• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.237-244
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• 2008

In this paper, an infra-structure using the ontology based on the pulse information is proposed for the context-aware service of medical information system in ubiquitous computing environment. An diagnosis service inference system that represents the pulse data which was generated by the pulse-diagnosis with wearable signal, temperature, humidity, time, and other factors as ontology with artificial intelligence methods and describes the service scenario based on the ontology is designed and implemented.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.279-284
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• 2005

Knowledge based fault diagnosis has a limitation in determining the cause and scheme for the fault, because it detects faults from signal pattern only Therefore, model-based fault diagnosis is requested to determine the fault by analyzing output of the equipment from its dynamic model. This research shows a method how to devise the automaton of system as a model for normal and faulty condition through the reduction of handling data by quantization of vibration signals and the example which is concerning to the bearing of ATM. The developed model based fault diagnosis was applied to detect the faulty bearing of ATM, which results.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.11
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• pp.1009-1017
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• 2010

As rotating machines play an important role in industrial applications such as aeronautical, naval and automotive industries, many researchers have developed various condition monitoring system and fault diagnosis system by applying various techniques such as signal processing and pattern recognition. Recently, fault diagnosis systems using artificial neural network have been proposed. For effective fault diagnosis, this paper used MLP(multi-layer perceptron) network which is widely used in pattern classification. Since using obtained signals without preprocessing as inputs of neural network can decrease performance of fault classification, it is very important to extract significant features of captured signals and to apply suitable features into diagnosis system according to the kinds of obtained signals. Therefore, this paper proposes the decision method of the proper feature vectors about each fault signal for neural-network-based fault diagnosis system. We applied LPC coefficients, maximum magnitudes of each spectral section in FFT and RMS(root mean square) and variance of wavelet coefficients as feature vectors and selected appropriate feature vectors as comparing error ratios of fault diagnosis for sound, vibration and current fault signals. From experiment results, LPC coefficients and maximum magnitudes of each spectral section showed 100 % diagnosis ratios for each fault and the method using wavelet coefficients had noise-robust characteristic.

• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.511-518
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• 2008

Medical diagnosis systems have been developed to make the knowledge and expertise of human experts more widely available, therefore achieving high-quality diagnosis. In this study, in order to support the diagnosis by the medical diagnosis system, we have preformed medical diagnosis inference three times: first by a neural network with the backpropagation algorithm, secondly by a discriminant analysis with all of the variables, and thirdly by a discriminant analysis with the selected variables. A discussion on comparison of these three methods has been provided.

• Journal of Physiology & Pathology in Korean Medicine
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• v.17 no.5
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• pp.1147-1150
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• 2003

Modern Objectification of Pulse Diagnosis, One of the Four Diagnosis Method of Oriental Medicine, is necessarily project to improving Oriental medical clinic status and quality by standardization of diagnosis database. At that, accurate measurement equipment or devices(sensor, system and instruments, etc,) to exactly detect MacSang(脈診 : the parameter and subject of pulse diagnosis) have not developed yet. Existing Pulse diagnosis devices are not satisfy clinical needs and medical equipments quality. We study for pulse diagnosis system, that CD is satisfying oriental medical clinic needs, is ensuring accuracy and reappearance to support in clinical diagnosis and treatment, is guaranteeing the quality of medical equipments. theoretical base and convenience.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8B
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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.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.6
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• pp.744-750
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• 2014

The monitoring and abnormality warning of marine diesel engine are important to take appropriate responses for safety navigation. If maintenance engineers do not take appropriate response because of diagnosis mistakes, it will occur a nasty accident. Therefore, we need integrated monitoring and diagnosis system for supporting a diagnosis objectively. In this paper, we analyze time-series data which measured by real-time, monitor the changing of conditions and trends of the analyzed data. Furthermore, we design and implement a monitoring and diagnosis system for objective supporting of real-time diagnosis. When the integrated monitoring and diagnosis system is adopted, it can help to improve stability of marine diesel engine by providing abnormality warning alarm with appropriate responses.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.455-456
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• 2002

Wear is one of the main factors causing breakdown and fault of machine, so ferrography technique analyzing wear particles can be an effective way for condition monitoring and fault diagnosis. On the base of the forward multilayer neural network, a nodes self-deleting neural network model is provided in this paper. This network can itself deletes the nodes to optimize its construction. On the basis of the nodes self-deleting neural network, an intelligent ferrography diagnosis expert system (IFDES) for wear particles recognition and wear diagnosis is described. This intelligent expert system can automatically slim lip knowledge by learning from samples and realize basically the entirely automatic processing from wear particles recognition to wear diagnosis.

• Journal of Ocean Engineering and Technology
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• v.15 no.4
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• pp.101-107
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• 2001

This paper describes a fault diagnosis method by a T-invariance of Petri Net (PN). First, a complicated fault system with some failure is modeled into a PN graphic expressions. Next, the PN model is analyzed by using the backward chaining of T-invariance to find out causes of the faults. In this step, an inter-node search technique which is suggested in this paper is applied for reducing searching area in the fault system. Also, a novel idea to compose incidence matrices which have different dimension each other in PN model is proposed. As the new knowledges which is discovered newly about faults can be added easily to conventional systems, the diagnosis system will be very flexible. Finally, the proposed method is applied to the automobile fault diagnosis system to confirm the validity of the method.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.2041_2042
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• 2009

The diagnostic/prognostic problems for condition based maintenance or Prognostics and Health Management has been used. Primary objectives of diagnosis/prognosis are maximizing system availability and minimizing downtime from fault isolation through more effective troubleshooting efforts. Diagnosis aims to detect the onset of failures to improve system performance and reduce life cycle cost by reducing the failure time. The prognosis can reduce operational and support total ownership cost and improve safety of machinery and complex systems. In this Paper, a fault diagnosis methodology has been described using a monopropellant propulsion system model as a test bench.