Study on the time-frequency characteristics of blasting seismic waves and peak particle velocity prediction model in deep mining stope

Abstract

To study the signal characteristics and vibration velocity attenuation mechanism of seismic wave in blasting roadway of deep stope, this study systematically analyzes the time-domain, frequency-domain, and instantaneous energy characteristics of seismic waves based on field monitoring data. The results indicate that blasting seismic waves exhibit multi-segmented time-domain characteristics, high-frequency components in the near field and low-frequency components in the far field in the frequency domain, as well as a dual-peak feature in instantaneous energy. By employing Butterworth signal processing techniques, the study successfully separates seismic waves induced by explosive loading and transient stress unloading, and develops a corresponding nonlinear fitting model. Based on dimensional analysis, a peak particle velocity (PPV) prediction model, BL-TU, was proposed, which comprehensively considers both explosive loading and transient unloading energy. Compared with the Sadov’s empirical formula, the BL-TU model offers a clearer physical interpretation and higher prediction accuracy. To further enhance predictive performance, a Bayesian optimization-based support vector regression model (BOA-SVR) was developed. The results demonstrate that the BL-TU and BOA-SVR models significantly outperform Sadov’s empirical formula in terms of prediction accuracy. These models provide an effective means for predicting peak particle velocity under complex deep geological conditions.