• 한국해양공학회지
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• 제11권1호
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• pp.36-43
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• 1997

Weld bead shape is an important measure for evaluation of weld quality. Many welding parameters have influence on the weld bead shape. The quantitative relationship between welding parameters and bead shape, however, is not determined yet because of their high complexity and many unknown factors. Fuzzy expert system is an advanced expert system which uses fuzzy rules and approximate reasoning. It is a vert useful tool for welding technology because is can process rationally the uncertain and inexact information such as the welding information. In this paper, the empirical and the qualitative relationship between welding parameters and bead shape are analyzed and represented by fuzzy rules. They are converted to the quantitative relationship by use of approximate reasoning of fuzzy expert system. Weld bead shape is estimated from the welding parameters using fuzzy expert system. The result of comparison between measured values of weld bead by welding experiments and the estimates values by fuzzy expert system shows a good consistancy.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2004년도 춘계학술대회 논문집
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• pp.194-197
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• 2004

In the tube hydroforming process, a tube is placed into the die cavity and the ends of the tube are sealed by fixing the axial cylinder piston into the ends. Then the tube is pressurized with a hydraulic fluid and simultaneously the axial cylinders move to feed the material into the expansion zone. Therefore, the quantitative relationship between process parameters such as internal pressure and feeding amount and hydroformabillity, is hard to establish because of their high complexity and many unknown factors. In this study, the empirical and the quantitative relationship between process parameters and hydroformabillity are analyzed by fuzzy rules. Fuzzy expert system is an advanced expert system which uses fuzzy rule and approximate reasoning. Many process parameters are converted to the quantitative relationship by use of approximate reasoning of fuzzy expert system. The comparison between experimentally measured hydroformabillity from hydroforming experiments and the predicted values by fuzzy expert system shows a good agreement.

• 한국지능시스템학회논문지
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• 제11권3호
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• pp.231-240
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• 2001

Conventional expert systems has been criticized due to its lack of capability to adapt to the changing decision-making environments. In literature, many methods have been proposed to make expert systems more environment-adaptive by incorporating fuzzy logic and neural networks. The objective of this paper is to propose a new approach to building a self-evolving expert system inference mechanism by integrating fuzzy neural network and fuzzy rule extraction technique. The main recipe of our proposed approach is to fuzzify the training data, train them by a fuzzy neural network, extract a set of fuzzy rules from the trained network, organize a knowledge base, and refine the fuzzy rules by applying a pruning algorithm when the decision-making environments are detected to be changed significantly. To prove the validity, we tested our proposed self-evolving expert systems inference mechanism by using the bankruptcy data, and compared its results with the conventional neural network. Non-parametric statistical analysis of the experimental results showed that our proposed approach is valid significantly.

• 지능정보연구
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• 제8권1호
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• pp.63-74
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• 2002

본 논문에서는 용해로 이상감시를 위한 실시간 유리 용해로 운전 전문가시스템을 구축한 결과를 소개한다. 유리용해 공정에서는 운전자의 경험지식에 의해 내부의 상황을 판단하게 되고, 이는 용해로 수명과 제품의 품질에 중요한 영향을 준다 이를 전문가 시스템으로 구현하기 위하여, 먼저 기존 운전자의 지식을 취합, 분석한다. 그 후, 취합된 각 지식들의 특성에 부합하도록 이진 규칙(Crisp Rule)과 퍼지 규칙(Fuzzy Rule)으로 구분한다. 이 때, 선형 회귀분석을 통하여 퍼지 규칙의 입력을 결정함으로써 보다 정확한 운전 지식의 표현이 가능하도록 하였다. 설계된 알고리즘은 젠심(Gensym)사의 실시간 전문가 시스템 개발 툴인 G2를 사용하여 구현하였다. 제시된 퍼지 전문가 시스템은 삼성코닝(주) 수원사업장의 실제 생산 용해 공정에 직접 적용하여 그 효율성이 검증되었다.

