Robust high-speed melt pool measurements for laser welding with sputter detection capability

Authors:
Nicolaj C. Stache;Henrik Zimmer;Jens Gedicke;Alexander Olowinsky;Til Aach
Affiliations:
Institute of Imaging & Computer Vision, RWTH Aachen University, Aachen, Germany;Institute of Imaging & Computer Vision, RWTH Aachen University, Aachen, Germany;Fraunhofer Institute for Laser Technology, Aachen, Germany;Fraunhofer Institute for Laser Technology, Aachen, Germany;Institute of Imaging & Computer Vision, RWTH Aachen University, Aachen, Germany
Venue:
Proceedings of the 29th DAGM conference on Pattern recognition
Year:
2007

Citing 2
Cited 0

Robust regression and outlier detection

Robust regression and outlier detection
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography

Communications of the ACM

Quantified Score

Hi-index	0.01

Visualization

Abstract

Although lasers are widely used for welding in precision engineering industry, it is still a challenge to achieve high accuracy in creating and positioning welding spots at extremely high processing speed. Towards this end, we propose a system for monitoring the welding process in order to ensure good quality of the welding spots. Our technology enables high speed image acquisition confocally to the laser beam with a direct view onto the melt. This innovative system permits accurate estimation of the melt pool's position and radius, which, however, must be performed at frame rates above 200 fps. We therefore employ fast correlation based approaches for sampling the melt pool's contour and robustly fitting a circle to it. In addition, the approaches enable sputter detection via outlier classification. To assess the performance of each presented method, extensive experiments are conducted. The proposed paradigms can furthermore be conveniently adapted to a variety of problems dealing with rapid shape estimation in noisy environments.