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Bearing fault classification based on minimum volume ellipsoid feature extraction
Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
Department of Informatics and Communications Technology, Technical Educational Institute of Epirus, 47100 Artas, Kostakioi.
Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.ORCID-id: 0000-0003-0126-1897
2013 (engelsk)Inngår i: 2013 IEEE Multiconference on Systems and Control (MSC), Hyderabad, India, August, 28-30, 2013, 2013, s. 1177-1182Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

This article presents a novel fault classification and diagnosis technique for bearings based on a Minimum Volume Ellipsoid (MVE) method for feature extraction. Data from two accelerometers located at two different sights of the test bed are combined to create a two dimensional representation and the feature extraction stage condenses that information using an ellipsoid description. The proposed features feed a simple non-linear classifier which separates almost perfectly between normal and faulty conditions, with also very high diagnostic accuracy between the faulty classes. The obtained results suggest that this novel representation can be used within a condition monitoring system.

sted, utgiver, år, opplag, sider
2013. s. 1177-1182
HSV kategori
Forskningsprogram
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Identifikatorer
URN: urn:nbn:se:ltu:diva-40649Scopus ID: 2-s2.0-84902248068Lokal ID: fd795f8a-8219-4627-b1cf-ce13c560c335OAI: oai:DiVA.org:ltu-40649DiVA, id: diva2:1014170
Konferanse
IEEE Multi-Conference on Systems and Control : 28/08/2013 - 30/08/2013
Prosjekter
Fault Detection in Bearings
Merknad
Godkänd; 2013; 20130515 (geonik)Tilgjengelig fra: 2016-10-03 Laget: 2016-10-03 Sist oppdatert: 2023-10-06bibliografisk kontrollert

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Mustafa, Mohammed ObaidNikolakopoulos, George

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