Search Results (193)

Mining (1) operations in remote areas (2) face significant challenges related to energy supply, high fuel costs, and limited infrastructure. This study investigates the potential for achieving energy independence (3) and resilience (4) in such environments through the integration of renewable energy sources (5) and battery–electric mining equipment. Using the “Studena Vrila” underground bauxite mine as a case study, a comprehensive techno-economic and environmental analysis was conducted across three development models. These models explore incremental scenarios of solar and wind energy adoption combined with electrification of mobile machinery. The methodology includes calculating levelized cost of energy (LCOE), return on investment (ROI), and greenhouse gas (GHG) reductions under each scenario. Results demonstrate that a full transition to RES and electric machinery can reduce diesel consumption by 100%, achieve annual savings of EUR 149,814, and cut GHG emissions by over 1.7 million kg CO₂-eq. While initial capital costs are high, all models yield a positive Net Present Value (NPV), confirming long-term economic viability. This research provides a replicable framework for decarbonizing mining operations in off-grid and infrastructure-limited regions. Full article

Illegal mining operations induce cascading ecosystem degradation by causing extensive ground subsidence, necessitating accurate underground goaf localization for effectively induced-hazard mitigation. The conventional locating method applied the synthetic aperture radar interferometry (InSAR) technique to obtain ground deformation to estimate underground goaf parameters, and the locating accuracy was crucially contingent upon the appropriateness of nonlinear deformation function models selection and the precision of geological parameters acquisition. However, conventional model-driven underground goaf locating frameworks often fail to sufficiently integrate prior geological information during the model selection process, potentially leading to increased positioning errors. In order to enhance the operational efficiency and locating accuracy of underground goaf, deformation model selection must be aligned with site-specific geological conditions under varying cases of prior information. To address these challenges, this study categorizes prior geological information into three different hierarchical levels (detailed, moderate, and limited) to systematically investigate the correlations between model selection and prior information. Subsequently, field validation was carried out by applying two different non-linear deformation function models, Probability Integral Model (PIM) and Okada Dislocation Model (ODM), with three different prior geological information conditions. The quantitative performance results indicate that, (1) under a detailed prior information condition, PIM achieves enhanced dimensional parameter estimation accuracy with 6.9% reduction in maximum relative error; (2) in a moderate prior information condition, both models demonstrate comparable estimation performance; and (3) for a limited prior information condition, ODM exhibits superior parameter estimation capability showing 3.4% decrease in maximum relative error. Furthermore, this investigation discusses the influence of deformation spatial resolution, the impacts of azimuth determination methodologies, and performance comparisons between non-hybrid and hybrid optimization algorithms. This study demonstrates that aligning the selection of deformation models with different types of prior geological information significantly improves the accuracy of underground goaf detection. The findings offer practical guidelines for selecting optimal models based on varying information scenarios, thereby enhancing the reliability of disaster evaluation and mitigation strategies related to illegal mining. Full article

Underground pumped storage hydropower stations (UPSH) are of great significance for energy structure adjustment, and coal mine underground reservoirs are an integral part of UPSH. This study investigates the fracture mechanics behavior of coal in mine water immersion environments with varying loading rates and layer direction. Three types of samples were analyzed: Crack-arrester, Crack-splitter, and Crack-divider types. The immersion duration extended up to 120 days. The results indicate that, after immersion in mine water for 120 days, the fracture toughness (K_IC), fracture modulus (E_S), and absorbed energy (U_T) of coal decreased by 60.87%, 53.38%, and 63.21%, respectively, compared to the unsaturated coal samples. An immersion period of 30 days significantly weakens the mechanical properties of coal fractures. The K_IC, E_S, and U_T of coal demonstrate a positive correlation with loading rate, primarily influenced by the duration of coal damage. At the same loading rate, the order of fracture toughness among the three coal types is as follows: Crack-divider > Crack-arrester > Crack-splitter. This hierarchy is determined by the properties of the coal matrix and bedding planes, as well as the mechanical structures composed of them. This study holds significant implications for the safe construction and operational design of underground water reservoirs in coal mines. Full article

