Bearing fault detection in wind turbines using dominant intrinsic mode function subtraction

This paper deals with a fault detection method based on an empirically data-driven approach combined to a statistical tool. This approach is an enhanced version of the empirical mode decomposition. The proposed fault detector application to bearing defects in wind turbine based on induction generator clearly shows that it is well suited for stationary and non-stationary behavior regardless the rank of the intrinsic mode function introduced by the fault.