Taking the filter membrane of a microbial sampler as the research background, a porous step model was used to simulate the structure of the microbial sampling membrane. The internal flow field of the sampler was numerically investigated using the finite element method. Simulations were conducted to analyze the filtration pressure drop, flow velocity variation patterns, and the distribution of velocity and pressure contours within the sampler. The influence of fluid inlet velocity parameters on the performance of the deep-sea microbial sampling device was studied, thereby determining the optimal fluid inlet velocity parameters for the deep-sea microbial sampler. The results show that under the conditions of inlet velocity of 0.1, 0.2, 0.3, 0.4, 0.5, the pressure drops on both sides of the filter membrane of the sampler are 36, 82, 139, 207, 288 Pa, and the differences of flow velocity on both sides of the filter membrane of the sampler are 0.05, 0.16, 0.26, 0.34, 0.38, respectively. The pressure drop across the filter membrane of the sampler and the velocity difference between both sides of the membrane increase with the increase in the inlet velocity, while the pressure behind the filter membrane decreases as the velocity increases. When the fluid inlet velocity is 0.3, the filtration performance of the sampler reaches its optimum. Numerical simulation results can provide a theoretical basis for researching the filtration performance of deep-sea microbial sampling devices.

The large range multi-level and multi-stope strength mining in deep metal mines causes frequent and violent adjustment of surrounding rock stress field, which is easy to induce engineering rock mass disasters such as spalling and caving. Aiming at the problems of high cost of multi-point test and poor timeliness in the inversion process of mining-induced stress field, an improved density clustering algorithm based on dynamic optimization of neighborhood search range of microseismic source radius was proposed, which divided microseismic activity into multiple clusters with high internal correlation. On this basis, the natural neighbor interpolation method was adopted to establish the inversion method of "microseismic signal apparent stress – microseismic event apparent stress – microseismic cluster apparent stress – mining-induced stress field". The engineering practice of deep metal mine shows that the average contour coefficient of microseismic data clustering cluster family is 0.56, which verifies the reliability of the improved density clustering algorithm for microseismic data clustering, and the apparent stress concentration area obtained by this method is highly consistent with the actual ground pressure disaster event area. The research results can provide theoretical and technical support for the identification and risk control of potential dangerous areas of mining-induced ground pressure in deep metal mines.

The gently inclined thick ore body below －675 m level in Chengchao Iron Mine is mined by two-step mining with sublevel drilling open stoping and subsequent filling. According to the theoretical analysis results, three numerical simulation research schemes of mine room (pillar) span were formulated. The stress, displacement and plastic zone distribution of each scheme were compared and analyzed, and the influences of different spans of mine room (pillar) on the stability of stope was explored. The results show that when the span of mine room (pillar) is 15 m, the maximum tensile stress of the goaf roof is less than 2 MPa, and the maximum compressive stress is less than 5 MPa, which is within the allowable range of the rock mass. The maximum subsidence value of the goaf roof is less than 5 cm, which does not exceed the allowable limit displacement. There is no large area of plastic zone penetration in the structural plane of the goaf. When the span of the mine room is 18 m, the roof settlement is 52.3 mm (over the warning value of 50 mm), which need to be supported. It is determined that the span of mine room (pillar) is 15 m as the optimal scheme. The maximum vertical subsidence value of the monitoring points in the center of the roof is 0.033 7 m, and the maximum vertical subsidence value of the monitoring points in the center of the surrounding rock is 0.031 4 m. According to the evaluation results of the influence of ground deformation on the buildings (structures), the mining of the ore body below －675 m level will have a slight impact on the surface buildings (structures), and the influence degree is within the allowable range, which ensures the safety of the new Chengchao Bay country on the surface of Chengchao Iron Mine.

In order to study the degradation law of mining height on the strength of overlying rock, taking the determination of reasonable initial mining height in the initial mining stage of Guojiawan 51208 working face as the background, the fracture density function was used to measure the degradation of mining height on the strength of overlying rock, and the theoretical model and numerical analysis model of the strength degradation of overlying rock under different mining heights were established. Combined with the parameters of the working face, the influence law of mining height on the stability of overlying rock was obtained. The results show that with the increase of mining height, the rotation angle gradually increases, the thickness of the rock layer loaded by the bearing layer gradually decreases, and the rock layer is more prone to rotary deformation and instability. When the advancing length of the working face is 40 m, the maximum displacement of the overlying rock and the plastic zone distribution of the basic roof are basically the same for the mining height of 2.5 m and 4.0 m. When the advancing length of the working face is 50 m and above, the maximum displacement of the overlying rock with a mining height of 4.0 m is more than10%higher than that with a mining height of 2.5 m, and the plastic zone of the basic roof is obviously increased. The peak value of advance support pressure increases with the increase of mining height, and the first weighting step decreases with the increase of mining height. The initial weighting step of 2.5 m mining height is 70 m. The initial mining height is 2.5 m, and the mining height is gradually adjusted to the actual coal thickness（4.0 m）after the first weighting of the main roof. The initial mining of the working face is more efficient and safe. The research results can provide reference for the initial mining roof control problem of the working face.

