Seam tracking monitoring based on adaptive Kalman filter embedded elman neural network during high-power fiber laser welding

IEEE Transactions on Industrial Electronics

Volumn 59, Issue 11, 2012, Pages 4315-4325

  Gao, Xiangdong ^a   You, Deyong ^a   Katayama, Seiji ^b  

^a GUANGDONG UNIVERSITY OF TECHNOLOGY   (China)

^b OSAKA UNIVERSITY   (Japan)

Author keywords

Elman neural network; fiber laser welding; Sage Husa adaptive Kalman filter; seam tracking monitoring

Indexed keywords

ADAPTIVE KALMAN FILTER; CENTROID ALGORITHM; ELMAN NEURAL NETWORK; ERROR ESTIMATORS; FILTERING ERROR; HIGH-POWER FIBER LASER WELDING; IMAGE DIFFERENCE; INFRARED IMAGES; MEASUREMENT EQUATIONS; MOLTEN POOL; POSITION VARIABLES; SAGE-HUSA; SEAM TRACKING; STATISTICAL CHARACTERISTICS; VISUAL SENSOR; WELD SEAM; WELDING PROCESS;

FIBER LASERS; INFRARED IMAGING; KALMAN FILTERS; NEURAL NETWORKS; WELDS;

LASER BEAM WELDING;

EID: 84862987041     PISSN: 02780046     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIE.2012.2193854     Document Type: Article

References (33)

