AHU 고장감지 및 진단을 위한 냉수코일밸브 고착에 따른 열환경 및 에너지 성능 분석

다국어 초록 (Multilingual Abstract)

This study simulated chilled water valve stiction (ratio 30, 60%) by EnergyPlus in order to develop a fault detection and diagnosis algorithm for Air Handing Unit (AHU) based on machine learning. The abnormal zone temperature and AHU power consumption generated by the chilled water valve stiction ratio were reviewed. It was determined that the chilled water valve stiction errors reduced the chilled water flow and increased energy consumption through temperature changes at each node point in the HVAC while also creating an unsuitable thermal environment. In the future, we will generate the fault data of various elements of AHU and develop AHU fault detection and diagnosis algorithms through machine learning.