Bearing Fault Detection in DFIG-Based Wind Turbines Using the First Intrinsic Mode Function

Yacine Amirat (1) , Vincent V. Choqueuse (2) , Mohamed Benbouzid (2) , Jean-Frederic Charpentier (3)

1 LISSI - Laboratoire Images, Signaux et Systèmes Intelligents
2 LBMS - Laboratoire brestois de mécanique et des systèmes
3 IRENAV - Institut de Recherche de l'Ecole Navale

Wind energy conversion systems have become a focal point in the research of renewable energy sources. In order to make the DFIG-based wind turbines so competitive as the classical electric power stations it is important to reduce the operational and maintenance costs by continuously monitoring the condition of these systems. This paper provides a method for bearing fault detection in DFIG-based wind turbines. The proposed method uses the first Intrinsic Mode Function (IMF) of the stator current signal. After extracting the first IMF, amplitude-demodulation is performed to reveal a generator bearing fault. Experimental results show that the proposed method significantly improves the result of classical amplitude-demodulation techniques for failure detection.

Mots clés: Wind turbine; Doubly Fed Induction Generator (DFIG); Fault detectio; Bearings; Signal processing

Domaines: Energie électrique

Yacine Amirat, Vincent V. Choqueuse, Mohamed Benbouzid, Jean-Frederic Charpentier. Bearing Fault Detection in DFIG-Based Wind Turbines Using the First Intrinsic Mode Function. XIX International Conference on Electrical Machines (ICEM), 2010, Sep 2010, ROME, Italy. pp.1-6, ⟨10.1109/ICELMACH.2010.5608066⟩. ⟨hal-01081638⟩