Multi-phase batch process monitoring based on multiway weighted global neighborhood preserving embedding method

doi:10.1016/j.jprocont.2018.06.012

	Multi-phase batch process monitoring based on multiway weighted global neighborhood preserving embedding method
	Hui, Yongyong1,2 ; Zhao, Xiaoqiang1,2,3
	2018-09
发表期刊	JOURNAL OF PROCESS CONTROL
ISSN	0959-1524
卷号	69 页码:44-57
摘要	A multi-phase batch process monitoring method based on multiway weighted global neighborhood preserving embedding (MWGNPE) is proposed. MWGNPE has three advantages. Firstly, for the multi-phase feature of batch process, gaussian mixture model (GMM) method is used to divide phases by clustering characteristics. Secondly, after the multiple phases have been divided, global and local structures are extracted by using global neighborhood preserving (GNPE) method. Thirdly, probability density estimation characteristic of GMM is introduced to estimate the probability density of the extracted global and local structures. It can amplify useful information and suppress noise. These three advantages make MWGNPE well suit for batch process monitoring. A full MWGNPE model is combined with the cluster and the density estimation characteristic of GMM concurrently to improve the effect of fault detection in batch process monitoring. The effectiveness and advantages of proposed method are verified by a numerical system and the penicillin fermentation process. The results show that the proposed method can effectively capture the fault information hidden in process data and has the superiority compared with other conventional methods. (C) 2018 Elsevier Ltd. All rights reserved.
关键词	Batch Process monitoring Multi-phase Global-local Probability weighted Gaussian mixture model
DOI	10.1016/j.jprocont.2018.06.012
收录类别	SCI ; SCIE
语种	英语
资助项目	National Natural Science Foundation of China[61763029]
WOS研究方向	Automation & Control Systems ; Engineering
WOS类目	Automation & Control Systems ; Engineering, Chemical
WOS记录号	WOS:000445312900005
出版者	ELSEVIER SCI LTD
EI入藏号	20183005603702
EI主题词	Batch data processing
EI分类号	723.2 Data Processing and Image Processing - 913.1 Production Engineering - 921.6 Numerical Methods - 922.1 Probability Theory
引用统计	被引频次：19[WOS] [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/32470
专题	电气工程与信息工程学院
通讯作者	Zhao, Xiaoqiang
作者单位	1.Lanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou 730050, Gansu, Peoples R China; 2.Lanzhou Univ Technol, Key Lab Gansu Adv Control Ind Proc, Lanzhou 730050, Gansu, Peoples R China; 3.Lanzhou Univ Technol, Natl Expt Teaching Ctr Elect & Control Engn, Lanzhou 730050, Gansu, 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
通讯作者单位	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	Hui, Yongyong,Zhao, Xiaoqiang. Multi-phase batch process monitoring based on multiway weighted global neighborhood preserving embedding method[J]. JOURNAL OF PROCESS CONTROL,2018,69:44-57.
APA	Hui, Yongyong,&Zhao, Xiaoqiang.(2018).Multi-phase batch process monitoring based on multiway weighted global neighborhood preserving embedding method.JOURNAL OF PROCESS CONTROL,69,44-57.
MLA	Hui, Yongyong,et al."Multi-phase batch process monitoring based on multiway weighted global neighborhood preserving embedding method".JOURNAL OF PROCESS CONTROL 69(2018):44-57.

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