Abstract
For the operation and maintenance management of Power Lines, this paper uses laser scanners to collect data from the research lines, and proposes a method combining random sampling consistency with Euclidean clustering to extract the traverse point cloud data. Firstly, the idea of random sampling consistency is used to eliminate a large number of ground points unrelated to target points. Secondly, Euclidean clustering is used to extract traverse and tower points, and then the tower and traverse are divided by combining tower coordinates and threshold. Finally, the polynomial model is used to construct a fitting traverse. The results show that this method can effectively extract the traverse points and accurately fit the traverse model, and it has certain applicability.
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