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Abstract

The purpose of the study is to increase the information reliability on the state of territories, buildings and structures at hazardous production facilities of a metallurgical enterprise, obtained using an unmanned aerial vehicle. The object of the study is the system of production control over the state of the territory, buildings and structures at hazardous production facilities of a metallurgical enterprise.The subject of the research is a technique for automated collection and processing of information based on computer methods of information processing. The study is carried out as part of research and development work at one of the leading ferrous metallurgy enterprises of the Russian Federation.The following methods were used in the study: analysis and synthesis for adequate decomposition of the study object into its constituent parts - elements, establishing links between them and the subject of study; decomposition to isolate constituent subtasks from the object and subject of research, to create chains of sequences of actions on selected subtasks; the experiment to study the features of natural conditions for collecting information.The result of the study are the developed methods: collection of information on the technical condition of the territory, buildings and structures at hazardous production facilities of a metallurgical enterprise; processing visual information about the technical condition of the territory, buildings and structures at hazardous production facilities of a metallurgical enterprise.The results of the study are the basis for creating an automated system for monitoring the state of the territory, buildings and structures at hazardous production facilities of a metallurgical enterprise, the use of which will ensure in real time and on an ongoing basis: the receipt of information on the current parameters of the safe operation of the facility into the industrial safety management system control; signaling personnel about the slightest quantitative changes in previously identified defects and damage, as well as the appearance of new ones; operational and, consequently, effective targeted response of enterprise services to signals from the monitoring system.

Keywords

System of intellectual support in making managerial decisions; machine vision; remote control; Industrial Safety; hazardous production facilities; territory, buildings and structures; examination of the technical condition; applied digital platform; expert system; image processing methods; unmanned aerial vehicle.

Vladimir D. Kornienko

Postgraduate student, Leading engineer in the field of industrial safety expertise, The Institute of Energy and Computing Systems, the Department of Computer Science and Programming, The Research Institute "Prombezopasnost", Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia, This email address is being protected from spambots. You need JavaScript enabled to view it., https://orcid.org/0000-0002-0637-5765

Mikhail Yu. Narkevich

Ph.D. (Engineering), Associate Professor, Head of the Department, the Department of Design and Construction of Buildings, Director of the Research Institute "Prombezopasnost", Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia, This email address is being protected from spambots. You need JavaScript enabled to view it., https://orcid.org/0000-0001-6608-8293

Oksana S. Logunova

D.Sc. (Engineering), Professor, Director of the Institute of Construction, Architecture and Art, Head of the Department of Computer Science and Programming, Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia, This email address is being protected from spambots. You need JavaScript enabled to view it., https://orcid.org/0000-0002-7006-8639

Anna E. Kozlova

Master’s Degree Student, the Institute of Energy and Computing Systems, the Department of Computer Science and Programming, Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia, This email address is being protected from spambots. You need JavaScript enabled to view it., https://orcid.org/0000-0002-3109-2185

Ivan P. Zaytsev

Master’s Degree Student, Engineer, the Institute of Construction, Architecture and Art, the Department of Urban Studies and Engineering Systems, the Research Institute "Prombezopasnost", Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia, This email address is being protected from spambots. You need JavaScript enabled to view it., https://orcid.org/0000-0002-6851-6017

1. Order of Rostekhnadzor dated November 30, 2020 no. 471. Requirements for registration of objects in the state register of hazardous production facilities and maintenance of the state register of hazardous production facilities, forms of a certificate of registration of hazardous production facilities in the state register of hazardous production facilities. Moscow, MINYUST Publ., 2020. 157 p. (In Russian)

2. Federalnaya sluzhba po ekologicheskomu, tekhnologicheskomu i atomnomu nadzoru [Federal Service for Ecological, Technological and Nuclear Supervision]. Available at: http://www.gosnadzor.ru/public/ (accessed 04 November 2022).

