Abstract: In the process of mining in underground coal face, it is the guarantee of safe and efficient production of coal mine to grasp the abnormal situation in front of coal face in time. Ground penetrating radar (GPR) is an efficient and non-destructive detection method, which is widely used in mines. Significant achievements have been made in the image interpretation and imaging accuracy of GPR for detecting abnormal body response, but how to delineate the location and spatial distribution of geological abnormal body with GPR is a hot research issue. In this paper, a new method, which combines multiple sections and linear interpolation, is developed for accurate detection of abnormal body in coal mining face. The main research ideas are as follows. Firstly, forward simulation of 3D model of coal seam cavity and fault is carried out by using finite difference time domain algorithm (FDTD), and the response range of abnormal body is roughly delineated by Kirchhoff migration. Secondly, the multi-section view of single channel wave data with abnormal body response was obtained, and the exact position coordinates and specific dimensions of abnormal body were determined by linear interpolation, and the area evaluation criterion was introduced to verify the similarity of detection results. Finally, a GPR of LTD-2600 and a 900 MHz shielded antenna were used to conduct field experiments on the constructed physical cavity model, and the calculated cavity profile was compared with the actual cavity size for verification. The proposed method was applied in 18201 face of Xiegou coal mine to verify its validity. It is proved by practice that the error between the measured and actual spatial positions is less than 10%, and the specific size and spatial distribution range of abnormal bodies can be delineated relatively accurately.

Key words: coal mining face, ground penetrating radar, advance detection, multi-section analysis, Kirchhoff migration