With the continuous exploitation of wolframite resources, the raw ore gradually tends to be poor and fine. Flotation has become an effective means to improve the recovery efficiency of fine wolframite. In recent years, study of flotation technology has mainly focused on the development of flotation reagents. Taking the development of wolframite flotation reagents as the starting point, the development of collectors, activators and inhibitors in wolframite flotation was introduced. The combination methods, advantages and disadvantages and indexes of reagents were described in detail. The flotation process mechanism of flotation reagents and the mechanism of solid-drug surface action were analyzed. The results show that the chelating collector has strong selectivity, but the cost of the reagent is high, the manufacturing process is complex and the stability is poor, and there are few reagents that can be applied in actual production. Fatty acid collectors are widely used because of their strong collecting ability and low price, but their selectivity will be reduced, and they are often used in combination with other agents. The collecting performance of arsonic acid and phosphonic acid collectors is better than that of fatty acid collectors, but because of its high price and environmental pollution, it has not been applied in actual industrial production. The combined use of collectors can not only reduce the production cost of mines, but also reduce the use of toxic agents to a certain extent. Highly selective activators and inhibitors can achieve efficient separation of wolframite slime and gangue minerals. According to the existing situation, new reagents with high selectivity, low dosage, environmental protection and non-toxicity should be developed according to different ore properties.

In view of the limitations of existing technologies in the field of hydrometallurgy regarding green environmental protection, the application value and development potential of the glycine leaching system as a new type of green hydrometallurgical leaching technology were explored. By analyzing the unique physicochemical properties of glycine and its application advantages in the hydrometallurgy industry, the development history of the glycine hydrometallurgical leaching technology was reviewed, the research status and commercial dynamics of this technology in treating different types of mineral resources were sorted out, and the main existing problems of the technology were systematically summarized. The research results show that the glycine green hydrometallurgical leaching technology can expand the existing technologies in the metallurgical industry, and has the potential to replace the traditional cyanide gold extraction technology, especially in the field of rare and precious metals. Meanwhile, from aspects such as applicable fields, leaching efficiency of target metals, universality for secondary resources, and the mechanism of synergistic leaching systems, the development direction of the technology is clarified. The glycine green hydrometallurgical leaching technology has significant application value in the field of green hydrometallurgy, and can provide references for metal resource utilization, recovery of rare and precious resources, and secondary resource processing.

With the deepening of environmental protection concepts and the continuous advancement of battery technology, the development of new energy vehicles has entered an explosive growth period, and it has also triggered a wave of disposal of retired batteries. In order to cope with the challenge of efficient and green recycling of waste lithium iron phosphate (LFP) batteries, the main literatures on the recycling of lithium iron phosphate batteries at home and abroad in recent years were comprehensively reviewed, and the latest developments of pretreatment, regeneration and repair, pyrometallurgical and wet recycling technologies were systematically introduced. By analyzing and comparing the main characteristics and shortcomings of various recovery technologies, the advantages of wet selective leaching in current recovery practice were pointed out, and the necessity of its development in the future comprehensive recovery of all components and multi-process coordination was emphasized.

Aiming at the problem of stable driving of mining rehicle in the complex terrain of submarine cobalt-rich crusts, a scheme of four-track all-wheel drive travel mechanism for deep-sea mining vehicles and a terrain-adaptive control method were proposed, and a mechanical model of four-track travel was established. A multi-body dynamics simulation model was built based on Recurdyn software. The characteristics of the four-track travel mechanism, such as straight-line travel, climbing, obstacle-crossing and steering, were analyzed, and laboratory tests and marine tests for the travel mechanism were carried out for verification. The results show that the test results are close to the theoretical calculation values, with the calculation error within 10%. The adaptive control method effectively improves the travel effect of the travel mechanism and reduces the deviation of straight-line travel. When the travel speed is 0.051 m/s, the adoption of vehicle body leveling control can improve the travel stability by 2 to 3 times. However, when the travel speed is 0.198 m/s, the control effect is relatively poor. On the whole, as the travel speed increases, the effect of the adaptive control weakens continuously. The research results can provide references for the research and development of travel technologies and equipment in deep-sea complex terrains.

