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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2007.1
- 수록면
- 149 - 158 (10page)
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초록· 키워드
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The Electric Power Research Institute (EPRI) demonstrated a method for monitoring the performance of instrument
channels in Topical Report (TR) 104965, “On-Line Monitoring of Instrument Channel Performance.” This paper presents the
results of several models originally developed by EPRI to monitor three nuclear plant sensor sets: Pressurizer Level, Reactor
Protection System (RPS) Loop A, and Reactor Coolant System (RCS) Loop A Steam Generator (SG) Level. The sensor sets
investigated include one redundant sensor model and two non-redundant sensor models. Each model employs an Auto-
Associative Kernel Regression (AAKR) model architecture to predict correct sensor behavior. Performance of each of the
developed models is evaluated using four metrics: accuracy, auto-sensitivity, cross-sensitivity, and newly developed Error
Uncertainty Limit Monitoring (EULM) detectability. The uncertainty estimate for each model is also calculated through two
methods: analytic formulas and Monte Carlo estimation. The uncertainty estimates are verified by calculating confidence
interval coverages to assure that 95% of the measured data fall within the confidence intervals. The model performance
evaluation identified the Pressurizer Level model as acceptable for on-line monitoring (OLM) implementation. The other two models, RPS Loop A and RCS Loop A SG Level, highlight two common problems that occur in model development and evaluation, namely faulty data and poor signal selection
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