INVESTIGATION OF REACTOR CONDITION MONITORING AND SINGULARITY DETECTION VIA WAVELET TRANSFORM AND DE-NOISING

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dc.contributor.authorKim, Ok Joo-
dc.contributor.authorCho, Nam Zin-
dc.contributor.authorPark, Chang Je-
dc.contributor.authorPark, Moon Ghu-
dc.date.accessioned2008-08-20T01:07:10Z-
dc.date.available2008-08-20T01:07:10Z-
dc.date.issued2007-06-
dc.identifier.citationNuclear Engineering and Technology, Vol.39, No.3, pp.221-230en
dc.identifier.issn1738-5733-
dc.identifier.urihttp://img.kisti.re.kr/view.jsp?db=JAKO&cn=JAKO200724737439357-
dc.identifier.urihttp://hdl.handle.net/10203/7165-
dc.description.abstractWavelet 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.isoen_USen
dc.publisherKorean Nuclear Societyen
dc.subjectDe-noising by Thresholding Algorithmen
dc.subjectSingularity Detectionen
dc.subjectWavelet Transformen
dc.subjectHANARO Research Reactoren
dc.titleINVESTIGATION OF REACTOR CONDITION MONITORING AND SINGULARITY DETECTION VIA WAVELET TRANSFORM AND DE-NOISINGen
dc.typeArticleen

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