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Rolling Element Bearing Fault Diagnosis Using Laplace-Wavelet Envelope Power Spectrum


The bearing characteristic frequencies (BCF) contain very little energy, and are usually overwhelmed by noise and higher levels of macro-structural vibrations. They are difficult to find in their frequency spectra when using the common technique of fast fourier transforms (FFT). Therefore, Envelope Detection (ED) has always been used with FFT to identify faults occurring at the BCF. However, the computation of the ED is suffering to strictly define the resonance frequency band. In this paper, an alternative approach based on the Laplace-wavelet enveloped power spectrum is proposed. The Laplace-Wavelet shape parameters are optimized based on Kurtosis maximization criteria. The results for simulated as well as real bearing vibration signal show the effectiveness of the proposed method to extract the bearing fault characteristic frequencies from the resonant frequency band.


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Correspondence to Khalid F. Al-Raheem.

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Al-Raheem, K.F., Roy, A., Ramachandran, K.P. et al. Rolling Element Bearing Fault Diagnosis Using Laplace-Wavelet Envelope Power Spectrum. EURASIP J. Adv. Signal Process. 2007, 073629 (2007).

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  • Fast Fourier Transform
  • Fault Diagnosis
  • Vibration Signal
  • Rolling Element
  • Element Bearing