Microseismic Response Characteristics Induced by Mining Activities: A Case Study

For deep coal mines, geological disturbances or mining activities can cause damage to coal and rock masses, easily inducing dynamic disasters such as rock bursts or coal and gas outbursts, which seriously threaten the safety production of coal mine. In this paper, first, the Liyazhuang Coal Mine introduced the SOS MS (Sensor Observation Service Microseismic) monitoring system from the Polish Research Institute and verified the accuracy of its positioning. ,en, to study the characteristics of MS signals induced by different mining activities, based on the field monitoring results, the waveform and frequency spectrum characteristics of MS signals at different energy levels induced by different mining activities are analyzed, and the energy levels of MS signals caused by different mining activities are classified. Studies have shown that there are large differences in the waveform and spectral characteristics of MS signals at different energy levels. High-level energy seismic signals are characterized by large amplitudes, low frequencies, relatively concentrated distribution, long vibration duration, and slow attenuation. In addition, the relationship between mining activities and MS events is also statistically analyzed based on the spatial and temporal distribution of MS events with the advancement of working face, and the results show that the increase of vibration frequency and energy can be precursor information for roof pressure. With the advance of the working face, the MS energy has the characteristic of periodic distribution, which is consistent with the periodic weighting revealed by the working resistance of the support. ,is study provides a reference for further revealing the energy release mechanism of rock burst.


Introduction
With the increase of mining depth, the occurrence conditions of coal seams are more and more complex. e frequency and damage degree of dynamic disasters such as rock burst and coal and gas outburst are increasing day by day [1][2][3]. us, there is an urgent need to develop new technologies and equipment to monitor coal and rock stability in real time. Under the action of ground stress, the formation and expansion of cracks in rock or coal body are accompanied by a large number of MS events. During crack initiation, propagation, and coalescence, the energy accumulated in the rock is dissipated in the elastic waveform, of which the signals can be captured by the MS monitoring system [4]. To reveal the evolution law of MS activity in the process of rock fracture, the frequency spectrum of MS waveform was used to evaluate the danger intensity of rock fracture [5,6]. Based on the analysis of field data, Zhang et al. [7] found that the minimum and maximum values of main frequency of MS events in heading face are 14 Hz and 515 Hz, and the maximum event duration is 1.78 s. Experimental results regarding the microseism signal time-frequency characteristics in the process of fault stick-slip instability indicate that the frequency band of the MS signal before the fault stick-slip is 0∼100 Hz, and the main frequency is within 10 Hz [8]. e study on the typical intensive rock burst cases under different excavation methods, tunnel boring machine (TBM), and drilling and blasting method (D&B) in deep marble tunnels of Jinping II hydropower station demonstrates that the single day lowest MS main frequency of both TBM and D&B is less than 200 Hz during the intensive rock burst development [9]. Wang and Zong [10] applied HHT method to analyze the vibration signals of deep-hole large-charge blasting. e results indicated that the vibration duration of blasting is about 150 ms, and the vibration energy is mainly concentrated in the frequency of 17.75 Hz. Li et al. [11] pointed out that the coal mining MS signals have lower dominant frequency (below 80 Hz) and longer vibration duration (more than 2 s) than the blasting signals (dominant frequency above 80 Hz and duration less than 2 s). And the following peak envelope curves of the two types of signals fit a power function. e VMD decomposition method is utilized by Zhang et al. [12] to analyze coalrock fracturing and blasting vibration signals. e results show that the energy of the rock fracturing signals is mainly concentrated in the low-frequency modes, whereas the energy of the blasting vibration signals is mainly concentrated in the three high-frequency modes. e main frequency of microseismic signals during coal outflow, blasting, and coal wall collapse is 0.80, 0.50, and 1.00 kHz, respectively. e lower frequency part of microseismic signals is mainly contributed by the impact failure, and the higher frequency part is mainly contributed by the coal body caving; additionally, the greater the impact failure, the lower the low-frequency bound of its signal [13]. Scholars have analyzed the frequency spectrum characteristics of a large number of MS events caused by different mining activities and taken their variation laws as the precursor information to predict the occurrence of rock burst [14][15][16]. Field test results from 8935 working face in Xinzhouyao Coal Mine show that the main frequency spectrum of MS signals before the rock burst is mainly concentrated in 5-60 Hz, and the sharp decrease of the main frequency and the obvious increase of the amplitude of MS signals can be considered as one of the precursors characteristics of rock burst [17]. e S transform (ST) time-frequency analysis technique is introduced to MS signal analysis field by Jiang et al. [18], and the rock failure scale can be investigated based on the frequency characteristic of MS signal. e MS signal transforms from high frequency to low frequency before the obvious rock deformation. us, the frequency decrease of MS signal can be regarded as the precursory information of macroscopic deformation of rock mass.
Most of previous research mainly focuses on the distribution of main frequencies of MS signals induced by rock deformation. However, there has been a relative lack of research on the characteristics of MS signals generated by different disturbances with different energy levels. e relationship between energy levels and spectral characteristics of MS signals caused by different mining activities is also fuzzy. Taking the island working face of Liyazhuang Coal Mine (Shanxi Province, China) as the research object, a SOS MS monitoring system was established. Based on the realtime monitoring data of MS activities in the deep rock masses during the mining, this study explored the waveform and spectrum characteristics of MS signal generated by different disturbances with different energy levels. And the MS response characteristics during different mining activities were also studied. And the flowchart of this study is shown in Figure 1.

