REVIEW

Research and Development Trend of Shape Control for Cold Rolling Strip

  • Dong-Cheng Wang ,
  • Hong-Min Liu ,
  • Jun Liu
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  • 1 National Engineering Research Center for Equipment and Technology of Cold Rolling Strip, Yanshan University, Qinhuangdao 066004, China;
    2 State Key Laboratory of Metastable Materials Science and Technology, Yanshan University, Qinhuangdao 066004, China;
    3 Anshan Iron and Steel Co. Ltd, Anshan 114002, China

Received date: 2016-11-17

  Revised date: 2017-05-04

  Online published: 2019-07-16

Abstract

Shape is an important quality index of cold rolling strip. Up to now, many problems in the shape control domain have not been solved satisfactorily, and a review on the research progress in the shape control domain can help to seek new breakthrough directions. In the past 10 years, researches and applications of shape control models, shape control means, shape detection technology, and shape control system have achieved significant progress. In the aspect of shape control models, the researches in the past improve the accuracy, speed and robustness of the models. The intelligentization of shape control models should be strengthened in the future. In the aspect of the shape control means, the researches in the past focus on the roll optimization, mill type selection, process optimization, local strip shape control, edge drop control, and so on. In the future, more attention should be paid to the coordination control of both strip shape and other quality indexes, and the refinement of control objective should be strengthened. In the aspects of shape detection technology and shape control system, some new types of shape detection meters and shape control systems are developed and have successfully industrial applications. In the future, the standardization of shape detection technology and shape control system should be promoted to solve the problem of compatibility. In general, the four expected development trends of shape control for cold rolling strip in the future are intelligentization, coordination, refinement, and standardization. The proposed research provides new breakthrough directions for improving shape quality.

Cite this article

Dong-Cheng Wang , Hong-Min Liu , Jun Liu . Research and Development Trend of Shape Control for Cold Rolling Strip[J]. Chinese Journal of Mechanical Engineering, 2017 , 30(5) : 1248 -1261 . DOI: 10.1007/s10033-017-0163-8

