Dutta, Samik and Karmakar, Abhishek and Roy, Himadri and Barat, Kaustav (2019) Automatic estimation of mechanical properties from fractographs using optimal anisotropic diffusion and Voronoi tessellation. Measurement, 134. pp. 574-585.

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Abstract

With the advent of materials informatics there is a high demand of establishing automatic structure-property correlationship of materials which is a popular research topics due to the advancement of image processing and pattern recognition algorithms. Therefore, in this work, an attempt is made to estimate mechanical properties (i.e. yield strength and ductility) of AISI 304LN stainless steel from the SEM images of fracture surfaces obtained from tensile tests carried out at different strain rates using image processing techniques. As the void morphologies of fracture surfaces change systematically with the change in strain rates, the automatic detection of voids and geometrical features estimation from detected voids from the obtained are key goals of this present study. Therefore, in this work, a novel method of optimal anisotropic diffusion technique along with contrast limited adaptive histogram equalization (CLAHE), Otsu's optimal thresholding and morphological thinning operation are applied over the fractographs for edge enhancement, overcoming inhomogeneous illumination, edge segmentation and thinning, respectively, to detect voids, automatically. Then, Voronoi tessellation technique, which is a geometrical texture analysis, is utilized on these edge images of fractographs to extract four features viz. Voronoi edges, mean area, mean elongation and mean perimeter of Voronoi polygons where the linear correlation values (R2) with mechanical properties are found in the range of 0.90–0.99. A high linear correlation of features (i.e. 0.97–0.99) with the ductility is noticed as ductility is a geometrical parameter measured during fracture.

Item Type:	Article
Subjects:	Mechanical testing
Depositing User:	Dr. Arup Kr. Nandi
Date Deposited:	05 Nov 2020 11:18
Last Modified:	05 Nov 2020 11:18
URI:	http://cmeri.csircentral.net/id/eprint/612

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