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JRM Vol.7 No.2 pp. 135-140
doi: 10.20965/jrm.1995.p0135
(1995)

Paper:

Estimation of the Under-Surface Temperature Pattern by Dynamic Remote Sensing

Minoru Inamura* and Hiromichi Toyota**

*Faculty of Engineering, Gunma University, 1-5-1, Tenjin, Kiryu, Gunma, 376 Japan

**Faculty of Engineering, Seikei University, 3-3-1, Kita-machi, Kichijyoji, Musashino, Tokyo, 180 Japan

Received:
November 15, 1994
Accepted:
November 25, 1994
Published:
April 20, 1995
Keywords:
Inversion method, System identification, Thermal image, Non-destructive test
Abstract

The remote sensing (R/S) methods can be classified into three kinds: 1) the measurement of the reflection of sun beams (passive R/S); 2) the measurement using millimeter wave or laser radar (active R/S); and 3) the measurement of infrared radiation. By these methods, one can obtain information on a measured object concerning 1) its surface temperature, 2) its effective emissivity, and 3) its effective reflectivity. The surface temperature, in effect, contains the total information on the under-surface structure. The authors performed a fundamental experiment for extracting such under-surface information by R/S, which is known as “dynamic remote sensing”. In the first place, we determined a special function for the medium (sand in our experiment), and then filtering the surface temperature pattern, and calculated the undersurface temperature pattern; from this data we estimated the form of the sample in the medium. In the second place, we analyzed the relation between the thermal input (the temperature in the bottom) and thermal output (the surface temperature) by analogy with electric circuits, calculated the heat capacity and ther thermal conductivity of the sample, and estimated its substance. As a result, the present study is expected to provide us with guidance to new methods for the exploration of underground water or minerals as well as non-destructive tests.

Cite this article as:
Minoru Inamura and Hiromichi Toyota, “Estimation of the Under-Surface Temperature Pattern by Dynamic Remote Sensing,” J. Robot. Mechatron., Vol.7, No.2, pp. 135-140, 1995.
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