Product Code: ICAL08_1706

Closed Loop Control of Laser Welding Processes with Cellular Neural Network (CNN) Cameras
F. Abt, Forschungsgesellschaft Fuer Strahlwerkzeuge Fgsw; Stuttgart Germany
L. Nicolosi, Technische Universit�T Dresden; Dresden Germany
D. Carl, Ipm Fraunhofer Institut Fuer Physikalische Messtechnik; Freiburg Germany
A. Blug, Ipm Fraunhofer-Institut Fuer Physikalische Messtechnik; Freiburg Germany
M. Geese, Wolfgang Von Goethe Universitaet; Frankfurt Am Main Germany
C. Deininger, Technologiegesellschaft Fuer Strahlwerkzeuge Mbh Tgsw; Stuttgart Germany
F. Dausinger, Dausinger + Giesen Gmbh; Stuttgart Germany
H. H�Fler, Ipm Fraunhofer Institut Fuer Physikalische Messtechnik; Freiburg Germany
R. Tetzlaff, Technische Universitaet Dresden; Dresden Germany
Presented at ICALEO 2008

The growing number of laser welding applications from automobile production to micro mechanics, requires fast and reliable process control systems. The high process dynamics - especially in scanner based remote welding or high speed micro welding - demand extremely fast and spatially resolved in-process control systems to create closed loop control for error prevention and correction. Todays conventional micro processor based image processing architectures are not able to provide the high frame rates needed for the real-time closed loop control of high speed laser welding. With Cellular Neural Networks (CNN) it is possible to implement Single-Instruction-Multiple-Data (SIMD)-architectures on the camera chip itself (Focal Plane Processor FPP). Such pixel parallel systems provide extremely fast real-time image processing. With these new CNN-cameras it is now possible to implement a camera based high speed in-process control system for laser welding that enables closed loop control of various quality features. With a multi modal diagnostic approach we were able to identify direct and explicit image attributes for a variety of quality features as a base for the process control. It could be shown that closed loop control of the full-penetration quality feature is possible with frame rates of up to 10 kHz with a CNN-camera system.

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