Feature extraction in laser welding processes
Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/Gutachten › Beitrag in Konferenzband › Beigetragen › Begutachtung
Beitragende
Abstract
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 [1], Q-Eye [1], and SCAMP-3 [2], 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.
Details
Originalsprache | Englisch |
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Titel | 2008 11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008, Cellular Nano-scale Architectures |
Seiten | 196-201 |
Seitenumfang | 6 |
Publikationsstatus | Veröffentlicht - 5 Aug. 2008 |
Peer-Review-Status | Ja |
Publikationsreihe
Reihe | IEEE International Workshop on Cellular Neural Networks and their Applications |
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ISSN | 2165-0144 |
Konferenz
Titel | 2008 11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008, Cellular Nano-scale Architectures |
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Dauer | 14 - 16 Juli 2008 |
Stadt | Santiago de Compostela |
Land | Spanien |
Externe IDs
ORCID | /0000-0001-7436-0103/work/142240292 |
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