Real time closed loop control of full penetration keyhole welding with cellular neural network cameras

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Felix Abt - , Universität Stuttgart (Autor:in)
  • Andreas Blug - , Fraunhofer Institute for Physical Measurement Techniques (Autor:in)
  • Leonardo Nicolosi - (Autor:in)
  • F. Dausinger - , Dausinger and Giesen GmbH (Autor:in)
  • Heinrich Höfler - , Fraunhofer Institute for Physical Measurement Techniques (Autor:in)
  • R. Tetzlaff - , Professur für Grundlagen der Elektrotechnik (GE) (Autor:in)
  • R. Weber - , Universität Stuttgart (Autor:in)

Abstract

Camera based in-process control for laser welding enables flexible image processing which allows the adaption of the system to different processes and quality features. A closed loop control system with a Cellular Neural Network Camera was implemented into a laser welding machine. The system is surveying the contour of the full penetration hole with a frame rate of over 10 kHz for both, acquisition and evaluation of area images. As a result the system reaches and holds the full penetration state automatically. This paper shows the latest experimental results including the extension to direction independent weldings.

Details

OriginalspracheEnglisch
Seiten (von - bis)131-137
Seitenumfang7
FachzeitschriftJournal of laser micro nanoengineering
Jahrgang6
Ausgabenummer2
PublikationsstatusVeröffentlicht - 2011
Peer-Review-StatusJa

Externe IDs

ORCID /0000-0001-7436-0103/work/142240325

Schlagworte

Schlagwörter

  • Cellular neural network (CNN), Closed loop, Laser welding, Process control

Bibliotheksschlagworte