Global method for learning an integrated temperature prediction model in a slab reheating furnace. (English) Zbl 1523.80003
Summary: Temperature prediction in a slab heating furnace is an important problem for steel production processes. However, the problem is complicated owing to process complexity and industrial noise. These factors make it difficult to obtain precise prediction results by a mechanism model in practical production. In this article, an integrated modelling approach is proposed through combining mechanism and data-driven models. This method constructs a generalized-kernel support vector regression (SVR) on new search space to improve the predictive performance of a mechanism model, in which the kernel matrix is a combination of multiple single kernels. The learning problem can be solved globally by a semi-definite programming (SDP) problem. Numerical experiments using actual data from an iron and steel enterprise in China are performed to illustrate the effectiveness of the proposed integrated method.
MSC:
| 80M50 | Optimization problems in thermodynamics and heat transfer |
| 90C22 | Semidefinite programming |
| 90C90 | Applications of mathematical programming |
References:
| [1] | Andrés-Pérez, E.; González-Juárez, D.; Martin-Burgos, M. J.; Carro-Calvo, L.; Salcedo-Sanz, S., Influence of the Number and Location of Design Parameters in the Aerodynamic Shape Optimization of a Transonic Aerofoil and a Wing through Evolutionary Algorithms and Support Vector Machines, Engineering Optimization, 49, 2, 181-198 (2017) · doi:10.1080/0305215X.2016.1165568 |
| [2] | Boser, B. E., Guyon, I. M., and Vapnik, V. N.. 1992. “A Training Algorithm for Optimal Margin Classifiers.” In Proceedings of the Fifth Annual Workshop on Computational Learning Theory (COLT ’92), 144-152. New York: Association for Computing Machinery (ACM).doi:10.1145/130385.130401. |
| [3] | Brunaud, B.; Grossmann, I. E., Perspectives in Multilevel Decision-Making in the Process Industry, Frontiers of Engineering Management, 4, 3, 256-270 (2017) · doi:10.15302/J-FEM-2017049 |
| [4] | Chih-Chung, C.; Chih-Jen, L., LIBSVM: A Library for Support Vector Machines, ACM Transactions on Intelligent Systems and Technology, 2, 3, 1-27 (2011) · doi:10.1145/1961189.1961199 |
| [5] | Cortes, C.; Vapnik, V., Support Vector Networks, Machine Learning, 20, 3, 273-297 (1995) · Zbl 0831.68098 · doi:10.1007/bf00994018 |
| [6] | Cristianini, Nello, Kandola, Jaz, Elisseeff, Andre, and Shawe-Taylor, John. 2006. “On Kernel Target Alignment.” In Innovations in Machine Learning—Theory and Applications, edited by Dawn E. Holmes and Lakhmi C. Jain, 205-256. Berlin: Springer.doi:10.1007/3-540-33486-6_8. |
| [7] | Das, Anupam; Maiti, J.; Banerjee, R. N., Process Control Strategies for a Steel Making Furnace Using ANN with Bayesian Regularization and ANFIS, Expert Systems with Applications, 37, 2, 1075-1085 (2010) · doi:10.1016/j.eswa.2009.06.056 |
| [8] | Dong, X. U.; Cheng, J. I.; Zhu, M. Y.; Tang, Z. Y., Simulation for Bloom Heating-Up Process in Reheating Furnace, Journal of Northeastern University (Natural Science), 34, 2, 244-251 (2013) · doi:10.3969/j.issn.1005-3026.2013.02.022 |
| [9] | Duan, K.; Keerthi, S. S.; Poo, A. N., Evaluation of Simple Performance Measures for Tuning SVM Hyperparameters, Neurocomputing, 51, 41-59 (2003) · doi:10.1016/s0925-2312(02)00601-x |
| [10] | Duan, L.; Xiao, N.; Li, G.; Cheng, A.; Chen, T., Design Optimization of Tailor-Rolled Blank Thin-Walled Structures Based on ϵ-Support Vector Regression Technique and Genetic Algorithm, Engineering Optimization, 49, 7, 1148-1165 (2017) · doi:10.1080/0305215x.2016.1241016 |
