A review study on ladle slag detection technologies in continuous casting process

Year 2019, Volume: 3 Issue: 3, 144 - 149, 15.12.2019

Hakan Kapusuz Mehmet Ali Güvenç , Selçuk Mıstıkoğlu

https://doi.org/10.35860/iarej.421657

Cited By: 4

Abstract

In
steel production, continuous casting method using BOF or EAF is increasing day
by day. However, the complex nature of the continuous casting process poses
many challenges for steelmakers. During the general steel production process of
liquid steel, the state of ladle slag penetration into liquid steel is one of
the most influential factors in steel quality. If the ingress of ladle slag
into liquid steel cannot be controlled, undesirable results in terms of poor
quality, safety and castability can occur. Generally, ladle slag consists of
oxides such as CaO, SiO 2, Al 2 O 3, MgO. In conventional methods, the operator
prevents the slag entry by manually controlling it. This method is performed
directly by the operator, so the error rate is high. For this reason, it is not
desired to be used by steel producers who want high quality products. In this
context, steel mills carry out various activities to separate slag from liquid
steel. The development of sensor technologies has accelerated the slag
detection process. Acceleration and magnetic sensors are among the most widely
used methods in this field. In this study,
the systems used worldwide for the determination of slag in the continuous
casting process were investigated and presented. The advantages and disadvantages
of these systems are discussed. The detection methods by considering investment
cost, detection time, accuracy were compared and presented. In the scope of
this study, it is seen that every method has own advantages and disadvantages
over other. 

