蛙跳式充电的无人机自主巡线技术与系统(二):基于机器视觉的自动充电控制
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刘杰荣(1985-),男,硕士,高级工程师,主要从事电力设备状态评价与检测方面的研究;E-mail:2034482563@qq.com

中图分类号:

TM755

基金项目:

南方电网公司重点科技项目(GDKJXM20180091)


Autonomous patrol technology and system of leapfrogcharging UAV (Ⅱ): automatic charging control based on machine vision
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    摘要:

    近年来多旋翼无人机在中国电力系统中得到了快速的推广和运用,越来越多的电力公司尝试利用无人机进行输电线路巡检。然而无人机在搭载巡检设备后,其续航时间仅为20min,续航能力十分有限,巡检时无人机中途降落充电的定位问题也一直存在。因此,该文提出一种基于机器视觉的自动充电控制技术,搭建基于蛙跳式的无人机自主充电系统。系统由无人机平台、自动充电平台和地面控制系统三部分构成,依托智能控制技术和飞控系统, 运用机器视觉、图像识别等技术实现无人机的高精度定位和智能精准降落,并结合无人机预设的卡位与地面充电平台充电接口的有效对接,完成无人机动力电池的自动可靠充电,进而实现巡线无人机的自动起降和充电功能。试验结果表明,该蛙跳式自主充电系统有效提高了无人机的续航能力,解决了无人机充电过程中高精度定位等系列技术难题。

    Abstract:

    Rotorcraft unmanned aerial vehicle (UAV) has been applied rapidly in the domestic electric power system. However, when loaded with patrol equipment, the drone's endurance time becomes only 20 minutes, which is limited. Therefore, based on machine vision, this paper proposes a key technology of automatic charging control to build the leapfrog automatic charging system. The system comprises of leapfrog type UAV charging platform, UAV automatic charging platform and ground control system. According to the flight control and intelligent control, with the aid of machine vision and image recognition technology to realize high precision positioning and automatic charging platform of intelligent precision landing, considering the connection of the clamping position and charging interface of UAV charging platform, the UAV battery automatic charging and the automatic takeoff and landing recharge are realized. The experimental results show that the problem of high precision positioning during UAV charging is effectively solved by using the leapfrog charging platform and machine vision image recognition and shutdown technology.

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刘杰荣,王伟冠,何其淼,等.蛙跳式充电的无人机自主巡线技术与系统(二):基于机器视觉的自动充电控制[J].电力科学与技术学报,2021,36(6):182-188.
LIU Jierong, WANG Weiguan, HE Qimiao, et al. Autonomous patrol technology and system of leapfrogcharging UAV (Ⅱ): automatic charging control based on machine vision[J]. Journal of Electric Power Science and Technology,2021,36(6):182-188.

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  • 在线发布日期: 2022-01-05
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