Application of empirical mode decomposition and artificial neural network for automatic bearing fault diagnosis based on vibration signals

Ben Ali, Jaouher; Fnaiech, Farhat; Chebel-Morello, Brigitte; Saidi, Lotfi; Fnaiech, Nader

doi:10.1016/j.apacoust.2014.08.016

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Application of empirical mode decomposition and artificial neural network for automatic bearing fault diagnosis based on vibration signals

Author(s): Jaouher Ben Ali , Nader Fnaiech , Lotfi Saidi , Brigitte Chebel-Morello , Farhat Fnaiech

Publication date Created: March 2015

Publication date (Print): March 2015

Journal: Applied Acoustics

Publisher: Elsevier BV

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A review on machinery diagnostics and prognostics implementing condition-based maintenance

Andrew Jardine, Daming Lin, Dragan Banjevic (2006)

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Rolling element bearing diagnostics—A tutorial

Robert Randall, Jérôme Antoni (2011)

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Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics

Hai Qiu, Jay H Lee, Jing Lin … (2006)

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Author and article information

Journal

Title: Applied Acoustics

Abbreviated Title: Applied Acoustics

Publisher: Elsevier BV

ISSN (Print): 0003682X

Publication date Created: March 2015

Publication date (Print): March 2015

Volume: 89

Issue:

Pages: 16-27

Article

DOI: 10.1016/j.apacoust.2014.08.016

SO-VID: bf035ec3-b0b8-473e-a334-09f6504be641

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Application of empirical mode decomposition and artificial neural network for automatic bearing fault diagnosis based on vibration signals

Read this article at

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African Journal of Empirical Research

Most cited references 25

A review on machinery diagnostics and prognostics implementing condition-based maintenance

Rolling element bearing diagnostics—A tutorial

Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics

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Journal

Article

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