• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.674-679
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• 1987

Process failures can occur at any time during operation, so a continuous effort of fault detection, diagsis, and correction is required. Expert system paridigm has been regarded as a promising approach to real time process supervisory control especially to fault diagnosis. The most important aspects of fault diagnostic expert systems(FDES) are the problem-solving inference strategy and knowledge organizations. The necessity of FDES, the nature of diagnostic knowledge, the representation of knowledge, and the inference mechanism of FDES, et al. are described, which are announced by previous researchers. And the existing FDES are categorized and critically reviewed in this work.

• Journal of Environmental Science International
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• v.8 no.5
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• pp.611-616
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• 1999

The diagnostic software for the wastewater treatment plant using activated-sluge process is developed in order to increase the efficiency of management of the wastewater treatment plant. This software is based on the expert system and the visualized user interface, including the diagnosis of quantitative and qualitative data. For the generalization of this software, the initialization of each unit process and updating the files can be possible.

• Proceedings of the KIEE Conference
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• 2000.07c
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• pp.1885-1887
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• 2000

In this paper we introduce preventative and diagnostic systems developed to prevent substations from accidental fault of electric power transmitting apparatus. We propose monitoring and diagnostic system for ultra high voltage GIS and main transformer of 765kV substations as an example of preventative and diagnostic techniques being applied in Korea. We also present a guideline to construct and manage an expert system for this purpose. Finally, an engineering solution as a substation management support system is proposed.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.4
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• pp.47-54
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• 1998

As higher reliability on generator facilities is required to early detect incipient faults, a diagnostic system for predictive maintenance of the facility is highly recommended. In this paper, an expert system is developed suing the CLIPS - expert system tool - utilizing the knowledge on the insulation diagnosis and the vibration diagnosis on the rotating machines. This expert system, with user - friendly interface for operator, is easy to revise and add diagnostic rules and knowledge.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.11
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• pp.218-226
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• 1998

In this study a neural network based expert system designed to diagnose operating status of a rotating spindle system supported by ball bearings was introduced. In order to facilitate practical failure situations, five exemplary abnormal status was fabricated. Out of several possible data source locations, seven most effective spots were chosen and proven to be the most successful in predicting single and multiple abnormalities. Increased signal strength was measured around where abnormality was embedded. Signal mea-surement locations producing high prediction rate were also classified. Even though multiple abnormalities were hard to be decoupled into their individual causes, proposed diagnostic system was somewhat effective in predicting such cases under certain combination of sensor locations. Among several abnormal operating conditions, highest prediction rate can be expected when signal is spoiled by the failure or damage in outer race. Proposed diagnostic system was again proven to be the most effective system in analyzing and ranking the importance of data sources.

• Journal of the Korean Data and Information Science Society
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• v.8 no.2
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• pp.173-181
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• 1997

In oriental medicine, it is required that correct medical knowledge should be maintained for medical expert system which analyzes and diagnoses patients symptoms. Typical medical expert system has a knowledge base as its core, and the knowledge base contains a domain specific knowledge about patients records. However, oriental medicine diagnostic knowledge is formed mostly as qualitative data, knowledge could be ambiguous and uncertain. In this paper, we looked at quantification methods and propose a method for quantifying the oriental medicine diagnostic knowledge, which is improving the knowledge base of an oriental medicine expert system.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.12
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• pp.75-83
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• 2004

With the rotating machinery getting more accurate and diversified, the necessity fur an appropriate diagnosis technique and maintenance system has been greatly recognized. However, until now, the operator has executed a monitoring of the machine by the senses or simple the change of RMS (root mean Square) value. So, the diagnostic expert system using the fuzzy inference which the operator can judge easily and expertly a condition of the machine is developed through this study. In this paper, the hardware and software of the diagnostic expert system was composed and the identification of the diagnostic performance of the developed system for 5 fault phenomena was carried out.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.805-812
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• 1989

An efficient diagnostic approach for real-time operation aiding expert system in chemical process plants is discussed. The approach is based on the hybrid of the simplified symptom tree(SST) and the fault consequence digraph(FCD), representation of propagation patterns of fault states. The SST generates fault hypothesis efficiently and the FCD resolve the real fault accurately. Frame based knowledge representation and object-oriented programming make diagnostic system general and efficient. Truth maintenance system enables robust pattern matching and provides enhanced explain facilities. A prototype expert system for supports operation of naphtha furnaces process, called OASYS, has been built and tested to demonstrate this methodology. Utilization of diversified process symbolic data, produced using dynamic normal standards, overcomes the problem of qualitative Boolean reasoning and enhance the applicability.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.143-145
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• 1996

This paper presents the hybrid type based expert system for fault diagnosis in transformers. The proposed system uses the novel fault diagnostic technique based on dissolved gas analysis(DGA) in oil-immersed transformers. The uncertainty of key gas analysis, norm threshold, and gas ratio boundaries are managed by using a fuzzy set. Also, the uncertainty of the fault diagnostic rules are handled by using fuzzy measures. Finally, kohnen's feature map performs fault classification in transformers. To verify the effectiveness of the proposed diagnosis technique, the hybrid type based expert system for fault diagnosis has been tested by using KEPCO's transformer gas records.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.4
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• pp.29-35
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• 2003

The rotating machineries always generate harmonic frequencies of their own rotating speed, and increment of vibration amplitude affects to the equipments which connected to the vibrational source and causes industrial calamities. The life cycle of equipments can be extended and damages to the human beings could be prevented by identifying the cause of malfunctions through prediction of the increment of vibration and records of vibrational history. In this study, therefore, diagnostic expert algorithm for the centrifugal pump is developed by integrating fuzzy inference method and signal processing techniques. And the validity of the developed diagnostic system is examined via various computer simulations.