3. Veselov A. V., Kornienko V.D. A new promising design of pavement with a monolithic ribbed cement concrete pavement. Stroitelnye materialy, oborudovanie, tekhnologii XXI veka [Building materials, equipment, technologies of the XXI century], 2018, no. 5-6 (232-233), pp. 38-41. (In Russian)

4. GOST 31937-2011.Buildings and constructions. Rules of inspection and monitoring of the technical condition. Moscow, STANDARTINFORM Publ., 2014. 55 p. (In Russian)

5. NarkevichM.Yu. Osnovy metrologii, standartizatsii, sertifikatsii i kontrolya kachestva [Basics of metrology, standardization, certification and quality control]. Magnitogorsk, Nosov Magnitogorsk State Technical University Publ., 2012. 136 p. (In Russian)

6. Veprzhitskiy I. Yu., Rytik N. A., Kustikova Yu. O. Operational control of buildings and structures. Molodezhnye innovatsii: Sbornik materialov seminara molodykh uchenykh XXII Mezhdunarodnoy nauchnoy konferentsii [Collection of materials of the seminar of young scientists of the XXII International scientific conference "Youth innovations"]. Tashkent, 2019. Moscow: National Research Moscow State University of Civil Engineering Publ., 2019, pp. 210-213. (In Russian)

7. Panfilov A.V., Bakhteev O.A., Deryushev V.V., Korotkiy A.A. A system of adaptive remote monitoring and control of the operation of hazardous facilities based on a risk-based approach. Bezopasnost tekhnogennykh i prirodnykh system [Safety of technogenic and natural systems], 2020, no. 2, pp. 19-29. (In Russian). doi: 10.23947/2541-9129-2020-2-19-29

8. Panova E.A., Albrekht A.Ya. Refined specific electrical parameters of double-circuit power lines 110 kV for remote location of damage. Elektrotekhnicheskie sistemy i kompleksy [Electrotechnical systems and complexes], 2016, no. 4(33), pp. 35-40. (In Russian). doi: 10.18503/2311-8318-2016-4(33)-35-40

9. Decree of the Government of the Russian Federation dated December 31, 2020 no. 2415 "On conducting an experiment to introduce an industrial safety remote control system". URL: https://docs.cntd.ru/document/573319188 (accessed 02 November 2022).

10. O vnedrenii system distantsionnogo kontrolya v ramkakh realizatsii reform kontrolno-nadzornoy deyatelnosti. [On the introduction of remote control systems as part of the implementation of the reform of control and supervisory activities]. Available at: http://government.ru/news/38172/ (accessed 02 November 2022).

11. Biznes ne vidit smysla v eksperimente Rostekhnadzora po vnedrenii sistemy distantsionnogo kontrolya na OPO. [Business does not see the point in Rostechnadzor's experiment on the introduction of a remote control system at the OPO]. Available at: https://finance.rambler.ru/economics/48755960/?utm_content=finance_media&utm_medium=read_more&utm_source=copylink (accessed 02 November 2022).

12. Zaurin R., Catbas F. N. Integration of computer imaging and sensor data for 912 structural health monitoring of bridges. Smart Mater. Struct. 2010, vol. 19(1). 015019. doi: 10.1088/0964-1726/19/1/015019

13. Duran O., Althoefer K., Seneviratne L. State of the art in sensor technologies for sewer inspection. IEEE Senors Journal. 2002, vol. 2(2), pp. 73-81. doi: 10.1109/JSEN.2002.1000245

14. Guo W., Soibelman L., Garrett J.H. Automated defect detection for sewer pipeline inspection and condition assessment. Automation in Construction. 2009, vol. 18(5), pp. 87-596. doi: 10.1016/j.autcon.2008.12.003

15. Duran O., Althoefer K., Senevatne L.D. Automated pipe defect detection and categorization using camera/laser-based profiler and artificial neural network. IEEE 1063 Transactions on Automation Science and Engineering. 2007, vol. 4(1), pp. 118-126. doi: 10.1109/TASE.2006.873225

16. Yang M.-D., Su T.-C. Automated diagnosis of sewer pipe defects based on machine learning approaches. Expert Systems with Applications. 2008, vol. 35(3), pp. 1327-1337. doi: 10.1016/j.eswa.2007.08.013

17. Favorskaya M.N., Nishchkhal N. Verification of oil spills on water surfaces from aerial photographs based on deep learning methods. Informatika i avtomatizatsiya [Computer Science and automation], 2022, vol. 21, no. 3, pp. 937-962. (In Russian). doi: 10.15622/ia.21.5.4

18. Belozerskiy L.A., Oreshkina L.V. Automation of histogram processing and analysis in space image recognition tasks. Issledovanie Zemli iz kosmosa [Exploration of the Earth from space], 2009, no. 3, pp. 47-54. (In Russian)

19. Remondino, F., Barazzetti, L., Nex, F., Scaioni, M., Sarazzi, D. (2011). UAV photogrammetry for mapping and 3D modeling – Current Status and Future Perspectives. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2011. no. XXXVIII-1/C22, pp. 25–31. doi: 10.5194/isprsarchives-XXXVIII-1-C22-25-201

20. Aber J.S., Marzolff I., Ries J.B. Small-Format Aerial Photography: Principles, Techniques and Geoscience Applications. Elsevier, 2010. 266 p.

