• 한국철도학회:학술대회논문집
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• 한국철도학회 2003년도 추계학술대회 논문집(III)
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• pp.529-534
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• 2003

Within industry induction motors have a broad application area to drive pumps, fans, elevators and electric trains. Sudden failures of such machines can cause the heavy economical losses and the deterioration of system reliability. Based on the reliability and cost competitiveness of driving system (motors), the faults detection and the diagnosis of system are considered very important factors. In order to perform the faults detection and diagnosis of motors, the vibration monitoring method and motor current signature analysis (MCSA) method are emphasized. In this paper, MCSA method are used for induction motor fault diagnosis. This method analyzes the motor's supply current, since this diagnoses faults of the motor. The diagnostic algorithm is based on the principal component analysis(PCA), and the diagnosis system is programmed by using LabVIEW and MATLAB.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 춘계학술대회논문집
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• pp.425-430
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• 2008

To verify the system performance of portable AE leak diagnosis system which can measure with moving conditions, AE activities such as RMS voltage level, AE signal trend, leak rate degree according to AE database, FFT spectrum were measured during operation on total 11 valves of the secondary system in nuclear power plant. AE activities were recorded and analyzed from various operating conditions including different temperature, type of valve, pressure difference, valve size and fluid. The results of this field study are utilized to select the type of sensors, the frequency band for filtering and thereby to improve the signal-to-noise ratio for diagnosis for diagnosis or monitoring of valves in operation. As the final result of application study above, portable type leak diagnosis system by AE was developed. The outcome of the study can be definitely applied as a means of the diagnosis or monitoring system for energy saving and prevention of accident for power plant valve. The purpose of this study is to verify availability of the acoustic emission in-situ monitoring method to the internal leak and operating conditions of the major valves at nuclear power plants. In this study, acoustic emission tests are performed when the pressurized temperature water and steam flowed through glove valve(main steam dump valve) and check valve(main steam outlet pump check valve) on the normal size of 12 and 18 ". The valve internal leak monitoring system for practical field was designed. The acoustic emission method was applied to the valves at the site, and the background noise was measured for the abnormal plant condition. To improve the reliability, a judgment of leak on the system was used various factors which are AE parameters, trend analysis, frequency analysis, voltage analysis and amplitude analysis of acoustic signal emitted from the valve operating condition internal leak.

• 전기학회논문지P
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• 제56권1호
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• pp.51-55
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• 2007

In this paper, a portable rotor bar fault diagnosis system for small 3 phase induction motors is suggested. For portable real-tine diagnosis system, an USB-DAQ board for collecting the 3 phase current data, three current probes, and a notebook computer are used. The LabVIEW graphical language is used for filtering, analysis, storing, and monitoring the current data. The three phase stator current are filtered and transformed to frequency level by FIT. An analysis window programed by LabVIEW is located in front panel to show the FIT results and this suggested window has a zooming function to detect the fault feature more easily near the feature frequency range which is varying by the slip frequency. To show the possibility of portable rotor bar diagnosis system, three types(healthy, one rotor bar fault, two rotor bar fault) of rotor bar are intentionally prepared and compared by the suggested window of front panel. Experimental results are shown that a suggested diagnosis system is applicable to portable diagnosis system and the rotor bar fault is detected by the frequency window in front panel programed in LabVIEW graphical language.

• 산업경영시스템학회지
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• 제23권54호
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• pp.155-165
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• 2000

The fault diagnosis is a systematic and unified method to find based on the observing data resulting in noises. This paper presents the fault prediction and diagnosis using fuzzy expert system technique to manipulate the uncertainties efficiently in predictive perspective. We apply a fuzzy event tree analysis to the computer system, and build up the fault prediction and diagnosis using fuzzy expert system that predicts and diagnoses the error of the system in the advance of error.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2008년 영문 학술대회
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• pp.16-21
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• 2008

Aero-engine, as one kind of rotating machinery with complex structure and high rotating speed, has complicated vibration faults. Therefore, condition monitoring and fault diagnosis system is very important for airplane security. In this paper, a vibration data acquisition and intelligent fault diagnosis system is introduced. First, the vibration data acquisition part is described in detail. This part consists of hardware acquisition modules and software analysis modules which can realize real-time data acquisition and analysis, off-line data analysis, trend analysis, fault simulation and graphical result display. The acquisition vibration data are prepared for the following intelligent fault diagnosis. Secondly, two advanced artificial intelligent(AI) methods, mapping-based and rule-based, are discussed. One is artificial neural network(ANN) which is an ideal tool for aero-engine fault diagnosis and has strong ability to learn complex nonlinear functions. The other is data mining, another AI method, has advantages of discovering knowledge from massive data and automatically extracting diagnostic rules. Thirdly, lots of historical data are used for training the ANN and extracting rules by data mining. Then, real-time data are input into the trained ANN for mapping-based fault diagnosis. At the same time, extracted rules are revised by expert experience and used for rule-based fault diagnosis. From the results of the experiments, the conclusion is obvious that both the two AI methods are effective on aero-engine vibration fault diagnosis, while each of them has its individual quality. The whole system can be developed in local vibration monitoring and real-time fault diagnosis for aero-engine.

