The purpose of this study was to develop a novel measurement method using a machine vision system. Besides using image processing techniques, the proposed system employs a detection line algorithm that detects the tool electrode length and drilling depth of a workpiece accurately and effectively. Different boundaries of areas on the tool electrode are defined: a baseline between base and normal areas, a ND-line between normal and drilling areas (accumulating carbon area), and a DD-line between drilling area and dielectric fluid droplet on the electrode tip. Accordingly, image processing techniques are employed to extract a tool electrode image, and the centroid, eigenvector, and principle axis of the tool electrode are determined. The developed detection line algorithm (DLA) is then used to detect the baseline, ND-line, and DD-line along the direction of the principle axis. Finally, the tool electrode length and drilling depth of the workpiece are estimated via detected baseline, ND-line, and DD-line. Experimental results show good accuracy and efficiency in estimation of the tool electrode length and drilling depth under different conditions. Hence, this research may provide a reference for industrial application in EDM drilling measurement.
Keywords: Detection line algorithm (DLA); Drilling depth; Electrical discharge machining (EDM); Electrode length; Peak decision method..