• 대한전기학회논문지
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• 제40권1호
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• pp.120-127
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• 1991

The purpose of this study is to develop a fault detection and diagnosis scheme that can monitor process fault and instrument fault of a steam generator. The suggested scheme consists of a Kalman filter and two bias estimators. Method of detecting process and instrument fault in a steam generator uses the mean test on the residual sequence of Kalman filter, designed for the unfailed system, to make a fault decision. Once a fault is detected, two bias estimators are driven to estimate the fault and to discriminate process fault and instrument fault. In case of process fault, the fault diagnosis of outlet temperature, feed-water heater and main steam control value is considered. In instrument fault, the fault diagnosis of steam genrator's three instruments is considered. Computer simulation tests show that on-line prompt fault detection and diagnosis can be performed very successfully.

• 한국멀티미디어학회논문지
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• 제19권7호
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• pp.1197-1207
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• 2016

The purpose of this study was to develop an evidence-based Nursing Process System on Nursing Diagnosis, Nursing Outcomes, and Nursing Interventions Classification targeting nurse students. We use standard classification-focused research data on the basis of Nursing Diagnosis Classification established by NANDA (North American Nursing Diagnosis Association), NOC (Nursing Outcomes Classification) and NIC (Nursing Interventions Classification) mainly developed by Iowa Sate University. The existing research methods are difficult to be applied the consistent nursing process, since such methods need to repeatedly enter the same nursing process without systematic guidelines. But, this study was coded data of standardized nursing process in accordance with the 10 clinical condition in order to implement the nursing process macro, and developed a system that reflects the needs of nursing educators. Therefore, nurse students can improve clinical decision-making ability, and naturally learn the nursing process through a system developed.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1428-1431
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• 1997

This paper presents an efficient fault diagnosis methodology for lare chemical processes. The methodology is based on a two-tier strategy, When a falt occurs in a process, a top tier identifies the sector (process part or unit) that may contain the fault(s). Afterwards, a bottom tier or lower level evaluates the suspicious sector. The process modeling methodology based on functionality-behavior relations of process units, is proposed and utilized in the top-tier. This methodology models a target process as sequences of functions and variables and their relations. In the bottom tier, each sector has a dedicated diagostic module, which is tailored to the available information or models of the sector. For the sectors selected in the top-tier diagnosis, each diagnostic module is executed to identify the actual faults within the sector. Teh utility of the methodology is illustrated in the diagnosis of the CSTR with heat exchanger.

• 한국안전학회지
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• 제34권4호
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• pp.59-67
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• 2019

Since it is really hard to construct process models based on prior process knowledges, various statistical approaches have been employed to build fault diagnosis models. However, the crucial drawback of these approaches is that the solutions may vary according to the fault magnitude, even if the same fault occurs. In this study, the parameter monitoring approach is suggested. When a fault occurs in a chemical process, this leads to trigger the change of a process model and the monitoring parameters of process models is able to provide the efficient fault diagnosis model. A few important variables are selected and their predictive models are constructed by partial least square (PLS) method. The Euclidean norms of parameters of PLS models are estimated and a fault diagnosis can be performed as comparing with parameters of PLS models based on normal operational conditions. To improve the monitoring performance, cumulative summation (CUSUM) control chart is employed and the changes of model parameters are recorded to identify the type of an unknown fault. To verify the efficacy of the proposed model, Tennessee Eastman (TE) process is tested and this model can be easily applied to other complex processes.

• 동의생리병리학회지
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• 제30권3호
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• pp.190-200
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• 2016

The aim of this study was to suggest the standard process in developing Questionnaire of Pattern Identification (QPI). The process in developing QPI was researched from validated and developed questionnaire and the standard process in developing QPI was suggested through review of the experts in research, statistics and clinics. Check list was also provided. The number of QPI reviewed in this research was 17(4 in disease in Korea Medicine, 5 in Pathological symptoms, 6 in Sasang constitutional Diagnosis, and 2 in etc), The standard process in developing QPI consisted of 11 phage and 33 check lists. 1) Composition of Research Member(3check lists), 2)Set up of the Aim(5), 3) Review for advanced research(3), 4) Finding an Important Index(3), 5) Review of item selection(4), 6) Developing the questions using items(5), 7) Developing Draft of Questionnaire(2), 8) 1^st Survey of Reliability and Validity(2), 9) Revision and Correction of Item(1), 10) 2^st Survey of Reliability and Validity(2), 11) Completion and Application(3). This study suggests the standard process in developing QPI for the first time in Korea. This following step may help A new QPI development.

• 한국정밀공학회지
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• 제14권11호
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• pp.135-146
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• 1997

This paper describes fault diagnosis method in complex system with hierachical 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 special neural network. Fault diagnosis system can forecast faults in a system and decide from current machine state signal information. Comparing with other diagnosis system for single fault, the developed system deals with multiple fault diagnosis comprising Hierarchical Neural Network(HNN). HNN consists of four level neural network, first level for item fault symptom classification, second level for item fault diagnosis, third level for component symptom classification, forth level for component fault diagnosis. UNIX IPC(Inter Process Communication) is used for implementing HNN wiht 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 newtork operate as a separate process in HNN. The message queue take charge of information exdhange and cooperation between each neural network.

