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Updated: Jan 11, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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An Enhanced TK Technology for Bearing Fault Detection Using Vibration Measurement.

Megha Malusare1, Manzar Mahmud2, Wilson Wang1

  • 1Department of Mechanical and Mechatronics Engineering, Lakehead University, Thunder Bay, ON P7B 5E1, Canada.

Sensors (Basel, Switzerland)
|November 13, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces an enhanced Teager-Kaiser (eTK) technique for reliable bearing fault detection and diagnosis. The method uses empirical mode decomposition and an eTK denoising filter to improve vibration signal analysis for early fault recognition.

Keywords:
Teager–Kaiser transformfault detectionrolling element bearingssignal processingvibration measurement

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Area of Science:

  • Mechanical Engineering
  • Signal Processing
  • Condition Monitoring

Background:

  • Rolling element bearings are crucial components in rotating machinery.
  • Effective bearing fault detection is essential for preventing performance degradation and reducing maintenance costs.
  • Existing fault detection methods face challenges in reliability.

Purpose of the Study:

  • To propose an enhanced Teager-Kaiser (eTK) technique for improved bearing fault detection and diagnosis.
  • To enhance the accuracy and reliability of bearing condition monitoring.

Main Methods:

  • Utilized vibration signals for bearing fault analysis.
  • Employed empirical mode decomposition (EMD) to identify representative intrinsic mode functions (IMFs).
  • Developed an eTK denoising filter to enhance signal-to-noise ratio of selected IMF features.
  • Applied analytical signal spectrum analysis for feature identification.

Main Results:

  • The proposed eTK technique demonstrated effectiveness in bearing fault detection and diagnosis.
  • The combination of EMD and eTK denoising improved the identification of fault-related features from vibration signals.
  • Experimental validation confirmed the technique's capability across various bearing conditions.

Conclusions:

  • The enhanced Teager-Kaiser (eTK) technique offers a novel and effective approach for bearing fault detection.
  • The method successfully addresses challenges in reliable bearing condition monitoring.
  • The proposed technique holds potential for practical applications in industrial machinery maintenance.