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神经网络在机器人焊接参数规划中的应用

Application of Neural Networks in Welding Parameters's Planning of Robots

  • 摘要: 离线编程因其不占用生产时间、适用性广等优点,已成为机器人编程中的重要的一个分支。而机器人焊接参数规划器是弧焊机器人任务级离线编程的一个非常必要的组成模块。本文采用了前馈式神经网络的一种新的学习算法——单参数动态搜索算法(SPDS),以完成焊接参数规划任务。该算法的特点是单参数动态搜索,大大减少了误差函数的计算量。同时本文利用了函数连接的思想,完成了神经网络输入参数的预处理。计算结果表明,在焊接参数规划方面,该方法的收敛效果要优于现行的BP算法。

     

    Abstract: Off line programming has become an important branch in robotic programming because it has many advantages such as wide applicability and not occupying production time.Welding parameters' planning is one of necessary components in Robotic Arc Welding Task-level Off Line System(RAWTOLS).In order to go on welding parameters' planning,a new training algorithm of the feed forward neural networks,Single Parameter Dynamic Search algorithm,is utilized.Single parameter dynamic search is the characteristic of this algorithm and therefore the calculation quantum of the objective function is reduced greatly.And the idea of functional link is used to preprocess the input of neural networks.The result of the calculation shows that the convergence effect of this method is better than BP algorithm in the field of welding parameters' planning.

     

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