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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2007.1
- 수록면
- 221 - 230 (10page)
이용수
초록· 키워드
오류제보하기
Wavelet theory was applied to detect a singularity in a reactor power signal. Compared to Fourier transform, wavelet
transform has localization properties in space and frequency. Therefore, using wavelet transform after de-noising, singular points
can easily be found. To test this theory, reactor power signals were generated using the HANARO (a Korean multi-purpose
research reactor) dynamics model consisting of 39 nonlinear differential equations contaminated with Gaussian noise. Wavelet
transform decomposition and de-noising procedures were applied to these signals. It was possible to detect singular events such as
a sudden reactivity change and abrupt intrinsic property changes. Thus, this method could be profitably utilized in a real-time
system for automatic event recognition (e.g., reactor condition monitoring).
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