Spatter tracking in laser machining

Timo Viitanen, Jari Kolehmainen, Robert Piché, Yasuhiro Okamoto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

In laser drilling, an assist gas is often used to remove material from the drilling point. In order to design assist gas nozzles to minimize spatter formation, measurements of spatter trajectories are required. We apply computer vision methods to measure the 3D trajectories of spatter particles in a laser cutting event using a stereo camera configuration. We also propose a novel method for calibration of a weak perspective camera that is effective in our application. The proposed method is evaluated with both computer-generated video and video taken from actual laser drilling events. The method performs well on different workpiece materials.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages626-635
Number of pages10
Volume7432 LNCS
EditionPART 2
DOIs
Publication statusPublished - 2012
Event8th International Symposium on Visual Computing, ISVC 2012 - Rethymnon, Crete, Greece
Duration: Jul 16 2012Jul 18 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume7432 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other8th International Symposium on Visual Computing, ISVC 2012
CountryGreece
CityRethymnon, Crete
Period7/16/127/18/12

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ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Viitanen, T., Kolehmainen, J., Piché, R., & Okamoto, Y. (2012). Spatter tracking in laser machining. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 2 ed., Vol. 7432 LNCS, pp. 626-635). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7432 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-33191-6_62