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Advances in Signal Processing and Artificial Intelligence Technologies in the Classification of Power Quality Events: A Survey

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Power quality monitoring has advanced from strictly problem solving to ongoing monitoring of system performance. The increased amount of data being collected requires more advanced analysis tools. New intelligent system technologies using expert systems and artificial neural networks provide some unique advantages regarding fault analysis. The purpose of this article is to review and discuss various tools and methodologies aimed at providing more flexible and efficient ways of assessing power quality. Advances in signal processing and artificial intelligence tools will be examined for their role in the detection and classification of events, the application of various mathematical transforms and the implementation of rules-based expert systems. We focus further on the review on several implementation methodologies, and a performance comparison of existing implementations are presented. Recommendations for future study are also outlined. This review opens the path for researchers to future comparative studies between different architectures, and as a reference point for developing more powerful and flexible structures.

Keywords: PQ; artificial intelligence; artificial neural network; classification; discrete wavelet transform; feature extraction; fuzzy logic

Document Type: Research Article


Affiliations: Faculty of Engineering, Multimedia University, Selangor, Malaysia

Publication date: December 1, 2005

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