Pipeline transportation of tailings slurry is the key to efficient tailings discharge in mines. In order to explore the variation law of flow resistance of mine tailings slurry during pipeline transportation, the influence of multiple factors such as flow velocity, transportation pipe diameter, slurry mass concentration and their interaction on the flow resistance of tailings slurry transportation was analyzed by orthogonal test, and the pipeline transportation parameters of tailings slurry were optimized. The results are as follows. Firstly, the F value of the established regression model is 4 660.66, the P value is less than 0.000 1, and the fitting value R²is 0.997, indicating that the model has high reliability. The model can accurately characterize the change of the resistance along the slurry transportation under different working conditions. Secondly, when the flow rate is low(1−2 m/s), the slope of the curve of the resistance loss along the way is small. When the flow rate is greater than 2 m/s, the curve of the resistance loss along the way is steeper, the resistance is greater, and it increases sharply. Thirdly, the influence degree of multi-factor interaction from large to small is the interaction of tailings slurry flow rate and mass concentration, the interaction of tailings slurry flow rate and transportation pipe diameter, and the interaction of slurry mass concentration and transportation pipe diameter. Fourthly, the optimized pipeline transportation parameters are as follows: the mass concentration of slurry transportation is 56%, the slurry transportation speed is 1.6 m/s, the transportation pipe diameter is 127 mm, and the predicted resistance along the way is 0.242 kPa/m. The measured resistance along the way in the test is 0.233 kPa/m, and the error is only 3.7%, which is within the controllable range. It shows that the accuracy of the prediction model is high, and the resistance along the way is small under this working condition, which meets the requirements of long-distance transportation. The test results provide a reference for the efficient pipeline transportation design of high mass concentration tailings slurry in mines.

In order to quantitatively evaluate the flocculation effect of flocculants and acquire the change law of floc pore structure, fractal theory was introduced to analyze the fractal dimensions and flocculation effect of four flocculants, including ZYD, JYC-1, JYC-2 and ZYZ. The pore structures inside different flocculants samples were analyzed using three-dimensional reconstruction and CT slices, and the mechanism of tailings flocculation and settlement was revealed. Through the static and dynamic flocculation tests, the optimal flocculant type and process parameters were determined, and the relationship between the underflow mass concentration of slurry and the material layer height was deduced. The results show that ZYZ-type flocculant has the largest fractal dimension, which is 1.842 3, with the best flocculation settling effect. ZYZ-type flocculant forms flocs with larger size at a faster settling speed, and forms a better water-conducting channel, achieving a significant thickening effect. Through the static and dynamic flocculation tests, the slurry mass concentration of 20% and the flocculant unit consumption of 20 g/t were determined as the best flocculation process parameters. If the overflow mass concentration of slurry is up to 70%, the height of the sediment layer that needs to be settled is 731 mm. On-site industrial application shows that the average sand mass concentration of the thickener is 70%, the urination rate is no more than 5%, the slurry fluidity is good, and the filling effect is good.

Using high-sulfur tailings and gobi materials as mixed filling aggregates, the mechanical properties of high-sulfur tailings backfill excited by industrial magnesium slag were investigated. A preliminary test was conducted to investigate the effect of different magnesium slag contents on the compressive strength of the backfill. Using NaOH as an alkaline activator, the influence of proportioning parameters of high-sulfur tailings backfill on compressive strength, stress-strain curve characteristics, and failure mode was systematically analyzed through orthogonal tests. The results show that when the ratio of tailings to gobi material is 1:1 and the dosage of NaOH is 1%, the compressive strength of the backfill reaches its maximum value at 28 d, which is 4.54 MPa. NaOH has an optimization effect on the mechanical properties of high-sulfur tailings backfill excited by magnesium slag, and reasonable control of the dosage of high-sulfur tailings, NaOH, and magnesium slag can significantly improve the compressive strength of the backfill. Increasing the dosage of NaOH, magnesium slag, and high-sulfur tailings can enhance the mechanical strength of the backfill, but it will lead to a brittle transition in its failure mode and exacerbate local failure characteristics. The research results can provide a basis for the resource utilization of magnesium slag and high-sulfur tailings, as well as the performance optimization of mine filling materials.

In order to improve the accuracy of the prediction of ore flowability in the ore storage section of the ore pass based on numerical simulation and indoor similarity test, the parameters of the parallel bond model based on the slump and expansion test were introduced in the numerical simulation process. The numerical simulation results obtained by this method were highly consistent with the indoor similarity test. The results indicate a significant decline in ore flowability within the moisture content range of 0 to 9%. Particularly when the moisture content is 7%−9%, the ores are prone to blockages. Therefore, this specific moisture content range should be strictly avoided during actual ore drawing operations. When the moisture content is 3%−5%, the flowability of the ore is the best. It is suggested that the moisture content of the ore should be controlled in this range in the actual project. Furthermore, the study reveals that as the ore storage height increases from 20 m to 40 m, the flowability of the ore improves significantly, reaching a peak mass flow rate at 40 m. However, when the ore storage height is further increased to 60 m, the mass flow rate stabilizes and exhibits a slight decline.

