Rock Burst In Coal Mine Research Articles

Определение индивидуального риска травматизма горнорабочих в результате динамического проявления

The article analyses the effect of gas-dynamic manifestations on occupational injuries. It has been established that the most hazardous gas-dynamic manifestation for underground deep mines is a rock burst. As the rock burst is identified by the authors as the most hazardous effect by its manifestations, the authors offer their methodology of identification of occupational injury risk caused by a rock burst for a wider discussion. The main characteristics and causes of rock bursts and their signs and forecasting methods have been described. The statistics of accidents caused by rock bursts have been provided. The article contains statistical information on mild, severe, and lethal injuries caused by rock bursts in coal mines of the Kuznetsk coal basin. Multifunctional safety systems able to obtain information on the condition of rock mass have been analyzed. Special attention has been paid to the system of current control and forecast of rock mass conditions based on the «Mikon-GEO» system. In the majority of cases, based on the problems to solve, such a system is a part of multifunctional safety systems. The authors suggest that the forecast methodology is to be based on the data obtained by such systems operating based on the seismoacoustics principles. The mathematical model using the source data obtained from the «Mikon-GEO» system has been considered. The calculation algorithm enabling the assessment of the rock burst probability has been provided. The algorithm and the results of measurements of rock mass basic parameters are used to determine the individual risk value that is advisable to compare with the average value of occupational risk at production. The results obtained by the authors have been tested in one of the Kuznetsk Basin coal mines. The preliminary results of the forecast methodology use have shown the relevance of the studies and identified certain issues requiring specification and further research.

Recognition and Prediction of Precursory Feature Signals of Coal Mine Rock Burst Based on Random Forest and MK Trend Test

This paper aims to identify and predict the precursory characteristic signals of coal mine rock burst by employing the Random Forest and MK (Mann-Kendall) trend test methods. Initially, the study conducts data preprocessing and analysis on indicators such as electromagnetic radiation intensity, acoustic wave intensity, and type. It uses clustering methods to distinguish various data types and analyzes the data after visual representation. The visualization of data illustrates the distribution and trends, which aids in understanding the characteristics of the data, such as the upward trend observed in precursory feature data. During the data preprocessing phase, diagrams of various classes of data for Acoustic Emission (AE) and Electromagnetic Radiation (EMR) intensity are presented, providing an intuitive reference for subsequent analysis. The research utilizes the Random Forest algorithm and MK trend test to recognize precursor signals and predict their occurrence intervals. The Random Forest model is chosen for its efficiency and accuracy in handling classification and regression issues, while the MK trend test provides a statistical basis for identifying precursory signals by analyzing monotonic trends within the dataset. This study not only enhances the accuracy of precursory signal identification for coal mine rock bursts but also offers scientific early warning and control measures for coal mine safety production, which is of significant practical value.

Damage evolution of coal with a strong bursting liability and 3D measurement method for elastic deformation energy distribution

When coal with a strong bursting liability is disturbed by a load, catastrophic instability disasters and rockbursts can easily occur. Loaded coal with a strong bursting liability undergoes complex damage evolution and failure behavior due to the intricate interplay among loads, gangue, fractures, and the coal matrix. Intuitively quantifying and characterizing the complex discontinuous structural features, deformation fields, and energy fields within coal is the foundation for the scientific analysis and prevention of disaster mechanisms caused by rockbursts. Therefore, studying the distribution and evolutionary processes of deformation fields and energy fields caused by the evolution of discontinuous structures within coal is highly important for the prevention and control of coal mine rockburst disasters and the protection of coal mine safety during mining operations. In this study, a series of X-ray computed tomography (X-CT) tests were conducted on coal specimens with varying gangue contents under uniaxial compressive loading. The X-CT images clearly illustrated the internal damage evolution of coal with a strong bursting liability, revealing fracture propagation, shear bands, and localized failure under varying loading conditions. Image segmentation was employed to quantitatively analyze the development of damage in coal with a strong bursting liability, revealing the influence patterns of gangue content on the prepeak deformation localization and strength of coal. Additionally, using digital volume correlation, the 3D volumetric displacement and strain of loaded impact-prone coal were determined based on the changes in natural speckle images. The nonuniform distribution of strain was mainly caused by the nonuniform distribution of gangue and pore fractures at the microscopic scale, which explains the localized deformation in coal materials. Importantly, this study provides new full-field strain tensor data and a novel method for measuring the elastic deformation energy of the 3D deformation and cracking processes of loaded coal.

