Extraordinary State Discrimination of Grinding Wheel Surface Using Pattern Classification

패턴 분류법을 이용한 연삭 숫돌면의 이상상태 판별

The grinding plays a key role which decide the quality of a product finally. But the grinding process is very irregular, so it is very difficult to analyse the process accurately. Therefore it is very important in the aspect of precision and automation to reduce the idle time and to decide the proper dressing time by visualizing. In this study, we choose the direct method of observation by making use of computer vision, and apply pattern classification technique to the method of measuring the wheel surface. Pattern classification technique is proper to analyse complex surface image. We observe the change of the wheel surface by making use of the gray level run lengths which are representative prince in this technique.