Feature extraction in laser welding processes
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
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
Original language | English |
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Title of host publication | 2008 11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008, Cellular Nano-scale Architectures |
Pages | 196-201 |
Number of pages | 6 |
Publication status | Published - 5 Aug 2008 |
Peer-reviewed | Yes |
Publication series
Series | IEEE International Workshop on Cellular Neural Networks and their Applications |
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ISSN | 2165-0144 |
Conference
Title | 2008 11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008, Cellular Nano-scale Architectures |
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Duration | 14 - 16 July 2008 |
City | Santiago de Compostela |
Country | Spain |
External IDs
ORCID | /0000-0001-7436-0103/work/142240292 |
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