Engineering Background
Liyazhuang Coal Mine is the second large-scale mine with design production capacity of 1.5 Mt./a coconstructed by China and Romania in Huozhou mining area (north area). e mine is located in Shizhuang District, Huozhou City, Shanxi province, 10 km away from southwest of Huozhou City (see Figure 2). It has mining area of 30.415 km 2 , geological reserves of 2.4114 billion tons, and recoverable reserves of 2.1064 billion tons. ere are 5 layers of mineable coal seam, and among them 2# coal seam is the current mining coal seam with average thickness of 3.16 m. Because the average dip angle of coal seam is 6°, the inclined-vertical shaft development is used. e II228 working face being prepared is the isolated island working face with two completely mined out sections at the upper and lower sides, located in panel 2 of 2# coal seam with elevation of +355 m. e advance length and width of II228 working face are 630 m and 130 m, respectively. e dip angle of coal seam is 4 to 10°, average 6°. e thickness of coal seam is 2.82 m to 3.45 m, average 2.67 m. Meanwhile, as a complex structural coal seam, it generally contains 2 layers of gangue, mainly mudstone and carbonaceous mudstone.
After entering the deep part of the panel II, influenced by the hilly terrain, the mining depth reaches more than 600 m, leading to the large deformation of the roadway, serious floor heave, and frequent coal burst. e II228 working face currently being prepared is the isolated island working face, where the adjacent two sections have been mined out in the upper and lower sides (see Figure 3). It is noted that Figure 3 is a simplified excavation engineering plan of Liyazhuang coal mine, in which some roadways are not drawn, aiming to illustrate the current state and layout of the II228 working face. Affected by factors such as plateau rock stress, mining stress, and gas accumulation, etc., during the driving period, the coal burst occurred frequently, and the drills were frequently ejected or grabbed when drilling, as well as the phenomenon of borehole spraying, which poses serious threat to the underground safety production. According to the analysis of current mining technical conditions, there are multiple factors that may cause the aforementioned dynamic danger phenomena, including the energy accumulated in the coal seam due to high in situ stress, the large elastic energy accumulated in the hard roof of multiple layers, and the accumulated gas internal energy, etc. erefore, the real-time Polish SOS MS monitoring system is introduced to determine and identify the energy source (hazard source) of the dynamic phenomenon based on the acquired MS signals and further formulate corresponding prediction and prevention methods to guarantee the safe production, meanwhile, providing useful guidance for other panels or mining areas with similar mining conditions.

