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기계학습을 이용한 재질별 음료 용기 분류기 모델 개발 Classifier Modeling of Beverage Containers by Material using Machine Learning

최덕기
  • 언어KOR
  • URLhttp://db.koreascholar.com/Article/Detail/416647
한국기계기술학회지 (韓國機械技術學會誌)
제24권 제4호 (2022.08)
pp.597-604
한국기계기술학회 (Korean Society of Mechanical Technology)
초록

In order to reduce environmental pollution, it is necessary to increase the recycling rate of waste. For this, the separation of recyclables is of utmost importance. The paper conducted a study to automatically discriminate containers by material for beverage containers among recyclables. We developed an algorithm that automatically recognizes containers by four materials: metal, glass, plastic, and paper by measuring the vibration signal generated when the beverage container collides with the bottom plate of the collection box. The amplitude distribution, time series information, and frequency information of the vibration signal were used to extract the characteristics indicating the characteristic difference of the vibration signal for each material, and a classifier was developed through machine learning using these characteristics.

저자
  • 최덕기(강릉원주대학교) | Choi, Deok Ki Corresponding author