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Deep Learning Based System to Electric Distribution Network Inspection

机译:基于深度学习的配电网检测系统

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In this paper, the authors discuss the results of the IA based on deep learning to improve the productivity of preventive thermographic inspections of the electrical network when compared to manual methods of analysis. The goal of this process is to use computer to capture and recognize images of hot spots from the distribution powergrid network during car's inspection deslocation. In order to that, a special vehicle was assembled. Initially the vehicle was equipped with eight cameras to proceed inspection in both side of the road and covers the front view as well. This solution results in the capability to inspect hundreds of miles of power distribution lines without the need to stop the vehicle and without the need for a human operator.
机译:在本文中,作者讨论了基于深度学习的IA的结果,与手动分析方法相比,该结果可提高对电网进行预防性热成像检查的效率。此过程的目标是在汽车检查错位期间,使用计算机捕获并识别配电网电网中的热点图像。为此,组装了一种特殊的车辆。最初,该车辆配备了八个摄像头,可以在道路两侧进行检查,并且还覆盖了正视图。该解决方案使得能够检查数百英里的配电线路,而无需停止车辆,也不需要人工。

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