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University of Adelaide

Digital signal processing techniques for improving the automatic classification of power quality events.

Abstract

dc:description.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. The thesis proposes new power quality processing techniques for detection and feature extraction sections, including the Hilbert and Clarke transforms. The former proposed technique was used for analysing single phase signals, while the later technique was proposed for the simultaneous analysis of three signals.

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Gargoom, Ameen M.

Subjects

dc:subject × 1

Identifiers

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Handle dc:identifier.uri
http://hdl.handle.net/2440/63561
OAI identifier oai:identifier
oai:digital.library.adelaide.edu.au:2440/63561

Chain of custody

source
Harvested from
University of Adelaide
Base URL
digital.library.adelaide.edu.au/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Gargoom, Ameen M.. Digital signal processing techniques for improving the automatic classification of power quality events.. 2007. http://hdl.handle.net/2440/63561