HOS-based method for power quality event classification

This paper presents a novel method for classification of power quality events in voltage signals which makes use of higher order statistics based technique for extracting a reduced and representative event signature vector. The signature vectors composed of samples from the diagonal slices of the second and forth order cummulants, which are selected with Fisher´s discriminant ratio (FDR), provide enough separability among classification regions resulting in classification rate as high as 100% if the voltage signals are corrupted by the presence of isolated events. A comparison performance among the proposed method and two other ones found on the literature is provided and reveals that the proposed method not only achieve a good performance, but it also surpass the performance of previous techniques.