• 지능정보연구
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• 제13권1호
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• pp.81-90
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• 2007

본 논문에서는 전문적인 지식이 부족한 일반인들을 대상으로 자신의 건강 상태를 파악 할 수 있는 지능형 자가 진단 시스템을 제안한다. 제안된 자가 진단 시스템은 보건 복지부에 제출된 '한국인이 부담을 가지는 질병' 관련보고서를 참조하여 선정한 30가지의 질병과 각 질병에 대한 대표 증상을 이용하여 질병을 도출한다. 본 논문에서는 개선된 FCM 알고리즘을 적용하여 질병 종류를 군집화하고 각 질병의 증상과 관련된 질의 결과를 입력 벡터로 적용하여 사용자의 건강 상태를 진단한다. 기존의 방법에서는 입력 벡터와 군집 중심과의 거리를 측정한 후 거리가 가까운 5가지를 선택하기 때문에 선택된 질의와 관련 없는 질병을 도출하는 단점이 있었다. 이러한 단점을 개선하기 위해, 선택된 질의와 도출된 질병에 대한 퍼지 소속도를 이용하여 정렬한다. 정렬된 질병에서 상위 5가지를 도출한 결과, 선택된 질의와 관련된 질병만을 도출하는 것을 확인 할 수 있었다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.203-207
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• 1998

In this paper, it is shown how Fuzzy Pattern Matching can be applied to diagnosis of the most common faults of Rotating Machinery. The whole diagnosis process has been divided in three steps : Fault Detection, Fault Isolation and Fault Identification, whose possible results are described by linguistic patterns. Diagnosis will consist in obtaining a set of matching indexes that indexes that express the compatibility of the fuzzified features extracted from the measured vibration signals, with the knowledge contained in the corresponding patterns.

• Journal of Advanced Marine Engineering and Technology
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• 제20권1호
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• pp.13-23
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• 1996

Weld defects degrade the strength and safety of astructure and are resulted from the various cases. The complexity of causal relation of weld defects requires an expert for the analysis of weld defects and the measures counter to them. An expert system has the intelligent functions such as the representation of knowledge and the inference. On this research, weld defect are systematically analysed and their causal model is developed. This information is saved to the knowledge base. The suitable inference algorithm for the diagnosis of weld defects is developed and realized with C++ programming.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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• pp.74-77
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• 2001

One of the most important technology in PA(Factory Automation) is to construct the diagnostic system for manufacturing process. To improve the productibility in the factory, the state of tools such as bite, drill, endmill should be monitored continuously. In this study, fuzzy logic was used to check the wear of drill in drilling process. The input variables to construct the fuzzy rules are cutting force and the rate of cutting force's change. The experiment was done with the fixed spindle speed and feed rate in cutting condition.

• 한국지능시스템학회논문지
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• 제14권1호
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• pp.1-8
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• 2004

본 논문에서는 실내대기 가스모니터링 시스템에서의 센서 고장 진단을 위한 신경회로망 기반 고장진단방법을 제안한다. 제안한 고장진단 방법에서는 신호패턴추출을 위해 센서히터 온도조절방법을 이용하였으며, 분류를 위해서는 ART2 신경회로망을 이용하였다. 그리고 가스모니터링 시스템의 실제 데이터를 이용한 시뮬레이션을 통해 제안한 ART2 신경회로망 기반 센서고장진단방법의 성능과 유용성을 확인하였다.

• Smart Structures and Systems
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• 제19권6호
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• pp.587-599
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• 2017

This paper introduces an approach to the realization of an ICT-based bridge remote monitoring system that enables real-time monitoring and controlled adjustments for unexpected heavy loads and also for damaging earthquakes or typhoons. In this paper, an integrated bridge remote monitoring system called the "Intelligent Bridge", which consists of a stand-alone monitoring system (SMS) and a web-based Internet monitoring system(IMS), was developed for not only bridge maintenance but also as an application for a para-stressing bridge system. To verify the possibility of controlling the actual structural performance of an "Intelligent Bridge", a model 2-span continuous cable-stayed bridge with adjustable cables was constructed. The experimental results demonstrate that the implemented monitoring system supplies detailed and accurate information about bridge behaviour for further evaluation and diagnosis, and it also opens up prospects for future application of a web-based remote system to actually adjust in-service bridges under field conditions.

• 대한안전경영과학회지
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• 제12권2호
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• pp.65-73
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• 2010

In an automated industry PLC plays a central role to control the manufacturing system. Therefore, fault free operation of PLC controlled manufacturing system is essential in order to maximize a firm's productivity. On the contrary, distributed nature of manufacturing system and growing complexity of the PLC programs presented a challenging task of designing a rapid fault finding system for an uninterrupted process operation. Hence, designing an intelligent monitoring, and diagnosis system is needed for smooth functioning of the operation process. In this paper, we propose a method to continuously acquire a stream of PLC signal data from the normal operational PLC-based manufacturing system and to generate diagnosis model from the observed PLC signal data. Consequently, the generated diagnosis model is used for distinguish the possible abnormalities of manufacturing system. To verify the proposed method, we provided a suitable case study of an assembly line.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.486-495
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• 2001

This paper describes an implementation of the interval based expert system for syndrome differential diagnosis of Oriental Traditional Medicine (OTM). An approximate reasoning model using fuzzy logic for syndrome differential diagnosis is proposed. Based on this model, we implemented the system for diagnosing Eight rule diagnosis, organ diagnosis and then final differential syndrome of OTM. After carrying out inference process, the system will provide patient\`s syndromes differentiation diagnosis in the intervals and will give the explanation, which helps the user to understand the obtained conclusions.

• 한국산업융합학회 논문집
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• 제7권2호
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• pp.199-205
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• 2004

This paper describes the fault diagnosis method to order to construct CIM in complex system with hierarchical structure similar to human body structure. Complex system is divided into unit, item and component. For diagnosing this hierarchical complex system, it is necessary to implement a special neural network. Fault diagnosis system can forecast faults in a system and decide from the signal information of current machine state. Comparing with other diagnosis system for a single fault, the developed system deals with multiple fault diagnosis, comprising hierarchical neural network (HNN). HNN consists of four level neural network, i.e. first is fault symptom classification and second fault diagnosis for item, third is symptom classification and forth fault diagnosis for component. UNIX IPC is used for implementing HNN with multitasking and message transfer between processes in SUN workstation with X-Windows (Motif). We tested HNN at four units, seven items per unit, seven components per item in a complex system. Each one neural network represents a separate process in UNIX operating system, information exchanging and cooperating between each neural network was done by message queue.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.284-287
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• 2003

In recent years, most of the researches on pattern recognition are for medical diagnosis or for characters recognition. In fact its applications are very wide. In this paper, the pattern recognition is employed by linguistic translation, i.e. the output of Pattern Recognition is translated into another language. In this paper, it focuses on several fields: (1) System overview-explicate the functions of each part individually; (2) Criteria on the system-discuss the difficulties in each part; (3) System implementation-discuss how to design the approaches for constructing the system. Furthermore, intelligent approaches are considered be use on the system in different parts. They are discussed in the late paper, and also we concentrate on user interface, which can make a serious of processes in order, and easy control-just only pressing a few buttons. It is a new and creative attempt in digital system.