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Closed loop control of laser welding processes using cellular neural network cameras: Measurement technology

: Blug, A.; Abt, F.; Nicolosi, L.; Carl, D.; Dausinger, F.; Höfler, H.; Tetzlaff, R.; Weber, R.

Postprint urn:nbn:de:0011-n-1193117 (819 KByte PDF)
MD5 Fingerprint: c655496e8aabaf9d9ea747e2fb2a8106
Erstellt am: 5.3.2010

Liu, X. ; Laser Institute of America -LIA-:
ICALEO 2009. Congress proceedings. CD-ROM : 28th International Congress on Applications of Lasers & Electro-Optics, November 2-5, 2009
Orlando, Fla.: LIA, 2009 (LIA 612, Vol.102)
Paper 1504
International Congress on Applications of Lasers and Electro Optics (ICALEO) <28, 2009, Orlando/Fla.>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IPM ()
CNN; image processing; laser welding

Today, image processing using coaxial camera setups is used to monitor the quality of laser material processes such as laser welding, cutting or ablation. This article proposes a sensing system for the next step: Using image based quality features to form an instant feedback signal in order to maintain the process in the desired state. The key component of the system is a camera based on Cellular Neural Networks (CNN). This technology enables real time image processing which is necessary for a robust feature analysis in highly dynamic laser processes. It is used to control the laser power of a welding system by the contour of the full penetration hole. Compared to conventional systems, the frame rate for both, acquisition and evaluation rises from about 1 kHz to 14 kHz. This paper prese nts the measurement technology including algorithms and some welding results which demonstrate that the full penetration state is maintained even under rapidly changing process conditions such as steps in material thickness or variation of speed. An in-depth discussion on welding results is found in [1].