• 제목/요약/키워드: 정풍량 공조기

검색결과 4건 처리시간 0.015초

퍼지 알고리즘을 이용한 정풍량 공조기의 고장 감지 및 진단 (Fault Detection and Diagnosis of a Constant Volume Air Handling Unit by a Fuzzy Algorithm)

  • 한도영;김진
    • 설비공학논문집
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    • 제17권5호
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    • pp.444-451
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    • 2005
  • The fault detection and diagnosis technology may be applied in order to decrease the energy consumption and the maintenance cost of an air-conditioning system. In this study, partial faults for fans, coils, dampers, and sensors of a constant volume air handling unit were considered. A fuzzy algorithm was developed to detect and diagnose these faults. Diagnostic results by the fuzzy algorithm were compared with those by the model reference algorithm. The fuzzy algorithm showed better results in diagnostic accuracies.

룰 베이스를 이용한 정풍량 공조기 고장 검출 및 진단 시스템의 실험적 연구 (An Experimental Study on the Rule Based Fault Detection and Diagnosis System for a Constant Air Volume Air Handling Unit)

  • 한도영;김진
    • 설비공학논문집
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    • 제16권9호
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    • pp.872-880
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    • 2004
  • The fault detection and diagnosis technology may be applied in order to decrease the energy consumption and the maintenance cost of the air-conditioning system. In this study, an air handling unit fault test apparatus was built and fault diagnosis algorithms were applied to diagnose various faults of an air handling unit. Test results showed the good diagnosis for applied faults. Therefore, these algorithms may be effectively used to develope the real time fault detection and diagnosis system for the air handling unit.

정풍량 공조시스템의 고장검출 및 진단 시뮬레이션 (Fault Detection and Diagnosis Simulation for CAV AHU System)

  • 한동원;장영수;김서영;김용찬
    • 설비공학논문집
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    • 제22권10호
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    • pp.687-696
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    • 2010
  • In this study, FDD algorithm was developed using the normalized distance method and general pattern classifier method that can be applied to constant air volume air handling unit(CAV AHU) system. The simulation model using TRNSYS and EES was developed in order to obtain characteristic data of CAV AHU system under the normal and the faulty operation. Sensitivity analysis of fault detection was carried out with respect to fault progress. When differential pressure of mixed air filter increased by more than about 105 pascal, FDD algorithm was able to detect the fault. The return air temperature is very important measurement parameter controlling cooling capacity. Therefore, it is important to detect measurement error of the return air temperature. Measurement error of the return air temperature sensor can be detected at below $1.2^{\circ}C$ by FDD algorithm. FDD algorithm developed in this study was found to indicate each failure modes accurately.