Surface Roughness Three-Dimensional Detection Based On SFS

Surface roughness is an important indicator of surface quality and has a direct influence on the service performances,lives and safety of machine parts,especially for special parts(seal,relative movement).Therefore,detecting the surface roughness of machine parts fastly,accurately and non-destructively is very important for the application of the parts and the safety of the system.Based on the theory of machine vision,the non-contact and nondestructive detection for end-milling and turning surface roughness are achieved by shape from shading(SFS).The main contents of this thesis are as follows:(1)The hardware platform for visual inspection of the surface roughness was built which consisted of VHX-1000 type super depth 3D microscopy system,CCD camera and computer.The surface images of end-milling and turning workpieces could be captured by this system.(2)Original images of the surfaces of machine parts were gathered,then grayed,denoised.Denoise processing is achieved by median filtering.(3)Taking the gray value E(x,y)of surface image as the input and the corresponding surface height value z(x,y)as the desired output,the three-dimensional reconstruction model of surface micro topography was constructed by using the SFS method based on computer vision theory.By using the existing physical light diffuse reflection model and the specular reflection model,a new illumination model which can be applied to the 3D reconstruction algorithm of metal surface is improved.(4)The three-dimensional reconstruction of end-milling surfaces and turning surfaces using 3D reconstruction algorithm based on improved illumination model were proposed.The feasibility of the proposed algorithm is verified by comparing the 2D contour curve of the vertical texture direction in the reconstructed surface with the measured contour curve.(5)A surface roughness measurement system is established.Based on the image information of 3D reconstruction,the 2D and 3D feature parameters of the surface roughness were extracted,and then the relationships between surface roughness parameters and different roughness levels were analyzed to enrich the surface roughness characterization.The MATLAB software was used to develop a simple GUI user interface of surface roughness detection system which could quickly,accurately and non-destructively detect the surface roughness.