Науковий вісник НГУ

Automatic compensation of the mill roll eccentricity in terms of limited speed of hydraulic compression devices

• 
• 

User Rating:  / 0

PoorBest 

Details

Category: Content №1 2025

Last Updated on 25 February 2025

Published on 30 November -0001

Hits: 55

Authors:

O.Boyko, orcid.org/0000-0002-9714-2843, Dnipro University of Technology, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

V.Kuvaiev, orcid.org/0000-0001-6329-071X, Dnipro University of Technology, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

O.Potap*, orcid.org/0000-0001-8643-0228, Ukrainian State University of Science and Technology, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

M.Potap, orcid.org/0009-0000-1116-6020, Ukrainian State University of Science and Technology, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

M.Rybalchenko, orcid.org/0000-0001-5162-5201, Ukrainian State University of Science and Technology, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

повний текст / full article

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2025, (1): 082 - 089

https://doi.org/10.33271/nvngu/2025-1/082

Abstract:

Purpose. To reduce deviation of vertical dimension (thickness) of rolled products from the specified value by enhancing the accuracy and shortening the setup time of an eccentricity compensation subsystem of mill rolls based on substantiation of an eccentricity compensation method. This method is based on an active search algorithm to determine the actual eccentricity parameters in real time, taking into account the actual response time of hydraulic compression devices (HCD) and investigating its effectiveness through simulation computer modelling.

Methodology. The research was based on the analytical determination of the frequency characteristics of the AGC system in sheet metal rolling, considering the actual response time of HCD of a rolling mill as well as a comprehensive model of a rolling process in a quarto mill with rolling movement and an automatic thickness control system (ATCS) that compensates for eccentricity. The study was conducted by comparing the results of computer simulation modelling of the improved ATCS, whose algorithm took into account the HCD response time, with the performance indicators of the previous system, which did not consider this factor.

Findings. It has been established that under the AGC thickness control conditions, the measured amplitude of a variable component of thickness does not match the amplitude of eccentricity due to the finite response time of HCD. The frequency characteristics of the AGC system have been determined analytically, taking into account the actual response time of HPD in a rolling mill. An improved procedure for determining the actual eccentricity amplitude in real time has been substantiated, which involves a temporary reduction in the HCD speed within the initial rolling section. A structure for an automated control system has been proposed for practical implementation of this procedure. It has been demonstrated that the proposed solutions allow for a threefold reduction in thickness variations caused by eccentricity compared to the corresponding performance indicators of the known eccentricity compensation systems with the AGC thickness control.

Originality. The influence of the HCD response time on the accuracy of AGC thickness control systems for rolled products has been established. An approximate linear relationship has been identified between the ratio of the amplitude of thickness fluctuations caused by eccentricity and the amplitude of roll gap fluctuations relative to the roll speed and HCD response time under the AGC algorithm thickness control conditions. The improved procedure for determining the actual eccentricity amplitude in real time has been substantiated.

Practical value. The effectiveness is substantiated of implementing an improved active search algorithm for determining the eccentricity parameters of mill rolls under the limited HCD response conditions in real time. This approach allows for a threefold reduction in the sheet thickness variability caused by roll eccentricity compared to the performance indicators of the known AGC thickness control systems, thereby ensuring the production of high-precision rolled products in Ukrainian sheet rolling mills.

Keywords: thickness control of rolled products, AGC algorithm, roll eccentricity, response speed of hydraulic compression devices, computer simulation modelling

References.

1. Prinz, K., Steinboeck, A., Müller, M., Ettl, A., Schausberger, F., & Kugi, A. (2019). Online parameter estimation for adaptive feedforward control of the strip thickness in a hot strip rolling mill. Journal of Manufacturing Science and Engineering. https://doi.org/10.1115/1.4043575.

2. Kexin, Y., Gang, Z., & Zhe, Y. (2023). Roll Eccentricity Detection and Application Based on SFT and Regional DFT. Nonlinear Model-Based Fault Detection for Industrial Applications. https://doi.org/10.3390/s23167157.

