대한건축학회논문집 (Journal of the Architectural Institute of Korea)

  • 제39권10호
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  • Pages.195-205
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  • 2023
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  • 2733-6239(pISSN)
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  • 2733-6247(eISSN)
대한건축학회 (Architectural Institute of Korea)
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동절기 실내 결로 발생 및 잔존조건 판별을 위한 Steam Sensor의 신뢰성 검토

Evaluating the Reliability of Steam Sensors for Detecting Indoor Condensation and Residual Conditions in Winter

  • 김승빈 (영남대 일반대학원 건축학과) ;
  • 손유라 (영남대 일반대학원 건축학과) ;
  • 양정훈 (영남대 건축학부)
  • 투고 : 2023.06.22
  • 심사 : 2023.09.18
  • 발행 : 2023.10.30
⟨ 이전 논문 다음 논문 ⟩

초록

This study serves as a foundation investigation to gather essential data for developing an algorithm to predict and prevent condensation using a Steam Sensor. In addition to utilizing temperature data typically employed in existing condensation prevention methods, the Steam Sensor was incorporated to monitor the continuous and discontinuous condensation behavior. This allowed for the collection of fundamental data for real-world condensation prediction and prevention. Before conducting the experiment, the heat flow rate for windows exposed to outdoor air using ISO-9869 was measured and validated. Indoor temperature and humidity were controlled through Arduino programming based on open-source platforms to observe the distribution of these factors. Subsequently, condensation was artificially induced by manipulating temperature and humidity conditions, then measured it with the Steam Sensor. During the experiment, as the indoor temperature was raised, absolute humidity and dew point temperature increased, resulting in an increase in the measured Steam Sensor values. When indoor humidity levels rise and the humidifier operates for an extended period, the accumulation of water vapor within the room increases. This elevated moisture level was detected by the Steam Sensor, and the condensation persisted until the end of the measurement. The experimental data gathered in this study will be valuable for future research where the aim is to develop a condensation prediction algorithm through machine learning techniques.

키워드

과제정보

이 연구는 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(No.2022R1F1A106417912)

참고문헌

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