A reasonable blasting construction method is critical to maintaining caverns′ stability and water-sealing integrity. In this study, seismic wave detection and acoustic wave detection were conducted within a water-sealed cavern. The HHT signal analysis method was used to process the seismic wave signals generated by blasting, and both Empirical Mode Decomposition(EMD) and Ensemble Empirical Mode Decomposition(EEMD) were applied to compare and reduce signal mode aliasing, improving the accuracy of signal analysis. The marginal spectrum, instantaneous energy spectrum, three-dimensional energy spectrum, and loose zones in surrounding rock were used to evaluate the influence of different blasting schemes on the water-sealed caverns. The results show that the EEMD-Hilbert analysis method effectively mitigates mode aliasing issues caused by traditional EMD decomposition, producing a smoother and more reliable vibration velocity time-history curve. Marginal spectrum analysis of the reconstructed signal reveals that the frequency band of the double-sided wall heading method ranges from 200 to 380 Hz. In contrast, the frequency band of the single-sided wall guide pit method is narrower, concentrated between 110 and 250 Hz, with relatively lower frequency energy in both conditions. The combined instantaneous energy of the double-sided wall guide method is higher than that of the single-sided wall guide method, with 41.67% and 23.73% of the total instantaneous energy concentrated in the first section of the cutting hole for each method, respectively. The instantaneous energy distribution of the single-sided wall guide method is more uniform and lower than that of the double-sided. The range of loosening rings on both sides of the arch waist in the double-sided wall heading method is about 1.0 to 1.2 m. In contrast, the single-sided wall guide pit method measured 0.8 meters and 1.0 to 1.2 meters on the expanding excavation surface and guide tunnel surface, respectively. A joint analysis of the EEMD Hilbert method and acoustic detection indicates that the single-sided wall guide pit method is more suitable for blasting excavation in water-sealed caverns.

In the field test of open-air step blasting, the explosion time is short and there is certain danger, so it is difficult to realize the detailed observation of blasting process. Based on the engineering background of step blasting in a mine, the discrete element model of particle flow is established. Combined with software LS-DYNA and PFC, the throwing and stacking process of step blasting is simulated based on continuous-discontinuous blasting model. Due to the different effects of blast stress wave and blast gas in the blasting process, the blast stress wave and blast gas are respectively simulated in the form of velocity and pressure in the numerical simulation, and the development and distribution of rock cracks in the blasting process and the throwing and stacking effect of blast heap are analyzed. Through field blasting experiments, it is verified that the simulation results are consistent with the field blasting results.

This study presents a comprehensive approach to solve the problem of low ore recovery caused by the difficulty in separating small-particle size ore from soil after blasting in a limestone building stone mine. Firstly, a correlation model between blasting fragmentation and dynamic damage of rock mass was established based on field measurement data and numerical simulation results, which can determine dynamic damage thresholds corresponding to various rock particle sizes. Secondly, the numerical simulation test of bench blasting in a three-dimensional fractured rock mass was carried out by using different air-decked charging stages and borehole distribution parameters, which can improve the particle size yield of 0.3~0.9 m and control the bulk ratio to obtain the best blasting parameters. Finally, the field blasting tests were conducted to optimize the charge structure and borehole distribution parameters based on numerical simulation results. The results show a negative exponential function relationship between the blasting block size and the dynamic damage value of the limestone. Specifically, the dynamic damage thresholds corresponding to the blasting size of 0.3 m and 0.9 m are 0.793 and 0.286, respectively. Using only an air-decked charging structure alone can increase the particle size ratio of 0.3~0.9 m and significantly raise the bulk rate. Conversely, combining an air-decked charging structure with a reduced hole spacing markedly enhances the particle size ratio of 0.3~0.9 m while maintaining a stable bulk rate. Optimal blasting results are achieved using a two-stage air interval charging structure and a strategic reduction in hole distribution parameters. The field application results show a 20.09 percentage point increase in the 0.3~0.9 m particle size ratio, with the bulk rate remaining virtually unchanged. Additionally, the unit consumption of explosives decreased by 10.29%.

The distribution of blasting fragmentation in open pit mines has a direct impact on subsequent excavation, transportation, and crushing operations. To effectively control the fragmentation distribution of blasted rocks in different regions of graphite mines, a new model for evaluating rock blastability was developed using the K-means unsupervised cluster learning method and entropy weight TOPSIS evaluation method. Evaluation indexes including rock density, dynamic energy dissipation rate, dynamic compressive strength, average strain rate, and brittleness index were selected. Through entropy weight calculation, it was determined that the degree of rock breakage is most influenced by the brittleness index and least influenced by the average strain rate. The model was then applied to an actual graphite mine to assess its effectiveness. The rock blastability was divided into 10 grades based on this evaluation model. The average particle size of rocks under different grades was calculated and it was observed that as blastability grade increased, so did the average particle size. This finding demonstrates clear classification characteristics and validates the efficacy of our model. From the perspective of rock mass type of graphite ore, the rock explosibility is ranked from easy to difficult: schist, gneiss, granodiorite, mixed rock. Combined with the analysis of microscopic observation results of graphite ore, it can be seen that the lithology changes from schist to mixed rock, and the graphite crystalline content in the rock decreases, and the graphite ore explosibility grade is also higher and higher. Additionally, there exists a linear positive relationship between density/energy dissipation rate/dynamic compressive strength with rock blastability while negative correlation is observed with respect to average strain rate/brittleness index.