With the increase of mining depth, open stope mining method is facing greater safety hazards and environmental pressure. Filling mining method, as a safe and green mining technology, has been widely used in mining. Taking a large copper mine as the research object, combined with theoretical analysis and numerical simulation methods, the stope structure parameters of upward layered point pillar filling mining method were optimized, and the effects of stope length, point pillar size and point pillar center spacing on stope stability and mine production capacity were systematically analyzed. The results show that when the stope length is 65 m, the point pillar size is 5 m×5 m, and the point pillar center spacing is 15 m, the stability of the mine stope is high and the production efficiency is the best. The optimization scheme of stope structure parameters can not only effectively guarantee the safe mining of the mine, but also improve the utilization rate of resources, which provides a scientific basis for the application of filling mining technology in similar mines.

To optimize the mechanical strength performance of mine waste rock-tailings cemented backfill, the Box-Behnken design within the response surface methodology (RSM) was used to conduct a three-factor-three-level test. The synergistic effects of waste rock particle size (0 to −5 mm, +5 mm to −10 mm, +10 mm to −15 mm), mass concentration (84%, 86%, 88%), and sand-to-binder ratio (53%, 60%, 67%) on the uniaxial compressive strength of backfill at different curing ages (7 and 28 days) were systematically explored. At the same time, the traditional orthogonal test was introduced to compare the prediction accuracy and efficiency with the RSM. The RSM results reveal that particle size of waste rock predominantly governs the early-stage strength of the backfill, while mass concentration significantly influences the later-stage strength. The synergistic interaction between particle size and mass concentration is the most pronounced, jointly regulating the skeleton stability and interfacial bonding properties of the backfill. After experimental verification, the accuracy (R²) of the backfill strength prediction model obtained based on RSM is 0.994 9 (7 d) and 0.983 7 (28 d), respectively. The corresponding optimal filling material proportion condition are waste rock particle size of +5 mm to −10 mm, mass concentration of 85.5%, and sand-to-binder ratio of 58.6%. The results of the orthogonal experiment indicate that the particle size of waste rock plays a dominant role in the backfill strength in the early and later stages. Research has shown that RSM can effectively analyze the nonlinear coupling relationship of multiple factors, and the prediction accuracy is significantly improved compared to traditional orthogonal experimental methods.

In order to investigate the microscopic structural characteristics and uniaxial damage evolution law of loess-slag-based cemented filling materials with different water-cement ratios, scanning electron microscopy and acoustic emission tests were conducted on the loess-slag-based cemented filling materials. Furthermore, PFC2D was used to investigate the crack evolution and particle damage characteristics of cemented filling materials with different water-cement ratios under uniaxial compression. The results show that when the water-cement ratio is small, the cemented filling material can generate more hydration products and the structure of the specimen is denser. The acoustic emission ringing count curves of cemented filling materials can be divided into compaction stage, linear-elastic deformation stage, crack constant-velocity expansion stage, crack sudden increase stage, and post-peak stage, and the ringing count characteristics are correlated with the strength characteristics. As the water-cement ratio increases, the cracking stress and damage stress during the compression process of the specimen gradually decrease, and the ratio of cracking stress to peak stress and damage stress to peak stress are not affected by the water-cement ratio. When the cemented filling material is damaged, shear cracks are the main type. As the water-cement ratio decreases, the number of cracks increases and the maximum value of the force chain increases. Changing the water-cement ratio has little effect on the spatial distribution of internal cracks and force chains in the specimens.

The measurement error of the filling batching system is the key factor affecting the quality of the filling body. In order to reveal the effect of the fluctuation in mass fraction and pumping agent dosage caused by the measurement error on the working performance of the filling slurry, based on the cement hydration mechanism and the action principle of the pumping agent, the response surface and variance analysis methods were used to carry out mechanical properties, flow properties and rheological properties tests, and industrial test verification was carried out to determine the optimal mass fraction and pumping agent dosage. The results are concluded as follows. Firstly, when the mass fraction and pumping agent dosage fluctuated within ±1%, the main effect significantly affected the 28 day strength, viscosity, slump, expansion and average viscosity coefficient, and the interaction effect significantly affected the 28 day strength, viscosity and average viscosity coefficient. Secondly, fluctuations in mass fraction and pumping agent dosage can cause changes in the proportion of free water in the filling slurry, thereby affecting the working performance of the filling slurry. Finality, it is suggested that the fluctuation range of the mass fraction of the mine should be kept between 78% and 79%, and the fluctuation range of the pumping agent dosage should be kept between 1% and 2%. The research results can provide a theoretical basis for the construction of filling batching systems and the accuracy calibration of batching equipment.

