## 1 Introduction  
Mining-induced earthquake refers to the phenomenon of vibrations caused by the rapid release of elastic energy in rock masses, induced by disturbances from underground resource extraction. These events are common and will invariably occur with the exploitation of underground solid resources [1]. However, as mining depth increases, the scale of goaf areas expands, the complexity of mine structure intensifies, and the surrounding stress levels rise, the frequency and intensity of high-energy mining-induced earthquake events are increasing [2; 3; 4]. Frequent high-energy mining-induced earthquake activity typically indicates the gradual accumulation of stress within rock masses, which can further lead to rockburst hazards, posing significant threats to mine safety and regional social stability [5]. Consequently, research on precursor identification and control strategies for high-energy mining-induced earthquake event risks is crucial to ensure safe mining operations. To enhance the safety and efficiency of deep coal mining, various monitoring and early warning methods have been widely applied, including microseismic monitoring [6; 7; 8], electromagnetic radiation monitoring [9; 10], stress monitoring [11; 12], and infrared monitoring [13; 14]. Additionally, in conditions of dynamic hazards, rock mass monitoring should be carried out in parallel with the selection of a support system capable of absorbing the largest possible amount of dynamic energy, ensuring the safety of mining operations by reducing the impact of dynamic events [15]. Domestic and international researchers have conducted in-depth studies on these monitoring techniques, continuously optimizing and integrating different methods, thereby establishing a solid technical foundation for the identification of high-energy mining-induced earthquake precursors and the development of effective risk control strategies. Microseismic monitoring, as a real-time and efficient monitoring method, utilizes sensors installed at various locations underground in coal mines to capture seismic signals generated by the fracturing of coal and rock masses. This technique enables the localization of seismic sources and the calculation of event energy [16; 17; 18] and has been widely applied in coal mine operations. [PERSON] et al. [5], using a microseismic monitoring system, analyzed the response characteristics of different parameters prior to mining-induced earthquake events and defined a new prediction parameter--the Energy Rockburst Warning (ERW) index. Source mechanism inversion is a crucial technique in seismic analysis, as it uses raw waveform data collected from multiple sensors to precisely locate seismic sources, determine fracture modes, and calculate parameters such as moment magnitude and energy [19], offering valuable insights into seismic risk precursors and triggering factors. [PERSON] et al. [20] investigated the destruction mechanisms and stress evolution in irregular coal pillar anomaly zones using microseismic monitoring, moment tensor inversion, and velocity tomography. Similarly, [PERSON] et al. [21] studied the outcomes of rockbursts, as well as the spatiotemporal evolution of microseismic (MS) and acoustic emission (AE) monitoring results. They analyzed the relationship between AE and MS precursor signals prior to rockbursts, finding that their spatiotemporal evolution patterns could serve as early warning indicators for rockbursts. Furthermore, the study also indicates that the \"silent period\" of mining-induced earthquakes is one of the critical precursor signals. In the hours to days leading up to a mining-induced earthquake, the frequency and energy of microseismic events often show a significant reduction or even a temporary cessation, a phenomenon referred to as the \"silent period\" [22; 23]. The identification of the silent period is crucial for predicting mining-induced earthquakes, as its presence often indicates high-risk areas for such events.