{"id":{"repo_id":"adelaide","oai_identifier":"oai:digital.library.adelaide.edu.au:2440/63561"},"canonical_url":"https://search.dev.ndltd.org/etd/adelaide/oai:digital.library.adelaide.edu.au:2440/63561","repository":{"repo_id":"adelaide","name":"University of Adelaide","base_url":"https://digital.library.adelaide.edu.au/server/oai/request"},"display":{"title":"Digital signal processing techniques for improving the automatic classification of power quality events.","abstract":"The work presented in this thesis investigates the application of digital signal processing techniques in the power quality automatic classification field, and thus, proposes an optimized automatic monitoring system with an improved accuracy. The proposed monitoring system involves three main sections: detection of the power quality events, extraction of the distinctive features that characterise each event, and automatic classification of the similar events under pre-defined categories. 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