Application of the extended knn method to resistance spot welding process identification and the benefits of process information

IEEE Transactions on Industrial Electronics

Volumn 54, Issue 5, 2007, Pages 2823-2830

  Koskimäki, Heli Junno ^a   Laurinen, Perttu ^a   Haapalainen, Eija ^a   Tuovinen, Lauri ^a   Röning, Juha ^a  

^a UNIVERSITY OF OULU   (Finland)

Author keywords

Initialization parameters; Past case utilization; Process drift; Quality control; Similarity

Indexed keywords

ELECTRICAL INDUSTRIES; HIGH QUALITIES; INITIALIZATION PARAMETERS; K-NEAREST NEIGHBORS; NEW PROCESS; PAST CASE UTILIZATION; PROCESS DRIFT; PROCESS INFORMATIONS; PROCESS PARAMETERS; RESISTANCE SPOT WELDING; SIMILARITY; SIMILARITY MEASURES; WELDING INDUSTRIES; WELDING PROCESS;

QUALITY ASSURANCE; QUALITY FUNCTION DEPLOYMENT; RESISTANCE WELDING; SPOT WELDING; TOTAL QUALITY MANAGEMENT; WELDING;

PROCESS CONTROL;

EID: 44349111963     PISSN: 02780046     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIE.2007.901353     Document Type: Article

References (19)

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," in Proc 1st Int. Conf. Informatics Control, Autom. and Robot, 2004, vol. 1, pp. 296-299.
2. E. Haapalainen, P. Laurinen, H. Junno, L. Tuovinen, and J. Röning, "Methods for classifying spot welding processes: A comparative study of performance," in Proc. Innov. Appl. Artif. Intell., 2005, pp. 412-421.
3. H. Junno, P. Laurinen, E. Haapalainen, L. Tuovinen, and J. Röning, "Resistance spot welding process identification using an extended knn method," in Proc. IEEE Int. Symp. Ind. Electron., 2005, vol. 1, pp. 7-12.
4. L. Tuovinen, P. Laurinen, H. Koskimäki, E. Haapalainen, and J. Röning, "Building a database to support intelligent computational quality assurance of resistance spot welding joints," in Proc. IEEE Int. Symp. Ind. Electron., 2007, pp. 1980-1985.
5. A. Aravinthan, K. Sivayoganathan, D. Al-Dabass, and V. Balendran, "A neural network system for spot weld strength prediction," in Proc. UK Simul Soc., 2001, pp. 156-160.
6. Y. Cho and S. Rhee, "Primary circuit dynamic resistance monitoring and its application on quality estimation during resistance spot welding," Weld. J., vol. 81, no. 6, pp. 104S-111S, 2002.
7. Y. Cho and S. Rhee, "Quality estimation of resistance spot welding by using pattern recognition with neural networks," IEEE Trans. Instrum. Meas., vol. 53, no. 2, pp. 330-334, Apr. 2004.
8. F. Garza and M. Das, "On real time monitoring and control of resistance spot welds using dynamic resistance signatures," in Proc. 44th IEEE Midwest Symp. Circuits and Syst., 2001, vol. 1, pp. 41-44.
9. Z. Xiaoyun, Z. Yansong, and C. Guanlong, "Weld quality inspection based on on-line measured indentation from servo encoder in resistance spot welding," in Proc. IEEE Instrum. and Meas. Technol. Conf., 2006, pp. 1353-1356.
10. L. Gong, C.-L. Liu, and X. F. Zha, "Model-based real-time dynamic power factor measurement in ac resistance spot welding with an embedded ANN," IEEE Trans. Ind. Electron., vol. 54, no. 3, pp. 1442-1448, Jun. 2007.
11. N. Ivezic, J. D. Alien, and T. Zacharia, "Neural network-based resistance spot welding control and quality prediction," in Proc. 2nd Int. Conf. Intell. Process. and Manuf. Mater., 1999, pp. 989-994.
12. L. Brown and J. Schwaber, "Identifying operating conditions from preweld information for resistance spot welding," in Proc. Amer. Control Conf., 2000, pp. 1535-1539.
13. H. Junno, P. Laurinen, L. Tuovinen, and J. Röning, "Studying the quality of resistance spot welding joints using self-organising maps," in Proc. 4th Int. ICSC Symp. Eng. Intell. Syst., 2004.
14. P. Laurinen, H. Junno, L. Tuovinen, and J. Röning, "Studying the quality of resistance spot welding joints using Bayesian networks," in Proc. Artif. Intell. and Appl., 2004, pp. 705-711.
15. C. H. Reinsch, "Smoothing by spline functions," Numer. Math., vol. 10, no. 3, pp. 177-183, Oct. 1967.
16. C. H. Reinsch, "Smoothing by spline functions, II," Numer. Math., vol. 16, no. 5, pp. 451-454, Feb. 1971.
17. T. Mitchell, Machine Learning. New York: McGraw-Hill, 1997.
18. S. Guttormsson, R. J. Marks, II, M. El-Sharkawi, and I. Kerszenbaum, "Elliptical novelty grouping for on-line short-turn detection of excited running rotors," IEEE Trans. Energy Comers., vol. 14, no. 1, pp. 16-22, Mar. 1999.
19. 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," in Proc. Poster 27th Annu. German Conf. Artif Intell., 2004, pp. 175-188.