New Opportunities in Real-Time Diagnostics of Induction Machines

Tatjana Baraškova, Karolina Kudelina () and Veroonika Shirokova
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Tatjana Baraškova: Mechanical Engineering and Energy Technology Processes Control Work Group, Virumaa College, Tallinn University of Technology, 30322 Kohtla-Järve, Estonia
Karolina Kudelina: Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia
Veroonika Shirokova: Mechanical Engineering and Energy Technology Processes Control Work Group, Virumaa College, Tallinn University of Technology, 30322 Kohtla-Järve, Estonia

Energies, 2024, vol. 17, issue 13, 1-16

Abstract: This manuscript addresses the critical challenges in achieving high-accuracy remote control of electromechanical systems, given their inherent nonlinearities and dynamic complexities. Traditional diagnostics often suffer from data inaccuracies and limitations in analytical techniques. The focus is on enhancing the dynamic model accuracy for remote induction motor control in both closed- and open-loop speed control systems, which is essential for real-time process monitoring. The proposed solution includes real-time measurements of input and output physical quantities to mitigate inaccuracies in traditional diagnostic methods. The manuscript discusses theoretical aspects of nonlinear torque formation in induction drives and introduces a dynamic model employing vector control and speed control schemes alongside standard frequency control methods. These approaches optimize frequency converter settings to enhance system performance under varying nonlinear conditions. Additionally, the manuscript explores methods to analyze dynamic, systematic errors arising from frequency converter inertial properties, thereby improving electromechanical equipment condition diagnostics. By addressing these challenges, the manuscript significantly advances the field, offering a promising future with enhanced dynamic model accuracy, real-time monitoring techniques, and advanced control methods to optimize system reliability and performance.

Keywords: condition monitoring; electromechanical system; induction motors; remote control; real-time monitoring (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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