Information Processing Algorithms in the Steel-Teeming Ladles Tracking System in Steelmaking

Purpose of research. The purpose of research is to increase the efficiency of control over the movement of steel ladles in steelmaking, through the development of mathematical and software.

Methods. The control of the movement of steel-pouring ladles can be divided into 2 parts: the first is the object detection in the image from a camera located on a certain section of the route, followed by determining the position of the object in the frame, and the second part is identification based on an array of data from different systems. Methods used in research are: mathematical modeling, neural networks, the basics of the theory of algorithms construction, as well as software and hardware of modern computer technologies. The article describes a model for the routes generation for the movement of steel ladles, on the basis of which the control of the movement of steel ladles is carried out. Algorithmic support is a combination of such algorithms as: an algorithm for generating possible routes for moving steel ladles, an algorithm for determining the position of a steel ladle on a route for moving steel ladles, an algorithm for identifying a steel ladle and a generalized algorithm for processing information. The structuralfunctional organization of the tracking system for steel-pouring ladles in steel-smelting production is given.

Results. Experimental verification of algorithmic support was carried out on a test data set, which was formed from real technological data. Adaptation and tuning of the algorithms and software will make it possible to apply this software system in steelmaking plants with a different composition of plant units.

Conclusion. Control over the movement of steel ladles allows build the process so that the movement of liquid steel will cause minimal heat loss. The need to heat steel in secondary processing units is correlates with energy costs. Thus, reducing heat loss and downtime of steel ladles will reduce energy costs for the entire process.

1. Glebova E.S., Blinnikov A.A., Bystrov S.V. [Cascade coding application for the solving of steel-pouring ladle marking problem]. Problemy i dostizheniya v nauke i tekhnike. Sbornik nauchnykh trudov po itogam mezhdunarodnoi nauchno-prakticheskoi konferentsii [Problems and achievements in science and technology. Collection of scientific papers based on the results of an international scientific and practical conference]. Omsk, 2016, no. 3, pp. 41-44 (In Russ.).

2. Atanov A.V., Krylovetskii A.A., Kurgalin S. D., Protasov S.I. Prostranstvennaya rekonstruktsiya v sistemakh komp'yuternogo zreniya na osnove web-kamer [Spatial reconstruction in computer vision systems based on webcams]. Vestnik Voronezhskogo gosudarstvennogo universiteta. Ser. Sistemnyi analiz i informatsionnye tekhnologii = Proceedings of Voronezh State University. Series. System Analysis and Information Technology, 2011, no. 2, pp. 149-153.

3. Loktev D.A., Alfimtsev A.N., Loktev A.A. Modelirovanie kompleksnoi sistemy videomonitoringa vnutri zdaniya. Chast' 1. Algoritm razmeshcheniya videokamer i ego programmnaya realizatsiya [Simulation of an integrated video monitoring system inside a building. Part 1. Algorithm for placing video cameras and its software implementation]. Vestnik MGSU = Bulletin of MGSU, 2012, no. 5, pp. 84-92.

4. Loktev D.A., Alfimtsev A.N., Loktev A.A. Modelirovanie kompleksnoi sistemy videomonitoringa vnutri zdaniya. Chast' 2. Algoritm raspoznavaniya ob"ektov [Simulation of an integrated video monitoring system inside a building. Part 2. Object recognition algorithm]. Vestnik MGSU = Bulletin of MGSU, 2012, no.5, 2012, pp. 124-131.

5. Petrichkovich Ya. Ya., Somikov V. P., Yudintsev V.A. Analiziruem sistemy videoanalitiki. Chast' 2. "Sistemy bezopasnosti" [Video analytics systems analyze. Part 2. "Security systems "]. 2009, no. 3. Available at: http://lib.secuteck.ru/articles2/ip-security/ analiziruem-sistemy-videoanalitiki

6. Gordon D., Kembhavi A., Rastegari M., Redmon J., D Fox., Farhadi A., IQA: Visual Question Answering in Interactive Environments. (2018)

7. Eremenko V.T., Tyutyakin A.V., Kondrashin A. A. Metodologicheskie aspekty obrabotki izobrazhenii v avtomatizirovannykh sistemakh diagnostiki [Methodological aspects of image processing in automated diagnostic systems]. Informatsionnye sistemy i tekhnologii = Information Systems and Technologies, 2011, no.2(64), pp. 19-26.

