Search Results (91)

China’s traditional approach to supplying land for mining operations hinders the sustainable use of land resources, resulting in extensive land degradation and idleness after mining activities conclude. Based on this, the competent national authorities have innovatively launched reforms to the temporary land supply model for open-pit coal mining operations. This study uses the Anjialing open-pit coal mine pilot project in Shanxi Province, China as a case example to construct a comprehensive lifecycle model for temporary mining land use in operational coal mines. It evaluates the land reclamation implementation at this mine and proposes a land management model for future pilot mines establishing new temporary mining sites. Research indicates that: (1) In pilot mining projects currently under construction, the larger the initial mining area, the lower the strip ratio and coal extraction rate, and the longer the overall duration of temporary land use. (2) Based on the overall land use cycle model for temporary mining sites, the land use cycle for the Anjialing open-pit coal mine is approximately 7 to 10 years, making it impossible to complete mining operations and return the land after reclamation within five years. (3) Based on historical image analysis using the GEE platform, by the end of 2020, the coal mine reclamation area barely reached the boundaries of the 2012 temporary land use plan. Consequently, the pilot project for temporary mining land use failed to pass the required acceptance inspection. Overall, the promotion of this new model not only upholds the critical mission of safeguarding national farmland and ensuring food security, but also holds significant implications for future resource extraction and sustainable land utilization. Full article

The recording of minerals extracted from a deposit is crucial for effective planning, exploitation management, and compliance with legal requirements. It also enables improved workplace safety and the minimization of negative environmental impact. Automation in mining optimizes exploitation, transportation, and data management processes, resulting in better forecasting, more accurate resource calculations, and reduced operational costs. The usage of geographic information system tools facilitates data modeling and analysis, enhancing monitoring and mining exploitation management. This paper presents the classical approach to determining the volume of extracted minerals and proposes GIS-based tools for the automation of the volume calculation process. The automation of the process is presented both from a theoretical perspective, providing requirements and parameters for individual calculation procedures, and from a practical perspective, using the example of a typical open pit mine, where the procedure is implemented starting from field measurements, carrying out calculations, and ending with visualization and interpretation. The study highlights the benefits of automating the calculation procedure for the volume of extracted minerals, including task execution acceleration, increased efficiency, reduced calculation time, and minimized human error. This ultimately leads to more precise and consistent results. Full article

Electric rope shovels play a critical role in open-pit mining, where their automation and operational efficiency directly affect productivity. This paper presents a LiDAR-based relative positioning method to determine the spatial relationship between the ERS and mining trucks. The method utilizes dynamic DBSCAN for noise removal and RANSAC for truck edge detection, enabling robust and accurate localization. Leveraging this positioning data, a time-optimal trajectory planning strategy is proposed specifically for autonomous swing motion during the unloading process. The planner incorporates velocity and acceleration constraints to ensure smooth and efficient movement, while obstacle avoidance mechanisms are introduced to enhance safety in constrained excavation environments. To execute the planned trajectory with high precision, a neural network-based sliding-mode controller is designed. An adaptive RBF network is integrated to improve adaptability to model uncertainties and external disturbances. Experimental results on a scaled-down prototype validate the effectiveness of the proposed positioning, planning, and control strategies in enabling accurate and autonomous swing operation for efficient unloading. Full article

To address challenges in automated charging operations of bulk explosive trucks in open-pit mines—specifically difficulties in borehole identification, positioning inaccuracies, and low operational efficiency—this study proposes an intelligent collaborative charging system integrating three modular components: (1) an explosive transport vehicle (with onboard terminal, explosive compartment, and mobility system enabling optimal routing and quantitative dispensing), (2) a charging robot (equipped with borehole detection, loading mechanisms, and mobility system for optimized search path planning and precision positioning), and (3) interconnection systems (coupling devices and interfaces facilitating auxiliary explosive transfer). This approach resolves three critical limitations of conventional systems: (i) mechanical arm-based borehole detection difficulties, (ii) blast hole positioning inaccuracies, and (iii) complex transport routing. The experimental results demonstrate that the intelligent cooperative charging method for open-pit mines achieves an 18% improvement in operational efficiency through intelligent collaboration among its modular components, while simultaneously realizing automated and intelligent charging operations. This advancement has significant implications for promoting intelligent development in open-pit mining operations. Full article

