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

Antoine Picot (1) , Ziad Obeid (2) , Jérémi Regnier (1) , Pascal Maussion (1) , Sylvain Poignant (3) , Olivier Darnis (3)

1 LAPLACE-CODIASE - COmmande et DIAgnostic des Systèmes Electriques
2 LAPLACE - LAboratoire PLasma et Conversion d'Energie
3 SAFRAN Group

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.

Mots clés: Vibratory indicator; Frequency bands; Synchronous machine; Bearings; Diagnostic; False alarms; Bearing fault detection; Statistical analysis; Stator current; Bearing defaults; Reference spectrum; Statistical based indicator; Centered reduced spectrum

Domaines: Génie mécanique [physics.class-ph]; Traitement du signal et de l'image [eess.SP]; Energie électrique

Antoine Picot, Ziad Obeid, Jérémi Regnier, 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⟩