Electric power quality disturbance classification using self-adapting artificial neural networks

Wijayakulasooriya, Janaka V., Putrus, Ghanim and Minns, Peter (2002) Electric power quality disturbance classification using self-adapting artificial neural networks. IEE Proceedings: Generation, Transmission and Distribution, 149 (1). p. 98. ISSN 1350-2360

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Official URL: http://dx.doi.org/10.1049/ip-gtd:20020014
Item Type: Article
Additional Information: This work on the “Power Quality” which is now recognised an essential feature that largely affects the performance of modern power networks. This paper presents a new technique for classifying electrical power quality disturbance events based on a novel Self-Adapting Artificial Neural Network (SAANN), which has the unique capability of adapting to new disturbances. A PhD project (J. V. Wijayakulasooriya) funded by the University studentship.
Uncontrolled Keywords: computer simulation, discrete wavelet transform, fast Fourier transform, feature vectors
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics and Information Sciences
Depositing User: EPrint Services
Date Deposited: 26 Nov 2008 14:06
Last Modified: 12 May 2017 10:01
URI: http://nrl.northumbria.ac.uk/id/eprint/344

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