This study analyzes the impact of the type of transported material (overburden, lignite, mixture) on the rate of core damage accumulation in Type St conveyor belts in open-pit mines. The research was conducted using the DiagBelt+ diagnostic system, which enables the assessment of belt core condition without dismantling the belt. Data were collected from over 100 conveyor belt loops, covering segments of varying lengths, ages, and operational histories. Damage density and area were assessed, and differences were analyzed depending on the material type. The results indicate that belt age and damage density vary significantly with material type, while the Resurs indicator (percentage of expected operating time) shows no clear dependence on the material type. A multiple regression analysis was also performed to predict failure density based on operational variables, such as Age, Resurs results, Loop Length, and Segment Length. The regression model explains approximately 46% of the variability in damage density, indicating the need for further research to improve predictive accuracy. The study emphasizes the importance of using non-destructive diagnostic systems to optimize maintenance planning and enhance conveyor belt reliability. Full article

Dust emissions from unpaved haul roads in open-pit coal mining pose a significant risk to air quality, health, and operational efficiency of mining operations. This study integrated real-time field monitoring with numerical simulations using ANSYS Fluent 2023 R1 to investigate the generation, dispersion, and migration of particulate matter (PM) at the Ha’erwusu open-pit coal mine under varying meteorological conditions. Real-time measurements of PM2.5, PM10, and TSP, along with meteorological variables (wind speed, wind direction, humidity, temperature, and air pressure), were collected and analyzed using Pearson’s correlation and multivariate linear regression analyses. Wind speed and air pressure emerged as dominant factors in winter, whereas wind and temperature were more influential in summer (R² = 0.391 for temperature vs. PM2.5). External airflow simulations revealed that truck-induced turbulence and high wind speeds generated wake vortices with turbulent kinetic energy (TKE) peaking at 5.02 m²/s², thereby accelerating particle dispersion. The dust migration rates reached 3.33 m/s within 6 s after emission and gradually decreased with distance. The particle settling velocities ranged from 0.218 m/s for coarse dust to 0.035 m/s for PM2.5, with dispersion extending up to 37 m downwind. The highest simulated dust concentration reached 4.34 × 10⁻² g/m³ near a single truck and increased to 2.51 × 10⁻¹ g/m³ under multiple-truck operations. Based on spatial attenuation trends, a minimum safety buffer of 55 m downwind and 45 m crosswind is recommended to minimize occupational exposure. These findings contribute to data-driven, weather-responsive dust suppression planning in open-pit mining operations and establish a validated modeling framework for future mitigation strategies in this field. Full article

The mining industry faces increasing pressure to improve efficiency, reduce operational costs, and adapt to modern technological trends. Central to these challenges is digitalization. This paper compares the level of digitalization in the mining industry internationally and in Slovakia, raising the question of the feasibility of implementing digitalization tools in small-scale Slovak mining operations. The presented case study demonstrates the creation of a simulation model and 3D animation for the development of small and medium-sized open pit mines, using Tecnomatix Plant Simulation software version 2302.0004, empirical data collection, and programming with SimTalk 2.0. Internationally, digitalization through modeling and simulation is already at a much higher level, with advanced solutions such as digital twins. In contrast, digitalization in Slovak mining operations is limited to basic simulation approaches, with only a few documented attempts, highlighting substantial opportunities for further development. The simulation model developed in this study enables more efficient planning and management of logistics and transportation processes, with potential benefits for operational improvements, safety, and sustainability. Adopting digitalization, even in small-scale operations, can drive the future development of the Slovak mining industry. Full article

This article is devoted to the study of the possibilities for improvAzing the quality of energy management systems adopted at open-pit mining enterprises in the Russian Federation. The main idea of the work is to apply stochastic boundary value analysis methods using the production function for individual and integral estimates of the performance of energy-consuming objects when performing various types of technological work. It is shown that mining enterprises are experiencing problems in the field of rational energy consumption due to the lack of strictly formalized ways to determine the frontiers of the efficiency value of the parameter of specific energy consumption (SEC). A justification is given for the need to apply stochastic frontier analysis (SFA) methods and use the Cobb–Douglas production function to account for the nonlinearity and stochasticity of the operating conditions of energy-consuming mining objects. The results of a statistical analysis of the data on the operation of EKG-10 excavators at operating enterprises in Siberia are presented, as well as an assessment of their energy efficiency using the adopted approach based on planning the target value of SEC. The results of computational experiments on constructing an energy efficiency model using the SFA/Cobb–Douglas function for various data segmentation options are presented. Computational experiments have been conducted to compare variants based on the Cobb–Douglas production function and translog function with semi-normal and exponential distribution forms for the same data set. A comparative assessment is given of the approaches to the complex analysis of activities adopted at enterprises and proposed in this study, characterizing potential hidden energy losses in the range from 4.53% to 20.73%. Full article

