## 3 Results and Discussion
### Strong Seismic Load Waveform Data and Source Parameter Analysis  
Nine typical dynamic load data are selected from the area circled in Figure 7 to solve the focal mechanism. The distribution locations of these events are shown in Figure 8a. The station arranged near the working face 3310 was monitored to obtain the velocity-time signal of the mining earthquakes, from which the low-frequency displacements of the respective mining earthquake events were obtained, as well as their low-frequency displacements. The vibration waveform signals of some of the strong mining earthquake events are given in Figure 8b. Source parameters can characterize the mechanical features of the seismic source in various aspects. In order to further classify the strong dynamic loads, Fast Fourier Transform (FFT) was applied to the waveforms of the nine strong dynamic load events to obtain the double-logarithmic displacement-frequency spectrum. The Brune model was then used for fitting, and the obtained low-frequency displacement \(\Omega_{0}\) and corner frequency \(f_{0}\) for each event were calculated, as shown in Table 1. The nine strong dynamic load waveforms were divided into three groups: pillar-type strong dynamic load data (M1, M2, M3), fault-type strong dynamic load data (D1, D2, D3), and roof-type strong dynamic load data (B1, B2, B3). According to the calculation method described in Section 2.2, the typical strong dynamic load seismic source parameters obtained are shown in Table 2. Figure 9, in turn, shows a comparison of the mean values for each of the three types of strong dynamic loads in terms of seismic moment, source radius. According to the statistical results shown in Table 2 and Figure 9, it can be concluded that the seismic moment of various strong dynamic load events is between \(10^{10}\) and \(10^{12}\) N-m. Under the same radiation energy condition, the coal pillar-type has the largest seismic moment, followed by the roof-type, and the fault-type has the smallest moment, indicating that the coal pillar source rupture intensity is greater. Both the focal radius and apparent volume can reflect the scale of the  
Figure 8: Spatial distribution (**a**) and partial waveforms of strong dynamic loads (**b**). focal rupture. Under the same focal radius, the volume increase in the coal and rock mass caused by the inelastic deformation of the fault-type source is the largest, followed by the coal pillar-type, and the roof-type has the smallest scale. Overall, the fault-type rupture has the smallest strength and scale, but its stress drop is high, and the stress level adjustment or release amplitude is the largest, followed by the coal pillar-type, and the roof-type is the smallest. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Event** & \(\mathbf{\Omega_{0}/m\cdot s}\) & \(\mathbf{f_{0}/Hz}\) & **Mark** \\ \hline
1 & \(1.29\times 10^{-7}\) & 1.83 & D1 \\
2 & \(1.54\times 10^{-7}\) & 2.22 & D2 \\
3 & \(2.47\times 10^{-7}\) & 10.42 & D3 \\
4 & \(4.56\times 10^{-7}\) & 2.09 & B1 \\
5 & \(1.13\times 10^{-8}\) & 16.84 & B2 \\
6 & \(1.19\times 10^{-8}\) & 37.96 & B3 \\
7 & \(1.62\times 10^{-8}\) & 7.19 & M1 \\
8 & \(2.65\times 10^{-8}\) & 2.77 & M2 \\
9 & \(6.02\times 10^{-7}\) & 9.86 & M3 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Statistics of typical strong dynamic load low-frequency displacement \(\Omega_{0}\) and corner frequency\(f_{0}\).