시스템엔지니어링 방법론을 적용한 소프트웨어 테스트 케이스 개발에 관한 연구

살림셀리,신중욱,김진일,Salim, Shelly,Shin, Junguk,Kim, Jinil 한국시스템엔지니어링학회 2018 시스템엔지니어링학술지 Vol.14 No.2

Software has become an integral part of almost any system, triggered by the ever-growing demand for automation and artificial intelligent throughout engineering domains. The complexities of software-centric systems are also increasing, which make software test efforts become essential in software development projects. In this study, we applied systems engineering methodology in generating software test cases. We found out the similarities between requirements analysis and traceability concept of systems engineering and test specification contents of software test. In terms of acceptance test, software test cases could be considered as validation requirements. We also suggested a method to determine test order using a SysML modeling tool.

모델 기반 중소형 플랜트 형상관리 시스템의 효과성 평가 사례

하가연,김진일,신중욱,염충섭,Ha, Ga Yeon,Kim, Jinil,Shin, Junguk,Yeom, Choong Sub 한국시스템엔지니어링학회 2021 시스템엔지니어링학술지 Vol.17 No.1

Plant Configuration Management(CM) is an activity to maintain consistency of design requirements, physical configuration, facility configuration information throughout the life cycle of the plant by systematically managing changes that occur during the plant design and operation process. Conformity between information must be ensured not only in the design stage, but also in the case of design changes in the operation and maintenance stages, and thus a computer system capable of efficiently managing them is required. In particular, in consideration of an application to small and medium-sized domestic plants, a computer system that can support configuration management at a low cost is needed. Accordingly, in this study, a configuration management system has been developed to support the management of plant design information and change procedures in the operation stage of small and medium-sized plants. Here, a case for quantitatively evaluating the effectiveness of the developed system is described.

MTS를 이용한 가압기 압력 제어 계통의 조기 고장 감지에 대한 연구

차재민,김준영,신중욱,염충섭,강성기,Cha, Jae-Min,Kim, Joon-Young,Shin, Junguk,Yeom, Choongseob,Kang, Seong-Ki 한국통계학회 2016 응용통계연구 Vol.29 No.7

원자력 발전소의 가압기는 1차 계통의 냉각재가 고온에서도 기화되지 않도록 압력을 가해주는 장치이다. 즉, 가압기의 고장은 원자력 발전소에 큰 영향을 미칠 수 있으며, 따라서, 가압기의 조기 고장 감지는 원자력 발전소의 안전에 매우 중요하다. 이를 위해, 본 연구에서는 마할라노비스 거리 개념과 다구찌 품질 공학 이론에 기반한 패턴 분류 인식 알고리즘 중 하나인 마할라노비스 다구찌 시스템(MTS)을 가압기 압력 제어 계통의 조기 고장 감지에 적용하였다. MTS의 고장 감지 성능을 검증하기 위해, 실제 원자력 발전소에서 발생하고 있는 가압기 압력전송기 고장 시나리오를 대상으로 하여, Full Scope 시뮬레이터를 통해 모사된 데이터에 적용하였다. 실험 결과, MTS는 단일 센서모니터링 기반의 전통적인 고장 감지에 비하여 매우 빠르게 고장을 감지할 수 있었다. A pressurizer is a major equipment system in a nuclear power plant (NPP) and controls the reactor cooling system pressure within the allowable range. Faults in the pressurizer can be critical to the NPP; therefore, early fault detection in the pressurizer is significant for NPP safety. This study applies Mahalanobis Taguchi system (MTS), which is one of the promising pattern classification methods, based on the Mahalanobis distance concept and Taguchi quality engineering theory to the early fault detection problem of the pressurizer pressure control system. We conducted experiments using data from full scope NPP simulator based on a pressurizer pressure transmitter faults scenario to validate the faults detection performance of MTS. As a result, MTS can rapidly detect the faults compared to conventional faults detection based on single sensor monitoring.

