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The Neural Network Training Method of Divided-ring Actuators for Active Reflector Antennas

文献类型：期刊论文

作者Ban, You3,4; Liu, Jialong3; Wang, Na4; Cai, Yang3; Li, Lin2; Feng, Shufei1
刊名RESEARCH IN ASTRONOMY AND ASTROPHYSICS
出版日期2025-12-01
卷号25期号:12页码:11
关键词standards methods: miscellaneous techniques: miscellaneous telescopes
ISSN号1674-4527
DOI10.1088/1674-4527/ae04b5
通讯作者Ban, You(banyou_xd@163.com)
英文摘要In order to improve the deep learning training efficiency of the large reflector antenna active adjustment technique, this paper synthesizes the characteristic that each actuator can only adjust the panel connected to it, and proposes a divided-ring antenna active adjustment deep learning training modeling method. The method organizes panel node data according to actuator ring positions, using panel displacements as input features and actuator adjustments as output labels. Through systematic sorting, reorganization, and normalization, the ring-divided data are transformed into grid-structured tensors suitable for convolutional processing. Multi-layer convolutional neural networks are then constructed for surface adjustment prediction, optimized through a hybrid strategy combining simulated annealing and the Adam algorithm. Through the dataset divided-ring preprocessing, active adjustment neural network construction and model training for the case of an 8 m reflector antenna, the analytical results show that the proposed method can effectively shorten the training time, and the final model's prediction accuracy is greatly improved, which demonstrates the feasibility and effectiveness of the proposed method.
WOS关键词SURFACE ANTENNA ; ADJUSTMENT
资助项目Tianshan Talent Foundation of Xinjiang Uygur Autonomous Region[2024TSYCCX0010] ; National Natural Science Foundation of China[12303094] ; National Natural Science Foundation of China[52165053] ; National Key R&D Program of China[2021YFC220350] ; Natural Science Foundation of Xinjiang Uygur Autonomous Region[2022D01C683] ; China Postdoctoral Science Foundation[2021M702751] ; China Postdoctoral Science Foundation[2023T160549]
WOS研究方向Astronomy & Astrophysics
语种英语
WOS记录号WOS:001595378600001
出版者IOP Publishing Ltd
资助机构Tianshan Talent Foundation of Xinjiang Uygur Autonomous Region ; National Natural Science Foundation of China ; National Key R&D Program of China ; Natural Science Foundation of Xinjiang Uygur Autonomous Region ; China Postdoctoral Science Foundation
源URL[http://ir.xao.ac.cn/handle/45760611-7/8253]  
专题脉冲星研究团组
通讯作者Ban, You
作者单位1.Dongguan Univ Technol, Sch Mech Engn, Dongguan 523808, Peoples R China
2.Xinjiang Univ, Sch Phys & Technol, Urumqi 830017, Peoples R China
3.Xinjiang Univ, Sch Mech Engn, Urumqi 830017, Peoples R China
4.Chinese Acad Sci, Xinjiang Astron Observ, Urumqi 830011, Peoples R China
推荐引用方式
GB/T 7714		 Ban, You,Liu, Jialong,Wang, Na,et al. The Neural Network Training Method of Divided-ring Actuators for Active Reflector Antennas[J]. RESEARCH IN ASTRONOMY AND ASTROPHYSICS,2025,25(12):11.
APA Ban, You,Liu, Jialong,Wang, Na,Cai, Yang,Li, Lin,&Feng, Shufei.(2025).The Neural Network Training Method of Divided-ring Actuators for Active Reflector Antennas.RESEARCH IN ASTRONOMY AND ASTROPHYSICS,25(12),11.
MLA Ban, You,et al."The Neural Network Training Method of Divided-ring Actuators for Active Reflector Antennas".RESEARCH IN ASTRONOMY AND ASTROPHYSICS 25.12(2025):11.

入库方式： OAI收割

来源：新疆天文台

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