8. Stat'ya ot kompanii Axis – lidera na rynke setevogo video, o problemakh raspoznavaniya i identifikatsii na izobrazheniyakh [An article from Axis, a leader in the network video market, about the problems of recognition and identification in images]. Available at: https:// www.axis.com/ru-ru/learning/web-articles/identification-and-recognition/resolution

9. Angella F., L Reithler., Gallesio F. Optimal Deployment of Cameras for Video Surveillance Systems [Optimal Deployment of Cameras for Video Surveillance Systems]. IEEE Conf. on Advanced Video and Signal Based Surveillance, 2007.

10. Simon J. D. Prince Computer Vision: Models, Learning, and Inference. Cambridge University Press, 2012. 598 p.

11. Tsai Y.M. et al. An intelligent vision-based vehicle detection and tracking system for automotive applications. Proceedings of the IEEE International Conference on Consumer Electronics, 2011, pp. 113-114.

12. Alpatov B.A., Balashov O.E., Shubin N.Yu. Algoritm izmereniya koordinat dvizhushchikhsya ob"ektov v posledovatel'nosti izobrazhenii [Moving objects coordinate measuring on a sequence of images algorithm]. Vestnik Ryazanskogo gosudarstvennogo radiotekhnicheskogo universiteta = Vestnik of Ryazan State Radio Engineering University. 2010, is. 34, pp. 32-36.

13. Provotorov A. V., Orlov A. A., Astaf'ev A. V. [System analysis of technologies and systems for pipeline products identification by marker in industrial production]. Materialy VIII nauchno-prakticheskoi konferentsii «Tatishchevskie chteniya: aktual'nye problemy nauki i praktiki» [Materialy VIII nauchno-prakticheskoi konferentsii "Tatishchev Readings: Actual Problems of Science and Practice"]. Tolyatti, 2011, pp. 187-195 (In Russ.).

14. Alpatov B.A., Babayan P.V., Shubin N.Yu. Algoritm otsenki koordinat ob"ektov na osnove preobrazovaniya Radona [Object coordinates estimation algorithm based on Radon Transform]. Tsifrovaya obrabotka signalov = Digital Signal Processing, 2011, no.3, pp. 17-20.

15. Volkhonskii G.V. Kriterii vybora razreshayushchei sposobnosti v sistemakh telenablyudeniya [Resolution choosing in television survelliance systems criteria]. PROSystem CCTV, 2009, no. 2 (38), pp. 60 - 64.

16. Trofimenko Ya.M. [Mathematical support of the tracking system for steel ladles in steelmaking]. Intellektual'no-informatsionnye tekhnologii i intellektual'nyi biznes (INFOS2021). Materialy dvenadtsatoi zaochnoi mezhdunarodnoi nauchno-tekhnicheskoi konferentsii [Intelligent information technologies and intellectual business (INFOS-2021). Materials of the twelfth correspondence international scientific and technical conference]. Vologda, 2021, pp. 169-173 (In Russ.).

17. Yakushev A.M. Proektirovanie staleplavil'nykh i domennykh tsekhov [Design of steelmaking plants and blast-furnace plants]. Moscow, Metallurgy Publ., 1984, 216 p

18. Videonablyudenie po IP [IP video surveillance]. Zhurnal setevykh reshenii/LAN = Network solutions magazine/LAN, 2010, № 04. Available at: https:// www.osp.ru/lan/2010 /04/13002109/

19. Zaitsev E. M., Kolomiets E. A., Nikolaev V. N. Formalization of Life Cycle Stages of Geographic Information Products Creation at Research and Production Enterprises. Izvestiya Yugo-Zapadnogo gosudarstvennogo universiteta = Proceedings of the Southwest State University. 2020; 24(4): 146-165 (In Russ.). https://doi.org/10.21869/2223-1560-2020- 24-4-146-165.