Real-Time Performance Evaluation of the Combustion Process of Coke Oven
Qi Lei*,** and Di Zhu*
*School of Automation, Central South University
No.932 South Lushan Road, Changsha, Hunan 410083, China
**Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems
No.388 Lumo Road, Hongshan District, Wuhan, Hubei 430074, China
Real-time performance assessment is one of the main methods to guarantee the steady operation of production during the combustion process of a coke oven. In this study, a real-time assessment method is proposed for this combustion process based on the analytic hierarchy process (AHP) and intuitionistic multiplicative preference relation. Relevant scholars, senior engineers, and elite workers participated in this project to build the AHP model with three aspects (i.e. safety, stability, and economic benefit) and perform pairwise comparisons of criteria and sub-criteria through group decisions. To support real-time, the pairwise comparisons of alternatives were realized by an automated method using measurement values. This comprehensive assessment method demonstrates ability to provide real-time performance evaluation for the combustion process. An experiment was conducted to evaluate the effectiveness and viability of the proposed method.
-  N. I. Yurin, O. S. Morozov, O. L. Likhacheva, V. I. Yukhimenko, and S. A. Shtekker, “Influence of coke quality on blast-furnace performance,” Steel in Translation, Vol.41, Issue 11, pp. 924-927, 2011.
-  M. J. Neely, “Dynamic Optimization and Learning for Renewal Systems,” IEEE Trans. on Automatic Control, Vol.58, Issue 1, pp. 32-46, 2013.
-  I. Asadi and E. Asadi, “Investigation on effect of real time optimization (RTO) on reducing energy consumption in the gas sweetening plant in Iran,” Proc. of the 3rd Int. Youth Conf. on Energetics (IYCE 2011), 2011.
-  M. Wu, Q. Lei, W. Cao, and J. She, “Integrated soft sensing of coke-oven temperature,” Control Engineering Practice, Vol.19, Issue 10, pp. 1116-1125, 2011.
-  M. Wu, Q. Lei, W. Cao, and J. She, “Intelligent integrated control of combustion process of coke oven based on determination of operating state,” Int. J. of Systems, Control and Communications, Vol.1, No.2, pp. 193-214, 2008.
-  H. Yan, Q. Lei, and M. Wu, “A Hierarchical Experimental Simulation Platform of Coking Production,” J. Adv. Comput. Intell. Intell. Inform., Vol.19, No.2, pp. 232-238, 2015.
-  N. K. Berkutov, Y. V. Stepanov, N. K. Popova, Y. P. Petrenko, and V. V. Belov, “The relation between coke quality and blast-furnace performance,” Steel in Translation, Vol.37, Issue 5, pp. 438-441, 2007.
-  H. Huo, Y. Lei, Q. Zhang, L. Zhao, and K. He, “China’s coke industry: Recent policies, technology shift, and implication for energy and the environment,” Energy Policy, Vol.51, pp. 397-404, 2012.
-  S. H. Zyoud, L. G. Kaufmann, H. Shaheen, S. Samhan, and D. Fuchs-Hanusch, “A framework for water loss management in developing countries under fuzzy environment: Integration of Fuzzy AHP with Fuzzy TOPSIS,” Expert Systems with Applications, Vol.61, pp. 86-105, 2016.
-  W. W. Kropp and J. K. Lein, “Assessing the Geographic Expression of Urban Sustainability: A Scenario Based Approach Incorporating Spatial Multicriteria Decision Analysis,” Sustainability, Vol.4, Issue 9, pp. 2348-2365, 2012.
-  M. Behzadian, S. K. Otaghsara, M. Yazdani, and J. Ignatius, “A state-of the-art survey of TOPSIS applications,” Expert Systems with Applications, Vol.39, Issue 17, pp. 13051-13069, 2012.
-  A. Ishizaka and A. Labib, “Review of the main developments in the analytic hierarchy process,” Expert Systems with Applications, Vol.38, Issue 11, pp. 14336-14345, 2011.
