International Journal of Mining Science and Technology (Nov 2024)
A new scientific explanation to rock fracture-induced electromagnetic radiation process
Abstract
The electromagnetic radiation (EMR) monitoring and early warning technology has experienced decades of successful applications for worldwide coal and rock dynamic disasters, yet a fundamental model unifying physical mechanism and generation process for EMR is still lacking. The effective revealing of EMR’s mechanism is crucial for dynamic disaster control and management. With this motive, a multi-scale experimental study was conducted in the earlier stage. At the micro-scale, the charge’s existence and non-uniform distribution on rock’s micro-surface were confirmed by atomic force microscope (AFM), and deduced the relationship with load changes. At the meso-scale, the time sequence synchronization and frequency domain consistency of EMR and micro-vibration (MV) in the rock fracture under load have been confirmed. Therefore, it is inferred that the vibration of the crack surface acts as the power source of rock fracture-induced EMR, and the original charge on the crack surface and the charge generated by the new crack surface are the electrical basis of EMR. Based on the above two experimental findings, this paper proposes a new mechanism of rock fracture-induced EMR defined as the electricity-vibration coupling mechanism, stating that, the vibrating charged crack generates the EMR. Subsequently, a generation model was constructed based on vibrating charged crack clusters to elucidate this mechanism. The experimental results demonstrated that the EMR waveform calculated by the model and measured by antenna exhibited good correspondence, thereby verifying the effectiveness of the constructed EMR model. The proposal of this new mechanism and the model further clarified the EMR’s mechanism induced by rock fracture. Moreover, the inter-relationship among crack propagation, vibration, and EMR was developed by this model, which could be immensely beneficial in EMR-based identification and prediction of dynamic disasters in complex mining environments worldwide.
