Bearing Fault Diagnosis in Induction Machine Based on Current Analysis using High-Resolution Technique

Mounir Djeddi (1) , Pierre Granjon (1) , Benoît Leprettre (2)

1 GIPSA-SA-IGA - GIPSA - Signal et Automatique pour le Diagnostic et la Surveillance
2 Schneider Electric Industries S.A.S.

In this paper, we propose to perform early fault diagnosis using high-resolution spectral analysis of the stator current to detect bearing faults in electrical induction machine. While most research works focus on mechanical vibration analysis, the originality of our work relies on the use of high-resolution methods to detect modulations in the stator current. We present the results obtained for real data to detect inner and outer raceway bearing defects made articially as well as bearing defects obtained through on-site ageing. The obtained results show that the proposed method yields better detection than classical spectum analysis.

Mots clés: high-resolution algorithm; current; induction machine; signal processing; bearing fault; voltage; phase modulation

Domaines: Energie électrique; Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Mounir Djeddi, Pierre Granjon, Benoît Leprettre. Bearing Fault Diagnosis in Induction Machine Based on Current Analysis using High-Resolution Technique. PowerENG 2007 - The 6th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, Sep 2007, Cracovie, Poland. ⟨hal-00186819⟩