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Analytical Model of Induction Machines with Multiple Cage Faults Using the Winding Tensor Approach

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Analytical Model of Induction Machines with Multiple Cage Faults Using the Winding Tensor Approach

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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.contributor.author Terrón-Santiago, Carla es_ES
dc.contributor.author Burriel-Valencia, Jordi es_ES
dc.contributor.author Pineda-Sanchez, Manuel es_ES
dc.date.accessioned 2022-02-15T19:03:49Z
dc.date.available 2022-02-15T19:03:49Z
dc.date.issued 2021-07-27 es_ES
dc.identifier.uri http://hdl.handle.net/10251/180862
dc.description.abstract [EN] Induction machines (IMs) are one of the main sources of mechanical power in many industrial processes, especially squirrel cage IMs (SCIMs), due to their robustness and reliability. Their sudden stoppage due to undetected faults may cause costly production breakdowns. One of the most frequent types of faults are cage faults (bar and end ring segment breakages), especially in motors that directly drive high-inertia loads (such as fans), in motors with frequent starts and stops, and in case of poorly manufactured cage windings. A continuous monitoring of IMs is needed to reduce this risk, integrated in plant-wide condition based maintenance (CBM) systems. Diverse diagnostic techniques have been proposed in the technical literature, either data-based, detecting fault-characteristic perturbations in the data collected from the IM, and model-based, observing the differences between the data collected from the actual IM and from its digital twin model. In both cases, fast and accurate IM models are needed to develop and optimize the fault diagnosis techniques. On the one hand, the finite elements approach can provide highly accurate models, but its computational cost and processing requirements are very high to be used in on-line fault diagnostic systems. On the other hand, analytical models can be much faster, but they can be very complex in case of highly asymmetrical machines, such as IMs with multiple cage faults. In this work, a new method is proposed for the analytical modelling of IMs with asymmetrical cage windings using a tensor based approach, which greatly reduces this complexity by applying routine tensor algebra to obtain the parameters of the faulty IM model from the healthy one. This winding tensor approach is explained theoretically and validated with the diagnosis of a commercial IM with multiple cage faults. 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 Inductance tensor es_ES
dc.subject Induction machines es_ES
dc.subject Fault diagnosis es_ES
dc.subject Winding asymmetries es_ES
dc.subject.classification INGENIERIA ELECTRICA es_ES
dc.title Analytical Model of Induction Machines with Multiple Cage Faults Using the Winding Tensor Approach es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/s21155076 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 Martinez-Roman, J.; Puche-Panadero, R.; Sapena-Bano, A.; Terrón-Santiago, C.; Burriel-Valencia, J.; Pineda-Sanchez, M. (2021). Analytical Model of Induction Machines with Multiple Cage Faults Using the Winding Tensor Approach. Sensors. 21(15):1-30. https://doi.org/10.3390/s21155076 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/s21155076 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 30 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 21 es_ES
dc.description.issue 15 es_ES
dc.identifier.eissn 1424-8220 es_ES
dc.identifier.pmid 34372314 es_ES
dc.identifier.pmcid PMC8347164 es_ES
dc.relation.pasarela S\445743 es_ES
dc.contributor.funder AGENCIA ESTATAL DE INVESTIGACION es_ES
dc.contributor.funder European Regional Development Fund es_ES
upv.costeAPC 2073,03 es_ES


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