The coarse aggregate backfill has high rigidity, poor toughness, and local energy storage accumulation, which is easy to cause safety problems. The addition of fiber can improve the toughness and ductility of the backfill and enhance its mechanical properties. Using coarse aggregate, waste rock, rod sand and river sand from Longshou Mine of Jinchuan as raw materials, the effect of fiber blending process on uniaxial compressive strength of backfill was studied. Design-Expert software was used to analyze the influences of various factors (slurry mass concentration, fiber volume rate, and cement content) on the early mechanical properties of backfill and optimize the parameters. The nonlinear regression models between the early uniaxial compressive strength value and various factors were established to reveal the interaction effects between different factors, and the cost of filling slurry material after adding fiber was calculated. The results show that the addition of fiber can significantly improve the compressive strength of the backfill. Compared with the blank group without fiber (3.03 MPa), the strength of the backfill in scheme Ⅱ (wet mixing of filling materials firstly, and then adding fibers in three stages) is 4.35 MPa, with an increase of 43.56%, which is the optimal scheme. The significant influencing factors of early mechanical properties of fiber reinforced backfill are ordered as slurry mass concentration > cement content > fiber volume rate. The interaction effect between slurry mass concentration and cement content is the most significant, which verifies the reliability of the regression model. After adding fibers, the cost of filling slurry material only increases by 0.67%−15.6%. On the premise of meeting the strength requirements of the backfill, the content of coarse aggregate and cement can be appropriately reduced, which can also reduce the cost.

With the increase of mining depth, the backfill body is affected by high ground stress, mining disturbance and groundwater erosion. In order to explore the influence of groundwater erosion on the mechanical properties of cemented backfill body with polypropylene fiber tailings, uniaxial compression test and Brazilian splitting test were carried out on specimens with different fiber contents, and specimens with better mechanical properties were selected. Based on the groundwater erosion environment, uniaxial compression and acoustic emission monitoring tests were carried out to study the damage and failure evolution characteristics of polypropylene fiber backfill body under the action of groundwater. The results show that with the increase of polypropylene fiber content, the compressive strength of backfill body increases first and then decreases, and the peak strength of the specimen with 0.3% fiber content is 3.82 MPa, which is the best. After groundwater erosion, the cumulative ringing count characteristics of acoustic emission can be divided into three stages: initial active stage, steady growth stage and rapid growth stage, and obvious damage precursor characteristics appear in the steady growth stage. The durability of the backfill body specimens with different pH erosion of groundwater is as follows: eroded backfill body specimens with pH=9> eroded backfill body specimens with pH=7> eroded backfill body specimens with pH=5> non eroded backfill body specimens. With the increase of groundwater pH, the RA-AF shear crack signal continues to decrease, the damage and failure of the backfill body changes from shear failure to tensile failure. The research results can provide reference for the improvement of mechanical properties and durability of mine backfill body.

In order to better monitor the filling morphology effect of goaf, a study on the characterization of grouting filling morphology effect with polarizability as the target was carried out based on resistivity parameters. Seven different kinds of cement were selected and prepared with five different contents of graphite powder. The variation of resistivity and polarizability of cement-based grouting filling materials was analyzed. The electrical characteristics and compressive strength of grouting filling materials under different cement types and ratios were studied, and the application test was carried out. The indoor test results indicate that with the increase of graphite powder conten, the compressive strength decreases, and the polarizability increases. When the ratio of cement to graphite is less than 10:1, the polarizability increases rapidly. In addition to sulphoaluminate cement, the content of graphite powder has little effect on the resistivity of cement-based grouting filling materials. Under the condition that the resistivity difference before and after grouting filling in goaf is not obvious, the visual characterization of filling morphology effect can be realized by polarizability (when the polarizability value of filling material is more than 3 times that of surrounding rock, the characterization effect is obvious). The research finding which is of great significance for broadening the field of grouting geophysical monitoring and improving the monitoring effect.

In order to explore the influence of physical properties of tailings on solid flux and optimize the thickening process parameters, the total tailings samples of 10 typical metal mines were selected, and the quantitative relationships between solid flux and tailings particle size or density was systematically studied. Combined with static flocculation sedimentation and dynamic thickening test data, a solid flux prediction model based on particle size-density composite parameters was established. The results show that under the condition of static flocculation sedimentation, the type and unit consumption of flocculant significantly affect the sedimentation rate and underflow concentration, and rational regulation of flocculation conditions can effectively improve sedimentation efficiency. The solid flux is significantly positively correlated with the square root of the median particle size and the density correction value of the tailings (R²≥0.94). The particle size-density composite parameters prediction model established based on nonlinear regression can accurately characterize the quantitative relationship between the physical properties of tailings and solid flux. Under dynamic thickening conditions, the feed rate of tailings slurry is linearly positively correlated with the solid flux, and the solid content of the overflow water forms a dual constraint mechanism on the flux threshold. The comparative test shows that the dynamic thickening process can increase the underflow concentration by 10%−15% compared with the static sedimentation, which fully verifies the technical advantages of the deep cone thickener in the preparation of high concentration slurry. The research results can provide theoretical basis and technical support for efficient thickening and intelligent filling of mine tailings.

