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Intelligent marine detection based on spectral imaging and neural network modeling

文献类型：期刊论文

作者Lu, Fengqin4,5,6; Gao, Xinyu4,6; Ma, Jun4,6; Xu, Jinfeng4,6; Xue, Qingsheng4,6; Cao, Diansheng4,6; Quan, Xiangqian1,2,3
刊名OCEAN ENGINEERING
出版日期2024-10-15
卷号310页码:10
关键词Machine intelligence Hyperspectral imaging Neural networks Hyperspectral data classification Offshore structures maintenance
ISSN号0029-8018
DOI10.1016/j.oceaneng.2024.118640
英文摘要Underwater spectral imaging combined with neural networks provides a practical means for intelligent detection and maintenance of offshore engineering. As an underwater detection technology, the data obtained from underwater hyperspectral imaging can be used for both qualitative analysis and quantitative detection of underwater targets, which is an efficient means of underwater target detection in offshore engineering. In this paper, An underwater hyperspectral imaging system based on PGP spectral structure line scanning imaging has been designed and developed for shallow water detection. It has a spectral range of 400-1000 nm, over 200 channels, a spectral resolution of 2.5 nm, a field of view angle of 35.2 degrees, and a focal length of 25 mm. According to the design results, the system was assembled, calibrated and tested. Aiming at solving the shortcomings of the current underwater hyperspectral system, such as the inability of real-time observation of the scanned image, large data volume and complicated processing, the upper computer software was designed and developed to realize the functions of controlling and adjusting the parameter, real-time displaying the scanned image, reconstructing the image and outputting the data in ENVI standard format to the underwater hyperspectral system. The prototype of the system was used to conduct coral detection experiments in Weizhou Island, and the neural network model was used to classify the experimental data, and the overall classification accuracy was above 98%. The experimental results show that the whole system has good imaging quality and good underwater detection capability, and the developed host computer software greatly reduces the workload of raw data processing, improves the experimental detection efficiency, and provides a feasible technical solution for underwater intelligent detection and analysis.
资助项目National Natural Science Foundation of China[U2006209] ; Fundamental Research Funds for the Central Universities[202362004] ; Fundamental Research Funds for the Central Universities[202364007] ; Key Technology Research and Development Program of Shandong[2020CXGC010706] ; Scientific Research Funds of Taishan Scholars[202105033008] ; Excellent Researcher Plan Project[202112003] ; Key Deployment Project of the Marine Science Research Center of the Chinese Academy of Sciences[COMS2019J04] ; Youth Innovation Promotion Association CAS[2020361]
WOS研究方向Engineering ; Oceanography
语种英语
WOS记录号WOS:001264879300001
出版者PERGAMON-ELSEVIER SCIENCE LTD
资助机构National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities ; Key Technology Research and Development Program of Shandong ; Scientific Research Funds of Taishan Scholars ; Excellent Researcher Plan Project ; Key Deployment Project of the Marine Science Research Center of the Chinese Academy of Sciences ; Youth Innovation Promotion Association CAS
源URL[http://ir.idsse.ac.cn/handle/183446/11506]  
专题深海工程技术部_深海视频技术研究室
通讯作者Quan, Xiangqian
作者单位1.Univ Calif San Diego, Scripps Inst Oceanog, La Jolla, CA 92093 USA
2.Univ Calif San Diego, Dept Mech & Aerosp Engn, La Jolla, CA 92093 USA
3.Chinese Acad Sci, Inst Deep Sea Sci & Engn, Sanya 572000, Peoples R China
4.Minist Educ, Engn Res Ctr Adv Marine Phys Instruments & Equipme, Qingdao 266100, Peoples R China
5.Ocean Univ China, Basic Teaching Ctr, Qingdao 266100, Peoples R China
6.Ocean Univ China, Coll Phys & Optoelect Engn, Dept Informat Sci & Engn, Qingdao 266100, Shandong, Peoples R China
推荐引用方式
GB/T 7714		 Lu, Fengqin,Gao, Xinyu,Ma, Jun,et al. Intelligent marine detection based on spectral imaging and neural network modeling[J]. OCEAN ENGINEERING,2024,310:10.
APA Lu, Fengqin.,Gao, Xinyu.,Ma, Jun.,Xu, Jinfeng.,Xue, Qingsheng.,...&Quan, Xiangqian.(2024).Intelligent marine detection based on spectral imaging and neural network modeling.OCEAN ENGINEERING,310,10.
MLA Lu, Fengqin,et al."Intelligent marine detection based on spectral imaging and neural network modeling".OCEAN ENGINEERING 310(2024):10.

入库方式： OAI收割

来源：深海科学与工程研究所

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