부산대학교 도서관

In view of the capacious efficacy of the Induction Motor (IM), the critical requisite is to monitor the power quality of the supply given to the induction motor in addition to the IM faults. The parameter involved to bolster the monitoring is the stator current of IM. The detection of the variations in the supply and the IM faults are processed using statistical methods. Cognitive classifiers like Support Vector Machine (SVM) and k-Nearest Neighbour (kNN) mechanise the process of classifying the condition of the IM and the nature of the supply. The classification efficiency of the SVM network is found to be 96.35% while that of kNN is 97.08%.