In the second-step mining of open stoping with subsequent filling mining method, the blasting vibration has significant influence on the stability of the artificial pillar formed after the cement filling in the first-step stope. Based on the background of mining in the transition from open-pit to underground in Sijiaying Iron Mine, a 3D geological model and a numerical calculation model of stope were established by using the FLAC numerical simulation method. And three mining sequences of the second-step stope in the mining panel were studied, including “from one side to the other side” “from the center to both sides” and “from two sides to the center”. When the distance between the blasting hole and the backfill was 1.0 m and 1.5 m respectively, the characteristics of the effect of blasting on the stability of the artificial pillar were obtained, and the strength demand of the backfill body was inverted. The results are concluded as follows. Firstly, when the peak pressure of the blasting load is 15 MPa, with the increase in the distance from the hole to the backfill, the maximum principal stress of the backfill in the first-step stope decreases. The concentrated stress and plastic failure range in the backfill under the “from two sides to the center” mining sequence are the least, which is the most favorable to the stability of the backfill. Secondly, when the mining sequence of the second-step stope is “from two sides to the center”, the longer the distance between the blasting hole and the backfill, the smaller the plastic zone in the backfill, which is more favorable to the stability of the backfill. Meanwhile, the larger the distribution range of the shear plastic zone formed in the two-step mining ore body, the more conducive to the carving of the two-step stope. Thirdly, the strength of cemented backfill prepared by cementing powder and unclassified tailings with a ratio of1:6can meet the stability requirements of artificial pillars.

Aiming at the problem of low prediction accuracy of existing blasting vibration velocity prediction formulas in complex ground environments, a BP neural network model based on improved grey wolf optimization (I-GWO) Algorithm was proposed. The grey wolf algorithm was improved by changing the convergence factor function of the neural network to enhance optimization accuracy, initializing the wolf pack position through chaotic mapping to accelerate solution speed, and dynamically adjusting weights based on step size Euclidean distance to improve optimization efficiency. Based on the monitoring data of blasting vibration velocity at the Lilou-Wuji Iron Mine, the I-GWO-BP model was established by selecting the blast center distance, the maximum single-stage charge amount, and total charge amount as input parameters. The results show that the convergence speed and accuracy of the I-GWO-BP model are better than those of the GWO-BP model and BP model, and the optimization effect is significant. The predicted values of the I-GWO-BP model are basically within the confidence band of the measured values ±0.08 cm/s, with an average absolute percentage error of 13.84%. Its prediction performance is significantly better than other prediction methods, and its prediction accuracy is high. The research results can provide some reference for predicting the blasting vibration velocity in mines.

In order to realize the safe and efficient mining of metal mines in the surface protection area, taking the mining of inclined orebodies under slope in Paishanlou Gold Mine as the engineering background, the roof caving characteristics, stability conditions of caving arch and its control and utilization technology in the goaf of inclined orebodies were systematically studied. It was analyzed and concluded that the inclined orebodies in Paishanlou Gold Mine conform to the characteristics of the arch caving model, and the mathematical relationships between the critical caving span and caving height of the inclined orebodies under slope were established. A goaf caving process control scheme with the subarea mining model as the core was proposed, and the subarea open-stope mining with subsequent centralized filling mining technology was developed. The results of on-site practice show that after adopting this mining technology, the mining cost is decreased by 26.8 yuan/t, the production capacity is increased by 20%, the ore loss rate is decreased by 1.5%, the dilution rate is decreased by 3%, and the mined metal quantity is increased by 427.5 kg. This method not only meets the surface protection requirements of Paishanlou Gold Mine, but also achieves the goals of low-cost, safe and efficient mining. The research results can provide technical references for the mining of low-grade orebodies in surface protection areas.

