Machine Current Signature Analysis as a Way for Fault Detection in Squirrel Cage Wind Generators

Abstract

At the moment renewable generation systems are increasing its presence. The paper is about how machine current signature analysis (MCSA) can reliably diagnose faults in squirrel cage generators. This paper focuses on the experimental investigation for incipient fault detection and fault detection methods, suitably adapted for use in wind generator systems using squirrel cage. The proposed system diagnoses asynchronous generators having three types of faults such as broken rotor bars, short circuit of stator windings and bearing fault. After processing current data the classical fast Fourier transform is applied to detect characteristics under the healthy and various faulted conditions with MCSA.