References

1. H M Liu, K R Ding, X D Li, et al. Theoretical computational method of shape standard curve. Chinese Journal of Mechanical Engineering, 2008, 44(8):137-142. (in Chinese)
2. D C Wang. Research on theory models of online shape pre-set control for strip tandem mill. Qinhuangdao:Yanshan University, 2009. (in Chinese)
3. F F Kong, A R He, J Shao. Research on rapid online calculation methods of roll stack deformation. Chinese Journal of Mechanical Engineering, 2012, 48(2):121-126. (in Chinese)
4. J Qin, Q Miao. The matrix iteration method for elastic deformation of multi-roll mill based on influence function method. Engineering Mechanics, 2013, 30(5):271-276. (in Chinese)
5. D C Wang, Y L Wu, H M Liu. High-efficiency calculation method for roll stack elastic deformation of four-high mill. Iron and Steel, 2015, 50(11):69-74. (in Chinese)
6. J R Zhu, X Z Lin, P Wu, et al. Development of unified simulation model of rolling for 6-Hi UCMW wide strip cold mill. Metallurgical Equipment, 2005, 8(4):7-10, 28. (in Chinese)
7. Y T Yang, Q D Zhang, W G Wang, et al. Research on an integrative simulating model for strip shape prediction during cold rolling. Steel Rolling, 2007, 24(5):13-16. (in Chinese)
8. A E Dixon, W Y D Yuen. A physical based method to predict spread and shape during flat rolling for real-time application. Steel Research International, 2008, 79(4):287-296.
9. D C Wang, Z X Zhao, H M Liu. High-efficiency software and its application for shape analysis and presetting of cold rolling strip. Iron and Steel, 2015, 50(7):54-60. (in Chinese)
10. D C Wang, H M Liu. A model coupling method for shape prediction. Journal of Iron and Steel International, 2012, 19(2):22-27.
11. X W Zhang, Y Wang. Application and development trend of intelligent recognition methods for flatness recognition. Journal of Iron and Steel Research, 2010, 22(1):1-13. (in Chinese)
12. H S Di, G M Liu, G W Jiang. A review of pattern recognition method for measured signals of shape in cold strip rolling. Henan Metallurgy, 2009, 17(4):1-6, 24. (in Chinese)
13. C Q Huang, M Zhao. Research progress of plate-profile recognition and control for cold-rolled strip. Journal of Iron and Steel Research, 2013, 25(12):2-7. (in Chinese)
14. L Hao, H S Di, D Y Gong, et al. Software development of strip flatness off-line display and pattern recognition. Journal of Northeastern University (Natural Science), 2010, 31(10):1414-1416, 1420. (in Chinese)
15. C Zhang, J P Tan. Strip flatness pattern recognition based on genetic algorithms-back propagation model. Journal of Central South University (Science and Technology), 2006, 37(2):294-299. (in Chinese)
16. J Liu, Y Q Wang, F Sun, et al. Fuzzy pattern recognition method if flatness based on particle swarm theory. Chinese Journal of Mechanical Engineering, 2008, 44(1):173-178. (in Chinese)
17. P F Niu, P F Li, G Q Li, et al. Application of GSA-SVR model in flatness pattern recognition. Iron and Steel, 2012, 47(12):45-49. (in Chinese)
18. H T He, Y Li. A new flatness pattern recognition model based on cerebellar model articulation controllers network. Journal of Iron and Steel International, 2008, 15(5):32-36.
19. C Y Jia, X Y Shan, H M Liu, et al. Fuzzy neural model for flatness pattern recognition. Journal of Iron and Steel International, 2008, 15(6):33-38.
20. X L Zhang, S Y Zhang, G Z Tan, et al. A novel method for flatness pattern recognition via least squares support vector regression. Journal of Iron and Steel International, 2012, 19(3):25-30.
21. X L Zhang, S Y Zhang, W B Zhao, et al. A novel method for flatness pattern recognition via MLSSVR. China Mechanical Engineering, 2013, 24(2):258-263. (in Chinese)
22. X L Zhang, T Xv, L Zhao, et al. Method of flatness pattern recognition based on GA-PID neural network. Journal of Shenyang University (Natural Science), 2013, 25(3):209-215. (in Chinese)
23. X L Zhang, L Zhao, J Y Zang, et al. Flatness intelligent based on T-S cloud inference neural network. ISIJ International, 2014, 54(11):2608-2617.
24. X Y Shan, H M Liu, C Y Jia. A recognition method of flatness pattern containing the cubic flatness. Iron and Steel, 2010, 45(8):56-60. (in Chinese)
