Acknowledgement
이 연구는 2021년도 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 기초연구사업이다. (No.2015R1A5A1037548)
Proceedings of the Korean Institute of Building Construction Conference (한국건축시공학회:학술대회논문집)
- 2021.05a
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- Pages.10-11
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- 2021
An Experimental Study on the Measurement of Finess Modulus Using CNN-based Deep Learning Model
CNN기반의 딥러닝 모델을 활용한 잔골재 조립률 예측에 관한 실험적 연구
- Published : 2021.05.20
Abstract
As concrete is used in many construction works, the use of aggregates is increasing. However, supply and demand of high-quality aggregates has become difficult recently, and although circular aggregates that recycle construction waste are used, the performance of concrete, such as liquidity and strength, are being reduced due to defective aggregates. As a result, quality tests such as sieve analysis test are conducted, but a lot of waste occurs such as time and manpower. To solve this problem, this study was conducted to measure the assembly rate of fine aggregate, which accounts for about 35% of the concrete volume, using Deep Learning.