• Journal of the Korean Society for Precision Engineering
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• v.12 no.6
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• pp.37-44
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• 1995

Grinding is used for machining high precision parts with high additional value. However, the grinding operation needs high skill and long experience of an operator because of a lack of the scientific knowledge and engineering principles. Also, the wheel and grinding conditions affect grinding results. For these reasons, it is difficult to construct computer integrated manufacturing system(CIMA). Therefore, it is necessary for Expert System to be informed of qualitative knowledge of grinding expert's skills and experiences. In this research, the Grinding Expert System is constructed by Fuzzy Decision Making Algorithm. Using this system, unskilled workers will be able to use the knowledge and experience of an expert.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.261-262
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• 2008

Failure Mode Effects and Criticality Analysis (FMECA) evaluates criticality and severity of each failure mode. Generally, those indices are determined subjectively by experts and operators. However, this process has no choice but to include uncertainty. In this paper, a method for eliciting expert opinions considering its uncertainty is proposed to evaluate the criticality and severity. In addition, a fuzzy expert system is constructed to determine the crisp value of risk level for each failure mode. The results are worth considering while deciding the proper policies for each component of the system.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.300-303
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• 2013

On BIPV systems, especially roof-top PV systems, the power generation is easier to be reduced due to the shades of facilities nearby, or roof itself. To secure profitability of roof-top PV systems, the optimal design of solar arrays through the precise shading analysis is an important item of design considerations. In this paper, an optimization system for array design of roof-top PVs is to be developed using three-dimensional Geospatial Information System(GIS). The profitability of income and expense is considered through the shading analysis of entire roofs. By applying the system to project for validation, the adequacy and the improvement of NPV of the system were verified compared to expert's design. The system has significance by reason that PV modules are placed through rules established with expert knowledge and geometric rules were applied to reflect the constructability and maintainability.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.9
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• pp.703-712
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• 2003

This paper suggests a fuzzy expert system for fault diagnosis of rotating machinery, based on modulated databases. In the proposed system, alarm and trip levels are set based on ISO, considering operating condition, machinery type and maintenance history. Input signals for diagnosis, such as sub-and super-harmonic components of vibration and mean value, are normalized from 0 to 1 under the threshold level and otherwise equal to one so that chronic faults slightly below the threshold level can be monitored. The database for diagnosis consists of two modules: the well-known Sohre's chart module and if-then type rules. The Sohre's chart is utilized for the most common problems of high-speed turbomachinery, while the rule-based module, which was collected from many papers and reports, is for diagnosing peculiar faults according to the type of machinery. To infer the results from two modules, a fuzzy operation of Yager sum was adopted. Using a simulator constructed in laboratory, experimental verification was performed for the cases of unbalance and resonance which were intended. The experimental results show that the proposed fuzzy expert system has feasibility in practical diagnosis of rotating machinery.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.303-312
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• 2003

This paper suggests a fuzzy expert system for fault diagnosis of rotating machinery, based on modulated databases. In the proposed system, alarm and trip levels are set based on ISO, considering operating condition, machinery type and maintenance history. Input signals for diagnosis, such as sub- and super-harmonic components of vibration and mean value, are normalized from 0 to 1 under the threshold level and otherwise equal to one so that chronic faults slightly below the threshold level can be monitored. The database for diagnosis consists of two modules: the well-known Sohre's chart module and if-then type rules. The Sohre's chart is utilized for the most common problems of high-speed turbomachinery, while the rule-based module, which was collected from many papers and reports, is for diagnosing peculiar faults according to the type of machinery. To infer the results from two modules, a fuzzy operation of Yager sum was adopted. Using a simulator constructed in laboratory, experimental verification was performed for the cases of resonance and housing looseness which were intended. The experimental results show that the proposed fuzzy expert system has feasibility in practical diagnosis of rotating machinery.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.50 no.11
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• pp.562-568
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• 2001

In this paper, we described the export system to monitor and diagnose 765KV power apparatus. To develop this expert system, we studied the knowledge bases and data bases for 765KV transformer and GIS. In order to make the reliable inference of knowledge base and the good MMI(Man Machine Interface), the data bases were consisted of the tables of power apparatus information, limit level value, measured input data, inference result and diagnosis result. The knowledge base had various rules to infer the conditions of transformer and GIS. We applied both the forward chaining and backward chaining methods to these rules of system for good inferences. This paper describes the applied methods for expert system. Also, this developed system was tested with dissolved gas analyzing result and the result was shown.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.51 no.4
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• pp.152-157
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• 2002

This paper describes an effect of a single- and a quadruple-lightning impulse currents on electrical characteristics of ZnO blocks, and an expert system to diagnose arrestor deterioration. To deduce the parameters needed for diagnosing arrester deterioration, an accelerate deterioration teat is carried out. In the experiment, leakage current components are measured. Also, wave height distribution of the leakage current according to the progress of arrester deterioration is analyzed. From the experimental results, the wave height distribution of the leakage current showed conspicuous difference even in an immaterial leakage current increase. Therefore, the use of wave height distribution of the leakage current in deterioration diagnostic technique makes more accurate diagnosis than the conventional method by using only a leakage currant value. Finally, the expert system based on the experimental results is developed and the system can diagnose arrestor deterioration by measuring the leakage current and its wade height distribution.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.12 no.3
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• pp.59-71
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• 2009

The goals of this study were to development Natural Ecosystem Value Assessment Model, to suggest the practical applicability of the Natural Ecosystem value assessment for development areas, and to assess natural ecosystem quantitatively using GIS. The Model can evaluate Natural Ecosystem Value between before and after land developments. To select indicators for the model, we conducted the literature reviews. and six indicators and the standard of evaluation had been developed through the expert interviews and literature reviews. the relative importance of the evaluation index throught two times expert questionnaires was found out. the Natural Ecosystem Value Assessment Model has been established, The results demonstrate that although the suggested six indicators are arranged by priority, to maintain quantitative and qualitative the natural ecosystem value, all indicators are desirable to be maintained complementarily. The findings of this study suggest that the natural ecosystem value assessment model appears to be effective an assessment for damaged natural environment value and possible to assign a score value. Also, this model can be applied to research areas and has implications to help maintain the natural ecosystem in land development districts.

• Journal of Computing Science and Engineering
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• v.2 no.1
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• pp.1-25
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• 2008

Spoken dialog tasks incur many errors including speech recognition errors, understanding errors, and even dialog management errors. These errors create a big gap between the user's intention and the system's understanding, which eventually results in a misinterpretation. To fill in the gap, people in human-to-human dialogs try to clarify the major causes of the misunderstanding to selectively correct them. This paper presents a method of clarification techniques to human-to-machine spoken dialog systems. We viewed the clarification dialog as a two-step problem-Belief confirmation and Clarification strategy establishment. To confirm the belief, we organized the clarification process into three systematic phases. In the belief confirmation phase, we consider the overall dialog system's processes including speech recognition, language understanding and semantic slot and value pairs for clarification dialog management. A clarification expert is developed for establishing clarification dialog strategy. In addition, we proposed a new design of plugging clarification dialog module in a given expert based dialog system. The experiment results demonstrate that the error verifiers effectively catch the word and utterance-level semantic errors and the clarification experts actually increase the dialog success rate and the dialog efficiency.