Research on prediction method of fusion forming coefficient at the bottom of ultra-narrow gap weld bead

Abstract

The fusion formation coefficient at the bottom of the weld bead is a key parameter to characterize the formation of a single-pass weld in ultra-narrow gap welding, and it is also an important content of welding quality control. Combined with the characteristics of the ultra-narrow gap welding method and the welding process, 14 characteristic parameters affecting the forming coefficient were extracted from the welding process signal and pre-welding preset parameters, and a convolutional neural network and a bidirectional long-short-term memory network (CNN-BILSTM-Attention) were established.) of the welding bead fusion forming coefficient prediction model, the results show that the model can effectively predict the welding bead fusion forming coefficient, and the mean square error of the prediction reaches 0.017, which provides a basis for further online control of welding quality.