To address the issue of low blasting efficiency in deep buried roadways excavation, the influence of detonation sequence under high stress conditions on the blasting effectiveness of parallel cut was studied. By combining physical model tests with numerical simulations, the dynamic laws of strain field evolution, crack expansion, and groove cavity formation with different detonation sequences were revealed. The metal wire electric explosion technology was used to simulate explosive blasting, combined with a confining pressure loading device to apply static pressure. The digital image correlation method (DIC) and ultra-high-speed camera were used to capture the surface strain field and crack expansion process of the specimens. Based on the 3D scanning results, the differences in groove shape with different detonation sequences were analyzed. The results show that when the first blast hole is located in the direction of the maximum principal stress (detonation sequence two), the circumferential strain of the empty hole is significantly increased, and it is easy to form penetrating cracks. The 3D scanning results show that the groove cavity volume of detonation sequence two is larger than that of detonation sequence one, and the residual rate at the bottom of the hole is reduced. Numerical simulation further verifies that when the first blast hole is along the direction of maximum principal stress, the distribution of damage zone is more uniform, the opening angle of the groove cavity increases, and the energy utilization efficiency of subsequent blast holes is effectively improved. The research has shown that prioritizing detonation in the direction of maximum principal stress can optimize the distribution of damage zones, improve the shape of the groove cavity, and reduce residue at the bottom of the hole.

Aiming at the problem of roadway stability during the collaborative mining of three middle sections of Jinchuan No.2 mining area, the maximum principal stress, roadway convergence rate, rock body integrity(K_v), rock quality (RQD), and support effectiveness were selected as evaluation indexes. Based on the combined weighting-boundary cloud modeling algorithm, the stability of the roadways during the collaborative mining of three middle sections in deep section was comprehensively evaluated and predicted, then compared with on-site working conditions. The results indicate that the stability grades of the roadways in the 1 018 m, 934 m, and 814 m sublevels across different mining phases primarily fall within grades Ⅱ to Ⅲ, but there are differences in the stability of the main roadways in each middle section. In current mining stage, the stability of the roadway in the 1 018 m sublevel is superior to that in the 934 m and 814 m sublevels, with the western and eastern areas of the 1 018 m sublevel exhibiting better stability than the central area. Conversely, the central and eastern areas of the 934 m and 814 m sublevels show greater stability than the western area. In the later stages of mining, the stability of the main roadway in each middle section gradually shifts from more stable to generally stable, resulting in a decrease in stability. The evaluation results align with the actual project, providing a reference for roadway support in the late stages of the collaborative mining of the three middle sections in Jinchuan No.2 mining area.

In order to solve the problem of roof instability and material waste caused by unreasonable value of roof support parameters, the optimization of support parameters was studied based on the research background of the north stope of Zhongguan Iron Mine. Firstly, based on the suspension theory and the loose circle theory, combined with the numerical simulation results without support, the plastic zone was used as the basis for the determination of the loose circle, and the thickness of the loose zone was obtained, and then the length of the bolt was 2.4−4.4 m. Secondly, according to the quality of rock mass, the designed row spacing between bolts was 0.8 m×0.8 m and 1.2 m×1.2 m respectively, the length of bolts was 2.4 m and 4.4 m respectively, and the anchoring force was 17.5 MPa and 20 MPa respectively. The FLAC3D software was used to establish the mining model, and the vertical stress, vertical displacement and plastic zone distribution of the roof of each scheme were compared and analyzed. Finally, based on the simulation results, the index satisfaction method was used to select the roof settlement, the height of the stress release zone, the area of the plastic zone and the total length of the bolt, and the optimization model of the bolt parameters considering the safety and economic benefits was established. The highest comprehensive satisfaction is 0.899, and the optimal scheme is determined to be a row spacing between bolts of 0.8 m×0.8 m, bolt length of 4.4 m and anchoring force of 20 MPa. The simulation results provide theoretical support for the determination of the bolt parameters of the ore body.

The mine ventilation system is the important subsystem in the underground engineering of the mine. The accurate control of the air volume is the basis for the optimization of the ventilation system, and the local resistance is one of the important factors affecting the air volume. In order to study the local flow field characteristics of the double-frame louver windshield, the Computational Fluid Dynamics (CFD) numerical simulation software was used to analyze the dynamic characteristics of the local flow field of the louver windshield under different inlet wind speeds and different blade opening angles. The relationship functions between the effective opening area of the windshield with the air volume and local resistance were established and compared with the measured results. The results show that when the blade opening angle is 45°, a high-speed flow field is gradually formed at the inlet of the windshield. With the increase of the inlet wind speed, the peak wind speed and the flow field area increase. When the blade opening angle increases from 60° to 90°, the local resistance at the windshield decreases and the distribution characteristics of the rear flow field change. During the process of the wind flow passing through the windshield, the static pressure energy and kinetic energy are converted to each other. The pressurization deceleration area and the vortex area formed on the leeward side of the air door become the key factors affecting the local resistance and energy loss in the flow field behind the double-frame louver windshield. The local resistance coefficient of the windshield depends on the effective wind area, which has a power function relationship with the blade opening angle. The maximum relative error between the local resistance of the windshield calculated by the formula and the measured results is 5.57%, which shows that the local resistance calculated by the formula is more accurate.

