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输电线路多旋翼无人机激光雷达点云数据自动分类技术研究及应用

Research and Application of Automatic Classification Technology of LiDAR Point Cloud Data of Multi Rotor UAV for Transmission Line

  • 摘要:
      目的  旨在提高输电线路激光点云数据处理的效率和质量,为输电线路树障检测提供数据保障。
      方法  基于自主研发的激光雷达无人机,提出了一种新的点云自动分类算法;基于该算法,研发了一款树障隐患分析软件,实现了一键式点云自动分类。
      结果  研究表明:点云分类的正确率可达到95%以上,点云自动分类的效率可达60 km/h,且在杆塔与电力线、杆塔与植被相互交叉的复杂区域,也取得了较好的分类效果。
      结论  本方法为树障隐患的分析提供了高效率、高质量、全自动、智能化的数据处理手段,有效地提高了地理空间三维信息数据的获取精度和处理效率。

     

    Abstract:
      Introduction  In order to improve the efficiency and quality of laser point cloud data processing and provide data guarantee for tree barrier detection for transmission lines.
      Method  A new automatic point cloud classification algorithm was proposed based on the self developed laser radar UAV, then a tree barrier analysis software was developed based on the algorithm to realize one-click automatic classification of point cloud.
      Result  The results show that the accuracy of point cloud classification can reach more than 95%, and the efficiency of point cloud automatic classification can reach 60 km/h, moreover, good classification results are achieved in the complex areas where the towers and power lines, towers and vegetation intersect each other.
      Conclusion  This method provides a high efficiency, high quality, automatic and intelligent data processing method for the analysis of tree barrier danger, and effectively improves the acquisition accuracy and processing efficiency of geospatial three-dimensional information data.

     

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