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Partial Discharge Detection from Large Motor Stator Slots Using EFPI Sensors.

Jinlong Wang1, Weizhong Sun1, Jun Zhou1

  • 1Yunnan Electric Test & Research Institute Group Co., Ltd., Kunming 650214, China.

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|January 25, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a novel Extrinsic Fabry-Perot Interferometer (EFPI) sensor to overcome challenges in detecting partial discharge (PD) in large motors. The new sensor accurately detects and localizes PD ultrasonic signals, improving motor insulation fault detection.

Keywords:
EFPI sensorPD source localizationacoustic field distributionfluid–structure interactionpartial discharge ultrasonic signals

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Area of Science:

  • Electrical Engineering
  • Materials Science
  • Acoustics

Background:

  • Traditional sensors face electromagnetic interference and signal instability for partial discharge (PD) detection in large motor stator slots.
  • Accurate detection and localization of PD are crucial for preventing motor failures.

Purpose of the Study:

  • To design and validate a novel sensor for enhanced sensitivity and stability in detecting PD ultrasonic signals.
  • To optimize sensor parameters for improved narrowband resonant detection within stator slots.

Main Methods:

  • Designed a novel Extrinsic Fabry-Perot Interferometer (EFPI) sensor with a vibration-coupling air gap.
  • Optimized diaphragm structure (20 μM quartz) and coupling interface.
  • Utilized simulation and experimental analyses to study ultrasonic signal propagation.

Main Results:

  • The EFPI sensor achieved a resonant frequency of 66 kHz for effective PD ultrasonic signal detection.
  • Demonstrated successful detection and localization of PD signals with an error of less than 5 mm.
  • Identified ultrasonic signal distribution and propagation characteristics within stator slots.

Conclusions:

  • The developed EFPI sensor offers a robust solution for detecting PD ultrasonic signals in large motor stators.
  • Provides theoretical and practical insights for efficient detection and precise localization of insulation faults.
  • Meets engineering requirements for PD detection and localization in critical industrial applications.