Item request has been placed!
×
Item request cannot be made.
×
Processing Request
Rotary Cement Kiln: A Review to The Control by Expert Systems ; Horno cementero rotatorio: una revisión al control mediante sistemas expertos
Item request has been placed!
×
Item request cannot be made.
×
Processing Request
- المؤلفون: Castillo Tirado, José Luis; Ospina Alarcón , Manuel Alejandro; Ortiz Valencia, Paula Andrea
- المصدر:
TecnoLógicas; Vol. 25 No. 55 (2022); e2391 ; TecnoLógicas; Vol. 25 Núm. 55 (2022); e2391 ; 2256-5337 ; 0123-7799- الموضوع:
- نوع التسجيلة:
article in journal/newspaper
review- اللغة:
Spanish; Castilian - المصدر:
- معلومة اضافية
- بيانات النشر: Instituto Tecnológico Metropolitano (ITM)
- الموضوع: 2022
- Collection: Portal de Revistas Academicas del ITM (Institución Universitaria adscrita al Municipio de Medellín)
- نبذة مختصرة : This article presents a review of research carried out using different control strategies applied in rotary cement kilns, a system where clinker is manufactured, an essential material for cement production. This exploration mentions studies that have been developed from the eighties to the present, highlighting in each one the control methodology used, the benefits obtained in the process and its future applications, in order to provide the reader with a global vision of the use of control techniques for rotary cement kilns and how scientific advances, over the years, have contributed to this industry in the efficiency and improvement of its production processes; therefore, contributions and control methods such as expert systems (ES), model predictive control (MPC), artificial neural networks and fuzzy logic are mentioned. At the end of the aforementioned review, it is inferred that artificial intelligence and industry 4.0 technologies that are currently available such as cloud computing, the processing of large volumes of data, the use of digital twins, the execution of machine learning algorithms and it’s prediction tools, together with the application of ES and other control techniques mentioned, would allow advanced control, which can respond satisfactorily to current production needs and offer multiple benefits such as response time control, stability, and improvements in production and material quality in a rotary kiln. ; Este artículo presenta una revisión de investigaciones realizadas mediante diferentes estrategias de control aplicadas en hornos cementeros rotatorios, sistema donde se da la fabricación de clínker, material indispensable para la elaboración del cemento. Esta exploración menciona estudios que se han desarrollado desde los años ochenta hasta el presente, destacando en cada una la metodología de control utilizada, los beneficios obtenidos en el proceso y sus futuras aplicaciones, esto con el fin de brindar al lector una visión global del uso de técnicas de control para hornos cementeros ...
- File Description: application/pdf; application/zip; text/xml; text/html
- Relation: https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2391/2593; https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2391/2610; https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2391/2611; https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2391/2618; R. Teja, P. Sridhar, and M. Guruprasath, “Control and Optimization of a Triple String Rotary Cement Kiln using Model Predictive Control,” IFAC-PapersOnLine, vol. 49, no. 1, pp. 748–753, 2016, https://doi.org/10.1016/j.ifacol.2016.03.146; L. Qion, T. Jin, Y. Fu, Q. Liu, and Z. Cui, “The Design and Implementation of a Cement kiln Expert System,” Workshop on Intelligent Information Technology Application (IITA 2007), pp. 153–156, 2007, https://doi.org/10.1109/IITA.2007.33; M. Sadeghian and A. Fatehi, “Identification, prediction and detection of the process fault in a cement rotary kiln by locally linear neuro-fuzzy technique,” J Process Control, vol. 21, no. 2, pp. 302–308, 2011, https://doi.org/10.1016/j.jprocont.2010.10.009; S. M. Zanoli, C. Pepe, and L. Barboni, “Application of Advanced Process Control techniques to a pusher type reheating