dc.contributor.author | Rogne, Olav | |
dc.date.accessioned | 2017-09-13T07:09:46Z | |
dc.date.available | 2017-09-13T07:09:46Z | |
dc.date.issued | 2017 | |
dc.identifier.uri | http://hdl.handle.net/11250/2454397 | |
dc.description | Masteroppgave fornybar energi ENE500 - Universitetet i Agder 2017 | nb_NO |
dc.description.abstract | The 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.iso | nob | nb_NO |
dc.publisher | Universitetet i Agder ; University of Agder | nb_NO |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no | * |
dc.subject | ENE500 | nb_NO |
dc.subject | Kraftstasjon | nb_NO |
dc.subject | Vibrasjonsanalyse | nb_NO |
dc.subject | Kulelager | nb_NO |
dc.title | Vibrasjonsanalyse : Feildeteksjon i Kulelager: Prosessering av Vibrasjonssignaler, Algoritmer, og Envelope Spektrum | nb_NO |
dc.type | Master thesis | nb_NO |
dc.subject.nsi | VDP::Teknologi: 500::Maskinfag: 570 | nb_NO |
dc.source.pagenumber | X, 67, [5] s. | nb_NO |