• 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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 C
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• pp.1906-1908
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• 2000

The central monitoring system with on-line diagnosis of high-voltage generator/motor stator insulation is developed. The system is capable of remote diagnosis and monitoring partial discharges of high-voltage generator/motor stator insulation. GOMS(Generator On-line Monitoring System) with maximum of 9 input channels can measure and analyze the status of high-voltage motor stator insulation by on-line. The measured and analysis data are brought to the central monitoring system via modem to build database. The central monitoring system can diagnose and monitor the insulation status of several high-voltage generator/motor at any time. The insulation status of those machines can be enhanced by the database on partial discharges.

• 한국기계가공학회지
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• 제18권5호
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• pp.37-47
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• 2019

Recently, as demand for various paper containers has rapidly grown, it is inevitable that paper cup-forming machines have increased their manufacturing speed. However, the faster manufacturing speed naturally brings more frequent manufacturing failures, which decreases manufacturing efficiency. As such, it is necessary to develop a system that monitors the failures in real time and diagnoses the failure progress in advance. In this research, a paper cup-forming machine diagnosis system was developed. Three major failure targets, paper deviation, temperature failure, and abnormal vibration, which dominantly affect the manufacturing process when they occur, were monitored and diagnosed. To evaluate the developed diagnosis system, extensive experiments were performed with the actual data gathered from the paper cup-forming machine. Furthermore, the desired system validation was obtained. The proposed system is expected to anticipate and prevent serious promising failures in advance and lower the final defect rate considerably.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1994년도 봄 학술발표회 논문집
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• pp.243-248
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• 1994

The purpose of this study is to develop Deterioration Diagnosis System for the Reinforced Concrete Structure which can be used preliminary in determining the factors causing deterioration by simple inspection and mapping of the indicators of deterioration. Total 29 items compromising material, structural and constructional factors causing deterioration were considered in this system. Also the indicators of deterioration were subdivided into 54 items such as concrete crack pattern and steel corrosion etc. Each indicator of deterioration was quantatified by allocating and giving grade to each item which has extra weight according to its conscquence. Satisfactory results were obtatined by applying this Diagnosis system to the indicators of deterioration in ref. [3]. Further research was required on the indicators of deterioration in construction site to enhance the field applicability of this system.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2001년도 학술대회논문집
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• pp.139-144
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• 2001

Insulation aging diagnosis system provides early warning regarding electrical equipment defect. Early warning is very important in that it can avoid great losses resulting from unexpected shutdown of the production line. Since relations of insulation aging and partial discharge dynamics are non-linear, it is very difficult to provide early warning in an electrical equipment. In this paper, we propose the design method of insulation aging diagnosis system that use a magnetic wave and acoustic signal to diagnoses an electrical equipment. Proposed system measures the partial discharge on-line from DAS(Data Acquisition System) and acquires 2D patterns from analyzing it. For filtering the noise contained in sensor signals we used ICA algorithms. Using this data, design of the neuro-fuzzy model that diagnoses an electrical equipment is investigated. Validity of the new method is asserted by numerical simulation.

• 대한기계학회논문집
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• 제17권12호
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• pp.3124-3134
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• 1993

Diagnosis is composed of two different but interrelated steps ; retrieving the sensory responses f the system and reasoning the state of the system through the given sensor data. This paper explains the probabilistic nature of reasoning involved in the diagnosis when the uncertainties are inevitably included in experts' diagnostic decision making. Uncertainties in decision making are experts' personal experiences, preferences, and system's coherent characteristics. In order to ensure a consistent decision based on the same responses from the system, expert system technology is adopted with the Bayesian reasoning scheme.

• 한국소음진동공학회논문집
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• 제11권9호
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• pp.414-421
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• 2001

If a machine has some faults, we can detect them using vibration or noise signals. However some maintenance engineers who don\`t have export knowledge, need the help of vibration experts for diagnosing the machine. In this paper a case based reasoning (CBR) system is developed which is able to manipulate the past experiences of vibration diagnosis experts. In the CBR system, the maintenance engineers can retrieve the information form previous cases which are most similar to new problem s that they can solve new problem using solutions form the previous cases. In this paper, a new case retrieval method of CBR system using Petri net is proposed and also applied to diagnosis for electric motors as a practical problem.

• 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.

• 조명전기설비학회논문지
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• 제12권4호
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• pp.47-54
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• 1998

발전설비에 있어 고신뢰성이 요구됨에 따라 진행되는 고장을 조기에 발견하는 예방 보전적 진단 시스템이 요구되고 있다. 본 논문에서는 발전설비 중에서 회전체의 절연진단과 진동진단에 대한 지식을 지식 베이스로 구성하고 이것을 다표정 언어를 이용하여 전문가 시스템을 구성하였다. 이 전문가 시스템은 진단 룰의 수정과 추가가 용이하며, 사용자와의 인터페이스도 양호한 구조를 취하고 있다.

• 동력기계공학회지
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• 제17권4호
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• pp.31-35
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• 2013

The emergency AC power supply system of the nuclear power plant is designed to supply the power to the nuclear power plant at the emergency operating condition. The safety function of the diesel generator at the nuclear power plant is to supply AC electric power to the safety system whenever the preferred AC power supply is unavailable. The reliable operation of onsite standby diesel generator should be ensured by a condition monitoring system designed to maintain, monitor and forecast the reliability level of diesel generator. The purpose of this paper is to improve the existing ultrasonic sensor used for condition diagnosis of engine fuel pump and cylinder head for the accurate diagnosis in actual engine condition of emergency diesel generator(EDG). As a result of this study, we could design and develop much more reliable ultrasonic sensor than existing ones.