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Volume 13
Issue 5
10.3390/ma13051024
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Open AccessArticle

Surface Reflectance: An Optical Method for Multiscale Curvature Characterization of Wear on Ceramic–Metal Composites

by
Julie Lemesle
1,
Frederic Robache
1,
Gaetan Le Goic
2,
Alamin Mansouri
2,
Christopher A. Brown
3 and
Maxence Bigerelle
1,*
1
CNRS UMR 8201—LAMIH—Laboratoire d’Automatique, de Mécanique et d’Informatique Industrielles et Humaines, Université Polytechnique Hauts-de-France, F–59313 Valenciennes, France
2
EA 7535—ImViA—Laboratoire Imagerie et Vision Artificielle, Université de Bourgogne, 21078 Dijon CEDEX, France
3
Surface Metrology Laboratory, Worcester Polytechnic Institute, Worcester, MA 01609, USA
*
Author to whom correspondence should be addressed.
Materials 2020, 13(5), 1024; https://doi.org/10.3390/ma13051024
Received: 22 January 2020 / Revised: 14 February 2020 / Accepted: 24 February 2020 / Published: 25 February 2020
(This article belongs to the Special Issue Tribology: Friction and Wear of Engineering Materials)
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Abstract

Surface gradient characterization by light reflectance (SGCLR) is used for the first time for multiscale curvature calculations and discrimination of worn surfaces on six damaged ceramic–metal composites. Measurements are made using reflectance transformation imaging (RTI). Slope and curvature maps, generated from RTI, are analyzed instead of heights. From multiscale decompositions, bootstrapping, and analysis of variance (ANOVA), a strong correlation (R² = 0.90) is found between the density of furrows of Mehlum curvatures, with a band pass filter at 5.4 µm, present in ceramic grains and their mechanical properties. A strong correlation is found between the mean curvatures of the metal and the ceramics, with a high pass filter at 1286 µm. View Full-Text
Keywords: roughness; metal matrix composite; wear; reflectance transformation imaging; peak curvature roughness; metal matrix composite; wear; reflectance transformation imaging; peak curvature
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
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MDPI and ACS Style

Lemesle, J.; Robache, F.; Le Goic, G.; Mansouri, A.; Brown, C.A.; Bigerelle, M. Surface Reflectance: An Optical Method for Multiscale Curvature Characterization of Wear on Ceramic–Metal Composites. Materials 2020, 13, 1024. https://doi.org/10.3390/ma13051024

AMA Style

Lemesle J, Robache F, Le Goic G, Mansouri A, Brown CA, Bigerelle M. Surface Reflectance: An Optical Method for Multiscale Curvature Characterization of Wear on Ceramic–Metal Composites. Materials. 2020; 13(5):1024. https://doi.org/10.3390/ma13051024

Chicago/Turabian Style

Lemesle, Julie; Robache, Frederic; Le Goic, Gaetan; Mansouri, Alamin; Brown, Christopher A.; Bigerelle, Maxence. 2020. "Surface Reflectance: An Optical Method for Multiscale Curvature Characterization of Wear on Ceramic–Metal Composites" Materials 13, no. 5: 1024. https://doi.org/10.3390/ma13051024

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