3. Wehr, M., Stenger, D., Schatzler, S., Beyer, R., & Abel, D. (2020). Online Model Adaptation in Cold Rolling for Improvement of Thickness Precision. 21 ^st IFAC World Congress. Berlin, Germany, (pp. 12-17). https://doi.org/10.1016/j.ifacol.2020.12.2776.

4. Yang, X., Luo, H., Krueger, M., Ding, S.X., & Peng, K. (2016). Online Monitoring System Design for Roll Eccentricity in Rolling Mills. IEEE Transactions on Industrial Electronics, 4(63). https://doi.org/10.1109/TIE.2015.2442223.

5. Imanari, H., & Koshinuma, K. (2011). Roll Eccentricity Control Using Identified Eccentricity of Top/Bottom Rolls by Roll Force. Transactions of the Society of Instrument and Control Engineers, 46, 525-531. https://doi.org/10.9746/sicetr.46.525.

6. Vuksanovic, B., & Bousbaine, А. (2013). Intelligent Control of Aluminium Rolling Mills Using Two Dimensional Adaptive Filters. International Journal of Modeling and Optimization, 3(5), 412-417. https://doi.org/10.7763/IJMO.2013.V3.310.

7. Gao, S., Xu, L., Li, Y., & Ji, J. (2022) Roll eccentricity extraction and compensation based on MPSO-WTD and ITD. PLoS ONE, 17(2). https://doi.org/10.1371/journal.pone.0259810.

8. Wehr, M., Stockert, S., Abel, D., & Hirt, G. (2018). Model predictive roll gap control in cold rolling with piezoelectric actuators. IEEE Conference on Control Technology and Applications (CCTA). https://doi.org/10.1109/CCTA.2018.8511333.

9. Waleed, I. Hameed, & Khearia, A. Mohamad (2014). Strip Thickness Control of Cold Rolling Mill with Roll Eccentricity Compensation by Using Fuzzy Neural Network. Engineering, 6(1). https://doi.org/10.4236/eng.2014.61005.

10. Zheng, G., Ge, L.H., Shi, Y.Q., Li, Y., & Yang, Z. (2018). Dynamic rolling force prediction of reversible cold rolling mill based on bp neural network with improved pso. In 2018 Chinese Automation Congress (CAC), IEEE. https://doi.org/10.1109/CAC.2018.8623139.

11. Wehr, M., Schätzler, S., Abel, D., & Hirt, G. (2020). Model Predictive Control of an Overactuated Roll Gap with a Moving Manipulated Variable. 2020 American Control Conference (ACC). https://doi.org/10.23919/ACC45564.2020.9147360.

12. Wehr, M., Stenger, D., Schätzler, S., Beyer, R., Abel, D., & Gerhard, H. (2020). Online Model Adaptation in Cold Rolling for Improvement of Thickness Precision. IFAC-PapersOnLine, 53(2), 10372-10379. https://doi.org/10.1016/j.ifacol.2020.12.2776.

13. Potap, O., Zinchenko, M., Rybalchenko, M., & Potap, M. (2018). Computer simulation of the automated system for compensating the eccentricity of rolling rolls. System technologies, 2(115), 75-83.

14. Potap, O., Zinchenko, M., Piven, V., & Potap, O. (2020). The method of automatic adjustment of the strip thickness with compensation of the eccentricity of rolling rolls. Patent UA No. 122616 C2.

15. Yang, Z., Liu, D., & Zheng, G. (2022). Roll Eccentricity Signal Detection and Its Engineering Application Based on SFFT-IAA. Applied Sciences, 12, 8913. https://doi.org/10.3390/app12178913.

16. Prinz, K., Steinboeck, A., Müller, M., Ettl, A., Schausberger, F., & Kugi, A. (2019). Online parameter estimation for adaptive feedforward control of the strip thickness in a hot strip rolling mill. Journal of Manufacturing Science and Engineering, 7(141). https://doi.org/10.1115/1.4043575.

17. Potap, O., & Ivanichik, A. (2022). The accuracy of rolling thickness adjustment in conditions of high-frequency disturbances taking into account the speed of roll setting devices. Fundamental and applied problems of ferrous metallurgy, 36, 299-307. https://doi.org/10.52150/2522-9117-2022-36-299-307.

• < Prev
• Next >