Establishment of the Polish SOS MS
Monitoring System at Liyazhuang Coal Mine rough the underground cables, the underground acquired signals will be transmitted to the DLM-SO signals acquisition station, of which the function is to rectify and filter the signals; besides, the DLM-SO acquisition station also powers to the geophone. Generally, a set of DLM-SO acquisition station works in conjunction with 16 DLM-2001 geophone sensors that isolate intrinsically safe signals from nonintrinsically safe signals. e current modulated signals in the measuring probe are transmitted through the underground cables into the acquisition station.

Advances in Civil Engineering
In the acquisition station, the signals are accurately reproduced and converted into corresponding voltage signals. e distance between each acquisition station and geophone probe would not exceed 10 km. e AS-1 Seismogram signals recorder is designed based on the IBM PC computer embedded A/D conversion card with 32 channels. Its main function is to convert seismic signals into digital signals. e software of this system is mainly divided into two parts, namely, Multilok and Seismogram. Multilok is mainly used to complete the three-dimensional position and relevant parameters calculation of the rock vibration source. And Seismogram is used to extract, visualize, and analyze useful MS signals and isolate and screen the wave groups, etc.
SOS MS system can continuously and automatically collect and filter shock signal and accurately calculate the occurrence time, energy, and space three-dimensional coordinates of shock event (>100 J). Its maximum sampling rate is 2500 Hz. e frequency bandwidth of MS signals that can be monitored by this system is 1-600 Hz.

Basic eory of MS Location.
Effectively and accurately detecting and locating the MS events, which contain a large amount of information about rock and coal fracture, is of important significance to detect potential dangers and further mitigate hazards [19]. In terms of the range and scale of coal mine field, the P-wave is often chosen for locating the MS events because of its advantages of high accuracy. e positioning principle of the MS monitoring system is to use the time difference of the P-wave under a specific wave velocity field to determine the rock failure point and further perform two-dimensional or three-dimensional MS source location. Besides, the energy released in the duration of the MS can be also calculated. In practical application, it is often assumed that the coal body is homogeneous and isotropic.
at is, the velocity of P-wave in each direction is a constant. us, for homogeneous and isotropic velocity models, the time from the MS source H � (X 0 , Y 0 , Z 0 ) T to the sensor i can be calculated: where X � (x i , y i , z i ) is the coordinate of the sensor i; t 0 is the time when the MS occurs; t i is the time when the P-wave reaches the sensor i; V P is the velocity of P-wave; i � 1, 2, . . ., n, n is the number of sensors installed. From the above formula, it can be seen that at least four sensors are needed providing enough data to solve the equation.

Sensors Layout and Installation.
e II228 working face in panel 2 is the key area for rock burst prevention and control, and it is also the important area for MS monitoring, which can provide useful information for rock burst prediction. Besides, the panel 2 in coal seam 2# has the risk of rock burst, so the monitoring stations should be arranged as close as possible to this area, and sufficient distribution density should be satisfied. us, based on the MS location  theory and MS monitoring principle [20,21], 11 sensors were designed to install around the II228 working face, and the detailed coordinates for the 11 MS sensors are listed in Table 1.
e map of the network topology of the MS monitoring system is shown in Figure 3. And the system diagram is shown in Figure 4.
Depending on the MS sensor used, the detector probe can be installed vertically on the drilling bolt with a depth of more than 1 m and an error of 10 degrees (the probe is fixed to the M2O-bolt thread). To ensure the good operation of MS sensors, the transmission lines of MS network should be well and tightly connected. erefore, under the condition that the positive and negative electrodes are correct, the probe output cable should be connected through the specially made explosion-proof sleeve or junction box. e schematic of MS sensors installation can be seen in Figure 5.

