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High Accuracy Evaluation of Concrete Delamination Risk by Deep Learning of Hammering Sounds
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- Sonoda Yoshimi
- Principal Investigator
- 九州大学
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- 玉井 宏樹
- Co-Investigator
- 九州大学
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- 別府 万寿博
- Co-Investigator
- 防衛大学校(総合教育学群、人文社会科学群、応用科学群、電気情報学群及びシステム工学群)
About This Project
- Japan Grant Number
- JP20H02234 (JGN)
- Funding Program
- Grants-in-Aid for Scientific Research
- Funding Organization
- Japan Society for the Promotion of Science
Kakenhi Information
- Project/Area Number
- 20H02234
- Research Category
- Grant-in-Aid for Scientific Research (B)
- Allocation Type
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- Single-year Grants
- Review Section / Research Field
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- Basic Section 22020:Structure engineering and earthquake engineering-related
- Research Institution
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- Kyushu University
- Project Period (FY)
- 2020-04-01 〜 2023-03-31
- Project Status
- Completed
- Budget Amount*help
- 17,680,000 Yen (Direct Cost: 13,600,000 Yen Indirect Cost: 4,080,000 Yen)
Research Abstract
本研究は，コンクリートの剥落事故を防ぐために,劣化損傷を模擬した供試体を製作し，軽度な繰り返し衝撃試験を行いながら，損傷進展による非破壊試験（打音・赤外線画像）データの変化を深層学習させることで，RC構造物のコンクリート剥落の予兆を捉える手法を確立するものである．
Keywords
Details 詳細情報について
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- CRID
- 1040285300695465984
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- Text Lang
- ja
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- Data Source
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- KAKEN