Surrogate model-based cognitive digital twin for smart remote maintenance of fusion reactor: modeling and implementation
文献类型：期刊论文
| 作者 | Yao, Zhixin1,2,3; Wu, Huapeng3; Song, Yuntao2; Cheng, Yong2 ; Pan, Hongtao2; Wu, Muquan1; Li, Ming3; Qin, Guodong2; Wang, Qi2,3; Zhang, Xi3,4
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| 刊名 | NUCLEAR FUSION
 |
| 出版日期 | 2024-12-01 |
| 卷号 | 64 |
| 关键词 | cognitive digital twin model-based system engineering surrogate model error compensation-based precision control fusion reactor smart maintenance |
| ISSN号 | 0029-5515 |
| DOI | 10.1088/1741-4326/ad7b56 |
| 通讯作者 | Yao, Zhixin(zhixin.yao@ipp.ac.cn) ; Wu, Huapeng(Huapeng.Wu@lut.fi) ; Wu, Muquan(wumuquan@szu.edu.cn) |
| 英文摘要 | A remote maintenance robot system (RMRS) plays a critical role in safeguarding the fusion energy experimental device's security and stability. State-of-the-art intelligent technology such as cognitive digital twins (CDTs) is widely considered capable of improving complex equipment's performance and reducing management burden using a visualized system. However, the CDT virtual space cannot mirror the RMRS which is a kind of flexible multi-body system in real-time and with high fidelity. Therefore, we propose a CDT modeling method based on a surrogate model for the RMRS. Firstly, model-based system engineering is leveraged to build a structural modular architecture, which can decrease the modeling complexity of CDT and increase the modeling efficiency. Then, the surrogate models are self-learning within the CDT physical space, which reconstructs the RMRS's real-time dynamic performances and endows CDT with cognitive capabilities. Finally, after integrating the CDT system, a smart decision-making plan that compensates for the operation error is generated for RMRS's accurate control. We take a China Fusion Engineering Test Reactor (CFETR) multi-purpose overload robot (CMOR) as an example to demonstrate the implementation process. According to the results, CDT can achieve real-time (230 ms time delay) high-fidelity (5 mm control error) monitoring and accurate control, and CMOR conducts smart maintenance based on the simulation results. This method improves the efficiency of remote maintenance and provides solutions for high-duty cycle time of CFETR, it can also be applied to other tokamak fusion energy devices. |
| 资助项目 | Comprehensive Research Facility for Fusion Technology Program of China ; National Key R&D Program of China[2022YFE03070000] ; National Key R&D Program of China[2022YFE03070004] ; National Key R&D Program of China[12075155] |
| WOS研究方向 | Physics |
| 语种 | 英语 |
| WOS记录号 | WOS:001321049400001 |
| 出版者 | IOP Publishing Ltd |
| 资助机构 | Comprehensive Research Facility for Fusion Technology Program of China ; National Key R&D Program of China |
| 源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/135610]  |
| 专题 | 中国科学院合肥物质科学研究院 |
| 通讯作者 | Yao, Zhixin; Wu, Huapeng; Wu, Muquan |
| 作者单位 | 1.Shenzhen Univ, Coll Phys & Optoelect Engn, Shenzhen 518060, 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 4.Huazhong Univ Sci & Technol, Sch Mech Sci & Engn, Wuhan 430074, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yao, Zhixin,Wu, Huapeng,Song, Yuntao,et al. Surrogate model-based cognitive digital twin for smart remote maintenance of fusion reactor: modeling and implementation[J]. NUCLEAR FUSION,2024,64. |
| APA | Yao, Zhixin.,Wu, Huapeng.,Song, Yuntao.,Cheng, Yong.,Pan, Hongtao.,...&Zhang, Xi.(2024).Surrogate model-based cognitive digital twin for smart remote maintenance of fusion reactor: modeling and implementation.NUCLEAR FUSION,64. |
| MLA | Yao, Zhixin,et al."Surrogate model-based cognitive digital twin for smart remote maintenance of fusion reactor: modeling and implementation".NUCLEAR FUSION 64(2024). |
入库方式： OAI收割
来源：合肥物质科学研究院
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