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.

Keywords

Tribology Third body dry friction Image processing

Domains

Chemical and Process Engineering Signal and Image Processing Computer Vision and Pattern Recognition [cs.CV]

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

Submitted on : Thursday, March 3, 2022-12:23:08 PM

Last modification on : Tuesday, September 17, 2024-3:45:01 PM

Dates and versions

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

Identifiers

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

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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