Paper Title:
Gear Fault Classification Using Kernel Discriminant Analysis
  Abstract

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, K. Ding, T. L. Shi, G. L. Liao, "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
$32.00
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