furnace,” J Phys Conf Ser, vol. 659, p. 012014, 2015, https://doi.org/10.1088/1742-6596/659/1/012014; O. Hernandez, P. Ortiz, and J. Herrera, “Cement rotary kiln model using fractional identification,” IEEE Latin America Transactions, vol. 12, no. 2, pp. 87–92, Mar. 2014, https://doi.org/10.1109/TLA.2014.6749522; G. A. Christopoulos, A. Zafiris, and A. N. Safacas, “Energy savings and operation improvement of rotating cement kiln by the implementation of a unique new drive system,” IET Electr Power Appl, vol. 10, no. 2, pp. 101–109, 2016, https://doi.org/10.1049/iet-epa.2015.0063; X. Shi, Q. Sun, Y. Ji, Q. Xu, X. Yang, and X. Hao, “Predictive control research for cement burning system using two-cycle coupling optimization,” Expert Syst Appl, vol. 191, Apr. 2022, https://doi.org/10.1016/j.eswa.2021.116259; S. Dai, L. Yu, X. Zhang, Y. Cheng, and Y. Chen, “Research on surface temperature compensation of rotary kiln based on inverse exponential model,” Infrared Phys Technol, vol. 88, pp. 128–132, 2018, https://doi.org/10.1016/j.infrared.2017.11.014; R. Vashchenko, A. Stepovoy, A. Bazhanov, and V. Magergut, “Application of the model based on fuzzy behavior charts in the advising control system of rotary cement kiln,” in 2016 International Conference on Information and Digital Technologies (IDT), Jul. 2016, pp. 299–304. https://doi.org/10.1109/DT.2016.7557190; Claudius Peters, “Tecnología de enfriamiento de clínker,” claudiuspeters.com. Accessed: May 09, 2022. [Online.] Available: https://www.claudiuspeters.com/es-ES/298/tecnologia-de-enfriamiento-de-clinker-de-claudius-peter; A. I. Okoji, A. N. Anozie, J. A. Omoleye, A. E. Taiwo, and F. N. Osuolale, “Energetic assessment of a precalcining rotary kiln in a cement plant using process simulator and neural networks,” Alexandria Engineering Journal, vol. 61, no. 7, pp. 5097–5109, Jul. 2022, https://doi.org/10.1016/j.aej.2021.10.010; A. Garcia S, Inteligencia Artificial, Fundamentos, prácticas y aplicaciones., 2nd ed. RC Libros, 2016. [Online]. Available: https://books.google.com.co/books?id=WDuqquRP70UC; E. Resendiz-Ochoa, I. A. Cruz-Albarran, M. A. Garduño-Ramon, D. A. Rodriguez-Medina, R. A. Osornio-Rios, and L. A. Morales-Hernández, “Novel expert system to study human stress based on thermographic images,” Expert Syst Appl, vol. 178, Sep. 2021, https://doi.org/10.1016/j.eswa.2021.115024; A. Saibene, M. Assale, and M. Giltri, “Expert systems: Definitions, advantages and issues in medical field applications,” Expert Syst Appl, vol. 177, p. 114900, Sep. 2021, https://doi.org/10.1016/j.eswa.2021.114900; S. Badaro, L. J. Ibañez, and M. Agüero, “SISTEMAS EXPERTOS: Fundamentos, Metodologías y Aplicaciones,” Ciencia y Tecnología, no. 13, pp. 349–363, Dec. 2013, https://doi.org/10.18682/cyt.v1i13.122; J. Varanasi and M. M. Tripathi, “A comparative study of wind power forecasting techniques — A review article,” in 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), Mar. 2016, pp. 3649–3655. [Online]. Available:https://ieeexplore.ieee.org/document/7724943; N. Wang, X. Chen, G. Wu, Y. C. Chang, and S. Yao, “A short-term based analysis on the critical low carbon technologies for the main energy-intensive industries in China,” J Clean Prod, vol. 171, pp. 98–106, 2018, https://doi.org/10.1016/j.jclepro.2017.09.261; H. Ifassiouen, N. E. Radhy and S. E. Tinani, "An expert system for conceiving a grinding chain of cement," Proceedings of IEEE Systems Man and Cybernetics Conference - SMC, 1993, pp. 36-41 vol.5, https://doi.org/10.1109/ICSMC.1993.390821; D. A. Linkens and Minyou Chen, “Expert control systems-I. Concepts, characteristics and issues,” Eng Appl Artif Intell, vol. 8, no. 4, pp. 413–421, 1995, https://doi.org/10.1016/0952-1976(95)00020-2; D. A. Linkens and M. Y. Chen, “Expert control systems-2. Design principles and methods,” Eng Appl Artif Intell, vol. 8, no. 5, pp. 527–537, 1995, https://doi.org/10.1016/0952-1976(95)00020-2; Z.-X. Caia, Y.-N. Wangb, and J.-F. Caia, “A real-time expert control system,” Artificial Intelligence in Engineering, vol. 10, no. 4, pp. 317–322, Nov. 1996, https://doi.org/10.1016/0954-1810(96)00013-1; G.