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Induction machine model with finite element accuracy for condition monitoring running in real time using hardware in the loop system

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Induction machine model with finite element accuracy for condition monitoring running in real time using hardware in the loop system

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dc.contributor.author Sapena-Bano, Angel es_ES
dc.contributor.author CHINESTA SORIA, FRANCISCO JOSE es_ES
dc.contributor.author Pineda-Sanchez, Manuel es_ES
dc.contributor.author Aguado-López, Jose Vicente es_ES
dc.contributor.author Borzacchiello, D. es_ES
dc.contributor.author Puche-Panadero, Rubén es_ES
dc.date.accessioned 2020-04-17T12:51:26Z
dc.date.available 2020-04-17T12:51:26Z
dc.date.issued 2019-10 es_ES
dc.identifier.issn 0142-0615 es_ES
dc.identifier.uri http://hdl.handle.net/10251/140952
dc.description.abstract [EN] Most industrial processes are run by induction machines (IMs). Condition monitoring of IM assures their continuity of service, and it may avoid highly costly breakdowns. Among the methods for condition monitoring, online motor current signature analysis is being attracting a rising interest, because it is non-invasive, and it can identify a wide variety of faults at early stage. To favour the development of on-line fault diagnosis techniques, it is necessary to have real-time currents with which test the new techniques and devices. Models running in real time in hardware-in-the-loop (HIL) simulators are a suitable alternative to balance the drawbacks of test benches (costly, limited machines, faults and working conditions). These models must be accurate enough to reflect the effects of a fault and they must be running in real time. A promising technique based on the equivalent circuit parameters calculation of IM by finite element analysis (FEA) is attracting a rising interest due to its reliability, performance and the possibility of being run in a HIL. Nevertheless, prior to running in a HIL, it is necessary to compute the IM parameters using FEA, which requires long simulation times and high computing resources. Consequently, covering a whole range of degrees of a giving fault could be unaffordable. What is proposed in this paper is to apply the sparse subspace learning (SSL) in combination with the hierarchical Lagrangian interpolation (HLI) to obtain the parametric solutions of the faulty IM model that cover the whole range of severity of a given fault, with a reduced number of FEA simulations. By means of this approach it is possible not only to boost the computation speed but also to achieve a significant reduction of memory requirements while retaining reasonable accuracy compared to traditional FEA, so enabling the real-time simulation of predictive models. es_ES
dc.description.sponsorship This work was supported by the Spanish "Ministerio de Education, cultura y Deporte" in the framework of the "Programa Estatal de Promotion del Talento y su Empleabilidad en I+D+i, Subprograma Estatal de Movilidad, del Plan Estatal de Investigation Cientifica y Tecnica y de Innovacion 2013-2016" in the subframework "Estancias de movilidad en el extranjero Jose Castillejo para jovenes doctores". es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof International Journal of Electrical Power & Energy Systems es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Fault diagnosis es_ES
dc.subject Hierarchical Lagrange interpolation es_ES
dc.subject Induction machines es_ES
dc.subject Model order reduction es_ES
dc.subject Sparse subspace learning es_ES
dc.subject.classification FISICA APLICADA es_ES
dc.subject.classification INGENIERIA ELECTRICA es_ES
dc.title Induction machine model with finite element accuracy for condition monitoring running in real time using hardware in the loop system es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.ijepes.2019.03.020 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Eléctrica - Departament d'Enginyeria Elèctrica es_ES
dc.description.bibliographicCitation Sapena-Bano, A.; Chinesta Soria, FJ.; Pineda-Sanchez, M.; Aguado-López, JV.; Borzacchiello, D.; Puche-Panadero, R. (2019). Induction machine model with finite element accuracy for condition monitoring running in real time using hardware in the loop system. International Journal of Electrical Power & Energy Systems. 111:315-324. https://doi.org/10.1016/j.ijepes.2019.03.020 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.ijepes.2019.03.020 es_ES
dc.description.upvformatpinicio 315 es_ES
dc.description.upvformatpfin 324 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 111 es_ES
dc.relation.pasarela S\384448 es_ES
dc.contributor.funder Ministerio de Educación, Cultura y Deporte es_ES


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