Search Results (54)

Coal gangue, the primary bulk solid waste generated during coal utilization, requires decarbonization and the enrichment of valuable components such as calcium and magnesium through methods like hydrocyclone separation for comprehensive utilization. This study observed the free-settling behavior of coal gangue particles using a high-speed dynamic image analysis system and analyzed their kinematic characteristics to guide the hydrocyclone separation process. The results indicate that particle size and density significantly influence settling behavior. Fine-grained, low-density particles exhibited more pronounced directional deflection and velocity fluctuations, while high-density coarse particles demonstrated higher settling velocities. Based on terminal velocity, the drag coefficient of fluid resistance acting on particles was calculated. The findings show that high-density coarse particles have larger drag coefficients, likely due to fluid disturbances and the hydrophobic nature of particle surfaces. Additionally, the mechanical properties of settling motion were analyzed, indicating that gravity dominates the settling process of coarse particles, while fine particles are subjected to relatively balanced forces. Furthermore, density variations primarily affect hydrodynamic drag, which is related to the surface properties of particles. Therefore, enhancing the centrifugal force field through cyclone structural optimization is necessary to improve separation precision for fine coal and gangue particles. Full article

Germanium, a critical material for advanced technologies, is enriched in certain coal deposits and by-products, including coal combustion and gasification fly ashes. This review examines germanium concentrations and occurrence modes in coal, coal gangue, and their combustion or gasification by-products, as well as hydrometallurgical recovery methods at laboratory, pilot, and industrial scales. Fly ashes from both coal combustion and gasification are particularly promising due to their higher germanium content and recovery rates, which can exceed 90% under optimal conditions. However, the low germanium concentrations and high levels of impurities in the leachates pose challenges, necessitating the development of innovative and selective separation techniques, primarily involving solvent extraction, ion exchange, or adsorption. Full article

The presence of pyrite in coal gangue significantly degrades the performance of its prepared kaolin in ceramic and coating applications. Implementing separation techniques to remove pyrite can markedly enhance the quality of kaolin products. However, there is no research on the effect of material particle size distribution on the separation effect in the current study on shaking table separation. For this reason, the coal gangue was crushed to different maximum particle sizes in this study, and its particle size distribution was fitted and analyzed. Based on the fitting results, the Rosin–Rammler–Sperling–Bennet (RRSB) distribution with a uniformity coefficient n of 0.74 was used to study the influence of the characteristic particle size d_e on the separation effect. Fuller distribution with distribution modulus q of 0.45 was also used to study the impact of maximum particle size d_max. The results showed that the Fuller distribution reduced the contents of SO₃ and Fe₂O₃ by 30.85% and 25.71%, respectively, compared with the raw materials. In comparison, the RRSB distribution reduced the contents of SO₃ and Fe₂O₃ by 41.01% and 30.85%, respectively, indicating that the separation effect of the RRSB distribution was better than that of the Fuller distribution. In addition, when the characteristic particle size d_e of the RRSB distribution was 37–42 μm, the content of SO₃ and Fe₂O₃ in the tailings varied very little, and the separation effect was stable. This study demonstrates that the particle size distribution significantly influences the separation efficiency of the shaking table, providing a novel idea for enhancing shaking table separation processes. Future studies may further explore the effect of another parameter or two-parameter coupling of RRSB distribution and Fuller distribution on the separation effect of the shaking table. Full article

Hard roof top-cutting and gob-side roadway retention is an effective way to improve the panel recovery ratio and reduce ground pressure. Based on the condition of Pingmei No.2 Mine, this paper establishes a stability mechanics model for the roof in a trapezoidal top-cutting roadway with inclined coal seam, in order to analyze the factors influencing the stability of the roof. This paper studies the deformation characteristics and control mechanism of the surrounding rock in a trapezoidal top-cutting roadway, and proposes targeted stability control technologies for the surrounding rock. The results showed that: (1) in a trapezoidal top-cutting roadway in the hard roof with inclined coal seam, the tensile stress of the uncut roof was inversely proportional to the coal seam dip angle, roof thickness and top-cutting height, while it was proportional to the top-cutting angle. According to actual engineering conditions, the top-cutting angle and height of the roof of the 21,100-panel were determined to be 10° and 5.0 m, respectively; (2) the special structure of the trapezoidal roadway led to asymmetric stress distribution in the surrounding rock, especially in the roof and rib. Using top-cutting, the pressure relief reduced the roof stress from 6.73 MPa to 2.04 MPa, the high stress zone moved to the inside of the solid coal, and the roof slid and deformed along the top line, showing characteristics of a “large deformation on the top side”; and (3) high-strength long anchor cables were used to reinforce the roof on the cut top side. Telescopic U-shaped steel and windshield cloth were used to block gangue and prevent wind leakage in the roadway. The on-site industrial test measured the maximum subsidence of the roof at 120 mm, and the maximum layer separation was 29 mm. Relative to non-top-cutting methods, the roof and sides showed significantly reduced deformation throughout the mining operations, which verified the reliability of the control technology. Full article

