Identification of ferroresonance based on S-transform and support vector machine

The aim of this paper is to develop a method based on S-transform and Support Vector Machine (SVM) for ferroresonance detection. Using this method ferroresonance can be discriminate from other transients such as capacitor switching, load switching and transformer switching. S-transform (ST) is used for decomposition of signals, feature selection is done by Kernel Principal Component Analysis (KPCA). SVM is used for classification. Ferroresonance data and other transients were obtained by simulation using EMTP program. Results show that the proposed procedure is efficient in identifying ferroresonance from other events.