• 한국정밀공학회지
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• 제7권3호
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• pp.66-74
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• 1990

This paper presents a knowledge-based computer aided process planning system that automatically selects machine tools, machining operations and cutting tools and determines sequences of the machining operations for prismatic parts in die manufacturing. In the proposed system, parts are described by manufacturing features and grouped into part families based on the functions. Each part is repressented by a part frame which consists of basic data and manufacturing features. Knowledge for manufacturing is acquired from the domain expert and represented by frames. A decision model for selection of machine tools, machining operations and cutting tools and for determining sequences of the machining operations are developed by employing the Mealy machine in finite automata with output. The decision procedure and the order of priority which inputs manufacturing features into the Mealy machine are represented by rule for each part family. Backward chaining is used for the proposed system. The proposed system is implemented by using TURBO-PROLOG on the IBM PC/AT. A case study for the slide core is presented to show the function of the proposed system.

• 한국안전학회지
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• 제7권4호
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• pp.105-114
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• 1992

This paper presents an study on the knowledge based system for diagnosing the fire causes using the Fuzzy Possibility Measure( FPM ) about the electric-fire ignition. The Ignition values needed for causes diagnosis is computed as FPM for electric-fire ignition based on the internal scale technique that assigns numerically the characteristic difference of facts to the-tin-ear scale. For the convinience of inference, ignition sources are classified into seven types : short, ground fault, leakge of electricity, overcurrent, cord junction overheating, bad Insulation and spark. The system for causes diagnosis of electric-fire is composed of Knowledge Acquisition System, Inference Engine and Man-Machine Interface, The diagnosis system is wrritten in an artificial intelligence langusge “PROLOG” which uses depth-first search and backward chaining schemes in reasoning process.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.714-717
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• 1996

This paper presents a fault detection and diagnosis methodologies based on weighted symptom model and pattern matching between the coming fault propagation trend and the simulated one. At the first step, backward chaining is used to find the possible cause candidates for the faults. The weighted symptom model(WSM) is used to generate those candidates. The weight is determined from dynamic simulation. Using WSMs, the methodology can generate the cause candidates and rank them according to the probability. Secondly, the fault propagation trends identified from the partial or complete sequence of measurements are compared to the standard fault propagation trends stored a priori. A pattern matching algorithm based on a number of triangular episodes is used to effectively match those trends. The standard trends have been generated using dynamic simulation and stored a priori. The proposed methodology has been illustrated using two case studies and showed satisfactory diagnostic resolution.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.430-435
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• 1992

Hazard identification is one of the most important task in process design and operation. This work has focused on the development of a knowledge-based expert system for HAZOP (Hazard and Operability) studies which are regarded as one of the most systematic and logical qualitative hazard identification methodologies but which require a multidisciplinary team and demand much time-consuming, repetitious work. The developed system enables design engineers to implement existing checklists and past experiences for safe design. It will increase efficiency of hazard identification and be suitable for educational purposes. This system has a frame-based knowledge structure for equipment failures/process material properties and rule networks for consequence reasoning which uses both forward and backward chaining. To include wide process knowledge, it is open-ended and modular for future expansion. An application to LPG storage and fractionation system shows the efficiency and reliability of the developed system.

• 대한전기학회논문지
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• 제39권10호
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• pp.1021-1028
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• 1990

본 논문은 전력계통의 고장진단 전문가시스템에 관한 것으로서 개발된 전문가 시스템은 전력계통에서의 사고 발생시 그 고장구간을 추정하고 보호기기의 오.부작동을 판정하며 이를 통하여 고장의 전파과정을 설명하도록 고안되었으며 또한 사고발생후 취하여질 복구작업에 필수적으로 요구되는 정전구역의 탐색의 효율을 위하여 탐색구간을 제한하였다. 본 전문가 시스템은 포롤로그 언어를 사용하여 구성하였으며 모의계통에 적용하여 그 요 성을 입증하였다. 입증하였다.

• 한국화재소방학회논문지
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• 제6권2호
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• pp.33-39
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• 1992

This work presents an expert system for the classification of a given substance and thus enabling one to select the proper container in consultation with the computer. The system consists of 34 rules and uses Micro Expert as a shell program based on backward chaining method. The prototype system will have to be under extensive test. However, its use is bound to have advantages over conventional methods, e.g. looking up in a reference book or using conventional programs with a database. Since the expert system determines the group of the given substance not by its name but by its physical and chemical properties, it is not necessary to add data items even for newly synthesized substances. The system also provides reasoning for its determination and therefore it can be used as a good package for the training of unskilled operators.