In response to the complexity and ambiguity of safety evaluation for coal mine electromechanical systems, interval approximation theory was introduced to improve the objectivity and reliability of evaluated results, and a comprehensive safety evaluation model for coal mine electromechanical systems based on G1-FDEMATEL-interval approximation was established. Firstly, according to the theory of accident causation intersection, 17 indicators were filtered from the four dimensions of human, machine, management, and environment to construct an evaluation system. Secondly, the G1-FDEMATEL method was coupled to obtain the comprehensive weights of indicators. Based on the principle of interval approximation, the interval estimation method was used to determine the evaluation data of indicators, which compensated for the limitation of discontinuous point estimation values and information missing in traditional models. By calculating the comprehensive distance, the safety level of coal mine electromechanical systems was determined. Finally, taking 5 coal mines as examples, the G1-FDEMATEL-interval approximation model was applied to analyze the safety status of the electromechanical systems. The results show that the safety levels of the electromechanical systems in all five coal mines were relatively safe, consistent with the expert conclusions. Compared with traditional VIKOR and TOPSIS models, it can effectively reflect the true safety status of the electromechanical systems, verify the adaptability and scientificity of the models, and provide a theoretical support for preventing and handling electrical system safety accidents.

In order to objectively evaluate the low-carbon ecological construction effect of mines and promote the coordinated development of economic construction and environmental protection of mining enterprises, an evaluation index system was established based on the framework of DPSIR. The index weight algorithm of DPSIR-DEMATEL-AHP was constructed using the DEMATEL method and AHP method. Using the interval number optimal algorithm and the binary connection number optimal algorithm, a method for evaluating the low-carbon ecological construction effect in mines based on interval number goodness was established to objectively reveal the close degree connection among the driving force of mining enterprise development, ecological environment pressure, environmental quality status of mining areas, the impact of mining on the environment and the response of mining enterprises. It provided a basis for dynamic evalution of the low-carbon ecological construction effect in mines and analysis of the key factors affecting low-carbon ecological construction. The model method was used to evaluate the low-carbon ecological construction effect of an open-pit mine and analyze its key influencing factors. The results show that the low-carbon ecological construction effect of this mine is the best in 2021 and the worst in 2020. Important measures to improve the effectiveness of low-carbon ecological construction in mines include enhancing the mining profit margin, saving energy and increasing efficiency in mines and reducing the CO₂ emissions, enhancing the solid waste utilization per unit of industrial output value, increasing the greening coverage rate in mining, implementing effective dust-reducing measures, strengthening the management of key work processes in mine production, as well as enhancing the coverage rate of energy-saving and emission-reduction campaigns and training and so on.

In order to evaluate the implementation effect of safety management in non-coal underground mines, a safety performance evaluation index system of non-coal underground mines was established, including 6 first-level indicators and 30 second-level indicators. The safety performance evaluation method of non-coal underground mines based on ANP method and TOPSIS method was constructed. The weight of evaluation index was determined by ANP method, and the comprehensive evaluation was carried out by TOPSIS method. Finally, XD company was taken as an example for empirical research. The evaluation results show that the safety performance score of XD company in 2023 is the highest, and the safety performance is grade Ⅱ. The average annual growth rate of safety performance comprehensive score from 2020 to 2023 is 5.36%. XD company is relatively good in safety education and training, and relatively weak in risk classification control and hidden danger investigation and management. The evaluation results can provide guidance for the safety management of mining enterprises.

In order to study the effect of mineral composition content on Microcrack propagation and static mechanical parameters of granite, a numerical model considering the meso-components of rock was established by combining thin section identification analysis and particle flow discrete element software PFC2D. The mesoscopic parameters of the model were calibrated by static uniaxial compression tests, and the effects of mineral component content on microcrack propagation, compressive strength and elastic modulus of granite were discussed. The results show that with the increase of quartz content, the failure mode of rock changes from “y” -shaped shear failure to “X” -shaped shear failure. With the increase of potassium feldspar content, the failure mode of rock changes from oblique section shear failure to “y” -shaped shear failure. With the increase of plagioclase content, the failure mode of rock changes from “V” -shaped shear failure to “X” -shaped shear failure. Biotite has the greatest influence on the failure mode of rock, with the increase of biotite content, the failure mode of rock changes from “V” cross shear failure to monoclinic shear failure, and then to composite shear failure. The elastic modulus of granite is negatively correlated with potassium feldspar and plagioclase, and positively correlated with quartz and biotite. Biotite has the greatest influence on compressive strength of granite, followed by plagioclase, then quartz, and potassium feldspar has the least influence. The Stiffness Heterogeneity Factor (SHF) is further introduced to analyze the relationship between mineral composition content and rock mechanical parameters. It is found that the peak stress and elastic modulus of rock decrease linearly with the increase of SHF.

