TY - JOUR
AU - Wang, Chen
AB - Abstract There are extensive studies on electromagnetic radiation (EMR) effects during coal and rock deformation and fracturing processes, but few systematic studies on the EMR features of gas-bearing coal under impact failure circumstances. In order to investigate whether the EMR is affected by the gas (CO2,CH4,N2) sorption, coal type and impact energy, we performed a series of impact loading tests on both briquette coal specimens (BCSs) and raw coal specimens (RCSs) at various pore pressures (0–1.5 MPa). We developed a drop hammer test apparatus to allow impact loading tests on gas-bearing coal, and recorded the EMR signal of the damage of coal simultaneously. The result showed that (i) the amplitude range of the EMR signal generated by the impact damage of the gas-bearing coal is approximately 10–600 mV, with an effective duration time of 3–1500 ms and accumulated energy of 0.1–1000 μJ; (ii) when pore pressure is increased, the maximum amplitude, duration and pulse counts of the EMR decrease accordingly; (iii) the coal powder size and impact energy affect damage features and EMR characteristics, where a higher impact impulse causes more severe damage to coal specimens and (iv) the influence of the presence of adsorptive gas on the EMR signal caused by the destruction of coal bodies has both enhancement and reduction effects. During the early warning assessment of coal and gas outbursts using EMR parameters, not all the waveform parameters are sensitive to coal mine methane, but the significant effect of methane on signal volatility should be considered. coal and gas outburst, gas-bearing coal, drop hammer method, impact failure, electromagnetic radiation signal 1. Introduction Coal and gas outbursts are harmful dynamic phenomena encountered in the production of underground coal mines (Tu et al. 2016). During the mining process, a large amount of coal and gas erupts from the coal seam within a very short period, greatly damaging the roadway and facilities, leading to significant economic losses and personal casualties (Beamish & Crosdale 1998; Guan et al. 2009). To date, there have been more than 600 outburst mines distributed in over 20 cities and provinces in China, and more than 4000 people have lost their lives in outburst disasters since the 1990s (Jin et al. 2018). With the increase in mining depth and intensity, outburst phenomena have become more severe (He & Song 2012). Preventing coal and gas outbursts is becoming a necessary prerequisite to ensure coal mine safety and improve economics (He et al. 2018). As conventional outburst prediction technologies and indicators poorly predict the danger and evolution process of outbursts in a timely and accurate manner, it is essential to develop a new robust and accurate prediction method. Currently, there are two main types of method used to predict coal outbursts: traditional contact methods and noncontact geophysical methods. In conventional methods, boreholes are made in the hazard-prone area of the coal seam. Then, basic parameters such as the rate of ‘drilled coal gas’ and the maximum volume of ‘drilled coal rubble’ are measured to evaluate the integrated risk of outbursts (Zhao et al. 2016). However, these parameters can only reflect the spatiotemporal degree of hazard at the location of the borehole and around drilling work. Additionally, as the drilling process usually interrupts production, it leads to time, economic and labor losses. Noncontact geophysical methods mainly include acoustic emission (AE), micro-seismic (MS) and electromagnetic radiation (EMR) techniques (Qiu et al. 2017; Shen et al. 2018; 2019a). AE, MS and EMR effects can reflect the stress state or energy dissipation features of the coal seam and its surrounding rocks in the development of outbursts. These noncontact methods can save both time and labor, and provide reasonably accurate and continuous monitoring results with a series of established data acquisition systems. For current coal mine production, the latest development trend is to use these effects mentioned to judge the outburst risk comprehensively. Many experiments have shown that the coupling process of methane gas and coal is a complex mechanical action: adsorbed-gas-induced swelling and erosion, pore/fracture-induced damage and failure will finally cause a change in the coal skeleton and its mechanic properties (Xie et al. 2018; Shen et al. 2019a). Large numbers of studies have been carried out to determine the relevant mechanisms and affecting factors (Wold et al. 2008; Skoczylas et al. 2014; Wen et al.2016; Fan et al. 2017; Shen et al. 2019b), and results have shown that outburst accidents usually occur in soft coal seams containing a high level of methane gas (Evans et al. 1984; Sobczyk 2014; Guo et al. 2016). The presence of methane gas was proved to affect the mechanical properties of coal and affect the emergence and development of outburst accidents (Geng et al. 2017). Peng et al. (2012) determined that the methane stored in a coal seam was the primary energy source for outbursts, which included throwing and grinding of coal. Therefore, it is vital to study the dynamic characteristics of gas-bearing or gas-containing coal, which is coal under conditions that allow it to adsorb a certain amount of methane. In the early stages of studying gas-bearing coal, most studies focused on the effect of methane on the mechanical properties of coal, such as coal intensity and creep behavior, and the corresponding constitutive models (Wang et al. 2017). Li et al. (2017) demonstrated that methane gas reduces the changes in coal creep properties. Although the EMR effects during the coal and rock deformation and fracturing process have been extensively studied experimentally, few systematic studies have been performed on the EMR features of gas-bearing coal under impact failure circumstances. He & Liu (1995) proved that EMR was generated in gas-bearing coal deformation and fracturing progress. Pores containing methane affect the generation of EMR, and they deemed that the combined action of a transient electric dipole, the variable rate motion of the separated charges along the fracture edge and the expansion and relaxation of separated charges contribute to the production of EMR. Due to the lack of an apparatus with which to implement impact loading on gas-bearing coal, few studies have investigated the dynamic features of gas-bearing coal and its EMR signal characteristics (He et al. 2012). In this study, we introduce a series of self-developed apparatuses to realise impact loading on gas-bearing coal with consideration of the influence of impact energy, impact velocity and pore pressure. Also, the law of energy accumulation during the crushing of gas-bearing coal under impact loads is analysed with the changes in EMR characteristics, such as signal intensity, pulse count, signal duration and spectrum characteristics. The research provides the theoretical foundation for analysing the rapid destruction features of underground coal seams with adsorbed methane gas and the application of EMR technology to realise accurate early warning systems of outbursts. 