e Verification of Location Accuracy of Monitoring
System. e location accuracy of MS monitoring system is the foundation of the prevention and early warning of rock burst.
us, the precision of source positioning must be validated after installation of the MS monitoring system. A common approach is to compare positioning results with actual locations of blasting activities, which provide a useful assessment on the validity of sensor's spatial distribution and performance of the entire system. To ensure the calculation accuracy of the position and source parameters of MS events, we also performed a location accuracy test of the MS events. eir places in panel 2 were chosen as the blasting positions. e coordinates of the blasting points determined through three artificial explosions at 3 positions showed a maximum error of 5.93 m and a minimum error of 1.85 m against the actual points, which meets the requirement for studying MS activities in the field monitoring. e reliability of the equipment is verified through this test. On the other hand, the rationality of sensors layout is also validated. e detailed data of blasting location and estimated locations are listed in Table 2.

e Spectrum Characteristics of MS Signals of Mining Tremor with Different Energy Levels in Liyazhuang Coal Mine.
Under the effect of external disturbances, dynamic failures would occur in the rock mass. In the process of rock failure, detectable acoustic and seismic signals would be produced, accompanied by the release of energy which can be monitored by the MS monitoring system. Due to the different failure mechanism of rock and coal, the monitored energy is in different magnitudes [22,23]. According to the focal mechanisms of mine tremors, the characteristics of MS signals produced by various types of seismic sources are different, including energy, frequency spectrum, etc. [24,25]. Previous studies have shown that there may be a relation between the MS energy and spectrum [26]. us, it is necessary to analyze the waveform and spectrum characteristics of MS signals with different energy levels and further provide the theoretical basis for identifying the types of mining-induced disturbances. It is also of important significance to take corresponding preventive measures for the occurrence of the rock burst or other dynamic disasters induced by different mining disturbances.
is section mainly aims at analyzing the spectrum characteristics of MS signals with different energy levels monitored and recorded in Liyazhuang Coal Mine. e energy of MS events recorded by the MS monitoring system in Liyazhuang Coal Mine was mainly concentrated between 10 2 and 10 5 J. Figure 6 shows the waveform and spectrum variation characteristics of MS events with energy greater than 10 4 J. From Figures 6(a) and 6(c), it can be seen that the amplitudes (vibration velocity) of MS signals mainly concentrate in (0.6-6.5) × 10 −4 m/s. e signal attenuation is fast, lasting from 800 ms to 1000 ms. Meanwhile, it also can be known that the MS signals monitored by sensors with different distances from the same vibration source have similar amplitudes. However, the closer the vibration source is, the longer the MS signals received by the sensor will last. From Figure 6(b), it can be seen that the main frequency is about 50 Hz and most of the amplitude is concentrated in the frequency bands between 25 Hz and 100 Hz, while from Figure 6(b), it can be known that the main frequency is about 60 Hz and most of the amplitude is concentrated in the frequency bands between 36 Hz and 90 Hz.
ey have similar characteristics of main frequency distributions. However, the closer the vibration source, the larger the amplitude spectrum of the signals. Generally, the seismic wave continuously attenuates along the rock medium, so that the MS signals monitored by the station closer to the vibration source may have more useful information. Figure 7 shows the waveform and spectrum variation characteristics of MS events with energy of 1050.7183 J. It can be seen that the amplitudes (vibration velocity) of MS signals mainly concentrate in (0.2-5) × 10 −4 m/s, and the MS signals last about 600 ms. In terms of the spectrum, the frequency band of the signal is 0-160 Hz. Besides, the main frequency bands range is about 10-75 Hz and most amplitude concentrates on the frequency bands of 10-50 Hz. Generally, the MS signals with such waveform characteristics and vibration energy of about 10 3 J are generated by the underground artificial blasting. Figure 8 shows the waveform and spectrum variation characteristics of MS events with energy of 871.7724 J. Obviously, the amplitudes (vibration velocity) of MS signals mainly concentrate in (0.2-0.6) × 10 −4 m/s, and the MS signals last about 550-750 ms. And the frequency band of the signal is 0-120 Hz, while the main frequency bands range is about 15-80 Hz.
As shown in Table 3, it can be concluded that the higher the vibration energy is, the longer the corresponding MS signals would last, and the larger the amplitude (vibration velocity) is. In addition, for the MS signals with high energy levels, the frequency is wide, but the main frequency band is narrow but centralized. Generally, the MS signals generated by strong vibration are characterized by large amplitude and low frequency, while the signals of vibration with low energy level have the characteristic of wide main frequency band. In most practical cases, the magnitude and the energy concentration degree of MS events were identified as the criteria Advances in Civil Engineering for rock burst hazards [27]. Generally, the minimum energy at which the rock burst occurs is 10 3 J, and most rock bursts start from 10 5 J. e area where the MS events with the energy magnitude of 10 5 or above frequently occur can be considered as the high-risk area [28][29][30].

