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Convolutional Neural Network Model for the Prediction of Back-Bead Occurrence in GMA Root Pass Welding of V-groove Butt Joint
2021
Journal of Welding and Joining
Gas metal arc (GMA) welding is widely used in the machinery industry. The quality of a welded joint is affected by the penetration of root pass welding in the V-groove joint. Automation using GMA welding is continuously required, and root pass welding automation is required to automate the entire welding process. In particular, the development of a prediction model that can ensure full penetration back-bead is required for the automation of root pass welding. In this study, a convolutional
doi:10.5781/jwj.2021.39.5.1
fatcat:shbrvs3buvg3jeddywzhwxjqji