Wind turbines condition monitoring and fault diagnosis using generator current amplitude demodulation

Wind energy conversion systems have become a focal point in the research of renewable energy sources. In order to make wind turbines as competitive as the classical electric power stations, it is important to reduce the operational and maintenance costs. The most efficient way of reducing these costs would be to continuously monitor the condition of these systems. This allows for early detection of the degradation of the generator health, facilitating a proactive response, minimizing downtime, and maximizing productivity. This paper provides then an approach based on the generator stator current data collection and attempts to highlight the use of Hilbert transformation for failure detection in a Doubly-Fed Induction Generator (DFIG) based wind turbine for stationary and nonstationary cases.