Keywords

Continuous cast, Ladle slag detection, Vibration

References

• 1. Oberbach M. High Grade Refractories for Clean Steel Technology. In: Steel Technology International, 1991. 26: pp 169–176.
• 2. Ozturk M., U. Korkut, Investigation of mechanical and microstructural performance of alkali activated electrical arc furnace slag mortars. International Advanced Research and Engineering journal, 2019. 03: p. 55–59.
• 3. Madias J., Electric Furnace Steelmaking. 2014, Elsevier Ltd.
• 4. Li P.Y., D.P. Tan., X.H. Pan, B.Y. Lin, Steel water continuous casting slag detection system based on wavelet. Key Engineering Materials, 2007. 353: p 3067–3071.
• 5. Yoshitani Y., Contribution of Control System to Energy Savings in Steel Works. IFAC Proceedings Volumes, 1983. 16: p 25–38.
• 6. Takács G., K. Ondrejkovič, G. Hulkó, A low-cost non-invasive slag detection system for continuous casting. IFAC-PapersOnLine, 2017. 50:438–445.
• 7. Zhang L., B.G. Thomas, Inclusions in continuous casting of steel. XXIV National Steelmaking Symposium2, 2013. 26:138–183.
• 8. Louhenkilpi S., Continuous Casting of Steel. In: Treatise on Process Metallurgy. 2014, Elsevier Ltd., pp 373–434.
• 9. Pistorius P. C., Slag carry-over and the production of clean steel. Journal of the Southern African Institute of Mining and Metallurgy,2019. 119: 557–561.
• 10. Varanasi S, Plant VS, Madhava V, et al Slag Modeling for Effective Desulphurization in Ladle Furnace Refining, APM 2019 conference, 2019.
• 11. Sanam V., P. K. Patra, Reduction of Slivers Due To Nonmetallic Inclusions in Continuous Casting. Materials Science and Technology, 2009. p. 1031–1041.
• 12. Zhang L., State of the Art in the Control of Inclusions in Tire Cord Steels - a Review. Steel Research International, 2006. 77: p. 158-169.
• 13. Qin Y., X. Wang, L. Li, F. Huang, Effect of Oxidizing Slag on Cleanliness of if Steel during Ladle Holding Process. Steel Research International, 2015. 86: p.1037–1045.
• 14. Holappa L, Wijk O., Inclusion Engineering, 2014, 1st ed. Elsevier Ltd.
• 15. Sahai Y, T. Emi, Tundish Technology for Clean Steel Production, 2008. World Scientific Publishing Co. Pte. Ltd.
• 16. Mills KC, A.B. Fox, Z. Li, R.P. Thackray, Performance and properties of mould fluxes. Ironmaking & Steelmaking, 2005. 32: p. 26–34.
• 17. Ludlow V., B. Harris, S. Riaz, A. Normanton Continuous casting mould powder and casting process interaction: why powders do not always work as expected. Ironmaking & Steelmaking, 2005. 32: p. 120–126.
• 18. Dede S., F. Altay, Biosensors from the First Generation to Nano-biosensors. International Advanced Research and Engineering Journal, 2018. 02: p. 200–207.
• 19. Luk’yanov SI, Suspitsyn ES, Pishnograev RS, Krasilnikov SS, Survey of melt stream infrared radiation parameters at various stages of steel tapping from basic oxygen furnace. International Journal of Advanced Manufacturing Technology, 2017. 88: p. 595–602.
• 20. Berner K., Detecting method for slag carry-over in steel production, 1996.
• 21. Zhang Z., L. Bin, Y. Jiang, Optik Slag detection system based on infrared temperature measurement. Optik - International Journal for Light and Electron Optics, 2014. 125: p. 1412–1416.
• 22. Sandberg E., B. Lennox, P. Undvall, Scrap management by statistical evaluation of EAF process data. Control Engineering Practice, 2017. 15: p. 1063–1075.
• 23. Raghavendra K., S. Sarkar, S.K. Ajmani, et al. Mathematical modelling of single and multi-strand tundish for inclusion analysis. Applied Mathematical Modelling, 2013. 37: p. 6284–6300.
• 24. Bhattacharya D., A. Mishra, G.P. Poddar, S. Misra, Case study of severe strip breakage in rolling mill of Thin Slab Casting and Rolling (TSCR) shop of TATA Steel, Jamshedpur. Case Studies in Engineering Failure Analysis, 2016. 5–6: p. 15–22.
• 25. Singh S., Continuous Casting. In: Reference Module in Materials Science and Materials Engineering, 2018. p. 1–11.
• 26. Chakraborty B, Sinha, BK Development of caster slag detection system through imaging technique. International Journal of Instrumentation Technology, 2011. 1(1): p. 84-91.
• 27. Chen D., H. Xiao, Q. Ji, Vibration Style Ladle Slag Detection Method based on Discrete Wavelet Decomposition. IEEE, 2014. p. 3019–3022.
• 28. Tan D, S. Ji, P. Li, X. Pan, Development of vibration style ladle slag detection methods and the key technologies. Science China Technological Sciences, 2010. 53: p. 2378–2387.
• 29. Wolfgang Theissen, E. Julius, R. Franz, Method and Apparatus for the Detection of Slag Co-Flowing Within a Stream of Molten Metal, 1989.
• 30. Tan D.P., L. Zhang, A. Bin, A WP-based nonlinear vibration sensing method for invisible liquid steel slag detection. Sensors and Actuators, B: Chemical, 2014. 202: p. 1257–1269.
• 31. Yang J., I. Tian, A. Fei, A New Vibratıon Ladle Slag Detectıon System, 2014. 285–291.
• 32. Kato H., M. Yamasita, New Automation and Control Technology of Slab Caster. IFAC Proceedings,1987. 20: p. 253–258.
• 33. Piccinini A., V.P. Campagnoni, S. Ierace, F. Floreani, A vibrational approach to Slag Sensing System: development and industrial application. IFAC-PapersOnLine, 2016. 49: 1412–1417.
• 34. ICP-accel1.jpg (655×464). [cited 2019 3 July]; Avaliable from: http://www.pcb.com/contentstore/mktgcontent/webimages/resources/techsupport/ICP-accel1.jpg.
• 35. Wenfang G., Formation and Prevention of Sliver Defects on the Surface of Cold-rolled Strip, 2012. 402: p. 221–226.
• 36. Zhang Q, J. Wang, Y. Zhang, G. Xu, Numerical simulation and manifold learning for the vibration of molten steel draining from a ladle. Journal of Vibroengineering, 2013. 15: p. 549–557.
• 37. Yang Z, Y. Wang, J. Rao, Z. Peng, Control and optimizing of unstable state in continuous casting process with automatic system. Advanced Materials Research, 2012. 472–475: p. 3057–3062.