Multiscale analyses and characterizations of surface topographies

Brown, Christopher; Hansen, Hans Nørgaard; Xiang, Jin; Blateyron, François; Berglund, Johan; Senin, Nicola; Bartkowiak, Tomasz; Dixon, Barnali M.; Goïc, Gaëtan Le; Quinsat, Yann; Stemp, W. James; Thompson, Mary Kathryn; Ungar, Peter S.; Zahouani, E. Hassan

doi:10.1016/j.cirp.2018.06.001

Cited by 164 publications

(112 citation statements)

References 150 publications

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“…In other words, topographic features of a given size are best discernible when observed at particular scales. This phenomenon is the principle of the third approach, i.e., multiscale methods [ 3 ]. The importance of scale lies in the characterizations of physical interactions between formation process and resulted surface topography.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Surface Microgeometry Created by Electric Discharge Machining

et al. 2020

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The objective of this work is to study the geometric properties of surface topographies of hot-work tool steel created by electric discharge machining (EDM) using motif and multiscale analysis. The richness of these analyses is tested through calculating the strengths of the correlations between discharge energies and resulting surface characterization parameters, focusing on the most representative surface features—craters, and how they change with scale. Surfaces were created by EDM using estimated energies from 150 to 9468 µJ and measured by focus variation microscope. The measured topographies consist of overlapping microcraters, of which the geometry was characterized using three different analysis: conventional with ISO parameters, and motif and multiscale curvature tensor analysis. Motif analysis uses watershed segmentation which allows extraction and geometrically characterization of each crater. Curvature tensor analysis focuses on the characterization of principal curvatures and their function and their evolution with scale. Strong correlations (R2 > 0.9) were observed between craters height, diameter, area and curvature using linear and logarithmic regressions. Conventional areal parameter related to heights dispersion were found to correlate stronger using logarithmic regression. Geometric characterization of process-specific topographic formations is considered to be a natural and intuitive way of analyzing the complexity of studied surfaces. The presented approach allows extraction of information directly relating to the shape and size of topographic features of interest. In the tested conditions, the surface finish is mostly affected and potentially controlled by discharge energy at larger scales which is associated with sizes of fabricated craters.

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Section: Introductionmentioning

confidence: 99%

Analysis of Surface Microgeometry Created by Electric Discharge Machining

et al. 2020

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“…Surface topographies, appropriately characterized, can explain a variety of physical phenomena, like wear and diffusion [1,2]. ISO 25178, EUR 15178N and ASME B46.1 standardize calculations of topographic and roughness characterization parameters.…”

Section: Introductionmentioning

confidence: 99%

“…One advantage of RTI is that the measuring apparatus can be used in more hostile environments than conventional topographic measurement instruments, which are most often designed for laboratory use. Issues that need to be addressed include scales for characterizations and analyses, as well as appropriate statistics for topographic heterogeneities [2].…”

Section: Introductionmentioning

confidence: 99%

“…Conventional 3D characterization parameters (ISO 25178, EUR 15178N, and ASME B46.1) are calculated on curvatures instead of traditional heights. Multiscale analysis using a progression of different band pass filters is performed on curvature maps to find relevant scales for discriminating and correlating these surface topographies [2]. Multiscale light scattering by topographies, modeled as reflective facets, was simulated by Shipulski et al [16].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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.

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“…We imagine an infinite ensemble of surfaces (possibly infinite themselves), usually corresponding formally to a random process, which may or may not be widesense stationary. Measurement of non-stationary fractal surfaces in an interval of scales in which they do exhibit self-affinity adds its own set of difficulties [9,18]. Here we will focus on roughness generated by stationary processes-and estimation of their parameters using a finite measurement of one realization.…”

Section: Introductionmentioning

confidence: 99%

Estimation of roughness measurement bias originating from background subtraction

Nečas

Klapetek

Valtr

2020

Meas. Sci. Technol.

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When measuring the roughness of rough surfaces, the limited sizes of scanned areas lead to its systematic underestimation. Levelling by polynomials and other filtering used in real-world processing of atomic force microscopy data increases this bias considerably. Here a framework is developed providing explicit expressions for the bias of squared mean square roughness in the case of levelling by fitting a model background function using linear least squares. The framework is then applied to polynomial levelling, for both one-dimensional and two-dimensional data processing, and basic models of surface autocorrelation function, Gaussian and exponential. Several other common scenarios are covered as well, including median levelling, intermediate Gaussian-exponential autocorrelation model and frequency space filtering. Application of the results to other quantities, such as Rq, Sq, Ra and Sa is discussed. The results are summarized in overview plots covering a range of autocorrelation functions and polynomial degrees, which allow graphical estimation of the bias.

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Multiscale analyses and characterizations of surface topographies

Cited by 164 publications

References 150 publications

Analysis of Surface Microgeometry Created by Electric Discharge Machining

Analysis of Surface Microgeometry Created by Electric Discharge Machining

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

Estimation of roughness measurement bias originating from background subtraction

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