A cross-process welding penetration status prediction algorithm based on unsupervised domain adaptation in laser and TIG welding

arXiv:2606.26078v1 Announce Type: cross Abstract: Supervised deep learning has been widely used for weld penetration state classification; however, its performance often degrades significantly under domain shift, such as when transferring models between welding processes with distinct physical mechanisms:for instance, from arc-dominated tungsten inert gas (TIG) welding to keyhole-based laser welding. To overcome this limitation, we propose an unsupervised domain adaptation (UDA) framework integr