Research on inverse modeling method of transmission line GIM model based on laser point cloud and image feature extraction

Rong Yu; Bin Liao; Hui Zhang; Di Wang; Qiumiao Cheng

doi:10.1117/12.3030622

5 June 2024 Research on inverse modeling method of transmission line GIM model based on laser point cloud and image feature extraction

Rong Yu, Bin Liao, Hui Zhang, Di Wang, Qiumiao Cheng

Author Affiliations +

Proceedings Volume 13163, Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024); 131633D (2024) https://doi.org/10.1117/12.3030622
Event: International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024), 2024, Xi'an, China

Abstract

Aiming at the stock transmission line engineering, a reverse modeling method of transmission line GIM model based on laser point cloud is proposed in this paper. First of all, the laser point cloud data of the line channel are collected and classified; then, the point cloud data are imported into the modeling tool to extract the general outline of the transmission line and tower, and build a preliminary model; then, based on the UAV inspection pictures, the insulation substring and hardware are extracted to further refine the transmission tower GIM model. Through the verification of model accuracy, the results show that this research method can make full use of the high precision and rich information of laser point cloud data to quickly construct the three-dimensional model of transmission lines, so as to improve the modeling efficiency and accuracy.

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

Citation Download Citation

Rong Yu, Bin Liao, Hui Zhang, Di Wang, and Qiumiao Cheng "Research on inverse modeling method of transmission line GIM model based on laser point cloud and image feature extraction", Proc. SPIE 13163, Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024), 131633D (5 June 2024); https://doi.org/10.1117/12.3030622

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KEYWORDS

Point clouds

Data modeling

3D modeling

Modeling

Data transmission

Unmanned aerial vehicles

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