Gallium, a critical and strategic material for advanced technologies, is anomalously enriched in certain coal deposits and coal by-products. Recovering gallium from solid residues generated during coal production and utilization can yield economic benefits and positive environmental gains through more efficient waste processing. This systematic literature review focuses on gallium concentrations in coal and its combustion or gasification by-products, modes of occurrence, gallium-hosting phases, and hydrometallurgical recovery methods, including pretreatment procedures that facilitate metal release from inert aluminosilicate minerals. Coal gangue, and especially fly ashes from coal combustion and gasification, are particularly promising due to their higher gallium content and recovery rates, which can exceed 90% under optimal conditions. However, the low concentrations of gallium and the high levels of impurities in the leachates require innovative and selective separation techniques, primarily involving ion exchange and adsorption. The scientific literature review revealed that coal, bottom ash, and coarse slag have not yet been evaluated for gallium recovery, even though the wastes can contain higher gallium levels than the original material. Full article

The efficient separation of coal and gangue remains a critical challenge in modern coal mining, directly impacting energy efficiency, environmental protection, and sustainable development. Current machine vision-based sorting methods face significant challenges in dense scenes, where label rewriting problems severely affect model performance, particularly when coal and gangue are closely distributed in conveyor belt images. This paper introduces CGDet (Coal and Gangue Detection), a novel compact convolutional neural network that addresses these challenges through two key innovations. First, we proposed an Object Distribution Density Measurement (ODDM) method to quantitatively analyze the distribution density of coal and gangue, enabling optimal selection of input and feature map resolutions to mitigate label rewriting issues. Second, we developed a Relative Resolution Object Scale Measurement (RROSM) method to assess object scales, guiding the design of a streamlined feature fusion structure that eliminates redundant components while maintaining detection accuracy. Experimental results demonstrate the effectiveness of our approach; CGDet achieved superior performance with AP50 and AR50 scores of 96.7% and 99.2% respectively, while reducing model parameters by 46.76%, computational cost by 47.94%, and inference time by 31.50% compared to traditional models. These improvements make CGDet particularly suitable for real-time coal and gangue sorting in underground mining environments, where computational resources are limited but high accuracy is essential. Our work provides a new perspective on designing compact yet high-performance object detection networks for dense scene applications. Full article

To address the low recognition accuracy of models for coal gangue images in intelligent coal preparation systems—especially in identifying small target coal gangue due to factors such as camera angle changes, low illumination, and motion blur—we propose an improved coal gangue separation model, Yolov8n-improvedGD(GD—Gangue Detection), based on Yolov8n. The optimization strategy includes integrating the GCBlock(Global Context Block) from GCNet(Global Context Network) into the backbone network to enhance the model’s ability to capture long-range dependencies in images and improve recognition performance. The CGFPN (Contextual Guidance Feature Pyramid Network) module is designed to optimize the feature fusion strategy and enhance the model’s feature expression capabilities. The GSConv-SlimNeck architecture is employed to optimize computational efficiency and enhance feature map fusion capabilities, thereby improving the model’s robustness. A 160 × 160 scale detection head is incorporated to enhance the sensitivity and accuracy of small coal and gangue detection, mitigate the effects of low-quality data, and improve target localization accuracy. Full article

Lithium, a critical material for the global development of green energy sources, is anomalously enriched in some coal deposits and coal by-products to levels that may be considered economically viable. Recovering lithium from coal, particularly from coal gangue or coal ashes, offers a promising alternative for extracting this element. This process could potentially lead to economic gains and positive environmental impacts by more efficiently utilizing coal-based waste materials. This review focuses on lithium concentrations in coal and coal by-products, modes of lithium occurrence, methods used to identify lithium-enriched phases, and currently available hydrometallurgical recovery methods, correlated with pretreatment procedures that enable lithium release from inert aluminosilicate minerals. Leaching of raw coal appears inefficient, whereas coal gangue and fly ash are more feasible due to their simpler composition and higher lithium contents. Lithium extraction can achieve recovery rates of over 90%, but low lithium concentrations and high impurity levels in the leachates require advanced selective separation techniques. Bottom ash has not yet been evaluated for lithium recovery, despite its higher lithium content compared to feed coal. Full article

