Turbinas eólicas: optimización en el pre-diagnóstico de fallas en el generador

Abstract

A non-invasive low cost method for pre-diagnosis faults in electrical machines of large wind turbines is proposed. The objective is to minimize fault risks and the removal of the machine with heavy equipment (such as cranes) for maintenance. Since it is normal to use more than one method to detect incipient faults, prediction requires corroboration for higher security (such as vibration measurement and current spectrum analyses). This practice is usual in industries, but optimum predictive maintenance of electric machines in a wind turbine requires the use of the fewest possible devices and a distance non-invasive monitoring method. The proposed method has all this characteristics and preliminary essays with low cost sensors show good results for experimental applications.