Splatter detection by artificial intelligence during laser processing

Abstract

A method for identifying splatters or weld seam defects during laser processing of a workpiece includes processing the workpiece using a processing laser beam of a laser processing machine, compiling at least one recording of radiation emerging during the processing of the workpiece using an optical sensor that has a plurality of pixels for recording the radiation, and inputting the at least one recording into an evaluation unit. The evaluation unit has a machine learning algorithm configured as a convolutional neural network in a U-Net architecture. The machine learning algorithm has been trained with verified recordings of splatters or weld seam defects. The method further includes identifying one or more splatters or weld seam defects in the processing of the workpiece by running the machine learning algorithm using the at least one recording as input, and outputting an output indicating the identified one or more splatters or weld seam defects.

Dependencies are inferred from the claim text.