Laser welding monitoring with multisensory data fusion: A brief review

Abstract

As digital manufacturing is being implemented across industries, the automation of the laser welding process is a crucial step to enhance production efficiency. To monitor the in-situ welding process, there are several approaches to detect the electromagnetic and mechanical waves on various frequencies for comprehending laser beam-material interaction. Five sensing techniques, namely the optical microphone, welding camera, inline coherent imaging, infrared camera, and heat flux sensor, can be employed to identify distinct features in the laser welding process. These features include pore formation, melt pool geometry, weld bead topography, keyhole depth, and thermal distribution. The discussion of a proposed welding system designed with compatibility for multisensory data fusion is included, both on its capabilities and potential challenges, to offer guidance of welding monitoring.