엔지니어링 데이터시트 인식 모델의 학습을 위한 데이터 생성 방법

유은섭(Eun-seop Yu),신중욱(Junguk Shin),염충섭(Choongsub Yeom),유보현(Bo Hyun Ryu) 대한기계학회 2023 대한기계학회 춘추학술대회 Vol.2023 No.11

X-band rising-sun 마그네트론 발진기

김해진(HaeJin Kim),신중욱(Junguk Shin),최진주(JinJoo Choi) 한국통신학회 2001 한국통신학회 학술대회논문집 Vol.2001 No.7

SysML DSL 기반 플랜트 모델링 케이스

이태경,차재민,김준영,신중욱,김진일,염충섭,Lee, Taekyong,Cha, Jae-Min,Kim, Jun-Young,Shin, Junguk,Kim, Jinil,Yeom, Choongsub 한국시스템엔지니어링학회 2017 시스템엔지니어링학술지 Vol.13 No.2

Implementation of Model-based Systems Engineering(MBSE) depends on a model supporting efficient communication among engineers from various domains. And SysML is designed to create models supporting MBSE but unfortunately, SysML itself is not practical enough to be used in real-world engineering projects. SysML is designed to express generic systems and requires specialized knowledge, so a model written in SysML is less capable of supporting communication between a systems engineer and a sub-system engineer. Domain Specific Languages(DSL) can be a great solution to overcome the weakness of the standard SysML. A SysML based DSL means a customized SysML for a specific engineering domain. Unfortunately, current researches on SysML Domain Specific Language(DSL) for the plant engineering industry are still on the early stage. So as the first step, we have developed our own SysML based Piping & Instrumentation Diagram (P&ID) creation environment and P&ID itself of a specific plant system, using a widely used SysML authoring tool called MagicDraw. P&ID is one of the most critical output during the plant design phase, which contains all information required for the plant construction phase. So a SysML based P&ID has a great potential to enhance the communication among plant engineers of various disciplines.

플라즈마 적용을 위한 촉매 복합개질 실험

김효식(Hyosik Kim),신중욱(Junguk Shin),오승천(Seung-chun Oh),김진호(Jinho Kim),조천현(Cheonhyeon Cho),강석환(Sukhwan Kang),류재홍(Jae-hong Ryu) 한국신재생에너지학회 2014 한국신재생에너지학회 학술대회논문집 Vol.2014 No.05

원전 상태 감시 및 조기 경보용 빅데이터 시범 플랫폼의 설계를 위한 시스템 엔지니어링 방법론 적용 연구

차재민,손충연,황동식,신중욱,염충섭,Cha, Jae-Min,Shin, Junguk,Son, Choong-Yeon,Hwang, Dong-Sik,Yeom, Choong Sub 한국시스템엔지니어링학회 2015 시스템엔지니어링학술지 Vol.11 No.2

With the era of big data, the big data has been expected to have a large impact in the NPP safety areas. Although high interests of the big data for the NPP safety, only a limited researches concerning this issue are revealed. Especially, researches on the logical/physical structure and systematic design methods for the big data platform for the NPP safety were not dealt with. In this research, we design a new big data pilot platform for the NPP safety especially focusing on health monitoring and early warning services. For this, we propose a tailored design process based on SE approaches to manage inherent high complexities of the platform design. The proposed design process is consist of several steps from elicitate stakeholders to integration test via define operational concept and scenarios, and system requirements, design a conceptual functional architecture, select alternative physical modules for the derived functions and assess the applicability of the alternative modules, design a conceptual physical architecture, implement and integrate the physical modules. From the design process, this paper covers until the conceptual physical architecture design. In the following paper, the rest of the design process and results of the field test will be shown.

순산소 연소형 석탄가스화-초임계 이산화탄소 발전 시스템 성능 해석

박성호(SungHo Park),윤문규(Munkyu Yoon),신중욱(Junguk Shin),김진일(Jinil Kim),임동렬(DongRyul Rhim) 한국에너지기후변화학회 2017 한국에너지기후변화학회 학술대회 Vol.2017 No.11

S-MTS를 이용한 강판의 표면 결함 진단

김준영(Joon-Young Kim),차재민(Jae-Min Cha),신중욱(Junguk Shin),염충섭(Choongsub Yeom) 한국지능정보시스템학회 2017 지능정보연구 Vol.23 No.1

