• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 추계학술대회 논문집
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• pp.292-297
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• 2004

The conventional computerized numerical controller (CNC) of machine tools has been increasingly replaced by a PC-based open architecture CNC (OAC) which is independent of the CNC vendor. The OAC and machine tools with OAC led the convenient environment where it is possible to implement user-defined application programs efficiently within CNC. Tis paper proposes a method of operational fault cause diagnosis which is based on the status of programmable logic controller (PLC) in machine tools with OAC. The operational fault is defined as a disability state occurring during normal operation of machine tools. The faults are occupied by over 70% of all faults and are also unpredictable as most of them occur without any warning. Two diagnosis models, the switching function (SF) and the step switching function (SSF), are propose in order to diagnose the fault cause quickly and exactly. The cause of an occurring fault is logically diagnosed through a fault diagnosis system (FDS) using the diagnosis models. A suitable interface environment between CNC and develope application modules is constructed in order to implement the diagnostic functions in the CNC domain. The diagnosed results were displayed on a CNC monitor for machine operators and provided to a remote site through a web browser. The result of his research could be a model of the fault cause diagnosis and the remote monitoring for machine tools with OAC.

• 생태와환경
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• 제53권1호
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• pp.1-10
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• 2020

본 연구는 훼손된 하천 수생태계의 훼손원인을 식별하고 그 전이 과정을 규명하기 위해 수생태계 훼손원인 진단체계를 구축하고 정책적 활용 가능성을 보고자 하였다. 수생태계 현황 조사 및 건강성 평가결과는 하천의 훼손에 대한 전반적인 상황을 알 수 있어 하천 복원 및 관리의 판단 근거로 사용된다. 그러나 하천이 훼손된 원인이나 훼손이 발생하게 된 전이 과정을 고려하지 못한다는 한계를 가진다. 따라서 본 연구에서는 과학적이고 체계적인 진단체계를 제안하여 훼손원인과 그 전이 과정을 규명하였다. 미국, 호주, 유럽의 사례를 분석하여 우리나라에 맞는 진단체계를 제안하였다. 총 8단계로 구성되며, 기초자료 조사, 하천 수생태계 훼손 판단, 훼손 구간 설정, 훼손 유형화 및 잠재적 훼손원인 도출, 본 조사, 주훼손원인 진단 및 최적 훼손 모델 도출, 종합분석 및 하천 복원방안으로 이루어져 있다. 이러한 진단체계는 하천 생태계의 복잡하고 다양한 특성을 고려하여 훼손원인을 파악할 수 있으며 하천 복원 및 관리 방안을 제시하여 효율적인 의사결정을 지원할 수 있다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 춘계학술대회 논문집
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• pp.1005-1010
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• 2000

Internet service has widely used in office automation such as, manufacturing management purchase, and material resource. Nowadays, factory automation and shop floor control system including CAD/CAM department need a web based monitoring and diagnosis to achieve global collaboration and tole-service. This raper deal with design of web based remote monitoring and diagnosis system which concerned with open architecture controller for machine tool.

• 의료ㆍ복지 건축 : 한국의료복지건축학회 논문집
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• 제26권4호
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• pp.29-38
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• 2020

Purpose: The first thing to be done in promoting community care is local diagnosis. Therefore, this study attempted to derive the physical infrastructure to be diagnosed, and to develop diagnostic items and diagnostic indicators applicable to this. Methods:: First, the physical infrastructure related to the community care is derived. And the diagnosis items are derived using the checklist of 'community support and health services' in the WHO Guide for Global age-friendly cities. Next, by analyzing previous studies, we develop diagnostic indicators for each diagnostic item and explore their applicability. Results: As a result of deriving the physical infrastructure for each area of housing, health service, and nursing care for community care, 22 facilities were derived for 9 types. Diagnosis items for the facilities are 1)regional equity, 2)proximity between facilities, 3)transportation access, 4)regional use, 5)barrier-free design, 6)diversity of facilities, and a total of 14 diagnostic indicators was derived. We reviewed and suggested the applicability of diagnostic items and indicators by each physical infrastructure. Implications: For the realization of community care, local diagnosis should not be limited to sim- ply grasping the presence or absence of facilities and the total amount. Instead it should strengthen capabilities by conducting diagnosis to understand the performance of facilities.

