dc.contributor.author | Fernández Cavero, Vanesa | |
dc.contributor.author | Pons Llinares, Joan | |
dc.contributor.author | Duque Pérez, Óscar | |
dc.contributor.author | Morinigo Sotelo, Daniel | |
dc.date.accessioned | 2025-01-16T12:01:46Z | |
dc.date.available | 2025-01-16T12:01:46Z | |
dc.date.issued | 2021-03 | |
dc.identifier.issn | 0093-9994 | |
dc.identifier.uri | http://hdl.handle.net/10259/9945 | |
dc.description.abstract | Fault detection in induction motors powered by inverters operating in nonstationary regimes remains a challenge. The trajectory in the time–frequency plane of harmonics related to broken rotor bar develops very in proximity to the path described by the fundamental component. In addition, their energy is much lower than the amplitude of the first harmonic. These two characteristics make it challenging to observe them. The Dragon Transform (DT), here presented, is developed to overcome the described problem. In this article, the DT is assessed with nonlinear inverter-fed startups, where its high time and frequency resolutions facilitate the monitoring of fault harmonics even with highly adjacent trajectories to the first harmonic path. | en |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | es |
dc.publisher | Institute of Electrical and Electronics Engineers | es |
dc.relation.ispartof | IEEE Transactions on Industry Applications. 2021, V. 57, n. 3, p. 2559-2568 | es |
dc.subject | Fault detection | en |
dc.subject | Induction motors (IM) | en |
dc.subject | Inverters | en |
dc.subject | Rotors | en |
dc.subject | Time-frequency domain analysis | en |
dc.subject.other | Electrotecnia | es |
dc.subject.other | Electrical engineering | en |
dc.subject.other | Ingeniería mecánica | es |
dc.subject.other | Mechanical engineering | en |
dc.title | Detection of Broken Rotor Bars in Nonlinear Startups of Inverter-Fed Induction Motors | en |
dc.type | info:eu-repo/semantics/article | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.relation.publisherversion | https://doi.org/10.1109/TIA.2021.3066317 | es |
dc.identifier.doi | 10.1109/TIA.2021.3066317 | |
dc.identifier.essn | 1939-9367 | |
dc.journal.title | IEEE Transactions on Industry Applications | es |
dc.volume.number | 57 | es |
dc.issue.number | 3 | es |
dc.page.initial | 2559 | es |
dc.page.final | 2568 | es |
dc.type.hasVersion | info:eu-repo/semantics/acceptedVersion | es |
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