Analysis of Wear Debris Through Classification

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Analysis of Wear Debris Through Classification

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Analysis of Wear Debris Through Classification

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2011

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

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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Počet stran výsledku

10

Strana od-do

273-283

Název nakladatele

Springer

Místo vydání

Berlin

Místo konání akce

Gent

Datum konání akce

22. 8. 2011

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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