• 한국경영과학회지
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• 제40권1호
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• pp.171-184
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• 2015

The purpose of this study is to develop the self-diagnosis methodology based on process for improving the effectiveness in public institutions service and to suggest it. For this goal, we would like to select the management methodology which can be easily handled from the viewpoint of working personnel in the public institutions and make it as a process. First, the strategy for the public institutions and the strategic task for practicing it are acquired using BSC (Balanced Score Card) which is now under the active research. At this time, the relative degree of significance is derived using the AHP (Analytic Hierarchy Process) which is conducted for the professionals and management to get the degree of importance in the strategic tasks. The acquired relative degree of significance and the figures related to the performance of each strategic task derived from the subsequent questionnaire are used to get the final highly efficient strategic task through IPA (Importance Performance Analysis). In this study, this process based self diagnosis methodology will be explained in detail using the case of Project A in order to verify the effectiveness of the management science technique on the self diagnosis of the public institutions.

• 여성건강간호학회지
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• 제19권1호
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• pp.1-12
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• 2013

Purpose: This study was performed to propose an ontology methodology based on standardized nursing process as framework in obstetric and gynecologic nursing practice. Methods: The instrument used in this study was based on the nursing diagnosis classification established by North American Nursing Diagnosis Association (NANDA) (2009-2011), fifth edition of the Nursing Interventions Classification (NIC) (2008), forth edition of the Nursing Outcomes Classification (NOC) (2008) developed by Iowa State University and systematized nomenclature of medicine clinical terms (SNOMED CT). The nursing records data were collected from electronic medical records of one hospital from August to October 2010. Results: One hundred and forty-one nursing diagnosis statements used in obstetric and gynecologic nursing unit were linked standardized nursing classifications and constructed nursing diagnosis ontology including interoperability. Conclusion: Not only will this result be helpful to complete nurse's lack of knowledge and experience, it will also help to determine nursing diagnosis logically by using standardized nursing process. It will be utilized as the method to construct ontology including interoperability in other nursing units. It will be presented nursing interventions according to nursing diagnosis and thus will be easier to establish nursing planning. This can provide immediate feedback of the nursing process application.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제7권11호
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• pp.443-450
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• 2018

최근 국내에서도 발병률이 증가하고 있는 크론병은 위장관의 모든 부위에서 발병할 수 있으며, 나타나는 증상도 다양하다. 특히, 크론병은 다른 궤양성 대장질환과 유사한 증상을 보일 수 있어 크론병을 진단하는데 어려움을 겪는다. 이로 인해 크론병 진단 가이드라인이나 크론병과 유사한 증상을 보이는 질병의 감별에 대한 연구가 진행되고 있다. 하지만 기존 연구에는 크론병에 대한 순차적인 진단 과정이 기술되지 않아, 크론병 진단을 위한 검사 과정에서 과다한 검사가 시행될 우려가 있다. 따라서 본 논문에서는 크론병과 유사한 증상을 보이는 궤양성 대장 질환을 감별하기 위해 중복성 및 순차적인 연관성, 질병의 진단 조건을 분석하여 감별 규칙으로 정의하고, 이를 기반으로 크론병 진단 프로세스를 제안한다. 또한, 제안하는 프로세스 중심의 연관성을 온톨로지로 정의함으로써 크론병과 유사한 증상을 보이는 대장 질환을 감별하고, 효과적으로 크론병을 진단하는데 도움을 줄 수 있다. 제안한 온톨로지를 5개의 사례에 적용해 본 결과, 모두 올바른 진단을 내렸으며 1개의 사례에서 더 적은 수의 검사로 진단할 수 있었다.

• 한국산학기술학회논문지
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• 제17권1호
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• pp.538-543
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• 2016

고품질의 제품과 조업 안전을 확보하기 위해서는 적절한 실시간 공정 감시 및 진단 시스템이 설치되어있는 것이 무엇보다 중요하다. 공정 감시 시스템과 결합된 신뢰도 높은 진단 시스템은 공정에서 발생한 특별한 사건이나 사고의 근본적인 원인과 공정 변수를 알려준다. 본 연구에서는 다변량 통계 분석과 분류기법에 기반한 공정진단 체계를 제시한다. 이 진단시스템은 비선형 데이터 표현과 필터링을 통한 지능적 데이터 표현으로 구성되어 있다. 진단 성능을 평가하기 위해 사례연구를 수행하였으며 다른 방법론과의 결과를 비교하기 위하여 진단 결과와 미래값 추정 방법을 평가하였다. 그 결과 본 연구에서 비교된 진단 방법론들에 비해 신뢰도 높은 진단 결과를 얻을 수 있었다.