The presence of pyrite poses a significant impediment to the comprehensive utilization of coal gangue, which is a prevalent solid waste in industrial production. However, the current efficacy of jig separation for pyrite in fine-grade coal gangue remains unsatisfactory. To investigate the influence of particle size distribution on the jig separation of pyrite in fine-grade coal gangue, the raw material was crushed to less than 2 mm using a jaw crusher and subsequently sieved to obtain its particle size distribution curve. Upon fitting the curve, it was observed that it tends towards the Rosin-Rammler (RRSB) and Fuller distributions. Leveraging these two-parameter distribution curves, adjustments were made to determine the mass within each particle size range before conducting thorough mixing followed by jig separation. The results indicate that for fine-grade gangue particles smaller than 2 mm, the RRSB distribution with a uniformity coefficient of n = 0.85 exhibits the most effective separation, although it is comparable to the separation achieved using the size distribution of raw ore. On the other hand, employing the Fuller distribution with modulus of distribution q = 1.5 yields superior separation performance. In comparison to the raw ore, the concentrate shows an increase in sulfur (S) and iron (Fe) content by factors of 3.4 and 2.4, respectively. Furthermore, compared to the RRSB distribution, there is an increase in S and Fe content by 1.91% and 2.30%, respectively; the contents of S and Fe in tailings is 0.71% and 2.72%, which can be directly used as raw materials for coating materials. Therefore, for fine-grade coal gangue particles, jigging under the Fuller distribution demonstrates better effectiveness than under the RRSB distribution. Full article

Gallium (Ga) and germanium (Ge) critical elements have a wide range of applications and market value. Extracting critical elements from coal gangue and combustion products can alleviate pressures on primary mining resources. Understanding the transformation behavior of Ga and Ge during coal gangue combustion processes is significant for resource utilization and environmental protection. Coal gangue from Xing’an League, Inner Mongolia, was chosen to explore how combustion temperatures (600 °C to 1000 °C) and particle sizes (50, 80, 10, 140, and 200 mesh) influence Ga and Ge migration during combustion. Techniques such as ICP-MS, XRD, XRF, SEM, TG-DSC, and sequential chemical extraction were employed to analyze the transformation of minerals and to quantify the contents and occurrence forms of Ga and Ge. Smaller gangue particle sizes were associated with higher concentrations of Ga and Ge. Approximately 99.19% of Ga and Ge in coal gangue were found in the residual, organic/sulfide-bound, and metal-oxide-bound modes. High temperatures promoted element volatilization and changed the reactions and interactions between elements and minerals. As combustion temperatures rose from 600 °C to 1000 °C, Ga and Ge contents in the products declined progressively. Under high temperatures, minerals like kaolinite, illite, and pyrite in gangue converted to silicate glass phases, mullite, and hematite. Minerals like kaolinite, calcite, and pyrite melted, leading to increased cohesion and agglomeration in the products. Over 90% of Ga and Ge in the combustion products existed in the residual, organic/sulfide-bound, and metal-oxide-bound forms. Moreover, Ga was enriched in combustion products, with its content exceeding critical extraction levels. The results may provide a useful reference for developing critical elements enrichment, extraction, and separation technologies from coal gangue. Full article

Instability in coal pillars and filling bodies is a common occurrence during the mining process of continuous mining and continuous backfilling (CMCB). In view of this, combining numerical simulation, similarity simulation, and on-site testing approaches, backfill mining models were established in Flac3d5.01 software, similarity model test bench, and “two-stage”, “three-stage”, and “four-stage” mining sequences were conducted; the stress characteristics of coal pillar-filling body and the displacement evolution law of surrounding rock have been compared under three typical mining sequences. The results show that compared to two-stage mining sequence, three-stage and four-stage mining sequences provide sufficient time for the solidification of the filling body. The coal pillar exhibits better stability in the early stage of mining, but the stress concentration phenomenon is more significant in the later stage of mining. The stress concentration coefficient is the highest when the width of the coal pillar is 10 m. The integrity of the overburden is intact in different mining sequences, with only a small amount of separation and longitudinal cracks. Increasing the number of mining stages significantly reduces the roof subsidence, with the maximum roof subsidence in the three- and four-stage mining sequences being only 62.0% and 33.9% of that in the two-stage mining sequence. “Two stages”, “three stages”, and “four stages” of mining sequences are implemented in response to the requirements of weak and thick coal seam mining in Haoyuan Coal Mine and gangue disposal in Chahasu Coal Mine. Good engineering applications are achieved, enabling the realisation of safe, green, and efficient coal mining. Full article

