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.