25. R R Bao, J Zhang, H B Li, et al. Flatness pattern recognition of ultra-wide tandem cold rolling mill. Chinese Journal of Engineering, 2015, 37(S1):6-11. (in Chinese)
26. G H Yang, J Zhang, H B Li, et al. Extraction method of typical shape defect vector for super-wide strip steel. Journal of University of Science and Technology Beijing, 2014, 36(4):523-528. (in Chinese)
27. Y B Sun, H M Liu, Y Peng. Reduced order model for shape discrimination of strip rolling. Engineering Mechanics, 2014, 36(4):523-528. (in Chinese)
28. J T Dai, Q D Zhang, J Qin. Analysis of local bucking for thin cold-rolled strip. Engineering Mechanics, 2011, 28(10):236-242. (in Chinese)
29. J T Dai, Q D Zhang. Analysis and experiment on central bucking and post bucking of thin cold-rolled sheet. Chinese Journal of Mechanical Engineering, 2011, 47(2):44-50. (in Chinese)
30. Q D Zhang, X F Lu, X F Zhang. Analysis of bucking deformation for thin cold-rolled strip with initial warping defect. Engineering Mechanics, 2014, 31(8):243-249. (in Chinese)
31. Q D Zhang, X F Lu, X F Zhang. Deformation of warping in apparent straight strip after shearing process. Engineering Mechanics, 2014, 31(S1):217-222. (in Chinese)
32. R Nakhoul, P Montmitonnet, M Potier. Multi-scale method for modeling thin sheet bucking under residual stresses in the context of strip rolling. International Journal of Solids and Structures, 2015, 66:62-76.
33. D C Tran, N Tardif, H E Khaloui, et al. Thermal buckling of thin sheet related to cold rolling:latent flatness defects. Thin-Walled Structures, 2017, 113:129-135.
34. S Abdelkhalek, H Zahrouni, N Legrand, et al. Post-bucking modeling for strips under tension and residual stresses using asymtotic numerical method. International Journal of Mechanical Science, 2015, 104:126-137.
35. J Bai, Q D Zhang, T Z Chang, et al. Target curve setting model for automatic flatness control on stand 1 of 1420 cold tandem mill. Iron and Steel, 2007, 42(10):56-59. (in Chinese)
36. F Z Lu, J Wen, J Bai. Research of flatness target curve optimization for high strength steel of 2030mm tandem cold mill. Steel Rolling, 2009, 26(4):4-6. (in Chinese)
37. P F Wang, D H Zhang, J W Liu, et al. Research and application of flatness target curve setting model for cold rolling mill. Iron and Steel, 2010, 45(4):50-55. (in Chinese)
38. M Luo. Application of flatness curve dynamic set on the hole in strip rolling process. China Metallurgy, 2015, 25(6):49-53. (in Chinese)
39. P F Wang, Y Peng, H M Liu. Actuator efficiency adaptive flatness control model and its application in 1250 mm reversible cold strip mill. Journal of Iron and Steel International, 2013, 20(6):13-20.
40. L Ma, P F Wang, D C Wang, et al. Optimization algorithm for closed-loop control system of flatness. Journal of Iron and Steel Research, 2015, 27(7):42-45. (in Chinese)
41. H M Liu, X L Zhang, Y R Wang. Transfer matrix method of flatness control for strip mills. Journal of Materials Processing Technology, 2005, 166:237-242.
42. H M Liu, H T He, X Y Shan, et al. Flatness control based on dynamic effective matrix for cold strip mills. Chinese Journal of Mechanical Engineering, 2009, 22(2):287-296.
43. H M Liu, X Y Shan, C Y Jia. Theory-intelligent dynamic matrix model of flatness control for cold rolled strips. Journal of Iron and Steel Research International, 2013, 20(8):1-7.
44. S Abdelkhalek, P Montmitonnet, N Legrand, et al. Coupled approach for flatness prediction in clod rolling of thin strip. International Journal of Mechanical Science, 2011, 53:661-675.
45. Y K Kim, W J Kwak, T J Shin, et al. A new model for the prediction of roll force and tension profiles in flat rolling. ISIJ International, 2010, 50(11):1644-1652.
46. B Moazeni, M Salimi. Investigations on formation of shape defects in square rolling of uniform thin flat sheet product. ISIJ International, 2013, 53(2):257-264.
47. X H Liu, Z Y Jiang, G D Wang. Analysis of 3-D deformation for crowning strip rolling by rigid-plastic FEM. Advanced Technology of Plasticity, 1993:717-720.
