j.issn.1003-9015.2018.05.026
收录类别	EI
语种	中文
出版者	Zhejiang University
EI入藏号	20185006241604
EI主题词	Batch data processing
EI分类号	701.1 Electricity: Basic Concepts and Phenomena - 723.2 Data Processing and Image Processing - 922.1 Probability Theory
来源库	Compendex
分类代码	701.1 Electricity: Basic Concepts and Phenomena - 723.2 Data Processing and Image Processing - 922.1 Probability Theory
引用统计	无
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/114525
专题	电气工程与信息工程学院
作者单位	1.College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou; 730050, China; 2.Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou; 730050, China; 3.National Experimental Teaching Center of Electrical and Control Engineering, Lanzhou University of Technology, Lanzhou; 730050, China
第一作者单位	兰州理工大学
第一作者的第一单位	兰州理工大学
推荐引用方式 GB/T 7714	Zhao, Xiao-Qiang,Zhou, Wen-Wei,Hui, Yong-Yong. Monitoring and Quality Prediction of CPLS Batch Process Based on Kernel Entropy Projection[J]. Gao Xiao Hua Xue Gong Cheng Xue Bao/Journal of Chemical Engineering of Chinese Universities,2018,32(5):1186-1193.
APA	Zhao, Xiao-Qiang,Zhou, Wen-Wei,&Hui, Yong-Yong.(2018).Monitoring and Quality Prediction of CPLS Batch Process Based on Kernel Entropy Projection.Gao Xiao Hua Xue Gong Cheng Xue Bao/Journal of Chemical Engineering of Chinese Universities,32(5),1186-1193.
MLA	Zhao, Xiao-Qiang,et al."Monitoring and Quality Prediction of CPLS Batch Process Based on Kernel Entropy Projection".Gao Xiao Hua Xue Gong Cheng Xue Bao/Journal of Chemical Engineering of Chinese Universities 32.5(2018):1186-1193.