e Spectrum Characteristics of MS Signals Induced by
Typical Underground Disturbances. Mining activity and tectonic activity are known to pose external disturbances on the rock and coal mass, resulting in the damage of the rock and coal mass. Under different disturbances, the MS signals generated by the rock and coal failure have different characteristics due to the different failure mechanics of rock and coal mass [31][32][33][34]. erefore, it is of practical significance to identify different focal sources and further make corresponding preventive measures by analyzing the waveform and spectrum characteristics of MS signals generated under different disturbance conditions.

Advances in Civil Engineering
By MS monitoring and analysis, in the advancement of working face, several typical shock events (Figure 3) occurred around the II228 working face. Figure 9 shows the waveforms of typical seismic signals and Figure 10 shows the corresponding curves of amplitude spectrum-frequency.
On May 5, 2011, a vibration was detected at the rear of 226 working face at 6:53:10 ( Figure 3). According to the analysis of SEISGR and Multilok software, the geographical coordinates of the shock event were (37569200.00, 4057027.00, −220.14), and the vibration energy was 1.78 × 10 3 J. And the vibration waveform was generated by the immediate roof falling in the gob (Figure 9(a)). From Figure 10 Figure 3). According to the analysis of SEISGR and Multilok software, the geographical coordinates of the shock event were (37569035.71, 4056781.66, −232.14), and the vibration energy was 2.72 × 10 4 J. And the vibration waveform was a typical waveform of main roof rupturing (Figure 9(b)). From Figure 10    areas have recorded the vibration information, indicating that the vibration energy is really large. According to the analysis of SEISGR and Multilok software, the geographical coordinates of the shock event were (37568889.84, 4057308.61, −217.87), and the vibration energy was 2.78 × 10 5 J. Figure 9(c) shows the waveform of this vibration. And the corresponding frequency spectrum is obtained by using the fast Fourier transform method, as shown in Figure 10(c). Obviously, the main frequency bands range is about 0-120 Hz and the maximum energy concentrates on the frequency bands of 35-55 Hz. On May 15, 2011, a mine seismicity with high energy occurred near the cut-off of the II228 working face at 22: 14:20 ( Figure 3). According to the analysis of SEISGR and Multilok software, the geographical coordinates of the shock event were (37568718.80, 4057133.48, −240.56), and the vibration energy was 1.38 × 10 4 J. From the location and the vertical elevation of the epicenter source, the vibration was caused by the roof fracturing due to the high stress superimposing at the II228 cut-off. e vibration waveform was shown in Figure 9(d). After waveform attenuation, there are still large fluctuations in the tail, which is obviously different from roof fracturing in the gob and artificial blasting. From Figure 10(d), the main frequency bands range is about 0-160 Hz and the maximum energy concentrates on the frequency bands of 40-80 Hz. Besides, the spectrum is relatively scattered. Although the amplitude and frequency of the wave caused by the vibration were relatively large, there was no rock burst occurring. is is because the vibration energy did not reach the average energy level required for the occurrence of rock burst under normal conditions; on the other hand, the location of the seismic source was deep, so the energy is attenuated to some extent during the propagation process.
On June 10, 2011, a vibration was detected at the NO.3 high-level drilling site near the II228 working face at 00:26: 52 ( Figure 3). According to the analysis of SEISGR and Multilok software, the geographical coordinates of the shock event were (37568545.00, 4056767.00, −224.06), and the vibration energy was 1.2 × 10 3 J. e vibration waveform was typical artificial blasting (Figure 9(e)), and the vibration information was recorded by 4 sensors arranged at II228 working face. Figure 10(e) shows the variation characteristics of corresponding frequency spectrum. It was found that the main frequency bands range is about 0-60 Hz and the maximum energy concentrates on the frequency bands of 0-10 Hz. From above analysis, it also can be found that the vibration waveform caused by main roof fracturing is similar to that of the immediate roof fracturing, but their spectrum is different. e main frequency of the waveform generated by the main roof fracturing is lower than that of the immediate roof fracturing, and the energy generated by the former is generally much higher than that of the latter. e energy released by roof fracturing is basically the same as that of artificial blasting, but the waveform is obviously different. Besides, the frequency bands which the maximum energy concentrate on are also different.

