Research on substation lifting safety early warning technology based on machine vision

Chengdong Lu; Yan Yang; Shuhan Fang; Chen Zou; Ao Yu; Feng Wang

doi:10.1117/12.3049146

17 October 2024 Research on substation lifting safety early warning technology based on machine vision

Chengdong Lu, Yan Yang, Shuhan Fang, Chen Zou, Ao Yu, Feng Wang

Author Affiliations +

Proceedings Volume 13289, International Conference on Optical Communication and Optoelectronic Technology (OCOT 2024); 132890G (2024) https://doi.org/10.1117/12.3049146
Event: The International Conference on Optical Communication and Optoelectronic Technology (OCOT 2024), 2024, Hangzhou, China

Abstract

Controlling the safety distance of crane arm lifting is a crucial requirement for high-voltage substation lifting operations. However, precise positioning is difficult to achieve with a single sensor. Therefore, this paper proposes a multi-sensor fusion approach that utilizes UWB (Ultra-Wideband) for global detection of crane and boom positions, binocular cameras to determine the distance between the top of the boom and overhead power lines, and depth point cloud cameras to detect the distance between the boom and surrounding objects in the substation environment. The integration of this information enables real-timse monitoring of operational conditions to achieve safe lifting operations. Through system testing, we achieved excellent early warning results, ensuring the safety of lifting operations and demonstrating the advanced nature of this research.

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

Citation Download Citation

Chengdong Lu, Yan Yang, Shuhan Fang, Chen Zou, Ao Yu, and Feng Wang "Research on substation lifting safety early warning technology based on machine vision", Proc. SPIE 13289, International Conference on Optical Communication and Optoelectronic Technology (OCOT 2024), 132890G (17 October 2024); https://doi.org/10.1117/12.3049146

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