Detecting insulation defects in electrical machines’ multi-turn windings based on analysis of transient electromagnetic processes

Authors

DOI:

https://doi.org/10.15587/1729-4061.2025.342301

Keywords:

high-frequency model, equivalent circuit, wave processes, diagnostics of winding insulation

Abstract

This study investigates transient processes occurring in a squirrel-cage induction motor with a stator’s multi-turn winding. These processes are used to devise efficient and simple diagnostic methods for assessing the condition of the least reliable element in an electrical machine – the winding insulation. This paper solves the task related to enhancing the operational reliability of electrical machines with multi-turn windings.

The proposed high-frequency model of transient processes in multi-turn windings of electrical machines aims to non-destructively diagnose the insulation. This model enables analysis of high-frequency and impulse phenomena with an equivalent frequency of up to tens of MHz, which may arise during the operation of the machine because of switching and atmospheric overvoltage, as well as when powering electric motors with inverters. Underlying the model is the frequency and time domain analyses under above-mentioned influences using a low-power multi-turn induction motor as an example.

To construct the model, a multi-segment equivalent circuit was used, represented as a series of connected four-poles with inductive-resistive-capacitive parameters corresponding to sections of the winding phase with conditionally uniform concentrated parameters.

The constructed model and the proposed method make it possible to achieve the necessary test overvoltage to detect hidden and undeveloped defects at minimal sparing energy impact, without causing its irreversible destruction. Taking into account the distributed parameters of the winding sections combined with the impulse nature of the excitation ensure non-destructive testing (or non-destructive evaluation) of multi-turn-wound AC machine windings compared to classical testing methods.

The proposed method makes it possible to obtain 2–2.5 times higher longitudinal test gradients with a comparable energetic impact at the level of 0.1 J. The results will contribute to improving the reliability of electrical machine operation in industrial settings by integrating the devised method into the system of planned preventive maintenance of electrical equipment.

Author Biographies

Vadim Chumack, National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"

PhD, Professor, Head of Department

Department of Electromechanics

Mykhailo Kovalenko, National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"

PhD, Associate Professor

Department of Electromechanics

Oksana Tymoshchuk, National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"

PhD, Associate Professor

Department of Mathematical Methods of System Analysis

Institute for Applied System Analysis

Roman Dukhno, National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"

