Winter is coming and in many places with it the risk of ice accumulation on overhead power lines and all the problems that can lead to, including, in extreme cases, pylon collapse.
Writing in the International Journal of Energy Technology and Policy, a team from China describes a new approach to monitoring ice accumulation on power lines and pylons using unmanned aerial vehicles, drones, to acquire images of the infrastructure and image-processing algorithms to identify icy problems.
Yang Yang, Hongxia Wang, Meng Li, Minguan Zhao, Yuanhao Wan, and Shuyang Ma of Xinjiang Power Transmission, Urumqi, Shenbing Hua of China Electric Power Research Institute Co., Ltd., Qifei He of the Power Dispatch Control Center of State Grid Corporation of China, Beijing, China, suggest their work could improve winter safety and reliability of electricity networks. It has real implications for countries such as China where transmission lines cross vast and diverse terrains stretching across remote and largely inaccessible areas.
Conventional approaches to checking for dangerous ice accumulation have led operators to act either too conservatively and so undertaking unnecessary maintenance or less cautiously and too late, risking damage and power outages. The new method uses camera-equipped drones to capture live images of power lines and then applies compressive sensing theory to the images to remove environmental noise and clean the data for processing. The Canny algorithm is then applied to carry out advanced edge detection to reveal ice formation on power lines. A random Hough transform then finds the straight edges of the ice deposits and helps with calculations of the ice thickness to show which stretches of transmission lines are likely to be problematic.
With China’s weather extremes, a better way to monitoring power lines in winter is crucial to keeping the lights on.
Yang, Y., Hua, S., Wang, H., Li, M., He, Q., Zhao, M., Wan, Y. and Ma, S. (2024) ‘Detection method of icing thickness of overhead transmission lines based on canny algorithm’, Int. J. Energy Technology and Policy, Vol. 19, Nos. 3/4, pp.344–362.
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