输电线路带电作业机器人机械手RBF神经网络控制

针对完全依靠人工带电拧紧高压输电线路耐张跳线引流板螺栓作业效率低、劳动强度大、高空高压危险设计了一种双臂、双机械手的螺栓紧固带电作业机器人.在整个作业过程中着重对螺栓拧紧的关键问题进行了理论分析,建立了螺栓拧紧过程控制的RBF神经网络模型.将机器人的螺栓拧紧过程抽象为神经网络的非线性逼近控制问题,提出了基于RBF神经网络的机器人螺栓拧紧状态监测控制方法.最后带电作业试验结果显示经过该控制方法机器人拧紧的螺栓联接可靠性增强,验证了所提出方法具有较强的工程实用性,同时进一步提高了作业效率、作业安全性及作业可操作性.

RBF Neural Network Control of Live Operation Robot Manipulator for High Voltage Transmission Line

Due to the shortage of manual tension clamp drainage board bolt tighten for high voltage transmission line， such as low operation efficiency， labor-intensive， high-altitude and high risk， an bolt tighten live operation robot was designed which had double arms and double manipulators. The key issues of bolt tighten was analyzed theoretically during the entire operation process， and a RBF neural network model of bolt tighten process control was established. The robot bolt tighten process was abstracted into nonlinear approximation， and a robot bolt tighten status monitoring control method based on the RBF neural network was proposed. Finally the live operation result showed that the connection reliability of the robot tighten bolts is greatly enhanced by using the proposed method that has strong engineering practicability， and the operation efficiency ，operation safety and operation operability are all improved.