dc.creator | Borrás-Talavera, María Dolores | es |
dc.creator | Castilla Ibáñez, Manuel | es |
dc.creator | Moreno-Alfonso, Narciso | es |
dc.creator | Montaño Asquerino, Juan-Carlos | es |
dc.date.accessioned | 2018-02-13T08:20:59Z | |
dc.date.available | 2018-02-13T08:20:59Z | |
dc.date.issued | 2001 | |
dc.identifier.citation | Borrás-Talavera, M.D., Castilla Ibáñez, M., Moreno-Alfonso, N. y Montaño Asquerino, J. (2001). Wavelet and Neural Structure: A New Tool for Diagnostic of Power System Disturbances. IEEE Transactions on Industry Applications, 37 (1), 184-190. | |
dc.identifier.citation | Borrás Talavera, M.D., Castilla Ibáñez, M., Moreno-Alfonso, N. y Montaño, J. (2001). Wavelet and Neural Structure: A New Tool for Diagnostic of Power System Disturbances. IEEE Transactions on Industry Applications, 37 (1), 184-190. | |
dc.identifier.issn | 0093-9994 | es |
dc.identifier.issn | 1939-9367 | es |
dc.identifier.uri | https://hdl.handle.net/11441/70237 | |
dc.description.abstract | The Fourier transform can be used for analysis of nonstationary signals, but the Fourier spectrum does not provide any time-domain information about the signal. When the time localization of the spectral components is needed, a wavelet transform giving the time-frequency representation of the signal must be used. In this paper, using wavelet analysis and neural systems as a new tool for the analysis of power system disturbances, disturbances are automatically detected, compacted, and classified. An example showing the potential of these techniques for diagnosis of actual power system disturbances is presented. | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | Institute of Electrical and Electronics Engineers | es |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Harmonic distortion | es |
dc.subject | Neural networks | es |
dc.subject | Signal analysis | es |
dc.subject | Transforms | es |
dc.subject | Wavelets | es |
dc.title | Wavelet and Neural Structure: A New Tool for Diagnostic of Power System Disturbances | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/acceptedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ingeniería Eléctrica | es |
dc.relation.publisherversion | http://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=19538 | es |
dc.identifier.doi | 10.1109/28.903145 | es |
dc.contributor.group | Universidad de Sevilla. TEP175: Grupo de Investigación en Ingeniería Eléctrica (Invespot) | es |
idus.format.extent | 7 p. | es |
idus.validador.nota | Postprint enviado por uno de los autores | es |
dc.journaltitle | IEEE Transactions on Industry Applications | es |
dc.publication.volumen | 37 | es |
dc.publication.issue | 1 | es |
dc.publication.initialPage | 184 | es |
dc.publication.endPage | 190 | es |
dc.identifier.sisius | 6680917 | es |