Acoustic emission-microseismic response and instability early warning of coal failure after drainage under different initial gas pressures

To achieve effective monitoring and early warning of coal seam instability after gas drainage, combined acoustic emission and microseismic monitoring tests were conducted on the coal failure process under different initial gas pressure conditions. The effects of initial gas pressure on the mechanical properties, energy dissipation characteristics, and acoustic emission-microseismic signal responses of coal were systematically analyzed, and an instability early-warning index for coal after gas drainage was established. The results show that, with increasing initial gas pressure, the internal deterioration of gas-drained coal intensifies, local strain energy is released earlier, acoustic emission and microseismic signals are activated in advance, and energy events change from a “single dominant cluster” to a “multi-cluster distribution.” The peak intensity and elastic modulus of the coal samples decrease exponentially, with reductions of 64.07 % and 69.51 %, respectively. The failure mode gradually changes from axial splitting to shear-dominated failure. The first stress drop occurred significantly earlier, and the relative lead-time ratio of crack initiation increased by 35.8 %. Based on the synergistic response characteristics of acoustic emission and microseismic signals, a composite graded early-warning index for coal instability was constructed, and the graded thresholds were determined. Under the 0 MPa condition, η A-M < 0.12, 0.12 ≤ η A-M < 0.36, and η A-M ≥ 0.36 correspond to risk-free, low risk, and high risk, respectively. Under the 1–2 MPa conditions, the thresholds are 0.08 and 0.24, respectively; under the 3 MPa condition, the thresholds are 0.06 and 0.16, respectively. Experimental verification shows that the high-risk warning moments identified by η A-M all occur during the intensified damage stage of coal, demonstrating that this index can be used for early warning of instability risk in gas-drained coal. The findings provide a theoretical basis for monitoring and early warning of dynamic disasters in gas-bearing coal mines.