Landslide prevention is crucial, particularly for protecting roads and infrastructure in rock landslide-prone areas. This global issue has garnered significant attention from researchers worldwide. This study addresses landslide prevention by modeling the factor of safety (FoS) for slope stability through the Geological Strength Index (GSI), limit equilibrium method (LEM), and finite element method (FEM). A GSI analysis was conducted using RocLab software version 1.0, and slope modeling was performed using RocScience SLIDE version 6.0 and RS2 version 11. The results revealed various cohesion and friction angles across six slopes, with Slope 5 exhibiting the highest FoS values (up to 3.27 with the FEM) and Slope 1 exhibiting the lowest (1.59 with the FEM). All slopes, designed with a uniform geometry, remained stable, exhibiting FoS values greater than 1.1. This study further provides an optimal slope design for the open pit in the andesite mining plan at Anugerah Berkah Sejahtera. These findings highlight the important role of accurate modeling in the assessment of slope stability. With a suggested safe slope height of 10 m and an angle of 80° (FoS = 1.62), slope stability analysis based on the factor of safety (FoS) showed that single slopes made of andesite maintain stability at steep angles. Claystone slopes, however, have a maximum slope height of 30 m at 20° (FoS = 1.27) and 27 m at 50° (FoS = 1.34), requiring more conservative geometries to maintain their stability. For an overall slope that comprises both rock types, a height of 30 m with a slope angle of 60° is recommended (FoS = 1.23) to ensure stability. The critical design condition for a claystone slope occurs at a height of 30 m with a slope angle of 50°, yielding a factor of safety (FoS) of 0.92, which indicates instability (FoS < 1.1). Similarly, a 35 m-high slope with a slope angle of 20° produced an FoS of 1.04, and a 35 m-high slope with a slope angle of 50° produced an FoS of 0.89, further confirming instability. For the overall slope configuration, instability occurs at a height of 30 m with a slope angle of 65° that produces an FoS of 1.09. Full article

As the primary method used in open-pit mining, blasting has a direct impact on the efficiency and cost of subsequent operations. Therefore, dynamic identification of rock fragment size after blasting is essential for evaluating blasting quality and optimizing mining plans. This study presents a YOLOv8-based binocular vision model for real-time recognition of blasting fragmentation. The model is trained on a dataset comprising 1536 samples, which were annotated using an automatic labeling algorithm and expanded to 7680 samples through data augmentation techniques. The YOLOv8 instance segmentation model is employed to detect and classify rock fragments. By integrating binocular vision-based automatic image capture with Welzl’s algorithm, the actual particle size of each rock fragment is calculated. Furthermore, region of interest (ROI) extraction and shadow-based data enhancement techniques are incorporated to focus the model on the blasting fragmentation area and reduce environmental interference. Finally, software and a system were independently developed based on this integrated model and successfully deployed at engineering sites. The dynamic recognition Mean Average Precision of this integrated model is 0.84, providing a valuable reference for evaluating blasting effects and improving work efficiency. Full article

Scientific and rational monitoring of eco-environmental effects induced by mining activities is a prerequisite for optimizing mining planning and contributes to the advancement of ecological civilization. Remote sensing and multi-source data provide advanced methods for long-term dynamic evaluation of mining-induced eco-environmental effects. This study systematically constructs eco-environmental effect indicators tailored to mining characteristics and establishes quantitative extraction methods based on Landsat data and spectral indices. The Mine Eco-environmental Effect Index (MEEI) was developed using kernel principal component analysis (KPCA). The Heidaigou Open-pit Coal Mine in Jungar Banner was selected as the study area to validate the MEEI’s performance and analyze ecological dynamics across five key temporal phases. Results indicate the following: (1) the KPCA-based MEEI effectively integrates multi-indicator features, offering an objective representation of comprehensive eco-environmental impacts; (2) from 1990 to 2020, the ecological trajectory of the coal mine followed a pattern of “sharp deterioration → gradual slowdown → relative stabilization”, with post-mining restoration and management measures significantly mitigating negative impacts and improving regional ecological quality. This study provides a methodological framework for dynamic evaluation of mining-related eco-environmental effects, supporting sustainable mining practices and ecological governance. Full article

