Search Results (216)

This study suggests a method for analyzing the risk of methane explosions using the N-K model and Social Network Analysis (SNA) to understand how different risk factors related to coal-mine methane explosions are connected and change over time, aiming to prevent these accidents effectively. We identified 41 secondary risk factors and four fundamental risk factors—human, equipment, environment, and management—based on the 4M accident causation theory. The SNA model was utilized to determine the main risk factors and their evolutionary routes, while the N-K model was utilized to quantify the degree of risk coupling. The findings show that the number of risk variables engaged in the methane-explosion risk system closely correlates with the number of accidents that occur and the maximum coupling level among the four elements. The primary control factors in the methane-explosion risk system are poor equipment management, broken safety monitoring and control systems, inadequate safety education and training, safety regulation violations, and poor safety production responsibility system implementation. We utilized the primary evolution paths and key elements to propose risk control approaches. A reference for ensuring safety in coal-mine operations can be found in the research findings. Full article

Natech events, involving multi-hazard coupling and cascading effects, pose serious threats to coal mine safety. This paper addresses flood-induced Natech scenarios in coal mining and introduces a two-stage cascading analysis framework based on hazard systems theory. A tri-layered network—comprising natural hazards, exposed elements, and secondary hazards—models hazard propagation. In Stage 1, an improved adjacency information entropy algorithm with multi-hazard coupling coefficients identifies critical exposed elements. In Stage 2, Dijkstra’s algorithm extracts key risk transmission paths. A dual-dimensional classification method, based on entropy and transmission risk, is then applied to prioritize emergency responses. This method integrates the criticality of exposed elements with the risk levels associated with secondary disaster propagation paths. Case studies validate the framework, revealing: (1) Hierarchical heterogeneity in the network, with surface facilities and surrounding hydrological systems as central hubs; shaft and tunnel systems and surrounding geological systems are significantly affected by propagation from these core nodes, exhibiting marked instability. (2) Strong risk polarization in secondary hazard propagation, with core-node-originated paths being more efficient and urgent. (3) The entropy-risk classification enables targeted hazard control, improving efficiency. The study proposes chain-breaking strategies for precise, hierarchical, and timely emergency management, enhancing coal mine resilience to flood-induced Natech events. Full article

In the coal industry, miner safety is increasingly challenged by growing mining depths and complex environments. The failure to wear Personal Protective Equipment (PPE) is a frequent issue in accidents, threatening lives and reducing operational efficiency. Additionally, existing PPE datasets are inadequate for model training due to their small size, lack of diversity, and poor labeling. Current methods often struggle with the complexity of multi-scenario and multi-type PPE detection, especially under varying environmental conditions and with limited training data. In this paper, we propose a novel minersPPE dataset and an improved algorithm based on YOLOv8, enhanced with Dilated-CBAM (Dilated Convolutional Block Attention Module) and DBB (Diverse Branch Block) Detection Block (YOLOv8-DCDB), to address these challenges. The minersPPE dataset constructed in this paper includes 14 categories of protective equipment needed for various body parts of miners. To improve detection performance under complex lighting conditions and with varying PPE features, the algorithm incorporates the Dilated-CBAM module. Additionally, a multi-branch structured detection head is employed to effectively capture multi-scale features, especially enhancing the detection of small targets. To mitigate the class imbalance issue caused by the long-tail distribution in the dataset, we adopt a K-fold cross-validation strategy, optimizing the detection results. Compared to standard YOLOv8-based models, experiments on the minersPPE dataset demonstrate an 18.9% improvement in detection precision, verifying the effectiveness of the proposed YOLOv8-DCDB model in multi-scenario, multi-type PPE detection tasks. Full article

Roof water inrush accidents in coal mine driving roadways occur frequently in China, accounting for a high proportion of major coal mine water hazard accidents and causing serious losses. Aiming at the lack of research on the mechanism of roof water inrush in driving roadways and the difficulty of predicting water inrush accidents, this paper constructs a local damage criterion for coal–rock mass and a seepage–fracture coupling model based on peridynamics (PD) bond theory. It identifies three zones of water-conducting channels in roadway surrounding rock, the water fracture zone, the driving fracture zone, and the water-resisting zone, revealing that the damage degree of the water-resisting zone dominates the transformation mechanism between delayed and instantaneous water inrush. A discriminant function for the effectiveness of water-conducting channels is established, and a single-index prediction and evaluation system based on damage critical values is proposed. A “geometry damage” dual-control water inrush prediction model within the PD framework is constructed, along with a non-local action mechanism model and quantitative prediction method for water inrush. Case studies verify the threshold for delayed water inrush and criteria for instantaneous water inrush. The research results provide theoretical tools for roadway water exploration design and water hazard prevention and control. Full article

