Feature extraction in laser welding processes

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...

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Bibliographic Details
Published in2008 11th International Workshop on Cellular Neural Networks and Their Applications pp. 196 - 201
Main Authors Geese, M., Tetzlaff, R., Carl, D., Blug, A., Hofler, H., Abt, F.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2008
Subjects
Laser beams
Materials
Metals
Pixel
Process control
Real time systems
Welding
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ISBN142442089X
9781424420896
ISSN2165-0144
DOI10.1109/CNNA.2008.4588677

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Summary: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.
ISBN:142442089X
9781424420896
ISSN:2165-0144
DOI:10.1109/CNNA.2008.4588677