• 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.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.1
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• pp.95-113
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• 1997

This paper outlines a framework for a diagnosis of a complex system with uncertain information. Sensor validation ploys a vital role in the ability of the overall system to correctly determine the state of a system monitored by imperfect sensors. Here, emphases are put on the heuristic technology and post-processor for reasoning. Heuristic Sensor Validation (HSV) exploits deeper knowledge about parameter interaction within the plant to cull sensor faults from the data stream. Finally the modified probability distributions and validated data are used as input to the reasoning scheme which is the runtime version of the influence diagram. The output of the influence diagram is a diagnostic mapping from the symptoms or sensor readings to a determination of likely failure modes. Once likely failure modes are identified, a detailed diagnostic knowledge base suggests corrective actions to improve performance. This framework for a diagnostic expert system with sensor validation and reasoning under uncertainty applies in $HEATXPRT^{TM}$ a data-driven on-line expert system for diagnosing heat rate degradation problems in fossil power plants [1].

• International Journal of Precision Engineering and Manufacturing
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• v.8 no.3
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• pp.54-59
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• 2007

It is widely recognized that increasing the accuracy and diversity of rotating machinery necessitates an appropriate diagnostic technique and maintenance system. Until now, operators have monitored machinery using their senses or by analyzing simple changes to root mean square output values. We developed an expert diagnostic system that uses fuzzy inference to expertly assess the condition of a machine and allow operators to make accurate judgments. This paper describes the hardware and software of the expert diagnostic system. An assessment of the diagnostic performance for five fault phenomena typically found in pumps is also described.

• Journal of Applied Reliability
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• v.8 no.2
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• pp.101-111
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• 2008

Good diagnostics improves both the safety and system unavailability of digital safety systems. The measure of a diagnostic capability is called the Coverage Factor. Because the Failure Modes, Effects and Diagnostic Analysis (FMEDA) provides information on the failure rates and failure mode distributions necessary to calculate a diagnostic coverage factor for a component, the FMEDA can be used as a useful tool to calculate it. Through performing FMEDA on a digital signal processor (DSP) board used in a digital safety system, it is shown that some components of the DSP board can be replaced or improved to satisfy the required diagnostic coverage. That is, the FMEDA can serve as a useful verification tool to design a diagnostic capability for the DSP board.

• The Mathematical Education
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• v.42 no.5
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• pp.673-682
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• 2003

In this paper, we studied how to organize and develop a web based diagnostic-formative evaluation system. We investigated the interest of students about the system and analyze their scores after we applied this system to 10-th grade students for 10 months.

• The Journal of the Korean dental association
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• v.38 no.4 s.371
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• pp.357-368
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• 2000

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.453-456
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• 1992

Diagnostic prototype expert system was developed by analyzing the measured acoustical data of automobile. For the utilities of this system, 1/3 octave filter(band-pass filter) and A/D converter were used for data acquisition and then information was analyzed using signal processing technique and pattern recognition by Hamming network algorithm. In order to raise the reliability of the diagnostic results, fuzzy inference technique was applied and, the results were displayed as graphical method to help the novice in diagnostic field. The validation of this diagnostic system was checked through experiments and it showed and acceptable performance for diagnostic process.

• Journal of Acupuncture Research
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• v.24 no.6
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• pp.159-170
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• 2007

Objectives : The 7-zone-diagnostic system is a diagnostic device to predetermine bodily locations by measuring the energy of a living body. This study was to investigate the relation between the different patterns of Factor AA in a 7-zone-diagnostic system and clinical parameters. The purpose of this study is to relate Korean traditional medicine and western medicine using the data from the 7-zone-diagnostic system and the clinical parameters. Methods : This study was carried out with the data from some clinical parameters. We made two groups according to the Factor AA patterns of VEGA-DFM 722, the 7-zone-diagnostic system The Factor AA patterns of Group A named hyperenergy is all the red bar graphs that arehigher than the normal range. The Factor AA patterns of Group B named hypoenergy is all the red bar graphs that are lower than the normal range. After the data from clinical parameters corresponding with conditions of each group were selected, the data from clinical parameters among each group was analyzed statistically. Results : The values of Weight, GOT, r-GTP, Uric acid and BMI of Group A are higher than those of Group B. The values of Sodium and Phosphorus of Group A are lower than those of Group B. Conclusions : To conclude, it is thought that Group A has a heat-excess type but Group B has colddeficient type.

• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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• pp.1-7
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• 1997

The inference process for medical expert system is mostly formed by diagnostic knowledge on the if-then rule base. Oriental medicine diagnostic knowledge, however, may involve uncertain knowledge caused by ambiguous concept. In this paper, we analyze an oriental medicine diagnostic process by a rule-based inference system, and propose a method for representing and processing uncertain oriental medicine diagnostic knowledge using CLP( R ) which is a kind of constraint satisfaction program.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.54-61
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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. By using the FCM, authors have proposed FCM-based fault diagnostic algorithm. However, it can offer multiple interpretations for a single fault. In process engineering, as experience accumulated, some form of quantitative process knowledge is available. If this information can be integrated into the FCM-based fault diagnosis, the diagnostic resolution can be further improved. The purpose of this paper is to propose an enhanced FCM-based fault diagnostic scheme. Firstly, the membership function of fuzzy set theory is used to integrate quantitative knowledge into the FCM-based diagnostic scheme. Secondly, modified TAM recall procedure is proposed. Considering that the integration of quantitative knowledge into FCM-based diagnosis requires a great deal of engineering efforts, thirdly, an automated procedure for fusing the quantitative knowledge into FCM-based diagnosis is proposed by utilizing self-learning feature of neural network. Finally, the proposed diagnostic scheme has been tested by simulation on the two-tank system.