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JDR Vol.12 No.3 pp. 415-421
doi: 10.20965/jdr.2017.p0415
(2017)

Paper:

Bridge Slab Damage Detection by Signal Processing of UHF-Band Ground Penetrating Radar Data

Tsukasa Mizutani*,†, Nagisa Nakamura*, Takahiro Yamaguchi*, Minoru Tarumi**, Yusuke Ando**, and Ikuo Hara**

*The University of Tokyo, The Department of Civil Engineering, Tokyo, Japan

Corresponding author

**The Department of Geophysical Survey, C. E. Management Integrated Laboratory Co. Ltd., Osaka, Japan

Received:
October 3, 2016
Accepted:
February 13, 2017
Online released:
May 29, 2017
Published:
June 1, 2017
Keywords:
UHF-band Ground Penetrating Radar, RC bridge slab, automatic damage detection, signal processing, on-vehicle measurement
Abstract

Maintenance costs for infrastructure, such as bridges, have been increasing particularly in the developed countries. Bridge slabs are important parts of bridges; however, the evaluation of their structural conditions requires significant manpower and time because dense hammering tests have to be conducted as part of the present inspection methods. To overcome this difficulty, a non-contact inspection technique using a radar is focused in this research. Radar techniques are typically utilized in the fields of mine-search, oil-source search, and geographical archeology. However, these searches are conducted by only visually checking reflected-wave images, and thus, the evaluation strongly depends on the abilities and expertise of the inspectors. To more effectively utilize these radar techniques for evaluating a bridge slab condition, analysis of the reflected wave signals should be made automatic, fast, and objective because the number of bridges to be inspected is large. In this research, to detect the damages on a slab, some signal processing techniques for measuring the reflected wave signal by a UHF-band fast scanning and non-contact radar are proposed, and their validity is shown by applying them to the signals obtained from full-scale bridge slab models in which certain ideal damages are embedded.

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Last updated on Dec. 12, 2017