Search Results (16)

The instability of mine roadways is significantly influenced by the coupled effects of groundwater seepage and non-uniform loading. These interactions often induce localized plastic deformation and progressive failure, particularly in the roof and sidewall regions. Seepage elevates pore water pressure and deteriorates the mechanical properties of the rock mass, while non-uniform loading leads to stress concentration. The combined effect facilitates the propagation of microcracks and the formation of shear zones, ultimately resulting in localized instability. This initial damage disrupts the mechanical equilibrium and can evolve into severe geohazards, including roof collapse, water inrush, and rockburst. Therefore, understanding the damage and failure mechanisms of mine roadways at the mesoscale, under the combined influence of stress heterogeneity and hydraulic weakening, is of critical importance based on laboratory experiments and numerical simulations. However, the large scale of in situ roadway structures imposes significant constraints on full-scale physical modeling due to limitations in laboratory space and loading capacity. To address these challenges, a straight-wall circular arch roadway was adopted as the geometric prototype, with a total height of 4 m (2 m for the straight wall and 2 m for the arch), a base width of 4 m, and an arch radius of 2 m. Scaled physical models were fabricated based on geometric similarity principles, using defect-bearing sandstone specimens with dimensions of 100 mm × 30 mm × 100 mm (length × width × height) and pore-type defects measuring 40 mm × 20 mm × 20 mm (base × wall height × arch radius), to replicate the stress distribution and deformation behavior of the prototype. Uniaxial compression tests on water-saturated sandstone specimens were performed using a TAW-2000 electro-hydraulic servo testing system. The failure process was continuously monitored through acoustic emission (AE) techniques and static strain acquisition systems. Concurrently, FLAC^3D 6.0 numerical simulations were employed to analyze the evolution of internal stress fields and the spatial distribution of plastic zones in saturated sandstone containing pore defects. Experimental results indicate that under non-uniform loading, the stress–strain curves of saturated sandstone with pore-type defects typically exhibit four distinct deformation stages. The extent of crack initiation, propagation, and coalescence is strongly correlated with the magnitude and heterogeneity of localized stress concentrations. AE parameters, including ringing counts and peak frequencies, reveal pronounced spatial partitioning. The internal stress field exhibits an overall banded pattern, with localized variations induced by stress anisotropy. Numerical simulation results further show that shear failure zones tend to cluster regionally, while tensile failure zones are more evenly distributed. Additionally, the stress field configuration at the specimen crown significantly influences the dispersion characteristics of the stress–strain response. These findings offer valuable theoretical insights and practical guidance for surrounding rock control, early warning systems, and reinforcement strategies in water-infiltrated mine roadways subjected to non-uniform loading conditions. Full article

Granite is widely used in laboratory rockburst simulations due to its exceptional strength, brittleness, and uniform composition. This study employs a true triaxial loading system to replicate asymmetric stress states near free surfaces, allowing precise control of three-dimensional stresses to simulate strain-mode rockbursts. Advanced monitoring tools, such as acoustic emission (AE) and high-speed imaging, were used to investigate the evolution process, failure mechanisms, and monitoring strategies. The evolution of strain-mode rockbursts is divided into five stages: stress accumulation, crack initiation, critical instability, rockburst occurrence, and residual stress adjustment. Each stage exhibits dynamic responses and progressive energy release. Failure is governed by a tension–shear coexistence mechanism, where vertical splitting and diagonal shear fractures near free surfaces lead to V-shaped craters and violent rock fragment ejection. This reflects the brittle nature of granite under high-stress conditions. The AE monitoring proved highly effective in identifying rockburst precursors, with key indicators including quiet periods of low AE activity and sudden surges in AE counts, coupled with ‘V-shaped’ b-value troughs, offering reliable early warning signals. These findings provide critical insights into strain-mode rockburst dynamics, highlighting the transition from elastic deformation to dynamic failure and the role of energy release mechanisms. Full article

