Improvement of the cold rolling mill diagnostic system based on the data base of its electromechanical processes
DOI:
https://doi.org/10.15588/1607-6761-2023-1-1Keywords:
diagnostics, database, electromechanical processes, cold rolling mill, fuzzy logic, transient process, modelingAbstract
Purpose. To improve the diagnostic system of the cold rolling mill based on the database of its electromechanical processes, by developing a fuzzy decision-making system as to the condition of the rolling mill electrical drives, which will increase the efficiency of the existing diagnostic system.
Methodology. Mathematical and computer modeling.
Findings.A fuzzy decision-making system about the state of two interconnected electric drives of the unwinding mechanism and the rolling mill has been developed to investigate and prevent the pre-emergency state associated with the break of the rolling metal strip. The specified decision-making system is built on the basis of a database of electromechanical processes of electric drives of the skin-threat single-celled state of cold rolling of the cold rolling shop No. 1 of PJSC "Zaporizhstal". At the input of this system, the voltage of the armature circuit of the unwinding mechanism motor, the armature circuit current of the unwinding mechanism motor, the tension of the rolled metal strip in the area between the unwinder and the rolling cage are set. At the output, the general state of the system is obtained, which depends on the values of the input data. Information on the value of the tensile strength of the rolled metal strip can be obtained on the basis of the pressure data and voltage sensors, which are installed on industrial equipment. Information about the value of the tension force of the rolled metal strip can be obtained both by installing additional measuring devices and indirectly, using mathematical models of the roll current radius and the linear speed of the rolled metal strip.
Originality. The system for diagnosing the condition of cold rolling has been improved by introducing a fuzzy decision-making system into its composition based on a database of electromechanical processes of the electric drives of the unwinding mechanism and the cage, which will allow to prevent an emergency condition caused by a break in the rolled metal strip.
Practical value. Prevention of breaking of the rolled metal strip on the basis of an improved system for diagnosing the state of cold rolling, which uses information from the database of its electromechanical processes in order to improve the efficiency of the product quality management process. Using complete organized information and experience of operating a cold rolling mill, you can form technical and technological solutions for the modernization of existing and development of new technological equipment and systems for automatic control of electric drives of rolling mills.
References
Hrabovskyi, H.H., Iievliev M.H., Moiseienko S.Ie. (2021). Systemy kontroliu ta diahnostyky v intehrovanykh ASU tovstolystovymy stanamy [Control and diagnostic systems in integrated ACS by thick-sheet mills]. Mathematical machines and systems, 4, 58-69. DOI: 10.34121/1028-9763-2021-4-58-69 (in Ukrainian)
Meshchaninov, S.K., Sai, O.V., Bahrii, V.V., Voloshyn, R.V. (2020). Diahnostyka avtomatyzovanykh system prokatnykh staniv z vykorystanniam neironnoi merezhi [Diagnostics of automated systems of rolling mills using a neural network]. Mathematical modeling, 1(42), 78-84. (in Ukrainian)
Bahlai, A.V. (2017). Vybratsyonnoe obsledovanye stana 1150 [Vibration inspection of mill 1150]. Technical diagnostics and non-destructive testing, 1, 54–57. https://doi.org/10.15407/tdnk2017.01.09 (in Russin)
Shushura, O. M. (2018). Metodolohichni osnovy pobudovy informatsiinykh tekhnolohii dlia avtomatyzatsii upravlinnia skladnymy systemamy na pryntsypakh nechitkoi lohiky [Methodological foundations of the construction of information tech-nologies for the automation of management of complex systems based on the principles of fuzzy logic] : dys. dokt. tekhn. nauk : 05.13.06 : zakhyshchena 11.03.18 : утв. 24.09.18 / Shushura Oleksii Mykolaiovych. - Kyiv, 322. (in Ukrainian)
Kyryk, V.V. (2019).Matematychnyi aparat shtuchno-ho intelektu v elektroenerhetychnykh systemakh: pidruchnyk [Mathematical apparatus of artificial in-telligence in electric power systems]. К. Politekhnika, 224. (in Ukrainian)
Krot, P.V., Verenov, V.V. (2009). Metody i tekhnichni zasoby avtomatyzovanoho monitorynhu dynam-ichnykh navantazhen ta diahnostyky znosu linii pryvodu prokatnykh staniv [Methods and technical means of automated monitoring of dynamic loads and diagnostics of wear of rolling mill drive lines]. Zb. statei proektiv za prohramoiu «RESURS» NAN Ukrainy, 123-129. (in Ukrainian)
Yue, W., Shengfeng, G., Lin, S. (2010). The Design and Application of Distributed Mill's Monitoring and Di-agnostic System Base on LabVIEW. Electrical and Control Engineering, International Conference. Wu-han, China, 2295-2298. doi: 10.1109/iCECE.2010.566
Liang, S. (2011). Research and Application of Moni-toring System for High-speed Wire Running. Sixth In-ternational Conference on Measuring Technology and Mechatronics Automation. Shangshai, China, 1019-1022. doi: 10.1109/ICMTMA.2011.536
Puchr, I., Herout, P. (2017). Probabilistic advisory sys-tem for operators can help with diagnostics of rolling mills. 21st International Conference on Process Con-trol (PC), 132-136. doi: 10.1109/PC.2017.7976202.
