• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.639-642
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• 2000

Chemical facility system have dangerous elements that can injure the human like an explosion and a fire, gas poisoning by a leakage of the harmful chemical material. In addition to a vibration of the machine occurs the leakage. Therefore, the chemical factory requires for periodic monitoring of the vibration. But, until now, the operator has executed a monitoring of the machine by the senses. So, the diagnostic expert system by which the operator can judge easily and expertly a condition of the machine is developed. This paper describes the structure of diagnostic system and the diagnostic algorithm using fuzzy inference

• 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 the Korea Society of Computer and Information
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• v.21 no.1
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• pp.9-16
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• 2016

In this paper, we present a performance evaluation agent based on fuzzy cluster analysis and validity measures. The proposed agent is consists of three modules, fuzzy cluster analyzer, performance evaluation measures, and feature ranking algorithm for feature selection step in CAD system. Feature selection is an important step commonly used to create more accurate system to help human experts. Through this agent, we get the feature ranking on the dataset of mass and calcification lesions extracted from the public real world mammogram database DDSM. Also we design a CAD system incorporating the agent and apply five different feature combinations to the system. Experimental results proposed approach has higher classification accuracy and shows the feasibility as a diagnosis supporting tool.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1272-1278
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• 1999

A fault is considered as a variation of physical parameters; therefore the design of fault detection and identification(FDI) can be reduced to the parameter identification of a non linear system and to the association of the set of the estimated parameters with the mode of faults. Neuro-Fuzzy Inference System which contains multiple linear models as consequent part is used to model nonlinear systems. Generally, the linear parameters in neuro-fuzzy inference system can be effectively utilized to fault diagnosis. In this paper, we proposes an FDI system for nonlinear systems using neuro-fuzzy inference system. The proposed diagnostic system consists of two neuro-fuzzy inference systems which operate in two different modes (parallel and series-parallel mode). It generates the parameter residuals associated with each modes of faults which can be further processed by additional RBF (Radial Basis Function) network to identify the faults. The proposed FDI scheme has been tested by simulation on two-tank system.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1901-1910
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• 2023

The safety-class (1E) digital control system (DCS) of nuclear power plant characterized structural multiple redundancies, therefore, it is important to quantitatively evaluate the reliability of DCS in different degree of backup loss. In this paper, a reliability evaluation model based on T-S fuzzy fault tree (FT) is proposed for 1E DCS of nuclear power plant, in which the connection relationship between components is described by T-S fuzzy gates. Specifically, an output rejection control system is chosen as an example, based on the T-S fuzzy FT model, the key indicators such as probabilistic importance are calculated, and for a further discussion, the T-S fuzzy FT model is transformed into Bayesian Network(BN) equivalently, and the fault diagnosis based on probabilistic analysis is accomplished. Combined with the analysis of actual objects, the effectiveness of proposed method is proved.

• Electrical & Electronic Materials
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• v.11 no.11
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• pp.1-8
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• 1998

This paper presents an arificial neuro-fuzzy technique based prtial discharge (PD) pattern classifier to power system application. This may require a complicated analysis method employ -ing an experts system due to very complex progressing discharge form under exter-nal stress. After referring briefly to the developments of artificical neural network based PD measurements, the paper outlines how the introduction of new emerging technology has resulted in the design of a number of PD diagnostic systems for practical applicaton of residual lifetime prediction. The appropriate PD data base structure and selection of learning data size of PD pattern based on fractal dimentsional and 3-D PD-normalization, extraction of relevant characteristic fea-ture of PD recognition are discussed. Some practical aspects encountered with unknown stress in the neuro-fuzzy techniques based real time PD recognition are also addressed.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.12
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• pp.1545-1551
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• 1995

As the modern industrial processes become more complex, it is getting more difficult to model and control the processes. Naturally, an advanced type of DCS(Distributed Control System) with higher level functions is being sought. Advanced DCS is a DCS with advanced functions such as fault diagnosis, GPC(Generalized Predictive Control), NN(Neural Network), and Fuzzy Control. In this thesis, we have studied a fuzzy control algorithm for realizing an advanced DCS. Its algorithm is implemented in a form of function code which is a process control language, being used by the industrial engineers. To verify the realized function code of the fuzzy control, the function code is applied to a continuous casting process of the Pohang Iron & Steel Works in Kwangyang. The rules of the fuzzy control were collected via interviews of the field operators and their operation documents. Finally under a real-time operating system environment, usability of the function code of the fuzzy control is shown via simulation for the continuous casting process.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.486-495
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• 2001

This paper describes an implementation of the interval based expert system for syndrome differential diagnosis of Oriental Traditional Medicine (OTM). An approximate reasoning model using fuzzy logic for syndrome differential diagnosis is proposed. Based on this model, we implemented the system for diagnosing Eight rule diagnosis, organ diagnosis and then final differential syndrome of OTM. After carrying out inference process, the system will provide patient\`s syndromes differentiation diagnosis in the intervals and will give the explanation, which helps the user to understand the obtained conclusions.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.19 no.3
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• pp.141-149
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• 2015

Objectives Recently the fuzzy logic is widely used in the decision making, identification, pattern recognition, optimization in various fields. In this study, we propose the fuzzy logic as the objective method of distinguishing hot and cold, the basis of diagnosis in Korean medicine. Methods We developed fuzzy inference system to distinguish whether the subjects had hot or cold. The cold and hot questionnaire of Korean traditional university textbook, the pulse rate and the DITI value of face used in the system. These three kinds of information were defined as 'fuzzy sets,' and 54 fuzzy rules were established on the basis of clinical practitioners' knowledge. The fuzzy inference was performed by using the Mamdani's method. To evaluate the usefulness of the fuzzy inference system, 200 cases of data measured in the Woosuk university hospital of oriental medicine were used to compare the determining hot, normal, cold results obtained from the experts and from the proposed system. Results As a result, 100 cases of "cold", 54 cases of "normal", and 34 cases of "hot" were matched between the experts and the proposed system. This fuzzy system showed the conformity degree of 94%(${\kappa}=0.853$). Conclusions In this study, we could express the process of distinguishing hot-cold using the fuzzy logic for objectification and quantification of hot-cold identification. This is the first study that introduce a fuzzy logic for distinguish pattern identification. The degree of the heat characteristic of the patients inferred by this system could provide a more objective basis for diagnosing the hot-cold of patients.

• Computers and Concrete
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• v.6 no.4
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• pp.281-303
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• 2009

The lack of safety of bridge deck structures causes frequent repair and strengthening of such structures. The repair induces great loss of economy, not only due to direct cost by repair, but also due to stopping the public use of such structures during repair. The major reason for this frequent repair is mainly due to the lack of realistic and accurate assessment system for the bridge decks. The purpose of the present research was to develop a realistic expert system, called Bridge Slab-Expert which can evaluate reasonably the condition as well as the service life of concrete bridge decks, based on the deterioration models that are derived from both the structural and environmental effects. The diagnosis assessment of deck slabs due to structural and environmental effects are developed based on the cracking in concrete, surface distress and structural distress. Fuzzy logic is utilized to handle uncertainties and imprecision involved. Finally, Bridge Slab-Expert is developed for prediction of safety and remaining service life based on the chloride ions penetration and fick's second law. Proposed expert system is based on user-friendly GUI environment. The developed expert system will allow the correct diagnosis of concrete decks, realistic prediction of service life, the determination of confidence level, the description of condition and the proposed action for repair.