Early warning for rock blasting is crucial for ensuring the safety of deep underground engineering. Existing methods primarily focus on classifying rock blasting levels, which makes it difficult to provide timely warnings. This paper proposes a novel early warning framework for rock blasting based on time series prediction of acoustic emission (AE) parameters. Based on uniaxial rock tests, ten AE parameters (rise time, ring count, energy, duration, amplitude, average frequency, RMS voltage, average signal level, peak frequency, and initial frequency) are identified as potential indicators for rock blasting early warning. These ten parameters collectively affect the accuracy of AE monitoring. Factor analysis is employed to process the normalized AE data, simplifying the data structure and identifying common variables. Additionally, it is found that the BP neural network optimized by Particle Swarm Optimization (PSO) is more suitable for predicting the future evolution of these AE parameters. This makes it possible to establish a comprehensive multi-indicator early warning system. The proposed framework provides a new perspective for rock blasting early warning systems. Full article

Rockburst is a common dynamic geological disaster in underground mining and tunneling engineering, characterized by randomness, abruptness, and impact. Short-term evaluation of rockburst potential plays an outsize role in ensuring the safety of workers, equipment, and projects. As is well known, microseismic monitoring serves as a reliable short-term early-warning technique for rockburst. However, the large amount of microseismic data brings many challenges to traditional manual analysis, such as the timeliness of data processing and the accuracy of rockburst prediction. To this end, this study integrates artificial intelligence with microseismic monitoring. On the basis of a comprehensive consideration of class imbalance and multicollinearity, an innovative modeling framework that combines local outlier factor-guided synthetic minority oversampling and an extremely randomized forest with C5.0 decision trees is proposed for the short-term evaluation of rockburst potential. To determine the optimal hyperparameters, the whale optimization algorithm is embedded. To prove the efficacy of the model, a total of 93 rockburst cases are collected from various engineering projects. The results show that the proposed approach achieves an accuracy of 90.91% and a macro F₁-score of 0.9141. Additionally, the local F₁-scores on low-intensity and high-intensity rockburst are 0.9600 and 0.9474, respectively. Finally, the advantages of the proposed approach are further validated through an extended comparative analysis. The insights derived from this research provide a reference for microseismic data-based short-term rockburst prediction when faced with class imbalance and multicollinearity. Full article

The Shuangjiangkou hydropower station in China has complex geological conditions with high in situ stress. During the tunnel excavation, rockbursts occurred frequently, which seriously affected construction progress. Microseismic (MS) monitoring technology was used to explore rock MS activities to predict rockbursts. The MS monitoring system can capture a large number of MS signals. Based on Hilbert–Huang transform (HHT) instantaneous frequency analysis technology, using MATLAB software (R2022a) to write a program to convert the MS waveform, the frequency and energy characteristics of MS signals at a certain time can be obtained. By analyzing the frequency and energy characteristics of every event, the microseism active areas can be determined, and then rockbursts can be predicted scientifically. This paper selected two different construction sites, which were the main powerhouse and the access tunnel in the main powerhouse, as the research background. Introducing HHT instantaneous time–frequency analysis technology conducted MS event dynamic analysis and predicted rockbursts. The HHT spectrum scientifically and comprehensively displayed MS signal frequency characteristics at a certain time and reflected the change laws of signal instantaneous energy and local abrupt change information. The results indicated that some parameter anomalies in the event spectrum can predict rockbursts. For complex tunnel construction conditions, the HHT time–frequency analysis technology can realize a new idea of using a single-channel signal to predict rockbursts, which was very meaningful. Full article

