Towards a quantitative characterization of wear particles using image analysis and machine learning Paper - Mines Saint-Étienne Access content directly
Conference Papers Year : 2021

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

Abstract

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.
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Dates and versions

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

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Cite

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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