• 대한기계학회논문집B
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• 제29권11호
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• pp.1220-1228
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• 2005

Fault detection and diagnostic (FDD) systems have the potential to reduce equipment downtime, service costs, and utility costs. In this study, model based algorithm and fuzzy algorithm were used to detect and diagnose various fault at System multi-air conditioner. various fault include the Refrigerant Low charging, Fouling of Indoor Heat Exchanger, Fouling of Outdoor Heat Exchanger A experimental verification was conducted in the 6HP System multi-air conditioner on an 8-floor building. Test results showed diagnosis result about 78 $\~$ 90$\%$ for given faults. This Study lays the foundation fur future work on develope the real-time fault detection and diagnosis system for the System multi-air conditioner.

• Journal of Biosystems Engineering
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• 제34권6호
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• pp.470-475
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• 2009

This study was performed to present the diagnosis basis of cooling performance deficiency according to air quantity included in refrigerant of air-conditioner by detecting the temperatures and pressures of refrigerant pipeline. The car air-conditioner of SONATA III (Hyundai motor Co., Korea) was tested by maximum cooling condition at 1500 rpm of engine speed in the room with controlled air condition at $33\sim35^{\circ}C$ and 55~57% RH. Measured variables were temperature differences between inlet and outlet pipe surface of the compressor (Tcom), condenser (Tcon), receive dryer (Trec) and evaporator (Teva), and high pressure (HP) and low pressure (LP) in the refrigerant pipeline, and temperature difference (Tcoo) between inlet and outlet air of the cooling vent of evaporator. Control variables were the refrigerant charging weight and the vacuum degree in the refrigerant pipeline before charging refrigerant. From the test, it was represented that the measuring values of (Tcom), LP and (Tcoo) were enabled to make the diagnosis of cooling performance deficiency according to quantity included in refrigerant of air-conditioner. The ranges of Tcom, LP and Tcoo to make the diagnosis of cooling performance deficiency were respectively less than $55^{\circ}C$, more than 166.7 kPa-g(1.7 kgf/$cm^2$) and less than $13.7^{\circ}C$. In the case of using only external sensors and the condition under the normal performances of air conditioner, it was considered that the ranges of LP and Tcoo to make the diagnosis of cooling performance deficiency were respectively more than 166.7 Pa and less than $12^{\circ}C$.

• 한국정밀공학회지
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• 제21권11호
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• pp.125-129
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• 2004

For the diagnosis of compressor abnormal condition in air-conditioner, AE signal which is derived from wear condition, compressed air and assembly error is analyzed experimentally. The burst and continuous type AE signal occurred by metal contact and compressed air and AE raw signal of compressors were directly acquired in production line. After extracting samples according to waveforms, Early Life Test(ELT) is conducted and classified to normal and abnormal waveform. The efficient parameters of waveform pattern are investigated in time and frequency domain and the diagnosis algorithm of air-conditioner by Neural Network estimation is suggested.

• Journal of Biosystems Engineering
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• 제36권5호
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• pp.319-325
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• 2011

This study was conducted to figure out the diagnosis basis of cooling performance depending on water amount in the refrigerant of air conditioner, which can be estimated by the temperatures and pressures along the refrigerant circulation line. A car air conditioner of SONATA III (Hyundai motor Co., Korea) was tested at maximum cooling condition at the engine speed of 1500 rpm in the room controlled at 33~$35^{\circ}C$ air temperature and 55~57% relative humidity conditionally. Measured variables were temperature differences between inlet and outlet pipe surfaces of the compressor, condenser, receive drier and evaporator; and high pressure and low pressure in the refrigerant circulation line; and temperature difference between inlet and outlet air of the cooling vent of evaporator. In this study, changes of the water amount in the refrigerant were correlated to the temperatures and pressure changes and also water amount caused poor cooling performance. As water amount increased in the refrigerant in the air conditioner, the performance of the cooling or the heat transfer became worse. Temporal variations of the surface temperature of the evaporator outlet pipe and the low-side pressure showed various patterns that could estimate the water amount. When the water amount caused bad cooling performance, the patterns of the temperature of the evaporator outlet pipe indicated irregular fluctuation greater than $5^{\circ}C$. When the diagnosis system is using just external sensors of the low-side pressure and the temperatures of inlet and outlet air of cooling vent of the evaporator, the precise pattern of bad cooling performance caused by excess water amount in the cooling line was irregular pressure fluctuation, 25 kPa under 120 kPa, and temperature, $12^{\circ}C$ and less.

