Resistance spot welding process identification using an extended knn method

IEEE International Symposium on Industrial Electronics

Volumn I, Issue , 2005, Pages 7-12

  Junno, H ^a   Laurinen, P ^a   Haapalainen, E ^a   Tuovinen, L ^a   Roning J ^a  

^a UNIVERSITY OF OULU   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

DATA ACQUISITION; ELECTRIC INDUSTRY; MATHEMATICAL TECHNIQUES; WELDING MACHINES;

K-NEAREST NEIGHBOURS (KNN) METHOD; RESISTANCE SPOT WELDING; WELDING SPOTS;

SPOT WELDING;

EID: 33748362646     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISIE.2005.1528880     Document Type: Conference Paper

References (17)

1. H. Junno, P. Laurinen, E. Haapalainen, L. Tuovinen, J. Röning, D. Zettel, D. Sampaio, N. Link, and M. Peschl, "Resistance spot welding process identification and initialization based on self-organising maps," Proceedings of 1st International Conference on Informatics in Control, Automation and Robotics, vol 1, pp. 296-299, 2004.
2. E. Haapalainen, P. Laurinen, H. Junno, L. Tuovinen, and Juha Röning, "Methods for classifying spot welding processes: A comparative study of performance," The 18th International Conference on Industrial & Engineering Applications of Artificial Intelligence & Expert Systems, 22-25.6, 2005, in press.
3. A. Aravinthan, K. Sivayoganathan, D. Al-Dabass, and V. Balendran, "A neural network system for spot weld strength prediction," UKSIM2001, Conf. Proc. of the UK Simulation Society, pp. 156-160, 2001.
4. Y. Cho, and S. Rhee, "Primary circuit dynamic resistance monitoring and its application on quality estimation during resistance spot welding," Welding Researcher, pp. 104-111, 2002.
5. H. Junno, P. Laurinen, L. Tuovinen, and J. Röning, "Studying the quality of resistance spot welding joints using self-organising maps," Proceedings of Fourth International ICSC Symposium on Engineering of Intelligent Systems, 2004.
6. P. Laurinen, H. Junno, L. Tuovinen, and J. Röning, "Studying the quality of resistance spot welding joints using bayesian networks," Proceedings of Artificial Intelligence and Applications, pp. 705-711, 2004.
7. D. Zettel, D..Sampaio, N. Link, A. Braun, M. Peschl, and H. Junno, "A self organising map (SOM) sensor for the detection, visualisation and analysis of process drifts," Poster Proceedings of the 27th Annual German Conference on Artificial Intelligence, pp. 175-188, 2004.
8. D. Mintz, and J. T. Wen, "Process monitoring and control for robotic resistive welding," Proceedings of the 4th IEEE Conference on Control Applications, pp. 1126 -1127, 1995.
9. R. Kulessky, G. Nudelman, and M. Zimin, "Digital electropneumatic control system of power boiler processes. Process identification and motion optimization," Nineteenth Convention of Electrical and Electronics Engineers in Israel, pp. 507-510, 1996.
10. D. Haesloop, and B.R. Holt, "Neural networks for process identification," IJCNN International Joint Conference on Neural Networks, Pages:429 - 434 vol.3, 1990.
11. C.H. Reinsch, "Smoothing by spline functions," Numerische Matematik. Vol. 10, pp. 177-83, 1967.
12. C.H. Reinsch, "Smoothing by spline functions, II, Numerische Matematik." Vol 16, pp.451-454, 1971.
13. T. Mitchell, Machine learning, The McGraw-Hill Companies, INC., 1997.
14. S-H. Cha, and s. Srihari, "Nearest neighbor search using additive binary tree," IEEE Conference on Computer Vision and Pattern Recognition, pp. 738-745, 2000.
15. Fachochschule Karlsruhe, http://www.fh-karlsruhe.de, the homepage of the university, referenced 29.11.2004.
16. Stanzbiegetechnik, http://www.stanzbiegetechnik.at, the homepage of the company, referenced 29.11.2004.
17. Harms+Wende, http://www.harms-wende.de, homepage of the company, referenced: 29.11.2004.