In view of the characteristics that the soft powder ore rock in the deep mining underground roadway of Jinshandian Mine can not take out the complete sample on site, the direct test of compressive strength of loose soft rock mass by rebound instrument was explored. Taking the powder ore and skarn fracture zone of −425 m and −455 m horizontal tunneling roadway in the east-west mining area of Jinshandian Mine as the research object, the rebound value was tested by rebound instrument. Based on the strength formula of concrete compressive strength detected by rebound instrument in national standards and industry standards, according to the engineering geological characteristics of Jinshandian Mine, the empirical formula was optimized, and the correlation sample of rebound value and compressive strength was constructed. Using mathematical statistics method, two modified empirical formulas for strength measurement of soft powder ore rock in Jinshandian Mine were obtained by regression. The results show that the average rebound value of −425 m horizontal powder ore rock in the east-west mining area is 19.35, and the average compressive strength is 6.58 MPa. The average rebound value of −455 m horizontal soft rock fracture zone in the west mining area is 21.92, and the average compressive strength is 14.994 MPa. The results are basically consistent with the results of the inversion of the soft powder rock roadway based on the convergence value of the roadway in Jinshandian Mine. The research results provide a feasible solution for the situation that was impossible to take samples on site for indoor rock compressive stength test under poor engineering geological conditions in underground engineering.

Dynamic disasters such as rockburst caused by mining disturbance seriously restrict the development and utilization of deep mineral resources. It is of great significance to explore the propagation process of internal cracks in rocks to reveal the rock failure mechanism and disaster warning. Based on this, the spatial-temporal response characteristics of acoustic emission of granite under uniaxial loading were monitored. The single linkage clustering (SLC) method was used to construct the SLC structure of acoustic emission events. By introducing the spatial correlation length of acoustic emission events, the spatial correlation degree between acoustic emission events at different time scales was analyzed. The results show that the three-dimensional localization and energy properties of acoustic emission events can characterize the propagation and damage evolution process of microcracks in granite specimens. As the stress increases, the link length in the SLC structure gradually decreases, and the correlation within the crack cluster increases. The spatial correlation length has experienced three stages of high-level fluctuations, stable fluctuations and sudden increase. When it is close to the fracture of granite, the spatial correlation length increases sharply due to the redistribution and transmission of stress in the sample, which can be used as the early warning point of granite instability. The SLC method provides an effective method for studying the evolution process of rock crack propagation, which can provide a reference for the early warning and prevention of dynamic disasters such as rock burst.

Aiming at the engineering problems such as insufficient crack detection accuracy and limited real-time performance in the complex geological environment of underground mine tunnels, an underground mine tunnel crack-segmentation network (UMTC-net) integrating multi-scale feature perception and adaptive attention mechanism was proposed. This network can realize cross-scale feature extraction of crack images from local texture to global structure through hierarchical cascading of Swin Transformer module groups. Meanwhile, a scaling cosine attention mechanism encoded by relative positions in logarithmic space was introduced to effectively suppress the interference of abnormal pixels. In addition, a codec framework based on dynamic patch merging/expansion was constructed, which solved the problems of ambiguous boundary positioning of fine cracks and high false detection rate in complex backgrounds in traditional methods. The results show that the UMTC-net has an accuracy of 85.15%, an average intersection-union ratio of 85.78%, and an F₁ value of 83.27% in the Crack 500 dataset, and an accuracy of 87.51%, an average intersection-union ratio of 79.98%, and an F₁ value of 86.95% in the MineTunnelCrack-2000 dataset. It exhibits stronger robustness, especially in low light and high dust environments. This network achieves an inference speed of 38.9 ms on the RTX 3060 mobile graphics card, occupying only 5 230 MB of memory and reducing deployment costs by more than 40%. It meets the real-time and low-power requirements of portable detection devices, and has a higher cost-effectiveness for adaptation. In the field test, the detection efficiency of UMTC-net is 8 times higher than that of manual inspection, and the missed detection rate is reduced from 18% to 3.2%. The research results provide an efficient and accurate new scheme for crack detection in underground mine tunnels, which is helpful to find potential safety hazards in time and ensure the safety of mine production and stable operation of equipment.

Fiber-reinforced wet-mix shotcrete has excellent properties such as deformation resistance and crack resistance. To evaluate the support performance of fiber-reinforced wet-mix shotcrete, a series of tests were conducted, including uniaxial compressive tests, notched beam flexural toughness tests, and disk flexural tests. The test results indicate that, although the addition of fibers slightly reduces the compressive strength of wet-mix shotcrete, the flexural strength and energy absorption capacity have been significantly enhanced. The roadway support test results shows that the compressive strength of the steel fiber wet-mix shotcrete can reach 25 MPa, the thickness of the spray layer is maintained at 100−150 mm, with a minimal rebound and notable support effectiveness.

