Shape is a key characteristic to determine the quality of outgoing flat-rolled products in the steel industry. It is greatly influenced by flatness, a feature to describe how the surface of a rolled product approaches a plane. Flatness is of the utmost importance in steelmaking, since it is used by most downstream processes and customers for the acceptance or rejection of rolled products. Flatness sensors compute flatness measurements based on comparing the length of several longitudinal fibers of the surface of the product under inspection. Two main different approaches are commonly used. On the one hand, most mechanical sensors measure the tensile stress across the width of the rolled product, while manufacturing and estimating the fiber lengths from this stress. On the other hand, optical sensors measure the length of the fibers by means of light patterns projected onto the product surface. In this paper, we review the techniques and the main sensors used in the steelmaking industry to measure and quantify flatness defects in steel plates, sheets and strips. Most of these techniques and sensors can be used in other industries involving rolling mills or continuous production lines, such as aluminum, copper and paper, to name a few. Encompassed in the special issue, State-of-the-Art Sensors Technology in Spain 2013, this paper also reviews the most important flatness sensors designed and developed for the steelmaking industry in Spain.
References
[1]
Müller, U.; Jelali, M.; Wolff, A.; Richardson, A.D.; Nilsson, A.; Bogdanoff, A. Reduction of Shape Defects and Yield Losses by Advanced online Adaptation of Control Systems and New Operation Strategies in Heavy Plate Rolling Mills. Technical Report No. 25089; European Commission, European Research Area: Brussels, Belgium, 2012.
[2]
Jelali, M.; Pinno, C.; Bathelt, J.; Georgi, H.; Sidestam, P.; Legrand, N.; López, A. Minimised Yield Losses by Innovative Integrated Edge-Drop, Width and Shape Control Based on Soft-Sensor Technology and New Actuators in Cold Rolling Mills. Technical Report No. 25334; European Commission: Brussels, Belgium, 2013.
[3]
Ginzburg, V.B.; Ballas, R. Geometry of Flat Rolled Products (Rolling Mill Technology Series); United Engineering: Pittsburgh, PA, USA, 1990; Volume 2.
[4]
Abdelkhalek, S.; Montmitonnet, P.; Potier-Ferry, M.; Zahrouni, H.; Legrand, N.; Buessler, P. Strip flatness modeling including buckling phenomena during thin strip cold rolling. Ironmak. Steelmak. 2010, 37, 290–297.
[5]
Weisz-Patrault, D.; Ehrlacher, A.; Legrand, N. A new sensor for the evaluation of contact stress by inverse analysis during steel strip rolling. J. Mater. Process. Technol. 2011, 211, 1500–1509.
[6]
Andersen, C.B.; Ravn, B.G.; Wanheim, T. Development of a commercial transducer for measuring pressure and friction on a model die surface. J. Mater. Process. Technol. 2001, 115, 205–211.
[7]
Legrand, N.; Lavalard, T.; Martins, A. New concept of friction sensor for strip rolling: Theoretical analysis. Wear 2012.
[8]
Nappez, C.; Boulot, S.; McDermott, R.C. Control of strip flatness in cold rolling: A global approach. Iron Steel Eng. 1997, 74, 42–45.
[9]
Usamentiaga, R.; Garc?a, D.F.; González, D.; Molleda, J. Compensation for Uneven Temperature in Flatness Control Systems for Steel Strips. Proceedings of the Industry Applications Conference, Conference Record of the 2006 IEEE, Tampa, FL, USA, 8–12 October 2006; Volume 1, pp. 521–527.
[10]
Malik, A.S.; Grandhi, R.V.. Chapter 30 Recent developments in strip-profile calculation. In Flat-Rolled Steel Processes. Advanced Technologies; CRC Press: New York, NY, USA, 2009; pp. 329–339.
[11]
Delivery Requirements for Surface Condition of Hot-Rolled Steel Plates, Wide Flats and Sections–General Requirements. EN Standard 10163:2005; BSI: London, UK, 2005.
[12]
Steels for Simple Presure Vessels–Technical Delivery Requirements for Plates, Strips and Bars. EN Standard 10207:2005; BSI: London, UK, 2005.
[13]
Sansoni, G.; Trebeschi, M.; Docchio, F. State-of-the-art and applications of 3D imaging sensors in industry, cultural heritage, medicine, and criminal investigation. Sensors 2009, 9, 568–601.
