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dc.contributor.author | Ruiz-Sarrió, José Enrique | es_ES |
dc.contributor.author | Antonino-Daviu, J. | es_ES |
dc.contributor.author | Martis, Claudia | es_ES |
dc.date.accessioned | 2024-11-13T19:13:18Z | |
dc.date.available | 2024-11-13T19:13:18Z | |
dc.date.issued | 2024-10-29 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/211737 | |
dc.description.abstract | [EN] Bearings are the most vulnerable component in low-voltage induction motors from a maintenance standpoint. Vibration monitoring is the benchmark technique for identifying mechanical faults in rotating machinery, including the diagnosis of bearing defects. The study of different bearing fault phenomena under induction motor transient conditions offers interesting capabilities to enhance classic fault detection techniques. This study analyzes the low-frequency localized bearing fault signatures in both the inner and outer races during the start-up and steady-state operation of inverter-fed and line-started induction motors. For this aim, the classic vibration envelope spectrum technique is explored in the time¿frequency domain by using a simple, resampling-free, Short Time Fourier Transform (STFT) and a band-pass filtering stage. The vibration data are acquired in the motor housing in the radial direction for different load points. In addition, two different localized defect sizes are considered to explore the influence of the defect width. The analysis of extracted low-frequency characteristic frequencies conducted in this study demonstrates the feasibility of detecting early-stage localized bearing defects in induction motors across various operating conditions and actuation modes. | es_ES |
dc.description.sponsorship | This research was funded in part by the European Commission (HORIZON program) within the context of the DITARTIS Project ( Network of Excellence in Digital Technologies and AI Solutions for Electromechanical and Power Systems Applications ) under the call HORIZONWIDERA-2021-ACCESS-03 (Grant Number 101079242), and in part by the Spanish Ministerio de Ciencia e Innovación , Agencia Estatal de Investigación and FEDER program in the framework of the Proyectos de Generación de Conocimiento 2021 of the Programa Estatal para Impulsar la Investigación Científico-Técnica y su Transferencia , belonging to the Plan Estatal de Investigación Científica, Técnica y de Innovación 2021 2023 (ref: PID2021-122343OB-I00). | 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 | AC machines | es_ES |
dc.subject | Vibration | es_ES |
dc.subject | Bearing | es_ES |
dc.subject | Fault diagnosis | es_ES |
dc.subject.classification | INGENIERIA ELECTRICA | es_ES |
dc.title | Localized Bearing Fault Analysis for Different Induction Machine Start-Up Modes via Vibration Time Frequency Envelope Spectrum | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3390/s24216935 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-122343OB-I00/ES/SENSORES INTELIGENTES BASADOS EN EL ANALISIS AVANZADO DE CORRIENTES Y FLUJO DE DISPERSION PARA LA MONITORIZACION FIABLE DE LA CONDICION DE MOTORES ELECTRICOS/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/HE/101079242/EU/NETWORK OF EXCELLENCE IN DIGITAL TECHNOLOGIES AND AI SOLUTIONS FOR ELECTROMECHANICAL AND POWER SYSTEMS APPLICATIONS/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Ingeniería Eléctrica - Departament d'Enginyeria Elèctrica | es_ES |
dc.description.bibliographicCitation | Ruiz-Sarrió, JE.; Antonino-Daviu, J.; Martis, C. (2024). Localized Bearing Fault Analysis for Different Induction Machine Start-Up Modes via Vibration Time Frequency Envelope Spectrum. Sensors. 24(21). https://doi.org/10.3390/s24216935 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3390/s24216935 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 24 | es_ES |
dc.description.issue | 21 | es_ES |
dc.identifier.eissn | 1424-8220 | es_ES |
dc.relation.pasarela | S\531277 | es_ES |
dc.contributor.funder | AGENCIA ESTATAL DE INVESTIGACION | es_ES |
dc.contributor.funder | European Regional Development Fund | es_ES |
dc.contributor.funder | COMISION DE LAS COMUNIDADES EUROPEA | es_ES |