MS Response Characteristics during Mining Activities and
Roof Weighting

Variation of MS Events in the Normal Production
Process. Generally, underground vibration caused by mining activities can be roughly divided into two categories. One type is directly caused by mining activities, including locomotive operation, loading loaders operation, artificial blasting, etc. e other is caused by the instability failure of surrounding rock due to mining activities. e SOS MS monitoring system can monitor, record, and preserve various vibration signals in real time, so as to locate the vibration source and calculate the magnitude of vibration energy.
(1) Temporal Distribution of MS Events. Figure 11 shows the variation of MS events near II226 working face in different periods of a day. More MS events occur in the period of normal production, while relatively less MS events occur in the period of handover and overhaul. Although the production time of Liyazhuang Coal Mine is not the same every day, in statistics, the frequency of MS events occurring near the working face in the period of normal production is twice that of the inspection time. For instance, during the shift period (14:00-16:00), as the mining activities reduce, the frequency of MS events is correspondingly reduced to a minimum. And after shift period (16:00-18:00), as mining activity increases, the frequency of MS events is also increased. us, it can be concluded that there exists a good correspondence between the frequency variation of MS events and mining activities, which validates the reliability of the SOS MS monitoring system from another prospective. Meanwhile, it also can be found that the MS events will not disappear immediately after stopping mining activities at working face, indicating that it would take some time for the surrounding rock to return to stability after the stopping of mining disturbance.
(2) Spatial Distribution of MS Events. Figure 12 shows the distribution of the MS events in daily production. e MS events are mainly concentrated in two zones: the first MS events concentration zone lies close to the II228 working face. In this zone, most MS events with high energy were mainly caused by the roof separation in front of the working face and roof fracturing and caving behind the working face. e second MS events concentration zone is the high-level drilling site, where most MS events were mainly generated by the artificial blasting. In this zone, a high-level drainage roadway was being excavated. us, artificial blasting was carried out every day. On the other hand, the release of internal elasticity of rock strata due to the change of in situ stress caused by excavation may produce more MS events. In addition, it can be easily found that, with the advancement of II228 working face, the location of MS events also changed. Generally, the distribution of MS events is affected by mining activities, both spatially and temporally. e energy of these vibrations is generally below 10 3 J, which has no great influence on the occurrence of dynamic disasters.