Choosing reasonable control measures for different intensity rockburst risks not only effectively prevents and mitigates rockburst risks but also reduces time and engineering investment costs. Due to the limitations of the tunnel boring machine’s structure and working conditions, tunnels excavated by TBMs are highly susceptible to rockbursts. What is even worse is that there are very few measures to control the rockburst risk in these tunnels. Implementing reasonable control measures from the limited mitigation measures to control and mitigate rockburst in TBM tunnels is an urgent problem that warrants a solution. In this paper, a large number of on-site rockburst risk control cases and a large amount of MS monitoring data (the total mileage of MS monitoring is approximately 7 km, lasting for 482 days) are used to derive a reasonable scheme to control the rockburst risk of different intensities in twin TBM tunnels. First, the rockburst early warning effect of the two headrace tunnels of the Neelum–Jhelum hydropower station based on microseismic monitoring is analyzed. Second, based on highly accurate rockburst warning results, 94 rockburst risk control cases are applied to analyze the control effect of different control measures at different intensities of rockburst risk. Then, by combining factors such as the time cost and expense cost of different control measures, more reasonable control measures for different intensity rockburst risks are proposed: for slight rockburst risk, normal excavation is preferred; for moderate rockburst risk, horizontal destress boreholes are preferred; and for intense rockburst risk, a combination of measures of shortening daily advance and horizontal destress boreholes is preferred. The research results can provide a reference for other TBM excavation projects to carry out rockburst risk prevention and mitigation. Full article

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. Full article

During excavation in a deep tunnel, dynamic disaster is an extremely severe impact failure. The necessity of an energy-absorbing support system is analyzed for different characteristics of dynamic disaster (rockburst) failure. The energy-absorbing support system design includes a combination of early-warning, energy-absorbing bolts, and other components. This support system is designed to meet the energy requirement of a rockburst disaster based on an early warning. The energy-absorbing rockbolt uses the stepwise decoupling technique to realize the brittle-ductile transition of the structure, which is referred to as a stepwise decoupling rockbolt (SD-bolt). The ultimate force, ultimate deformation, and energy were calculated as 241 kN, 442.3 mm, and 95.89 kJ under static pull-out load. Monitored by a microseismic system, the support system was tested by moderate rockburst disaster impact on site. Considering similar rockburst disaster failure cases, this energy-absorbing support system can reduce rockburst disaster damage to a certain extent and improve overall safety during deep engineering construction. Full article

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. Full article

Based on CiteSpace software, this paper reviews and analyzes the application articles of acoustic emission in coal from 2010 to 2020. In this paper, CiteSpace software visualizes 453 articles collected in the Web of Science core database. The cooperation networks between different countries, institutions, and authors are used to determine the connection of knowledge in papers. The keyword co-occurrence, keyword co-occurrence time zone map, and keyword clustering are used to determine the hot topics in the field. The cited collaborative network analysis reveals the important literature and the contribution of prominent authors in this area. In the future, for the research of acoustic emission in coal mining, compression tests will still be the main test methods. In terms of time domain parameters of acoustic emission, the application of ring counting, energy, waveform, and signal strength are very mature. The principal problem of acoustic emission location operation will become a focus in the future. The most widely used patterns in the determination of ruptures are the signal intensity fractal dimension, the acoustic emission number, and the b-value. In practical engineering problems, there is little research on the deformation activity law of steeply inclined coal seams and surrounding rock. The mining of steeply inclined coal seams is still a difficult problem. There are immature technologies in coal mining, rockburst early warning, and coal and gas outburst. In terms of the intellectualization and accuracy based on experience, there is room for improvement in the future. Scholars will continue a deeper exploration on the application of the numerical simulation. Full article

The time–frequency characteristics of electromagnetic radiation (EMR) waveform induced by rock fracture are very important to the monitoring and early–warning using the EMR method for the mine rockburst. The empirical wavelet transform (EWT), as a waveform time–frequency analysis method, has the advantages of a clear theoretical basis, convenient calculation, and no modal aliasing. To apply EWT to the field of EMR time–frequency analysis, the operation of Fourier axis segmentation of EWT is improved. In detail, the adaptive selection method for a window width of closing operation and the adaptive determination method of segment number of Fourier axis are proposed for EWT. The Fourier axis obtained by short–time Fourier transform (STFT) is used in the EWT process, rather than that obtained by discrete Fourier transform (DFT), taking a better Fourier axis segmentation effect. The improved EWT together with Hilbert transform (HT) applied to the time–frequency analysis for the EMR waveform of rock fracture, and the time–frequency spectrum obtained by EWT–HT can well describe the time–frequency evolution characteristics. Compared with STFT and Hilbert–Huang transform (HHT), EWT–HT has significant advantages in time–frequency resolution and overcoming modal aliasing, providing a powerful tool for time–frequency analysis for the EMR waveform induced by rock fracture. Full article

In order to explore the evolution characteristics of multi-scale rock-like material failure, we studied the acoustic emission (AE) and electromagnetic radiation (EMR) characteristics of different scale rock-like materials by using the AE-EMR experimental system of coal and rock failure, and the AE and EMR response law of rockburst in mining sites was analyzed. The results show that under uniaxial loading, the stress–strain curve of the specimen has a compaction stage, linear elastic stage, elastic–plastic stage and failure stage. The cumulative AE count, AE energy and stress level of the specimen have an exponential relationship during loading and compression. The cumulative EMR counts of loading and unloading showed a trend of first decreasing and then increasing with the increase in stress level. Electromagnetic radiation and microseismic hypocentral distance show an abnormal change trend when rockburst occurs, and this abnormal phenomenon can be used as a precursor feature signal for rockburst monitoring and early warning. Full article

Rockburst hazards pose a severe threat to mine safety. To accurately predict the risk level of rockburst, a LightGBM−TCN−RF prediction model is proposed in this paper. The correlation coefficient heat map combined with the LightGBM feature selection algorithm is used to screen the rockburst characteristic variables and establish rockburst predicted characteristic variables. Then, the TCN prediction model with a better prediction performance is selected to predict the rockburst characteristic variables at time t + 1. The RF classification model of rockburst risk level with a better classification effect is used to classify the risk level of rockburst characteristic variables at time t + 1. The comparison experiments show that the rockburst characteristic variables after screening allow a more accurate prediction. The overall RMSE and MAE of the TCN prediction model are 0.124 and 0.079, which are better than those of RNN, LSTM, and GRU by about 0.1–2.5%. The accuracy of the RF classification model for the rockburst risk level is 96.17%, which is about 20% higher than that of KNN and SVM, and the model accuracy is improved by 1.62% after parameter tuning by the PSO algorithm. The experimental results show that the LightGBM−TCN−RF model can better classify and predict rockburst risk levels at future moments, which has a certain reference value for rockburst monitoring and early warning. Full article

Due to the different geological conditions and construction methods associated with different projects, rockbursts in deep-buried tunnels often present different precursor characteristics, bringing major challenges to the early warning of rockbursts. To adapt to the complexity of engineering, it is necessary to review the latest advancements in rockburst early warning and to discuss general early warning methods. In this article, first, microseismic monitoring and localization methods applicable under tunneling construction are reviewed. Based on the latest engineering examples and research progress, the microseismic evolution characteristics of the rockburst formation process are summarized, and the formation process and mechanism of structure-type and delayed rockbursts are analyzed. The different methods for predicting the risk and level of rockbursts using microseismic indices are reviewed, and the implementation methods and application cases for predicting potential rockburst areas and rockburst probability based on a mechanical model are expounded. Finally, combined with the new practice in early warning methods, development directions for the early warning of rockbursts are put forward. Full article

Early warning of a potential rockburst risk and its area of occurrence helps to take effective and targeted measures to mitigate rockburst hazards. This study investigates the microseismic (MS) spatial-temporal precursory characteristic parameters in a typical steeply inclined and extremely thick coal seam (SIETCS) with high rockburst risk and proposes three spatial/temporal quantification parameters and a spatial-temporal early warning method. Analysis results of temporal parameters show that the sharp-rise-sharp-drop variation in total daily energy and event count can be regarded as a precursor for high energy tremor. The appearance of peak values of both energy deviation (≥20) and event count deviation (≥1) can be regarded as precursors that indicate imminent rockburst danger. A laboratory acoustic emission (AE) experiment reveals that precursor characteristics obtained from the study can be feasibly used to warn the rockburst risk. The spatial evolution laws of spatial parameters show that the high energy density index of MS (EDIM), velocity, velocity anomaly regions correlate well with stress concentration and rockburst risk areas. The field application verifies that the temporal-spatial early warning method can identify the potential rockburst risk in a temporal sequence and rockburst risk areas during the temporal early warning period. Full article