2. Experimental investigation 2.1. Test setup and instrumentation A self-developed drop hammer impact loading experimental system is introduced to conduct impact loading tests. The schematic of the entire experimental system is shown in figure 1. The experimental system mainly includes a drop hammer impact loading system, gas pressure control system, temperature control system, impact velocity test system, dynamic and static data acquisition system, EMR testing system, shielding system and protection system. Figure 1. Open in new tabDownload slide Schematic of the experimental setup for impact loading on gas-bearing coal. The drop hammer system is composed of a bottom gas-sealed cabin and a drop hammer device at the top. The specimen cabin is sealed with a specially made toughened glass. A series of preliminary experiments are conducted before the actual test, and toughened glass is tested for three different thicknesses (5, 8 and 10 mm). It has been found that 5-mm thickness can simultaneously meet the requirements of sealing 2 MPa gas pressure and ensure minimal impact energy loss while maintaining safe operation. Then, the two sides of the cabin are sealed with acrylic plexiglass to ensure that the EMR signal is transmitted from the cabin. The drop hammer device mainly includes drop hammers and four plug-in drop hammer barrels, each with a length of 0.5 m without including the connecting portion. Thus, the drop hammer system can provide different falling heights and hammer weights, with a maximum loading height of 2 m and a maximum loading weight of 9 kg. The gas pressure control system is comprised of a high-pressure tank, reference tank, vacuum pump, pressure transducer and pipelines and valves. The system can pressurise the gas in the sealed cabin and provide pore pressure conditions up to 2 MPa. The temperature control system mainly includes electric heating tape, a temperature monitor and a laboratory air conditioner. During the test, the temperature of the gas-sealed cabin is maintained with electric heating tape. At the same time, the whole system is exposed to ambient air with temperature control by an air conditioner at a fixed temperature of 20°C. The dynamic and static data acquisition system (DAQ) mainly includes the AFT-CM-32 strain data collector and HIOKI 8860–50 data acquisition system. The HIOKI 8860–50 apparatus provides both static and dynamic data acquisition functions, and it is used to record gas pressure and impact velocity data. In addition to the DAQ, the impact velocity test system still includes two laser velocity probes. The velocity of the drop hammer is mainly used to evaluate the impact energy on the specimen. The principle of the velocity test device is shown in figure 2. In addition, a special copper mesh was used for shielding all the possible electromagnetic interferences during the tests. Figure 2. Open in new tabDownload slide Design and calculation principle of the impact velocity measurement system. (a) Combined hammer; (b) laser beam switch; (c) schematic diagram of the impact velocity test system and (d) test signal and speed calculation principle. 2.2. Specimen preparation Coal blocks from three different collieries were collected and prepared into two types of specimens—raw coal specimens (RCSs) and briquette coal specimens (BCSs), shown in figure 3. The RCSs used in the experiment were taken from the No. 21 217 coal mining face of the Dongpang Mine, and the large coal blocks were drilled into ∅50 mm × 75 mm cylinders (number with DYM as a prefix). The remaining coal blocks were pulverised into powders for classification into four different particle sizes (<0.25, 0.25–0.5, 0.5–1.0 and 1.0–1.25 m) using standard sieves. Then, the appropriate amount of coal tar was added into the coal powders and mixed well to make cylindrical BCSs (∅50 mm × 75 mm) with a servo press machine at a fixed molded pressure (of 50–400 MPa). These samples were numbered with DXM as a prefix. The remaining BCSs were made with coal from the Wolonghu Coal Mine (number with WXM as a prefix). The same method was used to make ∅50 mm × 100 mm cylinders. Figure 3. Open in new tabDownload slide Coal specimens used in the tests. (a) BCSs, the DXM samples; (b) BCSs, the WXM samples; (c) RCSs, the DYM samples. 2.3. Test condition and procedure The purpose of the experiments is to investigate to what extent the gas parameters affect the coal strength and damage features under impact loading. Thus, the test variables of drop height, hammer weight, pore pressure, gas type, powder size, molding pressure and specimen type were introduced to analyse their effects on the EMR phenomenon. The details of the experimental arrangement are shown in Table 1. Table 1. Summary of test conditions . Test factors . Test level . Drop height (m) . Hammer weight (kg) . Pore pressure (MPa) . Gas type . Powder size (mm) . Molding pressure (MPa) . Specimen type . 1 2 9 0 N2 <0.25 50 RCS 2 1.5 6 0.3 CH4 0.25–0.5.0 100 BCS 3 1 — 0.7 CO2 0.5–1.0 200 — 4 — — 1.1 — 1.0–1.25 300 — 5 — — 1.5 — — 400 — . Test factors . Test level . Drop height (m) . Hammer weight (kg) . Pore pressure (MPa) . Gas type . Powder size (mm) . Molding pressure (MPa) . Specimen type . 1 2 9 0 N2 <0.25 50 RCS 2 1.5 6 0.3 CH4 0.25–0.5.0 100 BCS 3 1 — 0.7 CO2 0.5–1.0 200 — 4 — — 1.1 — 1.0–1.25 300 — 5 — — 1.5 — — 400 — Open in new tab Table 1. Summary of test conditions . Test factors . Test level . Drop height (m) . Hammer weight (kg) . Pore pressure (MPa) . Gas type . Powder size (mm) . Molding pressure (MPa) . Specimen type . 1 2 9 0 N2 <0.25 50 RCS 2 1.5 6 0.3 CH4 0.25–0.5.0 100 BCS 3 1 — 0.7 CO2 0.5–1.0 200 — 4 — — 1.1 — 1.0–1.25 300 — 5 — — 1.5 — — 400 — . Test factors . Test level . Drop height (m) . Hammer weight (kg) . Pore pressure (MPa) . Gas type . Powder size (mm) . Molding pressure (MPa) . Specimen type . 