Visual measurement and tracking in laser hybrid welding

Henri Fennander, Ville Kyrki*, Anna Fellman, Antti Salminen, Heikki Kälviäinen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

24 Citations (Scopus)

Abstract

This paper presents a novel system for the automatic analysis of a hybrid welding process. High-speed imaging and laser illumination are used to measure the regularity of electric arc frequency and flight directions of filler metal droplets. A fuzzy c-means clustering method is used to detect arcs and segment the video sequences. The droplets are localized by combining principal component analysis and a support vector machine classifier. The flight of a droplet is tracked using Kalman filtering. Experiments indicate that the system is able to track the flights of droplets and to determine the regularity of the arc frequency with a high accuracy if the imaging conditions are stable.

Original languageEnglish
Pages (from-to)103-118
Number of pages16
JournalMACHINE VISION AND APPLICATIONS
Volume20
Issue number2
DOIs
Publication statusPublished - Feb 2009
MoE publication typeA1 Journal article-refereed

Keywords

  • Fuzzy c-means clustering
  • Hybrid welding
  • Kalman tracking
  • Principal component analysis
  • Support vector machine

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