Journal of Power System Engineering (동력기계공학회지)

The Korean Society for Power System Engineering (한국동력기계공학회)
권호 표지
DOI QR코드

DOI QR Code

Performance analysis of shape recognition in Senzimir mill control systems

젠지미어 압연기 제어시스템에서 형상인식에 관한 성능분석

  • 이문희 (부산대학교 대학원 기계공학부) ;
  • 신종민 (부산대학교 대학원 기계공학부) ;
  • 한성익 (부산대학교 전자전기공학부) ;
  • 김종식 (부산대학교 기계공학부)
  • Received : 2011.04.25
  • Accepted : 2011.06.02
  • Published : 2011.10.31
Download PDF
⟨ Previous Next ⟩

Abstract

In general, 20-high Sendzimir mills(ZRM) use small diameter work rolls to provide massive rolling force. Because of small diameter of work rolls, steel strip has a complex shape mixed with quarter, edge and center waves. Especially when the shape of the strip is controlled automatically, the actuator saturation occurs. These problems affect the productivity and quality of products. In this paper, the problems in automatic shape control of ZRM were analyzed. In order to evaluate the problems for the automatic shape control in ZRM, recognition performance was analyzed by comparing the measured shape and the recognized shape. The actuator positions by the shape recognition and the manual operation were compared. From the analysis results, the necessity of the improvement of recognition performance in ZRM is suggested.

Keywords

References

  1. K. N. Shohet, N. A. Townsend, "Roll Bending methods of crown control in four-high plate mills", J. Iron Steel Inst, Vol. 206, No 11 pp. 1088-1098, 1968.
  2. K. N. Shohet, N. A. Townsend, "Flatness control in plate rolling", J. Iron Steel Inst. Vol. 209, Pt. 10 pp. 769-775, 1971.
  3. J. V. Ringwood, D. H. Owens, M. J. Grimble, "Feedback design of a canonical multivariable system with application to shape control in a Sendzimir mill", Trans. ASME, J. Dyn. Syst. Meas, Control March, pp. 2721-2722, 1994.
  4. G. W. D. M. Gunawardene, "Static model for Sendzimir cold-rolling mill", Metals Technology, Vol. 8, No. 17, pp. 274-283, 1981. https://doi.org/10.1179/030716981803275910
  5. T. Kono, et al. Nippon Stailess Tech. No. 17, pp. 95-104, 1982.
  6. Satoshi Hattori, Masaaki Nakajima, Yasunori Katayama, "Fuzzy control algorithm and neural networks for flatness control of a cold rolling process", Hitachi Review, Vol. 41, No. 1, pp 31-38, 1992.
  7. 이규택, "Sendzimir 압연기의 판 형상 분석 및 Neuro-Fuzzy 형상 제어", 부산대학교 공학 박사학위 논문, 2011.
  8. J. Y. Jung, Y. T. Im, L. K. Hyung, "Development of Fuzzy Control Algorithm for Shape Control in Cold Rolling", Journal of Materials Processing Technology, Vol. 48, Issues. 1-4, pp. 187-195, 1995. https://doi.org/10.1016/0924-0136(94)01649-L

Cited by

  1. Improvement of Shape Recognition Performance of Sendzimir Mill Control Systems Using Echo State Neural Networks vol.21, pp.3, 2014, https://doi.org/10.1016/s1006-706x(14)60049-2