1 2 9 0 N2 <0.25 50 RCS 2 1.5 6 0.3 CH4 0.25–0.5.0 100 BCS 3 1 — 0.7 CO2 0.5–1.0 200 — 4 — — 1.1 — 1.0–1.25 300 — 5 — — 1.5 — — 400 — Open in new tab During the test, the EMR probes were arranged around the outside of the cabin, and the EMR data acquisition system collects the EMR signals in real-time. The experimental procedures were as follows: The specimen was placed into the cabin, and the cabin was sealed with toughened glass. The data acquisition system was started to record the gas pressure data. The coal specimen and whole system were vacuumed for 8 h to ensure that no air remained inside the cabin. All the pipelines and the sealed tank were continuously isothermally heated to 293 K (=20°C) with heat tape and a continuous air condition system. A high-pressure gas cylinder was used to charge the preset gas into the sealed chamber to the designed gas pressure until it reached the adsorption equilibrium state (CH4 and CO2). For BCSs and RCSs, the adsorption equilibrium time was guaranteed to be no less than 24 and 48 h, respectively. The ZDKT-1 apparatus and the HIOKI 8860–50 storage recorder were started approximately 30 min in advance to ensure that all the equipment was in good working condition. When the preset working condition was reached, the drop hammer was released at the preset height to apply the impact loading on the gas-bearing coal sample; the experimental data were saved and preparations were made for the next test. 3. Test results and data analysis 3.1. Impact crushing effect of the coal samples The destruction of the coal samples and the crushing effects under different impact velocities are shown in figure 4. The impact speed is closely related to the crushing effects. As the velocity increases, the destruction degree of the samples increases significantly. When the impact velocity was relatively low, less than 2.344 m s−1, the coal samples were only slightly damaged, starting with longitudinal splitting at low speed and gradual crushing into coal pieces on a smaller scale. When the impact velocity reached 4.688 m s−1, the coal sample was finally destroyed into powder. As the impact speed depends on the drop height, the higher the drop height, the more the samples became damaged. Figure 4. Open in new tabDownload slide The failure pattern of coal specimens under different impact velocities. 3.2. Denoising and processing of the EMR signals Due to the complexity and uncertainty of the ambient environment, the monitored EMR signals would inevitably undergo interferences. Therefore, the wavelet packet transform and ensemble empirical mode decomposition methods were used to denoise the original signal before analysing the data. The EMR signals of the dynamic damage of both the BCSs and RCSs are shown in figure 5. Figure 5. Open in new tabDownload slide Typical EMR signals recorded during the impact loading of gas-bearing coal. 3.3. Analysis of the EMR signal characteristics To analyse the differences in the signal, four signal waveform parameters are chosen to characterise the EMR signal features: (i) the maximum amplitude, Amax; (ii) the duration, Tdui; (iii) the effective energy of the signal, Eeff and (iv) the pulse count, Npul. The threshold used to identify an actual EMR event is 10 mV. Some of the test results are shown in Table 2. As there are two channels for each EMR event, the average value for each wave parameter was used here. Table 2. Waveform characteristic parameters for the transient EMR signal from the impact destruction of the BCSs Sample ID . Loading height (m) . Loading weight (kg) . Molding pressure (MPa) . Pore pressure (MPa) . Gas type . Amax (mV) . Tdur (ms) . Eeff (μJ) . Npul . DXM01 2 9 55.81 0 — 33.14 232.72 2.16 10 DXM02 2 9 95.86 0 — 79.81 180.18 13.06 6 DXM03 2 9 196.36 0 — 91.07 26.95 5.86 1 DXM04 2 9 276.72 0 — 151.60 559.77 87.94 7 DXM05 2 9 380.72 0 — 110.65 93.85 18.15 5 DYM01 2 9 — 0 — 236.27 1344.53 477.71 7 DYM02 2 9 — 0.3 CH4 255.24 285.84 143.35 9 DYM03 2 9 — 0.7 CH4 110.70 210.06 18.87 3 DYM04 2 9 — 1.1 CH4 66.99 143.75 6.00 8 DYM05 2 9 — 1.5 CH4 33.14 232.72 2.16 10 Sample ID . Loading height (m) . Loading weight (kg) . Molding pressure (MPa) . Pore pressure (MPa) . Gas type . Amax (mV) . Tdur (ms) . Eeff (μJ) . Npul . DXM01 2 9 55.81 0 — 33.14 232.72 2.16 10 DXM02 2 9 95.86 0 — 79.81 180.18 13.06 6 DXM03 2 9 196.36 0 — 91.07 26.95 5.86 1 DXM04 2 9 276.72 0 — 151.60 559.77 87.94 7 DXM05 2 9 380.72 0 — 110.65 93.85 18.15 5 DYM01 2 9 — 0 — 236.27 1344.53 477.71 7 DYM02 2 9 — 0.3 CH4 255.24 285.84 143.35 9 DYM03 2 9 — 0.7 CH4 110.70 210.06 18.87 3 DYM04 2 9 — 1.1 CH4 66.99 143.75 6.00 8 DYM05 2 9 — 1.5 CH4 33.14 232.72 2.16 10 Open in new tab Table 2. Waveform characteristic parameters for the transient EMR signal from the impact destruction of the BCSs Sample ID . Loading height (m) . Loading weight (kg) . Molding pressure (MPa) . Pore pressure (MPa) . Gas type . Amax (mV) . Tdur (ms) . Eeff (μJ) . Npul . DXM01 2 9 55.81 0 — 33.14 232.72 2.16 10 DXM02 2 9 95.86 0 — 79.81 180.18 13.06 6 DXM03 2 9 196.36 0 — 91.07 26.95 5.86 1 DXM04 2 9 276.72 0 — 151.60 559.77 87.94 7 DXM05 2 9 380.72 0 — 110.65 93.85 18.15 5 DYM01 2 9 — 0 — 236.27 1344.53 477.71 7 DYM02 2 9 — 0.3 CH4 255.24 285.84 143.35 9 DYM03 2 9 — 0.7 CH4 110.70 210.06 18.87 3 DYM04 2 9 — 1.1 CH4 66.99 143.75 6.00 8 DYM05 2 9 — 1.5 CH4 33.14 232.72 2.16 10 Sample ID . Loading height (m) . Loading weight (kg) . Molding pressure (MPa) . Pore pressure (MPa) . Gas type . Amax (mV) . Tdur (ms) . Eeff (μJ) . Npul . DXM01 2 9 55.81 0 — 33.14 232.72 2.16 10 DXM02 2 9 95.86 0 — 79.81 180.18 13.06 6 DXM03 2 9 196.36 0 — 91.07 26.95 5.86 1 DXM04 2 9 276.72 0 — 151.60 559.77 87.94 7 DXM05 2 9 380.72 0 — 110.65 93.85 18.15 5 DYM01 2 9 — 0 — 236.27 1344.53 477.71 7 DYM02 2 9 — 0.3 CH4 255.24 285.84 143.35 9 DYM03 2 9 — 0.7 CH4 110.70 210.06 18.87 3 DYM04 2 9 — 1.1 CH4 66.99 143.75 6.00 8 DYM05 2 9 — 1.5 CH4 33.14 232.72 2.16 10 Open in new tab The test results show that both the RCS and BCS damage will release EMR under impact loads. The intensity, duration and signal energy of the EMR signal generated by the destruction of the RCS are higher than those of the BCS, 2.10, 1.70 and 5.01 times higher, respectively. At the same time, their pulse counts are equivalent. Specifically, the intensity (maximum amplitude) of the transient EMR generated by the BCSs is approximately 11.59–523.18 mV, with an average intensity of 71.98 mV, while for the BCSs it falls in the range of 10.94–458.11 mV, with an average intensity of 151.30 mV. The signal duration of the BCSs is 3.71–1185.94 ms, with an average duration of 243.11 ms, and the corresponding duration is 46.29–1445.1 ms for RCSs with an average duration of 412.40 ms. The total energy of the EMR signal for the BCSs is 0.12–749.98 μJ with an average of 27.50 μJ, while it is 1.08–951.19 μJ for the RCSs, with an average of 137.87 μJ. The EMR pulse count during BCS damage is approximately 1–17, 5.10 on average, and the EMR pulse count during RCS damage is 1–12, 5.7 on average. 