Skip to Main content Skip to Navigation
Journal articles

Assessing the discriminating power of roughness parameters using a roughness databank

Abstract : This article presents a methodology based on the use of a surface databank, which aims at assessing the discriminating power of 3D roughness parameters. The presented databank is composed of fourteen different sets of surfaces belonging to two main tribological categories: integrity and functionality. Each set of surface is composed of two classes, called A and B. These classes are obtained by varying process conditions or study parameters. The proposed methodology is first thoroughly described in the general case of comparing two classes of one set of 3D surfaces. Then, sandblasted surfaces are used as an example before applying the methodology to the entire database.
Complete list of metadata

https://hal.utc.fr/hal-02968734
Contributor : Julie MARTEAU Connect in order to contact the contributor
Submitted on : Friday, October 16, 2020 - 8:52:03 AM
Last modification on : Thursday, April 7, 2022 - 4:00:09 AM

Identifiers

Citation

Maxence Bigerelle, Julie Marteau, François Blateyron. Assessing the discriminating power of roughness parameters using a roughness databank. Surface Topography: Metrology and Properties, IOP Publishing 2017, 5 (2), pp.025002. ⟨10.1088/2051-672X/aa6e04⟩. ⟨hal-02968734⟩

Share

Metrics

Record views

18