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The Adjustment Analysis Method of the Active Surface Antenna Based on Convolutional Neural Network

文献类型：期刊论文

作者Ban, You1,3; Shi, Shang1; Wang, Na3; Xu, Qian3; Feng, Shufei2
刊名RESEARCH IN ASTRONOMY AND ASTROPHYSICS
出版日期2024-06-01
卷号24期号:6页码:065024
关键词techniques: radar astronomy telescopes methods: analytical methods: numerical
ISSN号1674-4527
DOI10.1088/1674-4527/ad4963
产权排序2
英文摘要Active surface technique is one of the key technologies to ensure the reflector accuracy of the millimeter/submillimeter wave large reflector antenna. The antenna is complex, large-scale, and high-precision equipment, and its active surfaces are affected by various factors that are difficult to comprehensively deal with. In this paper, based on the advantage of the deep learning method that can be improved through data learning, we propose the active adjustment value analysis method of large reflector antenna based on deep learning. This method constructs a neural network model for antenna active adjustment analysis in view of the fact that a large reflector antenna consists of multiple panels spliced together. Based on the constraint that a single actuator has to support multiple panels (usually 4), an autonomously learned neural network emphasis layer module is designed to enhance the adaptability of the active adjustment neural network model. The classical 8-meter antenna is used as a case study, the actuators have a mean adjustment error of 0.00252 mm, and the corresponding antenna surface error is 0.00523 mm. This active adjustment result shows the effectiveness of the method in this paper.
WOS关键词MAIN REFLECTOR ; ERROR
资助项目National Key R&D Program of China[2021YFC220350] ; National Natural Science Foundation of China[12303094] ; National Natural Science Foundation of China[52165053] ; Natural Science Foundation of Xinjiang Uygur Autonomous Region[2022D01C683] ; China Postdoctoral Science Foundation[2023T160549] ; China Postdoctoral Science Foundation[2021M702751] ; Guangdong Basic and Applied Basic Research Foundation[2020A1515111043] ; Guangdong Basic and Applied Basic Research Foundation[2023A1515010703]
WOS研究方向Astronomy & Astrophysics
语种英语
WOS记录号WOS:001249983000001
出版者NATL ASTRONOMICAL OBSERVATORIES, CHIN ACAD SCIENCES
资助机构National Key R&D Program of China ; National Natural Science Foundation of China ; Natural Science Foundation of Xinjiang Uygur Autonomous Region ; China Postdoctoral Science Foundation ; Guangdong Basic and Applied Basic Research Foundation
源URL[http://ir.xao.ac.cn/handle/45760611-7/6806]  
专题脉冲星研究团组
射电天文研究室_天线技术实验室
通讯作者Ban, You; Wang, Na
作者单位1.Xinjiang Univ, Sch Mech Engn, Urumqi 830017, Peoples R China
2.Dongguan Univ Technol, Sch Mech Engn, Dongguan 523808, Peoples R China
3.Chinese Acad Sci, Xinjiang Astron Observ, Urumqi 830011, Peoples R China
推荐引用方式
GB/T 7714		 Ban, You,Shi, Shang,Wang, Na,et al. The Adjustment Analysis Method of the Active Surface Antenna Based on Convolutional Neural Network[J]. RESEARCH IN ASTRONOMY AND ASTROPHYSICS,2024,24(6):065024.
APA Ban, You,Shi, Shang,Wang, Na,Xu, Qian,&Feng, Shufei.(2024).The Adjustment Analysis Method of the Active Surface Antenna Based on Convolutional Neural Network.RESEARCH IN ASTRONOMY AND ASTROPHYSICS,24(6),065024.
MLA Ban, You,et al."The Adjustment Analysis Method of the Active Surface Antenna Based on Convolutional Neural Network".RESEARCH IN ASTRONOMY AND ASTROPHYSICS 24.6(2024):065024.

入库方式： OAI收割

来源：新疆天文台

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