dc.contributor.author | Moríñigo Sotelo, Daniel | |
dc.contributor.author | Romero Troncoso, René de Jesús | |
dc.contributor.author | Panagiotou, P. A. | |
dc.contributor.author | Antonino Daviu, Jose A. | |
dc.contributor.author | Gyftakis, K. N. | |
dc.date.accessioned | 2024-01-20T16:44:36Z | |
dc.date.available | 2024-01-20T16:44:36Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | IEEE Transactions on Industry Applications, vol. 54, no. 2, pp. 1224-1234, March-April 2018 | es |
dc.identifier.issn | 1939-9367 | es |
dc.identifier.uri | https://uvadoc.uva.es/handle/10324/64786 | |
dc.description.abstract | Induction motors are used in a variety of industrial applications where frequent startup cycles are required. In those cases, it is necessary to apply sophisticated signal processing analysis methods in order to reliably follow the time evolution of the fault-related harmonics in the signal.In this paper, the zero-sequence current (ZSC) is analysed using the high-resolution spectral method of multiple signal
classification (MUSIC). The analysis of the ZSC signal has proved to have several advantages over the analysis of a single-phase current waveform. The method is validated through simulation and experimental results. The simulations are carried out for a 1.1 MW and a 4kW induction motors under
finite element analysis (FEA). Experimentation is performed on a healthy motor, a motor with one broken rotor bar, and a motor with two broken rotor bars. The analysis results are satisfactory since the proposed methodology reliably detects the broken rotor bar fault and its severity, both during transient
and steady state operation of the induction motor. | es |
dc.format.mimetype | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | The IEEE | es |
dc.rights.accessRights | info:eu-repo/semantics/restrictedAccess | es |
dc.subject.classification | Broken bar | es |
dc.subject.classification | Fault diagnosis | es |
dc.subject.classification | Induction motor | es |
dc.subject.classification | MUSIC | es |
dc.subject.classification | ZSC | es |
dc.title | Reliable Detection of Rotor Bars Breakage in Induction Motors via MUSIC and ZSC | es |
dc.type | info:eu-repo/semantics/article | es |
dc.rights.holder | The IEEE | es |
dc.identifier.doi | 10.1109/TIA.2017.2764846 | es |
dc.relation.publisherversion | https://ieeexplore.ieee.org/document/8074748 | es |
dc.identifier.publicationfirstpage | 1124 | es |
dc.identifier.publicationissue | 2 | es |
dc.identifier.publicationlastpage | 1234 | es |
dc.identifier.publicationvolume | 54 | es |
dc.peerreviewed | SI | es |
dc.description.project | This work was supported in part by the Spanish ‘Ministerio de Economía y Competitividad’ (MINECO) and FEDER program in the framework of the ‘Proyectos I+D del Subprograma de Generación de Conocimiento, Programa Estatal de Fomento de la Investigación Científica y Técnica de Excelencia’ (ref: DPI2014-52842-P) | es |
dc.type.hasVersion | info:eu-repo/semantics/draft | es |