Machine Learning Models for Detecting Weld Bead Defects in Wire-Arc Additive Manufacturing

In the wire-arc additive manufacturing (WAAM) process, which creates metal layers with weld beads, it is important to detect weld bead defects and resolve them properly and timely. In this paper, we propose a machine learning approach for automatically detecting weld bead defects based on voltage signature data captured during the WAAM process. We adopt multi-layer perceptron (MLP) and convolutional neural network (CNN) as machine learning...