Buried Object Detection Method Using Optimum Frequency Range in Extremely Shallow Underground

元データ 2011-07-25

概要

We propose a new detection method for buried objects using the optimum frequency response range of the corresponding vibration velocity. Flat speakers and a scanning laser Doppler vibrometer (SLDV) are used for noncontact acoustic imaging in the extremely shallow underground. The exploration depth depends on the sound pressure, but it is usually less than 10 cm. Styrofoam, wood (silver fir), and acrylic boards of the same size, different size styrofoam boards, a hollow toy duck, a hollow plastic container, a plastic container filled with sand, a hollow steel can and an unglazed pot are used as buried objects which are buried in sand to about 2 cm depth. The imaging procedure of buried objects using the optimum frequency range is given below. First, the standardized difference from the average vibration velocity is calculated for all scan points. Next, using this result, underground images are made using a constant frequency width to search for the frequency response range of the buried object. After choosing an approximate frequency response range, the difference between the average vibration velocity for all points and that for several points that showed a clear response is calculated for the final confirmation of the optimum frequency range. Using this optimum frequency range, we can obtain the clearest image of the buried object. From the experimental results, we confirmed the effectiveness of our proposed method. In particular, a clear image of the buried object was obtained when the SLDV image was unclear.

著者

Sugimoto Tsuneyoshi Department of Electronics and Information, Faculty of Engineering, Toin University of Yokohama, Yokohama 225-8503, Japan
Sugimoto Tsuneyoshi Department of Electronics and Information, Faculty of Engineering, Toin University of Yokohama, Yokohama 225-8502, Japan
Abe Touma Inspection Division, IHI Inspection & Instrumentation Co., Ltd., Shinagawa, Tokyo 140-0014, Japan

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