关键词: 径向基函数网络, 键合机, 误差, 修正, 精度

Abstract: To improve precision of bonding position which is a key technical index for bonder，a new compensation method based on neural network was proposed.A model based on Radial Basis Function（RBF）was set up，in which the output was bonding coordinate and the input was bonding angle.According to the inhibit condition between the test value and the output of the network，adjusting power factor formula and the center and width of the radial basis function to make the model have a good learning ability and generalization ability.The optimization algorithm reduces the running time to a practical degree but doesn't decrease the compensation precision obviously.The test results show that the system precision is improved by an order of magnitude by this optimal method and the nonlinear effect on the system is reduced.

Key words: radial basis function network, wire bonder, error, compensation, precision