Research of Computed Tomography Inversion Algorithm for Coal Face Based on Ground Penetrating Radar
Feng Yang, Cui Du, Meng Peng, Zequan Feng, Yangyang Sun, Enlai Li
Available Online February 2013.
- https://doi.org/10.2991/isccca.2013.172How to use a DOI?
- GPR, CT inversion, sparse matrix, coal face, disaster sources
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Feng Yang AU - Cui Du AU - Meng Peng AU - Zequan Feng AU - Yangyang Sun AU - Enlai Li PY - 2013/02 DA - 2013/02 TI - Research of Computed Tomography Inversion Algorithm for Coal Face Based on Ground Penetrating Radar BT - Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation (ISCCCA 2013) PB - Atlantis Press SP - 686 EP - 689 SN - 1951-6851 UR - https://doi.org/10.2991/isccca.2013.172 DO - https://doi.org/10.2991/isccca.2013.172 ID - Yang2013/02 ER -