Zhenrong Wang
CHN Energy Shendong Coal Group Co., Ltd., Ordos 01700, China
Shendong Coal Branch, China Shenhua Energy Co., Ltd., Ordos 01700, China
Yuan Yang
CHN Energy Shendong Coal Group Co., Ltd., Ordos 01700, China
Shendong Coal Branch, China Shenhua Energy Co., Ltd., Ordos 01700, China
Fengjuan Tao
Wuhan Changsheng Coalmine Safety Technology Co., Ltd., Wuhan 430300, China
Geological anomalies, including faults, fractured zones, and collapse pillars, pose serious threats to mining safety by increasing the risk of water inrush and roof collapse. To enable accurate ahead-of-face detection, this paper presents the development and practical application of a single-borehole impulse radar (BHR) system specifically designed for underground coal mine environments. The system incorporates a compact, explosion-proof probe constructed from fiberglass, with a diameter of 40 mm, making it suitable for deployment in confined boreholes. By leveraging wideband impulse signals, the BHR achieves high-resolution subsurface imaging while maintaining low power consumption and rapid data acquisition rates. The system’s detection performance was first verified through controlled ground experiments in a railway tunnel, where it accurately identified karst structures—a finding later confirmed by subsequent excavation. Field applications at Wangzhuang and Madaotou coal mines demonstrated its effectiveness in identifying fracture zones, water-rich strata, and fault systems. Repeated measurements across multiple boreholes demonstrated high detection stability and strong consistency with actual exposed geological conditions. Although operational challenges such as signal transmission in narrow spaces and high sampling rate requirements persist, the proposed system successfully balances imaging resolution, operational portability, and real-time processing capability. The results affirm the significant potential of impulse borehole radar for enhancing geological forecasting and improving safety in underground coal mining operations.
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Copyright © 2025 Zhenrong Wang, Yuan Yang, Fengjuan Tao
This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.
