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Solar UAV for the Inspection and Monitoring of Photovoltaic (PV) Systems in Solar Power Plants

机译:太阳能发电厂光伏(PV)系统的检查和监测的太阳能UAV

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This paper aims to design and fabricate a prototype of a solar-powered, fixed-wing, Unmanned Aerial Vehicle (UAV) with energy harvesting capabilities that can inspect and monitor panel arrays in solar power plants. In the energy sector, workers are susceptible to hazards such as working at large heights, high voltage contact, confined areas, and variable weather. Drone technology can be used to provide realtime, high-quality data that plant managers can use to conduct safe inspections, all at a low-cost. The primary goal for the UAV concept presented in this paper is use a lightweight, renewable energy source called Thermophotovoltaics, and attach the system to the wing of a drone to significantly extend its flight time without compromising the UAV's weight, size, or maneuverability and provide power for long-duration missions without having to land. The UAV concept will incorporate three technologies: machine learning algorithms, artificial intelligence and path-planning, and recognition methods. These methods will be used to achieve high accuracy and precision information on the degradation or defect presence on individual solar panel modules. In addition, thermal and optical imaging may reveal compromises in the solar panel array via electrical errors or structural issues.
机译:本文旨在设计和制造太阳能固定翼,无人驾驶飞行器(UAV)的原型,其能量收集能力可以检查和监控太阳能发电厂的面板阵列。在能源部门,工人易受危害的影响,如在大高度,高压接触,限制区域和可变天气下工作。无人机技术可用于提供实时,植物管理人员可以用于进行安全检查的高质量数据,所有这些数据都以低成本。本文提出的UAV概念的主要目标是使用轻量级,可再生能源,称为捕气器,并将系统连接到无人机的机翼,以显着扩展其飞行时间,而不会影响无人机的重量,尺寸或机动性和提供长期任务的力量而不落地。 UAV概念将包含三种技术:机器学习算法,人工智能和路径规划,以及识别方法。这些方法将用于实现有关各个太阳能电池板模块上的降低或缺陷的高精度和精确信息。另外,热和光学成像可以通过电误差或结构问题揭示太阳能电池板阵列中的折射。

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