Risk prediction of coal mine rock burst based on machine learning and feature selection algorithm

ABSTRACT With the intensification of coal mining in China, rock burst hazards have become increasingly frequent and serious. To comprehensively investigate the accident indicators during mining activities, identify the key triggering factors, and better prevent rockburst accidents, this study establishes a rockburst risk prediction index system containing 16 indicators in four subsystems: geological structure, mining technology, safety management, and employee situation. By using 118 cases as sample data, this study proposes to apply four feature selection methods (Boruta, PC, RF, BE) to reveal the relationship between these indicators and select the most salient indicators for risk prediction. Then four machine learning algorithms, namely Random Forest (RF), Gradient Boosting Machine (GBM), SVM, and KNN are used to compare the effects of different feature selection methods on the prediction accuracy of risk level. The results show that Boruta performs best as a feature selection method for RF, GBM, and KNN, and the Boruta-RF model has better predictive performance than the others.

Influence of pre-existing crack on rockburst characteristics in coal-rock combination: A laboratory investigation

The existing cracks in the roof rock are critical to stability of the coal-rock combination structure during mining activities, which is vital for safe exploitation in coal mines. However, the physical mechanisms by which pre-existing crack in the roof rock induces rockburst in coal mines are still poorly understood. In this study, to investigate the rockburst characteristics in an underground mine, triaxial compressive experiments on coal-rock combinations containing a pre-existing crack in the roof rock were carried out. Both mechanical and failure behaviours of composite specimen containing a pre-existing crack were analysed. The testing results showed that a pre-existing crack in roof significantly affects mechanical properties of combinations. The average peak stress and average elastic modulus of specimen exhibit an M-shaped change trend when dip angle is in a range of 0°–90°. The average peak strain increases before decreasing with increase in dip angle. In addition, the roof rock is more likely to fail when it contains a pre-existing crack. Both the initial failure location and failure pattern of combinations are highly related to angle of pre-existing crack. A novel rockburst model considering in-situ stress and pre-existing crack was proposed to determine the physical mechanism of rockburst. The findings are useful to understand characteristics and physical mechanism of rockburst in mine engineering.

Study on the technical management practice of rock burst prevention and control - Case study of Yankuang Energy Group Company Limited

To ensure the on-site implementation of regulations and technical measures for rock burst prevention and control, taking Yankuang Energy Group Company Limited. as an example, an on-site technical management system for preventing and controlling rock burst in coal mines is established. This on-site technical management system is based on the principles of “zero rock burst accident”, “graded management and control”, “general manager and chief engineer responsibility”, and “scientific, systematic, streamlined, and efficient management”. This system includes a technical management system and an on-site management mode, among which the former includes an organizational system, an institutional system, a technical data management system, and a comprehensive supervision and management system. Each system is interrelated, mutually promoting and supporting the other system. The on-site management mode includes five aspects and six links. These “five aspects” refer to the standardization of safe production, normalization of on-site operations, processization of system operation, quantification of antirisk ability, and demonstration of mine management. The “six links” on-site management mode includes the management system, source risk management and control, dynamic risk analysis, monitoring and control, on-site implementation and management, and emergency management. The construction of an on-site technical management system for rock burst prevention and control can ensure the timely detection and rectification of problems, remove management loopholes, and prevent the occurrence of rock burst disasters.

Research on the Laws of Overlying Rock Fracture and Energy Release under Different Mining Speeds

Mining activities are key triggers for strong mine earthquakes and even rock bursts in coal mines. This study explores the impact of mining speed on the overlying strata’s deformation and energy release through theoretical analysis, numerical simulation, and the digital speckle method. The temporal and spatial evolution characteristics of the impact energy during mining are simulated. The digital speckle method illustrates a positive correlation between rapid mining and increased fracture block degree of overburden rock and roof separation, confirming that accelerated mining speed extends the fracture distance of the stope. Furthermore, numerical simulations establish that both the energy associated with overlying rock breaking and the frequency of energy occurrence events are amplified during rapid mining, in contrast to slow mining. This observation corroborates that escalating mining speed augments the energy dispensed by the breaking of the upper rock. Consequently, this escalation induces a transformation in the energy levels of mine earthquakes, culminating in a heightened incidence of large-energy mine earthquakes.

Roadway rock burst prediction based on catastrophe theory

In order to quantitatively calculate the critical depth and critical load of mines affected by rock burst, and to achieve effective prevention and control of rock burst in coal mines, this paper proposes a mechanical model for predicting the occurrence of rock burst in coal mine roadways based on catastrophe theory. Additionally, a theoretical calculation formula for initiating rock burst is derived. The first step was to establish a mechanical analysis model, which directly correlated with the in-situ stress, physical and mechanical characteristics of the coal-rock mass, and engineering structural parameters. Following this, a mechanical instability criterion was derived for the key load-bearing circle within the surrounding rock of the roadway. In the final step, the critical depth and load for rock burst initiation were verified for 25 distinct coal mines in China that were prone to rock burst hazards. The research results demonstrate that the discrepancy between the theoretically calculated critical depth and the actual measured statistical values was less than 35%. In addition, the difference between the theoretically determined critical depth and the value calculated by Pan Yishan was less than 32%. Notably, the ratio of the theoretically calculated critical load to the uniaxial compressive strength of the coal-rock mass ranged from 0.38 to 1.93. This aligns with empirical data on rock burst occurrences, as set out in the engineering classification standards for rock masses. These research outcomes substantiated the practical utility of the proposed theory, thereby laying a robust theoretical groundwork for the quantitative control of rock burst.

Mechanism and early warning of coal mine rockburst accident based on SD-STAMP-DEMATEL

As coal mines shift from shallow to deeper excavation, the number of mines facing the risk of rock burst disasters is gradually increasing. Rockburst, with their characteristics of vibration, suddenness, complexity, and unpredictability, make it increasingly difficult to prevent and control these disasters. Therefore, the challenges of preventing and controlling rock burst disasters are becoming more and more severe. This paper, based on the system-theoretic accident model and processes (STAMP) theory, extracts the causal factors affecting coal mine rock burst accidents. Using the interpretative structural modeling (ISM) and decision-making trial and evaluation laboratory (DEMATEL) method, the accident-causing factors are quantitatively assigned. By constructing model equations and drawing causal loop diagrams and stock-flow diagrams, the event is dynamically simulated and early warnings are issued. The results show that the control defects leading to the accident are analyzed from the perspectives of the government level, management level, grassroots level, physical layer, and the dynamic process of the accident. In the short term, safety investment in grassroots operations is the most effective control. In the long run, the most effective measure is for the management level to strengthen its supervisory work. By changing the input ratios of various variables, it can be seen that different variables in the system dynamics (SD) model have different impacts on coal mine rock burst accidents. It is necessary to continuously strengthen the implementation of the safety responsibility system, improve the work efficiency of the government and management level, and enhance the timeliness of emergency decision-making.

Research on the causal mechanism of a rock burst accident in a longwall roadway and its prevention measures

Based on the disaster characteristics and the geo-conditions at the scene, in this study, the occurrence mechanism of a serious rock burst accident that occurred in the Tangshan Coal Mine, China, was analysed. Ground stress measurements showed that the mine is in a high ground stress area dominated by horizontal tectonic stress around 33 MPa. Laboratory testing revealed that the coal was a hard seam of 8.3 MPa over bedded by a thick and hard roof stratum with uniaxial compressive strength of 66 MPa. The calculation results indicated that the accident occurred in the roof rebounding area. It is proposed that the hard roof and the hard coal seam formed a seesaw structure around the working face. The vertical pressure relief caused the rib coal mass to lose its clamping forces from the roof and floor and rush into the roadway, resulting in a rock burst accident. Based on the causality mechanism of the rock burst disaster developed in this study, pertinent coal bump prevention measures have been undertaken in practice. Large-diameter boreholes were drilled to eliminate the pivot effect of the seam. Roof blasting was undertaken to prevent the roof from forming a seesaw plank. To summarize, a new causality mechanism for rock burst in coal mines under hard roof and hard seam geo-conditions was developed.

Microseismic Signal Characteristics of the Coal Failure Process under Weak-Energy and Low-Frequency Disturbance

In deep mining, “critical static stress + slight disturbance” is an important inducing form of coal mine rockburst disasters. In previous studies, the critical static stress has been shown to be consistent with the loading direction of a slight disturbance but cannot reflect all types of rockbursts. In addition, the research that uses microseismic (MS) signals to reflect the overall process and critical stages of coal failure and instability under weak-energy and low-frequency disturbance conditions is immature, and more information, such as the critical state, has not been fully revealed. The aims of this paper are to further elucidate the important role of weak-energy and low-frequency disturbances in the occurrence of rockburst disasters. First, briquette samples were prepared from the Tashan Coal Mine, which is severely affected by rockbursts, and their homogeneity was verified using ultrasonic longitudinal wave velocity. Second, the natural frequency of the coal sample specimens was measured using a testing system. Then, based on the self-developed static pressure loading system, dynamic and static combined loading test system and MS signal monitoring device, the MS signal characteristics during the process of coal body failure and instability were comprehensively analysed. Finally, a comparison was made between weak-energy and low-frequency disturbances and impact disturbances. The results are summarized as follows. (1) The longitudinal wave velocity test results reflect that the briquette samples prepared in the experiment have high homogeneity. The smaller the particle size is, the higher the density and moulding pressure, and the denser the sample. (2) The natural frequency of the briquette samples is between 30.79 Hz and 43.34 Hz, and most of them fluctuate at approximately 35 Hz. (3) During the static loading stage, the occurrence of more than three MS signals of larger magnitude in a continuous cluster is an important criterion for the critical failure of the samples. (4) The weak-energy and low-frequency disturbance actually leads to fatigue damage, and the briquette sample experiences three stages: the near-threshold stage, the high-speed expansion stage and the final fracture stage. The smaller the particle size of the coal sample, the denser the specimen, the stronger the amplitude and energy of the single effective MS signal formed during the destruction process, the longer the time duration of crack expansion from the near-threshold stage to the high-speed expansion stage, and the stronger the ability of the coal sample to resist weak-energy and low-frequency disturbances. This study may contribute to a more comprehensive understanding of the destabilization mechanism of coal bodies and MS signal characteristics under weak-energy and low-frequency disturbances and provide a reference for further research and discussion.

Coal Mine Rock Burst and Coal and Gas Outburst Perception Alarm Method Based on Visible Light Imagery

To solve the current reliance of coal mine rock burst and coal and gas outburst detection on mainly manual methods and the problem wherein it is still difficult to ensure disaster warning required to meet the needs of coal mine safety production, a coal mine rock burst and coal and gas outburst perception alarm method based on visible light imagery is proposed. Real-time video images were collected by color cameras in key areas of underground coal mines; the occurrence of disasters was determined by noting when the black area of a video image increases greatly, when the average brightness is less than the set brightness threshold, and when the moving speed of an object resulting in a large increase in the black area is greater than the set speed threshold (V > 13 m/s); methane concentration characteristics were used to distinguish rock burst and coal and gas outburst accidents, and an alarm was created. A set of disaster-characteristic simulation devices was designed. A Φ315 mm white PVC pipe was used to simulate the roadway and background equipment; Φ10 mm rubber balls were used to replace crushed coal rocks; a color camera with a 2.8 mm focal length, 30 FPS, and 110° field angle was used for image acquisition. The results of our study show that the recognition effect is good, which verifies the feasibility and effectiveness of the method.

Simulation of the Damage and Failure Characteristics of Coal under True Triaxial Static–Dynamic Loads

The damage evolution rules for coal under true triaxial combined static–dynamic loads are important to understand and reveal the mechanism of rockburst in coal mines. The numerical simulation was carried out using FLAC3D to explore the coupling effect of static and dynamic stress, especially the influence of dynamic load parameters. The results show that the increase in dynamic load amplitude not only makes the plastic zone grow exponentially and shortens the damage development time, but also decreases the residual strength of the coal sample, which leads to a much more violent dynamic failure. The stress wave propagation can be more stable in the coal sample with the increase in dynamic load frequency and the development time of the plastic zone also shows synchronous fluctuating features, and when the frequency is like the intrinsic frequency of the coal sample, the dynamic load has a significant stimulation effect. The static and dynamic loads have different damage effects on the coal sample under the true triaxial stress path, the weight decreases in descending order, namely the minimum principal stress, the maximum principal, the amplitude of the dynamic load and, lastly, the dynamic stress frequency, according to the entropy weight method analysis.

