| 基于无人机机载LiDAR的电力线点云提取与重建 |
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| 引用本文： | 朱依民,田林亚,毕继鑫,林松.基于无人机机载LiDAR的电力线点云提取与重建[J].激光技术,2021,45(5):554-560. |
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| 作者姓名： | 朱依民 田林亚 毕继鑫 林松 |
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| 作者单位： | 1.河海大学 地球科学与工程学院，南京 211100 |
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| 摘 要： | 为了提高基于无人机机载激光雷达点云电力线提取与重建的精度和效率，采用了一种综合电力线点云分步提取、分段k均值聚类采样及结合直线和抛物线拟合的电力线点云提取与重建方法。在对电力线走廊点云进行预处理和改进滤波的基础上，先对其进行分段并根据电力线点云在高程方向的分布特征进行粗提取，再将粗提取得的电力线点投影到水平面上用Hough变换对其进行精提取，然后通过对精提取的电力线点进行分段k均值聚类采样, 从而完成电力线的单根分离，最后使用直线和抛物线结合的模型对电力线进行拟合重建。选取实测数据进行试验，通过电力线提取的完整率以及重建的精度和效率对本文中算法进行了评价。结果表明，利用该算法提取电力线点的综合完整率达到96%以上。这一结果对高效地提取和重建单档单根电力线具有一定帮助。
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| 关 键 词： | 激光技术 电力线提取与重建 改进滤波算法 Hough变换 k均值聚类 |
| 收稿时间： | 2020-09-22 |
Power line point cloud extraction and reconstruction based on UAV-borne LiDAR |
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| Abstract: | In order to improve the accuracy and efficiency of power line extraction and reconstruction based on unmanned aerial vehicle (UAV)-borne light detection and ranging (LiDAR) point cloud, a comprehensive power line point cloud extraction and reconstruction method was adopted, in which a step-by-step extraction of power line point clouds, segmented k-means clustering sampling, and a combination of straight line and parabola fitting were combined together. Based on the preprocessing and filtering of the power line corridor point cloud, the power line corridor was segmented and roughly extracted according to the distribution characteristics of the power line point cloud in the elevation direction. Then, the roughly extracted power line points were projected onto the horizontal plane and extracted finely by Hough transform. Subsequently, the single-line separation of the power line was completed by performing segmented k-means cluster sampling on the extracted power line points. Finally, a model combining a straight line and a parabola was used to fit and reconstruct the power line. The measured data was selected to test, and the algorithm was evaluated by the integrity rate of power line extraction and the accuracy and efficiency of reconstruction. The experimental results show that the comprehensive integrity rate of extracting power line points using this algorithm is above 96%, and the result is helpful for efficiently extracting and reconstructing single file single power line point cloud. |
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