A comparative Study for Ball Bearing Fault Classification Using Kernel-SVM with Kullback Leibler Divergence Selected Features - CentraleSupélec Access content directly
Conference Papers Year :

A comparative Study for Ball Bearing Fault Classification Using Kernel-SVM with Kullback Leibler Divergence Selected Features

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

Domains

Signal and Image processing

Claude Delpha  : Connect in order to contact the contributor

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

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

Last modification on : Friday, March 24, 2023-2:53:12 PM

Not file

Dates and versions

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

Identifiers

Cite

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⟩

Export

BibTeX TEI Dublin Core DC Terms EndNote Datacite

Collections

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

Altmetric

Share

Gmail Facebook Twitter LinkedIn More