20.500.12556/RUL-127284 Power control during remote laser welding using a convolutional neural network The increase in complex workpieces with changing geometries demands advanced control algorithms in order to achieve stable welding regimes. Usually, many experiments are required to identify and confirm the correct welding parameters. We present a method for controlling laser power in a remote laser welding system with a convolutional neural network (CNN) via a PID controller, based on optical triangulation feedback. AISI 304 metal sheets with a cumulative thickness of 1.5 mm were used. A total accuracy of 94% was achieved for CNN models on the test datasets. The rise time of the controller to achieve full penetration was less than 1.0 s from the start of welding. The Gradient-weighted Class Activation Mapping (Grad-CAM) method was used to further understand the decision making of the model. It was determined that the CNN focuses mainly on the area of the interaction zone and can act accordingly if this interaction zone changes in size. Based on additional testing, we proposed improvements to increase overall controller performance and response time by implementing a feed-forward approach at the beginning of welding. convolutional neural network remote laser welding laser-power control triangulation feedback konvolucijske nevronske mreže lasersko daljinsko varjenje nadzor moči laserja triangulacijska povratna zanka true false true Angleški jezik Slovenski jezik Članek v reviji 2021-06-02 10:04:31 2021-06-02 10:04:36 2022-09-06 03:50:33 0000-00-00 00:00:00 2020 0 0 15 str. iss. 22, art. 6658 Vol. 20 Nov. 2020 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 621.791.725:004.032.26(045) 1424-8220 10.3390/s20226658 39691267 RAZ_Bozic_Alex_2020.pdf RAZ_Bozic_Alex_2020.pdf 1 9979AA6545458386637BB42762362B5F eb26cac1e281f01e102fc61c335fd1fc4a462021af6f84e1d86a0349f7e5c240 a72f4909-8021-11ec-abdb-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=153353 https://www.mdpi.com/1424-8220/20/22/6658 0 197cca06-c379-11eb-a523-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=143612 Fakulteta za strojništvo 0 0 0