Research of Multi-Rotor UAVs Detailed Autonomous Inspection Technology of Transmission Lines Based on Route Planning

He, Tong; Zeng, Yihui; Hu, Zhuangli · 2019 · DOAJ

DOI: 10.1109/ACCESS.2019.2935551

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Summary

This paper addresses the need for efficient, automated inspection methods for expanding transmission networks, which currently rely on low-efficiency manual UAV operations. The authors propose a detailed autonomous inspection technology for multi-rotor UAVs that focuses on inspecting key components of transmission towers, such as insulators and fittings, while ensuring flight safety. The research aims to overcome limitations of previous studies, which often neglected detailed component inspection or safety protocols, by establishing a theoretical model for safe, automated route planning. The methodology involves establishing a theoretical model for UAV inspection that includes safety distance calculations and flight attitude control. Safety distances are determined based on electric and magnetic field strengths, positioning errors, and physical UAV dimensions. An electronic fence is designed using 3D laser point cloud models of transmission towers to prevent collisions and maintain safe distances from energized parts. The effective monitoring range of UAV cameras is calculated to select appropriate imaging equipment. The route planning process involves manually flying the UAV to key inspection points to record waypoint data, including position and camera angles. These waypoints are then connected to generate an automatic flight route, which is verified against the electronic fence before execution. The system was tested on eight typical electric tower types, with a case study conducted on transmission lines in Guangdong, China. The results demonstrate that the proposed method achieves high precision and efficiency. The position error of the automatic detailed inspection was found to be less than 10 cm, while the height error ranged between 1.26 and 1.76 meters. All tested waypoints remained outside the designated electronic fence, confirming the safety mechanism's effectiveness. Compared to traditional manual inspection, the automatic method increased inspection efficiency by 57.98% to 62.88%. The study validated the approach through comparative analysis of inspection times and accuracy assessments of 20 randomly selected waypoints, showing that the automated system maintains consistent performance after the initial route learning phase. The significance of this work lies in its practical application for large-scale transmission line maintenance. By automating the detailed inspection of key components, the technology reduces reliance on skilled manual operators and significantly improves operational efficiency. The integration of safety models, such as the electronic fence and precise distance calculations, ensures that UAVs can operate safely near high-voltage infrastructure. This approach provides a scalable solution for power grid companies to enhance supply reliability and reduce maintenance costs through intelligent, automated inspection systems.

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