강판 표면 결함은 강판의 품질과 가격을 결정하는 중요한 요인 중 하나로, 많은 철강 업체는 그동안 검사자의 육안으로 강판 표면 결함을 확인해왔다. 그러나 시각에 의존한 검사는 통상 30% 이상의 판단 오류가 발생함에 따라 검사 신뢰도가 낮은 문제점을 갖고 있다. 따라서 본 연구는 Simultaneous MTS (S-MTS) 알고리즘을 적용하여 보다 지능적이고 높은 정확도를 갖는 새로운 강판 표면 결함 진단 시스템을 제안하였다. S-MTS 알고리즘은 단일 클래스 분류에는 효과적이지만 다중 클래스 분류에서 정확도가 떨어지는 기존 마할라노비스 다구찌 시스템 알고리즘(Mahalanobis Taguchi System; MTS)의 문제점을 해결한 새로운 알고리즘이다. 강판 표면 결함진단은 대표적인 다중 클래스 분류 문제에 해당하므로, 강판 표면 결함 진단 시스템 구축을 위해 본 연구에서는 S-MTS 알고리즘을 채택하였다. 강판 표면 결함 진단 시스템 개발은 S-MTS 알고리즘에 따라 다음과 같이 진행하였다. 첫째, 각 강판 표면 결함 별로 개별적인 참조 그룹 마할라노비스 공간(Mahalanobis Space; MS)을 구축하였다. 둘째, 구축된 참조 그룹 MS를 기반으로 비교 그룹 마할라노비스 거리(Mahalanobis Distance; MD)를 계산한 후 최소 MD를 갖는 강판 표면 결함을 비교 그룹의 강판 표면 결함으로 판단하였다. 셋째, 강판 표면 결함을 분류하는 데 있어 결함 간의 차이점을 명확하게 해주는 예측 능력이 높은 변수를 파악하였다. 넷째, 예측 능력이 높은 변수만을 이용해 강판 표면 결함 분류를 재수행함으로써 최종적인 강판 표면 결함 진단 시스템을 구축한다. 이와 같은 과정을 통해 구축한 S-MTS 기반 강판 표면 결함 진단 시스템의 정확도는 90.79%로, 이는 기존 검사 방법에 비해 매우 높은 정확도를 갖는 유용한 방법임을 보여준다. 추후 연구에서는 본 연구를 통해 개발된 시스템을 현장 적용하여, 실제 효과성을 검증할 필요가 있다. Steel plate faults is one of important factors to affect the quality and price of the steel plates. So far many steelmakers generally have used visual inspection method that could be based on an inspector"s intuition or experience. Specifically, the inspector checks the steel plate faults by looking the surface of the steel plates. However, the accuracy of this method is critically low that it can cause errors above 30% in judgment. Therefore, accurate steel plate faults diagnosis system has been continuously required in the industry. In order to meet the needs, this study proposed a new steel plate faults diagnosis system using Simultaneous MTS (S-MTS), which is an advanced Mahalanobis Taguchi System (MTS) algorithm, to classify various surface defects of the steel plates. MTS has generally been used to solve binary classification problems in various fields, but MTS was not used for multiclass classification due to its low accuracy. The reason is that only one mahalanobis space is established in the MTS. In contrast, S-MTS is suitable for multi-class classification. That is, S-MTS establishes individual mahalanobis space for each class. "Simultaneous" implies comparing mahalanobis distances at the same time. The proposed steel plate faults diagnosis system was developed in four main stages. In the first stage, after various reference groups and related variables are defined, data of the steel plate faults is collected and used to establish the individual mahalanobis space per the reference groups and construct the full measurement scale. In the second stage, the mahalanobis distances of test groups is calculated based on the established mahalanobis spaces of the reference groups. Then, appropriateness of the spaces is verified by examining the separability of the mahalanobis diatances. In the third stage, orthogonal arrays and Signal-to-Noise (SN) ratio of dynamic type are applied for variable optimization. Also, Overall SN ratio gain is derived from the SN ratio and SN ratio gain. If the derived overall SN ratio gain is negative, it means that the variable should be removed. However, the variable with the positive gain may be considered as worth keeping. Finally, in the fourth stage, the measurement scale that is composed of selected useful variables is reconstructed. Next, an experimental test should be implemented to verify the ability of multi-class classification and thus the accuracy of the classification is acquired. If the accuracy is acceptable, this diagnosis system can be used for future applications. Also, this study compared the accuracy of the proposed steel plate faults diagnosis system with that of other popular classification algorithms including Decision Tree, Multi Perception Neural Network (MLPNN), Logistic Regression (LR), Support Vector Machine (SVM), Tree Bagger Random Forest, Grid Search (GS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The steel plates faults dataset used in the study is taken from the University of California at Irvine (UCI) machine learning repository. As a result, the proposed steel plate faults diagnosis system based on S-MTS shows 90.79% of classification accuracy. The accuracy of the proposed diagnosis system is 6-27% higher than MLPNN, LR, GS, GA and PSO. Based on the fact that the accuracy of commercial systems is only about 75-80%, it means that the proposed system has enough classification performance to be applied in the industry. In addition, the proposed system can reduce the number of measurement sensors that are installed in the fields because of variable optimization process. These results show that the proposed system not only can have a good ability on the steel plate faults diagnosis but also reduce operation and maintenance cost. For our future work, it will be applied in the fields to validate actual effectiveness of the proposed system and plan to improve the accuracy based on the results.