Abandoned mine not only contains a large number of available resources, but also has many risk factors. In order to scientifically determine the reutilization mode and take into account the risk of many abandoned mines, a risk framework of abandoned mines including six dimensions of technical risk, safety risk, environmental risk, community risk, legal risk and financial risk was constructed, and the risk assessment of reutilization was carried out by LEC risk assessment method. Then, from the perspective of risk management, the method combining improved analytic hierarchy process (IAHP) and TOPSIS was proposed to determine the best reutilization mode of abandoned mines. Finally, taking the closed mine of Muchengjian Coal Mine in Jingxi Mining Area as an example, the proposed method was verified. The results show that the high risk factors of the closed mine are mainly concentrated on safety risk and social risk, and ecotourism is selected as the optimum reutilization mode. This risk management-based method can provide a reference for optimizing the reutilization mode of abandoned mines and effectively reduce the negative effects of mine closure.

In order to explore the potential value of a large amount of safety hazard data in the construction process of intelligent mines, taking a mine in Shandong as an example, comprehensive analysis of its historical safety hazard data from 2014 to 2023 was conducted, and a multidimensional analysis model for mine safety management was constructed. Firstly, a Multi-Layer Perceptron (MLP) was used to construct a personnel, equipment, and environmental classification model for identifying hazards and accidents. Using the Latent Dirichlet Allocation (LDA) topic model, equipment hazards were classified into eight topics of lighting, transportation, support, electrical, firefighting, blasting, ventilation, and miscellaneous. Then, based on the principle of Apriori algorithm, key information was extracted from unstructured hazard text, and the relationship between different hazard features and topics was explored and analyzed. Finally, deep analysis of the data mining results was conducted using a combination of multidimensional analysis and data visualization techniques. The results indicate that equipment related hazards are high-risk areas that require special attention in the safety management of the mine. The lack of support for the roof, potholes on sloping road surfaces, and installation of switch grounding are significant hazard topics and associated rules, and the areas such as S16181 and S18165 are gathering areas for this type of hazard. The multidimensional analysis model constructed by the research can provide a basis for the analysis of mining safety hazards.

In order to monitor the chlorophyll content of plants quickly and non-destructively, two different microbial reclamation treatments (inoculation group and control group) were set up, and six herbaceous plants (Astragalus adsurgens, Medicago sativa, Leymus chinensis, Agropyron cristatum, Elymus sibiricus, Bromus inermis) were selected according to four kinds of mixed sowing ratios (1∶1, 1∶2, 1∶3, 2∶1). The chlorophyll content and spectral reflectance of Astragalus adsurgens in the test area were measured respectively. Using the original spectrum, the logarithm of the reciprocal of the original spectrum, and the first-order differential, combined with three modeling methods of BP neural network regression, support vector machine (SVM) regression, and random forest (RF) regression, models were established for plant spectral characteristic curves under different treatments. The results show that the inoculation treatment increases the chlorophyll content, and the chlorophyll content is also different under different mixed sowing ratios. Compared with the original spectral curve, the modeling accuracy of the reciprocal logarithm and first order differential of original spectral is improved to varying degrees, and the modeling accuracy of FDR is the best. Under the condition of microbial reclamation, the RF regression model has the highest accuracy. Under the conditions of different planting ratios, the model established by BP neural network regression in the 1∶2 and 1∶3 regions of legumes has high accuracy, while the spectral samples in the 1∶1 and 2∶1 regions are more suitable for using RF regression method.

As one of the key processes in the stage open stope with subsequent filling mining method, the quality of the slot raise construction directly affects the effect of the subsequent blasting to form the cutting groove, and ultimately affects the quality of large-scale caving mining. In view of the problems of low intelligence, high safety risk and large occupational injury in the construction of traditional artificial sight distance operation raise boring machine, combined with the mining status and occurrence conditions of porphyry ore body in Shanxi Zijin, the existing construction mode of slot raise was optimized to realize the intelligent construction of slot raise. A dynamic optimization control technology for operation parameters was proposed, which used the mountain climbing method to achieve dynamic parameter optimization, and achieved autonomous and efficient continuous drilling through a remote intelligent control system based on 5G communication technology. The industrial application results show that the raise boring machine with remote intelligent control system can also maintain high-precision hole drilling and hole expansion operations in complex rock formations with fractured zones, with an average pilot hole footage of 1.75 m/hand an average reaming footage of 1.375 m/h, and a deviation rate of only 0.68%. The study can provide a reference for unmanned construction of wellbores in other scenarios.

