경로모델과 확률과정모델을 이용한 전자부품 잔여수명 예측
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | 장중순, 박상철 | - |
dc.contributor.author | 이선재 | - |
dc.date.accessioned | 2022-11-29T03:01:00Z | - |
dc.date.available | 2022-11-29T03:01:00Z | - |
dc.date.issued | 2022-02 | - |
dc.identifier.other | 31422 | - |
dc.identifier.uri | https://dspace.ajou.ac.kr/handle/2018.oak/20639 | - |
dc.description | 학위논문(석사)--아주대학교 일반대학원 :산업공학과,2022. 2 | - |
dc.description.abstract | The nuclear power plant is conducting periodic detailed inspections, and in the current state, only the pass/fail degree of the parts and circuits in the electronic card is judged. The instrumentation control card plays an important role in protecting and controlling nuclear power plants. Therefore, it is required to develop and construct a system that can predict and diagnose not only the current state of the nuclear power plant instrumentation and control card but also the progress failure that may occur during the operation of the power plant and perform pre-maintenance. The scope of this study is to determine the degree of degradation of 6 types of components (Photocoupler, BJT, SCR, Electrolytic Capacitor, MOSFET, Digital IC) that cause a lot of failure and predict the remaining lifespan using PHM (Prognostics and Health Management) technique. do. To analyze the degradation model, two major models are used: the Degradation Path Model and the Stochastic Process Model. A model that describes the mechanism of degradation is called a degradation path model. It refers to a model that shows changes over time in the characteristic parameters of parts and products related to failure. The parameters of the degradation model are divided into a deterministic coefficient model and a random coefficient model according to a constant or a random variable. The stochastic process model is widely used in various fields such as finance, meteorology, and aviation. Small particles floating on a liquid were introduced to mathematically model the random molecular motion. In order to compare the analysis results according to the degradation model, the photocoupler compared the degradation path model and the stochastic process model. Among the stochastic process models, data parts suitable for the gamma process were analyzed with the gamma process, and the photocoupler was analyzed with the Weibull process applying the gamma process because the gamma process was not suitable. As a result of the analysis, the electronic component with the longest lifespan was the MOSFET, and the component with the shortest lifespan was the photocoupler with the most failure. | - |
dc.description.tableofcontents | 제1장 서 론 1 제1절 연구의 목적 및 배경 1 제2절 연구의 범위 5 제2장 가속열화시험 및 열화모형 6 제1절 가속열화시험 6 제2절 Degradation Path model(열화 경로모형) 7 제3절 Stochastic Process model(확률과정모형) 9 제3장 실험 결과 및 분석 12 제1절 Photocoupler 12 제2절 BJT 18 제3절 SCR 22 제4절 Electrolytic Capacitor 25 제5절 MOSFET 28 제6절 Digital IC 30 제4장 결 론 32 참고문헌 34 Abstract 38 | - |
dc.language.iso | kor | - |
dc.publisher | The Graduate School, Ajou University | - |
dc.rights | 아주대학교 논문은 저작권에 의해 보호받습니다. | - |
dc.title | 경로모델과 확률과정모델을 이용한 전자부품 잔여수명 예측 | - |
dc.title.alternative | Remaining Useful Life Estimation of electronic components using Path model and Stochastic process model | - |
dc.type | Thesis | - |
dc.contributor.affiliation | 아주대학교 일반대학원 | - |
dc.contributor.department | 일반대학원 산업공학과 | - |
dc.date.awarded | 2022. 2 | - |
dc.description.degree | Master | - |
dc.identifier.localId | 1245132 | - |
dc.identifier.uci | I804:41038-000000031422 | - |
dc.identifier.url | https://dcoll.ajou.ac.kr/dcollection/common/orgView/000000031422 | - |
dc.subject.keyword | 경로모델 | - |
dc.subject.keyword | 잔여수명예측 | - |
dc.subject.keyword | 전자부품 | - |
dc.subject.keyword | 확률과정모델 | - |
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