2022 Fiscal Year Final Research Report
Construction and evaluation of a system for measuring changes in ground surface potential during earthquakes
Project/Area Number |
19K03045
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Multi-year Fund |
Section | 一般 |
Review Section |
Basic Section 09070:Educational technology-related
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Research Institution | Sasebo National College of Technology (2022) Ishikawa National College of Technology (2019-2021) |
Principal Investigator |
Yoshiaki Suda 佐世保工業高等専門学校, その他, 特命教授 (20124141)
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Co-Investigator(Kenkyū-buntansha) |
川崎 仁晴 佐世保工業高等専門学校, 電気電子工学科, 教授 (10253494)
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Project Period (FY) |
2019-04-01 – 2023-03-31
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Keywords | 地表面電位変化 / 地震 / 地殻変動 / 大気電界変化 / 自然災害 / 豪雨 / 豪雪 |
Outline of Final Research Achievements |
An inexpensive system to electrically detect extremely small precursory crustal deformations have been developed. The system was installed at eight technical colleges and universities throughout Japan. Using this system, we developed a device to collect and display electrical information from all over Japan.The results of this study revealed the follows. 1) Before an earthquake, there is a predominant change in electrical potential in the positive direction. This is thought to be due to ions generated by the shear stress of the earth. 2) Potential changes also occur with approaching cumulonimbus clouds that bring lightning strikes and heavy rainfall. During lightning strikes, the potential can be negative. 3) Potential changes in the negative direction occur during snowfall. 4) Potential changes almost always occur before an earthquake. But when a potential change occurs, the likelihood of an earthquake is found to be less than 30%.
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Free Research Field |
教育工学
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Academic Significance and Societal Importance of the Research Achievements |
地震や豪雨などの大規模自然災害を地表面電位変化からある程度予知できるシステムの開発を行った。これらの変化は、地震や降雨時前の積乱雲の接近でほぼ必ず起こるが、どのような電位変化のパターン後にどのような気象変動が起こるかは確実には分からなかった。また、電位変化は災害の必要条件ではあるが、十分条件ではないため、確実な予測には単純には利用できない。今後は、電位変化のパターンや計測装置の形状変化を工夫することと、これらのデータを多く蓄積し、AI等でパターン解析することによって、予知装置としての精度を上げられるか、検討していくとともに、地震や豪雨、豪雪、落雷を学習する装置として利用することを検討したい。
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