Optimization of the Weld Pool Boundary Calculated by the LSTM-Based Measurement Method in GTAW

Abstract

The shape of the weld pool surface contains a lot of important features to reflect the quality of the weld. However, it is difficult to obtain the weld pool boundary precisely. In this paper, a boundary extension method is designed first to optimize the boundary profile of the interpolated weld pool surface calculated by the long-short-term memory (LSTM)-based measurement method. Experimental results show that after boundary extension, the errors of the left and right part of the boundary of the weld pool are slightly improved. The weld width error in the X direction is reduced to 2.43%, and the weld width error in the Y direction is slightly increased to 8.68%. Then the robustness of the LSTM-based model is analyzed by studying the phenomena of missing points and more points. To solve the problem caused by the missing/adding the first few imaging points, a forward-reverse united reconstruction optimization method is then designed. After optimization by forward-reverse united reconstruction optimization method, the boundary error of the reconstructed weld pool surface is obviously reduced. The weld width error is reduced to 1.62% in the X direction and 3.94% in the Y direction.

Keywords

• Gas Tungsten Arc Welding (GTAW)
• weld pool surface
• LSTM neural network
• measurement
• reconstruction