Abstract: The authors propose a quantitative characterization method based on full acoustic waveform signals to detect cumulative damage in the surrounding rock of mountain tunnels after cyclic blasting. The results provide a theoretical basis for the accurate evaluation of damage to surrounding rock and the precise control of blasting construction. First, a damage-increment formulation that incorporates cumulative blasting effects is derived based on full acoustic waveform signals obtained before and after blasting. Furthermore, the multidimensional spatial distribution of blasting-induced damage in the surrounding rock is characterized by the Lorenz curve, Gini coefficient, and fractal theory. Finally, by examining the variations in the dominant frequency and the amplitude of the full acoustic waveform signals of the engineering rock mass before and after blasting, the evolution patterns in both the time and frequency domains are identified and are further verified using wavelet-packet energy spectra. The results lead to the following conclusions: (1) The acoustic wave velocity primarily reflects the average mechanical properties of the rock mass, whereas the Gini coefficient mainly captures the spatial distribution characteristics of damage and is particularly sensitive to localized abrupt attenuation in amplitude. (2) For intact surrounding rocks, the full acoustic waveform signals exhibit simple patterns, corresponding to relatively low fractal dimensions. In contrast, for cracked or damaged rock masses, the formation and propagation of defects lead to an increase in the associated fractal dimension. (3) The fractal dimension correlates positively with the damage level of surrounding rock in shallow-buried tunnels, whereas this correlation weakens in deep rock masses. (4) The cumulative damage intensifies with the number of blasting cycles, whereas the incremental damage gradually decreases. Thus, the amplitude of the time-domain characteristics of the acoustic signals decreases, the dominant frequency decreases in amplitude, and the lower frequencies gain in amplitude.

Key words: tunnels, surrounding rock blasting, full acoustic waveform signal, Gini coefficient, fractal theory, time-frequency analysis, energy spectrum