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...

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Main Authors: D. K. Harrison, K. P. Ramachandran, Asok Roy, Khalid F. Al-Raheem, Steven Grainger
Format: Article
Language:English
Published: SpringerOpen 2007-01-01
Series:EURASIP Journal on Advances in Signal Processing
Online Access:http://dx.doi.org/10.1155/2007/73629
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spelling doaj-0f79d2b2ac8142acaa99635d4dd18e3b2020-11-24T20:56:04ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802007-01-01200710.1155/2007/73629Rolling Element Bearing Fault Diagnosis Using Laplace-Wavelet Envelope Power SpectrumD. K. HarrisonK. P. RamachandranAsok RoyKhalid F. Al-RaheemSteven GraingerThe 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. http://dx.doi.org/10.1155/2007/73629
collection DOAJ
language English
format Article
sources DOAJ
author D. K. Harrison
K. P. Ramachandran
Asok Roy
Khalid F. Al-Raheem
Steven Grainger
spellingShingle D. K. Harrison
K. P. Ramachandran
Asok Roy
Khalid F. Al-Raheem
Steven Grainger
Rolling Element Bearing Fault Diagnosis Using Laplace-Wavelet Envelope Power Spectrum
EURASIP Journal on Advances in Signal Processing
author_facet D. K. Harrison
K. P. Ramachandran
Asok Roy
Khalid F. Al-Raheem
Steven Grainger
author_sort D. K. Harrison
title Rolling Element Bearing Fault Diagnosis Using Laplace-Wavelet Envelope Power Spectrum
title_short Rolling Element Bearing Fault Diagnosis Using Laplace-Wavelet Envelope Power Spectrum
title_full Rolling Element Bearing Fault Diagnosis Using Laplace-Wavelet Envelope Power Spectrum
title_fullStr Rolling Element Bearing Fault Diagnosis Using Laplace-Wavelet Envelope Power Spectrum
title_full_unstemmed Rolling Element Bearing Fault Diagnosis Using Laplace-Wavelet Envelope Power Spectrum
title_sort rolling element bearing fault diagnosis using laplace-wavelet envelope power spectrum
publisher SpringerOpen
series EURASIP Journal on Advances in Signal Processing
issn 1687-6172
1687-6180
publishDate 2007-01-01
description 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.
url http://dx.doi.org/10.1155/2007/73629
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AT asokroy rollingelementbearingfaultdiagnosisusinglaplacewaveletenvelopepowerspectrum
AT khalidfalraheem rollingelementbearingfaultdiagnosisusinglaplacewaveletenvelopepowerspectrum
AT stevengrainger rollingelementbearingfaultdiagnosisusinglaplacewaveletenvelopepowerspectrum
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