• 간호행정학회지
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• 제9권2호
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• pp.183-191
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• 2003

Purpose : to survey about satisfaction of nurses of NANDA nursing diagnosis and NIC nursing interventions and system's usefulness of information system forusing 10 medical diagnosis. Method : nurses learned about this system and used this system for 4 or 8 weeks. After that survey about satisfaction and usefulness of this system. Result : The good points of the nursing diagnosis systems are a rapid selection, accuracy, convenience of the using system. The good points of the nursing intervention system are same as the nursing diagnosis system. About the good points of the general system are easiness, improvement of nursing knowledge, convenience, etc. However, further studies for pilot operations of the system are mandatory. Conclusion : We expect this system can be used in many hospitals efficiently in the future after pilot operations are completed in some hospitals. After verifying the usefulness of the system through pilot operations, the further analysis on the relationship between medical diagnosis and NANDA nursing diagnosis is also necessary for the generalization.

• 한국통신학회논문지
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• 제31권8B호
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• pp.701-706
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• 2006

System-level diagnosis plays an important technique for fault detection in multi-processor systems. Efficient diagnosis is very important for real time systems as well as multiprocessor systems. Feng(1) proposed two adaptive diagnosis algorithms HADA and IHADA for hypercube system. The diagnosis cost, measured by diagnosis time and the number of test links, depends on the number and location of the faults. In this paper, we propose an adaptive diagnosis algorithm using the syndrome analysis. This removes unnecessary overhead generated in HADA and IHADA algorithm sand give a better performance compared to Feng's Method.

• 전기학회논문지
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• 제56권12호
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• pp.2084-2090
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• 2007

The DGA (Dissolved Gases Analysis) technique has been widely using for fault diagnosis of the power transformers. Some electric power utility company establishes the criteria of DGA to improve reliability, because of difference of operation environment and design of power transformer. In this paper, we introduce intelligent diagnosis system for DGA result of KEPCO (Korea Electric Power Cooperation). This system can classify patterns type of gases ratio that frequently occurs in recent result of gases analysis using Fuzzy Inference. The classification of Patterns let us know that major causes of gases generation based on type of patterns. Finally, Neural Network based on patterns diagnose transformer. NN was trained using result data of DGA of actually faulted transformers recently. Result of intelligent diagnosis system is right well in comparison with actual inner inspection of transformers.

• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제54권5호
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• pp.206-212
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• 2005

In this paper, criterion and algorithm for on-line dissolved gas of a Power transformer are studied. For the initial diagnosis of a power transformer, the on-line dissolved gas analysis is one of the most important and acceptable item to preventively diagnose a power transformer. But the criterion and algorithm of this item are not established yet in korea. In this paper, criterion and alarm level of the on-line dissolved gas analysis are based on the analysis of on-line data of operating transformers, Korea industrial standard and operation manual for a power transformer as well as accumulated data of the preventive diagnosis systems which have been operated at nine substations of Korea Electric Power Co.(KEPCO) since 1997, Therefore, the criterion and alarm level proposed in this paper are to be well suitable and are adaptable for the domestic operational environments and conditions of the power transformer. Considering that the conventional diagnosis system is capable only of accumulating and monitoring data of the power transformer operation, the criteria and the algorithms make it possible to accomplish an ultimate goal of the preventive diagnosis system. It is expected, therefore, that they will have a beneficial effect on broad applications of the preventive diagnosis system and the achievement of manless substation system in the future.

• 대한의용생체공학회:의공학회지
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• 제30권1호
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• pp.41-48
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• 2009

In this paper, we present the diagnosis system for swallowing disorder. There are some types of diagnosis device for swallowing disorder, for example, the video fluoroscopy, the nuclear medicine inspection, the endoscopy, EMG and motion analysis. But these systems need heavy devices or have dangerous nuclear exposure, so are uncomfortable for handicapped person. Our system has advantages of simplicity, accuracy and quantitative analysis. In addition to the diagnosis aspect, this system can be used to biofeedback treatment.