In:
Advanced Materials Research, Trans Tech Publications, Ltd., Vol. 765-767 ( 2013-9), p. 2364-2368
Abstract:
Currently, mine safety is the focal point in mining activity. As a new and advanced approach for geophysical prospecting, the ground penetrating radar (GPR) is used in the mine disaster detection. Aiming to solve the restriction of low resolution and limited depth of the GPR in the deep coal seam detection, the computed tomography (CT) technology is employed for deep disaster detection in this paper. A large number of coal seam digital simulation model, including different internal diseases, are established, and the simulation data are processed by using the Least Square QR-factorization (LSQR) inversion algorithm, which has the good performance in saving computational time and memory space. Additionally, the influences of iteration precision and grid size on the effect of inversion are analyzed. The inversion results show good agreements with simulation model feature configurations, and the diseases objects can be detected.
Type of Medium:
Online Resource
ISSN:
1662-8985
DOI:
10.4028/www.scientific.net/AMR.765-767
DOI:
10.4028/www.scientific.net/AMR.765-767.2364
Language:
Unknown
Publisher:
Trans Tech Publications, Ltd.
Publication Date:
2013
detail.hit.zdb_id:
2265002-7
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