Mostrar el registro sencillo del ítem
dc.contributor.author | Terrón-Santiago, Carla | es_ES |
dc.contributor.author | Martinez-Roman, Javier | es_ES |
dc.contributor.author | Puche-Panadero, Rubén | es_ES |
dc.contributor.author | Sapena-Bano, Angel | es_ES |
dc.date.accessioned | 2022-02-16T19:03:45Z | |
dc.date.available | 2022-02-16T19:03:45Z | |
dc.date.issued | 2021-10-20 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/180903 | |
dc.description.abstract | [EN] Since it is not efficient to physically study many machine failures, models of faulty induction machines (IMs) have attracted a rising interest. These models must be accurate enough to include fault effects and must be computed with relatively low resources to reproduce different fault scenarios. Moreover, they should run in real time to develop online condition-monitoring (CM) systems. Hybrid finite element method (FEM)-analytical models have been recently proposed for fault diagnosis purposes since they keep good accuracy, which is widely accepted, and they can run in real-time simulators. However, these models still require the full simulation of the FEM model to compute the parameters of the analytical model for each faulty scenario with its corresponding computing needs. To address these drawbacks (large computing power and memory resources requirements) this paper proposes sparse identification techniques in combination with the trigonometric interpolation polynomial for the computation of IM model parameters. The proposed model keeps accuracy similar to a FEM model at a much lower computational effort, which could contribute to the development and to the testing of condition-monitoring systems. This approach has been applied to develop an IM model under static eccentricity conditions, but this may extend to other fault types. | es_ES |
dc.description.sponsorship | This work was supported by the Spanish "Ministerio de Ciencia, Innovacion y Universidades (MCIU)", the "Agencia Estatal de Investigacion (AEI)" and the "Fondo Europeo de Desarrollo Regional (FEDER)" in the framework of the "Proyectos I+D+i -Retos Investigacion 2018", project reference RTI2018-102175-B-I00 (MCIU/AEI/FEDER, UE). | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | MDPI AG | es_ES |
dc.relation.ispartof | Sensors | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Fault diagnosis | es_ES |
dc.subject | Sparse identification | es_ES |
dc.subject | Model order reduction | es_ES |
dc.subject | Induction machines | es_ES |
dc.subject.classification | INGENIERIA ELECTRICA | es_ES |
dc.title | Low-Computational-Cost Hybrid FEM-Analytical Induction Machine Model for the Diagnosis of Rotor Eccentricity, Based on Sparse Identification Techniques and Trigonometric Interpolation | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3390/s21216963 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-102175-B-I00/ES/DISEÑO DE MODELOS AVANZADOS DE SIMULACION DE AEROGENERADORES PARA EL DESARROLLO Y PUESTA A PUNTO DE SISTEMAS DE DIAGNOSTICO DE AVERIAS "ON-LINE"./ | 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 | Terrón-Santiago, C.; Martinez-Roman, J.; Puche-Panadero, R.; Sapena-Bano, A. (2021). Low-Computational-Cost Hybrid FEM-Analytical Induction Machine Model for the Diagnosis of Rotor Eccentricity, Based on Sparse Identification Techniques and Trigonometric Interpolation. Sensors. 21(21):6963-6987. https://doi.org/10.3390/s21216963 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3390/s21216963 | es_ES |
dc.description.upvformatpinicio | 6963 | es_ES |
dc.description.upvformatpfin | 6987 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 21 | es_ES |
dc.description.issue | 21 | es_ES |
dc.identifier.eissn | 1424-8220 | es_ES |
dc.identifier.pmid | 34770270 | es_ES |
dc.identifier.pmcid | PMC8587933 | es_ES |
dc.relation.pasarela | S\448009 | es_ES |
dc.contributor.funder | AGENCIA ESTATAL DE INVESTIGACION | es_ES |
dc.contributor.funder | European Regional Development Fund | es_ES |