Fractal Characterization on Surface Texture of Cylinder Liner Based on Partitioned Iterated Function System

The physical characteristics of the surface texture are the key factors that affect the tribological characteristics of the piston assembly-liner system. In order to accurately describe the physical characteristics of the anti-friction texture on the surface of the piston assembly-cylinder liner system, a machine vision approach for characterizing the anti-friction texture based on the curvelet transform and the partitioned iterated function system (PIFS) is proposed. According to the gray image information of the surface texture of cylinder liner, the curvelet transform is employed to extract the physical features of the multi-scale and anisotropic surface topography image of cylinder liner. A PIFS-based fractal method is studied to describe the physical features of the surface texture, and compared with the fractal dimension calculated by the differential box-counting (DBC) method to verify the effectiveness of PIFS method. The results indicate that the proposed approach can effectively characterize the physical features of surface texture for different cross-hatched lines and dimple textures with different shapes, cross-section sizes and depths.