输电线路带电作业机器人机械手RBF神经网络控制

发布时间：2018-01-25 18:34

本文关键词： 引流板螺栓 RBF神经网络带电作业机器人机械手拧紧控制　出处：《东北大学学报(自然科学版)》2017年10期 　论文类型：期刊论文

【摘要】：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.
[Abstract]:A kind of double arms is designed in view of the low working efficiency, the high labor intensity and the high altitude high voltage danger of tightening the tension jumper draining plate bolt of the high voltage transmission line completely relying on the manual live. In the whole working process, the key problems of bolt tightening are analyzed theoretically. The RBF neural network model of bolt tightening process control is established. The bolt tightening process of robot is abstracted as a nonlinear approximate control problem of neural network. The monitoring and control method of bolt tightening state based on RBF neural network is proposed. Finally, the test results of live operation show that the reliability of bolt fastened by the control method is enhanced. It is verified that the proposed method has strong engineering practicability, and further improves the work efficiency, job safety and operation maneuverability.
【作者单位】：武汉大学动力与机械学院;国网吉林省电力有限公司白山供电公司;
【基金】：国家自然科学基金资助项目(51105281) 国网吉林省电力有限公司资助项目(JDK2016-19)
【分类号】：TM75;TP242
【正文快照】： 耐张杆塔是高压输电线路的主要组成部分之一,位于这类杆塔两侧的高压输电导线都是由耐张跳线和引流板两个关键部件联接起来的.由于恶劣自然环境下的外力震动及杆塔的施工工艺等各种因素容易造成引流板的螺栓发生松动导致接触不良后其接头处电阻变大,引流板的温度会大幅升高,在

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