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基于RBF网络的自适应熔焊插补容错算法

来旭辉,许燕,周建平,伊里哈木·阿布都热木

来旭辉,许燕,周建平,伊里哈木·阿布都热木. 基于RBF网络的自适应熔焊插补容错算法[J]. 焊接学报, 2018, 39(10): 81-87. DOI: 10.12073/j.hjxb.2018390253
引用本文: 来旭辉,许燕,周建平,伊里哈木·阿布都热木. 基于RBF网络的自适应熔焊插补容错算法[J]. 焊接学报, 2018, 39(10): 81-87. DOI: 10.12073/j.hjxb.2018390253
LAI Xuhui, XU Yan, ZHOU Jianping, Ilham ABDUREYIM null. Adaptive fault tolerant fusion interpolation algorithm based on RBF network[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2018, 39(10): 81-87. DOI: 10.12073/j.hjxb.2018390253
Citation: LAI Xuhui, XU Yan, ZHOU Jianping, Ilham ABDUREYIM null. Adaptive fault tolerant fusion interpolation algorithm based on RBF network[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2018, 39(10): 81-87. DOI: 10.12073/j.hjxb.2018390253

基于RBF网络的自适应熔焊插补容错算法

Adaptive fault tolerant fusion interpolation algorithm based on RBF network

  • 摘要: 为使非均匀有理B样条插补(NURBS插补)过程中速度变化平稳,设计了一种步长可控的实时插补算法. 推导了参数曲线的一般求值方法,并通过递推矩阵快速计算,能够根据曲线形状的变化,主动调整加工速度,并通过速度再修正模块保证微段曲线中加速度恒定,在满足机床启停能力的基础上平稳加工. 将径向基网络(RBF)和模糊控制相结合,实时筛选故障参数进行再训练,并编写可视化软件进行成形试验,对成形质量、成形速度加速度和预测精度进行分析评价. 试验结果表明,该算法与RBF网络和模糊控制相配合,能够在保证成形精度和设备稳定性的基础上使软件具有一定的容错能力.
    Abstract: In order to change the speed of NURBS interpolation smoothly, a real time interpolation algorithm is designed. The general evaluation method of parametric curve is deduced and the fast computation is done by recursive matrix. It can adjust the processing speed according to the shape of the curve. Then the acceleration of the micro section curve can be guaranteed by the velocity correction module and process smoothly based on the machine's starting and stopping ability. The RBF network and fuzzy control are combined, and the fault parameters are retrained in real time and then the visualization software is used to make the experiment in order to analyze and evaluate the forming quality, forming speed and prediction precision. The experimental results show that the algorithm can ensure the accuracy and stability of the equipment based on a certain degree of fault tolerance with the combination of RBF network and fuzzy control.
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  • 收稿日期:  2017-05-28

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