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基于机载激光点云语义分割的配网线路走廊树障在线识别技术

Online Identification of Distribution Network Line Corridor Tree Barrier Based on Airborne Laser Point Cloud Semantic Segmentation

  • 摘要: 配网线路走廊面积大、距离长,识别配网线路周围树障存在识别精度低的问题,因此研究基于机载激光点云语义分割的配网线路走廊树障在线识别技术。采用搭载在直升机的激光雷达设备来进行树木障碍物的数据采集,并对采集数据进行预处理。在LinkNet网络中,采用语义分割算法提取点云特征信息,并分配相应的类别标签。将类别标签进行聚类分析后,构建识别函数进行识别。实验结果表明,所提技术的聚类识别效果较优,能达到高精度识别要求;利用直升机搭载激光雷达对线路通道进行了全面扫描,成功测量出树障与导线间的距离为14.15 m,与实际情况较为一致,显著提升了树障识别的准确性。

     

    Abstract: Because of the large area and long distance of distribution network line corridors, the recognition accuracy of tree barriers around distribution network lines is low. Therefore, an online recognition of distribution network line corridor tree barriers based on airborne laser point cloud semantic segmentation is studied. The laser radar equipment mounted on the helicopter is used to collect the data of the tree obstacles, and the collected data is pre-processed. Semantic segmentation algorithm is used to extract the feature information of point cloud in LinkNet network and assign corresponding category labels. After cluster analysis of category labels, a recognition function is constructed for recognition. The experimental results show that the clustering recognition effect is better and can meet the requirement of high precision recognition. The laser radar mounted on the helicopter was used to conduct a comprehensive scan of the line channel, and the distance between the tree barrier and the wire was successfully measured to be 14.15 m, which was more consistent with the actual situation, and significantly improved the accuracy of tree barrier recognition.

     

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