Characterizing Spatters in Laser Welding of Thick Steel Using Motion Flow Analysis

  • Olli Lahdenoja
  • Tero Säntti
  • Jonne Poikonen
  • Mika Laiho
  • Ari Paasio
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7944)


Laser welding has become a very important method for industrial manufacturing. Despite of the inherent accuracy of laser welding, the resulting weld quality may still be affected by many dynamic conditions related to the operating parameters and to the properties of the welded material. Methods for monitoring the laser welding process are therefore needed to guarantee consistent manufacturing quality. In this paper, we present a method for characterizing spatters in laser welding of thick steel. Pre-processing and edge detection steps of the proposed algorithm are performed on-line with a very high speed by using a dedicated KOVA1 massively parallel image processing chip, and the actual characterization of the spatters is carried out off-line in Matlab. The methods proposed are simple and efficient, thus also facilitating possible integration of the whole algorithm for on-line processing.


Motion flow Optical flow Spatters Laser welding Thick steel High-Speed Imaging 


  1. 1.
    Shao, J., Yan, Y.: Review of techniques for On-Line Monitoring and Inspection of Laser Welding. Journal of Physics: Conf. Ser. 15, 101–107 (2005)CrossRefGoogle Scholar
  2. 2.
    Norman, P., Engström, H., Kaplan, A.F.H.: State-of-the-art of monitoring and imaging of laser welding defects. In: 11th NOLAMP Conference in Laser Processing of Materials, Lappeenranta, Finland (2007)Google Scholar
  3. 3.
    Jäger, M., Humbert, S., Hamprecht, F.A.: Sputter Tracking for the Automatic Monitoring of Industrial Laser-Welding Processes. IEEE Transactions on Industrial Electronics 55(5), 2177–2184 (2008)CrossRefGoogle Scholar
  4. 4.
    Nicolosi, L., Tetzlaff, R., Abt, F., Heider, A., Blug, A., Hofler, H.: Novel algorithm for the real time multi-feature detection in laser beam welding. In: IEEE International Symposium on Circuits and Systems (ISCAS), pp. 181–184 (2012)Google Scholar
  5. 5.
    Rodríguez-Vázquez, A., Domínguez-Castro, R., Jiménez-Garrido, F., Morillas, S., Listán, J., Alba, L., Utrera, C., Espejo, S., Romay, R.: The Eye-RIS CMOS Vision System. In: Casier, H., Steyaert, M., Roermond, A.V. (eds.) Analog Circuit Design: Sensors: Actuators and Power Drives: Integrated Power Amplifiers from Wireline to RF: Very High Frequency Front Ends (2). Springer (2008)Google Scholar
  6. 6.
  7. 7.
    Laiho, M., Poikonen, J., Paasio, A.: MIPA4k: Mixed-Mode Cellular Processor Array. In: Zarandy, A. (ed.) Focal-Plane Sensor-Processor Chips. Springer (2011)Google Scholar
  8. 8.
    Brox, T., Bruhn, A., Papenberg, N., Weickert, J.: High Accuracy Optical Flow Estimation Based on a Theory for Warping. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3024, pp. 25–36. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  9. 9.
    Lahdenoja, O., Laiho, M.: Regional image correspondence matching method for SIMD processing. In: European Conference on Circuit Theory and Design, pp. 802–805 (2009)Google Scholar
  10. 10.
    Franz, C., Abels, P., Merz, M., Singpiel, H., Trein, J.: Real-Time Process Control by Machine Vision. In: International Congress on Applications of Lasers and Electro Optics, pp. 104–109 (2011)Google Scholar
  11. 11.
    Ishii, I., Taniguchi, T., Yamoto, K., Takaki, T.: High Frame-Rate Optical Flow System. IEEE Transactions on Circuits and Systems for Video Technology 22(1), 105–112 (2012)CrossRefGoogle Scholar
  12. 12.
    Benkrid, K., Sukhsawas, S., Crookes, D., Benkrig, A.: An FPGA-Based Image Connected Component Labeler. In: Cheung, P.Y.K., Constantinides, G.A. (eds.) FPL 2003. LNCS, vol. 2778, pp. 1012–1015. Springer, Heidelberg (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Olli Lahdenoja
    • 1
  • Tero Säntti
    • 1
  • Jonne Poikonen
    • 1
  • Mika Laiho
    • 1
  • Ari Paasio
    • 1
  1. 1.Business and Innovation Development (BID) UnitUniversity of TurkuFinland

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