A support vector machine framework for fault detection in molecular pump

doi:10.1080/00223131.2022.2080124

	A support vector machine framework for fault detection in molecular pump
	Yuan, X. L.2; Kai, J.1; Chen, Y.2; Zuo, G. Z.2; Zhuang, H. D.2; Li, J. H.; Hu, J. S.2
刊名	JOURNAL OF NUCLEAR SCIENCE AND TECHNOLOGY
	2022-06-02
关键词	Fusion device fault detection molecular pump support vector machine
ISSN号	0022-3131
DOI	10.1080/00223131.2022.2080124
通讯作者	Yuan, X. L.(xlyuan@ipp.ac.cn) ; Hu, J. S.(hujs@ipp.ac.cn)
英文摘要	The molecular pump fault results in a vacuum leak that can lead to accidents in a fusion device. The fault detection for the molecular pump can provide an early warning to avoid a greater loss in a fusion device. This paper proposes a Support Vector Machine (SVM) framework for fault detection in a molecular pump. This study investigates the key technologies, framework, and system development methods of the data-driven fault detection system for a molecular pump. This study proposes a molecular pump test system to simulate the fault of a molecular pump to solve the highly unbalanced data problem and verify the framework availability. The packaged development framework, implemented in the test system, realizes the fault detection function. The developed system offers better practicability and can effectively detect perform faults in a molecular pump. The results obtained would support new ideas and methods for early warning in molecular pumps and pave the way for stable and reliable vacuum pump systems in a fusion device.
资助项目	National Nature Science Foundation of China[11905254] ; National Nature Science Foundation of China[11905138] ; National Nature Science Foundation of China[11905148] ; National Key Research and Development Program of China[2017YFE0301100] ; Maintenance and Renovation Program of Large Research Infrastructures of CAS[DSS-WXGZ-2020-0011] ; CASHIPS Director's Fund[YZJJ2019QN9] ; U.S. Dept. of Energy[DE-AC02-09CH11466] ; U.S. Dept. of Energy[DE-SC0016553] ; Excellence Program of Hefei Science Center CAS[2020HSC-UE010]
WOS关键词	DIAGNOSIS ; DISCHARGE ; SYSTEMS
WOS研究方向	Nuclear Science & Technology
语种	英语
出版者	TAYLOR & FRANCIS LTD
WOS记录号	WOS:000805304600001
资助机构	National Nature Science Foundation of China ; National Key Research and Development Program of China ; Maintenance and Renovation Program of Large Research Infrastructures of CAS ; CASHIPS Director's Fund ; U.S. Dept. of Energy ; Excellence Program of Hefei Science Center CAS
内容类型	期刊论文
源URL	[http://ir.hfcas.ac.cn:8080/handle/334002/131153]
专题	中国科学院合肥物质科学研究院
通讯作者	Yuan, X. L.; Hu, J. S.
作者单位	1.Anhui Polytech Univ, Sch Elect Engn, Wuhu, Peoples R China 2.Chinese Acad Sci, Inst Plasma Phys, Hefei 230031, Peoples R China
推荐引用方式 GB/T 7714	Yuan, X. L.,Kai, J.,Chen, Y.,et al. A support vector machine framework for fault detection in molecular pump[J]. JOURNAL OF NUCLEAR SCIENCE AND TECHNOLOGY,2022.
APA	Yuan, X. L..,Kai, J..,Chen, Y..,Zuo, G. Z..,Zhuang, H. D..,...&Hu, J. S..(2022).A support vector machine framework for fault detection in molecular pump.JOURNAL OF NUCLEAR SCIENCE AND TECHNOLOGY.
MLA	Yuan, X. L.,et al."A support vector machine framework for fault detection in molecular pump".JOURNAL OF NUCLEAR SCIENCE AND TECHNOLOGY (2022).