To investigate the remediation efficiency of different plant species on cadmium (Cd)-contaminated soil, this study conducted a pot experiment with two woody species (Populu adenopoda and Salix babylonica) and two herbaceous species (Artemisia argyi and Amaranthus hypochondriacus). Soils were collected from an abandoned coal mine and adjacent pristine natural areas within the dam-adjacent section of the Three Gorges Reservoir Area to establish three soil treatment groups: unpolluted soil (T1, 0.18 mg·kg⁻¹ Cd), a 1:1 mixture of contaminated and unpolluted soil (T2, 0.35 mg·kg⁻¹ Cd), and contaminated coal mine soil (T3, 0.54 mg·kg⁻¹ Cd). This study aimed to investigate the growth status of plants, Cd accumulation and translocation characteristics, and the relationship between them and soil environmental factors. Woody plants exhibited significant advantages in aboveground biomass accumulation. Under T3 treatment, the Cd extraction amount of S. babylonica (224.93 mg) increased by about 36 times compared to T1, and the extraction efficiency (6.42%) was significantly higher than other species. Among the herbaceous species, A. argyi showed the maximum Cd extraction amount (66.26 mg) and extraction efficiency (3.11%) during T2 treatment. While A. hypochondriacus exhibited a trend of increasing extraction amount but decreasing extraction efficiency with increasing concentration. With the exception of S. babylonica under T1 treatment (BCF = 0.78), the bioconcentration factor was greater than 1 in both woody (BCF = 1.39–6.42) and herbaceous species (BCF = 1.39–3.11). However, herbaceous plants demonstrated significantly higher translocation factors (TF = 1.58–3.43) compared to woody species (TF = 0.31–0.87). There was a significant negative correlation between aboveground phosphorus (P) content and root Cd (p < 0.05), while underground nitrogen (N) content was positively correlated to aboveground Cd content (p < 0.05). Soil total N and available P were significantly positively correlated with plant Cd absorption, whereas total potassium (K) showed a negative correlation. This study demonstrated that woody plants can achieve long-term remediation through biomass advantages, while herbaceous plants, with their high transfer efficiency, are suitable for short-term rotation. In the future, it is suggested to conduct a mixed planting model of woody and herbaceous plants to remediate Cd-contaminated soils in the tailing areas of reservoir areas. This would synergistically leverage the dual advantages of root retention and aboveground removal, enhancing remediation efficiency. Concurrent optimization of soil nutrient management would further improve the Cd remediation efficiency of plants. Full article

It is vital to stabilize pillar dams in underground reservoirs in coal mine goafs to protect groundwater resources and quarry safety, practice green mining, and protect the ecological environment. Considering the actual occurrence of coal pillar dams in underground reservoirs, acoustic emission (AE) mechanical tests were performed on dry, naturally absorbed, and soaked coal samples. According to the mechanical analysis, Quantitative analysis revealed that dry samples exhibited the highest mechanical parameters (peak strength: 12.3 ± 0.8 MPa; elastic modulus: 1.45 ± 0.12 GPa), followed by natural absorption (peak strength: 9.7 ± 0.6 MPa; elastic modulus: 1.02 ± 0.09 GPa), and soaked absorption showed the lowest values (peak strength: 7.2 ± 0.5 MPa; elastic modulus: 0.78 ± 0.07 GPa). The rate of mechanical deterioration increased by ~25% per 1% increase in moisture content. It was identified that the internal crack development presented a macrofracture surface initiating at the sample center and expanding radially outward, and gradually expanding to the edges by adopting AE seismic source localization and the K-means clustering algorithm. Soaked absorption was easier to produce shear cracks than natural absorption, and a higher water content increased the likelihood. The b-value of the AE damage evaluation index based on crack development was negatively correlated with the rock damage state, and the S-value was positively correlated, and both effectively characterized it. The research results can offer reference and guidance for the support design, monitoring, and warning of coal pillar dams in underground reservoirs. (The samples were tested under two moisture conditions: (1) ‘Soaked absorption’—samples fully saturated by immersion in water for 24 h, and (2) ‘Natural absorption’—samples equilibrated at 50% relative humidity and 25 °C for 7 days). Full article