• 한국안전학회지
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• 제7권1호
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• pp.31-38
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• 1992

This paper presents a study on application of expert system technique for the diagnosis of fire-causes in plants. A need is recognized for new methods to diagnose exactly the causes of fires without the help of the human experts. To cope with the difficulty, the expert system techiuque is applied to this area. The expert system suggested in this paper is developed to infer the causes of fires(or, ignition source ) by using the information drawn from the circumstances in fire. For the convenience of inference, ignition sources we classified into eight types ; elecoic spark, adiabatic compression, welding spark, material of high temperature, impact and friction, spontaneous ignition, naked fire, and static electricity. The knowledge base is composed of the rule base and dynamic database, which contain the rules and facts obtained by the expenence in this area, respectively. Both depth-first search and backward chaining schemes are used in reasoning process. This expert system is written in an artificial intelligence language "PROLOG", and its availability is demonstrated through the case study.

• 대한기계학회논문집
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• 제14권5호
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• pp.1138-1146
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• 1990

본 연구에서는 이러한 지식기반 전문가 시스템을 이용하여 에너지 저장용 기 계요소인 플라이 위일의 설계를 보조해 주는 지식기반 전문가 시스템을 개발하고자 한 다. 즉 플라이 휘일의 설계, 제작 과정을 크게 개념 설계, 상세 설계 및 해석, 제작, 시험의 단계로 분류할 때 본 연구의 목적은 초기 설계 단계인 개념 설계에 도움을 주 는 시스템을 구성하는 데 있다.프로그램의 구성은 정성적인 경험, 지식을 다룰 수 있는 기호적인 (symbolic)계산과 간단한 수치적인 (numerical)계산을 함께 할 수 있는 복합시스템(hybrid system)으로 구성하고 이러한 과정을 체계적이고 조직적으로 수행 하고 지식의 첨삭이 용이하도록 전체 설계광정을 계층 구조(hierarchical structure) 화하고 설계 자료를 자료 기반화하여 관리하며 그래픽과 연계시켜 전체 지식 기반 시 스템을 총합화 하였다.

• 제어로봇시스템학회논문지
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• 제3권5호
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• pp.520-525
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• 1997

This paper presents a fault detection and diagnosis methodology based on weighted symptom model and pattern matching between the coming fault propagation trend and the simulated one. In the first step, backward chaining is used to find the possible cause candidates for the faults. The weighted symptom model is used to generate those candidates. The weight is determined from dynamic simulation. Using WSM, the methodology can generate the cause candidates and rank them according to the probability. Second, the fault propagation trends identified from the partial or complete sequence of measurements are compared with the standard fault propagation trends stored a priori. A pattern matching algorithm based on a number of triangular episodes is used to effectively match those trends. The standard trends have been generated using dynamic simulation and stored a priori. The proposed methodology has been illustrated using two case studies, and the results showed satisfactory diagnostic resolution.

• 농촌지도와개발
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• 제4권1호
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• pp.97-120
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• 1997

This study intends to develop a computer software for an efficient swineherd production and management. Current softwares are concerned on the sow management and ignore the actual farm environment. This study focuses on the farm environment in developing the software and covers the production management financial management, marketing management, and business planning for swineherd farm. The FSR(Farming Systems Research) analysis and interview survey aye applied to collect the data for the system planning, farmer's demand and analysis on the system, system design and program development. The systems are designed to meet the needs for the progressive swineherd farmers. Visual FoxPro 5.1 is used to develop the system. The developed system includes pig farm financial records keeping and management, pig farm production management program, pig farm marketing management program, and pig farm business diagnosis and planning program to meet the scope of the study. The weekly maintenance records and financial records are adopted for the input interface since most of farmers use their computer less than 5 hours a week. Pulldown Menu systems are adopted and designed for easy use by structuring to meet the pig farm and system demands. The manu system allocates the input-output screen based on the sectors, scopes, users, frequencies, importances, and the usages of the information. The GUI(Graphic User Interface) method is used to develop input-output screens for easy use. Backward Chaining mechanism fo the Expert System is used in the diagnosis of the pig farm management and the Systems Simulators Approach is used in the pig farm management planning.