Rito, G. Di, Schettini, F., Galatolo, R. (2018). Model-Based Prognostic Health-Management Algorithms for the Freeplay Identification in Electromechanical Flight Control Actuators. 5th IEEE International Workshop on Metrology for AeroSpace (MetroAero-Space), Rome, Italy, 340-345, doi: 10.1109/MetroAeroSpace.2018.8453552.
Baldo, L., Bertone, M., Dalla, M. D. L. (2022). Ve-dova and P. Maggiore, "High-Fidelity Digital-Twin Validation and Creation of an Experimental Data-base for Electromechanical Actuators Inclusive of Failures. 6th International Conference on System Re-liability and Safety (ICSRS), Venice, Italy, 19-25, doi: 10.1109/ICSRS56243.2022.10067403.
Rednikov, S. N., Akhmedyanova, E. N., Za-kirov D. M. (2018). Experience in Using Combined Diagnostic Systems for Assessing State of Metallurgi-cal Equipment. Global Smart Industry Conference (GloSIC), 1-6. doi: 10.1109/GloSIC.2018.8570148.
Karandaev, A. S., Mugalimov, R. G., Petushkov, M. Y., Lukyanov, S. I., Sarvarov, A. S. (2019). Design of Smart Technical Condition Analysis Systems for Electric Equipment of an Iron-and-Steel. Interna-tional Ural Conference on Electrical Power Engineer-ing (UralCon), 448-453. doi: 10.1109/URALCON.2019.8877612.
Orcajo, G. A. (2016). Dynamic Estimation of Electri-cal Demand in Hot Rolling Mills. IEEE Transactions on Industry Applications, 52, 3, 2714-2723. doi: 10.1109/TIA.2016.2533483.
Nazarova, O. S. (2013). K voprosu razrabotky sys-tem dyahnostyrovanyia эlektromekhanycheskykh system stanov kholodnoi prokatky [On the issue of developing systems for diagnosing electromechanical systems of cold rolling mills]. Electrical engineering and power engineering, 1, 36-41. DOI: https://doi.org/10.15588/1607-6761-2013-1-6
Sadovoi, O., Nazarova, O., Bondarenko, V., Pirozhok A., Hutsol, Т., Nurek, T., Glowacki, Sz. (2020). Mod-eling and research of electromechanical systems of cold rolling mills. Krakow, Traicon, 138.
Nazarova, O. S., Vasyliev, B. V. (2022). Nechitka lohika v systemi monitorynhu ta diahnostyky el-ektromekhanichnykh protsesiv stanu kholodnoi pro-katky [Fuzzy logic in the system for monitoring and diagnosing electromechanical processes of the cold rolling state. Abstracts of the All-Ukrainian scientific and practical conference of young scientists and stu-dents on Information technologies in education, technology and industry, 151-152. (in Ukrainian)
Nazarova, O. S., Vasyliev, B.V., Punda, M.S. (2022). Monitoring of electromechanical processes of the cold rolling mill taking into account the variation of the inertia moment. International scientific confer-ence on Interaction between science and technology in modern conditions, Riga, Latvia, 50-4. https://doi.org/10.30525/978-9934-26-264-7-12
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Olena Nazarova, Bohdan Vasyliev, Danylo Shokurov
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Creative Commons Licensing Notifications in the Copyright Notices
Authors who publish with this journal agree to the following terms:
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under aCreative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.