A4 Refereed article in a conference publication
Characterizing spatters in laser welding of thick steel using motion flow analysis
Authors: Lahdenoja O, Säntti T, Poikonen J, Laiho M, Paasio A
Editors: Joni-Kristian Kämäräinen, Markus Koskela
Publication year: 2013
Journal: Lecture Notes in Computer Science
Book title : 18th Scandinavian Conference on Image Analysis
Journal name in source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
First page : 675
Last page: 686
Number of pages: 12
ISBN: 978-3-642-38885-9
eISBN: 978-3-642-38886-6
ISSN: 0302-9743
DOI: https://doi.org/10.1007/978-3-642-38886-6_63
Web address : http://api.elsevier.com/content/abstract/scopus_id:84884478220
Laser welding has become a very important method for industrial manufacturing. Despite of the inherent accuracy of laser welding, the resulting weld quality may still be affected by many dynamic conditions related to the operating parameters and to the properties of the welded material. Methods for monitoring the laser welding process are therefore needed to guarantee consistent manufacturing quality. In this paper, we present a method for characterizing spatters in laser welding of thick steel. Pre-processing and edge detection steps of the proposed algorithm are performed on-line with a very high speed by using a dedicated KOVA1 massively parallel image processing chip, and the actual characterization of the spatters is carried out off-line in Matlab. The methods proposed are simple and efficient, thus also facilitating possible integration of the whole algorithm for on-line processing. © 2013 Springer-Verlag.
