Fault detection and diagnosis for stand alone system based on induction generator

Abstract

This work presents an intelligent stand-alone system that is monitoring and analyzing results with the insertion of faults in this system. To fault detection it is used root mean square value combined with neural network. To ensure the fault signature, it was made different harmonic analysis simulations. The results obtained so far indicated that is possible detect the failure in the stand-alone system, so that, improving the repair of this system.