48. X C Wang, Q Yang, J W Xv, et al. Research on the improvement effect of high tension on flatness deviation in cold strip rolling. Steel Research International, 2014, 85(11):1560-1570.
49. Y L Liu. The self-curability and explicit and implicit heritability of shape defects in cold rolling//AISTech 2015 Proceedings, Cleveland, USA, May 4-7, 2015:2878-2893.
50. S Kapil, P Eberhard, S K Dwivedy. Dynamic analysis of coldrolling process using the finite-element method. Journal of Manufacturing Science and Engineering, 2016, 138(4):041002.
51. J L Sun, Y Peng, H M Liu, et al. Vibration of moving strip with distributed stress in rolling process. Journal of Iron and Steel Research International, 2010, 17(4):24-30.
52. Y Peng, Y Zhang, J L Sun, et al. Tandem strip mill's multicoupling dynamic modeling based on the thickness control. Chinese Journal of Mechanical Engineering, 2015, 28(2):353-362.
53. D C Wang, Q L Ma, H M Liu, et al. Study off backup roll contour optimization for cold strip temper rolling mill. Iron and Steel, 2009, 44(8):56-59. (in Chinese)
54. Z H Bai, K Wang, Y J Wang, et al. Inner roll shape optimization design technology of VC mill. China Mechanical Engineering, 2013, 24(22):3096-3099. (in Chinese)
55. Z H Bai, L P Yang, X D Li, et al. Roll shape setting technology of hot galvanizing and planishing mill. Journal of Iron and Steel Research International, 2007, 14(1):33-36.
56. H H Xie, A R He, J Liu, et al. Research of the roll contour optimization on 1720mm cold rolling skin pass mill. China Metallurgy, 2009, 44(8):56-59. (in Chinese)
57. G H Yang, J G Cao, J Zhang, et al. Comprehensive control for strip edge drop & crown and flatness on tandem cold rolling mill. Metallurgical Equipment, 2008, 6:1-4. (in Chinese)
58. G H Yang, J Zhang, J G Cao, et al. Roll configuration for edge drop control of wide strip on 4-Hi tandem cold rolling mills. Journal of Tianjin University, 2012, 45(12):1051-1056. (in Chinese)
59. Y Peng, H M Liu, D C Wang. Simulation of type selection for 6-high cold tandem mill based on shape control ability. Journal of Central South University of Technology, 2007, 14(2):278-284.
60. L J Xv. Flatness control in cold strip rolling and mill type selection. Beijing:Metallurgical Industry Press, 2007. (in Chinese)
61. X Q Liu. Shape simulation and mill type evaluation software development of cold rolling strip based on coupling model method. Qinhuangdao:Yanshan University, 2012. (in Chinese)
62. L Song, M G Shen, X B Chen, et al. Optimum control for technology coolant of cold rolling mill. Journal of Liaoning Technical University (Natural Science), 2014, 33(5):647-650. (in Chinese)
63. G Y Hu, Y Cui. Optimizing the shape control process of thin strip with bright roll in cold tandem mill. Journal of Liaoning Institute of Science and Technology, 2010, 12(2):11-12. (in Chinese)
64. S Q Li, S Q Xing, Y L Ma, et al. Study on leveling process optimization of cold rolled strip. Steel Rolling, 2011, 28(4):16-19. (in Chinese)
65. S M Wu. Model of temper rolling for chroming base plate by double cold reduction mill. Steel Rolling, 2008, 25(4):28-29,42. (in Chinese)
66. H C Chen, S M Wu, X J Li. Combination control of shape and surface quality for double UCM temper mill. China Metallurgy, 2009, 19(6):23-25. (in Chinese)
67. Z H Bai, H X Si, Q T Zhou, et al. Comprehensive optimized technology of processing lubrication system in double cold reduction. Iron and Steel, 2011, 46(6):60-62, 73. (in Chinese)
68. Z H Bai, X D Li, J C Lian, et al. Influence of local shape wave on ribbing of cold-rolled coil. Chinese Journal of Mechanical Engineering, 2006, 42(9):229-232. (in Chinese)
69. X D Li, H M Liu, J H Li. Origin of side convex defect for coldrolled strip coil. Journal of Iron and Steel Research, 2008, 20(7):29-33. (in Chinese)
70. X M Zhu, G H Feng, H L Zhang. Defect analysis on ridge buckles of cold-rolled pure titanium strip. Hot Working Technology, 2014, 43(19):227-230. (in Chinese)
71. B Yu, X L Yue, G F She, et al. Research ob roll contour optimization in solving defect of local convexity of steel coil. China Mechanical Engineering, 2008, 19(8):969-971. (in Chinese)
