# Digital Processing of Seismic Data from Open-Pit Mining Blasts
## 4 Results and Discussion
However, the experiment lacked the opportunity to do this, and currently a detailed explanation of the results does not seem possible. It is worth mentioning that basic seismic monitoring approaches do not involve natural vibration data from nearby objects, regardless of their effect on total vibration. For example, in [26; 29] the measurements were carried out the same way, but the instruments were located at selected points without direct recording of any nearby object's natural vibration. However, additional research on the dominant frequency changes when possible resonance is considered, which may improve the accuracy of the drilling and blasting parameters. The natural vibration of every nearby object can cause a positive or negative effect on the dominant frequency, depending on the phase term. There is no doubt that the resonance probability is quite low, but this requires additional assessment and should be considered in drilling and blasting parameter variations. To sum up, according to the authors' opinion, for enhanced seismic safety of the guarded objects, it is important to estimate the natural vibration of the guarded objects and the vibration of the objects located close to the explosion site. The findings need detailed investigations and perhaps additional experiments with the simultaneous measurement of close objects' natural vibration and resonance survey. Furthermore, the obtained results prove the practical relevance of preliminary experiments, since pretested conditions of drilling and blasting operations are helpful for parameter optimization. Using this dependence, it is possible to calculate the optimal drilling and blasting parameters for any specific task. For example, using this dependence and [PERSON]'s approach [11], it is possible to calculate the required mass of an explosive substance for a certain dominant frequency. The result of the signal wavelet analysis is illustrated in Figure 7. As one can see in the graph, the percentage distributions of energy at different distances are closely related to each other. To confirm this dependence, it was necessary to estimate the energy distribution correlation (in percent) based on the signal wavelet analysis obtained at different distances from the explosion center. This wavelet analysis shows that, on average, \(\sim\)80% of the entire signal is concentrated in the area up to the 16 th frequency range (half of the frequency spectrum). That is because the low frequency zone is of the most interest. The range of 80 percent is suggestive of the Pareto principle [38]. The correlation matrix for the energy distribution (in percent) based on the signal wavelet analysis at different distances from the explosion center is shown in Table 2.  
\begin{table}
\begin{tabular}{c c c c c c} \hline  & **13 m** & **16 m** & **19 m** & **22 m** & **25 m** \\ \hline
13 m & 1 & 0.9352648 & 0.8886231 & 0.8737632 & 0.8959375  
From Table 2 it is seen that the correlation ratio between the signals is very high. This result can be interpreted as proof of the experiment's validity. This tight correlation indicates the data's homogeneity, which means that all the necessary terms of the experiment are complied with. Within the experiment, it was hypothesized that each parameter that influences blast wave propagation can be detected at a certain signal frequency range. So, the signal decomposition into its frequency components can show how energy values correlate to other parameters influencing the blast wave nature at every frequency range (for example, strong correlation of energy and explosive mass values at the fifth range probably means that for optimal explosive mass determination it is necessary to analyze the signal frequencies of the fifth range, etc.). To prove this hypothesis, the research shows one more correlation assessment of the distance to the blast site and the energy values for each frequency range.