In this paper, a prototype wavelet-based neural-network classifier for recognizing power-
quality disturbances is implemented and tested under various transient events. The discrete …

Recognition of power quality events by analyzing the voltage and current waveform
disturbances is a very important task for the power system monitoring. This paper presents a …

Existing techniques for recognizing and identifying power quality disturbance waveforms are
primarily based on visual inspection of the waveform. It is the purpose of this paper to bring …

This paper proposes a wavelet-based extended fuzzy reasoning approach to power-quality
disturbance recognition and identification. To extract power-quality disturbance features, the …

This paper proposes a model of power-quality detection for power system disturbances
using adaptive wavelet networks (AWNs). An AWN is a two-subnetwork architecture …

This paper presents an S-Transform based probabilistic neural network (PNN) classifier for
recognition of power quality (PQ) disturbances. The proposed method requires less number …

A novel approach for detection and classification of power quality (PQ) disturbances is
proposed. The distorted waveforms (PQ events) are generated based on the IEEE 1159 …

This paper presents an integrated model for recognizing power-quality disturbances (PQD)
using a novel wavelet multiclass support vector machine (WMSVM). The so-called support …

Recognition of power quality events by analyzing voltage waveform disturbances is a very
important task for power system monitoring. This article presents a novel approach for the …

This paper presents a novel approach for the classification of power quality disturbances.
The approach is based on inductive learning by using decision trees. The wavelet transform …