Discrimination the Roller Bearing Faults with Harmonic Wavelet Package, Kernel Principal Component Analysis and Relevance Vector Machine

Discrimination the Roller Bearing Faults with Harmonic Wavelet Package, Kernel Principal Component Analysis and Relevance Vector Machine

For the purpose of discriminating the roller bearing faults, this paper proposes a novel method with harmonic wavelet package, Kernel Principal Component Analysis (KPCA) and Relevance Vector Machine (RVM). Firstly, compute the vector energy with wavelet coefficients after the roller bearing vibratio...

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Bibliographic Details
Main Authors: Tao Xu, Ailing Pei, Yong Liu
Format: Article
Language:English
Published: IFSA Publishing, S.L. 2014-09-01
Series:Sensors & Transducers
Subjects:
Discriminate fault
Roller bearing
Harmonic wavelet package
Kernel principal component analysis
Relevance vector machine.
Online Access:http://www.sensorsportal.com/HTML/DIGEST/september_2014/Vol_179/P_2405.pdf

Internet

http://www.sensorsportal.com/HTML/DIGEST/september_2014/Vol_179/P_2405.pdf

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