The engineering stability of jointed rock masses in cold regions is often affected by freeze-thaw cycles damage, which leads to geological hazards. The core control factor is the deterioration of shear strength of rock mass. In response to the engineering background of the coupled effects of freeze-thaw cycles and shear loads faced by jointed rock masses in cold regions, existing methods for calculating the shear strength of freeze-thaw joints have certain deviations. Therefore, a modified shear strength criterion was proposed that accounts for the strength degradation of jointed rock mass under freeze-thaw cycles. A systematic experimental study on freeze-thaw-shear coupling was conducted using similar material simulation methods. Based on direct shear test results of freeze-thaw joints, the degradation mechanism of rock bridges under freeze-thaw-shear coupling action was revealed as follows. The shear strength of non-persistent jointed rock mass consists of three components, including the shear strength of non-degraded rock bridges, the shear strength of degraded rock bridges, and the shear strength of the joint surfaces. A coupled damage model for rock bridges was established with shear modulus as the variable, achieving quantitative characterization of the degradation behavior of rock bridges. Building upon this foundation, the modified Jennings shear strength criterion demonstrates the following advantages: the mean relative error between theoretical predictions and test results is merely 3.28%, representing a significant improvement in prediction accuracy compared to the original Jennings criterion. This modified criterion effectively captures the strength characteristics of non-persistent jointed rock mass under freeze-thaw action, thereby providing a reliable theoretical basis for studying the freeze-thaw damage mechanisms and safety protection of jointed rock masses in cold regions.

Based on the working condition, structure composition and working principle of the mine unanchoring robot, the whole machine model was established by using the three-dimensional software SolidWorks, and the variation law of the center of gravity position of the whole machine and the anchor-breaking manipulator in different postures and the dynamic characteristics of the crawler walking system were analyzed. The results show that under ideal conditions, the maximum lateral slope angle that can meet the normal operation of the unanchoring robot is 10°. Under the forward and turning conditions, the force between the crawler board and the driving sprocket during the movement of the mine unanchoring robot is very similar in the vertical, longitudinal and horizontal directions. The force in the Y direction is approximately sinusoidal, and the force in the Z direction is almost fluctuating near zero. The numerical comparison shows that the force on the crawler board when turning is 2-3 times of that when forward, so the crawler board is more likely to be damaged when turning, and its maximum bearing capacity should be fully considered in the design and strength check. The research results can provide theoretical basis and technical support for the research and development of mine unanchoring robot.

A collaborative optimization control method based on conflict right-of-way decision-making and driving risk field was proposed to address the problem of efficient and safe access of vehicles at unsignalized intersections in unmanned transportation systems of a mine. Firstly, a vehicle conflict state detection model was established by introducing safety margin information, and a three-level right-of-way system of first-come and first-leave, load priority, and priority right-of-way decision library was constructed. Secondly, based on the characteristics of mine working conditions, a driving risk field was established as the safety optimization basis for collaborative optimization control of unsignalized intersections. Finally, by integrating environmental factors, an optimization objective function was established with minimizing traffic risk as the primary objective and traffic efficiency as the secondary objective. A validation scenario for open-pit mine transportation was designed, which includes multiple conflict situations, to verify the collaborative control method. The simulation results show that the collaborative control method can achieve the coordinated and orderly passage of multiple vehicles through unsignalized intersections without stopping, while maintaining the minimum safe distance. The research results can provide a safe and efficient access plan for unsignalized intersections in unmanned transportation systems of smart mines.

In order to achieve the goals of balanced coal flow control, energy saving, and efficiency improvement for the belt conveyor in the mining area of the 4205 working face at Longquan Coal Mine, a mathematical model of the belt conveyor was established. The Multiverse Optimizer (MVO) algorithm was employed to optimize the fuzzy PID controller. Simulations were conducted based on MATLAB, and the results were compared and validated against actual field data. The results are as follows. Firstly, compared with the traditional PID control, the fuzzy PID control optimized by MVO algorithm reduces the adjustment time and overshoot by 46.4% and 34.49 percentage points respectively, and the fitness value converges from 1 022 of the initial iteration to 901.8, indicating that the response speed, stability and anti-interference ability of the system are significantly improved. Secondly, by comparing and analyzing the actual belt speed of the belt conveyor and the regulated belt speed of MVO-Fuzzy-PID within 300 s of five time periods on the belt conveyor, it is verified that the regulated belt speed can be closer to the set value more accurately. Thirdly, from the power point of view, the total power of the motor after MVO-Fuzzy-PID control is significantly reduced. Therefore, the MVO algorithm optimizes the belt speed to achieve energy-saving control and fast matching of coal flow.

Aiming at the problem of low fault diagnosis accuracy caused by unbalanced fault categories of mining excavator engine, an intelligent fault diagnosis method of mining excavator engine based on improved whale optimization algorithm (WOA) to optimize light gradient boosting machine (LightGBM) was proposed. Firstly, the recursive feature cross-validation elimination method (RFECV) was used to extract the features of the fault data of collected excavator engine, and the irrelevant features were deleted. Secondly, Focal-Loss was used to improve the loss function of LightGBM, and an improved WOA was proposed to optimize the hyperparameters of LightGBM, and a new diagnostic model was constructed. Finally, the engine fault data of a mine excavator was used for verification, and compared with common integrated models, tuning frameworks and diagnostic algorithms. The results show that the accuracy and F1 score of the proposed mining excavator engine fault diagnosis model IWOA-LightGBM are 98.08% and 98.53% respectively, and the diagnostic performance is good, which can provide reference for the intelligent diagnosis of mining machinery and equipment.

