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A Review of Stator Insulation State-of-Health Monitoring Methods

Author

Listed:
  • Benjamin Sirizzotti

    (School of Electrical and Computer Engineering, Baylor University, Waco, TX 76798, USA)

  • Daniel Addae

    (School of Electrical and Computer Engineering, Baylor University, Waco, TX 76798, USA)

  • Emmanuel Agamloh

    (School of Electrical and Computer Engineering, Baylor University, Waco, TX 76798, USA)

  • Annette von Jouanne

    (School of Electrical and Computer Engineering, Baylor University, Waco, TX 76798, USA)

  • Alex Yokochi

    (School of Mechanical Engineering, Baylor University, Waco, TX 76798, USA)

Abstract

Tracking the state of the health of electrical insulation in high-power electric machines has always been a topic of great interest due to the high cost of downtime associated with unexpected failures. Over the years, there have been continuous efforts to develop and improve upon methods for testing and categorizing the health and expected lifetime of stator insulation. Methods such as partial discharge, surge, and dissipation factor testing are common examples. With the increasing use of high-specific-power electric machines in new applications such as traction and wind power generation, coupled with the increasing use of wide-bandgap semiconductor device-based inverters, some traditional methods for insulation health tracking may need adjustments or be combined with newer methods to remain accurate and useful. This paper outlines a review of the traditional insulation health tracking methods and newer methods and improvements that have been proposed to address the concerns and shortcomings of traditional methods.

Suggested Citation

  • Benjamin Sirizzotti & Daniel Addae & Emmanuel Agamloh & Annette von Jouanne & Alex Yokochi, 2025. "A Review of Stator Insulation State-of-Health Monitoring Methods," Energies, MDPI, vol. 18(14), pages 1-25, July.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:14:p:3758-:d:1702473
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    References listed on IDEAS

    as
    1. Adam Decner & Marcin Baranski & Tomasz Jarek & Sebastian Berhausen, 2022. "Methods of Diagnosing the Insulation of Electric Machines Windings," Energies, MDPI, vol. 15(22), pages 1-24, November.
    2. Yuanlin Luo & Zhaohui Li & Hong Wang, 2017. "A Review of Online Partial Discharge Measurement of Large Generators," Energies, MDPI, vol. 10(11), pages 1-32, October.
    3. Jian Zhang & Jiajin Wang & Hongbo Li & Qin Zhang & Xiangning He & Cui Meng & Xiaoyan Huang & Youtong Fang & Jianwei Wu, 2025. "A Review of Reliability Assessment and Lifetime Prediction Methods for Electrical Machine Insulation Under Thermal Aging," Energies, MDPI, vol. 18(3), pages 1-38, January.
    4. Chuxuan He & Stefan Tenbohlen & Michael Beltle, 2025. "Ageing Analysis of Hairpin Windings in Inverter-Fed Motor Under PWM Voltage," Energies, MDPI, vol. 18(6), pages 1-18, March.
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