DocumentCode :
2772407
Title :
Resonant frequency band estimation using adaptive wavelet decomposition level selection
Author :
Yaqub, M.F. ; Gondal, I. ; Kamruzzaman, J.
fYear :
2011
fDate :
7-10 Aug. 2011
Firstpage :
376
Lastpage :
381
Abstract :
The vibrations induced by machine faults help in diagnosis and prognosis of the machine. It is crucial for the fault diagnostic system to extract resonant frequency band which carries useful information about the defect frequencies and contains maximum signal to noise ratio. The spectral orientation of the resonant frequency band varies with the variation in machine dynamics. The existing techniques which employ wavelet transformation to exploit the signal energy distribution among different frequency sub-bands, are based on fixed decomposition level and do not optimize the wavelet parameters according to varying machine dynamics. The proposed study develops a novel technique: Adaptive Wavelet Decomposition and Resonance Frequency Estimation (AWRE) which estimates the positioning of the resonant frequency band based on adaptive selection of the wavelet decomposition levels. The results for the simulated as well as actual vibration data demonstrate that the proposed technique estimates the bandwidth of the resonant frequency band quite effectively.
Keywords :
adaptive signal processing; condition monitoring; fault diagnosis; frequency estimation; optimisation; singular value decomposition; spectral analysis; vibrations; adaptive wavelet decomposition; machine fault diagnostic; machine prognosis; optimization; resonant frequency band estimation; signal energy distribution; vibrations; Bandwidth; Harmonic analysis; Power harmonic filters; Resonant frequency; Time frequency analysis; Vibrations; Wavelet transforms; Adaptive wavelet decomposition; Bearing faults; Machine health monitoring; Resonant frequency band estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Automation (ICMA), 2011 International Conference on
Conference_Location :
Beijing
ISSN :
2152-7431
Print_ISBN :
978-1-4244-8113-2
Type :
conf
DOI :
10.1109/ICMA.2011.5985687
Filename :
5985687
Link To Document :
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