Журналы →  Chernye Metally →  2022 →  №3 →  Назад

Agglomeration and Production of Cast Iron
Название Simulation model for the selection of technological parameters to obtain a sinter with high consumer properties based on the committee method
DOI 10.17580/chm.2022.03.02
Автор P. F. Chernavin, A. V. Malygin, T. V. Detkova, V. Yu. Kuchin
Информация об авторе

Ural Federal University named after the first President of Russia B.N. Yeltsin, Ekaterinburg, Russia:

P. F. Chernavin, Cand. Econ., Associate Professor, Dept. of Big Data Analytics and Video Analysis Methods, e-email: chernavin.p.f@gmail.com

 

Ural Federal University named after the first President of Russia B.N. Yeltsin, Ekaterinburg, Russia1 ; Ferrox Ltd., Ekaterinburg, Russia2:
A. V. Malygin, Dr. Eng., Professor, Dept. of Metallurgy of Iron and Alloys1, Deputy Director2, e-mail: a.malygin@urfu.ru

 

PJSC Severstal, Moscow, Russia:
T. V. Detkova, Head of the Raw Materials Research Center3, e-mail: tvdetkova@severstal.com
V. Yu. Kuchin, Leading Expert (sinter production)3, e-mail: vyukuchin@severstal.com

Реферат

To control the quality characteristics of the agglomerate, a simulation model based on the committee method has been proposed. A generalized model of committee structures is presented in the form of a linear programming problem with partially integer variables. The model has been tested on real data. The minimum number of informative features is determined, in the space of which it is possible to construct a decision rule that separates agglomerate areas with high consumer characteristics from areas with satisfactory quality indicators. A high-quality agglomerate had to simultaneously meet the specified limits in terms of yield and strength. As a result of the calculations, a decision rule was built in the form of a seniority committee of five members in the space of 43 features. Geometrically, this is a convex region obtained from a hyperparallelepiped when it is truncated by five hyperplanes. This decision rule can be easily programmed with simple tools and integrated into the sinter quality control system. The practical importance lies in reducing the yield of structural fines during the destruction of the sinter cake, i.e., increasing the yield of a suitable agglomerate while keeping the technological parameters within the convex region.
Contributors to the preparation of the article: A. A. Eliseev, Raw Material Research Manager of PJSC Severstal, aaeliseev@severstal.com, Yu. A. Malygin, Director of Ferrox Ltd., y.malygin@ferrox.org,
N. P. Chernavin, Assistant of the Dept. of Big Data Analytics and Video Analysis Methods of Ural Federal University, ch_k@mail.ru, F. P. Chernavin, Cand. Econ., Associate Professor of the Dept. of Controlled Systems Modeling of Ural Federal University, chernavin_fedor@mail.ru.

Ключевые слова Charge, sintering parameters, sinter cake, destruction, yield of structural fines, sinter strength, committee method, mathematical programming, decision rule, sinter quality improvement
Библиографический список

1. Nechkin G. А., Chernavin D. А., Isaenko G. Е. Optimization of the blast-furnace charge according to the complex of metallurgical properties. Chernaya metallurgiya. Byulleten nauchnotekhnicheskoy i ekonomicheskoy informatsii. 2019. Vol. 75. No. 11. pp. 1244–1250.
2. Ryabchikov М. Yu., Grebennikova V. V, Ryabchikova Е. S. Management of the formation of the ore base of a metallurgical enterprise based on integration of models of the blast-furnace process and the sinter destruction. Zhurnal Sibirskogo federalnogo universiteta. Tekhnika i tekhnologii. 2018. No. 11 (2). pp. 168–180.
3. Frolov Yu. А., Filatov S. V., Kaplun L. I., Semenov О. А. Influence of the component composition and height of the charge layer on the quality of the sinter, fuel consumption and productivity of sintering machines of PJSC NLMK. Metallurg. 2020. No. 4. pp. 21–29.
4. Shapovalov А. N. Improvement of the quality of the sinter in the conditions of JSC Ural Steel. Tekhnologii metallurgii, mashinostroeniya i materialoobrabotki. 2017. No. 16. pp. 10–20.
5. Johnson N. S., Vulimiri P. S., To A. C., Brice C. A. Invited review: Machine learning for materials developments in metals additive manufacturing. Additive Manufacturing. 2020. Vol. 36. pp. 1–30.
6. Jian-Liang Zh. Effects of MgO on the sintering liquid, the properties and mineralogical morphology of the high-basity sinter. 7 European Coke and Ironmaking Congress (ECIC 2016), Linz, 12–14 Sept., 2016. Proceedings. Leoben. 2016. p. 122.
7. Zhang B., Zi J., Li M. Prediction of sinter yield and strength in iron sintering process by numerical simulation. Applied Thermal Engineering. 2018. Vol. 131. pp. 70–79.
8. Webster N., Pownceby M., Ware N., Pattel R. Predicting iron ore sinter strength through partial least square regression (PLSR) analysis of X-ray diffraction patterns. Powder diffraction. 2017. Vol. 32. pp. 66–69.
9. Kumar V., Sairam D., Kumar S., Singh A. Prediction of Iron Ore Sinter Properties Using Statistical Technique. Transaction of the Indian Institute of Metals. 2017. Vol. 70(6). pp. 6–17.
10. Wang Y., Zhang J., Zhang Y., Liu D., Liu Y. Characteristics of combustion zone and evolution of mineral phases along bed height in ore sintering. International Journal of Minerals, Metallurgy and Materials. 2017. Vol. 24. pp. 1087–1095.
11. Ershov Е. V., Vinogradova L. N., Bogachev D. V., Petrukhina О. S. System for forecasting the quality of products of metallurgical production. Izvestiya vuzov. Priborostroenie. 2015. Vol. 58. No. 2. pp. 123–127.
12. Malygin А. V., Maltsev V. А., Viduetskiy М. G. Ore preparation processes in smelting production. Ekaterinburg: OOO AMK «Den RA», 2016. 415 p.
13. Malygin А. V., Shumakov N. S. Dynamics of destruction of sinter cakes during mechanical processing. Izvestiya vuzov. Chernaya metallurgiya. 1997. No. 9. pp. 9–12.
14. Mazurov V. D., Polyakova Е. Yu. Existential questions of committee constructions. Part II. Vestnik Yuzhno-Uralskogo gosudarstvennogo universiteta. Seriya «Kompyuternye tekhnologii, upravlenie, radioelektronika». 2019. Vol. 19. No. 1. pp. 114–120.
15. Chernavin N. P. Forecasting exchange rate volatility using the committee method. Vestnik Chelyabinskogo gosudarstvennogo universiteta. 2019. No. 11(433). Ekonomicheskie nauki. Iss. 67. pp. 82–94.

Language of full-text русский
Полный текст статьи Получить
Назад