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Feature extraction in laser welding processes

: Geese, M.; Tetzlaff, R.; Carl, D.; Blug, A.; Höfler, H.; Abt, F.

Volltext urn:nbn:de:0011-n-832088 (4.0 MByte PDF)
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Erstellt am: 12.11.2008

López Vilariño, D. ; Institute of Electrical and Electronics Engineers -IEEE-:
11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008 : Santiago de Composteia i.e. Compostela, Spain, 14 - 16 July 2008
New York, NY: IEEE, 2008
ISBN: 978-1-4244-2089-6
ISBN: 978-1-4244-2090-2
International Workshop on Cellular Neural Networks and their Applications (CNNA) <11, 2008, Santiago de Compostela>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IPM ()

There is a rapidly growing demand for laser welding in a wide variety of manufacturing processes ranging from automobile production to precision mechanics. Up to now, the high dynamics of the process has made it impossible to construct a camera based real time quality and process control. Since new pixel parallel architectures are existing, which are now available in systems such as the ACE16k, Q- Eye, and SCAMP-3 (P. Dudek et al., 2006), one has become able to implement a real time laser welding processing. In this paper we will propose a feature extraction algorithm, running at a frame rate of 10 kHz, for a laser welding process. The performance of the algorithm has been studied in detail. In particular, it has been implemented on an Eye-RIS v.1.1 system and has been applied to laser welding processes.