Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
Application of laser welding technology requires that the laser beam is guided through the whole length of the joint with sufficiently high accuracy. This paper describes result of research on development of optomechatronic system that allows for the precise positioning of the laser head’s TCP point on the edge of welded elements during laser processing. The developed system allows for compensation of workpiece’s fixture inaccuracies, precast distortions and workpiece deformations occurring during the process.
Czasopismo
Rocznik
Tom
Strony
265--269
Opis fizyczny
Bibliogr. 14 poz., rys., wykr.
Twórcy
autor
- Department of Laser Technology, Automation and Organization of Production, Wroclaw University of Technology, Wybrzeże Wyspiańskiego 27 50-370 Wrocław, Poland
autor
- Department of Laser Technology, Automation and Organization of Production, Wroclaw University of Technology, Wybrzeże Wyspiańskiego 27 50-370 Wrocław, Poland
autor
- Department of Laser Technology, Automation and Organization of Production, Wroclaw University of Technology, Wybrzeże Wyspiańskiego 27 50-370 Wrocław, Poland
Bibliografia
- 1. De Graaf M. (2007), Sensor-guided robotic laser welding, University of Twente.
- 2. De Graaf M., Aarts R., Meijer J., Jonker J.B. (2005), Robot-sensor synchronization for real-time seam tracking in robotic laser welding, Proceeding of the Third International WLT-Conference on Lasers in Manufacturing, Munich.
- 3. De Graaf M., Aarts R., Jonker J.B., Meijer J. (2010), Real-time seam tracking for robotic laser welding using trajectory-based control, Control Eng. Pract., Vol. 18, No. 8, 944-953.
- 4. Dorsch F., Pfitzner D., Braun H. (2013), Improved continous tube welding due to unique process sensor system and process control, Phys. Procedia, Vol. 41, 137-139.
- 5. Fridenfalk M., Bolmsjö G. (2003), Design and validation of a universal 6D seam tracking system in robotic welding based on laser scanning, Industrial Robot: An International Journal, Vol. 30, No. 5, 437-448.
- 6. Gao X., Zhong X., You D. (2013), Kalman Filtering Compensated by Radial Basis Function Neural Network for Seam Tracking of Laser Welding, IEEE Trans. Control Syst. Technol., Vol. 21, No. 5, 1916- 1923
- 7. Huang W., Kovacevic R. (2011), A Laser-Based Vision System for Weld Quality Inspection, Sensors, Vol. 11, 506-521.
- 8. Huang W., Kovacevic R. (2012), Development of a real-time laserbased machine vision system to monitor and control welding processes, The International Journal of Advanced Manufacturing Technology, Vol. 63(1), 235-248.
- 9. Lee S.K., Na S. J. (2012), A study on automatic seam tracking in pulsed laser edge welding by using a vision sensor without an auxiliary source, Journal of Manufacturing Systems, Vol. 21(4), 302-315
- 10. Michalos G., Makris S., Eytan A., Matthaiakis S., Chryssolouris G. (2012), Robot Path Correction Using Stereo Vision System, Procedia CIRP, Vol. 3, 352-357.
- 11. Rafajłowicz E., Rafajłowicz W., Rusiecki A. (2009), Image processing algorithms and an introduction to working with the OpenCV library (in Polish), Wroclaw University of Technology Press.
- 12. Regaard B., Kaierle S., Poprawe R. (2009), Seam-tracking for high precision laser welding applications – Methods, restrictions and enhanced concepts, Journal of Laser Applications, Vol. 21 (4), 841– 875.
- 13. Siciliano B., Khatib O. (eds.) (2008), The Handbook of Robotics, Springer, Berlin, Heidelberg. 14. Siemens AG. (2006), SINUMERIK 840D Configuring the NCU.
- 14. Siemens A G. (2006), SINUMERIK 840D Configuring the NCU.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-735c8ce5-40a0-4367-8232-ce9cbad2c07e