4. Influence analysis on the EMR characteristics 4.1. Influence of pore pressure and gas type To study the influence of the pore pressure and gas type on the dynamic damage of coal, 15 BCSs were affected under different pore pressures (0, 0.3, 0.7, 1.1, 1.5 MPa) and gas types (N2, CH4, CO2). The test result is shown in figure 6. Figure 6a shows that the EMR intensity (the maximum amplitude) changes when considering different gases. By pressurising adsorbable gases (CO2 and CH4), the EMR signal decreases gradually with increasing pore pressure. The EMR signal generated by the gas-bearing coal decreases in intensity; the higher the gas pressure, the more significant the reduction is. Nevertheless, with non-adsorbable gas (N2), there seems to be no apparent influence on the EMR, as the signal intensity fluctuates obviously with pore pressure change. Additionally, different gases have different degrees of influence on the EMR strength, following the order of CO2 > CH4 > N2. Figure partss 6b–6d demonstrates that the duration and pulse count of the transient EMR signal have a clear downward trend with pore pressure when the charged gas is CO2. However, the signal energy does not show an apparent variation. When CH4 is used, with the change in gas pressure, the duration of the transient EMR signal and the pulse count varies considerably. However, the overall trend is still a downward trend. When charged with N2, the change in gas pressure has no significant effect on the EMR duration, energy and pulse count. Figure 6. Open in new tabDownload slide Effect of gas pressure and type on the characteristics of transient EMR during coal rupture. (a) EMR amplitude change; (b) EMR duration change; (c) EMR energy change; (d) EMR pulse counts change. Figure 7 shows the variation in the waveform characteristic of the transient EMR signal for the RCSs. A total of five specimens were charged with methane under different pore pressures and impacted under the same loading conditions. The test results show that the failure of the RCSs is more likely to produce EMR signals than that of the BCSs. Compared with BCSs, the RCS have apparent heterogeneity and anisotropy; thus, the main failure direction of an RCS is more random. This leads to the long duration of the EMR signal and strong variability in the EMR parameters. The maximum amplitude, EMR duration and pulse count of the coal sample damage showed a downward trend after adsorbing gas, but the energy did not attenuate. According to the definition of pulse count, it represents the fluctuation characteristics of the EMR signal. It is the embodiment of the ring number of the signal and is depicted as the waveform passing through the upper and lower threshold. It shows that although the maximum amplitude of the EMR signal decreases with the adsorption of methane, the average amplitude continues to exceed the pulse threshold, but the fluctuation is relatively gentle. In other words, although methane reduces the maximum amplitude of the EMR signal, it does not affect the overall strength or energy intensity of the signal. Figure 7. Open in new tabDownload slide Characteristics of the EMR signal from impact destruction of the RCSs. 4.2. Influence of the molding size of coal powders Eight pulverised BCSs with the same molding pressure but different coal powder sizes were impacted in the tests. Among the samples, four were charged with 1.5 MPa methane. The size of the powder particle used to make the sample is shown in Table 1. Figure 8 shows that as the particle size of the pulverised coal increases, the EMR signal shows a downward trend in its maximum amplitude, signal energy and pulse count characteristic parameters. Although the duration parameter fluctuates, the overall trend still decreases. Figure 8. Open in new tabDownload slide Influence of particle size on the transient EMR characteristics of BCSs. (a) BCS, pore pressure = 0 MPa and (b) gas-bearing BCS, pore pressure = 1.5 MPa, gas type = methane. Under the same molding pressure (100 MPa), the particle size used for making BCSs has a direct effect on the strength of the coal body. The smaller the pulverised coal particles are, the larger the specific surface area of the small particles. Under the same molding pressure, the particles can not only mix more fully with the coal tar, but can also contact and consolidate more with other particles; this will lead to high density and low porosity of the coal samples. According to the theory of damage mechanics, when an external force is applied, the part of the material with serious internal defects is more likely to cause crack growth and damage. When an impact occurs, the BCSs composed of large particles usually do not have sufficient energy storage capacity, and the frictional resistance between the particles is much smaller than that of the high-strength samples. Therefore, when the particle size is large, it is not conducive to the conversion of external loading energy into EMR energy; the increase in coal powder size thus leads to a decrease in the maximum amplitude, signal energy and pulse count. 4.3. Influence of the impact energy As shown in Table 3, a total of six tests were conducted under different impact energies, changing with the drop height and weight. According to figure 9, as the impact energy increases, the maximum amplitude, duration and energy of the EMR signal increase linearly. In contrast, the pulse count of the signal exhibits a decreasing trend; the number of pulses is between 4–8. For BCSs with similar mechanical properties, when the impact energy increases, the total amount of energy accumulated in the coal body increases significantly. The energy received by the coal body is converted into EMR energy when it is crushed. When the destruction process of the coal body is more severe, the broken fragments with free charge are thrown out with higher kinetic energy, so the signal duration and strength increase accordingly. However, the principle of the counting method determines the decrease in the pulse count. That is, although the number of times the waveform crosses the threshold is reduced, the signal waveform remains in a high-amplitude state, which is over the threshold; thus, the signal energy, duration and energy increase, but the pulse count decreases. Figure 9. Open in new tabDownload slide Influence of the impact energy on the characteristics of the transient EMR signal. (a) EMR amplitude change; (b) EMR duration change; (c) EMR energy change; (d) EMR pulse counts change. Table 3. Test schemes and working conditions of the impact energy tests Test ID . Loading height (m) . Loading weight (kg) . Test ID . Loading height (m) . Loading weight (kg) . WXM24 