A hybrid signal processing technique for bearing defect severity estimation

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Abstract

This paper presents a hybrid signal processing technique for bearing defect feature extraction and severity estimation. This is achieved by decomposing vibration signals measured on multiple bearings with different defect conditions into multiple sub-bands by means of the wavelet packet transform (WPT). Representative statistical features for each sub-band are then calculated. Subsequently, Principal Component Analysis (PCA) is performed on the statistical features to choose the best-suited representative features as inputs to a diagnostic classifier for bearing health diagnosis.

Original languageEnglish
Title of host publicationProceedings of the World Tribology Congress III - 2005
PublisherAmerican Society of Mechanical Engineers
Pages857-858
Number of pages2
ISBN (Print)0791842029, 9780791842027
DOIs
StatePublished - 2005
Externally publishedYes
Event2005 World Tribology Congress III - Washington, D.C., United States
Duration: 12 Sep 200516 Sep 2005

Publication series

NameProceedings of the World Tribology Congress III - 2005

Conference

Conference2005 World Tribology Congress III
Country/TerritoryUnited States
CityWashington, D.C.
Period12/09/0516/09/05

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