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Fault Diagnosis of Electric Transmission Lines Using Modular Neural Networks

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Fault Diagnosis of Electric Transmission Lines Using Modular Neural Networks

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dc.contributor.author Flores, A. es_ES
dc.contributor.author Quiles Cucarella, Eduardo es_ES
dc.contributor.author García Moreno, Emilio es_ES
dc.contributor.author Morant Anglada, Francisco José es_ES
dc.date.accessioned 2017-06-21T12:42:50Z
dc.date.available 2017-06-21T12:42:50Z
dc.date.issued 2016-08
dc.identifier.issn 1548-0992
dc.identifier.uri http://hdl.handle.net/10251/83369
dc.description "(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works." es_ES
dc.description.abstract This paper proposes a new method for fault diagnosis in electric power systems based on neural networks. With this method the diagnosis is performed by assigning a neural module for each type of component of the electric power system, whether it is a transmission line, bus or transformer. The neural modules for buses and transformers comprise two diagnostic levels which take into consideration the logic states of switches and relays, both internal and back-up. The neural module for transmission lines also has a third diagnostic level which takes into account the oscillograms of fault voltages and currents, as well as the frequency spectrums of these oscillograms, in order to verify if the transmission line had in fact been subjected to a fault. One important advantage of the diagnostic system proposed is that its implementation does not require the use of a network configurator for the system; it does not depend on the size of the power network, nor does it require retraining of the neural modules if the power network increases in size, making its application possible to only one component, a specific area, or the whole context of the power system.. es_ES
dc.language Inglés es_ES
dc.publisher Institute of Electrical and Electronics Engineers (IEEE) es_ES
dc.relation.ispartof IEEE Latin America Transactions es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Power systems es_ES
dc.subject Transmission networks es_ES
dc.subject Neural networks es_ES
dc.subject Fault diagnosis es_ES
dc.subject Fault voltages and currents es_ES
dc.subject Frequency spectrum es_ES
dc.subject.classification INGENIERIA DE SISTEMAS Y AUTOMATICA es_ES
dc.title Fault Diagnosis of Electric Transmission Lines Using Modular Neural Networks es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1109/TLA.2016.7786348
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica es_ES
dc.description.bibliographicCitation Flores, A.; Quiles Cucarella, E.; García Moreno, E.; Morant Anglada, FJ. (2016). Fault Diagnosis of Electric Transmission Lines Using Modular Neural Networks. IEEE Latin America Transactions. 14(8):3663-3668. doi:10.1109/TLA.2016.7786348 es_ES
dc.description.accrualMethod S es_ES
dc.description.upvformatpinicio 3663 es_ES
dc.description.upvformatpfin 3668 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 14 es_ES
dc.description.issue 8 es_ES
dc.relation.senia 322540 es_ES


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