2 9 WXM27 1.5 6 WXM25 2 6 WXM28 1 9 WXM26 1.5 9 WXM29 1 6 Test ID . Loading height (m) . Loading weight (kg) . Test ID . Loading height (m) . Loading weight (kg) . WXM24 2 9 WXM27 1.5 6 WXM25 2 6 WXM28 1 9 WXM26 1.5 9 WXM29 1 6 Open in new tab Table 3. Test schemes and working conditions of the impact energy tests Test ID . Loading height (m) . Loading weight (kg) . Test ID . Loading height (m) . Loading weight (kg) . WXM24 2 9 WXM27 1.5 6 WXM25 2 6 WXM28 1 9 WXM26 1.5 9 WXM29 1 6 Test ID . Loading height (m) . Loading weight (kg) . Test ID . Loading height (m) . Loading weight (kg) . WXM24 2 9 WXM27 1.5 6 WXM25 2 6 WXM28 1 9 WXM26 1.5 9 WXM29 1 6 Open in new tab 4.4. Analysis of the impact energy and crushing effect The particle size distribution of the coal fragments after impact load was used to characterise the crushing degree of the gas-bearing coal. The specific method is to first screen the crushed coal pieces through standard sieves into seven particle sizes of 0–0.25, 0.25–0.5.0, 0.5–1.0, 1.0–2.0, 2.0–5.0, 5.0–10 and above 10 mm; the sorting results of the sieved BCS are shown in figure 10. Figure 10. Open in new tabDownload slide Sieving results of the impact-induced crushed blocks of the BCSs. (a) BCS, WXM01; (b) BCS, WXM07. The weight of the pulverised coal powder in each size range is summarised in Table 4. The weight of the crushed coal particles 0–5 mm in size and that of coal blocks larger than 10 mm are analysed separately. Combined with the impact speed test results, the impulse value per unit area acting on the coal sample is determined. The impulse size per unit area of the coal sample impacted by the falling weight represents the magnitude of impact energy. Figure 11a shows that with the increase in the impact impulse, the proportion of the mass with a particle size below 5 mm increases accordingly, which indicates that the greater the impact energy, the higher the degree of coal crushing. Figure 11b shows that with the increase in impact energy, the mass proportion of blocks larger than 10 mm gradually decreases, indicating that under higher impact energy, the coal body is more likely to be broken into small blocks and relatively small particles. Figure 11. Open in new tabDownload slide Relationship between the impact energy and the crushing effect of the BCSs. (a) percentage change of 0-5 mm particles; (b) percentage change of >10 mm blocks. Table 4. Screening results of the impact crushing blocks of the BCS . Sieving weight of each particle size range (g) . Sample ID . 0–0.25 mm . 0.25–0.50 mm . 0.5–1.0 mm . 1–2 mm . 2–5 mm . 5–10 mm . >10 mm . WXM01 3.80 4.30 6.70 13.50 9.00 45.40 201.20 WXM02 0.88 1.77 3.09 6.98 5.12 50.79 234.36 WXM03 1.03 3.80 9.26 15.44 10.14 39.67 224.96 WXM04 1.06 2.66 5.17 12.77 8.74 88.60 197.50 WXM05 1.30 3.70 3.50 7.60 6.30 58.30 216.90 WXM06 0.82 3.38 9.23 25.76 7.22 36.63 233.27 WXM07 3.80 4.52 6.79 13.48 8.60 73.92 174.09 WXM08 1.16 1.84 2.71 6.58 5.23 49.64 232.14 WXM09 2.71 5.32 4.76 8.87 6.16 53.86 199.02 WXM10 4.07 4.17 6.82 12.01 6.61 47.53 206.79 . Sieving weight of each particle size range (g) . Sample ID . 0–0.25 mm . 0.25–0.50 mm . 0.5–1.0 mm . 1–2 mm . 2–5 mm . 5–10 mm . >10 mm . WXM01 3.80 4.30 6.70 13.50 9.00 45.40 201.20 WXM02 0.88 1.77 3.09 6.98 5.12 50.79 234.36 WXM03 1.03 3.80 9.26 15.44 10.14 39.67 224.96 WXM04 1.06 2.66 5.17 12.77 8.74 88.60 197.50 WXM05 1.30 3.70 3.50 7.60 6.30 58.30 216.90 WXM06 0.82 3.38 9.23 25.76 7.22 36.63 233.27 WXM07 3.80 4.52 6.79 13.48 8.60 73.92 174.09 WXM08 1.16 1.84 2.71 6.58 5.23 49.64 232.14 WXM09 2.71 5.32 4.76 8.87 6.16 53.86 199.02 WXM10 4.07 4.17 6.82 12.01 6.61 47.53 206.79 Open in new tab Table 4. Screening results of the impact crushing blocks of the BCS . Sieving weight of each particle size range (g) . Sample ID . 0–0.25 mm . 0.25–0.50 mm . 0.5–1.0 mm . 1–2 mm . 2–5 mm . 5–10 mm . >10 mm . WXM01 3.80 4.30 6.70 13.50 9.00 45.40 201.20 WXM02 0.88 1.77 3.09 6.98 5.12 50.79 234.36 WXM03 1.03 3.80 9.26 15.44 10.14 39.67 224.96 WXM04 1.06 2.66 5.17 12.77 8.74 88.60 197.50 WXM05 1.30 3.70 3.50 7.60 6.30 58.30 216.90 WXM06 0.82 3.38 9.23 25.76 7.22 36.63 233.27 WXM07 3.80 4.52 6.79 13.48 8.60 73.92 174.09 WXM08 1.16 1.84 2.71 6.58 5.23 49.64 232.14 WXM09 2.71 5.32 4.76 8.87 6.16 53.86 199.02 WXM10 4.07 4.17 6.82 12.01 6.61 47.53 206.79 . Sieving weight of each particle size range (g) . Sample ID . 0–0.25 mm . 0.25–0.50 mm . 0.5–1.0 mm . 1–2 mm . 2–5 mm . 5–10 mm . >10 mm . WXM01 3.80 4.30 6.70 13.50 9.00 45.40 201.20 WXM02 0.88 1.77 3.09 6.98 5.12 50.79 234.36 WXM03 1.03 3.80 9.26 15.44 10.14 39.67 224.96 WXM04 1.06 2.66 5.17 12.77 8.74 88.60 197.50 WXM05 1.30 3.70 3.50 7.60 6.30 58.30 216.90 WXM06 0.82 3.38 9.23 25.76 7.22 36.63 233.27 WXM07 3.80 4.52 6.79 13.48 8.60 73.92 174.09 WXM08 1.16 1.84 2.71 6.58 5.23 49.64 232.14 WXM09 2.71 5.32 4.76 8.87 6.16 53.86 199.02 WXM10 4.07 4.17 6.82 12.01 6.61 47.53 206.79 Open in new tab The mass proportion of the particle size distribution is an intuitive reflection of the destruction characteristics of the coal samples. As a result, the cumulative surface area index is adopted for different particle size ranges to analyse the relationship between the impact energy, pore pressure and crushing effect. The approximate particle surface area calculation method is as follows: suppose the total mass of the crushed blocks is m and that all blocks are spherical with a characteristic length of r; thus, the total surface area of a sample within a specified particle size range is S=V/v*s=3m(ρr)–1. The result of the cumulative surface area in each range is summarised in Table 5. Table 5. Calculation results of the impact crushing block surfaces of the BCSs . The approximate cumulative surface area of each particle size range (cm2) . Sample ID . 0–0.25 mm . 0.25–0.50 mm . 0.5–1.0 mm . 1–2 mm . 2–5 mm . 5–10 mm . >10 mm . Total cumulative surface area . WXM01 527.98 299.19 105.60 345.39 60.34 274.77 164.01 1777.28 WXM02 97.46 133.56 182.28 254.48 30.55 72.37 345.71 1116.41 WXM03 126.85 156.13 190.28 158.57 44.61 81.48 346.53 1104.45 WXM04 530.04 181.10 147.97 130.30 30.76 103.14 336.57 1459.87 WXM05 144.92 52.02 44.59 52.02 14.73 107.02 368.42 783.72 WXM06 154.15 210.20 140.14 435.59 28.03 112.58 288.85 1369.52 WXM07 163.81 155.41 73.51 79.81 28.35 122.44 341.64 964.96 WXM08 109.33 72.89 63.78 71.98 22.65 104.77 362.56 807.95 WXM09 145.49 76.79 56.58 68.70 23.38 103.66 363.57 838.17 WXM10 174.04 193.38 164.37 158.57 36.88 107.33 329.81 1164.37 . The approximate cumulative surface area of each particle size range (cm2) . Sample ID . 0–0.25 mm . 0.25–0.50 mm . 0.5–1.0 mm . 1–2 mm . 2–5 mm . 