With the increasing demand for mineral resources, sustainable mining development faces challenges such as low resource utilization efficiency. Ore blending optimization has emerged as a critical approach to enhance resource utilization. This study constructs a multi-objective ore blending optimization system for complex polymetallic open-pit mines based on the improved matter-element extension model and NSGA-II algorithm. By identifying key blending factors, objective functions are established to minimize both total ore quantity deviation and grade deviation, with six constraints defined to reflect production capacity limits. The NSGA-II algorithm is employed to solve the multi-objective optimization problem, generating a Pareto optimal solution set from which the optimal ore blending scheme is selected using the improved matter-element extension model. A case verification at Dabaoshan Mine demonstrates that the model-verified scheme achieves 1.035% higher total production accuracy than the planned value and 2.828% higher than actual production, while improving Cu grade deviation accuracy by 7.021% over the plan and 1.064% over actual production, and S grade deviation accuracy by 33.027% over the plan and 3.127% over actual production. This study, through the construction of systematic ore blending theory and empirical analysis, provides an important theoretical framework and methodological support for subsequent research on ore blending in polymetallic open-pit mines. It demonstrates significant practical application value in Dabaoshan Mine, offering an intelligent mine solution that combines scientific rationality and engineering practicability for polymetallic open-pit mines. Full article

A study was conducted concerning the perceptions of a future reservoir (4.7–8.9 square kilometres, 42.2 million cubic metres) by residents, tourists, and visitors; the location in question was the former Kotlarnia sand pit in the catchment area of the Bierawka River (tributary of the Oder River in southern Poland). Divergent concepts for the reclamation and development of the former sand pit emerged; the construction of a reservoir was initially the dominant option but was eventually abandoned despite it having the greatest acceptance among the respondents (out of the 134 respondents, 43.3% favoured the creation of a water reservoir, 29.9% favoured introducing nature protection arrangements in the area to enable spontaneous nature regeneration, and 16.4% favoured reforestation). A clear discrepancy arose between the public’s expectations related to the reclamation and development of the former sand pit in order to create a reservoir and the official position of the land user and administrator of the potential reservoir, which indicated that it no longer intended to create such a reservoir. This study indicates that in the process of developing concepts related to the reclamation and development of former mineral workings, it is essential to obtain the results of public consultation based on a diagnostic survey conducted among representatives of the local community. This is an effective tool for predicting the optimal use of sites regenerated after the damage caused by open-pit mining provided that all technical considerations related to the planned project are taken into account in advance. Full article

This study introduces an enhanced ORB-SLAM3 algorithm to address the limitations of traditional visual SLAM systems in feature extraction and localization accuracy within the challenging terrains of open-pit mining environments. It also tackles the issue of sparse point cloud maps for mobile robot navigation. By combining point-line features with a Micro-Electro-Mechanical System (MEMS) Inertial Measurement Unit (IMU), the algorithm improves the feature matching’s reliability, particularly in low-texture areas. The method integrates dense point cloud mapping and an octree structure, optimizing both navigation and path planning while reducing storage demands and improving query efficiency. The experimental results using the TUM dataset and conducting tests in a simulated open-pit mining environment show that the proposed algorithm reduces the absolute trajectory error by 44.33% and the relative trajectory error by 14.34% compared to the ORB-SLAM3. The algorithm generates high-precision dense point cloud maps and uses an octree structure for efficient 3D spatial representation. In simulated open-pit mining scenarios, the dense mapping outperforms at reconstructing complex terrains, especially in low-texture gravel and uneven surfaces. These results highlight the robustness and practical applicability of the algorithm in dynamic and challenging environments, such as open-pit mining. Full article

The Aitik mine is Sweden’s largest open-pit sulfide mine and Europe’s most important producer of gold, silver, and copper. However, the mine faces problems related to water inflow, particularly in the northern zone and western hanging wall sections of the pit, resulting from various mining activities, including blasting, loading, and hauling. The presence of fracture zones within the pit further exacerbates the issue, as continuous mining operations have aggravated the thickness of these fractures, potentially increasing the volume of water inflow. Consequently, this could lead to various geotechnical issues such as slope collapse, and increase the possibility of acid mine drainage formation. This research develops a numerical model using ModelMuse as the graphical user interface and MODFLOW to simulate groundwater flow in the mining pit under different scenarios, by considering the absence, presence, and varying thickness of fracture zones to address the issue. By analyzing these scenarios, the model estimates the volume of water inflow into the pit under steady-state conditions. The results indicate that the presence of a fracture zone plays a crucial role in controlling water inflows by significantly influencing the inflow budget—by 90% for the north shear inflow (NSI) and by 20% for the western hanging wall inflow (WHWI) at deeper depths of the pit. Variations in the fracture zone thickness result in a 15% increase in water inflow at deeper depths of the pit. These findings provide valuable insights for improving mine water management strategies and informing sustainable mine closure planning to mitigate long-term environmental risks. Full article