In this study, unit-water content was measured using a frequency domain reflecometry(FDR) sensor that complements the problems of the existing unit-water content measurement method to evaluate the unit-water content affecting the workability, durability, and quality of high strength concrete. The experiment used the unit-water content of high strength concrete as a variable, and the accuracy and probability distribution of the unit-water content measured through deep learning were analyzed for the output value output through the FDR sensor. In the case of the unit-water content predicted by deep learning analysis, a high accuracy and high distribution of more than 93% were found within the error range of ± 10 kg/m3. In the future, research is needed to secure high reliability by utilizing data obtained through experiments with various variables.
본 논문은 2022년 과학기술정보통신부 한국연구재단(과제번호:NRF-2022R1A2C1093253)의 일환으로 수행된 연구임을 밝히며 이에 감사를 드립니다.