基于RBF神经网络的难加工金属材料数控加工控制方法研究

Based on the RBF neural network control nc machining of difficult-to-machine metal material research methods

采用RBF神经网络开发的针对钛舍金等难加工金属材料数控加工的难题,结合数控加工设备实时监控难加工金属材料,应用效果表明,对难加工材料数控加工进行RBF神经网络控制后,工件圆度误差和粗糙度误差得到了有效的降低。

Using RBF neural network is developed for the titanium give gold and other difficult processing problem of nc machining of metallic materials,combined with the numerical control processing equipment real-time monitoring difficult processing metal materials,application effect shows that the nc machining of difficult-to-machine materials for RBF neural network control,