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An Optimal Resonant Frequency Band Feature Extraction Method Based on Empirical Wavelet Transform.

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This study introduces an Adaptive Average Spectral Negentropy (AASN) method to improve Empirical Wavelet Transform (EWT) for fault detection. The new approach enhances the extraction of fault modulation information from noisy signals.

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correlation coefficientempirical wavelet transformrotating machineryscale-space histogramspectral negentropy

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Area of Science:

  • Signal Processing
  • Mechanical Engineering
  • Biomedical Engineering

Background:

  • Empirical Wavelet Transform (EWT) is widely used for signal decomposition in various fields.
  • A key challenge in EWT is optimal Fourier spectrum division, especially with noise interference.
  • Existing methods like scale-space histogram can fail to extract fault information in noisy signals.

Purpose of the Study:

  • To propose an improved EWT method for accurate fault detection in noisy signals.
  • To enhance the extraction of fault modulation information by optimizing spectrum division.
  • To accurately determine the optimal resonant demodulation frequency band.

Main Methods:

  • The proposed method applies Adaptive Average Spectral Negentropy (AASN) to EWT analysis (AEWT).
  • It uses a parameterless clustering scale-space histogram method for initial spectrum segmentation.
  • It combines Average Spectral Negentropy (ASN) and correlation coefficient to identify the optimal frequency band for fault information.

Main Results:

  • The AEWT method effectively detects repetitive transients in signals with varying background noise intensities.
  • The approach optimizes the identification of fault-related frequency bands compared to traditional methods.
  • Experimental results demonstrate improved accuracy in fault detection under noisy conditions.

Conclusions:

  • The proposed AEWT method, utilizing AASN, significantly enhances fault detection capabilities.
  • This technique offers a robust solution for analyzing signals with significant noise interference.
  • The method provides a reliable way to reconstruct resonant frequency bands for envelope demodulation analysis.