Ensuring employee safety is a top priority for every enterprise, and it is especially critical in high-risk industries like coal mining. To achieve this goal, it is essential to focus efforts on identifying existing hazards and thoroughly assessing the associated risks. Accurate identification and detailed characterization of occupational hazards play a pivotal role in the occupational risk assessment process, providing the foundation for effective safety strategies. This article presents an analysis of the process of identifying occupational hazards in hard coal mining, based on applicable legal regulations and a review of the relevant literature. The analysis reveals, on the one hand, a diversity of approaches to hazard classification, and on the other, a limited use of the characteristic features of hazards in classification processes. The findings of this review form the basis for proposing a systematic classification of occupational hazards in hard coal mining, taking into account the specific features of hazards in relation to their sources and potential consequences. The proposed classification not only categorizes hazards but also describes the specifics of hazard sources, such as environmental conditions, machinery, chemicals, and human factors, as well as the possible outcomes of these hazards, including physical injury, health impacts, and even fatalities. The aim of this article is to present a proposed classification of occupational hazards in hard coal mining and to provide a detailed characterization of these hazards based on the description of their sources and potential consequences. The proposed approach, grounded in the identification of characteristic features of hazards, facilitates the effective selection of preventive measures that can be implemented to reduce risk and improve workplace safety. Due to the presence of the full spectrum of natural hazards in Polish hard coal mining, the analysis draws on available statistical data, focusing on those hazards that contribute most significantly to fatal accidents and serious injuries. In conclusion, the article emphasizes the importance of a structured and systematic approach to identifying and assessing occupational hazards in the coal mining industry. By drawing on legal and literature-based insights, it aims to contribute to the development of more effective safety practices that protect workers and minimize the occurrence of workplace accidents and illnesses. Full article

The exploration of the statistical characteristics and distribution patterns of workplace accidents can help to reveal the intrinsic features and general laws of safety issues, which is essential for forecasting and decision making in safe production. Here, we conduct the detailed analysis of the distribution characteristics between the fatality number and the frequency of workplace accidents based on the in-depth data mining of various industries. The results show that the distribution between the fatality number and the frequency of workplace accidents follows a power-law distribution. Moreover, the exponents of such power-law distributions in different industries exhibit significant industry dependence, with the characteristic values of the power-law exponents in the coal mining industry, the hazardous chemicals industry, the transportation industry, and the construction industry being 1.55, 2.16, 2.15, and 2.92, respectively. Meanwhile, the temporal variation in the power-law distribution exponent in each industry can be used for the short-term prediction and evaluation of safe production, which will inform the decision making of the safety management department. Last, but not the least, the results of this study provide the theoretical basis for Heinrich’s Law and confirm that a substantial reduction in the number of small-scale accidents can effectively help control the frequency of large-scale fatal accidents. Full article

To address the challenges in the collaborative control of strong mine pressure and surface damage during fully mechanized shallow soft coal seam top-coal caving mining, this study takes the 22,031 working face of Xindeng (Zhengzhou, China) Coal Mine as the research background. By combining analytical modeling and discrete-element granular flow simulation, this research elucidates how overburden fractures evolve and how the ground surface responds throughout the mining of shallow, soft coal seams. This research shows that the mechanical model analysis based on plate theory indicates that the first fracture of the immediate roof occurs 0.5 m from the goaf side of the mined-out area. Numerical simulations demonstrate that when the working face advances 80 m, the mining-induced influence extends to the surface. The displacement field of the overburden undergoes a dynamic temporal evolution law following the sequence of “rectangle–trapezoid” → “hyperbola-like” → “trapezoid”. During the advancement of the working face, the fracture pattern of the overburden evolves from “rectangle–trapezoid” to “trapezoid”, and the affected range on the surface transforms from an “inverted trapezoid” to a “trapezoid”. This study ultimately clarifies the dynamic law of collaborative deformation between the overburden and the surface, providing a theoretical basis for the safe mining of shallow coal seams, the prevention of roof accidents, and the optimization of mining technology. Full article

The ability to predict the volume of methane outbursts in coal mines is critical for the prevention of methane outburst accidents and the assurance of coal-mine safety. This paper’s central argument is that existing prediction models are limited in several ways. These limitations include the complexity of the models and their poor ability to generalize. The paper proposes a methane outburst volume-prediction and early-warning method. This method is based on a secondary decomposition and improved TSMixer model. First, data smoothing is achieved through an STL decomposition–adaptive Savitzky–Golay filtering–reconstruction framework to reduce temporal complexity. Second, a CEEMDAN-Kmeans-VMD secondary decomposition strategy is adopted to integrate intrinsic mode functions (IMFs) using K-means clustering. Variational mode decomposition (VMD) parameters are optimized via a novel exponential triangular optimization (ETO) algorithm to extract multi-scale features. Additionally, a refined TSMixer model is proposed, integrating reversible instance normalization (RevIn) to bolster the model’s generalizability and employing ETO to fine-tune model hyperparameters. This approach enables multi-component joint modeling, thereby averting error accumulation. The experimental results demonstrate that the enhanced model attains RMSE, MAE, and R² values of 0.0151, 0.0117, and 0.9878 on the test set, respectively, thereby exhibiting a substantial improvement in performance when compared to the reference models. Furthermore, we propose an anomaly detection framework based on STL decomposition and dual lonely forests. This framework improves sensitivity to sudden feature changes and detection robustness through a weighted fusion strategy of global trends and residual anomalies. This method provides efficient and reliable dynamic early-warning technology support for coal-mine gas disaster prevention and control, demonstrating significant engineering application value. Full article