-  Q. Wang, H. Wang, and Z. Qi, “An application of nonlinear fuzzy analytic hierarchy process in safety evaluation of coal mine,” Safety Science, Vol.86, pp. 78-87, 2016
-  M. J. Rahimdel and M. Karamoozian, “Fuzzy TOPSIS method to primary crusher selection for Golegohar Iron Mine (Iran),” J. of Central South University, Vol.21, Issue 11, pp. 4352-4359, 2014.
-  J. Hu, L. Zhou, and Y. Wang, “Comparative Analysis of Risk Assessment for Technical Standards Alliance Based on BP Neural Network and Fuzzy AHP Methods,” J. Adv. Comput. Intell. Intell. Inform., Vol.22, No.6, pp. 838-845, 2018.
-  A. N. Sperber, A. C. Elmore, M. L. Crow, and J. D. Cawlfield, “Performance evaluation of energy efficient lighting associated with renewable energy applications,” Renewable Energy, Vol.44, pp. 423-430, 2012.
-  K. Zhü, O. Cooper, S. Yang, and Q. Dong, “An Extension of the AHP Dummy Pivot Modeling Applied to the Restructuring of the Iron and Steel Industry in China,” IEEE Trans. on Engineering Management, Vol.61, Issue 2, pp. 370-380, 2014.
-  K. T. Atanassov, “Intuitionistic fuzzy sets,” Fuzzy Sets and Systems, Vol.20, Issue 1, pp. 87-96, 1986.
-  L. A. Zadeh, “Fuzzy sets,” Information and Control, Vol.8, Issue 3, pp. 338-353, 1965.
-  M. Xia, Z. Xu, and H. Liao, “Preference Relations Based on Intuitionistic Multiplicative Information,” IEEE Trans. on Fuzzy Systems, Vol.21, Issue 1, pp. 113-133, 2013.
-  H. Garg, “Generalized intuitionistic fuzzy multiplicative interactive geometric operators and their application to multiple criteria decision making,” Int. J. of Machine Learning and Cybernetics, Vol.7, Issue 6, pp. 1075-1092, 2016.
-  Q. Lei and D. Zhu, “Performance Evaluation for Combustion Process Based on Intuitionistic Multiplicative Analytic Hierarchy Process,” The Joint Int. Conf. of ISCIIA 2018 and ITCA 2018, No.3A1-2-3, 2018.
-  Z. Zhang and W. Pedrycz, “Intuitionistic Multiplicative Group Analytic Hierarchy Process and Its Use in Multicriteria Group Decision-Making,” IEEE Trans. on Cybernetics, Vol.48, Issue 7, pp. 1950-1962, 2017.
-  P. Ren, Z. Xu, and H. Liao, “Intuitionistic multiplicative analytic hierarchy process in group decision making,” Computers & Industrial Engineering, Vol.101, pp. 513-524, 2016.
-  Y. Jiang, Z. Xu, and X. Yu, “Compatibility measures and consensus models for group decision making with intuitionistic multiplicative preference relations,” Applied Soft Computing, Vol.13, Issue 4, pp. 2075-2086, 2013.
-  Y. Jiang and Z. Xu, “Aggregating information and ranking alternatives in decision making with intuitionistic multiplicative preference relations,” Applied Soft Computing, Vol.22, pp. 162-177, 2014.
-  J. Krejčí, D. Petri, and M. Fedrizzi, “From Measurement to Decision with the Analytic Hierarchy Process: Propagation of Uncertainty to Decision Outcome,” IEEE Trans. on Instrumentation and Measurement, Vol.66, Issue 12, pp. 3228-3236, 2017.
-  Z. Xu, “Priority Weight Intervals Derived From Intuitionistic Multiplicative Preference Relations,” IEEE Trans. on Fuzzy Systems, Vol.21, Issue 4, pp. 642-654, 2013.
-  Z. S. Xu and Q. L. Da, “An overview of operators for aggregating information,” Int. J. of Intelligent Systems, Vol.18, Issue 9, pp. 953-969, 2003.