In response to the problems of large mining range, ore dilution rate, low mechanization degree, and high safety risks in the shallow hole shrinkage mining method for sharply inclined thin ore veins in China, taking the occurrence conditions of a certain metal mine as the engineering application background, a mechanized mining process of shallow hole shrinkage mining method was proposed, and the mechanized mining idea of using micro rock drilling rigs to drill shallow holes upwards was determined. Firstly, based on the operating conditions of the experimental mining site, the design principles and main technical parameters of the micro rock drilling rig were determined. Secondly, the whole machine adopted the design scheme of modularization and 4-degree-of-freedom rock drilling positioning, and the passability, rock drilling positioning, machine stability, and in-situ steering drive system of the micro rock drilling rig were calculated and simulated in narrow and complex environments. The results show that the micro rock drilling rig can meet the practical engineering applications of narrow space transition driving, rock drilling positioning, and visual distance remote control operation in the mining of sharply inclined thin ore veins with shallow hole shrinkage method. The fastest single hole drilling speed can reach 2.2 m/min, the average of efficiency of artificialrock drilling is 1.35 m/min, and the drilling efficiency of equipment is 1.69 m/min, and the comprehensive rock drilling efficiency has been improved by more than 25% compared to manual rock drilling efficiency. At the same time, visual distance remote control can effectively reduce the number of operators, reduce mining amplitude, reduce safety risks, and improve comprehensive mining efficiency, which can provide equipment scheme reference for mechanized fransformation of steeply inclined thin veins with mining dip angle greater than 65° and pulse thickness less than 0.8 m.

Mine fire smoke target detection is one of the important preventive measures to prevent fire accidents in mines. In order to improve the accuracy and speed of fire smoke target detection in mines, a mine fire smoke target detection scheme based on improved YOLOv10s was proposed. Firstly, the collected mine fire smoke image dataset was divided into a training set, validation set and test set according to 7:2:1 after annotation on the online annotation platform. Before training, the images were subjected to wavelet denoising and Auto-Msrcr algorithm enhancement processing, then the original YOLOv10 loss function was reconstructed using Focaler-IoU. The attention module CBAM that strengthened the performance of convolutional neural networks was added, and the third C2f module in Neck was replaced by the cross-stage partial network module VoV-GSCSP, thereby improving the representation ability and decision-making performance of the model. Finally, the feature weights of mine fire smoke recognition were improved. The experimental results show that the improved YOLOv10s model has a 3.5% higher accuracy than the original model, the average precision mAP@50 and mAP@50−95 are increased by 0.7% and 2.2% respectively, and the detection frame rate is increased by 11.9 frames/s. Compared with other mainstream YOLO models, the improved YOLOv10s model has higher detection accuracy and speed, as well as better comprehensive detection performance, which is suitable for high-precision and high real-time mine fire smoke detection scenarios.

The implementation and application of AI management system module algorithms in coal mines is the core issues in the field of smart mine construction. Promoting integrated mine management and control can help improve the intelligent monitoring capabilities of mines. A three-level and five-layer mining AI management system architecture was constructed based on mining intelligent recognition technology, and mining AI management system algorithms including comprehensive mining module, excavation module, transportation module and general module were developed, forming a software+server intelligent visual application mode. The comprehensive mining module adopts CNN, YOLO Fastest V2 and YOLOv3 models to achieve coal mining equipment recognition, area target and support posture detection. The excavation module uses the YOLO model to identify the front beam support and human related detection. The transportation module uses the YOLACT model to identify the operation status of the belt, large coal blocks and foreign objects. The general module implements safety helmets, personnel behavior and environmental detection through OpenCV, YOLO and YOLOv4 models. Among them, the mean average precision of YOLACT model training prediction boxes is 86.79%, and the mean average precision of mask is 83.58%, both of which are at a high level. Real-time display of equipment, personnel, environment and other status results in the fully mechanized mining face. The excavation working face can realize the identification and alarm of personnel intrusion in hazardous areas and abnormal operation processes. The transportation system can realize monitoring of coal quantity of belt, large blocks, foreign objects, etc., real-time tracking and monitoring of the target and early warning of abnormal behavior. The general scenario timely alarms the unsafe behavior in the key underground areas to achieve comprehensive supervision of the entire mining area. The research results can promote the deep integration of AI technology and coal mine safety production, realize the intelligent application scenarios of reducing manpower and improving efficiency in coal mines, which is of great significance for the intelligent mining of coal mines in China.

