Unsupervised machine learning for anomaly detection in wind turbine converters

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dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.advisorPirttioja, Teppo
dc.contributor.authorStikhin, Oleg
dc.contributor.schoolSähkötekniikan korkeakoulufi
dc.contributor.supervisorHinkkanen, Marko
dc.date.accessioned2019-06-23T15:08:13Z
dc.date.available2019-06-23T15:08:13Z
dc.date.issued2019-06-17
dc.format.extent56 + 3
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/38969
dc.identifier.urnURN:NBN:fi:aalto-201906234035
dc.language.isoenen
dc.locationP1fi
dc.programmeAEE - Master's Programme in Automation and Electrical Engineering (TS2013)fi
dc.programme.majorElectrical Power and Energy Engineeringfi
dc.programme.mcodeELEC3024fi
dc.subject.keywordanomaly detectionen
dc.subject.keywordunsupervised machine learningen
dc.subject.keyworddata analysisen
dc.subject.keywordwind turbine converteren
dc.titleUnsupervised machine learning for anomaly detection in wind turbine convertersen
dc.titleOövervakad maskininlärning för avvikelsedetektion i omriktare för vindturbinersv
dc.typeG2 Pro gradu, diplomityöfi
dc.type.ontasotMaster's thesisen
dc.type.ontasotDiplomityöfi
local.aalto.electroniconlyyes
local.aalto.openaccessno

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