5–10 mm . >10 mm . Total cumulative surface area . WXM01 527.98 299.19 105.60 345.39 60.34 274.77 164.01 1777.28 WXM02 97.46 133.56 182.28 254.48 30.55 72.37 345.71 1116.41 WXM03 126.85 156.13 190.28 158.57 44.61 81.48 346.53 1104.45 WXM04 530.04 181.10 147.97 130.30 30.76 103.14 336.57 1459.87 WXM05 144.92 52.02 44.59 52.02 14.73 107.02 368.42 783.72 WXM06 154.15 210.20 140.14 435.59 28.03 112.58 288.85 1369.52 WXM07 163.81 155.41 73.51 79.81 28.35 122.44 341.64 964.96 WXM08 109.33 72.89 63.78 71.98 22.65 104.77 362.56 807.95 WXM09 145.49 76.79 56.58 68.70 23.38 103.66 363.57 838.17 WXM10 174.04 193.38 164.37 158.57 36.88 107.33 329.81 1164.37 Open in new tab Table 5. Calculation results of the impact crushing block surfaces of the BCSs . The approximate cumulative surface area of each particle size range (cm2) . Sample ID . 0–0.25 mm . 0.25–0.50 mm . 0.5–1.0 mm . 1–2 mm . 2–5 mm . 5–10 mm . >10 mm . Total cumulative surface area . WXM01 527.98 299.19 105.60 345.39 60.34 274.77 164.01 1777.28 WXM02 97.46 133.56 182.28 254.48 30.55 72.37 345.71 1116.41 WXM03 126.85 156.13 190.28 158.57 44.61 81.48 346.53 1104.45 WXM04 530.04 181.10 147.97 130.30 30.76 103.14 336.57 1459.87 WXM05 144.92 52.02 44.59 52.02 14.73 107.02 368.42 783.72 WXM06 154.15 210.20 140.14 435.59 28.03 112.58 288.85 1369.52 WXM07 163.81 155.41 73.51 79.81 28.35 122.44 341.64 964.96 WXM08 109.33 72.89 63.78 71.98 22.65 104.77 362.56 807.95 WXM09 145.49 76.79 56.58 68.70 23.38 103.66 363.57 838.17 WXM10 174.04 193.38 164.37 158.57 36.88 107.33 329.81 1164.37 . The approximate cumulative surface area of each particle size range (cm2) . Sample ID . 0–0.25 mm . 0.25–0.50 mm . 0.5–1.0 mm . 1–2 mm . 2–5 mm . 5–10 mm . >10 mm . Total cumulative surface area . WXM01 527.98 299.19 105.60 345.39 60.34 274.77 164.01 1777.28 WXM02 97.46 133.56 182.28 254.48 30.55 72.37 345.71 1116.41 WXM03 126.85 156.13 190.28 158.57 44.61 81.48 346.53 1104.45 WXM04 530.04 181.10 147.97 130.30 30.76 103.14 336.57 1459.87 WXM05 144.92 52.02 44.59 52.02 14.73 107.02 368.42 783.72 WXM06 154.15 210.20 140.14 435.59 28.03 112.58 288.85 1369.52 WXM07 163.81 155.41 73.51 79.81 28.35 122.44 341.64 964.96 WXM08 109.33 72.89 63.78 71.98 22.65 104.77 362.56 807.95 WXM09 145.49 76.79 56.58 68.70 23.38 103.66 363.57 838.17 WXM10 174.04 193.38 164.37 158.57 36.88 107.33 329.81 1164.37 Open in new tab The relationship between the cumulative total surface area, impact energy and gas pressure is shown in figure 12. With the increase in impact energy, the cumulative surface area of the coal particles increases correspondingly. With the increase in pore pressure, the cumulative surface area of the coal particles also slightly increases, indicating that the proportion of small particles increases and that the proportion of large blocks decreases during coal crushing. The analysis results here are consistent with the change rules of the waveform characteristic parameters of the EMR signal. Figure 12. Open in new tabDownload slide Influence of the impact energy and pore pressure on the crushing surface area of the BCSs. (a) influence of impact energy; (b) influence of pore pressure. 5. Discussion 5.1. Limitation of test devices and loading modes Previous researchers have mainly applied drop hammer, split Hopkinson pressure bar (SHPB) and Taylor bar methods to realise experimental studies on the dynamic characteristics of materials (Li et al. 2016). Nevertheless, these methods are mainly applied in scenarios without gas-bearing environments. In this study, the self-developed drop hammer device provided a sealed cabin allowing coal to adsorb methane gas and conduct impact loading. On the top of the cabin, a pane of toughened glass and an O-ring were used to seal the gas. Taking advantage of toughened glass requires the following considerations. (i) Considering the gas consumption and experimental cost, the volume of the sealed cabin should not be too large; thus, the cabin and the hammer barrel need to be isolated. (ii) The formation of a plug-in-type hammer barrel helps to achieve impact loading with different heights and weights. (iii) The toughened glass needs to be strong enough to seal pressured gas. (iv) When sharp parts strike it, the toughened glass will experience instant crushing damage. In preliminary testing, a series of tests was performed to determine the appropriate thickness of the glass. Toughed glass panes with five different thicknesses (12, 10, 8, 5 and 3 mm) were tested. The final results show that the 5 mm toughened glass could provide a gas pressure of no less than 2 MPa while also ensuring the smallest loss of impact energy and basic safety requirements. To avoid the loss of impact energy, we also designed an impact speed test system to measure the exact impact speed at the glass for both coal specimen types. Regarding the EMR data acquisition, the drop hammer was made with 304 stainless steel to avoid the possible electromagnetic interference caused by the falling of ferromagnetic materials. Additionally, a PA6-III nylon bar with a length of 150 mm was used as the dowel bar; that is, the falling hammer hits the nylon rod first and then brakes through the toughened glass to impact the coal sample. It was also verified whether the smashing of toughened glass generated an EMR signal, but no apparent EMR phenomenon was detected. Overall, the devices used in this test are relatively simple and have some limitations. These limitations also include the need to measure some vital mechanical parameters, which leads to slight inaccuracies in the analysis of the mechanical response of gas-bearing coal. We thus attempt to use the SHPB method to conduct impact loading on gas-bearing coal, as it will be helpful to analyse the dynamic response of the gas-bearing material with its EMR phenomenon. 