• 전자공학회논문지B
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• 제31B권10호
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• pp.53-66
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• 1994

In this paper, a fuzzy expert system is developed for fault diagnoisis of a drum-type boiler system in fossil power plants. The develped fuzzy espert system is composed of knowledge base, fuzzification module, knowledge base process module, knowledge base management module, inference module, and linguistic approximation module. The main objective of the fuzzy expert system is to check the states of the system including the drum level and detect faults such as the feedwater flow sensor fault, feedwater flow control valve fault, and water wall bube rupture. The fuzzy expert system diagnoses faults using process values, manipulated values, and knowledge base which is built via interviews and questionaries with the experts on the plant operations. Finally, the validity of the developed fuzzy expert system is shown via experiments using the digital simulator for boiler system is Seoul Power Plant Unit 4.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2000년도 봄 학술발표회 논문집
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• pp.101-108
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• 2000

In this study, an expert system was developed to predict the safety of tunnel and choose proper tunnel reinforcement system using fuzzy quantification theory and fuzzy inference rule based on tunnel information database. The expert system developed in this study have two main parts named pre-module and post-module. Pre-module decides tunnel information imput items based on the tunnel face mapping information which can be easily obtained in-situ site. Then, using fuzzy quantification theory II, fuzzy membership function is composed and tunnel safety level is inferred through this membership function. The comparison result between the predicted reinforcement system level and measured ones was very similar. In-situ data were obtained in three tunnel sites including subway tunnel under Han river, This system will be very helpful to make the most of in-situ data and suggest proper applicability of tunnel reinforcement system developing more resonable tunnel support method from dependance of some experienced experts for the absent of guide.

• 산업경영시스템학회지
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• 제23권54호
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• pp.155-165
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• 2000

The fault diagnosis is a systematic and unified method to find based on the observing data resulting in noises. This paper presents the fault prediction and diagnosis using fuzzy expert system technique to manipulate the uncertainties efficiently in predictive perspective. We apply a fuzzy event tree analysis to the computer system, and build up the fault prediction and diagnosis using fuzzy expert system that predicts and diagnoses the error of the system in the advance of error.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권6호
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• pp.457-464
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• 2004

Hard Disk Drive (HDD) test system is an equipment for the final test of HDD product by iterative read/write/seek test. This paper proposes an expert system for the fault diagnosis of HDD test systems. The purposed expert system is composed with two cascade inference, fuzzy logic and conventional binary logic. The fuzzy logic determines the possibility of the system fault using the test history data, then, the binary logic inferences the fault location of the test system. The proposed expert system is tested in SAMSUNG HDD production line, KUMI, KOREA, and shows satisfactory results.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.759-762
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• 2002

A preliminary design process in the multi-stage gear drives design is important part. a preliminary design support system which run efficiently the design is developed with fuzzy expert system. the system automatically generate the mechanism of multi-stats gear drives and select a candidate mechanism by the general expert rule and sorting using fuzzy expert system. the preliminary mechanism design of multi-stage gear drives have a short execution time, add accuracy in a preliminary design considering volume, cost, power and efficiency in preliminary, a design efficiency is increased and a preliminary design have a elasticity using a weight on variable's sorting mechanism.

• 제어로봇시스템학회논문지
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• 제9권10호
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• pp.782-788
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• 2003

Making deicing countermeasure plan against snow accretion on power line is a very complicated problem, which should take into account both the possibility of accidents due to snow accretion on power line and the stable operation of power system. As knowledge engineering can be a good solution to this field of problems, a prototype expert system to assist power system operators in forecasting snow accretion on power lines and making a list of all the feasible and effective deicing countermeasures has been developed. The system has been remodelled into a fuzzy expert system by adopting fuzzy rulebase and fuzzy inference method to systematically process the fuzziness included in the heuristic knowledges. Simulation results based on the past snow accretion accident data show that the proposed system is very promising.