• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 추계학술대회 논문집
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• pp.954-957
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• 2005

In order to implement Artificial Intelligence, various technologies have been widely used. Artificial Intelligence is applied for many industrial product and machine tools are the center of manufacturing devices in intelligent manufacturing system. The purpose of this paper is to present the construction of Rule Base for knowledge structure that is applicable to machine tools. This system is that decision whether to act in accordance with machine status is support system. It constructs Rule Base of knowledge used of machine toots. The constructed Rule Base facilitates the effective operation and control of machine tools and will provide a systematic way to integrate the expert's knowledge that will apply Intelligent Machine Tools.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.1467-1470
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• 2003

In order to enhance the productivity of design and manufacture of injection molds, various computer-aided systems have been developed and introduced to mold manufacturers. The customized 3-D CAD systems for mold design is one of the most representative computer-aided system. However, these systems usually do not provide a convenient way to access and manage design knowledge implemented in them. To overcome this shortage, knowedge-based engineering systems have been developed, and now they are imbedded as modules of commercial CAD systems. In this paper, we introduced a 3-D design system for standard mold base based on Knowledge Fusion, a commercialized KBE system imbedded in Unigraphics. By introducing KBE system, design knowledge can be exposed to the users and modified by the end-users.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.807-810
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• 2003

This research uses high-resolution satellite images as a source of collecting farmland information. For effectively extract the paddy area, we use texture information and different classify methods to assist the satellite image classification. First, using maximum likelihood classifier to extract paddy information from images. The results show that User Accuracy and Procedure Accuracy of the paddy area can increase from 80.60% to 95.45% and 84.38% to 95.45%. Second, establishing a paddy Knowledge Base and using Knowledge Base Classifier to extract paddy area, and result shows the User Accuracy and Producer Accuracy to be 92.16% and 90.06%. Finally, The result shows we can effectively contribute to the paddy field information extraction from high-resolution satellite images.

• 대한토목학회논문집
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• 제12권1호
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• pp.9-17
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• 1992

본 논문에서는 교량의 예비설계 단계중에서 상부구조 형식의 선정에 대한 전문가 시스템을 구축하는 것을 나타낸다. 본 시스템을 구축하기 위한 도구로는 전진추론방식 및 생산시스템으로 지식표현되는 전문가 시스템 개발용 도구인 K-CLIPS가 이용되었으며, 이 도구 위에서 구성된 지식 모듈, 데이터 베이스 및 지식 베이스로 시스템이 구성되었다. 지식 모듈은 주로 교량의 형식 선정과정을 관리하는 설계순서에 관한 지식이고, 지식 베이스 내에 있는 각 부 시스템이 심볼처리에 의해 수행되는 과정에서 데이타 베이스는 이를 지원해 주는 역할을 한다.

• 대한전기학회논문지:전력기술부문A
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• 제48권6호
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• pp.800-806
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• 1999

This paper proposes IIKBAG(Intelligent Interlocking Knowledge Base Generator) which can build automatically the interlocking knowledge base utilized as the real-time interlocking strategy of the electronic interlocking system in order to enhance it's reliability and expansion. The IIKBAG consists of the inference engine and the knowledge base. The former has an auto-learning function which searches all the train routes for the given station model based on heuristic search technique while dynamically searching the model, and then generates automatically the interlocking patterns obtained from the interlocking relations of signal facilities on the routes. The latter is designed as the structure which the real-time expert system embedded on IS(Interlocking System) can use directly in order to enhances the reliability and accuracy. The IIKBAG is implemented in C computer language for the purpose of the build and interface of the station structure database. And, a typical station model is simulated to prove the validity of the proposed IIKBAG.

• 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.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2008년도 추계학술대회
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• pp.5-8
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• 2008

This study proposed the Knowledge Base Building method reflecting the user's preferences based on the fuzzy set theory to develop information contents which support pedestrian's navigation. This research evaluated subject's preferences on the commercial spaces set to the hypothetical destination. Also it surveyed the causal relationship between the visual characteristics and the emotional characteristics to propose the methods of Navigation Knowledge Base (NKB). The NKB was composed by three elements; 1.the correlation model between emotional characteristics, 2.the causal relationship between visual characteristics and emotional characteristics, 3.the transformation model between visual characteristics and the physical characteristics.

• 대한안전경영과학회지
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• 제9권5호
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• pp.79-85
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• 2007

Intelligent machines respond to external environments on the basis of decisions that are made by sensing the changes in the environment and analyzing the obtained information. This study focuses on the construction of a knowledge base which enables decision making with that information. Approximately 70% of all errors that occur in machine tools are caused by thermal error. In order to proactive deal with these errors, a system which measures the temperature of each part and predicts and compensates the displacement of each axis has been developed. The system was built in an open type controller to enable machine tools to measure temperature changes and compensate the displacement. The construction of a machining knowledge base is important for the implementation of intelligent machine tools, and is expected to be applicable to the network based intelligent machine tools which look set to appear sooner or later.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 추계학술대회논문집 II
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• pp.633-639
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• 2001

This paper proposes a knowledge-based expert system. which is assembled into hardware organized with sensor module. AID converter, USB. data acquisition PC and software composed of monitoring and diagnosis module combined with a frame-based method using Sohre's chart and a rule-based method. Vibration signals using various sensors are acquired by AID converter. transferred into PC and processed to obtain a continuous monitoring of the machine status displayed into several plots. Through combining frame-base which covers wide vibration causes with rule-base which gives relatively specified diagnosis results, high accuracy of fault diagnosis can be guaranteed and knowledge base can be easily extended by adding new causes or symptoms. Some examples using experimental data show the good feasibility of the proposed algorithm for condition monitoring and diagnosis of industrial rotating machinery.

• 지식경영연구
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• 제1권1호
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• pp.81-90
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• 2000

This study proposes the knowledge discovery process for the effective mining of knowledge on the web. The proposed knowledge discovery process uses the Prior knowledge base and the Prior knowledge management system to reflect tacit knowledge in addition to explicit knowledge. The prior knowledge management system constructs the prior knowledge base using a fuzzy cognitive map, and defines information to be extracted from the web. In addition, it transforms the extracted information into the form being handled in mining process. Experiments using case-based reasoning and neural network" are performed to verify the usefulness of the proposed model. The experimental results are encouraging and prove the usefulness of the proposed model.