21. Siebert S., Teizer J. Mobile 3D mapping for surveying earthwork projects using an Unmanned Aerial Vehicle (UAV) system. Automation in Construction. 2014, vol. 41, pp. 1-14. doi: 10.1016/j.autcon.2014.01.004

22. Tziavou O., Pytharouli S., Souter J. Unmanned Aerial Vehicle (UAV) based mapping in engineering geological surveys: Considerations for optimum results. Engineering Geology. 2018, vol. 232(9), pp. 12-21.doi: 10.1016/j.enggeo.2017.11.004

23. Jordan S., Moore J., Hovet S., Box J., Perry J., Kirsche K., Lewis D., Tse Z.T.H. State-of-the-art technologies for UAV inspections. IET Radar, Sonar & Navigation. 2017, vol. 12(2), pp. 151-164. doi: 10.1049/iet-rsn.2017.0251

24. Alejo D., Cobano J.A., Heredia G., Martínez-de Dios J.R., Ollero A. Efficient trajectory planning for WSN data collection with multiple UAVs. Cooperative Robots and Sensor Networks 2015. Studies in Computational Intelligence. Vol. 604. Springer, Cham., 2015, pp. 53-75. doi: 10.1007/978-3-319-18299-5_3

25. Tokekar P., Vander Hook J., Mulla D., Isler V. Sensor planning for a symbiotic UAV and UGV system for precision agriculture. IEEE Transactions on Robotics. 2016, vol. 32, pp. 1498-1511.doi: 10.1109/TRO.2016.2603528

26. Augugliaro F., Lupashin S., Hamer M., Male C., Hehn M., Mueller M.W., Willmann J.S., Gramazio F., Kohler M., D’Andrea R. The Flight Assembled Architecture installation: Cooperative construction with flying machines, 2014, vol. 34(4), pp. 46-64. doi: 10.1109/MCS.2014.2320359

27. LLS "ASKON-Biznes-resheniya". System for collecting and analyzing information on product quality 8D. Quality management (8D. Quality management). Computer program RF, no. 2019660078, 2019. (In Russian)

28. Lobantsev A.А., Gusarova N.F., Vatian А.S., Kapitonov А.А., Shalyto А.А. Comparative assessment of text-image fusion models for medical diagnostics. Information and Control Systems. 2020, no. 5(108), pp. 70-79. doi: 10.31799/1684-8853-2020-5-70-79

29. Sergeev D.I., Andreev A.E., Drobintseva A.O., Cenevska S., Kukavitsa N., Drobintsev P.D. Development of automated computer vision methods for cell counting and endometrial gland detection for medical images processing. Proceedings of the Institute for System Programming of the RAS. 2020, vol. 32(3), pp. 119-130. doi: 10.15514/ISPRAS-2020-32(3)-11

30. Alexandrov D. V. Overview of Face Recognition Algorithms for Person Identification. Programmnaya Ingeneria. 2022, vol. 13(7), pp. 331-343. doi: 10.17587/prin.13.331-343

31. Kozlov D.A., Karnaukhov D.D. Process of recognition and comparison of fingerprints. Vestnik molodykh uchenykh i spetsialistov Samarskogo universiteta [Bulletin of young scientists and specialists of the Samara University], 2018, no. 2(13), pp. 61-71. (In Russian)

32. Posokhov I.A. Visualization and processing of information about the quality of continuously cast billet. Elektrotekhnicheskie sistemy i kompleksy [Electrotechnical systems and complexes], 2016, no. 2(31), pp. 35-43. (In Russian). doi: 10.18503/2311-8318-2016-2(31)-35-43

33. NarkevichM. Yu., Logunova O.S., Arkulis M.B. An applied digital platform for assessing the quality dynamics of hazardous production facilities at a metallurgical enterprise: structure and algorithms. Vestnik Cherepovetskogo gosudarstvennogo universiteta. [Bulletin of Cherepovets State University], 2022, no. 5, pp. 29-48. (In Russian). doi:10.23859/1994-0637-2022-5-110-3

