无人机激光雷达智能识别输电线路缺陷
发布时间：2019-01-30 11:56
【摘要】：针对我国高压输电线路巡检周期长、作业强度大、无法保证巡检结果客观性与完整性的问题,提出了一套无人机三维激光雷达智能识别输电线路缺陷的研究方法。该方法首先使用自动化分类方法将走廊三维点云进行金字塔式数据重采样及分档式处理;其次将分档数据自动划分为地面、植被、杆塔、导线4个类别,结合人工判读识别低等电力线、公路等其他类别;最终,根据国网相关安全局规程提取当前工况下导线与周围地物存在的安全缺陷。实验数据表明,所提出的方法可有效识别导线-植被、导线-建筑物、导线-交跨等多类重要缺陷,可大幅提升现有高压输电线路巡检流程的质量与效率。
[Abstract]:Aiming at the problem that the inspection period of HV transmission lines in China is long and the intensity of operation is too large to guarantee the objectivity and integrity of the inspection results, a set of intelligent identification methods for 3D lidar of UAV to identify the defects of transmission lines is proposed. The method firstly uses automatic classification method to carry out pyramid data resampling and file processing of corridor 3D point cloud. Secondly, the classified data are automatically divided into four categories: ground, vegetation, tower and wire, combined with manual interpretation to identify the lower power line, highway and other categories; Finally, according to the relevant safety rules of the national network, the safety defects of the wire and the surrounding objects are extracted under the current operating conditions. Experimental data show that the proposed method can effectively identify many kinds of important defects such as traverse vegetation traverse-building traverse-intersection and so on and can greatly improve the quality and efficiency of the existing high voltage transmission line inspection process.
【作者单位】： 北京拓维思科技有限公司;南方电网科学科研院有限责任公司;天津航天中为数据系统科技有限公司;天津市智能遥感信息处理技术企业重点实验室;云南中能投资股份有限公司楚雄直升机作业分公司;
【分类号】：TM75;TN958.98
，
本文编号：2418105
[Abstract]:Aiming at the problem that the inspection period of HV transmission lines in China is long and the intensity of operation is too large to guarantee the objectivity and integrity of the inspection results, a set of intelligent identification methods for 3D lidar of UAV to identify the defects of transmission lines is proposed. The method firstly uses automatic classification method to carry out pyramid data resampling and file processing of corridor 3D point cloud. Secondly, the classified data are automatically divided into four categories: ground, vegetation, tower and wire, combined with manual interpretation to identify the lower power line, highway and other categories; Finally, according to the relevant safety rules of the national network, the safety defects of the wire and the surrounding objects are extracted under the current operating conditions. Experimental data show that the proposed method can effectively identify many kinds of important defects such as traverse vegetation traverse-building traverse-intersection and so on and can greatly improve the quality and efficiency of the existing high voltage transmission line inspection process.
【作者单位】： 北京拓维思科技有限公司;南方电网科学科研院有限责任公司;天津航天中为数据系统科技有限公司;天津市智能遥感信息处理技术企业重点实验室;云南中能投资股份有限公司楚雄直升机作业分公司;
【分类号】：TM75;TN958.98
，
本文编号：2418105
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