Anomaly Detection with GRU Based Bi-autoencoder for Industrial Multimode Process

doi:10.1007/s12555-021-0323-6

CASIA OpenIR > 中科院工业视觉智能装备工程实验室 > 精密感知与控制

	Anomaly Detection with GRU Based Bi-autoencoder for Industrial Multimode Process
	Xu, Xinyao1,2 ; Qin, Fangbo1,2 ; Zhao, Wenjun 3; Xu, De1,2 ; Wang, Xingang1,2 ; Yang, Xihao 3
发表期刊	INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
ISSN	1598-6446
	2022-04-29
页码	14
通讯作者	Xu, Xinyao(xuxinyao2018@ia.ac.cn)
摘要	The anomaly detection for multimode industrial process is a challenging problem, because the multiple operation modes present various main distributions of monitored variables, and the dynamic sequential characteristics exist within each operation mode. This paper proposes an anomaly detection method based on sequence-to-sequence gated recurrent units (SGRU). First, to better model both the cross-mode trends and mode-specific sequential characteristics, a main reconstruction module and residual reconstruction module are integrated to improve the ability to represent complex process. Both modules are implemented by SGRUs. Second, a reconstruction error prediction module is designed to estimate the mean values of mode-specific reconstruction errors, which helps to determine the more reliable alarm thresholds. Third, the two anomaly indicators are utilized to represent the deviation degree of monitored variables against the normal conditions, according to the statistical errors and biases of reconstructions, respectively. The effectiveness of the proposed method is validated on simulations with multimode process, and on the practical data set collected from the Cleaning-in-Place multimode process of an aseptic beverage filling line in a real factory.
关键词	Anomaly detection autoencoder gated recurrent unit multimode process
DOI	10.1007/s12555-021-0323-6
关键词[WOS]	MULTIPLE OPERATING MODES ; FAULT-DETECTION ; NETWORK ; PCA
收录类别	SCI
语种	英语
资助项目	National Key R&D Program of China[2018YFD0400902] ; State Key Laboratory of Smart Manufacturing for Special Vehicles and Transmission System[GZ2019KF008]
项目资助者	National Key R&D Program of China ; State Key Laboratory of Smart Manufacturing for Special Vehicles and Transmission System
WOS研究方向	Automation & Control Systems
WOS类目	Automation & Control Systems
WOS记录号	WOS:000788953900005
出版者	INST CONTROL ROBOTICS & SYSTEMS, KOREAN INST ELECTRICAL ENGINEERS
七大方向——子方向分类	目标检测、跟踪与识别
引用统计	被引频次：6[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/48426
专题	中科院工业视觉智能装备工程实验室_精密感知与控制
通讯作者	Xu, Xinyao
作者单位	1.Chinese Acad Sci, Res Ctr Precis Sensing & Control, Inst Automat, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100190, Peoples R China 3.State Key Lab Smart Mfg Special Vehicles & Transm, Baotou City 014000, Inner Mongolia, Peoples R China
第一作者单位	精密感知与控制研究中心
通讯作者单位	精密感知与控制研究中心
推荐引用方式 GB/T 7714	Xu, Xinyao,Qin, Fangbo,Zhao, Wenjun,et al. Anomaly Detection with GRU Based Bi-autoencoder for Industrial Multimode Process[J]. INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS,2022:14.
APA	Xu, Xinyao,Qin, Fangbo,Zhao, Wenjun,Xu, De,Wang, Xingang,&Yang, Xihao.(2022).Anomaly Detection with GRU Based Bi-autoencoder for Industrial Multimode Process.INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS,14.
MLA	Xu, Xinyao,et al."Anomaly Detection with GRU Based Bi-autoencoder for Industrial Multimode Process".INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS (2022):14.