-M. Yang, X.-H. Fan, X.-L. Chen, X.-X. Huang, and Z.-P. Li, “Intelligent control of grate-kiln-cooler process of iron ore pellets using a combination of expert system approach and takagi-sugeno fuzzy model,” Journal of Iron and Steel Research International, vol. 23, no. 5, pp. 434–441, May 2016, https://doi.org/10.1016/S1006-706X(16)30069-3; A. Sharifi, M. Aliyari Shoorehdeli, and M. Teshnehlab, “Identification of cement rotary kiln using hierarchical wavelet fuzzy inference system,” J Franklin Inst, vol. 349, no. 1, pp. 162–183, Feb. 2012, https://doi.org/10.1016/j.jfranklin.2011.10.012; M. A. Sellitto, E. Balugani, R. Gamberini, and B. Rimini, “A Fuzzy Logic Control application to the Cement Industry,” IFAC-PapersOnLine, vol. 51, no. 11, pp. 1542–1547, 2018, https://doi.org/10.1016/j.ifacol.2018.08.277; Y. Cao, Z. J. Zhou, C. H. Hu, S. W. Tang, and J. Wang, “A new approximate belief rule base expert system for complex system modelling,” Decis Support Syst, vol. 150, p. 113558, Nov. 2021, https://doi.org/10.1016/j.dss.2021.113558; A. Sarazin et al., “Expert system dedicated to condition-based maintenance based on a knowledge graph approach: Application to an aeronautic system,” Expert Syst Appl, vol. 186, p. 115767, Dec. 2021, https://doi.org/10.1016/j.eswa.2021.115767; R. Müller, L. Hörauf, and D. Burkhard, “Development of an AI-based expert system for the part- and process-specific marking of materials,” Procedia CIRP, vol. 100, pp. 361–366, 2021, https://doi.org/10.1016/j.procir.2021.05.083; E. H. Mamdani, H. J. Efstathiou, and K. Sugiyama, “Developments in fuzzy logic control,” in The 23rd IEEE Conference on Decision and Control, Dec. 1984, pp. 888–893. https://doi.org/10.1109/CDC.1984.272140; M. B. Hall, “Kiln stabilization and control-a COMDALE/C expert system approach,” in [1993] Record of Conference Papers 35th IEEE Cement Industry Technical, May. 1993, pp. 201–218. https://doi.org/10.1109/CITCON.1993.296984; C. W. Ruby, “A new approach to expert kiln control,” in 1997 IEEE/PCA Cement Industry Technical Conference. XXXIX Conference Record (Cat. No.97CH36076), Apr. 1997, pp. 399–412. https://doi.org/10.1109/CITCON.1997.599411; A. Correcher, F. Morant, E. Garcia, R. Blasco-Gimenez, and E. Quiles, “Failure diagnosis of a cement kiln using expert systems,” in IEEE 2002 28th Annual Conference of the Industrial Electronics Society. IECON 02, Nov. 2001, vol. 3, pp. 1881–1886. https://doi.org/10.1109/IECON.2002.1185258; C. Wang, S. Wang, G. Yu, and X. Li, “Application Research of a Fault Diagnosis Expert System for Cement Kiln Based on .Net Platform,” in 2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics, Aug. 2010, pp. 208–212. https://doi.org/10.1109/IHMSC.2010.58; H. Yu, W. Liu, and H. Dong, “Research on recognition of working condition for calciner and grate cooler based on expert system,” in 2012 12th International Conference on Control Automation Robotics & Vision (ICARCV), Dec. 2012, pp. 1733–1737. https://doi.org/10.1109/ICARCV.2012.6485411; S. Deng, X. Qing-song, and J. Zhou, “A lime shaft kiln diagnostic expert system based on holographic monitoring and real-time simulation,” Expert Syst Appl, vol. 38, no. 12, pp. 15400–15408, Nov. 2011, https://doi.org/10.1016/j.eswa.2011.06.021; C. Yang, Hongqiu Zhu, and Weihua Gui, “An Intelligent Control System for Coke Calcination in Rotary Kiln,” in 2007 IEEE International Conference on Control and Automation, May 2007, pp. 2365–2369. https://doi.org/10.1109/ICCA.2007.4376784; Y. Zhugang, C. Pu, and W. Xiaohong, “The Power Consumption Analysis of Cement Rotary Kiln Production Line System,” in 2013 Sixth International Symposium on Computational Intelligence and Design, Oct. 2013, pp. 11–14. https://doi.org/10.1109/ISCID.2013.10; H. Yu, F. Wang, X. Wang, and X. Ma, “Study on dynamic models of cement calciner based on typical working conditions,” in 2016 35th Chinese Control Conference (CCC), Jul. 2016, pp. 2103–2107. https://doi.org/10.1109/ChiCC.2016.7553677; M. Järvensivu, K. Saari, and S.