딥러닝 기반 형상 인식 기술을 활용한 치과용 스케일링 수공구 연마 자동화 시스템 연구
A Study on Dental Scaling Hand Tool Polishing Automation System Using Deep Learning-Based Shape Recognition Technology
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※ 학술발표대회집, 워크숍 자료집 중 4페이지 이내 논문은 '요약'만 제공되는 경우가 있으니, 구매 전에 간행물명, 페이지 수 확인 부탁 드립니다.
4,000원
원문정보
초록
영어
This study attempted to overcome the limitations of the existing manual process by applying automation technology to the polishing process of hand tools (scaling tools) for removing tartar. The current polishing process is causing quality deviation, high defect rate, and safety problems depending on the skill level of the worker. Therefore, this study attempted to achieve precise control of the polishing angle and reduction of the defect rate at the same time by applying machine vision-based high-precision location recognition and deep learning correction algorithm. In particular, the performance was verified through experiments by manufacturing tray design and prototype automation equipment that can stably supply various tools. As a result of the experiment, the proposed system reduced the polishing angle error from ±2.5° to ±0.5° compared to the existing manual work, and the defect rate was reduced from 5% to less than 2%. In addition, the work efficiency improved by more than 30%. These achievements provide an important basis for reducing dependence on foreign equipment in the domestic dental hygiene educational equipment market and securing competitiveness in overseas markets.
목차
Abstract 1. 서론 2. 본론 2.1 연구 방법 및 시스템 구성 2.2 연구과제 개발의 최종 목표 및 단계별 목표 2.3 연구개발 과제의 내용 3. 결론 및 향후 연구 References