72. J H Li, J Li, W P Li. Elimination of ridge defect of cold rolled strip coil. Iron and Steel, 2008, 43(9):49-52. (in Chinese)
73. Z Y Dou, B Huang, S Q Feng. Analysis and countermeasures of bulging defect at the edge of cold-rolled products. Iron Steel Vanadium Titanium, 2012, 33(6):91-94. (in Chinese)
74. Y L Lu, G Chen, Z Y Zhu, et al. Causes and control strategy for ridge buckle of silicon steel in continuous annealing line. Shanghai Metals, 2015, 37(2):54-56, 62. (in Chinese)
75. X M Zhou, Q D Zhang, C S Wang, et al. Automative edge drop control system of UCMW cold mill and its optimization. Iron and Steel, 2007, 42(9):56-59. (in Chinese)
76. Z Y Li, J R Zhu, X W Ye, et al. Development of a new edge drop control system for the PL-TCM. Baosteel Technology, 2006, 5:40-42. (in Chinese)
77. Q Hu, X C Wang, Q Yang. Design and application of automatic edge drop control system for 6-high tandem cold rolling mill. Metallurgical Industry Automation, 2016, 40(1):34-39, 44. (in Chinese)
78. K J Wang, J H Xv, S Q Li. Automatic edge drop control system of Baosteel//Proceedings of the National Production of Rolling Technology, Ningbo, China, August 14-15, 2012:1016-1019. (in Chinese)
79. Q D Zhang, X F Zhang, J Wen. Theory and technology of transverse thickness deviation control for DI tinplate during tandem cold rolling. Journal of Mechanical Engineering, 2013, 49(24):30-38. (in Chinese)
80. W Q Sun, Q Yang, J Shao, et al. Edge drop control technique of silicon steel for UCM tandem cold rolling mills. Journal of University of Science and Technology Beijing, 2010, 32(10):1340-1345. (in Chinese)
81. A R He, J Shao, W Q Sun, et al. Transverse thickness deviation control of non-oriented silicon steel during cold rolling. Journal of Mechanical Engineering, 2011, 47(10):25-30. (in Chinese)
82. R Li, Q D Zhang, X F Zhang, et al. Control method for steel strip roughness in two-stand temper mill rolling. Chinese Journal of Mechanical Engineering, 2015, 28(3):573-579.
83. L P Xv, L You, D H Wang, et al. Application of ABB shape meter in cold-strip steel production. China Metallurgy, 2014, 24(1):23-26. (in Chinese)
84. X G Liang, Z J Jiao, G D Wang, et al. The technology of flatness measurement in cold rolling. Metallurgical Equipment, 2006, 6:36-39, 77. (in Chinese)
85. L J Chen, B Han, W Tan, et al. Technology status and trend of shape detecting and shape controlling of rolled strip. Steel Rolling, 2012, 29(4):38-42. (in Chinese)
86. D Wen, Z Li. Application of non-contact shape meter in CAL of cold rolling line. Steel Rolling, 2015, 32(5):62-65. (in Chinese)
87. G H Yang, J Zhang, J G Cao, et al. Relationship between strip amplitude and shape for shapemeter based on airflow excitation and eddy current. Transactions of Beijing Institute of Technology, 2015, 35(7):671-676. (in Chinese)
88. H M Liu, B Q Yu, L P Yang, et al. Development of cold strip shape meter with entire roller inlayed block intelligence and its industrial application. Iron and Steel, 2011, 46(12):86-89. (in Chinese)
89. B Q Yu, L P Yang, J L Sun. Research status of shape detecting roller of cold rolled strip. Steel Rolling, 2011, 28(2):44-46. (in Chinese)
90. B Q Yu, L P Yang, H M Liu, et al. Development and industry application of contact shape meter with new structure. Chinese Journal of Scientific Instrument, 2010, 31(4):904-911. (in Chinese)
91. B Q Yu, L P Yang, Z M Li, et al. Research on embedded DSP shape signal processing system for cold rolling strip. Measurement and Control Technology, 2011, 30(8):23-26. (in Chinese)
92. J C Lian, H M Liu. Thickness and shape control for rolling strip. Beijing:Weapons Industry Press, 1996. (in Chinese)
93. V B Ginzburg. High-quantity steel rolling:theory and practice. New York:Marcel Dekker, Inc., 1993.
94. B Q Yu. Research on entire roller intelligence cold strip shape meter and its industrial application. Qinhuangdao:Yanshan University, 2010. (in Chinese)
95. H M Liu, B Q Yu, L P Yang, et al. Entire roller embedded shapemeter:China, 201310209604.2. 2015-09-16. (in Chinese)
96. H M Wu, H M Liu, B Q Yu, et al. Determination of interference fit value on entire embedded shapemeter. Journal of Central South University, 2014, 21(12):4503-4508.
