基于RBF的模具复杂曲面的逆向工程造型

Reverse Engineering Modeling of the Complicated Curved Surface of the Mould Based on RBF

根据产品试验件的外形数据 ,结合产品制造工艺过程中的变形信息 ,对模具复杂曲面进行逆向工程设计。采用RBF神经网络对天线罩模具进行逆向工程曲面重构 ,RBF神经网络具有很强的非线性逼近能力 ,模具曲面的重构精度高并且网络训练速度快 ,将RBF网络输出数据输入到CATIA的数字曲面编辑器 ,对模具曲面进行造型 ,该方法具有很高的实用推广价值。

Reverse engineering design has been conducted on the complicated curved surface of the mould for a sample,radar dome,according to the outline data of the sample and the deformation information measured in the manufacturing process.Radial Basis Function(RBF)neural network has been used to reconstruct the mould cavity surface.RBF neural network has a strong capability of nonlinear approximation,with a high reconstruction precision and high training speed.The output data from RBF neural network are input to the digital curved-surface editor of CATIA to design the model of the mould cavity surface.This method is valuable to practice and generalize.