A novel spatter detection algorithm based on typical cellular neural network operations for laser beam welding processes
Real-time monitoring of laser beam welding (LBW) has increasingly gained importance in several manufacturing processes ranging from automobile production to precision mechanics. In the latter, a novel algorithm for the real-time detection of spatters was implemented in a camera based on cellular neu...
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| Veröffentlicht in: | Measurement science & technology 2012-01, Vol.23 (1), p.015401-1-8 |
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| container_title | Measurement science & technology |
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| creator | Nicolosi, L Abt, F Blug, A Heider, A Tetzlaff, R Höfler, H |
| description | Real-time monitoring of laser beam welding (LBW) has increasingly gained importance in several manufacturing processes ranging from automobile production to precision mechanics. In the latter, a novel algorithm for the real-time detection of spatters was implemented in a camera based on cellular neural networks. The latter can be connected to the optics of commercially available laser machines leading to real-time monitoring of LBW processes at rates up to 15 kHz. Such high monitoring rates allow the integration of other image evaluation tasks such as the detection of the full penetration hole for real-time control of process parameters. |
| doi_str_mv | 10.1088/0957-0233/23/1/015401 |
| format | Article |
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| ispartof | Measurement science & technology, 2012-01, Vol.23 (1), p.015401-1-8 |
| issn | 0957-0233 1361-6501 |
| language | eng |
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| source | IOP Publishing Journals; Institute of Physics (IOP) Journals - HEAL-Link |
| subjects | Algorithms Cellular Laser beam welding Monitoring Neural networks Real time Tasks |
| title | A novel spatter detection algorithm based on typical cellular neural network operations for laser beam welding processes |
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