Stator Current based Indicators for Bearing Fault Detection in Synchronous Machine by Statistical Frequency Selection

Ziad Obeid (1) , Sylvain Poignant (2) , Jérémi Regnier (3) , Pascal Maussion (3)

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

The aim of this paper is to present some indicators developed for efficient detection of bearing defaults in high speed synchronous machines using a stator current analysis. These actuators are used in an air conditioning fan for aeronautic applications. The signatures of the bearing defects appear through an increase in amplitude of specific current harmonics multiples of the rotation frequency. From an experimental comparison between a healthy fan and another with damaged bearings, an automatic frequency selection is performed to identify the frequency ranges for which the energy is the most sensitive to the considered faults. From these frequencies, several strategies are investigated to propose a suitable indicator for the bearing fault detection. A post-processing algorithm is then developed and tested for different measurements, different types of faults and different operating points, to ensure the robustness of the proposed method.

Mots clés: Diagnostic; Bearing fault detection; Current spectrum analysis; Automatic frequency research

Domaines: Energie électrique

Ziad Obeid, Sylvain Poignant, Jérémi Regnier, Pascal Maussion. Stator Current based Indicators for Bearing Fault Detection in Synchronous Machine by Statistical Frequency Selection. IEEE IECON 2011, Industrial Electronics CONference, Nov 2011, Melbourne, Australia. pp. 2036-2041. ⟨hal-01219765⟩