Show simple item record

dc.contributor.authorRogne, Olav
dc.date.accessioned2017-09-13T07:09:46Z
dc.date.available2017-09-13T07:09:46Z
dc.date.issued2017
dc.identifier.urihttp://hdl.handle.net/11250/2454397
dc.descriptionMasteroppgave fornybar energi ENE500 - Universitetet i Agder 2017nb_NO
dc.description.abstractThe report deals with fault detection and diagnosis of roller element bearings. Vibration and shaft position sensor data combined with three algorithms are tested to determine which combination may detect bearing faults early and reliably. Experimental data from an accelerated life-time test is used to verify the performance. Results show that the vibration signal combined with a fast spectral correlation algorithm yields the most reliable diagnosis.nb_NO
dc.language.isonobnb_NO
dc.publisherUniversitetet i Agder ; University of Agdernb_NO
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.subjectENE500nb_NO
dc.subjectKraftstasjonnb_NO
dc.subjectVibrasjonsanalysenb_NO
dc.subjectKulelagernb_NO
dc.titleVibrasjonsanalyse : Feildeteksjon i Kulelager: Prosessering av Vibrasjonssignaler, Algoritmer, og Envelope Spektrumnb_NO
dc.typeMaster thesisnb_NO
dc.subject.nsiVDP::Teknologi: 500::Maskinfag: 570nb_NO
dc.source.pagenumberX, 67, [5] s.nb_NO


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal