Rock Dynamic Disasters Research Articles

Fractal characteristics of acoustic emissions from coal under multi-stage true-triaxial compression

The fractal characteristics of acoustic emissions (AEs) are widely used for monitoring and warning of coal and rock dynamic disasters such as coal and gas outburst and rock bursts. However, most research has focused on fractal behavior during coal and rock failure under uniaxial and conventional triaxial compression. For this study, we conducted true-triaxial multi-stage loading tests on coal under different stress conditions. Based on the AE count rate data collected from these experiments, we calculated the fractal dimension of every loading step by the Grassberger and Procaccia algorithm using phase space reconstruction theory. The results show that the AE count rate represents the load during the failure well. In the initial loading stage, AEs are very active; in the initial portion of the load maintenance stage, AE counts decrease gradually until they almost cease later in that stage. AE count rates during failure for all loading steps exhibit fractal features and show a generally consistent pattern. The fractal dimension fluctuates in the early loading stages and then begins to decline, reaching a minimum when failure occurs. The critical fluctuation coefficient where the fractal dimension begins to enter the continuous decline stage is about 55.5%–66.5% of the stress level. The relationship between the change of fractal dimension and the ‘quiet period’ of AE before coal failure is discussed and the proposal that the combination of two monitoring methods can more effectively predict coal and rock dynamic disasters is put forward.

Study on the influence factors of the initial expansion energy of released gas

Abstract Coal and gas outburst is a serious coal and rock dynamic disaster, and effective prediction is essential to control. The initial expansion energy of released gas (IEERG) is a new method to predict coal and gas outburst, which depends primarily on the gas pressure and degree of coal fragmentation. The IEERG reflects the effects of the ground stress, the gas pressure, and coal strength on the coal and gas outburst. On the basis of the single factor on the IEERG, three factors have been studied by orthogonal experiments, including gas pressure, coal particle size, and moisture. The results show that the influence of gas pressure, coal particle size, and water content on the IEERG decreases in turn; that gas expansion energy increases significantly as gas pressure increases; and that the greater the gas pressure, the faster the increase. The index Wp of IEERG first increases and then decreases with an increase in coal particle size and decreases with an increase in moisture content. Through this work, the main influencing factors of gas expansion energy have been defined. This method offers an important theoretical and practical significance to predict coal and gas outbursts.

Experimental Investigation on Influence Factors of Acoustic Emission Activity in Coal Failure Process

Stress-dominated coal and gas outburst disaster has become one of the main safety problems in deep coal mines. Acoustic emission (AE) or microseismic technology has been viewed as a promising method that can effectively reflect the stress and stability status of rock mass. The AE activity precursor of coal failure is the theoretical basis of this technology. In this study, AE experiments in failure process of coal specimens with different properties and under different stress conditions were performed in laboratory to explore influence factors and their effect of AE activity, and AE activity pattern classification was proposed based on the failure type of coal. The results indicate that the AE activity of different coals under loading are associated with the failure phase, and the evolution pattern of AE activity depends on the failure type of stressed coal. Both the mechanical property and the external stress condition have an important influential effect on the failure type and AE activity pattern in coal failure process. The internal mechanical property decides the inherent tendency of stressed coals to perform brittle or ductile behavior, and the responded AE activity pattern. The contrast of fissure distribution of specimens suggested that fissure structure in coal significantly affects the fracturing mode of coal in uniaxial compression and the AE activity pattern. The external stress condition has a transition effect on AE event energy distribution and AE activity pattern. Under the effect of external stress condition, the energy distribution of AE events was transforming between relative disperse and relative concentration, the failure type and AE activity evolution pattern of coal could appear the brittle-ductile transition. Based on the view of failure type, the pattern of AE activity of coal failure can be classified into three types, i.e., ductile, brittle, and semi-brittle pattern. It is suggested that the high-level AE activity can be viewed as the precursor of brittle instability of coal, and relative quiet phenomenon of AE activity as the precursor of ductile or semi-brittle instability. The research achievement can provide a theoretical base for the prewarning criteria establishment of coal and rock dynamic disasters at depth and improve the insight of AE activity in the coal failure process.

