• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.7
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• pp.688-696
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• 2000

A scheme for fault detection on the subsystem level is presented. The method uses analytical redundancy and consists in generating residuals by comparing each measurement with an estimate computed from the reference models. In this study regression neural network models are used as reference models. The regression neural network is memory-based feed forward network that provides estimates of continuous variables. The simulation result demonstrated that the proposed method can effectively detect faults in an air handling unit(AHU). The results show that the regression models are accurate and reliable estimators of the highly nonlinear and complex AHU.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.1267-1271
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• 2009

In the present study, performance characteristics on environment change of A/C applied fin-tube and PF heat exchangers were experimentally investigated. Capacity and COP changing an outlet air velocity, an indoor/outdoor temperature and a relative humidity were obtained. Air－enthalpy calorimeter was used. As the air velocity, indoor temperature and relative humidity increase, capacity and COP increase. PF A/C has smaller refrigerant weight than the fin-tube A/C. The performance of PF-2 A/C with the squarer fin was more excellent than that of PF-1 A/C with the triangler fin.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.9
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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.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.18 no.12
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• pp.999-1006
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• 2006

A study of temperature profiles in mixing zone of AHU (air handling unit) can contribute greatly to enhance performance of AHU system, so the study on the temperature distribution between RA (return air) and OA (outdoor air) is important to analyze the mixing characteristics in a mixing zone of AHU. Accordingly, the temperature profiles during RA (return air) and OA (outdoor air) supply process into mixing zone of AHU with an air mixer are studied experimentally. The effect of air mixer, OA temperature and RA/OA flow rate are studied in detail. In this study, the results show that the mixing efficiency is all high for installed the air mixer. The more OA temperature increase and OA flow rate decrease, the more mixing efficiency is high.

• Proceedings of the SAREK Conference
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• 2007.11a
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• pp.322-327
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• 2007

Dedicated outdoor air-conditioning(DOA) system that utilizes pre-cooling and desiccant dehumidification can be superior to conventional cooling and reheating system with respect to energy consumption and indoor thermal comfort. In this work, simulation has been conducted to study various factors that affect the performance of DOA. Dynamic simulation shows the transient variation of temperature and humidity as the on/off control logic is imposed. Exit humidity of process air and flow rate are varied to study the effect on exit temperature of process air, dehumidification quantity, required regeneration temperature and exit humidity of regeneration air. For an outdoor air condition of $28.5^{\circ}C$ temperature, 16 g/kg humidity ratio and 2000 cmh flow rate, the dehumidification efficiency is increased by 4.6% as the flow rate is doubled.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.12
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• pp.1288-1296
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• 2001

A scheme for on-line fault detection and diagnosis of an air-handling unit is presented. The fault detection scheme uses residuals which are generated by comparing each measurement with analytical redundancies computed from the reference models. In this paper, artificial neural networks (ANNs) are used to estimate analytical redundancy and to classify faults. The Lebenburg-Marquardt algorithm is used to train feed forward ANNs that provide estimates of continuous states and diagnosis results. The simulation result demonstrated that the ANNs can effectively detect and diagnose faults in the highly non-linear and complex HVAC systems.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.14 no.7
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• pp.552-559
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• 2002

The fault detection and diagnosis (FDD) technology may be applied in order to decrease the energy consumption and the maintenance cost of the air conditioning system. In this study, rule bases and curve fitting models were used to detect faults in an air handling unit. Gradually progressed faults, such as the fan speed degradation, the coil water leakage, the humidifier nozzle clogging, the sensor degradation and the damper stoppage, were applied to the developed FBD system. Simulation results show good detections and diagnoses of these faults. Therefore, this method may be effectively used for the fault detection and diagnosis of the air handling unit.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.24 no.2
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• pp.161-176
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• 1995

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.24 no.6
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• pp.628-634
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• 1995

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.19 no.1
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• pp.27-35
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• 1990