An Industrial Internet Application for Real-Time Fault Diagnosis in Industrial Motors

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dc.contributor.authorLangarica Chavira, Saúl Alberto
dc.contributor.authorRuffelmacher, Christian
dc.contributor.authorNuñez, Felipe
dc.date.accessioned2022-05-18T14:04:53Z
dc.date.available2022-05-18T14:04:53Z
dc.date.issued2020
dc.description.abstractBeing able to detect, identify, and diagnose a fault is a key feature of industrial supervision systems, which enables advance asset management, in particular, predictive maintenance, which greatly increases efficiency and productivity. In this paper, an Industrial Internet app for real-time fault detection and diagnosis is implemented and tested in a pilot scale industrial motor. Real-time fault detection and identification is based on dynamic incremental principal component analysis (DIPCA) and reconstruction-based contribution (RBC). When the analysis indicates that one of the vibration measurements is responsible for the fault, a convolutional neural network (CNN) is used to identify the unbalance or bearing fault type. The application was evaluated in its three functionalities: fault detection, fault identification, and fault identification of vibration-related faults, yielding a fault detection rate over 99%, a false alarm rate below 5%, and an identification accuracy over 90%.
dc.fuente.origenIEEE
dc.identifier.doi10.1109/TASE.2019.2913628
dc.identifier.eissn1558-3783
dc.identifier.issn1545-5955
dc.identifier.urihttps://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8715407
dc.identifier.urihttps://doi.org/10.1109/TASE.2019.2913628
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/64130
dc.identifier.wosidWOS:000507640900022
dc.information.autorucEscuela de ingeniería ; Langarica Chavira, Saúl Alberto ; S/I ; 222832
dc.issue.numero1
dc.language.isoen
dc.nota.accesoContenido completo
dc.pagina.final295
dc.pagina.inicio284
dc.publisherIEEE
dc.revistaIEEE Transactions on Automation Science and Engineering
dc.rightsacceso restringido
dc.subjectFault diagnosis
dc.subjectReal-time systems
dc.subjectFault detection
dc.subjectMaintenance engineering
dc.subjectPrincipal component analysis
dc.subjectProductivity
dc.subjectSignal processing algorithms
dc.subject.ods06 Clean Water and Sanitation
dc.subject.odspa06 Agua limpia y saneamiento
dc.titleAn Industrial Internet Application for Real-Time Fault Diagnosis in Industrial Motorses_ES
dc.typeartículo
dc.volumen17
sipa.codpersvinculados222832
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