This paper proposes a fundamental investigation of coal gangue and fly ash impact on B. pasteurii to enhance the properties of backfill materials. The goal is to obtain effective microbial mineralization and potential mechanical properties of coal gangue and fly ash as backfill materials and to mitigate the impact of the most common binders used in the backfill material of mines. Micro-scale mineralization was performed with B. pasteurii bacteria using microbially induced carbonate precipitation (MICP) technology to clarify solid waste impact on B. pasteurii and to bind coal gangue and fly ash. Several tests were carried out to analyze the behavior of B. pasteurii, especially when it coexists with these two waste materials separately. In such cases, it was possible to observe a reduction in mineralization initiation time with respect to the natural mineralization of the MICP technology. Moreover, at the macro-scale, the new mineralized backfilling material shows good workability in the fresh state, whereas the strength at 28 days is 5.34 times higher than that obtained with non-mineralized coal gangue and fly ash. Full article

Intelligent gangue sorting with high precision is of vital importance for improving coal quality. To tackle the challenges associated with coal gangue target detection, including algorithm performance imbalance and hardware deployment difficulties, in this paper, an intelligent gangue separation system that adopts the elevated YOLO-v5 algorithm and dual-energy X-rays is proposed. Firstly, images of dual-energy X-ray transmission coal gangue mixture under the actual operation of a coal mine were collected, and datasets for training and validation were self-constructed. Then, in the YOLOv5 backbone network, the EfficientNetv2 was used to replace the original cross stage partial darknet (CSPDarknet) to achieve the lightweight of the backbone network; in the neck, a light path aggregation network (LPAN) was designed based on PAN, and a convolutional block attention module (CBAM) was integrated into the BottleneckCSP of the feature fusion block to raise the feature acquisition capability of the network and maximize the learning effect. Subsequently, to accelerate the rate of convergence, an efficient intersection over union (EIOU) was used instead of the complete intersection over union (CIOU) loss function. Finally, to address the problem of low resolution of small targets leading to missed detection, an L2 detection head was introduced to the head section to improve the multi-scale target detection performance of the algorithm. The experimental results indicate that in comparison with YOLOv5-S, the same version of the algorithm proposed in this paper increases by 19.2% and 32.4% on mAP @.5 and mAP @.5:.95, respectively. The number of parameters decline by 51.5%, and the calculation complexity declines by 14.7%. The algorithm suggested in this article offers new ideas for the design of identification algorithms for coal gangue sorting systems, which is expected to save energy and reduce consumption, reduce labor, improve efficiency, and be more friendly to the embedded platform. Full article

Coal gangue image recognition is a critical technology for achieving automatic separation in coal processing, characterized by its rapid, environmentally friendly, and energy-saving nature. However, the response characteristics of coal and gangue vary greatly under different illuminance conditions, which poses challenges to the stability of feature extraction and recognition, especially when strict illuminance requirements are necessary. This leads to fluctuating coal gangue recognition accuracy in industrial environments. To address these issues and improve the accuracy and stability of image recognition under variable illuminance conditions, we propose a novel coal gangue recognition method based on laser speckle images. Firstly, we studied the inter-class separability and intra-class compactness of the collected laser speckle images of coal and gangue by extracting gray and texture features from the laser speckle images, and analyzed the performance of laser speckle images in representing the differences between coal and gangue minerals. Subsequently, coal gangue recognition was achieved using an SVM classifier based on the extracted features from the laser speckle images. The fusion feature approach achieved a recognition accuracy of 94.4%, providing further evidence of the feasibility of this method. Lastly, we conducted a comparative experiment between natural images and laser speckle images for coal gangue recognition using the same features. The average accuracy of coal gangue laser speckle image recognition under various lighting conditions is 96.7%, with a standard deviation of the recognition accuracy of 1.7%. This significantly surpasses the recognition accuracy obtained from natural coal and gangue images. The results showed that the proposed laser speckle image features can facilitate more stable coal gangue recognition with illumination factors, providing a new, reliable method for achieving accurate classification of coal and gangue in the industrial environment of mines. Full article

In order to find a better collector for the separation of carbon and kaolin from coal gangue flotation, and to explore the action mechanism of collectors, this paper selected 12 kinds of collectors for systematic comparison, including five non-polar organics with different carbon chain lengths, and polar organic matters with double bonds, triple bonds, benzene, as well as cycloalkyl, ester, carboxyl, and aldehyde groups. The flotation results show that the longer carbon chain (with a carbon atom number of 13~15), the better the flotation effect, the better the effect of the collector with the phenyl group (among the four hydrocarbon groups), and the better the effect of the collector with the ester group (among the three functional groups). In order to explore the flotation mechanism at the microscopic level, the molecular structure of carbon in coal gangue was detected using a solid nuclear magnetic test. Afterwards, the organic macromolecule model of carbon was simulated. Finally, the interaction energy values between carbon and collectors were calculated in accordance with the density functional theory, and the order of the acting force of collectors was obtained, which was consistent with that of the collectors in the macro experiment. Full article