Research on spatial analysis and hidden danger detection of power line point-selected equipment based on deep learning

Rongrong Sun; Chengsi Wang

doi:10.1117/12.3047652

17 October 2024 Research on spatial analysis and hidden danger detection of power line point-selected equipment based on deep learning

Rongrong Sun, Chengsi Wang

Author Affiliations +

Proceedings Volume 13289, International Conference on Optical Communication and Optoelectronic Technology (OCOT 2024); 132890N (2024) https://doi.org/10.1117/12.3047652
Event: The International Conference on Optical Communication and Optoelectronic Technology (OCOT 2024), 2024, Hangzhou, China

Abstract

Firstly, this paper deeply studies the deep learning theory and its application in the field of image processing. By constructing an efficient convolutional neural network model, it can realize the automatic extraction and recognition of the spatial position and shape of the point-selected equipment of the transmission line. On this basis, the powerful learning ability of the deep learning model is used to accurately judge the operating status of the point-selection equipment of the transmission line, effectively improving the accuracy and efficiency of hidden danger detection.The research in this paper not only enriches the application research of deep learning in the field of power system, but also provides a new idea and method for intelligent monitoring and hidden danger detection of transmission line point equipment, which has important theoretical significance and practical value.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Rongrong Sun and Chengsi Wang "Research on spatial analysis and hidden danger detection of power line point-selected equipment based on deep learning", Proc. SPIE 13289, International Conference on Optical Communication and Optoelectronic Technology (OCOT 2024), 132890N (17 October 2024); https://doi.org/10.1117/12.3047652

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