High definition metrology enabled three dimensional discontinuous surface filtering by extended tetrolet transform

Surface topography is of great importance for the functional behavior of a part, and filtering is a key step in achieving topography analysis. The traditional filtering methods such as Gaussian and spline filter have been effectively applied in the continuous surface, but most parts have a great quantity of crucial discontinuous surfaces in engineering practice. A new filtering method based on extended tetrolet transform is proposed for the three dimensional (3D) discontinuous surface in this paper. The proposed filtering method consists of 3D discontinuous surface measurement and point cloud conversion, edge detector generation, extended tetrolet transform and 3D characterization parameters evaluation. It overcomes the drawback of edge effect which occurs in the discontinuous surface using traditional filtering methods. The 3D discontinuous surface is measured by high definition metrology that can generate millions of data points representing the entire surface. To verify the effectiveness of the extended tetrolet transform, it is compared with the areal Gaussian filter and areal spline filter both for the simulated continuous and discontinuous surface. The low frequency and high frequency components of engineering surfaces are separated exactly, and these results demonstrate that the proposed method is effective for the 3D discontinuous surface filtering without edge distortions.