DocumentCode :
3376964
Title :
Bearing envelope analysis window selection Using spectral kurtosis techniques
Author :
Bechhoefer, Eric ; Menon, Prathyush ; Kingsley, Michael
Author_Institution :
NRG Syst., Hinesburg, VT, USA
fYear :
2011
fDate :
20-23 June 2011
Firstpage :
1
Lastpage :
6
Abstract :
Envelope Analysis is a well-known signal processing technique for bearing fault detection. However, improper window selection can result in poor fault detection performance. Using a known fault data set, we quantify the performance of spectral kurtosis (SK) and envelope kurtosis (EK) as a technique for setting an optimal frequency and bandwidth window for the envelope analysis. We establish a measure of effectiveness (MOE): the correlation of fault energy with total spall length. With this MOE, we evaluate the ability of SK/EK to predict the optimal envelope analysis window.
Keywords :
fault tolerance; machine bearings; mechanical engineering computing; signal processing; statistics; bearing envelope analysis; bearing fault detection; effectiveness measurement; envelope kurtosis technique; fault energy correlation; signal processing technique; spectral kurtosis technique; window selection; Bandwidth; Correlation; Energy measurement; Frequency measurement; Frequency modulation; Inspection; Resonant frequency; Bearing Envelope Analysis; Freiquency/Bandwidth Selection; Inner Race Energy; Spectral Kurtosis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Prognostics and Health Management (PHM), 2011 IEEE Conference on
Conference_Location :
Montreal, QC
Print_ISBN :
978-1-4244-9828-4
Type :
conf
DOI :
10.1109/ICPHM.2011.6024338
Filename :
6024338
Link To Document :
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