2006 Fiscal Year Final Research Report Summary
On-line Nuclear Reactor Monitoring and Diagnosis in earliest stages using Neural Network
| Project/Area Number |
16560735
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Nuclear engineering
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| Research Institution | Kyushu University |
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Principal Investigator |
KUDO Kazuhiko Kyushu University, Faculty of Applied Quantum Physics and Nuclear Engineering, Professor, 大学院工学研究院, 教授 (40039681)
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| Co-Investigator(Kenkyū-buntansha) |
NAKAO Yasuyuki Kyushu University, Faculty of Engineering, Professor, 大学院工学研究院, 教授 (00164129)
KOTOH Kenji Kyushu University, Faculty of Engineering, Associate Professor, 大学院工学研究院, 助教授 (50091351)
MATUURA Hideaki Kyushu University, Faculty of Engineering, Research Associate, 大学院工学研究院, 助手 (50238961)
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| Project Period (FY) |
2004 – 2006
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| Keywords | Nuclear Reactor / Diagnosis / Neural Network / Kohonenn Model / HTTR / PWR |
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| Research Abstract |
The object of this research is to develop the on-line nuclear reactor monitoring and diagnosis system using Neural Network theory. The nuclear reactor diagnostic system was developed and examined using reactor simulator and existing reactor data.
In 2004 the diagnostic system applying auto-associative neural network theory was developed and examined about the ability of anomaly detection.
In 2005 application of Kohonen network theory was investigated selectively. It was thought that in addition to anomaly detection, reactor diagnosis will be realized by using Kohonen network. The operational data of existing nuclear reactor which contain noise and power fluctuations was used for training the diagnosis system and the ability of diagnosis was tested.
In 2006 the occurrence of error signal and anomaly diagnosis was examined using PWR simulator. The diagnosis of research reactor data(RSG-GAS, Indonetia) which contain noise was tested and succeeded. The detection of small helium leak which occur in HTTR ( High Temperature Gas Cooled Test Reactor, JAEA ) and power change caused by reactivity change was estimated correctly using this diagnosis system.
These results were presented in some international proceedings and journals.
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[Journal Article] Development of On-Line Monitoring System for Nuclear Power Plant (NPP) Using Neuro-Expert, Noise Analysis, and Modified Neural Networks2006
Author(s)
S.MUHAMMAD, T.OHNO, K.TAKAMATSU, K.NABESHIMA, K.KUDO
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Journal Title
Proceedings of 17th International Topical Meeting on Nuclear Plant, Instrumentation, Controls, and Human Machine Interface Tech. (NPIC＆HMIT2006) Albuquerque,USA
Pages: 75-82
Description
「研究成果報告書概要(和文)」より
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[Journal Article] Development of On-Line Monitoring System for Nuclear Power Plant (NPP) Using Neuro-Expert, Noise Analysis, and Modified Neural Networks
Author(s)
S.MUHAMMAD, T.OHNO, K.TAKAMATSU, K.NABESHIMA, K.KUDO
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Journal Title
Proceedings of 17^<th> International Topical Meeting on Nuclear Plant, Instrumentation, Controls, and Human Machine Interface Tech.(NPIC＆HMIT 2006) Albuquerque USA (Nov.,2006)
Description
「研究成果報告書概要(欧文)」より
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