• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.790-795
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• 1994

This paper describes multiple fault diagnosis method in complex system with hierarchical structure. Complex system is divided into subsystem, item, component. For diagnosing this hierarchical complex system, it is necessary to implement special neural network. We introducd to Hierarchical Artificial Neural Network(HANN) for this purpose. HANN consists of four level neural network, first level for symptom classification, second level for item fault diagnosis, third level for component symptom classification,forth level for component fault diagnosis. Each network is multi layer perceptron with 7 inputs, 30 hidden node and 7 outputs trainined by backpropagation. UNIX IPC(Inter Process Communication) is used for implementing HANN with multitasking and message transfer between processes in SUN workstation. We tested HANN in reactor system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1705-1711
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• 1991

On-line fault detection and diagnosis has an increasing interest in a chemical process industry, especially for a process control and automation. The chemical process needs an intelligent operation-aided workstation which can do such tasks as process monitoring, fault detection, fault diagnosis and action guidance in semiautomatic mode. These tasks can increase the performance of a process operation and give merits in economics, safety and reliability. Aiming these tasks, series of researches have been done in our lab. Main results from these researches are building appropriate knowledge representation models and a diagnosis mechanism for fault detection and diagnosis in a chemical process. The knowledge representation schemes developed in our previous research, the symptom tree model and the fault-consequence digraph, showed the effectiveness and the usefulness in a real-time application, of the process diagnosis, especially in large and complex plants. However in our previous approach, the diagnosis speed is its demerit in spite of its merits of high resolution, mainly due to using two knowledge models complementarily. In our current study, new knowledge representation scheme is developed which integrates the previous two knowledge models, the symptom tree and the fault-consequence digraph, into one. This new model is constructed using a material balance, energy balance, momentum balance and equipment constraints. Controller related constraints are included in this new model, which possesses merits of the two previous models. This new integrated model will be tested and verified by the real-time application in a BTX process or a crude unit process. The reliability and flexibility will be greatly enhanced compared to the previous model in spite of the low diagnosis speed. Nexpert Object for the expert system shell and SUN4 workstation for the hardware platform are used. TCP/IP for a communication protocol and interfacing to a dynamic simulator, SPEEDUP, for a dynamic data generation are being studied.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 춘계학술대회 논문집
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• pp.457-462
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• 1995

This paper describes diagnosis strategy of the Flexible Multiple Fault Diagnosis Module for forecasting faults in system and deciding current machine state form sensor information. Most studydeal with diagnosis control stategy about single fault in a system, this studies deal with multiple fault diagnosis. This strategy is consist of diagnosis control module such as backward tracking expert system shell, various neural network, numerical model to predict machine state and communication module for information exchange and cooperate between each model. This models are used to describe structure, function and behavior of subsystem, complex component and total system. Hierarchical structure is very efficient to represent structural, functional and behavioral knowledge. FT(Fault Tree). ST(Symptom Tree), FCD(Fault Consequence Diagrapy), SGM(State Graph Model) and FFM(Functional Flow Model) are used to represent hierachical structure. In this study, IA(Intelligent Agent) concept is introduced to match FT component and event symbol in diagnosed system and to transfer message between each event process. Proposed diagnosis control module is made of IPC(Inter Process Communication) method under UNIX operating system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.1109-1114
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• 1992

Modern chemical processes are becoming more complicated. The sophisticated chemical processes have needed the fault diagnosis pxpert systems that can detect and diagnose the fault diagnosis expert systems that can detect and diagnose the faults of some processes and give and advice to the operator in the event of process faults. We present the Time-Delay Neural Network(TDNN) approach for on-line fautl diagnosis. The on-line fault diagnosis system finds the exact origin of the fault of which the symptom is propagated continuously with time. The proposed method has been applied to a pilot distillation column to show the merits and applicability of the TDNN.

• 한국태양에너지학회 논문집
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• 제37권3호
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• pp.23-32
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• 2017

This paper presents losses comparison and analysis results for different types of fault modes of grid-connected photovoltaic system generated for long-term operation. The approach of losses comparison and analysis by faults is to identify relationship between measured and estimated values of five loss factors which are quantified from irradiance to system output power. This paper presents the symptom results for faults such as snow, shading, sensor defect, blackout, soiling and so on from three years or more monitored data. These results will indicate that it is useful to develop fault detection and diagnosis tool to enhance capacity factor and save operation and maintenance cost of grid-connected photovoltaic system in the field.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 추계학술대회 논문집 학회본부
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• pp.152-156
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• 1996

Identification of incipient faults and various events on the distribution feeders is very important to develop the prediction method of fault symptom. In this paper, the configuration of data acquisition system to get the real field data is introduced. And the Quantification of incipient faults is also discussed. Based on the acquired field data, how the time domain parameters of voltage and current signals are applied to this research is partly introduced.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.157.1-157
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• 2001

A new methodology is presented to diagnose faults in equipment plasma. This is accomplished by using neural networks as a pattern recognizer of radio frequency(rf) impedance match data. Using a realtime match monitor system, the match data were collected. The monitor system consisted mainly of a multifunction board and a signal flow diagram coded by Visual Designer. Plasma anomaly was effectively represented by electrical match positions. Twenty sets of fault-symptom patterns were experimentally simulated with experimental variations in process factors, which include rf source power, pressure, Ar and O$_2$ flow rates. As the inputs to neural networks, two means and standard deviations of positions were used ...