34. Narkevich M.Yu., Kornienko V.D., Polyakova M.A. Visual control as a basis for the development of automated systems for remote control and assessment of the quality of buildings and structures at hazardous production facilities. Izvestiya Tulskogo gosudarstvennogo universiteta. Tekhnicheskie nauki [Bulletin of the Tula State University. Technical science], 2021, no. 5, pp. 570-576. (In Russian). doi: 10.24412/2071-6168-2021-5-570-576

35. Narkevich M.Yu., Logunova O.S., Kornienko V.D., Nikolaev A.A., Tyulyumov A.N., Zlydarev N.V., Deryabin D.I. Monitoring the condition of buildings and structures using unmanned aerial vehicles: results of a pilot experiment. Sbornik trudov Vserossiyskoy nauchno-prakticheskoy konferentsii «Programmnoe obespechenie dlya tsifrovizatsii predpriyatiy i organizatsiy» [Proceedings of the All-Russian Scientific and Practical Conference "Software for digitalization of enterprises and organizations"]. Magnitogorsk, NMSTU Publ., 2021, pp. 33-37. (In Russian)

36. NarkevichM.Yu., Logunova O.S., Kornienko V.D., Kalitaev A.N., Egorova L.G., Nikolaev A.A., Tyulyumov A.N., Zlydarev N.V., Deryabin D.I. Razrabotka i primenenie metodik kontrolya territorii, zdaniy i sooruzheniy PAO “MMK” s ispolzovaniem bespilotnykh vozdushnykh sudov (BVS) [Development and application of methods for monitoring the territory, buildings and structures of PJSC MMK using unmanned aerial vehicles (UAVs)]. Stage No. 01: R&D report (interim). Magnitogorsk: Nosov Magnitogorsk State Technical University, 2021. 274 p. (In Russian)

37. NarkevichM.Yu., Logunova O.S., Kornienko V.D., Sagadatov A.I., Kalitaev A.N., Egorova L.G., Nikolaev A.A., Tyulyumov A.N., Zlydarev N.V., Deryabin D.I., Kozlova A.E., Chernyshova A.S., Gavrilov K.V. Razrabotka i primenenie metodik kontrolya territorii, zdaniy i sooruzheniy PAO “MMK” s ispolzovaniem bespilotnykh vozdushnykh sudov (BVS) [Development and application of methods for monitoring the territory, buildings and structures of PJSC MMK using unmanned aerial vehicles (UAVs)]. Stage No. 02: R & D report (interim). Magnitogorsk: Nosov Magnitogorsk State Technical University, 2021. 124 p. (In Russian)

38. Narkevich M.Yu., Kornienko V.D., Nikolaev A.A., Zlydarev N.V., Logunova O.S., Tyulyumov A.N. Automatic detection of damage parameters from digital images. Computer program RF, no. 2021665102, 2021.

39. Gonsales R., Vuds R. Tsifrovaya obrabotka izobrazheniy [Digital image processing], Moscow, Tekhnosfera Publ., 2005. 172 p. (In Russian).

40. Shapiro L., Stokman Dzh. Kompyuternoe zrenie [Computer vision], Moscow, BINOM. Laboratoriya znaniy Publ., 2006. 752 p. (In Russian)

41. Logunova O.S., Nurov Kh.Kh. Structure and algorithms of software for automated quality assessment of continuously cast ingots. Avtomatizatsiya tekhnologicheskikh i proizvodstvennykh protsessov v metallurgii [Automation of technological and production processes in metallurgy], 2004, no. 1, pp. 168-174 (In Russian)

42. Logunova O.S., Nurov Kh.Kh., Pavlov V.V., Suspitsyn V.G. Organization of an automated workplace for assessing the quality of the macrostructure of continuously cast varietal blanks. Vestnik Magnitogorskogo gosudarstvennogo tekhnicheskogo universiteta im. G.I. Nosova [Bulletin of Magnitogorsk State Technical University named after G.I. Nosov], 2006, no. 3(15), pp.51-55. (In Russian)

Kornienko V.D., Narkevich M.Yu., Logunova O.S., Kozlova A.E., Zaytsev I.P. Methodology for Collecting and Processing Information to Monitor the State of the Territory, Buildings And Structures at Hazardous Production Facilities of a Metallurgical Enterprise. Elektrotekhnicheskie sistemy i kompleksy [Electrotechnical Systems and Complexes], 2022, no. 4(57), pp. 76-87. (In Russian). https://doi.org/10.18503/2311-8318-2022-4(57)-76-87