基于云计算的变电站机器人巡检路径规划研究

M. Tang, Fei Xia, Hu Song, Yuanhan Du, Ling Wang, Xinyun Cheng
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引用次数: 0

摘要

随着智能电网的不断发展,变电站的数量也在不断增加。针对变电站巡检任务繁重、人工巡检可视化水平低的问题,提出了一种基于云计算的变电站机器人巡检路径规划方法。通过基于图像识别的变电站场景等效建模,构建巡检机器人的运动模型,并采用改进的深度强化学习算法规划变电站机器人的巡检路径。通过实际变电站等效验证,所提出的改进卷积神经网络深度强化学习算法比传统算法计算时间更短,效率更高。更有利于准确规划变电站巡检机器人的巡检路径,提高变电站巡检的效率。自动化程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Path Planning of Substation Robot Inspection Based on Cloud Computing
With the continuous development of smart grids, the number of substations has also increased. Aiming at the problems of heavy inspection tasks in substations and low level of manual inspection visualization, this paper proposes a cloud computing-based substation robot inspection path planning method. Through the equivalent modeling of the substation scene based on image recognition, the motion model of the inspection robot is constructed, and the inspection path of the substation robot is planned by the improved deep reinforcement learning algorithm. Through the actual substation equivalent verification, the proposed deep reinforcement learning algorithm of the improved convolutional neural network has shorter calculation time and higher efficiency than the traditional algorithm. It is more conducive to accurate planning of the inspection path of the substation inspection robot, and improves the substation inspection. The level of automation.
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