A comparative Study for Ball Bearing Fault Classification Using Kernel-SVM with Kullback Leibler Divergence Selected Features - Archive ouverte HAL Access content directly
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A comparative Study for Ball Bearing Fault Classification Using Kernel-SVM with Kullback Leibler Divergence Selected Features

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Zahra Mezni
  • Function : Author
Université de Carthage - University of Carthage
Claude Delpha
Laboratoire des signaux et systèmes
CV
Demba Diallo
Laboratoire Génie électrique et électronique de Paris
CV
Ahmed Braham
  • Function : Author
INSAT Tunis

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Engineering Sciences [physics] Signal and Image processing

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https://hal-centralesupelec.archives-ouvertes.fr/hal-02295400

Submitted on : Tuesday, September 24, 2019-10:56:07 AM

Last modification on : Saturday, June 25, 2022-10:39:43 PM

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hal-02295400 , version 1 (24-09-2019)

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Zahra Mezni, Claude Delpha, Demba Diallo, Ahmed Braham. A comparative Study for Ball Bearing Fault Classification Using Kernel-SVM with Kullback Leibler Divergence Selected Features. IEEE International Conference on Industrial Electronics (IEEE IECON 2019), Oct 2019, Lisbonne, Portugal. ⟨10.1109/iecon.2019.8926731⟩. ⟨hal-02295400⟩

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CNRS SUP_LSS SUP_SIGNAUX CENTRALESUPELEC GEEPS ECO2 UNIV-PARIS-SACLAY SORBONNE-UNIVERSITE SU-SCIENCES GS-ENGINEERING GS-COMPUTER-SCIENCE INSTITUT-SCIENCES-LUMIERE
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