Abstract
The wound-rotor induction generator (WRIG) is commonly used for wind energy application. WRIGs have simple construction, are robust with high starting torque and low starting current. Additionally, WRIGs allow rotor resistance control and can be driven at variable speeds. Despite the relative robustness of WRIGs, these machines still experience a variety of faults in practice. This paper presents an in-depth review of condition monitoring techniques for three-phase wound-rotor induction generators. Various recent research applying current signature analysis as a method of detecting and diagnosing different types of faults on both the stator and rotor of this machine is reviewed. The application of probabilistic and artificial intelligence methods such as Bayesian classification, artificial neural networks and fuzzy logic used for fault diagnosis are also investigated.