The combination of discrete wavelet transform and self organizing map for identification of fault location on transmission line

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dc.contributor.authorPothisarn, C.
dc.contributor.authorNgaopitakkul, A.
dc.date.accessioned2026-08-06T10:03:46Z
dc.date.available2026-08-06T10:03:46Z
dc.date.issued2012-01-01
dc.description.abstractIn the literature for fault location, Artificial neural networks (ANNs) have been reported. At the present time, unsupervised learning is not well understood. This paper proposes a new algorithm for identifying fault location on transmission lines, using Discrete Wavelet Transform (DWT) and Self-organizing maps (SOMs). The mother wavelet daubechies4 (db4) is employed to decompose high frequency component from these signals. The coefficients of scalel obtained using the DWT are used for training and test processes of the SOMs. After the training process, case studies are varied. The result shows that the average accuracy obtained from combination of DWT and SOMs is satisfactory.
dc.identifier.citationLecture Notes in Engineering and Computer Science, 2196, 1083-1086, 2012
dc.identifier.issn20780958
dc.identifier.other2-s2.0-84867479489
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/4060
dc.sourceLecture Notes in Engineering and Computer Science
dc.subjectFault Location
dc.subjectTransmission Line
dc.subjectUnsupervised network
dc.subjectWavelet Transform
dc.titleThe combination of discrete wavelet transform and self organizing map for identification of fault location on transmission line
dc.typeConference Paper

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