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Article

Motor Temperature Observer for Four-Mass Thermal Model Based Rolling Mills

by
Boris M. Loginov
1,
Stanislav S. Voronin
1,
Roman A. Lisovskiy
1,
Vadim R. Khramshin
2 and
Liudmila V. Radionova
1,*
1
Department of Automation and Control, Moscow Polytechnic University, 38, Bolshaya Semyonovskaya Str., 107023 Moscow, Russia
2
Power Engineering and Automated Systems Institute, Nosov Magnitogorsk State Technical University, 455000 Magnitogorsk, Russia
*
Author to whom correspondence should be addressed.
Sensors 2025, 25(14), 4458; https://doi.org/10.3390/s25144458
Submission received: 3 June 2025 / Revised: 8 July 2025 / Accepted: 14 July 2025 / Published: 17 July 2025
(This article belongs to the Section Industrial Sensors)

Abstract

Thermal control in rolling mills motors is gaining importance as more and more hard-to-deform steel grades are rolled. The capabilities of diagnostics monitoring also expand as digital IIoT-based technologies are adopted. Electrical drives in modern rolling mills are based on synchronous motors with frequency regulation. Such motors are expensive, while their reliability impacts the metallurgical plant output. Hence, developing the on-line temperature monitoring systems for such motors is extremely urgent. This paper presents a solution applying to synchronous motors of the upper and lower rolls in the horizontal roll stand of plate mill 5000. The installed capacity of each motor is 12 MW. According to the digitalization tendency, on-line monitoring systems should be based on digital shadows (coordinate observers) that are similar to digital twins, widely introduced at metallurgical plants. Modern reliability requirements set the continuous temperature monitoring for stator and rotor windings and iron core. This article is the first to describe a method for calculating thermal loads based on the data sets created during rolling. The authors have developed a thermal state observer based on four-mass model of motor heating built using the Simscape Thermal Models library domains that is part of the MATLAB Simulink. Virtual adjustment of the observer and of the thermal model was performed using hardware-in-the-loop (HIL) simulation. The authors have validated the results by comparing the observer’s values with the actual values measured at control points. The discrete masses heating was studied during the rolling cycle. The stator and rotor winding temperature was analysed at different periods. The authors have concluded that the motors of the upper and lower rolls are in a satisfactory condition. The results of the study conducted generally develop the idea of using object-oriented digital shadows for the industrial electrical equipment. The authors have introduced technologies that improve the reliability of the rolling mills electrical drives which accounts for the innovative development in metallurgy. The authors have also provided recommendations on expanded industrial applications of the research results.
Keywords: rolling mill; motor; thermal state; observer; four-mass model; temperature; validation rolling mill; motor; thermal state; observer; four-mass model; temperature; validation

Share and Cite

MDPI and ACS Style

Loginov, B.M.; Voronin, S.S.; Lisovskiy, R.A.; Khramshin, V.R.; Radionova, L.V. Motor Temperature Observer for Four-Mass Thermal Model Based Rolling Mills. Sensors 2025, 25, 4458. https://doi.org/10.3390/s25144458

AMA Style

Loginov BM, Voronin SS, Lisovskiy RA, Khramshin VR, Radionova LV. Motor Temperature Observer for Four-Mass Thermal Model Based Rolling Mills. Sensors. 2025; 25(14):4458. https://doi.org/10.3390/s25144458

Chicago/Turabian Style

Loginov, Boris M., Stanislav S. Voronin, Roman A. Lisovskiy, Vadim R. Khramshin, and Liudmila V. Radionova. 2025. "Motor Temperature Observer for Four-Mass Thermal Model Based Rolling Mills" Sensors 25, no. 14: 4458. https://doi.org/10.3390/s25144458

APA Style

Loginov, B. M., Voronin, S. S., Lisovskiy, R. A., Khramshin, V. R., & Radionova, L. V. (2025). Motor Temperature Observer for Four-Mass Thermal Model Based Rolling Mills. Sensors, 25(14), 4458. https://doi.org/10.3390/s25144458

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