In the field of mining engineering, the drill-and-blast method is a prevalent excavation technique. The structural planes of the rock mass directly influence the propagation and attenuation of blasting stress waves, thereby rendering the precise and efficient determination of rock layer interface positions essential for the operational efficiency and safety of drill-and-blast operations. This study leverages a self-developed indoor digital drilling test platform to conduct cutting and drilling experiments on layered rock-like specimens, obtaining drilling operational parameters and vibration response signals. A prediction model for identifying layered rock mass interfaces is established using the GA-K-means algorithm, with the CH index employed as a fitness metric to enhance the model′s global search capability. A comparative analysis demonstrates that the cumulative errors for drilling vibration response and drilling operational parameters are 2.02 mm and 6.08 mm, respectively, indicating that the former exhibits greater sensitivity to variations in rock layers and provides more accurate interface identification outcomes. Drilling parameters are prone to significant deviations due to uneven rock breaking by the drill bit, while changes in these parameters notably influence vibration response signals in rock layer strength. Predicted interface positions often occur ahead of actual interfaces, revealing their potential for early prediction. This paper proposes a method based on feature weighting and cluster analysis to improve the accuracy and efficiency of rock layer interface identification. Compared to the K-means algorithm, the GA-K-means algorithm achieves over 31% higher identification accuracy. The results demonstrate that the GA-K-means rock layer interface identification model can effectively extract key rock layer information from complex drilling parameters, providing valuable references for geological exploration.

To enhance the accuracy of blasting vibration predictions in an open-pit mine stripping project, a new peak particle velocity(PPV) prediction formula is proposed, incorporating geological elevation differences and slope effects. Based on the principles of dimensional analysis, the traditional Sadovsky formula was modified by introducing the elevation difference(H) and slope coefficient(γ), resulting in a new prediction model(Formula 11). Notably, when H=0, the new formula reverts to the traditional Sadovsky formula, ensuring its reliability. A field vibration monitoring test was conducted in the mine, with 5 monitoring points at elevation differences of 0.222 m, 0.176 m, 0.865 m, 1.617 m, and 2.465 m. Using the TC-4850 blasting vibration meter, vibration data were recorded, and multiple predictions, including the Sadovsky and the newly proposed formula, were fitted using multivariate nonlinear regression. Results show that the proposed formula achieves the highest correlation coefficient(R²=0.905), surpassing other models. Furthermore, the new formula exhibits improved prediction accuracy, with a maximum relative error of 20.85% and an average error of 8.11%, compared to 24.89% and 10.31% for the original Sadovsky formula. By considering the factors of elevation and slope, the proposed prediction formula significantly improves the precision of PPV predictions under complex terrain conditions, providing a scientific basis for blasting vibration control and safety management. Applying the specific scheme and data proves the effectiveness and practicality of the formula.

To optimize the initiation delay time of an open-pit mine and enhance blasting efficiency, a three-dimensional bench blasting model is developed using ANSYS/LS-DYNA software. The model consists of 2 blast holes in the front row and 1 blast hole in the back row arranged in a triangular pattern. The bottom initiation was employed, and 5 stress monitoring points were placed within the hole placement area. Simulated tests were conducted to evaluate rock fragmentation under different delay times between rows(42 ms) and between holes(11, 13, 15, 17, 19, 21, and 23 ms), while monitoring their effective stress levels. Additionally, a delayed detonation profile model for the two front row boreholes was established to observe the propagation characteristics of explosion stress waves. The results indicate that when the delay time between rows is set at 42 ms and between holes at 17 ms, it leads to peak values of maximum effective stress at each monitoring point which facilitates overall rock fragmentation. The advantage of time-delay blasting lies in its ability to enhance rock damage by utilizing the pre-blast hole as a foundation, while the front-row hole acts on the post-blast hole through pre-detonation effects, creating a new free surface. Through field testing and demonstration, we analyzed the distribution of rock fragmentation in blasting pile photos using split-desktop software. The findings indicate that with an inter-row delay time of 42 ms and an inter-hole delay time of 17 ms, approximately 77.24% of rocks are below 20 cm in size, while only a negligible proportion(0.31%) exceeds 50 cm. Overall, the crushing effect is satisfactory and meets both production and operational requirements for open-pit mining operations.