Local Directional Fractal Signature Method for Surface Texture Analysis

The detection of changes in surface texture characteristics is an important issue in manufacturing, contact mechanics, control of interactions between surfaces, machine failure analysis, and others. These changes can be detected early on when surface texture is quantified locally at each point. To this end, a new method called local directional fractal signature has recently been developed that calculates local fractal dimensions (FD = 3 − slope) at individual scales and directions. In this method, texture parameters are derived from the slopes of lines fitted to log–log plots of local surface profiles against scales, and FDs to measure local surface roughness and directionality. First, the method is tested on computer-generated isotropic fractal surfaces with the objective to evaluate its ability to differentiate between surfaces exhibiting an increasing local roughness. This follows the method application to detect the anisotropy changes in computer-generated surfaces with increasing roughness in two directions. Finally, the method’s detection ability in finding differences between surfaces is evaluated. Microscopic range-images of sandblasted and abraded titanium alloy plates are used in the evaluation. This work is a further contribution to the advancement in the characterization of surface textures, the numerical tools development for the design of tribological components and the diagnosis of worn and damaged surfaces. Practical applications of the method (e.g., classification of wear images, characterization of coated and uncoated surfaces) would be reported later in the future.