Ice thickness detection method for overhead transmission lines based on remote sensing satellite data and SVM algorithm

Kai Zhou; Ruizhe Zhang; Lei Tan; Liuxue Zhao; Kuan Ye

doi:10.1117/12.3024644

21 February 2024 Ice thickness detection method for overhead transmission lines based on remote sensing satellite data and SVM algorithm

Kai Zhou, Ruizhe Zhang, Lei Tan, Liuxue Zhao, Kuan Ye

Author Affiliations +

Proceedings Volume 12988, Second International Conference on Environmental Remote Sensing and Geographic Information Technology (ERSGIT 2023); 129881B (2024) https://doi.org/10.1117/12.3024644
Event: Second International Conference on Environmental Remote Sensing and Geographic Information Technology (ERSGIT 2023), 2023, Xi’an, China

Abstract

Icing can cause problems such as line overload and disconnection, posing a threat to the stability and safety of the power system. The traditional ice thickness detection method mainly relies on manual inspection and simple measurement tools, which is not only inefficient but also difficult to ensure accuracy. Therefore, this article proposes a method for detecting the ice thickness of overhead transmission lines based on remote sensing satellite data and SVM (Support Vector Machine) algorithm. This method utilizes remote sensing satellite data to monitor overhead transmission lines, obtain image information of the line surface, and then use SVM algorithm to process and analyze the image to predict the ice thickness. The experimental results show that this method can effectively detect the icing thickness of overhead transmission lines and improve prediction accuracy. This method has important practical value for ensuring the stability and safety of the power system.

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

Citation Download Citation

Kai Zhou, Ruizhe Zhang, Lei Tan, Liuxue Zhao, and Kuan Ye "Ice thickness detection method for overhead transmission lines based on remote sensing satellite data and SVM algorithm", Proc. SPIE 12988, Second International Conference on Environmental Remote Sensing and Geographic Information Technology (ERSGIT 2023), 129881B (21 February 2024); https://doi.org/10.1117/12.3024644

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