| [11] | Feng, H.; Chen, L.; Xie, Z.; Sun, F., Constructal Designs for Insulation Layers of Steel Rolling Reheating Furnace Wall with Convective and Radiative Boundary Conditions, Applied Thermal Engineering, 100, 925-931 (2016) · doi:10.1016/j.applthermaleng.2016.02.129 |
| [12] | Gestel, T. V.; Suykens, J. A. K.; Baesens, B.; Viaene, S.; Vanthienen, J.; Dedene, G.; Moor, B.; Vandewalle, J., Benchmarking Least Squares Support Vector Machine Classifiers, Machine Learning, 54, 1, 5-32 (2004) · Zbl 1078.68737 · doi:10.1023/b:mach.0000008082.80494.e0 |
| [13] | Grant, Michael, Boyd, Stephen, and Ye, Yinyu. 2006. “Disciplined Convex Programming.” In Global Optimization, 155-210. Boston, MA: Springer Science+Business Media.doi:10.1007/0-387-30528-9_7. · Zbl 1130.90382 |
| [14] | Gu, M. Y.; Chen, G.; Liu, X.; Wu, C.; Chu, H., Numerical Simulation of Slab Heating Process in a Regenerative Walking Beam Reheating Furnace, International Journal of Heat & Mass Transfer, 76, 6, 405-410 (2014) · doi:10.1016/j.ijheatmasstransfer.2014.04.061 |
| [15] | Han, S. H.; Baek, S. W.; Kim, M. Y., Transient Radiative Heating Characteristics of Slabs in a Walking Beam Type Reheating Furnace, International Journal of Heat & Mass Transfer, 52, 3, 1005-1011 (2009) · Zbl 1156.80327 · doi:10.1016/j.ijheatmasstransfer.2008.07.030 |
| [16] | Horn, R. A.; Johnson, C., Matrix Analysis (1985), New York: Cambridge University Press, New York · Zbl 0576.15001 · doi:10.1017/CBO9780511810817 |
| [17] | Hsieh, C. T.; Huang, M. J.; Lee, S. T.; Wang, C. H., Numerical Modeling of a Walking-Beam-Type Slab Reheating Furnace, Numerical Heat Transfer, 53, 9, 966-981 (2008) · doi:10.1080/10407780701789831 |
| [18] | Jaklič, A.; Vode, F.; Kolenko, T., Online Simulation Model of the Slab-Reheating Process in a Pusher-Type Furnace, Applied Thermal Engineering, 27, 5-6, 1105-1114 (2007) · doi:10.1016/j.applthermaleng.2006.07.033 |
| [19] | Jang, J. H.; Lee, D. E.; Kim, M. Y.; Kim, H. G., Investigation of the Slab Heating Characteristics in a Reheating Furnace with the Formation and Growth of Scale on the Slab Surface, International Journal of Heat & Mass Transfer, 53, 19-20, 4326-4332 (2010) · Zbl 1194.80033 · doi:10.1016/j.ijheatmasstransfer.2010.05.061 |
| [20] | Kim, J. G.; Huh, K. Y.; Kim, Il T., Three-Dimensional Anaysis of the Walking-Beam-Type Slab Reheating Furnace in Hot Strip Mills, Numerical Heat Transfer, Part A: Applications, 38, 6, 589-609 (2000) · doi:10.1080/104077800750021152 |
| [21] | Kumar, V.; Dixit, U. S., Selection of Process Parameters in a Single-Pass Laser Bending Process, Engineering Optimization, 50, 9, 1609-1624 (2017) · doi:10.1080/0305215X.2017.1405395 |
| [22] | Lanckriet, G., Cristianini, N., Bartlett, P., Ghaoui, L. E., and Jordan, M. I.. 2002. “Learning the Kernel Matrix with Semi-Definite Programming.” Journal of Machine Learning Research5: 27-72. · Zbl 1222.68241 |
| [23] | Laurinen, P.; Röning, J., An Adaptive Neural Network Model for Predicting the Post Roughing Mill Temperature of Steel Slabs in the Reheating Furnace, Journal of Materials Processing Technology, 168, 3, 423-430 (2005) · doi:10.1016/j.jmatprotec.2004.12.002 |
| [24] | Liu, Y. J.; Li, J. D.; Misra, R. D. K.; Wang, Z. D.; Wang, G. D., A Numerical Analysis of Slab Heating Characteristics in a Rolling Type Reheating Furnace with Pulse Combustion, Applied Thermal Engineering, 107, 1304-1312 (2016) · doi:10.1016/j.applthermaleng.2016.07.074 |
