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Related Experiment Video

Updated: Nov 27, 2025

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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Gearbox Composite Fault Diagnosis Method Based on Minimum Entropy Deconvolution and Improved Dual-Tree Complex

Ziying Zhang1,2, Xi Zhang1, Panpan Zhang2

  • 1School of Mechanical, Electronic and Information Engineering, China University of Mining and Technology (CUMT), Xueyuan Road, Beijing 100083, China.

Entropy (Basel, Switzerland)
|December 3, 2020
PubMed
Summary

This study introduces an improved dual-tree complex wavelet transform (IDTCWT) combined with minimum entropy deconvolution (MED) for gearbox composite fault diagnosis. The method effectively identifies outer ring and gearbox faults without mode mixing.

Keywords:
frequency mixinggearbox composite faultimproved dual-tree complex wavelet transformminimum entropy deconvolution

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Area of Science:

  • Mechanical Engineering
  • Signal Processing

Background:

  • Dual-tree complex wavelet transform (DTCWT) shows promise for gearbox fault diagnosis.
  • Existing methods have limitations in accurately diagnosing composite faults.

Purpose of the Study:

  • To propose an improved dual-tree complex wavelet transform (IDTCWT) combined with minimum entropy deconvolution (MED) for enhanced gearbox composite fault diagnosis.
  • To address the weaknesses of traditional DTCWT in composite fault analysis.

Main Methods:

  • Adaptive determination of decomposition levels and sub-bands using a correlation coefficient matrix.
  • Removal of frequency mixing via notch filtering.
  • Noise reduction in sub-bands using minimum entropy deconvolution (MED).
  • Comparative analysis with Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD), and Variational Mode Decomposition (VMD).

Main Results:

  • Successful extraction of outer ring fault at 160 Hz and gearbox faults at 360 Hz and 720 Hz from compound fault vibration signals.
  • Demonstrated absence of mode mixing in the results.
  • Validation of the proposed method's feasibility through simulation and experimental data.

Conclusions:

  • The IDTCWT-MED method offers a novel and effective approach for gearbox composite fault feature extraction.
  • The proposed technique overcomes limitations of existing methods, providing superior diagnostic accuracy.