人工神经网络在镀锌钢板点焊性能估测中的应用

将人工神经网络引入镀锌钢板点焊的质量预测中，将实验得到的大量点焊规范参数与相应点焊接头质量的试验数据提供给神经网络学习，通过其非线性映射的泛化能力自动抽取所学习知识的特征，描述点焊规范参数空间与焊点接头质量空间的映射关系。结果表明，学习后的神经网络的预测曲线能够合理地预测焊接电流对镀锌钢板点焊的焊点熔核直径与拉剪强度的影响规律，恰当地反映点焊的基本原理，说明人工神经网络在镀锌板点焊性能估测中的应用是可行的。

Application of Artificial Neural Networks to Performance Predicting in Spot Welding of Zinc-Coated Steel Sheets

Artificial neural networks (ANN) were used in quality predicting in the spot welding of zinc coated steel sheets. Lots of experimental data about welding parameters and corresponding spot weld quality were provided to the ANN. Through the generalization of nonlinear mapping, the characteristics of the learnt knowledge were summarized and the mapping relationship between welding parameters and welding quality was described by ANN after studying. The results show that the influence of welding currents on nugget diameters or shear loads of spot welds can be predicted by ANN, and the predicted curves made by ANN conform to the principles of resistance spot welding. So the application of ANN in quality predicting of zinc coated steel sheets is feasible.