Noise pollution in mining areas is a prominent problem in the construction of green mines, and achieving precise and continuous monitoring of noise is crucial for environmental protection and occupational health. To address the the problem of insufficient timeliness and continuity in traditional manual noise monitoring applications in mining areas, taking a typical mining area in Hunan Province as the research background, eight functional areas including open-pit mines, beneficiation plants, transportation work areas, and living areas were selected to carry out 24-hour continuous manual and automatic noise monitoring. Linear regression and bias analysis were conducted to verify the reliability of automatic monitoring technology by comparing over 190 sets of equivalent sound level data per hour. The results show that the automatic monitoring and manual monitoring results are highly consistent, with linear regression slopes ranging from 0.983 5 to 1.055 4, correlation coefficients (r) above 0.997, and absolute deviations controlled within ±1 dB. It is fully verified that the automatic noise monitoring system has good applicability and accuracy in complex mining environments. The monitoring data also reveals that the noise level in the production area (70 - 85 dB) is significantly higher than that in the living area(<55 dB), and after conducting prevention and control measures, the sound level has been reduced by about 20−30 dB compared to the source intensity, with significant prevention and control effects. Finally, noise management suggestions are put for forward for the mine.

With the exhaustion of high-grade magnesite resources, it is of great significance to carry out fine purification of low-grade magnesite through beneficiation methods. The most effective beneficiation method for magnesite is flotation, and the key factor determining the flotation effect is flotation collector. The research status of flotation collectors for magnesite at home and abroad was introduced, and the research progress of the interaction mechanism of collectors and magnesite and its gangue minerals were analyzed from two aspects, including macroscopic conventional characterization test technology and microscopic molecular simulation technology. Comprehensive analysis indicates that it is necessary to strengthen the research on new collectors for synergistic impurity removal. The combination of experiments and molecular simulation techniques to verify the flotation performance and mechanism of collectors will be the focus of future research. The new collector should also have the characteristics of green, environmental protection and no pollution while having high selectivity and collecting ability. The research results can provide a reference for the sustainable development of magnesite resources and the development of flotation reagents.

The iron ore resources are abundant in China, but showing poor, fine, miscellaneous characteristics, more than 98% of iron ore resources need to be beneficiation processing to be effectively utilized. Grinding process, as a preparatory process for the processing and utilization of iron ore, plays a crucial role in the subsequent separation indexes. However, it has high energy consumption and low energy utilization rate, especially during fine and ultrafine grinding, which consumes more energy and is not conducive to reducing mineral processing costs. Adding grinding aids in the grinding process is one of the effective measures to improve grinding efficiency and reduce production costs. By reviewing the research and application status of grinding aids in the field of iron ore grinding, the development and application of new grinding aids, the impact of grinding aids on subsequent operations, and the action mechanism of grinding aids, it is pointed out that the selection and application of iron ore grinding aids need to be adapted to the properties of the ore, the grinding environment, and the grinding conditions. It is necessary to strengthen the development of new grinding aids and the research on their impacts on subsequent mineral processing operations, so as to provide guidance for the selection and application of grinding aids in the field of iron ore grinding.

Taking the fine grinding deep separation tailings of micro-fine iron concentrate in a factory in Panxi area as the research object, the TiO₂ grade is 19.51%, and the gangue minerals are mainly pyroxene, chlorite and amphibole. According to the characteristics of the ore, BY series inhibitors were developed and used with MOH collector. The optimal reagent dosage was determined by inhibitor screening test, inhibitor dosage test, collector dosage test and pH condition test, and the flotation closed-circuit test was carried out. The results show that considering the grade and recovery rate of titanium concentrate, it is determined that BY-3 is used as inhibitor, the optimal dosage is 1 500 g/t, the optimal dosage of MOH collector is 2 500 g/t, and the pH is controlled at about 3.5 during roughing. Through the closed-circuit process of "one coarse, one fine and desulfurization, combining one coarse, one sweep and four fine, as well as returning the intermediate ore in sequence for titanium selection", the ilmenite concentrate with a yield of 30.98%, a TiO₂ grade of 46.94% and a TiO₂ recovery of 74.54% and the tailings with a TiO₂ grade of 5.27% can be obtained. The research results can provide a reference for the efficient recovery and utilization of the same type of ore.

An iron tailings in Peru contain valuable metals such as copper, lead and zinc. The copper grade of the tailings is 0.38%, which mainly existing in the form of primary copper sulfide and secondary copper sulfide. The lead grade is 0.79%, mainly occurring in sulfide and carbonate minerals. The zinc grade is 2.68%, mainly occurring in sulfides. The sulfur grade is 8.45%, mainly existing in the form of sulfides. The optimization test of flotation reagent type was carried out by using the process flow of "copper-lead-zinc partially mixed floating, copper and lead-zinc separation, lead-zinc and other floating re-separation". In the mixed flotation roughing operation, lime + CL agent was used as the regulator, butyl xanthate + ester-112 was used as the collecting foaming agent. Sodium sulfide + sodium bisulfite inhibitor system was used in the separation of copper-zinc, and 25^# black powder was used as the collecting foaming agent in the floating and re-separation operation of lead-zinc. A closed-circuit flotation test was designed based on the open-circuit test results of the whole process flotation and the middlings circulation scheme. The results show that the copper grade of the copper concentrate is 22.03%, and the copper recovery rate is 64.93%. The zinc grade of zinc concentrate is 47.12%, and the zinc recovery rate is 72.00%. The lead grade of lead-zinc concentrate is 21.65%, the zinc grade is 25.13%, the lead recovery rate is 58.84%, and the zinc recovery rate is 19.95%.