The existing object detection algorithms for shaking table concentrate bands have problems such as inability to balance detection accuracy and speed, high computational costs, difficulty in compressing model size, and slow inference speed. To address these problems, a lightweight fusion network for shaking tables (YC-Lightweight Net) object detection algorithm was proposed. The YC-Lightweight Net model firstly used a repetitive visual transformation network to extract features from the images of shaking table sub-banding. Then, by introducing group space convolution, multi-scale efficient cross stage fusion modules, and using skip connections, an efficient and lightweight neck network was designed. Finally, a weight based layer adaptive pruning algorithm was used to compress the model size. The experimental results show that the accuracy, recall, mean average precision, and FPS indicators of the YC-Lightweight Net model are 98.4%, 97.9%, 98.8% and 333 frame/s, respectively. The detection accuracy and speed are significantly better than those of the compared models. The number of parameters, floating-point operations, and model size after pruning are 13.9%, 15.4% and 17.5% of the original model, respectively. The pruning operation greatly reduces the computational complexity and model size of the model. The YC-Lightweight Net model has good detection accuracy and real-time performance, meeting the requirements of industrial equipment for lightweight models in shaking table mineral processing plants. The study can provide a technical support for accurate identification of separation points in mineral bands and intelligent upgrading of the shaking table mineral processing plant equipment.

In order to explore the influences of different cutting parameters on the cutting performance of the oscillating cutting disc, the Discrete Element Method was used to simulate the cutting process of the oscillating cutting disc, and the influences of eccentricity distance, oscillating frequency, feed rate and cutting depth on the cutting performance were studied. The results show that the average load of rock breaking with the oscillating cutting disc is obviously lower than that of the non-oscillating cutting disc. When the feed rate is 60 mm/s, 90 mm/s, 120 mm/s, 150 mm/s and 180 mm/s respectively, compared with the non-oscillating condition, the average load of the cutting disc under the oscillating condition is reduced by 37.37%, 44.19%, 57.47%, 60.32% and 61.25% respectively. Under the same condition, with the increase of eccentricity distance, the average load decreases firstly and then tends to be stable. With the increase of feed rate, the average load decreases gradually, and the maximum load increases gradually and then tends to be stable. When the feed rate is less than or equal to 90 mm/s, the average load increases with the increase of the oscillating frequency. When the feed rate is greater than 90 mm/s, the larger the oscillating frequency, the smaller the average load. When the cutting depth is 40 mm, the average load and the maximum load are the smallest. When the eccentricity distance, oscillating frequency, feed rate and cutting depth of the oscillating cutting disc are 3 mm, 60 Hz, 150 mm/s and 40 mm, the cutting performance is the best. The research results can provide a reference for the determination of the cutting parameters of the oscillating cutting disc.

To reveal the energy consumption patterns of irregular ore particles under impact crushing, impact crushing tests were conducted on six types of iron ore with different properties, and the fractal characteristics of irregular iron ore fragmentation were analyzed, as well as the size effect on average particle size of fragments, fractal dimension, and unit absorption energy. Then, the energy consumption model of irregular single particle crushing was established. The results show that the average particle size of fragments, fractal dimension, unit absorption energy all exhibit a power function relationship with initial isosphere diameter under the same impact conditions. As the isosphere diameter of the particles increases, the average particle size of the fragments gradually increases, and the fractal dimension and unit absorption energy gradually decrease. There is an increasing relationship with power function between unit absorption energy and average particle size of fragments. The relationship between the logarithm of unit absorption energy and fractal dimension shows a linear increase. Through the method of ore crushing tests of irregular single ore particle, relationship models of unit crushing energy consumption of irregular iron ore particles changing with the initial size, average particle size of fragments, and fractal dimension were established, with an average correlation coefficient of 0.789, which effectively describes the energy consumption pattern of ore crushing.

