Combination of discrete wavelet transform and probabilistic neural network algorithm for detecting fault location on transmission system

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dc.contributor.authorNgaopitakkul, Atthapol
dc.contributor.authorJettanasen, Chaiyan
dc.date.accessioned2026-08-06T10:02:06Z
dc.date.available2026-08-06T10:02:06Z
dc.date.issued2011-04-01
dc.description.abstractThis paper proposes a new algorithm for detecting faults in an electrical power transmission system, using discrete wavelet transform (DWT) and probabilistic neural network (PNN). Fault conditions are simulated using ATP/EMTP to obtain current signals. The algorithm used to analyze fault locations is developed on MATLAB. Fault detection is processed using the positive sequence current signals. The comparison among the maximum coefficients in first scale of each bus which can detect fault is performed in order to detect the faulty bus. The first peak time obtained from the faulty bus is used as an input for training pattern. Various cases based on Thailand electricity transmission systems are studied to verify the validity of the proposed technique. The result shows that the algorithm is capable of performing the fault locations with accuracy. ICIC International © 2011.
dc.identifier.citationInternational Journal of Innovative Computing Information and Control, 7(4), 1861-1873, 2011
dc.identifier.issn13494198
dc.identifier.other2-s2.0-79952539391
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/3569
dc.sourceInternational Journal of Innovative Computing Information and Control
dc.subjectDiscrete wavelet transform
dc.subjectFault location
dc.subjectProbabilistic neural network
dc.titleCombination of discrete wavelet transform and probabilistic neural network algorithm for detecting fault location on transmission system
dc.typeArticle

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