Research on Acoustic Emission and Electromagnetic Emission Characteristics of Rock Fragmentation at Different Loading Rates

The relationships among the generation of acoustic emission, electromagnetic emission, and the fracture stress of rock grain are investigated, which are based on the mechanism of acoustic emission and electromagnetic emission produced in the process of indenting rock. Based on the relationships, the influence of loading rate on the characteristics of acoustic emission and electromagnetic emission of rock fragmentation is further discussed. Experiment on rock braking was carried out with three loading rates of 0.001 mm/s, 0.01 mm/s, and 0.1 mm/s. The results show that the phenomenon of acoustic emission and electromagnetic emission is produced during the process of loading and breaking rock. The wave forms of the two signals and the curve of the cutter indenting load show jumping characteristics. Both curves have good agreement with each other. With the increase of loading rate, the acoustic emission and electromagnetic emission signals are enhanced. Through analysis, it is found that the peak count rate, the energy rate of acoustic emission, the peak intensity, the number of pulses of the electromagnetic emission, and the loading rate have a positive correlation with each other. The experimental results agree with the theoretical analysis. The proposed studies can lead to an in‐depth understanding of the rock fragmentation mechanism and help to prevent rock dynamic disasters.

Experimental research on the electromagnetic radiation (EMR) characteristics of cracked rock.

Coal rock would emit the electromagnetic radiation (EMR) while deformation and fracture, and there exists structural body in the coal rock because of mining and geological structure. In this paper, we conducted an experimental test the EMR characteristics of cracked rock under loading. Results show that crack appears firstly in the prefabricated crack tip then grows stably parallel to the maximum principal stress, and the coal rock buckling failure is caused by the wing crack tension. Besides, the compressive strength significantly decreases because of the precrack, and the compressive strength increases with the crack angle. Intact rock EMR increases with the loading, and the cracked rock EMR shows stage and fluctuant characteristics. The bigger the angle, the more obvious the stage and fluctuant characteristics, that is EMR becomes richer. While the cracked angle is little, EMR is mainly caused by the electric charge rapid separates because of friction sliding. While the cracked angle is big, there is another significant contribution to EMR, which is caused by the electric dipole transient of crack expansion. Through this, we can know more clear about the crack extends route and the corresponding influence on the EMR characteristic and mechanism, which has important theoretical and practical significance to monitor the coal rock dynamical disasters.

Study on the characteristics of coal rock electromagnetic radiation (EMR) and the main influencing factors

Coal rock would produce electromagnetic radiation (EMR) in the loading process, but study on the influence factors influence on the coal rock EMR characteristics in the mesoscopic level is not insufficient. In the paper, the EMR characteristics of coal and rock samples under uniaxial loading are studied. Several typical microcosmic mechanisms affecting the characteristics of EMR are discussed, such as strength, composition and microstructure of the samples. Results show that the macroscopic structure of the outburst coal is soft, the corresponding EMR signal increases slowly with the loading increase and the EMR peak is smaller. The rockburst coal has a strong brittleness, the EMR signal increases quickly and EMR peak appears while the coal breaks is larger than the outburst coal. The EMR characteristics of rock samples are similar to the rockburst coal, but the EMR peak is the largest. When the coal rock microstructure is complete, the coal rock block is larger and the brittleness is stronger, then the corresponding strength would be larger. And the free charge generated by thermal excitation, field emission and intergranular chemical bond breakage would also be more. In the meantime, the crack propagation rate becomes greater, therefore the EMR is more stronger. The piezoelectric effect is mainly caused by the linear elastic stage of the specimen deformation and rupture, which contributes less to the EMR signals. This study is of great theoretical and practical value for assessing the mechanical state of coal rock through EMR technology, and accurately monitoring and predicting the coal rock dynamic disasters.

Fractural structure of thick hard roof stratum using long beam theory and numerical modeling

The thick hard rock (THR) roof of the long-wall mining face is prone to the large-sized cantilever roof, and its sudden fracture will cause serious rock dynamic disasters, such as coal and gas outburst and rockburst. In this study, based on the long beam theory, the initial fracture mechanical model for THR was established, and the first weighting characteristics and extreme fracture step distance were calculated. This study introduced a new technology called deep-hole pre-splitting blasting (DPB) which could break the THR by drilling holes with different depths and angles at different levels of roof rock and then blasting it. Field measurement analysis indicated that the immediate roof and lower thick hard strata were fully collapsed to fill the goaf, and the upper thick hard stratum was effectively cut off. The results showed that mechanical model and drilling holes method and DPB technique were so notably that would lead to a foundation for large-scale popularization and application in a Chinese Mine.

Characteristics of coal mining microseismic and blasting signals at Qianqiu coal mine

The signal waveforms caused by blasting events, which are similar to the microseismic (MS) signal waveforms caused by mining activities, are very common during the MS monitoring at coal mines. However, these blasting signals are not useful for monitoring and early warning of the coal or rock dynamic disasters by MS monitoring technique. To distinguish between the coal mining MS signals and the blasting signals, we studied the differences between these waveforms by analyzing the dominant frequency, signal duration, following peak attenuation, and multifractal parameters [Δα and Δf(α)]. The main results are: 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). The following peak envelope curves of the two types of signals fit a power function. Moreover, the power exponent and fitting accuracy were obtained to describe the attenuated speed and stabilities of the MS signals. The coal mining MS signals attenuate slower, and the coda waves are more complex than the blasting signals. The dividing line of the power exponent between the mining MS and the blasting signals is 8. According to the multifractal theory, the mining MS signals have smaller spectral width Δα (below 1.2) and Δf(α) (below 0.3) than the blasting signals (Δα above 1.2 and Δf(α) above 0.3). The research results lay a foundation for the automatic identification of mining MS signals and blasting signals recorded in coal mines.

Automatic crack detection method for loaded coal in vibration failure process.

In the coal mining process, the destabilization of loaded coal mass is a prerequisite for coal and rock dynamic disaster, and surface cracks of the coal and rock mass are important indicators, reflecting the current state of the coal body. The detection of surface cracks in the coal body plays an important role in coal mine safety monitoring. In this paper, a method for detecting the surface cracks of loaded coal by a vibration failure process is proposed based on the characteristics of the surface cracks of coal and support vector machine (SVM). A large number of cracked images are obtained by establishing a vibration-induced failure test system and industrial camera. Histogram equalization and a hysteresis threshold algorithm were used to reduce the noise and emphasize the crack; then, 600 images and regions, including cracks and non-cracks, were manually labelled. In the crack feature extraction stage, eight features of the cracks are extracted to distinguish cracks from other objects. Finally, a crack identification model with an accuracy over 95% was trained by inputting the labelled sample images into the SVM classifier. The experimental results show that the proposed algorithm has a higher accuracy than the conventional algorithm and can effectively identify cracks on the surface of the coal and rock mass automatically.

Time-varying characteristics of electromagnetic radiation during the coal-heating process

Forecasting and predicting coalfield fire and coal concealed fire are difficult components of coal fire control, and there is currently a lack of widely applicable effective methods for these processes. Electromagnetic radiation (EMR) has the advantage of multi-direction cross-locating and has been widely used to monitor and provide early warnings for coal and rock dynamic disasters. In this paper, the time-varying characteristics of EMR during 3 metamorphic grades of the coal-heating process were studied. EMR signals were clearly generated in different metamorphic grades of the coal-heating process. The variation trend of the EMR signals was different for 3 metamorphic grades of coal. According to R/S statistical analysis of the EMR signal time series, all Hurst values were greater than 0.5 and the correlation coefficient was above 0.9. There is a positive correlation between the EMR signals and coal temperature. In the coal-heating process, the EMR signal intensity varied if the EMR test frequency was 1kHz, 15kHz and 50kHz. Thermal deformation and thermal cracking of the coal body occurred in the coal-heating process. The free electrons and electric dipole in coal migrate and generate EMR. Based on the changing characteristics of the EMR in the coal-heating process, we present the conceptual design of a method to detect concealed fire in underground mines.

Automatic event detection in low SNR microseismic signals based on multi-scale permutation entropy and a support vector machine

Microseismic monitoring is an effective means for providing early warning of rock or coal dynamical disasters, and its first step is microseismic event detection, although low SNR microseismic signals often cannot effectively be detected by routine methods. To solve this problem, this paper presents permutation entropy and a support vector machine to detect low SNR microseismic events. First, an extraction method of signal features based on multi-scale permutation entropy is proposed by studying the influence of the scale factor on the signal permutation entropy. Second, the detection model of low SNR microseismic events based on the least squares support vector machine is built by performing a multi-scale permutation entropy calculation for the collected vibration signals, constructing a feature vector set of signals. Finally, a comparative analysis of the microseismic events and noise signals in the experiment proves that the different characteristics of the two can be fully expressed by using multi-scale permutation entropy. The detection model of microseismic events combined with the support vector machine, which has the features of high classification accuracy and fast real-time algorithms, can meet the requirements of online, real-time extractions of microseismic events.

Microseismic Signal Spectra, Energy Characteristics, and Fractal Features Prior to Rock Burst: A Case Study from the Qianqiu Coal Mine, China

Microseismic (MS) technology has been widely adopted for monitoring coal and rock dynamic disasters. Insights into MS wave characteristics contribute to the accurate prediction of these disasters. In this study, MS wave characteristics were analysed from three aspects: the signal spectra, wavelet packet energy and fractal features. It is shown that prior to the rock burst, the MS wave main frequency decreased following a power law, the amplitude linearly increased, the wavelet packet energy tended to become concentrated on the low frequency bands, and the correlation dimension decreased. When the rock burst occurred, the MS wave main frequency, wavelet packet energy and correlation dimension declined to their lowest levels. Meanwhile, the amplitude rose to a maximum. Therefore, the MS wave characteristics in this study were found to effectively identify and extract precursor information of value for predicting rock dynamic disasters.

