Gear Fault Classification Using Kernel Discriminant Analysis

Abstract:

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This paper presents a study of KDA(kernel discriminant analysis) in gearbox failure feature extraction and classification. Experimental gearbox vibration signals measured from normal, gear small spall, gear severe spall and gear wear operating conditions are analyzed using either KPCA(kernel principal component analysis) or KDA as the feature extraction and fault classification methods. Experiment results indicate the effectiveness and thesuperiority of KDA for gear fault classification over KPCA.

Info:

Periodical:

Key Engineering Materials (Volumes 321-323)

Edited by:

Seung-Seok Lee, Joon Hyun Lee, Ik Keun Park, Sung-Jin Song, Man Yong Choi

Pages:

1556-1559

DOI:

10.4028/www.scientific.net/KEM.321-323.1556

Citation:

W. H. Li et al., "Gear Fault Classification Using Kernel Discriminant Analysis", Key Engineering Materials, Vols. 321-323, pp. 1556-1559, 2006

Online since:

October 2006

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Price:

$35.00

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