Research of Computed Tomography Inversion Algorithm for Coal Face Based on Ground Penetrating Radar

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.

• Periodical: Advanced Materials Research (Volumes 765-767)
• Pages: 2364-2368
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.765-767.2364
• Online since: September 2013
• Authors: Feng Yang, Cui Du, Meng Peng, Ze Quan Feng, Yang Yang Sun, En Lai Li
• Keywords: Coal Face, CT Inversion, Disaster Sources, GPR, Sparse Matrix

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