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Single point bearing fault diagnosis using simplified frequency model

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Abstract

The time synchronous averaging (TSA) is a well-known technique used for early detection of bearing failure in electrical machines. This method is very efficient if the characteristic default frequency is perfectly known. In this article, a reduced frequency model, derived from ESPRIT algorithm, is used to provide a very accurate estimation of the fault frequency. The precision obtained on this frequency allows to apply TSA algorithm under optimal conditions. The proposed method is tested on simulated and real vibration signals for inner and outer ring faults. Finally, a fault indicator is proposed to discriminate the healthy case from the faulty one.

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Acknowledgments

This work has been realized through the collaboration between LaSIE laboratory, University of La Rochelle, France and LIAS laboratory, University of Poitiers, France, with the financial support of FEDER program no: 33288-2010.

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Authors and Affiliations

  1. LIAS Laboratory, University of Poitiers, B25, 2 rue Pierre Brousse, 86022, Poitiers, France

    Mohamed Lamine Masmoudi, Erik Etien & Sandrine Moreau

  2. LaSIE Laboratory, University of La Rochelle, La Rochelle, France

    Mohamed Lamine Masmoudi & Anas Sakout

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  1. Mohamed Lamine Masmoudi
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  2. Erik Etien
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  3. Sandrine Moreau
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  4. Anas Sakout
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Correspondence to Mohamed Lamine Masmoudi.

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Masmoudi, M.L., Etien, E., Moreau, S. et al. Single point bearing fault diagnosis using simplified frequency model. Electr Eng 99, 455–465 (2017). https://doi.org/10.1007/s00202-016-0441-y

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  • DOI: https://doi.org/10.1007/s00202-016-0441-y

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