Many researches have been developed in order to design intelligent systems for diagnosing faults in electrical machines. These faults involve since electrical problems, such as short circuit in one phase of the stator, until mechanical problems, such as bearing damage. Among the intelligent systems applied in these situations, we highlight the artificial neural networks, the fuzzy inference systems, the genetic algorithms and the hybrid systems, such as those neuro-fuzzy approaches. This paper describes an overview of the most relevant works in this area, which have obtained promising results from the use of intelligent systems in the processes involved to the fault diagnosis in electrical motors. Its main contribution is in providing several technical aspects in order to address future works in this application field.
Electrical machines; induction motors; artificial neural network; fuzzy systems; fault diagnosis; intelligent systems