-L. Jämsä-Jounela, “Intelligent control system of an industrial lime kiln process,” Control Eng Pract, vol. 9, no. 6, pp. 589–606, Jun. 2001, https://doi.org/10.1016/S0967-0661(01)00017-X; J. Ziatabari, A. Fatehi, and M. T. H. Beheshti, “Cement rotary kiln control: A supervised adaptive model predictive approach,” in 2008 Annual IEEE India Conference, Dec. 2008, pp. 371–376. https://doi.org/10.1109/INDCON.2008.4768752; S. M. Zanoli, C. Pepe, and M. Rocchi, “Control and optimization of a cement rotary kiln: A model predictive control approach,” in 2016 Indian Control Conference (ICC), Jan. 2016, pp. 111–116. https://doi.org/10.1109/INDIANCC.2016.7441114; B. Yang and X. Ma, “Neural dynamic programming based temperature optimal control for cement calcined process,” in 2009 Chinese Control and Decision Conference, Jun. 2009, pp. 1903–1908. https://doi.org/10.1109/CCDC.2009.5192785; S. M. Zanoli, C. Pepe, and M. Rocchi, “Cement rotary kiln: Constraints handling and optimization via model predictive control techniques,” in 2015 5th Australian Control Conference (AUCC), Nov. 2015, pp. 288–293. [Online]. Available: https://ieeexplore.ieee.org/document/7361950; G. Feng, L. Bin, H. Xiaochen, and G. Peng, “Research on the fuzzy predictive control for calcining temperature of the rotary cement kiln,” in IEEE 10th International Conference on Signal Processing Proceedings, Oct. 2010, pp. 2568–2571. https://doi.org/10.1109/ICOSP.2010.5655752; Shengwang Li, Rui Li, and Weitao Liu, “The application of expert system and fuzzy control system in cement grate cooler system,” in 2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS), Aug. 2016, pp. 770–773. https://doi.org/10.1109/ICSESS.2016.7883181; K. S. Stadler, J. Poland, and E. Gallestey, “Model predictive control of a rotary cement kiln,” Control Eng Pract, vol. 19, no. 1, pp. 1–9, Jan. 2011, https://doi.org/10.1016/j.conengprac.2010.08.004; H. Yu, C. Yao, and X. Wang, “Study on cement clinker burning energy efficiency,” in The 26th Chinese Control and Decision Conference (2014 CCDC), May 2014, pp. 5198–5201. https://doi.org/10.1109/CCDC.2014.6853108; Z. Yang, X. Wang, and H. Yu, “Study on generalized predictive control of cement rotary kiln calcining zone temperature,” in 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC), Oct. 2016, pp. 1653–1658. https://doi.org/10.1109/IMCEC.2016.7867498; A. Nevado, C. de Mora, and H. Pastor, “Control Adaptativo Predictivo Experto: Metodología Y Aplicación Industrial,” Control, no. January, pp. 1–11, 2005, [Online]. Available: https://www.researchgate.net/publication/228636972; T. Engin and V. Ari, “Energy auditing and recovery for dry type cement rotary kiln systems––A case study,” Energy Convers Manag, vol. 46, no. 4, pp. 551–562, Mar. 2005, https://doi.org/10.1016/j.enconman.2004.04.007; K. Anand, E. Mamatha, C. S. Reddy, and M. Prabha, “Design of Neural Network Based Expert System for Automated Lime Kiln System,” Journal Européen des Systèmes Automatisés, vol. 52, no. 4, pp. 369–376, Oct. 2019, https://doi.org/10.18280/jesa.520406; Q. Xu, X. Hao, X. Shi, Z. Zhang, Q. Sun, and Y. Di, “Control of denitration system in cement calcination process: A Novel method of Deep Neural Network Model Predictive Control,” J Clean Prod, vol. 332, p. 129970, Jan. 2022, https://doi.org/10.1016/j.jclepro.2021.129970; https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2391
- الدخول الالكتروني : https://doi.org/10.1016/j.ifacol.2016.03.146
https://doi.org/10.1109/IITA.2007.33
https://doi.org/10.1016/j.jprocont.2010.10.009
https://doi.org/10.1088/1742-6596/659/1/012014
https://doi.org/10.1109/TLA.2014.6749522
https://doi.org/10.1049/iet-epa.2015.0063
https://doi.org/10.1016/j.eswa.2021.116259
https://doi.org/10.1016/j.infrared.2017.11.014
https://doi.org/10.1109/DT.2016.7557190
https://doi.org/10.1016/j.aej.2021.10.010 - Rights: Derechos de autor 2022 TecnoLógicas ; http://creativecommons.org/licenses/by-nc-sa/4.0
- الرقم المعرف: edsbas.95020819
- بيانات النشر:
حقوق النشر© 2024، دائرة الثقافة والسياحة جميع الحقوق محفوظة Powered By EBSCO Stacks 3.3.0 [353] | Staff Login
حقوق النشر © دائرة الثقافة والسياحة، جميع الحقوق محفوظة
No Comments.