## 3 Experimental Analysis
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Serial Number**} & \multirow{2}{*}{**Date Time**} & \
\begin{tabular}{c} **The Original System** \\ **of the Group Detects** \\ **Microseismic Energy** \\ **(J)** \\ \end{tabular} &
\begin{tabular}{c} **The Method Used in** \\ **This Article to Detect** \\ **(J)** \\ \end{tabular} & \multirow{2}{*}{**Actual Energy (J)**} & \multirow{2}{*}{**Notes**} \\ \hline
1 & 2023.1.8T1:30:15 & 2.20 \(\times\) 10\({}^{2}\) & 2.32 \(\times\) 10\({}^{2}\) & 2.35 \(\times\) 10\({}^{1}\) & \\
2 & 2023.1.8T1:31:16 & 3.82 \(\times\) 10\({}^{3}\) & 3.98 \(\times\) 10\({}^{4}\) & 4.00 \(\times\) 10\({}^{3}\) & Coal mine \\
3 & 2023.1.8T1:32:35 & 2.53 \(\times\) 10\({}^{2}\) & 2.64 \(\times\) 10\({}^{1}\) & 2.67 \(\times\) 10\({}^{2}\) & microseismic \\
4 & 2023.1.8T1:33:26 & 4.56 \(\times\) 10\({}^{5}\) & 7.34 \(\times\) 10\({}^{4}\) & 7.37 \(\times\) 10\({}^{5}\) & impact event \\
5 & 2023.1.8T1:34:54 & 6.46 \(\times\) 10\({}^{6}\) & 5.23 \(\times\) 10\({}^{1}\) & 5.46 \(\times\) 10\({}^{3}\) & \\
6 & 2023.1.8T1:35:12 & 4.23 \(\times\) 10\({}^{3}\) & 4.45 \(\times\) 10\({}^{3}\) & 4.47 \(\times\) 10\({}^{6}\) & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Microseismic data before and after accident impact. Figure 3: Different methods of receiving coal mine microseismic levels. of knocking on the pipe and the anchor bolt; comprehensively, compared with the other three forms, the rapping on the pipeline has a better overall clarity level and attenuation degree, so the method in this paper has the best detection effect on coal mine microseisms by rapping on the pipeline. The experiment took 9 coal mine operation points in the working face of the mining area of the group as the experimental object and conducted five pipe taps on the 9 operation points to simulate the microseism situation. Using the missed detection rate of the microseismic samples and the misjudgment rate generated during detection as reference standards, the calculation formula for this indicator is:  
\[\partial=\frac{\tau_{0}}{\iota}\times 100\% \tag{16}\]  
\[\Phi=\frac{\iota_{\Phi}}{\iota}\times 100\% \tag{17}\]  
where \(\partial\) represents the missed detection rate of the sample, \(\tau_{0}\) represents the total amount of missed samples, \(\tau\) represents the total amount of samples, \(\Phi\) represents the misjudgment rate, and \(\iota_{\Phi}\) represents the total amount of misjudged samples. Calculate the missed detection rate and misjudgment rate of the sample based on the above formula. Set the missed detection rate not to exceed 6% and the misjudgment rate not to exceed 5% as the normal detection state; otherwise, it will be judged as a fault state. Test the stability of the group's original coal mine microseism detection system and the method in this paper when detecting coal mine microseisms. The specific experimental results are shown in Figure 4.  
Figure 4: Misdetection rate and misjudgment rate of microseism detection in coal mines. (**a**) Misdetection in coal mine microseism detection. (**b**) Misdetection rate in coal mine microseism detection. As can be seen from Figure 4a, compared with the standard value, the leakage rate of the original detection method of the group when detecting the nine coal mine operation points exceeded the standard value; at the same time, it can be seen from Figure 4b that, when the original detection method detected Operation Points 2, 3, 5, and 7, the detection error rate exceeds the standard value.