Machined Surfaces Texture Analysis Based on Hough Transform and Run Length Statistics

Abstract

Conditions of tool wear can be indirectly reflected by the texture features of the machined image due to the direct contact between the work piece and tool in cutting process. In this paper, a new texture analysis method is proposed based on the Hough transform and Run length statistics. In order to remove non uniform illumination and noise, the original machined images are preprocessed by contrast enhancement algorithm and adjacent region average method, and then the edge images are obtained by a canny edge detector. Hough transform is then applied to the edge images to detect all line segments. The length characteristics of line segments are detected by using Run length statistics method. The average length and angle characteristics of edge images are used to determine the tool wear. Through our experiments, we found a high degree of correlation between texture features of machined images and tool wear. The combination of Hough transform and Run length statistics method improve the monitoring performance.