Stator current based indicators for bearing fault detection in synchronous machine by statistical frequency selection

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.