Analysis of Wear Debris Through Classification
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25510%2F11%3A39883455" target="_blank" >RIV/00216275:25510/11:39883455 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Analysis of Wear Debris Through Classification
Original language description
This paper introduces a novel method of wear debris analysis through classi cation 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 ferrography is 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 classi cation of wear debris particles into several classes de ned by the origin of such particles. Unlike the earlier methods, the proposed classi cation 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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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
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
10
Pages from-to
273-283
Publisher name
Springer
Place of publication
Berlin
Event location
Gent
Event date
Aug 22, 2011
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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