The underground coal mine environment is complex and dynamic, making the application of visual algorithms for object detection a crucial component of underground safety management as well as a key factor in ensuring the safe operation of workers. We look at this in the context of helmet-wearing detection in underground mines, where over 25% of the targets are small objects. To address challenges such as the lack of effective samples for unworn helmets, significant background interference, and the difficulty of detecting small helmet targets, this paper proposes a novel underground helmet-wearing detection algorithm that combines dynamic background awareness with a limited number of valid samples to improve accuracy for underground workers. The algorithm begins by analyzing the distribution of visual surveillance data and spatial biases in underground environments. By using data augmentation techniques, it then effectively expands the number of training samples by introducing positive and negative samples for helmet-wearing detection from ordinary scenes. Thereafter, based on YOLOv10, the algorithm incorporates a background awareness module with region masks to reduce the adverse effects of complex underground backgrounds on helmet-wearing detection. Specifically, it adds a convolution and attention fusion module in the detection head to enhance the model’s perception of small helmet-wearing objects by enlarging the detection receptive field. By analyzing the aspect ratio distribution of helmet wearing data, the algorithm improves the aspect ratio constraints in the loss function, further enhancing detection accuracy. Consequently, it achieves precise detection of helmet-wearing in underground coal mines. Experimental results demonstrate that the proposed algorithm can detect small helmet-wearing objects in complex underground scenes, with a 14% reduction in background false detection rates, and thereby achieving accuracy, recall, and average precision rates of 94.4%, 89%, and 95.4%, respectively. Compared to other mainstream object detection algorithms, the proposed algorithm shows improvements in detection accuracy of 6.7%, 5.1%, and 11.8% over YOLOv9, YOLOv10, and RT-DETR, respectively. The algorithm proposed in this paper can be applied to real-time helmet-wearing detection in underground coal mine scenes, providing safety alerts for standardized worker operations and enhancing the level of underground security intelligence. Full article

Remote drilling technologies play a crucial role in automating both underground and open-pit hard rock mining operations. These technologies enhance efficiency and, most importantly, improve safety in the mining sector. Autonomous drilling rigs can navigate to pre-determined positions and utilize the appropriate parameters to drill boreholes effectively. This article explores various aspects of automation, including the integration of advanced data collection methods that monitor the drilling parameters and facilitate the creation of 3D models of rock hardness. The shift toward machine automation involves transitioning from human-operated machines to systems powered by artificial intelligence, which are capable of making real-time decisions. Navigating underground environments presents unique challenges, as traditional RF-based localization systems often fail in these settings. New solutions, such as constant localization and mapping techniques like SLAM (simultaneous localization and mapping), provide innovative methods for navigating mines, particularly in uncharted territories. The development of robotic exploration rigs equipped with modules that can operate autonomously in hazardous areas has the potential to revolutionize mineral exploration in underground mines. This article also discusses solutions aimed at validating and improving existing methods by optimizing drilling strategies to ensure accuracy, enhance efficiency, and ensure safety. These topics are explored in the context of the Horizon Europe-funded PERSEPHONE project, which seeks to deliver fully autonomous, sensor-integrated robotic systems for deep mineral exploration in challenging underground environments. Full article

To advance the construction of intelligent mining, electro-hydraulic digital control technology has emerged as a critical direction for the digital transformation of mining machinery. This study proposes a digital control scheme based on the pressure state of the system and the operating state of the actuator. The scheme utilises a novel convergence rate sliding film position control method to regulate the system pressure in real time by controlling the pilot valve, which is driven by a permanent magnet synchronous motor (PMSM). Moreover, a prototype of an incremental digital pressure control valve was developed for high-pressure, high water-based working conditions. A simulation model of the valve was established using AMESim/Simulink, and dynamic characteristics under various operating conditions were analyzed. The relative error between simulated and experimental pressure results remained within ±4.7%. Finally, a multi-parameter optimization was conducted using a genetic algorithm. The results demonstrate that the optimized digital pressure control valve achieved a stabilized inlet pressure within 44.8 ms, with a pressure overshoot of 4.1% and a response time of 20.1 ms, exhibiting excellent real-time dynamic pressure regulation capabilities. This study provides a theoretical foundation and practical reference for comprehensive research on pressure control in underground emulsion pump stations. Full article

The Sierra de las Navajas is a Late Pliocene volcanic complex with a rhyolitic composition and peralkaline affinity. It is located on the northeastern edge of the Trans-Mexican Volcanic Belt in the state of Hidalgo. Within this rocky massif lies Cerro de las Navajas, the site of the most intensively exploited archaeological obsidian deposit in Mesoamerica. Obsidian extraction in this area has been carried out through open-pit mining and unique underground mining. The geological identity of the deposit encompasses the origin, distribution, and petrological characteristics of the obsidian from Cerro de las Navajas, determined through detailed geological mapping, petrographic study, and geochemical analysis. The results reveal the obsidian deposit’s style as well as its temporal and spatial position within the eruptive evolution of the region. The deposit originated from a local explosive eruptive mechanism associated with the partial collapse of a lava dome, forming a Block and Ash Flow Deposit (BAFD). The obsidian blocks, exploited by different cultures, correspond to the pyroclastic blocks within this deposit, which can reach up to 1 m in diameter and are embedded in a weakly consolidated ash matrix. The BAFD was later buried by (a) subsequent volcanic events, (b) structural adjustments of the volcanic edifice, and (c) soils derived from the erosion of other volcanic units. This obsidian deposit was mined underground from the Early Formative period to the Colonial era by the cultures of the Central Highlands and colonized societies. Interest in the vitreous quality and exotic nature of obsidian lithics from the BAFD led to the development of a complex exploitation system, which was generationally refined by the Teotihuacan, Toltec, and Aztec states. Full article

