Detail publikace

Analysis Wear Debris Through Classification

JURÁNEK, R. MACHALÍK, S. ZEMČÍK, P.

Originální název

Analysis Wear Debris Through Classification

Typ

článek ve sborníku mimo WoS a Scopus

Jazyk

angličtina

Originální abstrakt

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 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 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.

Klíčová slova

Wear, Wear Debris, Classification, AdaBoost, CS-LBP, LBP

Autoři

JURÁNEK, R.; MACHALÍK, S.; ZEMČÍK, P.

Rok RIV

2011

Vydáno

22. 8. 2011

Nakladatel

Springer Verlag

Místo

Heidelberg

ISBN

978-3-642-23686-0

Kniha

Proceedings of Advanced Concepts of Inteligent Vision Systems (ACIVS 2011)

Edice

Lecture Notes in Computer Science

Strany od

273

Strany do

283

Strany počet

11

BibTex

@inproceedings{BUT76367,
  author="Roman {Juránek} and Stanislav {Machalík} and Pavel {Zemčík}",
  title="Analysis Wear Debris Through Classification",
  booktitle="Proceedings of Advanced Concepts of Inteligent Vision Systems (ACIVS 2011)",
  year="2011",
  series="Lecture Notes in Computer Science",
  volume="6915",
  pages="273--283",
  publisher="Springer Verlag",
  address="Heidelberg",
  isbn="978-3-642-23686-0"
}