[14]
Magnetic Materials. Methods of Determination of the Geometrical Characteristics of Electrical Steel Sheet and Strip. EN Standard 10251:1997; BSI: London, UK, 1997.
[15]
Specification for Tolerances on Dimensions, Shape and Mass for Hot Rolled Steel Plates 3 mm Thick or above. EN Standard 10029:1991; BSI: London, UK, 1991.
[16]
Richelsen, A.B. Elastic-plastic analysis of the stress and strain distributions in asymmetric rolling. Int. J. Mech. Sci. 1997, 39, 1199–1211.
[17]
Peregrina, S.; Redondo, J.G.; Quiroga, P.F.; González, D.; Garc?a, D.F. Hot strip flatness optimisation by means of edge masking in the ROT. Revue Metall. 2006, 103, 381–387.
[18]
Association of Iron and Steel Engineers. Hot Strip Mill Profile and Flatness Study, Phase I; AISE: Pittsburgh, PA, USA, 1986.
[19]
Molleda, J.; Usamentiaga, R.; Garc?a, D.F.; Bulnes, F.G. Real-time flatness inspection of rolled products based on optical laser triangulation and three-dimensional surface reconstruction. J. Electron. Imaging 2010, 19, 031206.
[20]
Mücke, G.; Pütz, P.D.; Gorgels, F.. Chapter 27 Methods of Describing, Assessing, and Influencing Shape Deviations in Strips. In Flat-Rolled Steel Processes. Advanced Technologies; CRC Press: New York, NY, USA, 2009; pp. 287–298.
[21]
Liu, J.; Zhang, D.; Wang, P. Research in shape meter roll deflection compensation model. Adv. Mater. Res. 2011, 146–147, 793–797.
[22]
Greenberger, J.I. Combination Strip Contacting Device for Use in Rolling Mill. U.S. Patent 4004459, 27 January 1977.
[23]
Mühlberg, W. Measurement of Longitudinal Stresses in Moving Metal Bands and Devices Therefor. U.S. Patent 3557614, 26 January 1971.
[24]
Berger, K.B.; Müke, H.G.; Thies, K.H.; Neschütz, R.E. Apparatus for Measuring Stress Ddistribution Across the Width of Flexible Strip. U.S. Patent 4366720, 4 January 1983.
[25]
Dahlberg, C.; Jonsson, L. Seamless Stressometer Roll Eliminating the Strip Marking and Flatness Measurement Dilemma. In Achieving Profile and Flatness in Flat Products; The Institute of Materials, Minerals and Mining: London, UK, 2006; pp. 37–40.
[26]
Hongmin, L.; Bingqiang, Y.; Zhongxing, H.; You, H.; Yan, P. Multi-Roll-Piece Inner Bore Piezomagnetic Sensor Type Shape Meter. Chinese Patent 200610048380, 21 March 2007.
[27]
Yang, L.P.; Yu, B.Q.; Ding, D.; Liu, H.M. Industrial shape detecting system of cold rolling strip. J. Central South Univ. Technol. 2012, 19, 994–1001.
[28]
Sivilotti, O.G. Strip Flatness Sensor. U.S. Patent 3481194, Swedish Patent 321365, 2 December 1969.
[29]
Dahle, O. Method and Device for Indicating and Measuring Mechanical Stresses within Ferro-Magnetic Material. U.S. Patent 1959, 2912642.
[30]
Berger, K.B.; Müke, H.G.; Neschütz, R.E.; Thies, K.H. Deflection Measuring Roller. U.S. Patent 4989457, 5 February 1991.
[31]
Gautschi, G. Piezoelectric Sensorics; Springer-Verlag: Zürich, Switzerland, 2002.
[32]
Faure, J.P.; Malard, T. Method for and a Device for Flatness Detection. U.S. Patent 6729757, 4 May 2004.
[33]
Abdelkhalek, S.; Nakhoul, R.; Zahrouni, H.; Montmitonnet, P.; Legrand, N.; Potier-Ferry, M. Applications of Advanced Models to Prediction of Flatness Defects in Cold Rolling of Thin Strips. Proceedings of the 15th International Conference on Advances in Materials and Processing Technologies, Sydney, Australia, 23–26 September 2012.
