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Proceedings Paper

Seam tracking with adaptive image capture for fine-tuning of a high power laser welding process
Author(s): Olli Lahdenoja; Tero Säntti; Mika Laiho; Ari Paasio; Jonne K. Poikonen
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Paper Abstract

This paper presents the development of methods for real-time fine-tuning of a high power laser welding process of thick steel by using a compact smart camera system. When performing welding in butt-joint configuration, the laser beam’s location needs to be adjusted exactly according to the seam line in order to allow the injected energy to be absorbed uniformly into both steel sheets. In this paper, on-line extraction of seam parameters is targeted by taking advantage of a combination of dynamic image intensity compression, image segmentation with a focal-plane processor ASIC, and Hough transform on an associated FPGA. Additional filtering of Hough line candidates based on temporal windowing is further applied to reduce unrealistic frame-to-frame tracking variations. The proposed methods are implemented in Matlab by using image data captured with adaptive integration time. The simulations are performed in a hardware oriented way to allow real-time implementation of the algorithms on the smart camera system.

Paper Details

Date Published: 14 February 2015
PDF: 7 pages
Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 94451V (14 February 2015); doi: 10.1117/12.2180872
Show Author Affiliations
Olli Lahdenoja, Univ. of Turku (Finland)
Tero Säntti, Univ. of Turku (Finland)
Mika Laiho, Univ. of Turku (Finland)
Ari Paasio, Univ. of Turku (Finland)
Jonne K. Poikonen, Univ. of Turku (Finland)


Published in SPIE Proceedings Vol. 9445:
Seventh International Conference on Machine Vision (ICMV 2014)
Antanas Verikas; Branislav Vuksanovic; Petia Radeva; Jianhong Zhou, Editor(s)

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