• DocumentCode
    2415898
  • Title

    Feature extraction in laser welding processes

  • Author

    Geese, Marc ; Tetzlaff, Ronald ; Carl, Daniel ; Blug, Andreas ; Höfler, Heinrich ; Abt, Felix

  • Author_Institution
    Johann Wolfgang von Goethe Univ., Frankfurt
  • fYear
    2008
  • fDate
    14-16 July 2008
  • Firstpage
    196
  • Lastpage
    201
  • Abstract
    There is a rapidly growing demand for laser welding in a wide variety of manufacturing processes ranging from automobile production to precision mechanics. Up to now, the high dynamics of the process has made it impossible to construct a camera based real time quality and process control. Since new pixel parallel architectures are existing, which are now available in systems such as the ACE16k, Q-Eye, and SCAMP-3 (P. Dudek et al., 2006), one has become able to implement a real time laser welding processing. In this paper we will propose a feature extraction algorithm, running at a frame rate of 10 kHz, for a laser welding process. The performance of the algorithm has been studied in detail. In particular, it has been implemented on an Eye-RIS v.1.1 system and has been applied to laser welding processes.
  • Keywords
    cameras; feature extraction; laser beam welding; manufacturing processes; process control; production engineering computing; quality control; ACE16k; Eye-RIS v.1.1 system; Q-Eye; SCAMP-3; automobile production; camera; feature extraction; laser welding processes; manufacturing processes; pixel parallel architectures; precision mechanics; process control; real time quality control; Cameras; Feature extraction; Inorganic materials; Laser beams; Laser theory; Manufacturing processes; Optical materials; Power lasers; Process control; Welding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cellular Neural Networks and Their Applications, 2008. CNNA 2008. 11th International Workshop on
  • Conference_Location
    Santiago de Compostela
  • Print_ISBN
    978-1-4244-2089-6
  • Electronic_ISBN
    978-1-4244-2090-2
  • Type

    conf

  • DOI
    10.1109/CNNA.2008.4588677
  • Filename
    4588677