During deep mining engineering, coal bodies are subjected to complex geological stresses such as periodic roof pressure and blasting impacts, which may induce mechanical property deterioration and trigger severe rock burst accidents. This study systematically investigated the mechanical characteristics and failure mechanisms of coal under strain rates on two orders of magnitude through quasi-static cyclic loading–unloading experiments and split Hopkinson pressure bar (SHPB) tests, combined with acoustic emission (AE) localization and crack characteristic stress analysis. The research focused on the differential mechanical responses of coal-rock masses under distinct stress environments in deep mining. The results demonstrated that under quasi-static loading, the stress–strain curve exhibited four characteristic stages: compaction (I), linear elasticity (II), nonlinear crack propagation (III), and post-peak softening (IV). The peak strain displayed linear growth with increasing cycle, accompanied by a failure mode characterized by oblique shear failure that induced a transition from gradual to abrupt increases in the AE counts. In contrast, under the dynamic loading conditions, there was a bifurcated post-peak phase consisting of two unloading stages due to elastic rebound effects, with nonlinear growth of the peak strain and an interlaced failure pattern combining lateral tensile cracks and axial compressive fractures. The two loading conditions exhibited similar evolutionary trends in crack damage stress, though a slight reduction in stress occurred during the final dynamic loading phase due to accumulated damage. Notably, the crack closure stress under quasi-static loading followed a decrease–increase pattern with cycle progression, whereas the dynamic loading conditions presented the inverse increase–decrease tendency. These findings provide theoretical foundations for stability control in underground engineering and prevention of dynamic hazards. Full article

Ensuring occupational safety in underground mines is a fundamental priority due to the major risks associated with this unfriendly work environment. This involves employing a set of technical, organizational, and educational measures to reduce the hazards for workers and minimize the risks of accidents and occupational diseases due to electrical and mechanical causes. Old and precarious coal extraction methods, in conjunction with obsolete infrastructure and electrical and mechanical installations, lead to high accident risk, endangering the lives of underground workers when at work. Precarious working conditions and working materials alongside the carelessness of decision makers make underground mine-based work a major cause of accidents and professional illnesses. In this paper, the authors identify, estimate, prioritize, and evaluate the vulnerabilities within underground mines and discuss the actions and resources necessary to mitigate, stop, and/or eliminate these vulnerabilities, as well as a mitigation strategy for stopping and/or eliminating them to achieve increased occupational safety. Full article

Gas accumulation triggered by coal and gas outbursts is the core cause of secondary disasters in coal mines. This study focuses on the risk assessment of gas accumulation during disaster scenarios, proposing a multidimensional evaluation method integrating the analytic hierarchy process (AHP), information entropy theory, kernel density estimation, and dynamic risk propagation modeling. A unified intelligent prevention system encompassing “monitoring–prediction–decision making” is established. Leveraging the TFIM3D simulation platform and case studies from the Qunli Coal Mine accident, this research reveals spatiotemporal evolution patterns of gas concentration and explosion risk thresholds. A ventilation optimization strategy based on risk classification is proposed. The results demonstrate that the dynamic risk index (DRI), derived from the coupling of the roadway air volume stability coefficient and gas concentration information entropy, can accurately identify high-risk zones. The findings provide theoretical foundations and practical pathways for dynamic risk management in ventilation systems during coal and gas outburst disasters. Full article

To address the intense mining pressure and dynamic accidents, such as shield collapse during mining in shallow coal seams crossing the Maoliang terrain, this study focuses on Panel 30206 of the Yanghuopan Coal Mine. Through theoretical analysis, numerical simulation, and field measurements, the stress transfer patterns and dynamic changes in shield loads during mining were analyzed, and the mechanism of dynamic mining pressure and calculation method for maximum support resistance were determined. The results show that when the working face enters the load-affected zone of the Maoliang terrain, the base load ratio of the overburden increases. The fracturing of the roof strata causes a synchronized motion between the key stratum and the overlying surface layer. The fracture and instability of the key stratum under mining-induced terrain loads significantly increase the shield resistance and intensify the mining pressure, with a hysteresis effect. Field measurements indicate a maximum shield working resistance of 8974 kN at Panel 30206, showing a 3.25% deviation from the theoretical value of 9266 kN, with a 25 m lag behind the peak load in the Maoliang terrain. This research provides criteria for support selection and ground control in Maoliang terrain mining, ensuring safe production. Full article

