Towards a quantitative characterization of wear particles using image analysis and machine learning Paper

The current work proposes to move towards a quantitative characterization through advanced image processing. Four steps are followed: pin-on-disk experiments (to generate third body), image acquisition of third body particles, image processing, and extraction of quantitative characteristics of third body particles.

Mots clés

Tribology Third body dry friction Image processing

Domaines

Génie des procédés Traitement du signal et de l'image [eess.SP] Vision par ordinateur et reconnaissance de formes [cs.CV]

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https://hal-emse.ccsd.cnrs.fr/emse-03595709

Soumis le : jeudi 3 mars 2022-12:23:08

Dernière modification le : jeudi 1 février 2024-14:21:58

Dates et versions

emse-03595709 , version 1 (03-03-2022)

Identifiants

HAL Id : emse-03595709 , version 1
DOI : 10.1117/12.2587647

Citer

Alizée Bouchot, Amandine Ferrieux-Paquet, Sylvie Descartes, Guilhem Mollon, Johan Debayle. Towards a quantitative characterization of wear particles using image analysis and machine learning Paper. QCAV 2021 - Fifteenth International Conference on Quality Control by Artificial Vision, May 2021, Tokushima, Japan. pp.1179416, ⟨10.1117/12.2587647⟩. ⟨emse-03595709⟩

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