Directional Fractal Signature Analysis of Self-Structured Surface Textures

• Published in: Tribology letters Vol. 47; no. 3; pp. 323 - 340
• Main Authors: Wolski, Marcin, Podsiadlo, Pawel, Stachowiak, Gwidon W.
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01-09-2012; Springer Nature B.V
• Subjects: Atomic force microscopes; Atomic force microscopy; Chemistry and Materials Science; Corrosion and Coatings; Fractal analysis; Fractals; Materials Science; Measurement methods; Methods; Microscopes; Nanotechnology; Original Paper; Physical Chemistry; Rotation; Shearing; Signature analysis; Surface roughness; Surfaces and Interfaces; Texture; Theoretical and Applied Mechanics; Thin Films; Tribology; Numerical analysis; Surface characterization; Self-structured surfaces; Texture
• ISSN: 1023-8883; 1573-2711
• DOI: 10.1007/s11249-012-9988-6

Currently available directional fractal signature (DFS) methods are not suited for self-structured surface textures since they base on the assumption of Brownian fractal or they do not use the entire image data in calculation. To address these difficulties, two new DFS methods were developed in this study, i.e., an augmented blanket with rotating grid (ABRG) method and a blanket with shearing image (BSI) method. The performance of these methods in measuring surface roughness and directionality, the capacity for quantifying multi-patterned textures, and the ability to detect differences between textures of self-structured surfaces were evaluated. The methods were compared against a blanket with rotating grid (BRG) method. Computer-generated images of self-structured surface textures with different roughness, directions and patterns, and atomic force microscope images of real self-structured surfaces were used. The computer texture images were generated using a specially developed motif-based texture generator. Results obtained showed that the ABRG method is more accurate and reliable than the BRG and BSI methods.