Research on fault diagnosis method for hydraulic system of CFETR blanket transfer device based on CNN-LSTM
文献类型：期刊论文
| 作者 | Guo, Xinpeng1,2; Lu, Kun2 ; Cheng, Yong2; Zhao, Wenlong2; Wu, Huapeng3; Li, Dongyi1,2; Li, Junwei1,2; Yang, Songzhu2; Zhang, Yu2
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| 刊名 | FUSION ENGINEERING AND DESIGN
 |
| 出版日期 | 2022-12-01 |
| 卷号 | 185 |
| ISSN号 | 0920-3796 |
| 关键词 | CFETR Hydraulic system Fault simulation Fault diagnosis CNN-LSTM |
| 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. |
| WOS关键词 | CONCEPT DESIGN ; RELIABILITY ; MAINTENANCE ; TURBINE |
| 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 |
| 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). |
入库方式： OAI收割
来源：合肥物质科学研究院
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