[34]
Chen, F.; Brown, G.M.; Song, M. Overview of three-dimensional shape measurement using optical methods. Opt. Eng. 2000, 39, 10–22.
[35]
Besl, P.J.. Chapter 1 Active Optical Range Imaging Sensors. In Advances in Machine Vision; Springer-Verlag Inc.: New York, NY, USA, 1989; pp. 1–63.
[36]
Ahlers, R.J.; Lu, J.A. Stereoscopic vision: An application-oriented overview. Proc. SPIE 1989, 1194, 298–308.
[37]
Frauel, Y.; Tajahuerce, E.; Matoba, O.; Castro, A.; Javidi, B. Comparison of passive ranging integral imaging and active imaging digital holography for three-dimensional object recognition. Appl. Opt. 2004, 43, 452–462.
[38]
Pirlet, R.; Luckers, J.; Boelens, J.; WIlmotte, S.; Mulder, J.; Verspeelt, P. Rometer. A New Shape Measuring Device for Hot Strip Mills. Proceedings of the 7th Mineral Waste Utilization Symposium, Chicago, IL, USA, 20–21 October 1980; Volumer 1, pp. 391–398.
[39]
Pirlet, R.; Mulder, J.; Adriaensen, D.; Boelens, J.; Lochen, C. Rometer. A non-contact system for measuring hot strip flatness. Iron Steel Eng. 1983, 60, 45–50.
[40]
Shapeline. Shapeline Product Overview. 2013. Available online: http://www.shapeline.com (accessed on 20 July 2013).
[41]
Pernkopf, F. 3D surface acquisition and reconstruction for inspection of raw steel products. Comput. Ind. 2005, 56, 876–885.
[42]
Usamentiaga, R.; Garc?a, D.F.; Molleda, J.; Bulnes, F.G.; Peregrina, S. Vibrations in Steel Strips: Effects on Flatness Measurement and Filtering. Proceedings of 2013 IEEE Industry Applications Conference, Orlando, FL, USA, 6–11 October 2013.
[43]
Zhang, S. Recent progresses on real-time 3D shape measurement using digital fringe projection techniques. Opt. Lasers Eng. 2010, 48, 149–158.
[44]
Müller, U.; Peuker, G.; Somenschein, E.; Winter, M.D.; Degner, D.M.; Thiemann, B.G. Flatness Measurement System for Metal Strip. U.S. Patent 6286349, 11 September 2001.
[45]
B?rchers, J.; Gromov, A. Topometric measurement of the flatness of rolled products–The system TopPlan. Metallurgist 2008, 52, 247–252.
[46]
Takasaki, H. Moiré topography. Appl. Opt. 1970, 9, 1467–1472.
[47]
Meadows, D.M.; Johnson, W.O.; Allen, J.B. Generation of surface contours by Moiré patterns. Appl. Opt. 1970, 9, 942–947.
[48]
Paakkari, J. On-Line Measurement of Large Steel Plates Using Moireé Topography. Ph.D. Thesis, Oulu University, Oulu, Finland, 1998.
[49]
Vollmer. VIP08 Flatness Measurement System. Available online: http://vollmeramerica.com/2010/02/vip-08-flatness-measurement-system/( (accessed on 16 February 2013).
[50]
Spreitzhofer, G.; Duemmler, A.; Riess, M.; Tomasic, M. SI-FLAT contactless flatness measurement for cold rolling mills and processing lines. Revue Metall. 2005, 102, 589–595.
[51]
Lopera, J.M.; Villegas, P.J.; Linera, F.F.; Hernández-Magadan, F.; Martin-Ramos, J.; Daz, J.; Vecino, G.; Rendueles, J.L. A Low-Cost System for Flatness Monitoring in Metal Processes. Proceedings of 2006 IEEE Industry Applications Conference, Tampa, FL, USA, 8–12 October 2006; Volume 1, pp. 528–533.
[52]
Lopera, J.M.; Villegas, P.J.; Linera, F.F.; Hernández-Magadan, F.; Martin-Ramos, J.; Daz, J.; Vecino, G.; Rendueles, J.L. Flatten it out: Designing a low-cost system for flatness monitoring in metal processes. IEEE Ind. Appl. Mag. 2008, 14, 62–66.