Gas extraction from coal seams can significantly mitigate gas accidents and improve resource utilization. The effectiveness of borehole sealing directly determines the concentration and efficiency of gas drainage. In recent years, liquid-phase sealing materials, represented by non-solidifying pastes, gel-based materials, and inorganic retarders, have gradually become a research hotspot. Compared to the traditional solid sealing materials such as cement-based or organic polymers, liquid-phase sealing materials can effectively seal secondary fractures caused by mining vibration through grout replenishment. However, the influence of each component in liquid-phase non-solidified materials on sealing properties such as fluidity, water retention, and permeability remains unclear. To address these issues, a novel liquid-phase non-solidified hole sealing material was developed using bentonite as the base material, sodium dodecyl benzene sulfonate as the dispersant, and sodium carboxymethyl cellulose as the thickener. Initially, single-factor experiments were applied to investigate the effects of material ratios on the fluidity, water retention, and permeability. Subsequently, orthogonal experimental design and response surface methodology were used to establish nonlinear quadratic regression models relating these properties to water–bentonite ratio, dispersant content, and thickener content. The results indicated that an optimal water–bentonite ratio enhances both fluidity and permeability, while dispersants improve water retention and permeability and thickeners primarily boost water retention. Finally, the optimized composition was determined as a water–bentonite ratio of 4.41:1, a dispersant content of 0.38%, and a thickener content of 0.108%. We believe that the developed slurry materials will maintain excellent sealing performance through the entire gas extraction period. Full article

Based on considering the stress state distribution and potential failure surface of the specimen during uniaxial compression, the drilling parameters (layout, spacing, position) are set. Thoroughly understanding the influence of different drilling parameters on the pressure relief effect is conducive to reducing the occurrence of coal mine rock burst accidents. Through laboratory tests and numerical simulation tests under different drilling parameters, the influence laws of mechanical parameters, failure characteristics, AE characteristic parameters and energy evolution of specimens under different drilling parameters were studied. The pressure relief effect under different drilling parameters was evaluated by using the pressure relief effect evaluation index (X), and the best combination of drilling parameters was obtained. The results show the following: (1) Compared with the intact specimen, the peak strength of the drilling specimen is significantly reduced, and the drilling layout has the greatest influence on the mechanical properties, followed by the drilling spacing and drilling position. (2) Different drilling layouts will form different weak-strength surfaces in the specimen, and lead the expansion and penetration of cracks, resulting in different failure modes of the specimen. The stress distribution inside the specimen will affect the stress concentration around the borehole, finally affect the damage degree of the specimen. (3) Drilling can not only effectively reduce the energy accumulation capacity, but also enhance the degree of energy dissipation. The AE ringing counts and energy of the triangular-drilling specimens are the least. The AE ringing counts and energy decrease first and then increase with the increase in drilling spacing, and are the smallest at three times the drilling diameter. The AE ringing counts and energy increase gradually with the upward movement of the drilling position. (4) The optimal combination of drilling parameters was obtained by the test, and it was triangular-layout drilling, drilling spacing three times the diameter, and the drilling position in the middle of the specimen, and the value of the pressure relief effect evaluation index (X) was 65.41. The research results can provide some reference for the selection and optimization of drilling pressure relief parameters in rock burst mines. Full article

Coal and gas outburst accident is a significant risk in high-gas outburst coal seams, and effective pressure relief gas extraction plays a crucial role in mitigating these hazards. The core challenge lies in understanding the seepage behavior of the coal rock body in the three zones of the overburden during multiple protective layer mining. This study employed a damaged coal rock body seepage test system to conduct repeated loading and unloading seepage tests on coal rock samples from these zones. The results show that the permeability of the broken coal rock body in the caving zone decreases with increasing stress, while it increases with (a) larger particle sizes of the broken coal rock body and (b) with a higher proportion of rock in the sample. The permeability distribution in the goaf follows an “O”-shaped circle pattern and gradually increases from the center outward. Additionally, When the protected layer is located within the fracture zone of the protective layer mining, and the first protective layer mining has already resulted in significant stress relief and permeability improvement, the effect of stress release and permeability enhancement from the second protective layer mining becomes less pronounced. In contrast, if the first protective layer mining does not sufficiently relieve stress or enhance permeability, the second protective layer mining has a more substantial effect. These findings are significant for analyzing the effects of pressure relief enhancement in multi-protective layer mining of high-gas outburst coal seams and for optimizing gas extraction. Full article