Detection of induction motors rotor faults by using negative selection algorithm based on Park's vector approach

The stator current signals of induction motors are often used to detect the broken rotor bar faults. However, the detection work becomes rather tedious owing to the fact that the fundamental supply frequency is much greater and quite close to the fault frequency. To get rid of this difficulty, the use of filters is often employed. Besides the fundamental supply frequency, the filter methods used tend to press on the fault frequency and necessitate a lot of calculations. Several studies on methods detecting rotor faults exist in the literature. Unlike literature, this study applies the Negative Selection Algorithm on training and testing schemes of the a, b, c stator phase currents subjected to Park transformation after changing them into the id and iq magnitudes. The use of Park transformation eliminates the need of filter designs and lessens calculation load for the algorithm whereas application of the Negative Selection Algorithm helps with detection of both normal and fault values in the system. Backed with the experimental results, the method proposed in this study has shown the effects, accuracy and applicability of the algorithm in detecting broken rotor bar faults in induction motors.