Measurement of Surface Roughness of Machined Surfaces Using Vision Systems

With the increasing demand for accurate engineering products, the control of surface texture has become vital. Surface roughness of machined parts need to be specified on the basis of their use and application environment. The geometrical and material properties of surface can significantly affect the friction, wear, fatigue and corrosion of that part. Hence evaluation of surface roughness and characterization of that surface has become essential for design, manufacturing and inspection. Many methods of measuring surface finish have been investigated ranging from simple touch comparator to sophisticated optical techniques. The latest technology of measuring surface roughness is the combination of optical techniques and computer vision systems. In this paper an attempt has been made to develop an experimental technique to measure the surface roughness based on the analysis of the intensity distribution of scattered light from the surface. For this purpose a low cost vision system is proposed. By impinging a laser beam at an angle on the machined surface, a random pattern of bright and dark regions known as speckle is observed. These speckle images are captured using charge coupled device (CCD) camera and are stored in digital format. Further a source code In C++ is developed to read the image data and to compute optical roughness values from stored images. Since the results obtained through this technique are encouraging, this method is well adapted for measurement of rough surface that fall within the range of engineering surface generated by common machining process like grinding, turning and milling. A few conclusions are drawn on the effectiveness of adopting the proposed system.