Method to extract information of surface roughness in three dimensions of particle reinforced aluminum matrix composites

To compare the effectiveness of three methods to extract the information of 3d surface roughness of particle reinforced aluminum matrix composites, specimens was high-speed milled, and the surface micro-topography was measured by OLS 3000 microscope. The least squares method, Gaussian filtering method and extensional Gaussian filtering method were adopted to extract the information of 3d surface roughness and 3d roughness parameters were computed. Gaussian filtering and extensional Gaussian filtering method are sensitive to the defect, also the information extracted is unstable. The least squares method is appropriate for this material because of the retention of the defect's information and the high stability.