Comprehensive early warning method of microseismic, acoustic emission, and electromagnetic radiation signals of rock burst based on deep learning

Microseismic, acoustic emission, and electromagnetic radiation monitoring methods are often used to monitor rock burst disasters in coal mines. In the process of coal mining, the time series characteristics and amplitude characteristics of microseismic, acoustic emission, and electromagnetic radiation data are mainly used to identify rockburst risk, but the results of risk identification through the three monitoring methods are quite different. Consequently, the accurate and comprehensive early warning of rock burst risk is still an urgent problem to be solved. The development of deep learning provides a new means for intelligent early warning of rock burst risk. In this paper, a comprehensive early warning method of microseismic, acoustic emission, and electromagnetic radiation (MS-AE-EMR) signals of rock bursts was proposed based on a deep learning algorithm. This method uses long short-term memory recurrent neural networks (LSTM-RNNs) to intelligently identify the MS-AE-EMR precursor signal of rock burst risk, predicts the MS-AE-EMR signal by a convolution neural network (CNN), analyses the MS-AE-EMR precursor signal of rock burst risk through the data analysis method and obtains the risk coefficient of rock burst. Moreover, by using the MS-AE-EMR original signal and risk coefficient, it trains the multi-input CNN and inputs the predicted signal into the trained multi-input CNN to obtain the predicted risk coefficient of rock burst. Analysing the risk coefficient completes the comprehensive early warning of the MS-AE-EMR signal of rock burst. After field verification, the RNN-based comprehensive early warning method of the MS-AE-EMR signal can respond positively to rock burst risk and capture the information in advance. Therefore, this method is of great significance for accurate monitoring and early warning of rock burst in coal mines.

Mechanism and Empirical Study of Rockburst in the Adjacent Area of a Fully Mechanized Top-Coal Caving Face Based on Microseismic Technology

Monitoring and providing warnings for coal mine rockburst disasters is a worldwide problem. Several rockburst accidents have occurred in a 1301 belt transport chute near a 1300 fully mechanized caving mine face. To address this issue, an empirical study of the occurrence mechanism of rockbursts in the adjacent area of the fully mechanized top-coal caving face was carried out. This paper mainly addresses the following issues: (1) based on microseismic monitoring technology, the distribution characteristics of the host-rock-supported pressure of the 1300 working face were measured, and the evolution and distribution of the deep-well caving working face host-rock-supported pressure were analyzed. It is revealed that the occurrence mechanism of rockburst in the adjacent area is actually caused by the evolution and superposition of the lateral abutment pressure of the 1300 stope, and the stress of the original rock along the 1301 belt transport down chute; (2) a theoretical calculation model of dynamic and static abutment pressure in longwall stope is built, and an example is tested. The results show that the peak position of lateral abutment pressure of the coal body outside the 1300 goaf is around 63 m, and the peak value of abutment pressure is around 47 MPa; (3) coal body stress monitoring, bolt dynamometer detection, and other means are compared and analyzed. At the same time, with the help of CT geophysical prospecting and drilling cutting measurements, it is concluded that the 1301 belt transport down chute is in the bearing pressure influence zone (superimposed zone), which further verifies the validity of microseismic analysis results and the accuracy of the above theoretical model. Based on this, the early warning system and prevention measures for rockburst based on microseismic monitoring are proposed. The engineering practice shows that the dynamic and static bearing pressure distribution and evolution law of the working face can be dynamically obtained by using microseismic technology, which provides a basis for the accurate prediction and treatment of rockbursts.

Application of vibration wave CT technology in the dynamic prediction of shock hazards

The vibration wave CT detection technology could be used for forecasting dynamic disasters such as coal and gas outburst and rock burst in coal mines as well as for dynamic monitoring and warning of impact risks. Based on the positive correlation between stress and vibration wave velocity and the positive abnormal distribution of vibration wave velocity, the impact danger area could be determined. Two evaluation indexes on the impact risk were constructed: the anomalous coefficient An and abnormal value Am of the gradient variation coefficient (VG) of wave velocity. The critical values of the two indexes corresponding to the impact risk degree were given. In addition, the field engineering practice was carried out by using the inversion results of vibration wave CT detection technology. Combined with the field engineering geological conditions, the impact risk area of the F15-24080 working face was defined comprehensively. The results showed high precision of this CT detection technology. Vibration wave CT detection technology could make dynamic prediction and evaluation of the impact risk on a site and provide guidance and test for the formulation and implementation effect of pressure relief measures in high-impact danger areas.