Relationship between MS Events and Periodic
Weighting of Working Face. To study the periodic weighting in the II226 working face, the real-time monitoring of hydraulic support working resistance was applied in the field. e measurement stations were arranged along the direction of working face. In the process of periodic pressure analysis, the sum of the average end-cycle resistance of the hydraulic support and its mean variance is taken as the main index to judge the periodic pressure. It can be calculated as where σ P is the mean variance of the average end-cycle support resistance; n is the number of cycles; P ti is the endcycle support resistance in the ith cycle; P t is the average value of the end-cycle support resistance. e criterion for the roof weighting can be expressed as After calculation, the weighting criterion of each support is shown in Table 4. Figure 13 shows the variation characteristics of periodic end-cycle support resistance of each support. e red lines indicate the weighting criterion, and the green lines indicate the weighting position. Table 5 shows the statistics of periodic weighting time of each support in June, and Figure 14 shows the daily number and energy of MS events before and after three periodic weighting times in June. e column represents the daily total energy and the red line represents the daily numbers of MS events. e three times of periodic weighting of II226 working face were on June 5, 13, and 23, respectively. From Figures 13 and 14, with the breakage occurring in the main roof, the hydraulic support pressure increases periodically in the time of roof weighting. Two days before the period weighting, the daily average number of monitored vibrations was about 11 times, and the number of vibrations showed an increasing trend; the total energy of daily monitored vibrations was about 4500 J, of which the daily maximum vibration energy was 1800 J, and the overall vibration energy also showed an increasing trend. is increase of vibration 12 Advances in Civil Engineering    frequency and energy can be precursor information for roof pressure. With the advancement of the working face, the MS energy has the characteristic of periodic distribution, which is consistent with the periodic weighting revealed by the working resistance of the support.

Discussion
In the process of fracturing and sliding of coal and rock under the mining disturbances, microseismic waves with a certain frequency will propagate to the surrounding rock, which is also accompanied by the release of accumulated energy. e amplitude and frequency of the waves depend on the strength, stress state, fracture size, and the deformation speed of coal and rock [35]. e incubation process of rock burst is actually the process of the occurrence and expansion of cracks or secondary cracks in coal and rock mass structure, which is the process of energy accumulation. And the occurrence of rock burst is the fracture and instability process of damage rock structure, which is the process of energy release [36]. e vibration energy of the roof pressure signals is large, and the amplitude of the signal is about 10 4 , which is due to the large deformation and failure area in the rock mass during the roof rupturing, and a large amount of elastic energy is released. Actually, for the process of fault activation, the initial instability of surrounding rock compaction fault is the initial stage of fault activation, and the single vibration energy generated is large, but the frequency is low. en, the elastic stick-slip oscillation process of surrounding rock is the most important stage of the release of fault activation energy, and the vibration frequency is high. And the vibration frequency and energy are low in the process of plastic stick-slip failure. With the vibration energy and frequency of the surrounding rock in the stage of restabilization of the failure of the wall rock, the release of energy is large [37]. It can be seen that the analysis results of this paper are consistent with previous studies. Besides, the energy accumulated in coal and rock mass increases gradually, and the energy is in a stable release state. When the propulsion speed reaches a certain degree, this stable state will be destroyed, and the sudden release of energy will lead to the occurrence of large energy events.
us, the distribution characteristic of MS energy and events can reflect the roof movement.

Conclusion
(1) ere are large differences in the waveform and spectral characteristics of MS signals at different energy levels. High-level energy seismic signals are characterized by large amplitudes, low frequencies, relatively concentrated distribution, long vibration duration, and slow attenuation. As the energy decreases, the vibration attenuation rate gradually becomes faster, and the signal duration becomes shorter. Besides, the dominant frequency gradually develops from concentration to diffusion. (2) Due to the different fracture mechanisms of rock or coal mass, the different types of vibration induced by underground mining activities are different. ere is a strong impact risk during fault activation because of its more released energy. In comparison, less energy would be released during roof falling.
(3) With the advancement of the working face, the MS energy has the characteristic of periodic distribution, which is consistent with the periodic weighting revealed by the working resistance of the support. 1-2 days before the periodic weighting of working face, the MS events would increase. Combined with the real-time monitoring of hydraulic support, these MS characteristics can be regarded as precursory information of periodic weighting.
Data Availability e data reported in this article are available from the corresponding author upon request.

Disclosure
Meanwhile, the sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; and in the decision to publish the results.

Conflicts of Interest
e authors declare no conflicts of interest, and the manuscript is approved by all authors for publication.  16 Advances in Civil Engineering