机载LIDAR输电巡检中绝缘子缺陷识别研究

Research on Insulator Defect Identification in Airborne LIDAR Transmission Inspection

随着智能电网建设的大规模开展,对电网快速、高精度勘测、巡查和可视化管理提出了巨大的应用需求。在输电线路中绝缘子是电网中用量庞大、种类繁多的零部件,而且极易损坏。通过机载LIDAR及可见光传感器对输电通道绝缘子进行缺陷识别,利用Canny算法对绝缘子影像进行边缘检测,处理后所获取图像边缘更完整、清晰。边缘连接性更强,轮廓边缘的细节更加完整,能有效抑制噪声对边缘检测的干扰,实验结果表明,该方法可以较好地完成对目标图像的识别,从而对绝缘子缺陷监测和定位提供数据支撑。

With the large-scale development of smart grid construction,there is a huge application demand for rapid and high-precision survey,inspection and visual management of power grid.In the transmission line,insulator is a large amount of parts and components,and it is easy to be damaged.Through the airborne lidar and visible light sensor to identify the defects of the insulator in the transmission channel,and using canny algorithm to detect the edge of the insulator image,the edge of the image obtained after processing is more complete and clear.The edge connectivity is stronger,the details of the contour edge are more complete,which can effectively suppress the interference of noise on edge detection.The experimental results show that the method can better complete the recognition of the target image,thus providing data support for insulator defect monitoring and positioning.