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A Novel Method of Autonomous Inspection for Transmission Line based on Cable Inspection Robot LiDAR Data

机译:基于电缆检测机器人LiDAR数据的输电线路自动检测新方法

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摘要

With the growth of the national economy, there is increasing demand for electricity, which forces transmission line corridors to become structurally complicated and extend to complex environments (e.g., mountains, forests). It is a great challenge to inspect transmission line in these regions. To address these difficulties, a novel method of autonomous inspection for transmission line is proposed based on cable inspection robot (CIR) LiDAR data, which mainly includes two steps: preliminary inspection and autonomous inspection. In preliminary inspection, the position and orientation system (POS) data is used for original point cloud dividing, ground point filtering, and structured partition. A hierarchical classification strategy is established to identify the classes and positions of the abnormal points. In autonomous inspection, CIR can autonomously reach the specified points through inspection planning. These inspection targets are imaged with PTZ (pan, tilt, zoom) cameras by coordinate transformation. The feasibility and effectiveness of the proposed method are verified by test site experiments and actual line experiments, respectively. The proposed method greatly reduces manpower and improves inspection accuracy, providing a theoretical basis for intelligent inspection of transmission lines in the future.
机译:随着国民经济的增长,对电力的需求不断增加,这迫使输电线路的走廊变得结构复杂,并延伸到复杂的环境(例如山脉,森林)。在这些地区检查传输线是一个巨大的挑战。针对这些困难,提出了一种基于电缆巡检机器人(CIR)LiDAR数据的输电线路自主检查的新方法,主要包括两个步骤:初步检查和自主检查。在初步检查中,位置和定位系统(POS)数据用于原始点云划分,地面点过滤和结构化分区。建立分级分类策略以识别异常点的类别和位置。在自主检查中,CIR可以通过检查计划自主到达指定点。这些检查目标通过坐标转换通过PTZ(摇摄,倾斜,变焦)摄像机成像。分别通过测试现场实验和实际线路实验验证了该方法的可行性和有效性。所提出的方法大大减少了人力,提高了检测精度,为将来的输电线路智能检测提供了理论依据。

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