Simple record

dc.rights.licenseAttribution 4.0 International*
dc.contributor.authorAizpurua Unanue, Jose Ignacio
dc.contributor.authorPenalba, Markel
dc.contributor.authorKirillova , Natalia
dc.contributor.authorAlcorta Andoaga, Illart
dc.contributor.otherLekube, Jon
dc.contributor.otherMarina, Dorleta
dc.date.accessioned2022-01-31T12:27:53Z
dc.date.available2022-01-31T12:27:53Z
dc.date.issued2021
dc.identifier.otherhttps://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=166983en
dc.identifier.urihttp://hdl.handle.net/20.500.11984/5450
dc.description.abstractThe Mutriku Wave Power Plant (WPP) is a wave energy conversion plant based on the oscillating water column technology (OWC). The energy production and the health state of the plant are directly dependent on the sea-state conditions along with component-specific operation efficiency and failure modes. In this context, this paper presents a preliminary air turbine conditional anomaly detection (CAD) approach for condition monitoring of the Mutriku WPP. The proposed approach is developed based on an ensemble of Gaussian Mixture models, where each anomaly detection model learns the expected air turbine operation conditioned on specific seastates information. Early results show that the integration of sea-states in the anomaly detection learning process improves the discrimination capability of the anomaly detection model.en
dc.language.isoengen
dc.rights© The Prognostics and Health Management Societyen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleBuilding an Air Turbine Conditional Anomaly Detection Approach for Wave Power Plantsen
dc.typeinfo:eu-repo/semantics/conferenceObjecten
dcterms.accessRightsinfo:eu-repo/semantics/openAccessen
dcterms.sourceProceedings of the Annual Conference of the PHM Societyen
dc.description.versioninfo:eu-repo/semantics/publishedVersionen
local.contributor.groupMecánica de fluidoses
local.description.peerreviewedtrueen
local.identifier.doihttps://doi.org/10.36001/phmconf.2021.v13i1.3028en
local.contributor.otherinstitutionIkerbasquees
local.contributor.otherinstitutionBasque Energy Agencyes
local.contributor.otherinstitutionBiscay Marine Energy Platformes
local.source.detailsVol. 13. N. 1, 2021en


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Simple record

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