Accurate bearing remaining useful life prediction based on Weibull distribution and artificial neural network

Author:

Ben Ali Jaouher,Chebel-Morello Brigitte,Saidi Lotfi,Malinowski Simon,Fnaiech Farhat

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference38 articles.

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2. Rotating machinery prognostics: state of the art, challenges and opportunities;Heng;Mech. Syst. Sig. Process.,2009

3. Application of empirical mode decomposition and artificial neural network for automatic bearing fault diagnosis based on vibration signals;Ben Ali;Appl. Acoust.,2015

4. J. Coble, W. Hines, Identifying optimal prognostic parameters from data:a genetic algorithms approach,” in: Annual Conference of the Prognostics and Health Management Society, USA, 2009.

5. Prognosis of fauls in gaz turbine engines;Brotherton;Intell. Aerosp. Conf. Proc. IEEE,2000

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