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Characterizing Spatters in Laser Welding of Thick Steel Using Motion Flow Analysis

Olli Lahdenoja, Tero Säntti, Jonne Poikonen, Mika Laiho, Ari Paasio, Characterizing Spatters in Laser Welding of Thick Steel Using Motion Flow Analysis. In: Erkki Oja, Matti Pietikäinen (Eds.), SCIA : 18th Scandinavian Conference on Image Analysis, Springer Lecture Notes in Computer Science (LNCS), 675–686, Springer Berlin Heidelberg, 2013.

Abstract:

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.

BibTeX entry:

@INPROCEEDINGS{inpLaSxPoLaPa13a,
  title = {Characterizing Spatters in Laser Welding of Thick Steel Using Motion Flow Analysis},
  booktitle = {SCIA : 18th Scandinavian Conference on Image Analysis},
  author = {Lahdenoja, Olli and Säntti, Tero and Poikonen, Jonne and Laiho, Mika and Paasio, Ari},
  series = {Springer Lecture Notes in Computer Science (LNCS)},
  editor = {Oja, Erkki and Pietikäinen, Matti},
  publisher = {Springer Berlin Heidelberg},
  pages = {675–686},
  year = {2013},
}

Belongs to TUCS Research Unit(s): Embedded Computer and Electronic Systems (ECES)

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