DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Ok Joo | - |
dc.contributor.author | Cho, Nam Zin | - |
dc.contributor.author | Park, Chang Je | - |
dc.contributor.author | Park, Moon Ghu | - |
dc.date.accessioned | 2008-08-20T01:07:10Z | - |
dc.date.available | 2008-08-20T01:07:10Z | - |
dc.date.issued | 2007-06 | - |
dc.identifier.citation | Nuclear Engineering and Technology, Vol.39, No.3, pp.221-230 | en |
dc.identifier.issn | 1738-5733 | - |
dc.identifier.uri | http://img.kisti.re.kr/view.jsp?db=JAKO&cn=JAKO200724737439357 | - |
dc.identifier.uri | http://hdl.handle.net/10203/7165 | - |
dc.description.abstract | 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). | en |
dc.language.iso | en_US | en |
dc.publisher | Korean Nuclear Society | en |
dc.subject | De-noising by Thresholding Algorithm | en |
dc.subject | Singularity Detection | en |
dc.subject | Wavelet Transform | en |
dc.subject | HANARO Research Reactor | en |
dc.title | INVESTIGATION OF REACTOR CONDITION MONITORING AND SINGULARITY DETECTION VIA WAVELET TRANSFORM AND DE-NOISING | en |
dc.type | Article | en |
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