TRANSMISSION LINE INSPECTION WITH UAVS: A REVIEW OF TECHNOLOGIES, APPLICATIONS, AND CHALLENGES

Year 2024, Volume: 9 Issue: 1, 60 - 69, 30.12.2024

Esra İnce

https://doi.org/10.55088/ijesg.1596043

Abstract

Regular inspection of energy transmission lines plays a critical role to ensure the safety of energy infrastructures and minimise failure risks. While traditional inspection methods have limitations such as high cost, long duration and hazardous working conditions, unmanned aerial vehicles (UAVs) are emerging as an innovative alternative in this field. This paper provides a comprehensive review of the use of UAVs in the inspection of power transmission lines, focusing on the sensor technologies, artificial intelligence algorithms and field applications. The integration of LiDAR, thermal camera and multispectral sensors into UAVs offers many advantages such as three-dimensional modelling of power lines, detection of thermal anomalies and assessment of environmental risks. In addition, deep learning and reinforcement learning algorithms have been observed to improve the performance of UAVs by accelerating data processing and improving autonomous navigation. In this study, different approaches and case studies in the literature are analysed in detail, and the strengths and limitations of UAV-based inspection systems are comparatively evaluated. Accordingly, environmental challenges, sensor integration and legal regulations stand out as the main obstacles faced by these technologies in field applications. However, it is emphasised that significant improvements in data processing processes can be achieved with the integration of 5G technology and edge computing systems. This study not only evaluates the current status of UAVs in the inspection of energy infrastructures, but also provides recommendations for future research. More widespread adoption of UAV-based inspection systems will contribute to a more reliable, efficient and sustainable management of the energy sector.

Keywords

Energy transmission line inspection, Unmanned aerial vehicles, Artificial intelligence assisted systems, Lidar and Sensor Technologies

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