• Journal of the Korean Institute of Gas
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• v.1 no.1
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• pp.27-32
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• 1997

Continual monitoring of abnormal operating conditions i a key issue in maintaining high product quality and safe operation, since the undetected process abnormality may lead to the undesirable operations, finally producing low quality products, or breakdown of equipment. The statistical projection method recently highlighted has the advantage of easily building reference model with the historical measurement data in the statistically in-control state and not requiring any detailed mathematical model or knowledge-base of process. As the complexity of process increases, however, we have more measurement variables and recycle streams. This situation may not only result in the frequent occurrence of process Perturbation, but make it difficult to pinpoint trouble-making causes or at most assignable source unit due to the confusing candidates. Consequently, an ad hoc skill to monitor and diagnose in plat-wide scale is needed. In this paper, we propose a hierarchical plant-wide monitoring methodology based on hierarchical decomposition and principal component analysis for handling the complexity and interactions among process units. This have the effect of preventing special events in a specific sub-block from propagating to other sub-blocks or at least delaying the transfer of undesired state, and so make it possible to quickly detect and diagnose the process malfunctions. To prove the performance of the proposed methodology, we simulate the Tennessee Eastman benchmark process which is operated continuously with 41 measurement variables of five major units. Simulation results have shown that the proposed methodology offers a fast and reliable monitoring and diagnosis for a large scale chemical plant.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.267-270
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• 2021

In order to diagnose a vehicle, it is achieved by collecting diagnostic data within the ECU or between ECUs and managing the diagnostic data by utilizing various communication methods through an electronic device composed of an ECU(Electronic Control Unit), which is an automotive electronic device. As communication methods, LIN, CAN, FlexRay are mainly used. Recently, wired/wireless communication is being used based on Ethernet. In order to perform vehicle diagnosis, it is necessary to know the diagnosis code generated by the ECU and to collect diagnosis data using diagnosis communication. In addition, diagnostic data can be managed from the ECU only when the application software required for vehicle diagnosis is configured. If many automobile manufacturers are manufacturing ECUs based on the AUTOSAR standard, which is an automotive electronic standard, the software structure is also configured to be applied according to the standard. In this paper, we understand the vehicle diagnosis communication method of the AUTUSAR standard, study the configuration and processing method of diagnosis data, and study the contents of software components, diagnosis communication, and diagnosis event processing.

• Korean Journal of Cognitive Science
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• v.13 no.1
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• pp.53-59
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• 2002

This paper presents a model for diagnosing students'learning misconceptions in the domain of heat and temperature using fuzzy cognitive maps(FCM) and fuzzy associative memory(FAM). In a model for diagnosing learning misconceptions. an FCM can represent with cause and effect between preconceptions and misconceptions that students have about scientific phenomenon. An FAM which represents a neurallike memory for memorizing causal relationships is used to diagnose causes of misconceptions in learning. This study will present a new method for more autonomous and intelligent system than a model to diagnose misconceptions that was being done with classical methods in learning and may contribute as an intelligent tutoring system for learning diagnosis within various educational contexts.

• Proceedings of the Safety Management and Science Conference
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• 1999.11a
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• pp.133-146
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• 1999

오늘날의 산업용 로봇, CNC 공작기계 및 여러 산업설비들은 시스템간에 관계가 복잡하게 연결되어 높은 신뢰성(reliability)을 달성하여 왔다. 그러나 가동시 발생하는 결과의 고장 가능성은 적은 반면에, 고장 발생의 파급 효과는 매우 높은 것으로 나타났다. 따라서 복잡한 구조의 산업설비들에 대한 안전진단 결과들을 적절하게 분석하고 관리할 필요성이 크게 대두되고 있다. 이러한 안전진단 작업은 여러 가지 정량적ㆍ정성적인 방법들을 포함하는 전형적인 분석방법이 필요하다. 최근에는 고장탐색, 진단처리 작업 및 신뢰성 분석 작업에 지식기반(knowledge-based)을 기초로한 퍼지 전문가 시스템을 적용하고자 하는 시도가 많이 이루어지고 있다. 안전진단 분석에 관한 일반화된 지식은 이들 후속 단계들에서 상당히 효율적일 수 있다. 그러나 이러한 연구를 수행하기에는 지금까지 상대적으로 열악한 계산 도구들을 이용하였기 때문에 안전진단 분석을 행하기에는 한계가 있었다. 그러나 오늘날 컴퓨터를 이용하여 위의 여러 단계들의 수행과정에 안전진단 분석을 행할 수 있는 적절한 방법으로써, 지식-기반(knowledge-base) 전문가 시스템들을 이용하는 방법을 연구하고 있다. 이에 본 연구는 시스템의 설계단계 뿐만 아니라, 시스템의 가동ㆍ유지ㆍ보수ㆍ수리시에도 비전문가가 고장안전진단을 수행할 수 있도록 하는데 목표를 두었다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3779-3784
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• 2012