97. H M Wu. Study of thermal deformation and optimization design of entire roller embedded shapemeter roll. Qinhuangdao:Yanshan University, 2015. (in Chinese)
98. H M Wu, H M Liu, B Q Yu, et al. Transient temperature field and stress field analysis of entire roller embedded shapemeter roll. Iron and Steel, 2014, 49(5):47-51. (in Chinese)
99. H M Liu, B Q Yu, L P Yang, et al. A type of seamless and embedded signal processor used for shapemeter:China, CN105005287A. 2015-10-28. (in Chinese)
100. L He, J Wang, F Zhang. Research and application of discrete tracking differentiator in shape flatness recognition. Journal of Iron and Steel Research, 2013, 25(2):58-62. (in Chinese)
101. X Y Shan. Research on matrix model of shape control for cold strip mills. Qinhuangdao:Yanshan University, 2011. (in Chinese)
102. R M Li, L P Yang, B Q Yu, et al. Effect of shape detecting roll deflection on original waveform signal of cold rolling strip. Iron and Steel, 2013, 48(5):41-45. (in Chinese)
103. R M Li, L P Yang, B Q Yu, et al. Effect of detection roll installation precision on online shape signal of cold rolling strip. Iron and Steel, 2013, 48(7):40-40, 48. (in Chinese)
104. Z X Zhao, D C Wang, P F Wang, et al. Research and application of position error compensation model for shape meter. Iron and Steel, 2015, 50(3):49-53. (in Chinese)
105. L P Yang, B Q Yu, R M Li, et al. Compensation model of abnormal signal and shape detection error of cold rolling strip. Chinese Journal of Mechanical Engineering, 2014, 50(6):30-38. (in Chinese)
106. P F Wang, D H Zhang, J J Liu, et al. Research and application of the flatness measurement calculation model on cold rolling mill. Chinese Journal of Mechanical Engineering, 2011, 47(4):58-65. (in Chinese)
107. X L He, F Wang, Z C Sun. Automatic strip shape control system of 1420mm TCM at Meigang. Meishan Keji, 2010, 5:59. (in Chinese)
108. W Q Sun, A R He, J Shao, et al. Research and application of automatic control system for high precision cold rolling. Metallurgical Industry Automation, 2015, 39(3):44-49. (in Chinese)
109. Z F Li, H Y Li, Z H Cao, et al. Development and application of flatness control system for temper mill. Angang Technology, 2016, 1:25-28, 62. (in Chinese)
110. D Y Gong, J Z Xv, J Zhang, et al. Shape Preset mathematic model establishment of UCM reversing mill. Steel Rolling, 2011, 28(6):1-3. (in Chinese)
111. X G Liang. Preset model of bending force for six-high tandem cold rolling mill. Iron and Steel, 2014, 49(10):40-43, 50. (in Chinese)
112. Z H Bai, X P Kang, S M Wu. Technology of online setting shape parameter in double frame UCM tempers. Iron and Steel, 2009, 44(5):39-43. (in Chinese)
113. M Jelali. Performance assessment of control systems in rolling mills-application to strip thickness and flatness control. Journal of Process Control, 2007, 17:805-816.
114. A Benporad, D Bernardini, F A Cuzzola, et al. Optimizationbased automatic flatness control in cold tandem rolling. Journal of Process Control, 2010, 20:396-407.
115. G Pin, V Francesconi, F A Cuzzola, et al. Adaptive task-space control of strip flatness in multiroll mill stands. IFAC Proceedings Volumes, 2011, 44(1):11720-11725.
116. G Pin, V Francesconi, F A Cuzzola, et al. Adaptive task-space metal strip-flatness control in cold multi-roll mill stands. Journal of Process Control, 2013, 23:108-119.
117. Y Zhang, Q Yang, X C Wang. Control strategies of asymmetric strip shape in six-high cold rolling mill. Journal of Iron and Steel International, 2011, 18(9):27-32.
118. L Song, M G Shen, L P Yang, et al. Shape control dimensionality reduction efficiency inherited regulation method of cold rolling wide strip. Iron and Steel, 2016, 51(1):70-75. (in Chinese)
119. X Y Shan, C Y Jia, H M Liu. Neural fuzzy PID model of tilting roll and bending roll flatness control for strip mill. Journal of Mechanical Engineering, 2009, 45(9):254-259. (in Chinese)
120. Y N Xia, S Zhao. China Manufacturing 2025. Beijing:China Machine Press, 2016. (in Chinese)
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