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4,000원
원문정보
초록
영어
In this study, we have developed a movable defect detection system based on a vision module with machine-learning algorithm for distinguishing product quality. Machine-learning model determined the results in good or no good through images acquired from the vision module consisting of a camera, processor unit, and lighting. To ensure versatility for use in a variety of settings, we have integrated a robot arm and cart for the movable defect detection system, and the robot arm that adjusts the focus length is made to be able to rotate in all directions. The type of defect was divided into eccentricity defect and printing defect. As a result, it was confirmed that classification accuracy showed 0.9901 in our developed device.
목차
ABSTRACT 1. 서론 2. 실험 및 방법 2.1 하드웨어 제작 2.2 불량 Class 분류 2.3 실험 set-up 3. Data 처리 및 분석 3.1 이미지 처리 3.2 기계학습 알고리즘 4. 결과 및 논의 5. 결론 후기 References