Novel algorithm for the real time multi-feature detection in laser beam welding

Abstract

In this paper, a novel visual multi-feature detecting algorithm for the real time monitoring and control of laser beam welding (LBW) processes is discussed. It was implemented in the Eye-RIS vision system (VS) which includes a focal plane processor programmable by typical Cellular Neural Network (CNN) operators. The algorithm is based on the extraction of “spatters” - explosions of rear melt pool - to provide on-line quality information about the process and on the detection of the full penetration hole (FPH) for the laser power control to maintain a constant penetration depth into the workpiece. A single image evaluating step is performed in about 90 µs.