Intelligent perception recognition and positioning method of distribution network drainage line

Shuzhou Xiao, Qiuyan Zhang, Q. Fan, Jianrong Wu, Chao Zhao
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Abstract

Due to the serious interference of illumination and background on the camera during the live operation of the distribution network robot, it is difficult to match, identify, and locate the feature points of the target image, such as the drainage line. This paper proposes the intelligent perception recognition and positioning method of the distribution network drainage line. First, YOLOv4 is used to identify and classify the typical parts of the distribution network and determine the two-dimensional position of the operation point. Subsequently, the Res-Unet segmentation network was improved to perform image segmentation of drainage lines and wires to avoid complex background interference. Finally, binocular vision is used to extract the center line of the wire through the image geometric moment and determine the image line of the wire and the center of the double eyes. The intersection line of the wire is the spatial three-dimensional coordinates of the wire. After the target detection, wire segmentation, and operation point positioning experiments, this method can achieve a positioning accuracy of 1 mm in the x and y directions and 3 mm in the z direction under the camera coordinate system, which provides a guarantee for accurate perception and recognition and reliable operation control of the power distribution robot operation.
配电网排水线路智能感知识别与定位方法
配电网机器人在现场运行过程中,由于光照和背景对摄像机的严重干扰,难以匹配、识别和定位目标图像的特征点,如排水线路。本文提出了配电网排水线路的智能感知识别与定位方法。首先,利用YOLOv4对配电网的典型部件进行识别和分类,确定操作点的二维位置。随后,对Res-Unet分割网络进行改进,对排水线进行图像分割,避免复杂背景干扰。最后,利用双目视觉通过图像几何矩提取线的中心线,确定线的图像线和双眼的中心。导线的交点线是导线的空间三维坐标。经过目标检测、线段分割、操作点定位实验,该方法在摄像机坐标系下可实现x、y方向1 mm、z方向3 mm的定位精度,为配电机器人运行的准确感知识别和可靠运行控制提供了保障。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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