articleTop 10% cited

Power quality detection and classification using wavelet-multiresolution signal decomposition

IEEE Transactions on Power Delivery · 1999 · Vol. 14(4) · pp. 1469–1476

A.M. Gaouda✉(University of Waterloo)M.M.A. SalamaM.R. Sultan(Hatch (Canada))A.Y. Chikhani(Royal Military College of Canada)

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Abstract

The wavelet transform is introduced as a powerful tool for monitoring power quality problems generated due to the dynamic performance of industrial plants. The paper presents a multiresolution signal decomposition technique as an efficient method in analyzing transient events. The multiresolution signal decomposition has the ability to detect and localize transient events and furthermore classify different power quality disturbances. It can also be used to distinguish among similar disturbances.

Power Quality and Harmonics Power Transformer Diagnostics and Insulation Image and Signal Denoising MethodsWavelet transformMultiresolution analysisWaveletSIGNAL (programming language)DecompositionTransient (computer programming)Power qualityComputer scienceSignal processingArtificial intelligence

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583

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10.27

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Cited by

Detection and Classification of Power Quality Disturbances Using S-Transform and Probabilistic Neural Network