Underground coal mines face increasing challenges in the scheduling of Electric Rubber-Tired Vehicles (ERTVs) due to confined spaces, dynamic production demands, and the need to coordinate multiple constraints such as complex roadway topologies, strict time windows, and limited charging resources in the context of clean energy transitions. This study presents a Constraint Programming (CP)-based optimization framework that integrates Virtual Charging Station Mapping (VCSM) and sensor fusion positioning to decouple spatiotemporal charging conflicts and applies a dynamic topology adjustment algorithm to enhance computational efficiency. A novel RFID–vision fusion positioning system, leveraging multi-source data to mitigate signal interference in underground environments, provides real-time, reliable spatiotemporal coordinates for the scheduling model. The proposed multi-objective model systematically incorporates hard time windows, load limits, battery endurance, and roadway regulations. Case studies conducted using real-world data from a large-scale Chinese coal mine demonstrate that the method achieves a 17.6% reduction in total transportation mileage, decreases charging events by 60%, and reduces vehicle usage by approximately 33%, all while completely eliminating time window violations. Furthermore, the computational efficiency is improved by 54.4% compared to Mixed-Integer Linear Programming (MILP). By balancing economic and operational objectives, this approach provides a robust and scalable solution for sustainable ERTV scheduling in confined underground environments, with broader applicability to industrial logistics and clean mining practices. Full article

Haigou deposit, located in Dunhua City, southeast Jilin Province, NE China, is a large-scale gold deposit. The gold ore body is categorized into two types: quartz-vein type and altered rock type, with the quartz-vein type being predominant. The vein gold ore body primarily occurs within the monzonite granite and monzonite rock mass in the Haigou area and is controlled by fault structures trending northeast, northwest, and near north-south. In order to constrain the age and tectonic setting of quartz vein-type gold mineralization, we conducted a detailed underground investigation and collected samples of monzonite granite and pyroxene diorite porphyrite veins related to quartz-vein-type gold mineralization for LA-ICP-MS zircon U-Pb dating and whole-rock main trace element data testing to confirm that monzonite granite is closely related to gold mineralization. Pyroxene diorite porphyry and gold mineralization were found in parallel veins. The zircon U-Pb weighted mean ages of monzonite and pyroxene diorite porphyrite veins are 317.1 ± 3.5 Ma and 308.8 ± 3.0 Ma, respectively, indicating that gold mineralization in monzonite, pyroxene diorite porphyrite veins, and quartz veins occurred in the Late Carboniferous. The monzonite granite and pyroxene diorite porphyrite veins associated with quartz vein-type gold mineralization have high SiO₂, high K, and high Al₂O₃ and are all metaluminous high-potassium calc-alkaline rock series. Both of them are relatively enriched in light rare earth elements (LREE) and macroionic lithophile elements (LILE: Rb, Ba, K, etc.), but deficient in heavy rare earth elements (HREE) and high field strength elements (HFSE: Nb, Ta, P, Ti, etc.), the monzonitic granite Eu is a weak positive anomaly (δEu = 1.15–1.46), the pyroxene diorite porphyre dyke Eu is a weak positive anomaly (δEu = 1.09–1.13), and the Nb and Ta are negative anomalies. The Th/Nb values are 0.28–0.73 and 1.48–2.05, and La/Nb are 2.61–4.74 and 4.59–5.43, respectively, suggesting that diagenetic mineralization is the product of subduction in an active continental margin environment. In recent years, scholarly research on Sr, Nd, and Pb isotopes in Haigou rock masses has indicated that the magmatic source region in the Haigou mining areas is complex. It is neither a singular crustal source nor a mantle source but rather a mixed crust-mantle source, primarily resulting from the partial melting of lower crustal materials, with additional contributions from mantle-derived materials. In summary, the metallogenic characteristics, chronology data, geochemical characteristics, and regional tectonic interpretation indicate that at least one phase of magmatic-hydrothermal gold mineralization was established in the Late Carboniferous as a result of the subduction of the Paleo-Asian ocean plate at the northern margin of the North China Craton. Full article