Disturbance response instability theory of rock bursts in coal mines and its application

Disturbance response instability theory of rock bursts in coal mines and its application

Multi-Index Geophysical Monitoring and Early Warning for Rockburst in Coalmine: A Case Study.

Rockburst is a major disaster in deep mining, restricting the safety and the production efficiency of the Laohutai Coal Mine in Fushun, Liaoning Province. To predict and prevent coalmine rockbursts, a comprehensive method based on multi-instrument monitoring is proposed by using a YDD16 acoustic-electromagnetic monitor and microseismic monitoring system, including microseismic (MS) monitoring, electromagnetic radiation (EMR) monitoring, and acoustic emission (AE) monitoring. Field investigation shows that MS, AE, and EMR signals have abnormal precursors before rockbursts in a new working face. Based on the fluctuation theory and D-S evidence theory, the multi-index geophysical monitoring and early warning technology for rockburst disasters in the Laohutai Coal Mine are established. The method has been applied to the prediction of rockbursts in the Laohutai Coal Mine. The application shows that the acoustic-electromagnetic synchronous monitoring and early warning technology can accurately identify the potential rockburst risk and trigger an early warning, which is more reliable than a single method. The case study of the Laohutai rockburst shows that the joint early warning method of multi-instrument comprehensive monitoring can predict the possibility of rockbursts.

Insights into fundamental problems of rockburst under the modern structure stress field

Rockbursts are some of the most severe dynamic disasters in coal mines. In this paper, the discrimination method of the tectonic stress field is proposed by analyzing the modern stress field in China. The tectonic stress field formed by modern tectonic movement guides in situ stress measurements. According to the stress state classification, most rockbursts in coal mines in China are closely associated with tectonic stress. For tectonic stress-driven rockbursts, modern tectonic movement and modern tectonic stress fields must be considered. The stress change and energy transfer caused by tectonic movement affect the geological structure where coal mines are located. Energy accumulation under rockburst conditions is mainly formed by natural geo-dynamic movement and the mining configuration, and energy accumulation is the basis for rockbursts. The application of the geo-dynamic environmental evaluation method to determine the coalfield geo-dynamic process and the influence of modern tectonic movement is proposed. Accordingly, the classification method of rockbursts in coal mines is established. Based on the distribution characteristics of modern tectonic conditions in China, it is revealed that these dynamic disasters follow a “110” distribution. Finally, a “three condition” criteria of rockbursts is proposed: the geo-dynamic environment is a necessary condition for rockbursts, mining disturbance is a sufficient condition for rockbursts, and risk-releasing measures are a condition controlling rockburst risk mitigation.

Research on Multifactor Analysis and Quantitative Evaluation Method of Rockburst Risk in Coal Mines

Abstract The prevention of rockbursts is significant to ensure mining safety in deep coal mines. The multifactor analysis and a new quantitative evaluation method for rockbursts in coal mines are proposed in this study. In the aspect of rockburst analysis, a multifactor system of rockburst risk based on the material, stress, and large-scale geological structure is proposed. The factors influencing rockbursts in coal mines are analyzed by numerical simulations. Based on a standard mining model, three comparative models considering the rockburst tendency, high stress, and geological structure are established. The distribution of maximum principal stress and plastic zone during the mining process is compared. The reasons why these three types of factors are liable to trigger rockbursts lie in generating high-stress zones in surrounding rock masses. In the aspect of quantitative evaluation, the monitored microseismic signal is selected as the key indicator, and the daily frequency of microseisms is analyzed. A normal distribution function based on the daily frequency of microseisms is established. The interval of daily frequency of microseisms is set to judge whether the microseismic frequency is abnormal and then determine the rockburst risk of coal mines. Considering the results of multifactor analysis, it is proposed that the monitoring system combining microseisms with stress is the direction to accurately and quantitatively evaluate the rockburst risk in the future. This study makes specific explorations in the quantitative evaluation of rockburst risk in coal mines.