| Project/Area Number |
13650477
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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 |
Measurement engineering
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| Research Institution | Chiba University |
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Principal Investigator |
HATTORI Katsumi Chiba University, Marine Biosystems Research Center, Associate Professor, 海洋バイオシステム研究センター, 助教授 (60244513)
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| Co-Investigator(Kenkyū-buntansha) |
ISEZAKI Nobuhiro Chiba University, Faculty of Earth Sciences, Professor, 理学部, 教授 (60107943)
NAGAO Toshiyasu Tokai University, School of Marine Science and Technology, Professor, 海洋学部, 教授 (20183890)
HAYAKAWA Masashi The University of Electro-Communications, Faculty of Electronic Engineering, Professor, 電気通信学部, 教授 (80023688)
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| Project Period (FY) |
2001 – 2003
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| Project Status |
Completed (Fiscal Year 2003)
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| Budget Amount *help |
¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 2003: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 2002: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 2001: ¥1,900,000 (Direct Cost: ¥1,900,000)
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| Keywords | short-term earthquake prediction / measurement of seismo-electromagnetics / automatic detection of anomalous changes / noise reduction / predictor / principal component analysis / fractal analysis / interstation transfer function method / インターステーション応答関数 / レファレンス観測点 / 地球超高層起源の電磁場変動の除去 / 直流電車の信号 / 適応信号処理 / 房総ゆっくり地震 / 2000年伊豆諸島群発地震 / ULF磁場データ / 時系列データ / ウェーブレット変換 / 電磁場変動を除去 / 適応フィルタ / 非線形適応フィルタ / transientな現象 / トリンピ効果 / 自動認識・検出 / 異常変化 / 線形適応フィルタ(ADF) / ニューラルネットワーク / 非線形適応フィルタ(NDF) / 信号予測器 |
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| Research Abstract |
To realize the short-term earthquake prediction with using electromagnetic approach, developments of methodologies for automatic detection of anomalous changes and noise reduction in the seismo-electromagnetics measurements. The main results are as follows.
(1)As for the automatic detection of anomalous changes in the time series data, signal predictors with a linear adaptive filter concept and a nonlinear neural network filter concept has been developed, estimates the next datum in time series using the past data. The designed predictor is applied to the automatic detection of a transient signal in the upper atmospheric physics, Trimpi effect. The results show that both are good at good SNR but NNF is superior when SNR is bad.
(2)The signal discrimination methods for seismo-electromagnetics have been developed and examined. They are principal component analysis (PCA), fractal analysis, and interstation transfer function (ISTF) method using wavelet transform. PCA is applied to the data o
… More
bserved at the army system in Izu peninsula, which are associated with the 2000 Izu islands earthquake swarm. It is found that a factor associated with solar activity is dominant in the first principal component. In the second principal component, the influence of artificial noise is rather severe, and the third principal component is concerned with the earthquake-related electromagnetic phenomena. Results of the fractal analysis of ULF magnetic variations indicate that the stage seems to be critical (SOC) at one month or a few days before the large earthquake.
The ISTF method with wavelet transform has been developed for remove global external source fields originated from solar-terrestrial interaction. The results show the external field variations are almost removed successfully in both magnetic and electric fields (t<1,000sec). The residual includes the regional signals such as artificial noises and earthquake-related signals. The signal separation between artificial and earthquake-related is future problem. Less
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