• 한국정보과학회논문지:소프트웨어및응용
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• 제35권12호
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• pp.716-730
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• 2008

서비스 지향 아키텍처에서 서비스 제공자는 재사용 가능한 서비스를 개발하고 저장소에 배포하며, 서비스 사용자는 인터페이스를 통하여 블랙박스 컴포넌트 형태의 서비스를 사용한다. 저장소에 배포된 서비스는 시간이 지남에 따라 변경/진화될 가능성이 높고, 다양한 언어 또는 플랫폼을 사용하여 구현되는 이질성(Heterogeneity)을 가진다. 이런 이유로, 서비스 사용자는 서비스 내부 구조를 알기 힘들기 때문에, 서비스가 기능을 수행하는 도중 문제점이 발생하면 문제점을 식별하여 해결하는 등의 서비스 결함을 효과적으로 관리하는 것이 어렵다. 자율 컴퓨팅(Autonomic Computing, AC)은 사람의 개입을 최소화하고 시스템이 스스로의 결함을 관리하도록 설계하는 방식이다. AC는 시스템을 자율적으로 결함을 관리할 수 있는 주요 원칙들을 제안하고 있으므로, 서비스 결함 관리에 관한 기술적 이슈들은 AC의 기법들을 사용하여 해결될 수 있다. 본 논문에서는 SOA 환경에서 자율적으로 서비스의 결함을 관리하기 위한 이론적 모델인 Symptom-Cause-Actuator(SCA) 모델을 제시한다. SCA 모델은 의사가 환자를 치료하는 과정으로부터 유도된다. 먼저, 다섯 단계로 구성된 SCA 컴퓨팅 모델을 정의하고 SCA의 메타모델을 제안한다. 또한, SCA 모델의 저장소 역할을 하는 SCA 프로파일을 정의하고, SCA 프로파일에 저장되는 symptom, cause, actuator의 인스턴스와 이들 간의 의존 관계를 기계가 인식할 수 있는 형식으로 표현한다. 그리고, 서비스의 결함을 자율적으로 관리하는 컴퓨팅 모델의 다섯 단계를 수행하는데 필요한 알고리즘을 상세하게 기술한다. 마지막으로, SCA 모델의 실행 가능성을 보여주기 위하여, SCA 프로파일과 알고리즘을 구현한 프로토타입을 '비행기 예약 시스템'에 적용하는 사례 연구를 수행한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 A
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• pp.165-166
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• 2006

Recently, after Wide Area Outage of the North-Eastern United States occurred, many countries started to be concerned about WAMS (Wide Area Monitoring System), and Korean power system also experienced Wide Area outage according to typhoon Mae-Mi, and Haenam-Jeju HVDC line fault. Since it is too difficult to detect a symptom based on SCADA or EMS, a defense system of electric power infrastructure has required. In this research, the designed and developed system processes the time synchronized real time power system information based on GPS and shows the 2D/3D monitoring viewer using the phasor data and the results of three algorithms.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1996년도 추계학술대회발표논문집; 고려대학교, 서울; 26 Oct. 1996
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• pp.23-26
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• 1996

인과관계적 추론 방법(causal reasoning)은 시스템 고장을 시스템 구조나 행동의 원인 상과관계를 사용하여 분류하는 것으로서 관측된 행도오가 기대행동의 차이를 조사하여 인식하게 된다. 본 연구에서는 징후(symptom)를 분석 및 분류할 때에 시스템의 기능적인 계층구조를 이용한다. 전문가시스템의 구축은 KAPPA-PC를 사용하였다. KAPPA-PC는 규칙 및 논리에 근거한 방법과 객체지향적 지식 표현 기법을 사용한다. 대다수의 사람들이 일상적으로 사용하는 PC(Personal Computer)는, 특히 하드웨어에서 고장이 일어났을 때 수리자의 노우하우(know-how)로 고쳐지는 경우가 대부분이다. 본 논문에서는 자주 일어날수 있는 PC의 하드웨어적 고장에 일반사용자들이 쉽게 접근해서 그 원인과 진단을 내릴 수 있도록 했으며 작은 고장 원인이 전체 시스템구조내에서 어떤 상관관계를 가지는지를 고찰하였다.