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dc.rights.licenseAttribution 4.0 International*
dc.contributor.authorIzagirre Aizpitarte, Unai
dc.contributor.authorAndonegui Artegui, Imanol
dc.contributor.authorEgea Cáceres, Aritz Imanol Alejandro
dc.contributor.authorZurutuza Ortega, Urko
dc.date.accessioned2020-11-20T10:27:13Z
dc.date.available2020-11-20T10:27:13Z
dc.date.issued2020
dc.identifier.issn2076-3417en
dc.identifier.otherhttps://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=161579en
dc.identifier.urihttp://hdl.handle.net/20.500.11984/1927
dc.description.abstractThis manuscript focuses on methodological and technological advances in the field of health assessment and predictive maintenance for industrial robots. We propose a non-intrusive methodology for industrial robot joint health assessment. Torque sensor data is used to create a digital signature given a defined trajectory and load combination. The signature of each individual robot is later used to diagnose mechanical deterioration. We prove the robustness and reliability of the methodology in a real industrial use case scenario. Then, an in depth mechanical inspection is carried out in order to identify the root cause of the failure diagnosed in this article. The proposed methodology is useful for medium and long term health assessment for industrial robots working in assembly lines, where years of almost uninterrupted work can cause irreversible damage.en
dc.language.isoengen
dc.publisherMDPI AGen
dc.rights© 2020 by the authors. Licensee MDPI, Basel, Switzerlanden
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectPHMen
dc.subjectindustrial robotsen
dc.subjectIndustry 4.0en
dc.subjectpredictive maintenanceen
dc.titleA methodology and experimental implementation for industrial robot health assessment via torque signature analysisen
dc.typeinfo:eu-repo/semantics/articleen
dcterms.accessRightsinfo:eu-repo/semantics/openAccessen
dcterms.sourceApplied Sciencesen
dc.description.versioninfo:eu-repo/semantics/publishedVersionen
local.contributor.groupAnálisis de datos y ciberseguridades
local.contributor.groupRobótica y Automatizaciónes
local.description.peerreviewedtrueen
local.identifier.doihttps://doi.org/10.3390/app10217883en
local.rights.publicationfeeAPCen
local.rights.publicationfeeamount1692 EUR (1800 CHF)en
local.source.detailsVol. 10. N.21. N. Artículo 7883, 2020en


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Except where otherwise noted, this item's license is described as Attribution 4.0 International