Multi-stage fusion regression network for quality prediction of batch process

doi:10.1002/cjce.24940

	Multi-stage fusion regression network for quality prediction of batch process
	Yao, Hongjuan 1,2; Zhao, Xiaoqiang1,2,3 ; Li, Wei1,2,3 ; Hui, Yongyong1,2,3
	2023-05-03
发表期刊	CANADIAN JOURNAL OF CHEMICAL ENGINEERING
ISSN	0008-4034
摘要	In most batch processes, the correlations of process variables present multi-stage characteristic as the process progress and operating conditions change. The methods building a local model at each stage ignore the potential correlations among stages, resulting in poor quality prediction of batch process. To solve this problem, a batch process quality prediction method based on multi-stage fusion regression network (MSFRN) is proposed. First, the affine propagation clustering (AP) algorithm is used to automatically divide the stages for batch process without relying on prior knowledge. Second, the input reconstruction error and quality prediction error are organically combined to develop a stacked isomorphic and quality-driven autoencoder (SIQAE) for each stage, which fully extracts the quality-related features for each stage while reducing the input cumulative loss. Then, the self-attention mechanism is used to integrate the quality-related features of each stage so as to obtain global features which consider the correlations among stages. Finally, the global features are input into the fully connected regression layer to predict the quality variables of batch process. The effectiveness of the proposed method was verified by applying on penicillin fermentation process.
关键词	batch process multi-stage quality prediction self-attention stacked autoencoders
DOI	10.1002/cjce.24940
收录类别	SCIE ; EI
语种	英语
WOS研究方向	Engineering
WOS类目	Engineering, Chemical
WOS记录号	WOS:000980957300001
出版者	WILEY
EI入藏号	20231914067412
EI主题词	Clustering algorithms
EI分类号	723.2 Data Processing and Image Processing ; 903.1 Information Sources and Analysis ; 922.2 Mathematical Statistics
来源库	WOS
引用统计	被引频次[WOS]：0 [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/162134
专题	电气工程与信息工程学院
作者单位	1.Lanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou, Peoples R China; 2.Lanzhou Univ Technol, Key Lab Gansu Adv Control Ind Proc, Lanzhou, Peoples R China; 3.Lanzhou Univ Technol, Natl Expt Teaching Ctr Elect & Control Engn, Lanzhou, Peoples R China
第一作者单位	电气工程与信息工程学院; 兰州理工大学
第一作者的第一单位	电气工程与信息工程学院
推荐引用方式 GB/T 7714	Yao, Hongjuan,Zhao, Xiaoqiang,Li, Wei,et al. Multi-stage fusion regression network for quality prediction of batch process[J]. CANADIAN JOURNAL OF CHEMICAL ENGINEERING,2023.
APA	Yao, Hongjuan,Zhao, Xiaoqiang,Li, Wei,&Hui, Yongyong.(2023).Multi-stage fusion regression network for quality prediction of batch process.CANADIAN JOURNAL OF CHEMICAL ENGINEERING.
MLA	Yao, Hongjuan,et al."Multi-stage fusion regression network for quality prediction of batch process".CANADIAN JOURNAL OF CHEMICAL ENGINEERING (2023).