[53]
Vicente, P.; Lopes, C.; Becler, D.; Prendes, P.; Vecino, G.; Espina, A.; Brana, P.; Amrane, L.; Madelaine, O.; Legrand, N. Innovative Techniques and Solutions for Controlling Flatness on Cold Strip Mills and on Downstream Continuous Lines. Proceedings of the 10th International Conference on Steel Rolling, Beijing, China, 15–17 September 2010.
[54]
Garc?a, D.F.; del R?o, M.A.; Diaz, J.L.; Suárez, F.J. Flatness Defect Measurement System for Steel Industry based on a Real-time Linear-image Processor. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Le Touquet, France, 17–20 October 1993; Volume 3, pp. 331–336.
[55]
Garc?a, M.; Garc?a, D.F.; D?az, J.L.; Suárez, F. Flatness Defects Detection in Rolling Products with Real-time Vision System. Proceedings of the Second International Conference on Intelligent Systems Engineering, Hamburg-Harburg, Germany; 1994; pp. 407–412.
[56]
Garc?a, D.F.; Garc?a, M.; D?az, J.L.; Arias, J.R.; Garc?a, J. Real-time Flatness Sensor Based on a Linear-vision Multiprocessor System (RV-05). Proceedings of the 20th IECON (Industrial Electronics Conference, Bologna, Italy, 5–9 September 1994; Volume 2, pp. 873–878.
[57]
Garc?a, D.F.; Garc?a, M.; Obeso, F.; Fernández, V. Real-time flatness inspection system for steel strip production lines. Real-Time Imaging 1999, 5, 35–47.
[58]
Garc?a, D.F.; Garc?a, M.; Obeso, F.; Fernández, V. Flatness Measurement System Based on a Non-linear Optical Triangulation Technique. Proceedings of the 17th IEEE Instrumentation and Measurement Technology Conference, Baltimore, MD, USA, 1–4 May 2000; Volume 3, pp. 1297–1302.
[59]
Garc?a, D.F.; Garc?a, M.; Obeso, F.; Fernández, V. Flatness measurement system based on a nonlinear optical triangulation technique. IEEE Trans. Instrum. Meas. 2002, 51, 188–195.
[60]
López, C.; Garc?a, D.F.; Usamentiaga, R.; González, D.; González, J.A. Real time system for flatness inspection of steel strips. Proc SPIE 2005, 5679, 228–238.
[61]
Usamentiaga, R.; Molleda, J.; Garc?a, D.F.; Bulnes, F.G. Machine Vision System for Flatness Control Feedback. Proceedings of the 2009 2nd International Conference on Machine Vision (ICMV 2009), Dubai, United Arab Emirates, 28–30 December 2009; pp. 105–110.
[62]
Usamentiaga, R.; Molleda, J.; Garc?a, D. Fast and robust laser stripe extraction for 3D reconstruction in industrial environments. Mach. Vision Appl. 2012, 23, 179–196.
[63]
Molleda, J.; Usamentiaga, R.; Garc?a, D.F.; Bulnes, F.G.; Ema, L. Shape measurement of steel strips using a laser-based three-dimensional reconstruction technique. IEEE Trans. Ind. Appl. 2011, 47, 1–8.
[64]
Molleda, J.; Usamentiaga, R.; Garc?a, D.F.; Bulnes, F.G.; Espina, A.B.D.; Smith, L.N. An improved 3D imaging system for dimensional quality inspection of rolled products in the metal industry. Comput. Ind. 2013. in press.
[65]
Garc?a, D.F.; López, C.; Canga, I.; González, D.; Usamentiaga, R.; lez, J.A. Visualization of the Flatness of Steel Strips during and after their Manufacturing. Proceedings of the International Conference on Visualization, Imaging and Image Processing (VIIP), Benalmadena, Spain, 8–10 September 2003; 2003; Volume 2, pp. 843–848.
[66]
González, R.C.; Valdés, R.; Cancelas, J.A. Vision based measurement system to quantify straightness defect in steel sheets. Comput. Anal. Images Patterns. Lect. Note. Comput. Sci. 2001, 2124, 427–434.
[67]
Molleda, J.; Usamentiaga, R.; Garc?a, D.F.; Bulnes, F.G.; Ema, L. Uncertainty Analysis in 3D Shape Measurement of Steel Strips using Laser Range Finding. Proceedings of 2011 IEEE Instrumentation and Measurement Technology Conference, Hangzhou, China, 10–12 May 2011; pp. 592–597.