The introduction of autonomous vehicles in underground mine trackless transportation systems can significantly reduce safety risks for personnel in production operations and improve transportation efficiency. Current autonomous mining vehicle technology is characterized by complex algorithms and high deployment costs, which limit its widespread application in underground mines. This paper proposes a light-band-guided autonomous driving method for trackless mining vehicles, where a continuous, digitally controllable light band is installed at the tunnel ceiling to provide uninterrupted vehicle guidance. The light band is controlled by an independent hardware system and uses different colors to indicate vehicle movement status, enabling vehicles to navigate simply by following the designated light trajectory. We designed the necessary hardware and software systems and built a physical model for validation. The system enabled multiple vehicles to be guided simultaneously within the same area to perform diverse transportation tasks according to operational requirements. The model vehicles maintained a safe distance from tunnel walls. In GPS-denied environments, positioning was achieved using dead reckoning and periodic location updates at designated points based on the known light-band trajectory. The proposed method demonstrates high potential for practical applications. Full article

To address the challenges posed by significant parallax, dynamic changes in monitoring camera positions, and the need for rapid wide-field image stitching in underground coal mine tunneling faces, this paper proposes a fast image stitching method for tunneling face images based on navigation and positioning data. First, using a pixel-based calculation approach, the tunneling face scene is partitioned into the cutting section and the ground, enhancing the reliability of scene segmentation. Then, the spatial distance between the camera and the cutting plane is computed based on the tunneling machine’s navigation and positioning data, and a plane-induced homography model is employed to efficiently determine the dynamic transformation matrix of the cutting section. Finally, the Dual-Homography Warping (DHW) method is applied to achieve fast panoramic image stitching of the tunneling face. Comparative experiments with three classical stitching methods, SURF, SIFT, and BRISK, demonstrate that the proposed method reduces stitching time by 60%. Field experiments in underground environments verify that this method can generate a complete panoramic stitched image of the tunneling face, providing an unobstructed perspective beyond the machine body and cutting head to clearly observe the shovel plate and surrounding ground conditions, significantly enhancing the visibility and convenience of remote operation. Full article

$\mathrm{Visible}\mathrm{light}\mathrm{communication}$ (VLC) is an emerging technology that offers an alternative to traditional wireless communications systems. However, the technology presents limitations related to the impact of the receiver’s orientation, which can significantly impact its performance. To address this issue, VLC systems use diversity schemes, such as transmitter and receiver diversity. In this paper, we derive an analytical expression for the probability of maintaining a line-of-sight (LoS) link in an underground mining visible light communication (UM-VLC) system with a receiver embedded in an object, such as a helmet, by considering user mobility. We show that the angle of incidence depends on the distance from the source and derive the probability accordingly for single-input single-output (SISO), multiple-input single-output (MISO), and single-input multiple-output cases (SIMO). Our results show that the analytical results fit with the simulated results. Furthermore, the resulting probabilities show that the angular position of the receiver significantly affects the channel’s quality, with the optimal position dependent on the field-of-view characteristics. These findings can provide an appropriate framework for receiver and transmitter diversity design through analytical expression. Full article

Aiming to solve the problems of communication interruption caused by the collapse of underground space, this study constructs a strong penetration information transmission system and proposes a centroid localization method based on the received signal strength indication (RSSI) in an underground space ground electrode current field. This is applicable to localization in underground space such as subways, mines, tunnels, etc., as well as under the environment of collapse. First, the propagation characteristics of the ground current field signal in underground space are analyzed, and the attenuation model of the ground current field signal is constructed by combining the RSSI ranging method. On this basis, an improved weighted centroid localization algorithm is introduced to improve the localization accuracy and reliability by optimizing the algorithm parameters to cope with the fluctuations and instabilities generated in the signal propagation process. The experimental results show that the proposed localization method achieves an average positioning error of 7.47 m in an underground environment of 10,000 square meters, which is 32.32% less compared with the weighted centroid localization algorithm, and 62.74% less compared with the traditional centroid localization algorithm. This method presents a positioning technology that operates independently in underground spaces, overcoming the limitation of traditional wireless positioning systems, which rely on external transmission links. Its application will provide crucial technical support for life-saving operations in underground environments, acting as the ‘last line of defense’ in rescue missions. By completing the emergency response chain, it will enhance disaster rescue capabilities, offering substantial practical value and promising prospects. Full article