The dynamical response characteristics of elastic–plastic coal under dynamic load

At present, it has been confirmed that tensile stress can be generated in coal bodies through instantaneous unloading, which leads to severe damage in certain areas of the coal. However, the process for the generation of this tensile stress is still unclear. In this study, by taking the elastic–plastic coal in the front of the tunneling face and the rock cross-cut coal uncovering region as examples, and by applying the rules of reflection and transmission to the stress waves, the concrete propagation process of stress waves in coal under dynamic loading was examined. At the same time, the formation and acting mechanisms of the tensile stress waves under the interaction of the loading and unloading stress waves were studied. The results indicated that compression-shear, tension, and tension-shear failures in the elastic–plastic coal were evident, under the role of the instantaneous loading and unloading. Due to the fact that the wave impedance of the coal tended to distribute unevenly in the front of the tunneling face, the loading and unloading stress waves were thereby transmitted and reflected in the propagation process of the coal body, and formed unloading stress waves. The tensile stress generated in the coal under the unloading waves, which were prone to severe damage to coal body, led to dramatic increases of the gas desorption rate, as well as a significant rising of the gas pressure. These results led to the occurrences of the coal and gas outburst accidents. Therefore, the development process of the coal and gas outbursts was determined to have begun on the inside of the coal, then to gradually develop towards the tunneling face. Multi-beam unloading waves were formed by the instantaneous unloading of the blast-hole wall, as well as the pressure released around the coal. Radial tensile stress waves in the coal were prominent, under the role of the unloading waves, which led to tension failure in the coal, which in turn generated circumferential cracks. This caused the spallation phenomena of the coal around the outburst-hole wall during the process of the coal and gas outbursts. The conclusions of this study have important theoretical guiding significance for the prevention of coal and rock dynamic disasters.

A Study on the Characteristics of Microseismic Signal during Deformation and Failure of Different Materials under Uniaxial Compression

With the decline of shallow coal reserves and increase in demand of coal consumption, the hazard of coal and rock dynamic disasters is expanding. In this paper, we conducted some laboratory scale tests on coal, cement, and glass materials to figure out the microseismic (MS) characteristic differences among materials. A new method, denoted as WPT-LMD, is proposed to conduct signal denoising and analysis work. A series of basic analyses regarding MS are conducted, including the relationships between MS characteristics and loading rate, coal powder particle size, loading stage, and MS event statistics. Research results show that the damage of all these three materials is accompanied with MS events, abundant with low frequency component (0–200 Hz). But cement and coal specimens produce with relative wide frequency distribution in sample frequency domain, while glass specimens were found to only produce low frequency event. The powder particle sizes have obvious influence on the strength of coal specimen, but the loading rate seems to have no influence on the MS characteristics. The outcome of the paper will further provide a theoretical basis for understanding the mechanism of MS activities and has great significance to improve the coal mining safety.

Mechanical genesis of Henan (China) Yima thrust nappe structure

Considering the serious coal and rock dynamic disasters around the main slip plane called F16 in the coal mining area) of Henan Yima (China) thrust nappe structure, the mechanical genesis of the Yima thrust nappe structure was studied comprehensively using geomechanics, fault mechanics, elastic mechanics, and Coulomb’s law of friction. First, using the centrifugal inertia force of Earth’s rotation as a source, a mechanical model of N-S compression superimposed with W-E reverse torsion was established to explain the formation of the early Yima coal basin and Jurassic Yima Group coal measures. Second, an equation for the ultimate stress in the forming stage of F16 was derived using the plastic slip-line field theory and the parabolic Mohr failure criterion. Moreover, the distribution of ultimate stress and the geometric characteristics of the fault profile were obtained using the field model parameters. Finally, the stress field of F16 and the mechanical genesis of the large-scale reverse thrust sheet were discussed based on elastic mechanics theory and Coulomb’s law of friction. The results show that the tectonic framework of the early Yima coal basin and the formation pattern of Jurassic Yima Group coal measures given by the model are consistent with the in-situ explorations. The geometric characteristics of the fault profile obtained by numerical calculation can better reflect the shape of F16 in its forming stage, and the mechanical genesis of the large-scale reverse thrust sheet also concurred with the field situations. Thus, this work can provide a foundation for further studies on the genesis of the thrust nappe structure, the mechanism of rock bursts induced by F16, and the characteristics of the residual stress field in the Yima mining area.

