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PTZ Control System of Indoor Rail Inspection Robot Based on Neural Network Prediction Model

机译:基于神经网络预测模型的室内轨道巡检机器人云台控制系统

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With the development of the automation of electric power system, indoor inspection rail robots are applied in many transformer substations to inspect the equipment. During the inspecting of robot, the PTZ plays an important role so that the accuracy of the PTZ determines the final inspection results to a large extent. The PTZ's control accuracy is influenced by the difference of the mechanical damping and gear clearance among different PTZs. A kind of PTZ control system based on neural network prediction model was designed in this article, which can improve the control accuracy of the PTZ by auto adjust difference among different PTZs. The hardware and software was designed for the PTZ control system. The Validity and reliability of the system was verified by the experimental result, which meets the requirements of robot inspection.
机译:随着电力系统自动化的发展,室内巡检机器人被应用于许多变电站,对设备进行巡检。在机器人检查过程中,PTZ扮演着重要的角色,因此PTZ的准确性在很大程度上决定了最终的检查结果。 PTZ的控制精度受不同PTZ之间机械阻尼和齿轮间隙的差异的影响。设计了一种基于神经网络预测模型的云台控制系统,可以通过自动调整不同云台之间的差异来提高云台的控制精度。硬件和软件是为PTZ控制系统设计的。实验结果验证了系统的有效性和可靠性,符合机器人检查的要求。

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