A fuzzy-expert system for classifying power quality disturbances
This paper presents a fuzzy-expert system for automated detection and classification of power quality disturbances. The types of concerned disturbances include voltage sags, swells, interruptions, switching transients, impulses, flickers, harmonics, and notches. It is assumed that the analyzed waveforms are available in sampled form. Fourier transform and wavelet analysis are utilized to obtain unique features for the waveforms. A fuzzy-expert system is designed for making a decision regarding the type of the disturbance. Simulation studies are presented to verify the accuracy of the proposed approach. Comparison studies between an Artificial Neural Network based classification technique and the proposed approach are also reported to show the advantages of the proposed approach.
fuzzy-expert system wavelet analysis artificial neural network power quality disturbance classification