Presentation 2019-12-22
Study on hammering test system using artificial intelligence
Tsubasa Fukumura, Atsushi Ito, Katsuhiko Hibino,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Social infrastructure such as bridges and tunnels is very important in economic activities, but in recent years aging has progressed and demand for inspection work is expected to expand. Among inspection work, it is possible to inspect by abnormal sound which can’t be visually observed, such as the inside of concrete wall, by change of sound by hammering sound. In the inspection called this hammering test, the distinction of abnormal sound depends on the feeling of the person performing the hammering sound, and there is a possibility that the results may be inconsistent. In addition, since hammering is performed manually, there is also a problem that it takes time to perform a wide range of examination. Therefore, in this paper, we describe a system for a small hammering tone inspection device which can analyze and judge sounds hit the wall with a hammer with artificial intelligence and judge an abnormal part even for unskilled people. In addition, we will raise the issues and consider a new system using GPU and transfer learning to improve work efficiency and accuracy.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Social infrastructure / Hammering test / Deep learning / Transfer Learning / GPU
Paper # TL2019-44
Date of Issue 2019-12-15 (TL)

Conference Information
Committee TL
Conference Date 2019/12/22(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Hiroshi Sano(Tokyo Univ. of Foreign Studies)
Vice Chair Tadahisa Kondo(Kogakuin Univ.) / Kazuhiro Takeuchi(Osaka Electro-Comm. Univ.)
Secretary Tadahisa Kondo(Kobe Gakuin Univ.) / Kazuhiro Takeuchi(Kyoto Inst. of Tech.)
Assistant Nobuyuki Jincho(Miidas) / Akinori Takada(Ferris Univ.) / Akio Ishikawa(KDDI Research)

Paper Information
Registration To Technical Committee on Thought and Language
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Study on hammering test system using artificial intelligence
Sub Title (in English)
Keyword(1) Social infrastructure
Keyword(2) Hammering test
Keyword(3) Deep learning
Keyword(4) Transfer Learning
Keyword(5) GPU
1st Author's Name Tsubasa Fukumura
1st Author's Affiliation Utsunomiya University(Utsunomiya-u)
2nd Author's Name Atsushi Ito
2nd Author's Affiliation Utsunomiya University(Utsunomiya-u)
3rd Author's Name Katsuhiko Hibino
3rd Author's Affiliation Port electric Inc.(Port Inc)
Date 2019-12-22
Paper # TL2019-44
Volume (vol) vol.119
Number (no) TL-352
Page pp.pp.7-12(TL),
#Pages 6
Date of Issue 2019-12-15 (TL)