The objectives of this work are to demonstrate the use of multiscale curvature tensor analysis for characterizing surfaces of stainless steel created by micro-electrical discharge machining (μEDM), and to study the strengths of the correlations between discharge energies and resulting surface curvatures (i.e., principal, Gaussian, or mean curvatures) and how they change with scale. Surfaces were created by μEDM techniques using energies from 18 nJ to 16,500 nJ and measured by confocal microscope. The curvature tensor T is calculated using three proximate unit vectors normal to the surface. The multiscale effect is achieved by changing the size of the sampling interval for the estimation of the normals. Normals are estimated from regular meshes by applying a covariance matrix method. Strong correlations (R2 > 0.9) are observed between calculated principal maximal and minimal as well as mean and Gaussian curvatures and discharge energies. This method allows detailed analysis of the nature of surface topographies and suggests that different formation processes governed the creation of surfaces created by higher energies.
A Characterization of Process–Surface Texture Interactions in Micro-Electrical Discharge Machining Using Multiscale Curvature Tensor Analysis
Manuscript received April 30, 2017; final manuscript received August 8, 2017; published online December 18, 2017. Assoc. Editor: Tony Schmitz.
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Bartkowiak, T., and Brown, C. A. (December 18, 2017). "A Characterization of Process–Surface Texture Interactions in Micro-Electrical Discharge Machining Using Multiscale Curvature Tensor Analysis." ASME. J. Manuf. Sci. Eng. February 2018; 140(2): 021013. https://doi.org/10.1115/1.4037601
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