1. S. Katayama and Y. Kawahito, "Laser direct joining of metal and plastic," Scr. Mater., vol. 59, no. 12, pp. 1247-1250, Dec. 2008.
2. M. Jäger and F. A. Hamprecht, "Principal component imagery for the quality monitoring of dynamic laser welding processes," IEEE Trans. Ind. Electron., vol. 56, no. 4, pp. 1307-1313, Apr. 2007.
3. B. Fabrice, C. Adolfo, M. L. H. Jose, C. Olivier, A. Pascal, D. Thierry, H. Mats, N. Per, J. Peter, D. C. J. Julian, and P. H. Duncan, "Optical techniques for real-time penetration monitoring for laser welding," Appl. Opt., vol. 44, no. 19, pp. 3869-3876, Jul. 2005.
4. F. Bonaccorso, L. Cantelli, and G. Muscato, "An arc welding robot control for a shaped metal deposition plant: Modular software interface and sensors," IEEE Trans. Ind. Electron., vol. 58, no. 8, pp. 3126-3132, Aug. 2011.
5. K. Suwanratchatamanee, M. Matsumoto, and S. Hashimoto, "Robotic tactile sensor system and applications," IEEE Trans. Ind. Electron., vol. 57, no. 3, pp. 1074-1087, Mar. 2010.
6. J. Steele, C. Mnich, C. Debrunner, T. Vincent, and S. Liu, "Development of closed-loop control of robotic welding process," Int. J. Ind. Robot, vol. 32, no. 4, pp. 350-355, 2005.
7. L. Quintino, A. Costa, R. Miranda, D. Yapp, and C. J. Kong, "Welding with high power fiber lasers-A preliminary study," Mater. Des., vol. 28, no. 4, pp. 1231-1237, 2007.
8. A. H. Amin and P. Robert, "An autonomous low-cost infrared system for the on-line monitoring of manufacturing processes using novelty detection," Int. J. Adv. Manuf. Technol., vol. 22, no. 3/4, pp. 249-258, Sep. 2003.
9. S. Nagarajan, P. Banerjee, W. H. Chen, and B. A. Chin, "Control of the welding process using infrared sensors," IEEE Trans. Robot. Autom., vol. 8, no. 1, pp. 86-93., Feb. 1992.
10. R. S. Huang, L. M. Liu, and G. Song, "Infrared temperature measurement and interference analysis of magnesium alloys in hybrid laser-TIG welding process," Mater. Sci. Eng. A, vol. 447, no. 1/2, pp. 239-243, Feb. 2007.
11. M. Charkhgard and M. Farrokhi, "State-of-charge estimation for lithiumion batteries using neural networks and EKF," IEEE Trans. Ind. Electron., vol. 57, no. 12, pp. 4178-4187, Dec. 2010.
12. S. S. Saab and Z. Nakad, "A standalone RFID indoor positioning system using passive tags," IEEE Trans. Ind. Electron., vol. 58, no. 5, pp. 1961-1970, May 2011.
13. C. Mitsantisuk, K. Ohishi, and S. Katsura, "Control of interaction force of twin direct-drive motor system using variable wire rope tension with multisensor integration," IEEE Trans. Ind. Electron., vol. 59, no. 1, pp. 498-510, Jan. 2012.
14. E. J. Fuentes, C. A. Silva, and J. I. Yuz, "Predictive speed control of a twomass system driven by a permanent magnet synchronous motor," IEEE Trans. Ind. Electron., vol. 59, no. 7, pp. 2840-2848, Jul. 2012.
15. F. Zhang, G. Liu, L. Fang, and H. Wang, "Estimation of battery state of charge with H8 observer: Applied to a robot for inspecting power transmission lines," IEEE Trans. Ind. Electron., vol. 59, no. 2, pp. 1086-1095, Feb. 2012.
16. T. Schuhmann, W. Hofmann, and R. Werner, "Improving operational performance of active magnetic bearings using Kalman filter and state feedback control," IEEE Trans. Ind. Electron., vol. 59, no. 2, pp. 821-829, Feb. 2012.
17. X. D. Gao and S. J. Na, "Detection of weld position and seam tracking based on Kalman filtering of weld pool images," J. Manuf. Syst., vol. 24, no. 1, pp. 1-12, 2005.
18. M. Jäger, S. Humbert, and F. A. Hamprecht, "Sputter tracking for the automatic monitoring of industrial laser-welding processes," IEEE Trans. Ind. Electron., vol. 55, no. 5, pp. 2177-2184, May 2008.
19. K. Szabat and T. Orlowska-Kowalska, "Performance improvement of industrial drives with mechanical elasticity using nonlinear adaptive Kalman filter," IEEE Trans. Ind. Electron., vol. 55, no. 3, pp. 1075-1084, Mar. 2008.
20. H. Dai, X. Wei, and Z. Sun, "State and parameter estimation of a HEV Li-ion battery pack using adaptive Kalman filter with a new SOCOCV concept," in Proc. Int. Conf. Meas. Technol. Mechatron. Autom., Shanghai, China, 2009, pp. 375-380.
21. Z. Lin, H. Chen, X. Wang, and Z. Su, "Research on satellite attitude determination with adaptive filter," in Proc. ICIA, Jun. 2010, pp. 1045-1048.
22. S.W. Perry and L. Guan, "A recurrent neural network for detecting objects in sequences of sector-scan sonar images," IEEE J. Ocean. Eng., vol. 29, no. 3, pp. 857-871, Jul. 2004.
23. J. Choi, M. Bouchard, and T. H. Yeap, "Decision feedback recurrent neural equalization with fast convergence rate," IEEE Trans. Neural Netw., vol. 16, no. 3, pp. 699-708, May 2005.
24. A. G. Parlos, S. K. Menon, and A. F. Atiya, "An algorithmic approach to adaptive state filtering using recurrent neural networks," IEEE Trans. Neural Netw., vol. 12, no. 6, pp. 1411-1432, Nov. 2001.
25. J. Choi, A. C. Lima, and S. Haykin, "Kalman filter-trained recurrent neural equalizers for time-varying channels," IEEE Trans. Commun., vol. 53, no. 3, pp. 472-480, Mar. 2005.
26. R. E. Kalman, "New result in linear filtering and prediction theory," Trans. ASME, J. Basic Eng., Ser. D, vol. 83, no. 1, pp. 95-108, Mar. 1961.
27. A. P. Sage and G. W. Husa, "Adaptive filtering with unknown prior statistics," in Proc. Joint Autom. Control Conf., 1969, pp. 760-769.
28. J. L. Elman, "Finding structure in time," Cognit. Sci., vol. 14, pp. 179-211, 1990.
29. F. J. Lin, Y. C. Hung, and S. Y. Chen, "FPGA-based computed force control system using Elman neural network for linear ultrasonic motor," IEEE Trans. Ind. Electron., vol. 56, no. 4, pp. 1238-1253, Apr. 2009.
30. T. Sawaragi and T. Kudoh, "Self-reflective segmentation of human bodily motions using recurrent neural networks," IEEE Trans. Ind. Electron., vol. 50, no. 5, pp. 903-911, Oct. 2003.
31. C. H. Lu and C. C. Tsai, "Adaptive predictive control with recurrent neural network for industrial processes: An application to temperature control of a variable-frequency oil-cooling machine," IEEE Trans. Ind. Electron., vol. 55, no. 3, pp. 1366-1375, Mar. 2008.
32. C.-H. Lu, "Design and application of stable predictive controller using recurrent wavelet neural networks," IEEE Trans. Ind. Electron., vol. 56, no. 9, pp. 3733-3742, Sep. 2009.
33. X. H. Shi, Y. C. Liang, H. P. Lee, W. Z. Lin, X. Xu, and S. P. Lim, "Improved Elman networks and applications for controlling ultrasonic motors," Appl. Artif. Intell., vol. 18, no. 7, pp. 603-629, 2004.