PhD Student

Department of Electromechanics

References

  1. Asgari, A., Hanisch, L. V., Anspach, J., Franzki, J., Kahn, M., Kurrat, M., Henke, M. (2024). Reliability of Insulation Systems and Its Impact on Electric Machine Design for Automotive and Aviation Applications. Energies, 18 (1), 92. https://doi.org/10.3390/en18010092
  2. Zhang, J., Wang, J., Li, H., Zhang, Q., He, X., Meng, C. et al. (2025). A Review of Reliability Assessment and Lifetime Prediction Methods for Electrical Machine Insulation Under Thermal Aging. Energies, 18 (3), 576. https://doi.org/10.3390/en18030576
  3. Saeed, M., Fernández, D., Guerrero, J. M., Díaz, I., Briz, F. (2024). Insulation Condition Assessment in Inverter-Fed Motors Using the High-Frequency Common Mode Current: A Case Study. Energies, 17 (2), 470. https://doi.org/10.3390/en17020470
  4. Ghassemi, M. (2019). Accelerated insulation aging due to fast, repetitive voltages: A review identifying challenges and future research needs. IEEE Transactions on Dielectrics and Electrical Insulation, 26 (5), 1558–1568. https://doi.org/10.1109/tdei.2019.008176
  5. Hassan, W., Hussain, G. A., Wahid, A., Safdar, M., Khalid, H. M., Jamil, M. K. M. (2024). Optimum feature selection for classification of PD signals produced by multiple insulation defects in electric motors. Scientific Reports, 14 (1). https://doi.org/10.1038/s41598-024-73196-z
  6. Li, Z., Qian, Y., Wang, H., Zhou, X., Sheng, G., Jiang, X. (2021). A novel image‐orientation feature extraction method for partial discharges. IET Generation, Transmission & Distribution, 16 (6), 1139–1150. https://doi.org/10.1049/gtd2.12356
  7. Ji, Y., Giangrande, P., Madonna, V., Zhao, W., Galea, M. (2021). Reliability-Oriented Design of Inverter-Fed Low-Voltage Electrical Machines: Potential Solutions. Energies, 14 (14), 4144. https://doi.org/10.3390/en14144144
  8. Wang, J., Kong, Y., Cai, Y., Wang, Y. (2024). Effect of the repetition frequency and polarity of square wave voltage on the partial discharge of electric machine insulation for more electrical aircraft. Journal of Physics: Conference Series, 2820 (1), 012110. https://doi.org/10.1088/1742-6596/2820/1/012110
  9. Sun, H., Wang, Y., Lu, F., Ding, Y., Xinyang, Z., Yin, Y. (2023). Research on Partial Discharge of More Electric Aircraft Propulsion Motor Insulation Under Low Pressure and Square Wave Voltage. https://doi.org/10.13336/j.1003-6520.hve.20221785
  10. Jiang, J., Li, Z., Li, W., Ranjan, P., Wei, X., Zhang, X., Zhang, C. (2023). A review on insulation challenges towards electrification of aircraft. High Voltage, 8 (2), 209–230. https://doi.org/10.1049/hve2.12304
  11. Ji, Y., Giangrande, P., Zhao, W. (2024). Effect of Environmental and Operating Conditions on Partial Discharge Activity in Electrical Machine Insulation: A Comprehensive Review. Energies, 17 (16), 3980. https://doi.org/10.3390/en17163980
  12. Zhou, X., Giangrande, P., Ji, Y., Zhao, W., Ijaz, S., Galea, M. (2024). Insulation for Rotating Low-Voltage Electrical Machines: Degradation, Lifetime Modeling, and Accelerated Aging Tests. Energies, 17 (9), 1987. https://doi.org/10.3390/en17091987
  13. Chumack, V., Kovalenko, M., Tymoshchuk, O., Stulishenko, A., Ihnatiuk, Y. (2023). Design of a multilink system for calculating high-frequency processes in electric machines with mesh windings. Eastern-European Journal of Enterprise Technologies, 3 (8 (123)), 54–63. https://doi.org/10.15587/1729-4061.2023.282375
  14. Kovalenko, M., Chumack, V., Tymoshchuk, O., Kovalenko, M., Bazenov, V., Ihnatiuk, Y., Stulishenko, A. (2023). Research of high-frequency remagnetization model in laminated magnetic cores of electromechanical and electromagnetic energy converters. Eastern-European Journal of Enterprise Technologies, 4 (5 (124)), 6–15. https://doi.org/10.15587/1729-4061.2023.286002
  15. Chumak, V., Dukhno, R., Stulishenko, A., Svyatnenko, V. (2024). High-Frequency Processes In The Windings Of General-Purpose Electrical Machines In The Presence Of Defects In The Ground-Wall Insulation. Engineering, Energy, Transport AIC, 2 (125), 130–141. https://doi.org/10.37128/2520-6168-2024-2-15
  16. Kaganov, Z. G. (1990). Elektricheskie tsepi s raspredelyonnymi parametrami i cepnye skhemy. Moscow: Energoatomizdat, 248.
  17. Mahdavi, S., Hameyer, K. (2012). High frequency equivalent circuit model of the stator winding in electrical machines. 2012 XXth International Conference on Electrical Machines, 1706–1711. https://doi.org/10.1109/icelmach.2012.6350110
  18. Heller, B., Veverka, A. (1960). Vlnové procesy v elektrických strojích. Praha: SNTL – Nakladatelství technické literatury, 392.
  19. Boglietti, A., Carpaneto, E. (1999). Induction motor high frequency model. Conference Record of the 1999 IEEE Industry Applications Conference. Thirty-Forth IAS Annual Meeting (Cat. No.99CH36370), 3, 1551–1558. https://doi.org/10.1109/ias.1999.805947
  20. Ostroverkhov, M., Chumack, V., Kovalenko, M., Falchenko, M. (2022). Voltage Control of the Magnetoelectric Generator Based on the Change of the Magnetic Resistance of the Auxiliary Flux Circuits. 2022 IEEE 8th International Conference on Energy Smart Systems (ESS), 169–174. https://doi.org/10.1109/ess57819.2022.9969289
  21. Ostroverkhov, M., Chumack, V., Kovalenko, M., Ihnatiuk, Y. (2022). Magnetoelectric Generator with Magnetic Flux Shunting for Electric Power Complexes. 2022 IEEE 8th International Conference on Energy Smart Systems (ESS), 160–164. https://doi.org/10.1109/ess57819.2022.9969246
  22. Kovalenko, M. A., Kovalenko, I. Y., Tkachuk, I. V., Harford, A. G., Tsyplenkov, D. V. (2024). Mathematical modeling of a magnetic gear for an autonomous wind turbine. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, 2, 88–95. https://doi.org/10.33271/nvngu/2024-2/088
Detecting insulation defects in electrical machines’ multi-turn windings based on analysis of transient electromagnetic processes

Downloads

Published

2025-10-31

How to Cite

Chumack, V., Kovalenko, M., Tymoshchuk, O., & Dukhno, R. (2025). Detecting insulation defects in electrical machines’ multi-turn windings based on analysis of transient electromagnetic processes. Eastern-European Journal of Enterprise Technologies, 5(5 (137), 19–30. https://doi.org/10.15587/1729-4061.2025.342301

Issue

Section

Applied physics