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dc.contributor.author | Jaen-Cuellar, Arturo Yosimar | es_ES |
dc.contributor.author | Osornio-Ríos, Roque Alfredo | es_ES |
dc.contributor.author | Trejo-Hernández, Miguel | es_ES |
dc.contributor.author | Zamudio-Ramírez, Israel | es_ES |
dc.contributor.author | Díaz-Saldaña, Geovanni | es_ES |
dc.contributor.author | Pacheco-Guerrero, José Pablo | es_ES |
dc.contributor.author | Antonino-Daviu, Jose Alfonso | es_ES |
dc.date.accessioned | 2023-04-18T18:00:44Z | |
dc.date.available | 2023-04-18T18:00:44Z | |
dc.date.issued | 2021-12 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/192821 | |
dc.description.abstract | [EN] The computer numerical control (CNC) machine has recently taken a fundamental role in the manufacturing industry, which is primordial for the economic development of many countries. Current high quality production standards, along with the requirement for maximum economic benefits demand the use of tool condition monitoring (TCM) systems able to monitor and diagnose cutting tool wearing. Current TCM methodologies mainly rely on vibration signals, cutting force signals, acoustic emission (AE) signals, which have the common drawback of requiring the in-stallation of sensors near the working area, a factor that limits their application under practical terms. Moreover, as machining processes require the optimal tuning of cutting parameters, novel methodologies must be able to perform the diagnosis under a variation of cutting parameters. This paper proposes a novel non-invasive method capable to automatically diagnose cutting tool wearing in CNC machines under the variation of cutting speed, and feed rate cutting parameters. The proposal relies on the sensor information fusion of spindle-motor stray flux and current signals by means of statistical and non-statistical time-domain parameters, which are then reduced by means of a linear discriminant analysis (LDA), and then a feed-forward neural network is used to automatically classify the level of wear on the cutting tool. The proposal is validated with a Fanuc Oi mate Computer Numeric Control (CNC) turning machine for three different cutting tool wearing levels and different cutting speed, and feed rate values. | es_ES |
dc.description.sponsorship | This work was supported by the Spanish 'Ministerio de Ciencia Innovacion y Universidades' and FEDER program in the framework of the 'Proyectos de I + D de Generacion de Conocimiento del Programa Estatal de Generacion de Conocimiento y Fortalecimiento Cientifico y Tecnologico del Sistema de I + D + i, Subprograma Estatal de Generacion de Conocimiento' (ref: PGC2018-095747-B-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 | Condition monitoring | es_ES |
dc.subject | Tool wear | es_ES |
dc.subject | Cutting speed | es_ES |
dc.subject | Feed rate | es_ES |
dc.subject | Sensors fusion | es_ES |
dc.subject | Stray flux | es_ES |
dc.subject | Ac current | es_ES |
dc.subject.classification | INGENIERIA ELECTRICA | es_ES |
dc.title | System for Tool-Wear Condition Monitoring in CNC Machines under Variations of Cutting Parameter Based on Fusion Stray Flux-Current Processing | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3390/s21248431 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-095747-B-I00/ES/TECNOLOGIAS AVANZADAS BASADAS EN EL ANALISIS DEL FLUJO DE DISPERSION EN REGIMEN TRANSITORIO PARA EL DIAGNOSTICO PRECOZ DE ANOMALIAS ELECTROMECANICAS EN MOTORES ELECTRICOS/ | 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.description.bibliographicCitation | Jaen-Cuellar, AY.; Osornio-Ríos, RA.; Trejo-Hernández, M.; Zamudio-Ramírez, I.; Díaz-Saldaña, G.; Pacheco-Guerrero, JP.; Antonino-Daviu, JA. (2021). System for Tool-Wear Condition Monitoring in CNC Machines under Variations of Cutting Parameter Based on Fusion Stray Flux-Current Processing. Sensors. 21(24):1-23. https://doi.org/10.3390/s21248431 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3390/s21248431 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 23 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 21 | es_ES |
dc.description.issue | 24 | es_ES |
dc.identifier.eissn | 1424-8220 | es_ES |
dc.identifier.pmid | 34960525 | es_ES |
dc.identifier.pmcid | PMC8705382 | es_ES |
dc.relation.pasarela | S\452134 | es_ES |
dc.contributor.funder | AGENCIA ESTATAL DE INVESTIGACION | es_ES |
dc.contributor.funder | European Regional Development Fund | es_ES |