5.2. Synchronisation analysis of two EMR channels In the experiment, two ferrite rod antennas were used to collect EMR signals. Considering that the transmission of EMR is usually directional, the two antennas were arranged perpendicular to each other. This section will discuss the synchronisation and consistency of the data from the two antenna channels. The EMR signal parameter characteristics obtained by the two antennas are shown in figure 13. According to the data, the signals of the two channels have obvious directivity in energy and maximum amplitude, showing an alternating trend in value. Therefore, the result indicates that the signals have both differences in directions and values, and sometimes there are situations where one channel receives the EMR signal, while the other channel does not receive the EMR signal. Additionally, the signals measured by two antennas have high uniformity in signal duration and pulse count, and the differences are small. Overall, the EMR signals received from two magnetic rod antennas have a mutually confirmed and complementary relationship. Figure 13. Open in new tabDownload slide Consistency and synchronisation analysis of the two EMR receiving antennas: (a) total EMR energy; (b) EMR duration; (c) EMR maximum amplitude and (d) EMR pulse count. Theoretically, when a coal sample is crushed due to an impact, the internal damage points of the coal samples will generate a transient electromagnetic field. Then, the electromagnetic waves will propagate outward from the coal; when passing through the magnetic rod antenna, these waves will cause the magnetic flux to change transiently. According to the Faraday law of electromagnetic induction, the coil wound on the magnetic rod will generate an induced electromotive force. Suppose the transient electromagnetic field caused by coal damage is composed of many points field sources from the multiple local failure points in the coal specimen. Due to the differences in damage point location and damage severity, the internal failure points of each coal specimen from the two antennas are also different. Thus, the propagation path and attenuation characteristics of the electromagnetic waves reflect the EMR parameter changes in terms of both direction and value. 5.3. Influence of gas on coal crushing According to some previous studies (He et al. 2011, 2012), the influence mechanism is mainly controlled by two aspects: First, the existence of both free gas and adsorbed gas will weaken the strength of the coal. The free gas has a stick-slip effect on the crack wall surface, which decreases the shear strength and compressive strength of the coal. The adsorbed gas leads to the micropore destruction and swelling deformation in the coal matrix (Zhang et al. 2016). Thus, with the increase in pore pressure, the strength of the coal specimen decreases gradually. As high-strength samples have better energy storage capacity, the transient failure and disintegration are also more severe. Thus, the crack splitting speed, crack propagation morphology, the total amount of free charge inside the body and the initial velocity of the peeling coal debris will indirectly affect the EMR characteristics of the coal body. With the decrease in coal strength, the EMR effects will decrease. Second, during the loading process of the coal mass, especially during impact loadings such as those induced by explosions and shocks, a high-intensity electric field will form between the internal crack tips or frictional surfaces. Due to the test method, the gas adsorbed by a coal sample will be released immediately when the impact loading is applied. The significant change in pore pressure may cause gas ionisation. This will generate free electrons and provide the basis for electromagnetic emission; moreover, the release of gas from the coal mass is actually in a turbulent state, and the flow of gas will generate fluctuations in the pressure on the pores and crack walls. The expansion and closure of the charged wall surface of pores and cracks will radiate electromagnetic waves (He & Liu 1995; He et al. 2012). Thus, the participation of gas also enhances the EMR effect. In other words, the influence of the presence of adsorptive gas on the EMR signal caused by the destruction of coal bodies has both an enhancement effect and a reduction effect. According to the test data, the EMR signals show different degrees of declines in the amplitude, duration and pulse count. The higher the pore pressure and the stronger the adsorption performance of the gas, the greater the decreasing trend of the EMR. Thus, the attenuation effect caused by the reduction in coal body strength plays a leading role in dynamic impact failure. 6. Conclusions In this study, a self-developed apparatus was introduced to realise dynamic impact loading on gas-bearing coal. During the test, the influencing factors on the damage features and corresponding EMR characteristics were analysed. The main conclusions are summarised as follows: The amplitude of the EMR signal generated by the impact damage of gas-bearing coal is approximately 10–600 mV, with a duration time of 3–1500 ms and accumulated energy of 0.1–1000 μJ; the maximum amplitude, duration and signal energy of the RCSs are 2.10, 1.70 and 5.01 times greater than those of the BCSs. As adsorbable gas charges a coal sample, the EMR parameters, such as the maximum amplitude, duration and pulse count, decrease. These trends will be more apparent if the gas adsorption rate is more significant (CO2 > CH4 > N2). The participation of gas induces an overall eduction in the peak strength of the electromagnetic signals. Nevertheless, the effect on the mean value of the EMR signal is not apparent, and the gas also reduces the EMR fluctuations. Although the BCSs have good homogeneity and orientation, the coal powder size and impact energy still affect the damage features and EMR characteristics. The higher the impact impulse is, the more severe the damage to the coal specimens. As the particle size of the pulverised coal increases, the EMR signal shows a downward trend in its maximum amplitude, signal energy and pulse count characteristic parameters. The influence of the presence of adsorptive gas on the EMR signal caused by the destruction of coal bodies has both an enhancement effect and a reduction effect. During the early warning analysis of coal and gas outbursts using EMR parameters, not all the waveform parameters are sensitive to coal mine methane, but the significant effect of methane on signal volatility should be considered. Acknowledgements The authors are grateful for the financial support from the National Natural Science Foundation of China (grant no. 51804287) and the National Key Research and Development Project (grant no. 2018YFC0808500-02). Conflicts of Interests The authors declare no conflicts of interest. References Beamish B.B. , Crosdale P.J., 1998 . Instantaneous outbursts in underground coal mines: an overview and association with coal type , International Journal of Coal Geology , 35 , 27 – 55 . Google Scholar Crossref Search ADS WorldCat Evans J.C. , Rowlands C.C., Cross R.M., Rigby N., 1984 . E.P.R. studies of outburst-prone anthracite coal , Fuel , 63 , 1471 – 1472 . Google Scholar Crossref Search ADS WorldCat Fan C.J. , Li S., Luo M.K., Du W.Z., Yang Z.H., 2017 . Coal and gas outburst dynamic system , International Journal of Mining Science and Technology , 27 , 49 – 55 . Google Scholar Crossref Search ADS WorldCat Geng J.B. , Xu J., Nie W., Peng S.J., Zhang C.L., Luo X.H., 2017 . Regression analysis of major parameters affecting the intensity of coal and