• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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• pp.382.1-382
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• 2002

This paper presents a new approach integrated Case-Based Reasoning with Self- Organization Map(SOM) in diagnosis systems. The causes of faults are obtained by case-base trained from SOM. When the vibration problem of rotating machinery occurs, this provides an exact diagnosis method that shows the fault cause of vibration problem. In order to verify the performance of algorithm, we applied it to diagnose the fault cause of the electric motor.

• Journal of Biomedical Engineering Research
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• v.10 no.1
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• pp.17-24
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• 1989

This papaer presents a new algorithm for the P-wave detection in the ECG signal. Digital differentiation method (7-point derivative) is used for detecting P-waves exactly. This algorithm can detect various parameters of PR, PP, RR interval, which are important to diagnosis AV blocks and WPW syndrome. Especially, this algorithm can detect P-waves very efficiently not only in well-preprocessed waves but in pccr waves with noise and artifact. And it enables to develope more reliable automatic diagnosis algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.61-69
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• 1995

The diagnosis has an very important role in curing dementia. But there was not the effective method to diagnose it until now. In this paper we analyzed the EEG in Alzheimer's disease and normal control groups to differentiated them by nonlinear parameter such as the correlation dimension. And we propose the nonlinear analysis of EEG in Alzheimer's disease as a useful tool of early diagnosis of it.

• Journal of Electrical Engineering and information Science
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• v.2 no.5
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• pp.45-50
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• 1997

This paper present an advanced fault diagnosis expert system to assist the operators at local control center. The system utilizes all th information available in a local control center for the better diagnostic performance. The major feature of the system is dealing with multiple faults diagnosis based on the certainty factor method for the reasoning process. the overall performance and the generality are also enhanced by utilizing the general topological knowledge. ASCADA simulator is also developed for he test and demonstration.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.283-286
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• 1996

This study suggests a new methodology for the fault diagnosis based on the signed digraph in developing the fault diagnosis system of a boiler plant. The suggested methodology uses the new model, fault-effect tree. The SDG has the advantage, which is simple and graphical to represent the causal relationship between process variables, and therefore is easy to understand. However, it cannot handle the broken path cases arisen from data uncertainty as it assumes consistent path. The FET is based on the SDG to utilize the advantages of the SDG, and also covers the above problem. The proposed FET model is constructed by clustering of measured variables, decomposing knowledge base and searching the fault propagation path from the possible faults. The search is performed automatically. The fault diagnosis system for a boiler plant, ENDS was constructed using the expert system shell G2 and the advantages of the presented method were confirmed through case studies.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.11 s.188
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• pp.50-57
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• 2006

The water leak in water-cooled generator stator windings can generate the serious accidents such as insulation breakdown and it brings a generator to the unexpected sudden outage. Accordingly, it is important to diagnose the water absorption of them for the effective operation of power plant. Especially, the capacitance value which is measured for diagnosis is very small so the special diagnosis methods like stochastic theory are needed. KEPRI developed the water absorption test equipment and diagnosis technology for them. The developed diagnosis technology is applied to the real system and the results of water absorption test for stator windings are agreed to them of water leak test.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.1
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• pp.120-127
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• 1991

The purpose of this study is to develop a fault detection and diagnosis scheme that can monitor process fault and instrument fault of a steam generator. The suggested scheme consists of a Kalman filter and two bias estimators. Method of detecting process and instrument fault in a steam generator uses the mean test on the residual sequence of Kalman filter, designed for the unfailed system, to make a fault decision. Once a fault is detected, two bias estimators are driven to estimate the fault and to discriminate process fault and instrument fault. In case of process fault, the fault diagnosis of outlet temperature, feed-water heater and main steam control value is considered. In instrument fault, the fault diagnosis of steam genrator's three instruments is considered. Computer simulation tests show that on-line prompt fault detection and diagnosis can be performed very successfully.

• Proceedings of the KIEE Conference
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• 2001.07c
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• pp.1664-1666
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• 2001

This paper presents the development of electromagnetic wave detecting equipment for diagnosis of enclosed switchboard. High voltage power equipments are very important equipment of the key industries and the private enterprise. Power line accidents are national plans because of those set off casualties lose of power equipments and communication networks. Therefore the necessity of the development of detecting for power equipment diagnosis is demand for prevention of high voltage equipment accidents. This paper is the development of electromagnetic wave detecting equipment for diagnosis of high voltage equipment. This paper establishes the diagnosis method for high voltage power equipments, that secures original technique and possesses detecting technique for electromagnetic wave. By the study we developed electromagnetic wave detector, and we applied this equipment application tests at the place constructed high voltage equipments.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.62-68
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• 1999

FCM(Fuzzy Cognitive Map) is proposed for representing causal reasoning. Its structure allows systematic causal reasoning through a forward inference. Authors have already proposed a diagnostic system based on FCM to utilized to identify the true origin of fault by on-line pattern diagnosis. In FCM based fault diagnosis, Temporal Associative Memories (TAM) recall of FCM is utilized to identify the true origin of fault by on-line pattern match where predicted pattern sequences obtained from TAM recall of fault FCM models are compared with actually observed ones. In engineering processes, the propagation delays are induced by the dynamics of processes and may vary with variables involved. However, disregarding such propagation delays in FCM-based fault diagnosis may lead to erroneous diagnostic results. To solve the problem, a concept of FTCM(Fuzzy Time Cognitive Map) is introduced into FCM-based fault diagnosis in this work. Expecially, translation method of FTCM makes it possible to diagnose the fault for some discrete time. Simulation studies through two-tank system is carried out to verify the effectiveness of the proposed diagnostic scheme.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.6
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• pp.22-28
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• 2003

We should maintain the maximum operation capacity for production facilities and find properly out the fault of each equipment rapidly in order to decrease a loss caused by its failure. The acoustic signals of a machine always carry the dynamic information of the machine. These signals are very useful for the feature extraction and fault diagnosis. We performed a fundamental study which develops a system of fault diagnosis for a pump. We obtained noises by a microphone, analysed and compared the signals converted to Sequency range for normal products, artificially deformed products. We tried to search a change of noise signals according to machine malfunctions and analyse the type of deformation or failure. The results showed that acoustic signals as well as vibration signals can be used as a simple method for a detection of machine malfunction or fault diagnosis.