• Structural Engineering and Mechanics
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• 제16권5호
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• pp.581-595
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• 2003

Since the conventional direct approaches are hard to be applied for damage diagnosis of complex large-scale structures, a two-step approach for diagnosing the joint damage of framed structures is presented in this paper by using artificial neural networks. The first step is to judge the damaged areas of a structure, which is divided into several sub-areas, using probabilistic neural networks with natural Frequencies Shift Ratio inputs. The next step is to diagnose the exact damage locations and extents by using the Radial Basis Function (RBF) neural network with the second Element End Strain Mode of the damaged sub-area input. The results of numerical simulation show that the proposed approach could diagnose the joint damage of framed structures induced by earthquake action effectively and has reliable anti-jamming abilities.

• 한국주거학회논문집
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• 제26권2호
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• pp.67-79
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• 2015

As the Korean construction market in the apartment housing has changed to a housing consumer focused market, interest and importance on efficient use and management on existing buildings has increased rather than demand for new buildings. Interest of housing consumers on apartment house quality has increased in this market paradigm, and this spontaneously is connected to quality flaw related defect disputes and lawsuits that the importance of defect diagnosis has continuously increased. This defect diagnosis is directly connected to maintenance charges in defect dispute and lawsuit processes that rather objective and highly credible progress of duty is required. However, most defect diagnosis firms today that progress defect diagnosis are using different diagnosis methods and depend on the experience of experienced professionals that there is no standardized defect diagnosis process. Therefore, the purpose of this study is to provide common defect diagnosis process model for defect diagnosis firms utilizing the BPMN (Business Process Modeling Notation) modeling method. It is expected that this will contribute to professional and reliable task performances of concerned defect diagnosis workers. Furthermore, it is expected that design lawsuit damage will be substantially reduced by standardizing defect diagnosis processes.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.109-114
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• 1997

As CNC machine tool is one of core elements of manufacturing system, it is much important that it remains without troubleshoots. As a virtual machine is a recent alternative using IT for optimal utilization of CNC machine tool, it is a computer model that represents a CNC machine tool. But a virtual machine is still conceptual. So, in this paper, it is proposed that a virtual machine be a realistic model in the fault diagnosis module. For this purpose, the fault diagnosis system of machine tool using CORBA and fault diagnosis expert system has been implemented. Using this system, we have expections to diagnose exactly and prompty without the restriction of time or location, to reduce MTTR(Mean Time To Repair) and finally to increase the availability of manufacturing system.

• 대한전기학회논문지:시스템및제어부문D
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• 제50권4호
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• pp.192-200
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• 2001

As the high density memory is widely used in the various applications, the need for reproduction of memory is increased. In this paper we propose an efficient fault diagnosis algorithm of linear order O(n) that enables the reproduction of memory. The new algorithm can distinguish various fault models and identify all the cells related to the faults. In addition, a new BIST architecture for fault diagnosis is developed. Using the new algorithm, fault diagnosis can be performed efficiently. And the performance evaluation with previous approaches proves the efficiency of the new algorithm.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권9호
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• pp.512-519
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• 2000

A Neural networks has been used for a expert system and fault diagnosis system. It is possible to nonlinear function mapping and parallel processing. Therefore It has been developing for a Diagnosis system of nuclear plower plant. In general Neural Networks is a static mapping but Dynamic Neural Network(DNN) is dynamic mapping.쪼두 a fault occur in system a state of system is changed with transient state. Because of a previous state signal is considered as a information DNN is better suited for diagnosis systems than static neural network. But a DNN has many weights so a real time implementation of diagnosis system is in need of a rapid network architecture. This paper presents a algorithm for RCP monitoring Alarm diagnosis system using Self Dynamic Neural Network(SDNN). SDNN has considerably fewer weights than a general DNN. Since there is no interlink among the hidden layer. The effectiveness of Alarm diagnosis system using the proposed algorithm is demonstrated by applying to RCP monitoring in Nuclear power plant.

• 대한산업공학회지
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• 제36권4호
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• pp.230-242
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• 2010

In this paper, an environmental monitoring and diagnosis system based on ubiquitous computing technology, shortly u-Eco Monitoring System, is proposed. u-Eco Monitoring System is designed to: 1) Collect information from the manufacturing processes via ubiquitous computing technology, 2) Analyze the current status, 3) Identify the cause of problem if detected by rule-based and case-based reasoning, and 4) Provide the results to the operator for proper decision making. Based on functional modeling, a generic architecture is derived, followed by application to a manufacturing system in iron and steel making industry. Finally, to show the validity of the proposed method, a prototype is developed and tested. The developed methods can be used as a conceptual framework for designing environmental monitoring and diagnosis system for industrial practices by which monitoring accuracy and response time for abnormal status can be significantly enhanced, and relieving operator pressure from manual monitoring and error-prone decision making.