gas outbursts in laboratory , International Journal of Mining Science and Technology , 27 , 327 – 332 . Google Scholar Crossref Search ADS WorldCat Guan P. , Wang H.Y., Zhang Y.X., 2009 . Mechanism of instantaneous coal outbursts , Geology , 37 , 915 – 918 . Google Scholar Crossref Search ADS WorldCat Guo H.J. , Cheng Y.P., Ren T., Wang L., Yuan L., Jiang H.N., Liu H.Y., 2016 . Pulverization characteristics of coal from a strong outburst-prone coal seam and their impact on gas desorption and diffusion properties , Journal of Natural Gas Science and Engineering , 33 , 867 – 878 . Google Scholar Crossref Search ADS WorldCat He S.Q. , Jin L.Z., Ou S.N., Ming X.H., 2018 . Soft coal solid-gas coupling similar material for coal and gas outburst simulation tests , Journal of Geophysics and Engineering , 15 , 2033 – 2046 . Google Scholar Crossref Search ADS WorldCat He X. , Liu M., 1995 . Electromagnetic Dynamics of Coal or Rock Containing Gas , China University of Mining and Technology Press , Xuzhou (in Chinese) . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC He X.Q. , Chen W.X., Nie B.S., Mitri H., 2011 . Electromagnetic emission theory and its application to dynamic phenomena in coal-rock , International Journal of Rock Mechanics and Mining Sciences , 48 , 1352 – 1358 . Google Scholar Crossref Search ADS WorldCat He X.Q. et al. ., 2012 . Research progress on electromagnetic radiation in gas-containing coal and rock fracture and its applications , Safety Science , 50 , 728 – 735 . Google Scholar Crossref Search ADS WorldCat He X.Q. , Song L., 2012 . Status and future tasks of coal mining safety in China , Safety Science , 50 , 894 – 898 . Google Scholar Crossref Search ADS WorldCat Jin K. et al. ., 2018 . Experimental investigation on the formation and transport mechanism of outburst coal-gas flow: implications for the role of gas desorption in the development stage of outburst , International Journal of Coal Geology , 194 , 45 – 58 . Google Scholar Crossref Search ADS WorldCat Li C.W. , Sun X.Y., Wang C., Xu X.M., Xie B.J., Li J., 2016 . The correlated characteristics of micro-seismic and electromagnetic radiation signals on a deep blasting workface , Journal of Geophysics and Engineering , 13 , 1020 – 1035 . Google Scholar Crossref Search ADS WorldCat Li X.C. , Yang C.L., Ren T., Nie B.S., Zhao C.H., Liu S.W., Jiang T., 2017 . Creep behaviour and constitutive model of coal filled with gas , International Journal of Mining Science and Technology , 27 , 847 – 851 . Google Scholar Crossref Search ADS WorldCat Peng S.J. , Xu J., Yang H.W., Liu D., 2012 . Experimental study on the influence mechanism of gas seepage on coal and gas outburst disaster , Safety Science , 50 , 816 – 821 . Google Scholar Crossref Search ADS WorldCat Qiu L.M. , Wang E.Y., Song D.Z., Liu Z.T., Shen R.X., Lv G.G., Xu Z.Y., 2017 . Measurement of the stress field of a tunnel through its rock EMR , Journal of Geophysics and Engineering , 14 , 949 – 959 . Google Scholar Crossref Search ADS WorldCat Shen R. et al. ., 2018 . An effect evaluation method of coal seam hydraulic flushing by EMR , Journal of Natural Gas Science and Engineering , 54 , 154 – 162 . Google Scholar Crossref Search ADS WorldCat Shen R. , Qiu L., Zhao E., Han X., Li H., Hou Z., Zhang X., 2019a . Experimental study on frequency and amplitude characteristics of acoustic emission during the fracturing process of coal under the action of water , Safety Science , 117 , 320 – 329 . Google Scholar Crossref Search ADS WorldCat Shen R.X. , Li H.R., Wang E.Y., Li D.X., Hou Z.H., Zhang X., Han X., 2019b . Mechanical behavior and AE and EMR characteristics of natural and saturated coal samples in the indirect tensile process , Journal of Geophysics and Engineering , 16 , 753 – 763 . Google Scholar Crossref Search ADS WorldCat Skoczylas N. , Dutka B., Sobczyk J., 2014 . Mechanical and gaseous properties of coal briquettes in terms of outburst risk , Fuel , 134 , 45 – 52 . Google Scholar Crossref Search ADS WorldCat Sobczyk J. , 2014 . A comparison of the influence of adsorbed gases on gas stresses leading to coal and gas outburst , Fuel , 115 , 288 – 294 . Google Scholar Crossref Search ADS WorldCat Tu Q.Y. , Cheng Y.P., Guo P.K., Jiang J.Y., Wang L., Zhang R., 2016 . Experimental study of coal and gas outbursts related to gas-enriched areas , Rock Mechanics and Rock Engineering , 49 , 3769 – 3781 . Google Scholar Crossref Search ADS WorldCat Wang G. , Li W.X., Wang P.F., Yang X.X., Zhang S.T., 2017 . Deformation and gas flow characteristics of coal-like materials under triaxial stress conditions , International Journal of Rock Mechanics and Mining Sciences , 91 , 72 – 80 . Google Scholar Crossref Search ADS WorldCat Wen Z.J. , Wang X., Tan Y.L., Zhang H.L., Huang W.P., Li Q.H., 2016 . A study of rockburst hazard evaluation method in coal mine , Shock and Vibration , 2016 , 1 – 9 . Google Scholar OpenURL Placeholder Text WorldCat Wold M.B. , Connell L.D., Choi S.K., 2008 . The role of spatial variability in coal seam parameters on gas outburst behaviour during coal mining , International Journal of Coal Geology , 75 , 1 – 14 . Google Scholar Crossref Search ADS WorldCat Xie J.L. , Xu J.L., Wang F., 2018 . Mining-induced stress distribution of the working face in a kilometer-deep coal mine—a case study in Tangshan coal mine-a case study in Tangshan coal mine , Journal of Geophysics and Engineering , 15 , 2060 – 2070 . Google Scholar Crossref Search ADS WorldCat Zhang Y.H. , Lebedev M., Sarmadivaleh M., Barifcani A., Iglauer S., 2016 . Swelling-induced changes in coal microstructure due to supercritical CO2 injection , Geophysical Research Letters , 43 , 9077 – 9083 . Google Scholar Crossref Search ADS WorldCat Zhao W. , Cheng Y.P., Jiang H.N., Jin K., Wang H.F., Wang L., 2016 . Role of the rapid gas desorption of coal powders in the development stage of outbursts , Journal of Natural Gas Science and Engineering , 28 , 491 – 501 . Google Scholar Crossref Search ADS WorldCat © The Author(s) 2020. Published by Oxford University Press on behalf of the Sinopec Geophysical Research Institute. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. © The Author(s) 2020. Published by Oxford University Press on behalf of the Sinopec Geophysical Research Institute.
TI - Experimental investigation on the characteristics of transient electromagnetic radiation during the dynamic fracturing progress of gas-bearing coal
JO - Journal of Geophysics and Engineering
DO - 10.1093/jge/gxaa030
DA - 2020-09-25
UR - https://www.deepdyve.com/lp/oxford-university-press/experimental-investigation-on-the-characteristics-of-transient-uCf6rhR2iH
SP - 799
EP - 812
VL - 17
IS - 5
DP - DeepDyve
ER -