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DEVELOPMENT OF A KNOWLEDGE-BASED HYBRID FAILURE DIAGNOSIS SYSTEM FOR URBAN TRANSIT
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  • DEVELOPMENT OF A KNOWLEDGE-BASED HYBRID FAILURE DIAGNOSIS SYSTEM FOR URBAN TRANSIT
  • DEVELOPMENT OF A KNOWLEDGE-BASED HYBRID FAILURE DIAGNOSIS SYSTEM FOR URBAN TRANSIT
저자명
Kim. H.J.,Bae. C.H.,Kim. S.H.,Lee. H.Y.,Park. K.J.,Suh. M.W.
간행물명
International journal of automotive technology
권/호정보
2009년|10권 1호|pp.123-129 (7 pages)
발행정보
한국자동차공학회
파일정보
정기간행물|ENG|
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기타
이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
서지반출

기타언어초록

Urban transit is a complex system that contains both electrical and mechanical entities; therefore, it is necessary to construct a maintenance system for ensuring safety during high-speed driving. Expert systems are computer programs that use numerical or non-numerical domain-specific knowledge to solve problems. This research aims to develop an expert system that diagnoses the causes of failures quickly and displays measures to correct them. For the development of this expert system, the standardization of a failure code classification and the creation of a Bill of Materials (BOM) were first performed. Through the analysis of both failure history and maintenance manuals, a knowledge base has been constructed. Also, for retrieving the procedure of failure diagnosis and repair linking with the knowledge base, we have built a Rule-Based Reasoning (RRB) engine with a pattern matching technique and a Case-Based Reasoning (CBR) engine with a similar search method. Finally, this system has been developed as web based in order to maximize accessibility.