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Title: Power quality monitoring using an integrated Fourier linear combiner and fuzzy expert system
Authors: Dash, P K
Jena, R K
Salama, M M A
Keywords: Fourier linear combiner
Fuzzy expert system
Disturbance waveform
Issue Date: Oct-1999
Publisher: Elsevier
Citation: International Journal of Electrical Power & Energy Systems, Vol 21, Iss 7, P 497-506
Abstract: The paper presents a new approach for the classification of transient disturbance waveforms in a power system by using a Fourier linear combiner and a fuzzy expert system. The measured voltage or current waveforms at a distribution bus are passed through a Fourier linear combiner block to provide peak or root mean square (RMS) amplitude and phase of the fundamental component at every sampling instant. The peak or RMS amplitude and computed slope of the waveforms are then passed on to a diagnostic module that computes the truth value of the signal combination and determines the class to which the waveform belongs. Computer simulated tests are carried out using programs to obtain the disturbance waveform classification with the help of a new hybrid approach which is much simpler than the recently postulated neural network and wavelet based techniques. The classification is found to be robust and yields accurate results in most cases with the least amount of computational burden.
Description: Copyright of this article belongs to Elsevier Science Ltd
Appears in Collections:Journal Articles

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