Analysis Wear Debris Through Classification

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F11%3APU96070" target="_blank" >RIV/00216305:26230/11:PU96070 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Analysis Wear Debris Through Classification
Original language description
This paper introduces a novel method of wear debris analysis through classification of the particles based on machine learning. Wear debris consists of particles of metal found in e.g. lubricant oils used in engineering equipment. Analytical ferrographyis one of methods for wear debris analysis and it is very important for early detection or even prevention of failures in engineering equipment, such as combustion engines, gearboxes, etc. The proposed novel method relies on classification of wear debris particles into several classes defined by the origin of such particles. Unlike the earlier methods, the proposed classification approach is based on visual similarity of the particles and supervised machine learning. The paper describes the method itself, demonstrates its experimental results, and draws conclusions.
Czech name
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Czech description
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Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of Advanced Concepts of Inteligent Vision Systems (ACIVS 2011)
ISBN
978-3-642-23686-0
ISSN
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e-ISSN
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Number of pages
11
Pages from-to
273-283
Publisher name
Springer Verlag
Place of publication
Heidelberg
Event location
Het Pand, Ghent, Belgium
Event date
Aug 22, 2011
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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