Online monitoring and fault diagnosis for uneven length batch process based on multi-way orthogonal enhanced neighborhood preserving embedding

doi:10.1002/apj.2763

	Online monitoring and fault diagnosis for uneven length batch process based on multi-way orthogonal enhanced neighborhood preserving embedding
	Zhang, Yan 1,2; Zhao, Xiaoqiang1,2,3 ; Hui, Yongyong1,2,3 ; Liu, Kai 1,2
	2022-05
发表期刊	ASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING
ISSN	1932-2135
卷号	17 期号:3
摘要	In the practical batch process, the duration of each batch is probably different, and the key event happened may also vary from batch to batch. This paper proposes an effective fault diagnosis algorithm to synchronize the batch runs with uneven duration and keep the key features that reflect the running state of batch process. To address the batch out of sync, the relaxed greedy time warping is used to accurate on-line synchronization of ongoing batch and avoid evaluating the optimal path every time a new sample is available. For online monitoring and fault diagnosis, an important step is how to extract key features that reflect the running state of batch process, on which basis a weight matrix considers the distance between the neighbor data is embedded to construct the enhanced objective function, and then the mutually orthogonal basis functions which represent the local geometrical structure are computed to extract key features of batch process. After a fault is detected, the contribution plot method is used to diagnose the variables that cause this fault. The effectiveness of the proposed algorithm is verified by the penicillin fermentation process.
关键词	batch process fault diagnosis neighborhood preserving embedding orthogonal basis functions uneven length
DOI	10.1002/apj.2763
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:000769678300001
出版者	WILEY
EI入藏号	20221111800274
EI主题词	Batch data processing
EI分类号	723.2 Data Processing and Image Processing723.4 Artificial Intelligence921 Mathematics
来源库	WOS
引用统计	被引频次：1[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/158079
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, 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
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	Zhang, Yan,Zhao, Xiaoqiang,Hui, Yongyong,et al. Online monitoring and fault diagnosis for uneven length batch process based on multi-way orthogonal enhanced neighborhood preserving embedding[J]. ASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING,2022,17(3).
APA	Zhang, Yan,Zhao, Xiaoqiang,Hui, Yongyong,&Liu, Kai.(2022).Online monitoring and fault diagnosis for uneven length batch process based on multi-way orthogonal enhanced neighborhood preserving embedding.ASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING,17(3).
MLA	Zhang, Yan,et al."Online monitoring and fault diagnosis for uneven length batch process based on multi-way orthogonal enhanced neighborhood preserving embedding".ASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING 17.3(2022).