| [25] | Liu, C.; Tang, L. X.; Liu, J. Y., A Dynamic Analytics Method Based on Multistage Modeling for a BOF Steelmaking Process, IEEE Transactions on Automation Science and Engineering, 16, 3, 1097-1109 (2019) · doi:10.1109/TASE.2018.2865414 |
| [26] | Otsuka, K.; Matoba, Y.; Kajiwara, Y.; Kojima, M.; Yoshida, M., A Hybrid Expert System Combined with a Mathematical Model for Blast Furnace Operation, ISIJ International, 30, 2, 118-127 (2007) · doi:10.2355/isijinternational.30.118 |
| [27] | Overton, M. L.; Womersley, R. S., Optimality Conditions and Duality Theory for Minimizing Sums of the Largest Eigenvalues of Symmetric Matrices, Mathematical Programming, 62, 1-3, 321-357 (1993) · Zbl 0806.90114 · doi:10.1007/bf01585173 |
| [28] | Sturm, J. F., Using SeDuMi 1.02, A Matlab Toolbox for Optimization Over Symmetric Cones, Optimization Methods and Software, 11, 14, 625-653 (1999) · Zbl 0973.90526 · doi:10.1080/10556789908805766 |
| [29] | Talya, S. S.; Chattopadhyay, A.; Rajadas, J. N., Multidisciplinary Design Optimization Procedure for Improved Design of a Cooled Gas Turbine Blade, Engineering Optimization, 34, 2, 175-194 (2002) · doi:10.1080/03052150210917 |
| [30] | Tang, L. X.; Dong, Y.; Liu, J. Y., Differential Evolution with an Individual-Dependent Mechanism, IEEE Transactions on Evolutionary Computation, 19, 4, 560-574 (2015) · doi:10.1109/tevc.2014.2360890 |
| [31] | Tian, H. X.; Mao, Z. Z., An Ensemble ELM Based on Modified AdaBoost.RT Algorithm for Predicting the Temperature of Molten Steel in Ladle Furnace, IEEE Transactions on Automation Science and Engineering, 7, 1, 73-80 (2009) · doi:10.1109/TASE.2008.2005640 |
| [32] | Tian, H. X.; Mao, Z. Z.; Wang, A. N., Hybrid Modeling for Soft Sensing of Molten Steel Temperature in LF, Journal of Iron & Steel Research, 16, 4, 1-6 (2009) · doi:10.1016/s1006-706x(09)60051-0 |
| [33] | Tripathy, H. P.; Bej, D.; Pattanaik, P.; Mishra, D. K.; Kamilla, S. K.; Tripathy, R. K., Measurement of Zone Temperature Profile of a Resistive Heating Furnace through RVM Model, IEEE Sensors Journal, 18, 11, 4429-4435 (2018) · doi:10.1109/jsen.2018.2826722 |
| [34] | Vapnik, V. N., An Overview of Statistical Learning Theory, IEEE Transactions on Neural Networks, 10, 5, 988-999 (1999) · doi:10.1109/72.788640 |
| [35] | Wang, Z. J.; Guan, S. P.; Chai, T. Y., Adaptive Temperature Prediction Model of Slab in Reheating Furnace [In Chinese], Journal of Iron and Steel Research, 11, 2, 70-74 (1999) · doi:10.13228/j.boyuan.issn1001-0963.1999.02.017 |
| [36] | Wild, D.; Meurer, T.; Kugi, A., Modelling and Experimental Model Validation for a Pusher-Type Reheating Furnace, Mathematical Modelling of Systems, 15, 3, 209-232 (2009) · Zbl 1169.93308 · doi:10.1080/13873950902927683 |
| [37] | Xi, Z. M.; Fu, Y.; Yang, R. J., Model Bias Characterization in the Design Space under Uncertainty, 38th Design Automation Conference, Parts A and B, 3, 1249-1260 (2013) · doi:10.1115/detc2012-71111 |
| [38] | Xia, Q.; Wang, X. P.; Tang, L. X., Furnace Operation Optimization with Hybrid Model Based on Mechanism and Data Analytics, Soft Computing, 23, 19, 9551-9571 (2019) · doi:10.1007/s00500-018-3519-9 |
| [39] | Yin, Ruiyu., Metallurgical Process Engineering (2011), Heidelberg: Springer, Heidelberg · doi:10.1007/978-3-642-13956-7 |
| [40] | Zhu, X.; Zhao, C.; Wang, X.; Zhou, Y.; Hu, P.; Ma, Z. D., Temperature-Constrained Topology Optimization of Thermo-Mechanical Coupled Problems, Engineering Optimization, 51, 10, 1687-1709 (2019) · Zbl 1523.74162 · doi:10.1080/0305215X.2018.1554065 |
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.
