• 설비공학논문집
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• 제18권10호
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• pp.791-799
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• 2006

The fault diagnosis technologies may be applied in order to decrease the energy consumption and the maintenance cost of an air-conditioning system. In this paper, a fault diagnosis algorithm was developed by using a neural no-fault model and a dual fuzzy logic. Five different faults, such as the compressor valve leakage, the liquid line blockage, the condenser fouling, the evaporator fouling, and the refrigerant leakage of an air-conditioning system, were considered. The fault diagnosis algorithm was tested by using a fault simulation facility. Test results showed that the algorithm developed for this study was effective to detect and diagnose various faults. Therefore, this algorithm may be practically used for the fault diagnosis of an air-conditioning system.

• 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.

• 설비공학논문집
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• 제18권7호
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• pp.587-595
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• 2006

A system operating algorithm was developed for the effective operation of a multi-type air-conditioning system. The system operating algorithm includes control algorithms for a safety mode, an initial operating mode, a stabilization mode, a fault diagnosis mode, an efficiency mode, and a tracking mode. Various tests were performed to show the effectiveness of these algorithms. Tests showed good results for the operation of a multi-type air-conditioning system. Therefore, these algorithms developed for this study may be used for the effective control of a multi-type air-conditioning system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2015년도 제46회 하계학술대회
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• pp.1066-1067
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• 2015

This paper presents a diagnosis method for the detection and location of open-short switch faults in the three-phase power conditioning system. A method for switch fault diagnosis on the power conditioning system is proposed, based on the concordia transform. The switch fault types and locations on power conditioning system are diagnosed by a method in which analyze the d-q current vector locus and current pattern. The Simulation results confirm the proposed diagnostic method.

• 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.

• 설비공학논문집
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• 제14권7호
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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.

• Journal of Power Electronics
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• 제16권2호
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• pp.695-703
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• 2016

A fuel cell power conditioning system for online diagnosis and load leveling under the condition of varying load is developed in this study. The proposed system comprises a unidirectional boost converter and a bidirectional buck-boost converter with a battery. The system operates in two different modes. In normal mode, the bidirectional converter is utilized for load leveling; in diagnostic mode, it is utilized to control load voltage while the boost converter generates perturbation current to implement the online diagnosis function through in-situ electrochemical impedance spectroscopy (EIS). The proposed method can perform EIS for a fuel cell under varying-load conditions with no influence on the load. The validity and feasibility of the proposed system are verified by experiments, and the design procedure of the proposed system is detailed.

• International Journal of Air-Conditioning and Refrigeration
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• 제16권4호
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• pp.137-144
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• 2008

This study deals with on-line fault detection and diagnosis(FDD) for heat exchangers of a variable speed refrigeration system(VSRS) based on current information. The current residual which is the difference between real detected current from current sensors and estimated current from no fault model was utilized to diagnose faults of the heat exchangers. Comparing to the conventional FDD of constant refrigeration system based on temperature and pressure information, the suggested FDD method shows better robustness to the VSRS which has a feedback control loop. Moreover the suggested method can be expected more precise and faster diagnosis of faults about heat exchangers. Throughout some experiments, the validity of the method was verified.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2008년도 하계학술발표대회 논문집
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• pp.30-35
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• 2008

This paper describes a fault detection and diagnosis (FDD) system developed for the heat source apparatus in building air-conditioning system. As HVAC&R systems in building become complex and instrumented with highly automated controllers, the processes and systems get more difficult for the operator to understand and detect the mal-functions. Poorly maintained, degraded, and improperly controlled equipment wastes an estimated 15% to 30% of energy used in commercial building. When operating a complex facility, FDD system is beneficial in equipment management to provide the operator with tools which can help in decision making for recovery from a failure of the system. Automated FDD for HVAC&R system has the potential to reduce energy and maintenance costs and improves comfort and reliability. Over the last decade there has been considerable research for developing FDD system for HVAC&R equipment. However, they are being made too much of a theoretical study, so only a small of FDD methods are deployed in the field. This study deduced an actual defect source for the heat source apparatus and suggested a low price FDD method which is ready to be deployed in the field.

• International Journal of Air-Conditioning and Refrigeration
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• 제11권3호
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• pp.125-131
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• 2003

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 paper, two fault detection methods were considered. One is a generic neural network, and the other is an moving average neural network. In order to compare the performance of fault detection results from these methods, two different types of faults in an air-conditioning system were applied. These are the condenser 30% fouling and the evaporator fan 25% slowdown. Test results showed that the moving average neural network was more effective for the detection of partial faults in the air-conditioning system.