When oleic acid is used as collector in winter production of a fluorite concentrator in Chengde, due to poor water solubility and dispersion of oleic acid, the collection capacity is insufficient and the low-temperature resistance is poor. It is necessary to heat the slurry to more than 20 ℃, resulting in high production cost and energy consumption. In order to solve these problems, a new type of low-temperature fluorite collector CK-1 was developed using oleic acid with different iodine values to sulfonate and compound-saponification-emulsification. After the application of collector CK-1, the recovery rate of fluorite concentrate increases by 0.77 percentage points compared with the original production index under the condition of normal temperature production in summer. In the case of slurry temperature of 12 ℃ in winter, the beneficiation index is similar to that of the original condition with slurry temperature of 25 ℃ in summer and oleic acid as collector, but the heating cost per ton of ore is reduced by 11.03 yuan, and the flotation without heating in winter is realized, and the economic benefit is remarkable. In the northern region of China, the annual heating cost of fluorite beneficiation in winter reaches tens of millions of yuan, so CK-1 has good application value in the northern region of China.

In order to promote the resource utilization of coal gasification slag (CGS), the effect of composite excitation of four activators on the volcanic ash activity of CGS was studied by response surface method. The compressive strength of the prepared samples at different ages was measured respectively, and then the corresponding activity index was calculated to evaluate the volcanic ash activity. Meanwhile, a quaternary quadratic polynomial regression model for the effects of the dosages of four activators on the activity index was established, and the optimal composite excitation ratio of CGS was obtained through multi-objective optimization. The results show that in the process of composite chemical excitation, water glass has the greatest influence on the 3 d and 7 d activity index of CGS, and calcium carbide slag has the greatest influence on the 28 d activity index of CGS. The multivariate correlation coefficients of the three regression equation models are close to 1, which proves that the model has a good fitting effect. Numerical function of Design-Expert software was used to optimize the multi-objective. The optimal ratio of composite chemical excitation is obtained: the dosage of calcium carbide slag, desulfurization gypsum, sodium sulfate anhydrous and water glass is 0.97%, 1.61%, 2.55% and 10%, respectively. The absolute error between the measured value and the predicted value of the activity index on 3 d, 7 d and 28 d is not more than14%, and the relative error is not more than 7%, indicating that the regression model is reliable.

Research on the exploration and development of hot dry rock is significant for promoting the global energy transition, achieving sustainable utilization of clean energy, and supporting carbon neutrality goals. To comprehensively and macroscopically understand the latest research progress and technological trends in the field of hot dry rock exploration and development, a bibliometric analysis and thematic exploration of relevant papers and patents were conducted. The trend of publication, the trend of patent application, the distribution of major countries and institutions, research topics and research hotspots were analyzed. The results indicate that the global research in the field of hot dry rock is in a period of rapid development, and China has occupied a dominant position in basic research and technology research and development, but there is still room for improvement in research quality and internationalization process. The research hotspots focus on five key areas, including geothermal energy extraction and utilization, genesis and resource exploration of hot dry rock, reservoir mechanical properties and heat storage construction, reservoir monitoring and evaluation, and seismic prediction and control. Among them, the coupling mechanism of high temperature environment and stress, low temperature fracturing technology and the application of nuclear magnetic resonance technology are important research fields in recent years. Although the development and utilization of hot dry rock is gradually entering the engineering demonstration stage, the commercialization still faces challenges such as technical bottlenecks, environmental risks, and insufficient economic viability. Future efforts should focus on advancing geophysical exploration technologies, enhancing heat reservoir modification techniques, optimizing hydraulic fracturing and drilling processes, investigating the dynamic evolution of fracture networks and long-term stability of heat reservoirs, and improving heat extraction and heat exchange efficiency. Additionally, strengthening the integration of fundamental research and applied technologies is critical to overcome technical challenges, reduce development costs, and promote the sustainable utilization of hot dry rock resources.

In order to alleviate the imbalance between supply and demand of some key rare earth metals in the electric vehicle industry, the Gompertz model and the material flow analysis method were used to predict the theoretical demand of electric vehicles in China from 2024 to 2050. The effects of two paths of motor technology innovation and comprehensive utilization of resources on the supply and demand of four key rare earth metals (neodymium, dysprosium, praseodymium and terbium) in the electric vehicle industry were discussed. The results show that under the given scenario of weak motor technology innovation effect, praseodymium and neodymium are in sufficient supply, while dysprosium and terbium are still in short supply by 2050. In the semi-derare earthing scenario and the radical scenario where the effect of motor technology innovation is more significant, dysprosium will achieve supply and demand balance in 2043 and 2039 respectively, and terbium will achieve sufficient supply in 2041 and 2031 respectively. In the path of comprehensive utilization of resources, recycling has a significant effect on alleviating the imbalance between supply and demand of rare earths in the long run, and the overall decline in the output of restricted electric vehicles is 79%. The hybrid vehicle reduces the use of rare earth resources and improves the allocation efficiency. The two paths of motor technology innovation and comprehensive utilization of resources can effectively alleviate the imbalance between supply and demand of key rare earth metals by promoting the development of new quality productive forces.