Real-time process monitoring and diagnosis of industrial processes is one of important operational tasks for quality and safety reasons. The objective of fault diagnosis or identification is to find process variables responsible for causing a specific fault in the process. This helps process operators to investigate root causes more effectively. This work assesses the applicability of combining a nonlinear statistical technique of kernel Fisher discriminant analysis with a preprocessing method as a tool of on-line fault identification. To compare its performance to existing linear principal component analysis (PCA) identification scheme, a case study on a benchmark process was performed to show that the fault identification scheme produced more reliable diagnosis results than linear method.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.67-68
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• 2018

본 논문에서는 다수의 음향방출 센서로부터 취득한 원 데이터를 관리하고 보일러 튜브에 대한 상태를 실시간으로 진단하고 모니터링을 할 수 있는 네트워크 기반의 보일러 튜브 모니터링 시스템을 제안한다. 본 시스템을 화력발전소 보일러 튜브에 설치한다면 보일러의 불시정지를 예방하는데 효과적일 것으로 기대된다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.887-888
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• 2013

본 논문에서는 엘리베이터에서 발생할 수 있는 다양한 고장 요소들을 실시간으로 진단하고 일정시간 이상 운행이 정지된 경우 고장으로 판단하여 운행상태를 CAN 통신을 이용하여 원격으로 모니터링이 가능한 시스템을 설계하였다. 엘리베이터 내의 승객 탑승여부 확인, 현재 운행위치, 주요 고장내용을 실시간으로 진단하고 CAN 메시지를 이용 메인 컨트롤러에 송신하고 엔지니어는 서버기반의 어플리케이션을 통해 확인이 가능하도록 하였다. 또한 자동차, 선박 등 전장분야에 적용되고 있는 CAN 프로토콜을 이용하여 통신의 신뢰성을 확보하고 엘리베이터 관련 운행 및 고장 상태 등을 실시간을 파악할 수 있도록 하여 효율적인 엘리베이터 유지보수를 가능하도록 하였다. 설계된 시스템의 성능평가는 시뮬레이션 및 프로토콜 모니터링을 통해 수행하였다.

• The Korean Journal of Nuclear Medicine
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• v.29 no.4
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• pp.492-496
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• 1995

To evaluate the usefulness of hepatic uptake in neonatal jaundice, Tc-99m-DISIDA cholescintigraphy was reviewed for 13 infants with prolonged mired jaundice and no demonstrable excretion into bowel,even after 24hr. Five patients proved to have biliary atresia. The remainder had neonatal hepatitis. There was no distinct differentiation of the hepatic uptake of tracer at 5 and 10 minutes between biliary atresia and neonatal hepatitis. The consideration of hepatic uptake rate of the tracer is not useful in differentiating neonatal hepatitis from biliary atresia.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.2027_2028
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• 2009

본 연구에서는 한국수자원공사 고압회전기 고정자권선 절연체의 진단데이터에 대한 통계적 분석연구에 관하여 설명하고 있다. 10년 이상 수집된 진단데이터를 사용하여 와이블 함수를 이용한 누적확률을 구하였으며, 그 결과로부터 각 진단항목에 대하여 형상모수와 절연상태를 판정하는 진단기준치를 제시하였다. 그 결과로 수력발전기의 대지간 전압에 대한 부분방전량의 기준값으로 10,000pC이하를 제시하였다.

• The Korean Journal of Applied Statistics
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• v.35 no.3
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• pp.435-443
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• 2022

In this paper, using Covid-19 diagnostic data provided by the Korea Disease Control and Prevention Agency (KDCA), we examine the probability of confirmed cases and the probability of actually being confirmed when the rapid test is negative according to the sensitivity and specificity of the rapid diagnostic kit. When we know the conditional probability of confirmation given a positive test, we induce the relationship between sensitivity and specificity, and compute the actual sensitivity of the rapid diagnosis kit based on the data of KDCA.