基于无人机红外热像的电缆隐患点智能检测

城市输电电缆是城市电力供应的生命线,保障其安全可靠地运行是电网企业日常工作的重中之重,运维工作面临巨大的挑战,人工检查手段难以快速有效发现并及时排除隐患点.因此,本文提出基于无人机红外热像智能检测电缆隐患点的方法.首先,采用无人机对户外电缆终端进行航拍,得到户外电缆终端的红外热图;其次,对红外热图采用改进的Bernsen二值化处理;再次,使用投影法从二值化图像中提取出待检测的主体电缆,通过形态学方法去除背景或干扰区域对隐患点诊断的影响;最后,根据强度色谱确定主体电缆图像中颜色高亮的异常区域为隐患点.通过应用本方法,电网企业能够实现快速的缺陷识别,消缺和故障判断,全面提升城市输电电缆状态的管控能力.

Intelligently Detecting Hidden Points of Cables Based on Infrared Thermal Image of UAV

Urban transmission cables are the lifeline of urban power supply. It is important for grid corporations to ensure the safe and reliable operation of the cables in the daily work. It still remains to be a challenge and manual inspection is difficult to quickly and effectively find and eliminate hidden dangerous points. Therefore, this study proposes a method for intelligently detecting hidden dangerous points of cables based on infrared thermal images. First, using UAV to obtain the infrared map of the outdoor terminal of the cable. Next, the infrared thermal map is binarized by an improved Bernsen algorithm. Then, the projection method is used to extract the subject cables from the binary image in order to eliminate the influence of the background. Finally, according to the intensity chromatogram, the abnormal areas with bright colors in the subject cable image are determined as hidden dangerous points. By applying this method, grid corporations can achieve rapid defect identification, elimination, and fault judgment. It can comprehensively improve the ability to manage and control the status of urban transmission cables.