Acoustic Emission (AE) Propagation Attenuation Theory and Rule in Non-Perfect Elastic Coal and Rock

Propagation rule of acoustic emission (AE) signal in coal and rock is an important basis when AE technique forecasts coal and rock dynamical disasters. Based on correlative theory of quality factor Q, Acoustic emission signal propagation attenuation formula in non-perfect elastic coal and rock are analyzed, Based on the theoretic formula, Effects of different quality factor and propagation distance on AE propagation attenuation are theoretically analyzed ;Based on theoretic analysis results, AE signal propagation numerical simulation and field test programs are designed, AE signal propagation rules in elastoplastic coal and rock are obtained. Field test and numerical simulation experimentation results validate rationality of theoretic forumla. Study production can guide AE technique that forecasts mine and rock dynamical disasters.

Research on Stress Migration and Evolution Law of Coal in Driving Face and Generation Mechanism of Acoustic Emission

By means of FLAC3D software, firstly 3-demensional model was built, and stress migration and evolution law of coal seam in the process of mine roadway excavation are studied. Then according to the stress evolution law, the mechanism of acoustic emission (AE) generation in coal after excavation was analyzed. The results show that: after excavation, due to lateral displacement constraints in the coal body near the free face is removed, the coal in this zone was in 2-dementional stress condition. Because the vertical stress exceeded the uniaxial strength of coal body, the coal got into the post-peak strain-softening state. With the evolution of time, the stress in the zone gradually reduced until a state of equilibrium. In this zone the principle of AE generation is that lateral stress reduction result in macro crack propagation, coal mass failure, then elastic wave emitted. Signals come from the zone, i.e. stress relief zone, is the main part of AE signals, and should be the focus of study in AE technology of predicting coal or rock dynamic disasters. In stress-peak zone, due to the constraints of the lateral displacement, the lateral stress and strength of coal increased, the vertical stress of coal body gradually increased until the strength peak in the 3-dimensional stress state. After the excavation of roadway, the stress in stress-concentration and stress-peak zone gradually increased to equilibrium state over time. The principle of AE generation in this region is that due to the increase of the vertical stress, coal and rock gradually damaged that resulted in the release of the elastic wave.

Uniaxial Compression with Acoustic Emission Experimental Study on Rock Damage Process

Acoustic emission technique is an important technique for monitoring crack propagation and failure process of rock, coal and concrete material. A uniaxial compression test with acoustic emission monitoring on coal and rock samples’ deformation and failure process were carried out. Failure precursor information of rock, coal and concrete material were studied through contrast analysis the experiment result include acoustic emission signals, strain, load correlation of sample inner crack propagation to failure process. The test provided necessary data to further understand on rock burst failure disaster. The test result provides a theoretical basis for further application of acoustic emission for prediction coal rock dynamic disaster, assessment rock and concrete structure stability and study rock concrete material failure process mechanism.

Removal of noises from electromagnetic radiation of coal or rock with EEMD-adaptive morphological filter

The electromagnetic radiation (EMR) signal collected by monitoring system during coal or rock dynamic disaster may be interferred easily by electromagnetic noises in mines. The noises have a direct influence on the recognition and analysis of the EMR signal features during the disaster. With the aim of removing these noises, an ensemble empirical mode decomposition (EEMD) adaptive morphological filter was proposed. From the result of the simulation and the experiment, it is shown that the method can restrain the random noise and white Gaussian noise mixed with EMR signal effectively. The filter is highly useful for improving the robustness of the coal or rock dynamic disaster monitoring system.

Fractal characteristics and its application in electromagnetic radiation signals during fracturing of coal or rock

The present study analyzed the electromagnetic radiation (EMR) time series of the destruction process of coal or rock sample under uniaxial loading and the monitoring process in working face by means of fractal geometry, and results of the correlation dimension change curve of EMR time series were obtained. In the meantime, the current study also sought the fractal characteristic to the EMR signals by contrast to the change curve of EMR signals and explored the precursory phenomenon of rock burst. This paper concluded the main findings as followed: the EMR time series of the destruction process of coal or rock sample under uniaxial loading and the monitoring process in working face corresponded to fractal; the correlation dimension of EMR time series reflected the process of coal or rock damage deformation, that is, the inner damage of coal or rock made a change from random to order. In the field application, the correlation dimension served as a new index of forecasting the coal or rock dynamic disaster.