Acoustic emission (AE) signal processing and interpretation are essential in mining engineering to acquire source information about AE events. However, AE signals obtained from coal mine monitoring systems often contain nonlinear noise, limiting the effectiveness of conventional analysis methods. To address this issue, a novel denoising approach using enhanced variational mode decomposition (VMD) and fuzzy entropy is proposed in this study. The denoised AE signal’s spectral multifractal features are analyzed. The optimization algorithm based on VMD with a weighted frequency index is introduced to avoid mode mixing and outperform other decomposition methods. The characteristic parameter Δα of the AE spectral multifractal parameter serves as an early warning indicator of coal instability. These findings contribute to the accurate extraction of time–frequency features and provide insights for on-site AE signal processing.

In order to study the prevention and control technology for hard roof type coal burst in the isolated working face of the Chenjiashan coal mine, the 418 isolated working face was selected as the engineering case study. Based on the different impact danger zones and mining areas, a roof breaking blasting pressure relief technical scheme was proposed. The anti-impact effect was verified through hole peeping and infrared radiation data. The research shows: (1) According to the geological conditions of the 418 working face of the Chenjiashan coal mine, the working face is divided into weak impact hazard areas and moderate impact hazard areas. Targeted roof blasting schemes were proposed for the initial square area of the working face, moderate danger area, weak danger area, initial mining and initial caving area, and the strike area of the working face. (2) On-site borehole data show that after blasting, a large number of fractures and delaminations were formed in the roof, and some fractures further developed into delaminations, with local areas showing crushed zones. This proves the formation of a “buffer zone” in the roof and floor, achieving pre-cracking of the thick and hard roof, full development of fractures, significant reduction in stress concentration, and the roof blasting can achieve good pressure relief effect. (3) The temperature monitoring near the blasting point and the infrared radiation temperature shows that within an hour after the implementation of the roof blasting, the coal mass at the breaking position experienced a process of heating up and then cooling down, with the temperature at the monitoring point rising by 0.5–0.7 °C. After the implementation of the roof blasting, the key layer above the working face was destroyed, and the stress was released and transmitted to the corresponding area of the coal mass, the stress of the coal increased, and the infrared radiation temperature increased, proving that the blasting pressure relief achieved the expected effect.

Predicting rock bursts is essential for maintaining worker safety and the long-term growth of subsurface infrastructure. The purpose of this study is to investigate the precursor reactions and processes of rock instability. To determine the degree of rock damage, the research examines the time-varying acoustic emission (AE) features that occur when rocks are compressed uniaxially and introduces AE parameters such as the b-value, γ-value, and β_t-value. The findings suggest that the evolution of rock damage during loading is adequately reflected by the b-value, γ-value, and β_t-value. The relationships between b-value, γ-value, and β_t-value are studied, as well as the possibility of using these three metrics as early-warning systems for rock failure.

Predicting coal bursts in deep mining requires understanding the crack propagation and acoustic emission (AE) characteristics of coal under triaxial stress conditions. This study employs discrete element simulation to investigate the mechanical behavior and AE responses of cylindrical coal specimens under varying confining pressures. The results demonstrate that peak strength increases with loading rate, particularly under low confining pressures, while higher pressures dampen this sensitivity. Volumetric strain-stress curves effectively identify crack initiation and damage thresholds, which increase with confining pressure while reducing the duration of unstable crack propagation. The proportion of tensile cracks gradually decreases while the proportions of shear and mixed-mode cracks increase. Specimens remain stable when β _t -value < 1 and enter instability when β _t -value > 1, with β _t -value remaining unaffected by confining pressure variations., Meanwhile, b-value exhibit a “sharp-drop-plateau” pattern prior to failure. These findings provide a theoretical framework for interpreting AE signals in deep mining environments, enhancing coal burst prediction capabilities through mechanistic insights into confining pressure effects on crack evolution and precursor indicator.