Akademik Veri Yönetim Sistemi
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, cilt.220, sa.9, ss.1409-1415, 2006 (SCI-Expanded)
A computer vision-based approach to drilling tool condition monitoring is proposed in this paper. Firstly, image frames are captured using a high-speed CCD camera. Then, a Canny edge detector is employed to extract tool features from the acquired images. In order to obtain a measure of tool wear, the deviation from linearity (DEFROL) metric is proposed. Experimental results show that the proposed method detects the condition of all tested tools successfully.