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A monitoring system for laser beam welding based on an algorithm for spatter detection

: Nicolosi, L.; Tetzlaff, R.; Blug, A.; Höfler, H.; Carl, D.; Abt, F.; Heider, A.


Institute of Electrical and Electronics Engineers -IEEE-:
ECCTD 2011, 20th European Conference on Circuit Theory and Design : August 29-31, 2011 in Linköping, Sweden
Piscataway/NJ: IEEE, 2011
ISBN: 978-1-4577-0616-5
ISBN: 1-4577-0616-4
ISBN: 1-4577-0617-2
ISBN: 978-1-4577-0617-2
ISBN: 978-1-4577-0618-9
European Conference on Circuit Theory and Design (ECCTD) <20, 2011, Linköping>
Fraunhofer IPM ()
CNN; cellular neural network (CNN); SIMD processor; closed loop system; feature extraction; laser welding; spatter

This paper deals with the realization of a visual monitoring system for the real time detection of spatters in laser beam welding (LBW). Spatters deteriorate the corrosion resistance and the aesthetics of the welding result. Therefore, the real time detection of spatters allows providing on-line quality information about the process, thus reducing material waste in production chains. The proposed Cellular Neural Network (CNN) based algorithm has been implemented in the Eye-RIS vision system (VS). Monitoring rates up to 15 kHz have been reached, allowing the integration of the spatter detection with the evaluation of additional image features, e.g. the full penetration hole (FPH).