Research on fault diagnosis method for hydraulic system of CFETR blanket transfer device based on CNN-LSTM

doi:10.1016/j.fusengdes.2022.113321

	Research on fault diagnosis method for hydraulic system of CFETR blanket transfer device based on CNN-LSTM
	Guo, Xinpeng 1,2; Lu, Kun 2; Cheng, Yong 2; Zhao, Wenlong 2; Wu, Huapeng 3; Li, Dongyi 1,2; Li, Junwei 1,2; Yang, Songzhu 2; Zhang, Yu 2
刊名	FUSION ENGINEERING AND DESIGN
	2022-12-01
卷号	185
关键词	CFETR Hydraulic system Fault simulation Fault diagnosis CNN-LSTM
ISSN号	0920-3796
DOI	10.1016/j.fusengdes.2022.113321
通讯作者	Cheng, Yong(chengyong@ipp.ac.cn)
英文摘要	Conducting fault diagnosis on the hydraulic system of the blanket transfer device Mover in the Chinese Fusion Engineering Test Reactor (CFETR) is a key technical issue that needs to be addressed urgently. In this article, a CNN (Convolutional Neural Networks)-LSTM (Long Short-Term Memory) deep learning model-based method is proposed for fault diagnosis, combining the advantages of feature extraction of the CNN model with the ad-vantages of the LSTM model for time series data processing. Therefore, this model shows a " multi-perspective" property, greatly improving its ability to extract features from data. In the fault diagnosis experiment under the condition of four typical faults, the proposed model has the highest accuracy of 98.56% on the test set and good efficiency in computation time compared to the other three models. This method provides some insights for future research on the Prognostics and Health Management (PHM) of the Mover's hydraulic system and the CFETR's remote handling intelligent operational decision system.
资助项目	Comprehensive Research Facility for Fusion Technology program of China ; Anhui Extreme Environment Robot Engineering Laboratory ; [2018-000052-73-01-001228]
WOS关键词	CONCEPT DESIGN ; RELIABILITY ; MAINTENANCE ; TURBINE
WOS研究方向	Nuclear Science & Technology
语种	英语
出版者	ELSEVIER SCIENCE SA
WOS记录号	WOS:000877339400001
资助机构	Comprehensive Research Facility for Fusion Technology program of China ; Anhui Extreme Environment Robot Engineering Laboratory
内容类型	期刊论文
源URL	[http://ir.hfcas.ac.cn:8080/handle/334002/130033]
专题	中国科学院合肥物质科学研究院
通讯作者	Cheng, Yong
作者单位	1.Univ Sci & Technol China, Hefei 230026, Peoples R China 2.Chinese Acad Sci, Inst Plasma Phys, Hefei Inst Phys Sci, Hefei 230031, Peoples R China 3.Lappeenranta Univ Technol, Lappeenranta, Finland
推荐引用方式 GB/T 7714	Guo, Xinpeng,Lu, Kun,Cheng, Yong,et al. Research on fault diagnosis method for hydraulic system of CFETR blanket transfer device based on CNN-LSTM[J]. FUSION ENGINEERING AND DESIGN,2022,185.
APA	Guo, Xinpeng.,Lu, Kun.,Cheng, Yong.,Zhao, Wenlong.,Wu, Huapeng.,...&Zhang, Yu.(2022).Research on fault diagnosis method for hydraulic system of CFETR blanket transfer device based on CNN-LSTM.FUSION ENGINEERING AND DESIGN,185.
MLA	Guo, Xinpeng,et al."Research on fault diagnosis method for hydraulic system of CFETR blanket transfer device based on CNN-LSTM".FUSION ENGINEERING AND DESIGN 185(2022).