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Bearing fault Detection in Synchronous Machine based on the Statistical Analysis of Stator Current

Abstract : In this paper, an original method to compute an indicator for efficient detection of bearing defaults in high speed synchronous machines is presented. This indicator is based on the statistical analysis of the stator current spectrum. The principle of the method is to compare the current spectrum to a healthy reference spectrum. The reference spectrum is used to center and reduce the current spectrum and provides an indication on its difference from the reference spectrum. A statistical based indicator is then constructed as the sum of the contributions of the centered reduced spectrum for different interesting frequency bands. This indicator has been tested on 2 different test campaigns, for 4 different speeds and compared a vibratory indicator. Results show that the proposed indicator evolves the same way than the vibratory indicator and provides with an efficient detection of bearing fault with only very few false alarms.
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Antoine Picot, Ziad Obeid, Jérémi Régnier, Pascal Maussion, Sylvain Poignant, et al.. Bearing fault Detection in Synchronous Machine based on the Statistical Analysis of Stator Current. 38th Annual Conference on IEEE Industrial Electronics Society (IECON 2012) , Oct 2012, Montréal, Canada. ⟨10.1109/IECON.2012.6389275⟩. ⟨hal-01430335⟩

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