Surface Roughness Measuring Based On The Theory Of Fractal Geometry

Surface roughness is an important factor that influences the performance of machine parts and products in mechanical industry, which also plays as an important indicator to assess all kinds of surface quality by mechanical processing. Therefore, Measurement and evaluation of machining surface roughness is of prime importance. With the constant improvement of the surface machining accuracy and updating of roughness evaluation standards, higher requirements are put forward on surface roughness measurement and evaluation.The stylus profilometer is still widely used so far because of its stability, objectivity and reliability. Conventionally surface roughness evaluation method is given priority to with profile method, that several statistical roughness parameters are used for describing surface. But measurments with different scan lengths and resolutions yield different results of these statistical parameters for the same surface. Due to the deficiency of traditional characterizing methods, the fractal characteristic of the rough surface is studied in this paper.A surface roughness measuring instrument is redesigned based on a Talysurf4profilometer for both hardware and software. The working principle of the stylus profilometer is studied and the signal conditioning process of snail canal model differential inductance sensor is analyzed. By using measurement and control technology, electronic and computer technology, the measuring circuit of the instrument is reconstructed and a high speed data acquisition system is designed based on USB bus. The roughness measurement and evaluation software of this system is also written by some algorithms of fractal geometry theory. The paper completes the integrated design with analog circuit, Digital Circuit and system software. Through the measurement of standard samples, results indicate that work-piece surface presents fractal characteristic, and larger roughness level Ra corresponds to larger fractal dimension D but smaller characteristic length scale G. The fractal characterization of surface roughness, to some extent, overcomes the deficiencies of traditional evaluation method, and shows higher sensitivity and accuracy.