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dc.contributor.authorPizza, Gianmarco-
dc.contributor.authorNotaristefano, Antonio-
dc.contributor.authorFabbri, Gregory Sean-
dc.contributor.authorGoren Huber, Lilach-
dc.date.accessioned2021-02-04T11:13:46Z-
dc.date.available2021-02-04T11:13:46Z-
dc.date.issued2020-06-08-
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/21546-
dc.description.abstractPredictive maintenance is a key element for lowering Operation and Maintenance (O&M) costs of wind turbines. Predictive maintenance models are usually based on drivetrain vibration data or operational timeseries from the Supervisory Control And Data Acquisition (SCADA) system, while readily available alarms and warnings from the SCADA system are typically not utilized. In this work we present a novel Artificial Intelligence (AI) based approach for early fault detection of wind turbines using alarms and warnings from the SCADA system.de_CH
dc.language.isoende_CH
dc.publisherWindEuropede_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectFault detectionde_CH
dc.subjectPredictive maintenancede_CH
dc.subjectArtificial intelligencede_CH
dc.subjectMachine learningde_CH
dc.subjectWind turbinesde_CH
dc.subjectSCADA datade_CH
dc.subjectError logsde_CH
dc.subject.ddc006: Spezielle Computerverfahrende_CH
dc.subject.ddc620: Ingenieurwesende_CH
dc.titleAn AI-based fault detection model using alarms and warnings from the SCADA systemde_CH
dc.typeKonferenz: Posterde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Datenanalyse und Prozessdesign (IDP)de_CH
zhaw.conference.detailsWindEurope Technology Workshop 2020 : Resource Assessment & Analysis of Operating Wind Farms, online, 8-11 June 2020de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewPeer review (Abstract)de_CH
zhaw.title.proceedingsProceedings of the WindEurope Technology Workshop 2020de_CH
zhaw.funding.zhawMachine Learning Based Fault Detection for Wind Turbinesde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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Pizza, G., Notaristefano, A., Fabbri, G. S., & Goren Huber, L. (2020, June 8). An AI-based fault detection model using alarms and warnings from the SCADA system. Proceedings of the WindEurope Technology Workshop 2020.
Pizza, G. et al. (2020) ‘An AI-based fault detection model using alarms and warnings from the SCADA system’, in Proceedings of the WindEurope Technology Workshop 2020. WindEurope.
G. Pizza, A. Notaristefano, G. S. Fabbri, and L. Goren Huber, “An AI-based fault detection model using alarms and warnings from the SCADA system,” in Proceedings of the WindEurope Technology Workshop 2020, Jun. 2020.
PIZZA, Gianmarco, Antonio NOTARISTEFANO, Gregory Sean FABBRI und Lilach GOREN HUBER, 2020. An AI-based fault detection model using alarms and warnings from the SCADA system. In: Proceedings of the WindEurope Technology Workshop 2020. Conference poster. WindEurope. 8 Juni 2020
Pizza, Gianmarco, Antonio Notaristefano, Gregory Sean Fabbri, and Lilach Goren Huber. 2020. “An AI-Based Fault Detection Model Using Alarms and Warnings from the SCADA System.” Conference poster. In Proceedings of the WindEurope Technology Workshop 2020. WindEurope.
Pizza, Gianmarco, et al. “An AI-Based Fault Detection Model Using Alarms and Warnings from the SCADA System.” Proceedings of the WindEurope Technology Workshop 2020, WindEurope, 2020.


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