• 설비공학논문집
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• 제14권7호
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• pp.560-566
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• 2002

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, two different types of faults in the air-conditioning system, such as the condenser fouling and the evaporator fan slowdown, were considered. The neural network algorithm combined with data preprocessor was developed and applied to detect the faults of the real system. Test results show that this method is very effective to detect the faults in the air-conditioning system. Therefore, this developed method can be used for the development of the air-conditioner fault detection system.

• International Journal of Precision Engineering and Manufacturing
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• 제7권3호
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• pp.14-17
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• 2006

To diagnosis abnormal compressor conditions in an air-conditioner, the acoustic emission (AE) signal, which is derived from wear condition, compressed air, and assembly error, was analyzed experimentally. Burst and continuous type AE signals resulted from metal contact and compressed air, and the raw AE signal of compressors was acquired in the production line. After extracting samples using waveforms, the Early Life Test (ELT) was conducted and the waveform was classified as normal or abnormal. Efficient parameters in the waveform pattern were investigated in time and frequency domains and a diagnosis algorithm for air-conditioners using Neural Network estimation is suggested.

• 한국산학기술학회논문지
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• 제14권4호
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• pp.1568-1575
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• 2013

자동차의 유지보수 및 수리를 위한 장비에서 환경오염에 대한 관심이 증대되고 있음에도 불구하고, 국내 자동차 공조시스템에 대한 대부분의 이러한 장비는 환경오염에 대해 무관심뿐만 아니라 그 기능도 뒤떨어진 것이 사실이다. 이 논문에서는 자동차 공조시스템의 냉매의 회수 및 재충전을 위한 모니터링 기술과 진단 시스템을 개발하였다. 이러한 개발된 기술과 시스템은 냉매상태의 정확한 진단과 모니터링을 통하여 자동차 공조시스템에 정확한 냉매량을 충전가능하게 해준다. 또한 이러한 기술은 주변 온도에 따라서 냉매의 회수압력을 조절함으로서 냉매의 회수와 충전에 대한 정확한 제어를 가능하게 해준다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회B
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• pp.2070-2075
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• 2008

Identification of steady-state is the first step in developing a fault detection and diagnosis (FDD) system. In a complete FDD system, the steady-state detector will be included as a module in a self-learning algorithm which enables the working system's reference model to "tune" itself to its particular installation. In this study, a steady-state detector of a residential air conditioner based on moving windows was designed. Seven representing measurements were selected as key features for steady-state detection. The optimized moving window size and the feature thresholds was suggested through startup transient test and no-fault steady-state test. Performance of the steady-state detector was verified during indoor load change test. From the research, the general methodology to design a moving window steady-state detector was provided for vapor compression applications.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2008년도 하계학술발표대회 논문집
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• pp.282-287
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• 2008

Identification of steady-state is the first step in developing a fault detection and diagnosis (FDD) system. In a complete FDD system, the steady-state detector will be included as a module in a self-learning algorithm which enables the working system's reference model to "tune" itself to its particular installation. In this study, a steady-state detector of a residential air conditioner based on moving windows was designed. Seven representing measurements were selected as key features for steady-state detection. The optimized moving window size and the feature thresholds was suggested through startup transient test and no-fault steady-state test. Performance of the steady-state detector was verified during indoor load change test. From the research, the general methodology to design a moving window steady-state detector was provided for vapor compression applications.

• 대한기계학회논문집B
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• 제34권4호
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• pp.333-339
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• 2010

고장감지 및 진단(FDD) 시스템의 구축의 기초 연구로 정상상태 진단기에 대한 연구를 수행하였다. 정상상태에 대한 진단은 시스템 전체를 관찰하거나 몇몇 필요한 시스템 파라미터를 모니터링 함으로써 가능하다. 최적화된 정상상태 진단기를 이용하면 FDD 시스템에서 필수적인 정상운전 시의 기준모델(no fault reference model)을 자가학습을 통하여 적용할 수 있다. 본 연구에서는 가정용 열펌프가 냉방조건으로 작동할 경우에 대해 이동창을 기반으로 7개의 측정값들에 대한 표준편차를 분석함으로써 정상상태 판정을 내리도록 하였다. 정상상태 진단기의 작동의 여부는 실내부하를 조절함으로써 확인하였다. 본 연구를 통하여 열펌프 등의 증기압축 사이클 시스템에 대하여 이동창을 기반으로 한 정상상태 진단기 개발 방법을 제시하였다.