With the continuous progress of mineral resources exploration technology, the intelligent identification of rock minerals has become increasingly important in the field of mineral composition analysis. In order to analyze the influence of complex texture structure and variable mineral morphology of rock thin section images on intelligent identification technology, an intelligent identification model of rock minerals based on improved YOLOv8 algorithm (Mineral-YOLO model) was proposed. The Mineral-YOLO model innovatively integrates the LSK module to enhance the identification capacity of the model for different target and background information differences. The ODConv technology is introduced to reduce the influence of background interference, thereby improving the performance of the convolutional network. The loss function is optimized to improve the accuracy mAP of bounding box positioning. In the model training, the self-built data set was extended using the combination enhancement technology, so that the samples of the data set were more abundant. The validation set was used to verify the trained model. The results show that the mean average accuracy of the proposed mineral intelligent identification model is 83.3% and F₁ is 78% when identifying 6 kinds of minerals. Compared with the YOLOv8 model, it is increased by 3 percentage points and 1 percentage points respectively, which proves the high efficiency and accuracy of the Mineral-YOLO model in the intelligent identification of rock minerals.

With the widespread application of lithium-ion batteries in underground mines, the safety issue of mining batteries has become increasingly prominent. The thermal runaway characteristics of large capacity lithium iron phosphate batteries for mining were studied by overcharging tests of 200 Ah LiFePO₄/C battery cell and battery module under different overcharging rates (0.5 C, 1 C, 1.5 C). The results show that the thermal runaway behaviors of the lithium iron phosphate batteries are divided into three stages: shell expansion, slow flue gas injection, and violent flue gas injection with subsequent natural cooling. As overcharging rate increases, the overcharged capacity required in each stage gradually decreases. The temperature after thermal runaway of the battery can reach up to more than 400 ℃, and the maximum temperature in the battery module test is significantly higher than that in the battery cell test. High temperature will pose a severe challenge to the safety of underground mines, and corresponding cooling and protective measures need to be taken. The thermal runaway effect of overcharged battery in the battery module does not cause thermal runaway reactions of adjacent batteries. The critical conditions for the thermal runaway chain reaction of mining batteries still need further study.

Based on the first-principles of density functional theory, quantum chemical calculations were performed using the CASTEP module of Materials Studio (MS) software to simulate and optimize the crystal structure, cleavage surface, and adsorption models of magnesite and hornblende in adsorption with reagents. On this basis, the band structure and density of states of magnesite and hornblende were analyzed. The adsorption energies of dodecylamine and the novel collector KDLX on the magnesite (104) and amphibole (110) surfaces were obtained, respectively. The results show that the band gap widths of magnesite and hornblende are 4.920 eV and 3.962 eV. The optimized crystal structure has a better stability. The ammonium hydrogen atoms in dodecylamine and KDLX undergo hydrogen bonding and physical adsorption with the oxygen atoms of minerals. Compared with dodecylamine, KDLX has a stronger adsorption capacity for hornblende and it is predicted that the collector can be used for flotation removal of silica-containing gangue minerals in magnesite ore. This study has revealed the surface characteristics of minerals and the adsorption mechanism of reagents, which has a guiding significance for the flotation separation of magnesite and hornblende and the selection of flotation reagents.

China's iron ore resources are increasingly depleted, and they have difficult to select characteristics such as poor, fine and miscellaneous. The traditional anionic collector has large dosage, complex reagent system and poor activity. In order to solve this problem, the surfactant processed by industrial waste amine (YTDB) was used as cationic collector to study the single mineral flotation test and mineral adsorption mechanism of quartz and hematite. The results show that when dodecylamine (DDA) is used as collector, under the conditions of pH=7 and collector dosage of 20 mg/L, the recovery rate of quartz is 78.36%, and the recovery rate of hematite is 12.57%. At this time, the flotation difference is the largest. When YTDB is used as collector, under the condition of pH=7 and collector dosage of 15 mg/L, the recovery rate of quartz is 91.27%, and the recovery rate of hematite is 12.67%. At this time, the flotation difference is the largest. YTDB is obviously better than DDA in flotation index, and saves the dosage of reagent to a certain extent. By testing the infrared spectrum, surface tension and Zeta potential before and after the interaction of the agent and the mineral, it is found that YTDB adsorbed on the surface of quartz.

The contents of silver (Ag), lead (Pb), zinc (Zn), iron (Fe), manganese (Mn) and sulfur (S) in a polymetallic ore in Heilongjiang are 330.52 g/t, 0.57%, 0.29%, 25.77%, 9.05% and 3.38%, respectively. Due to the carbon content is high, mineral dissemination relationship is complex, as well as Ag, Pb and Zn are partially wrapped in Fe-Mn minerals, it is difficult to guarantee the concentrate grade and recovery rate. In order to realize the comprehensive recovery of valuable components in the ore, the process of Ag−Pb−Zn mixed flotation and Fe-Mn magnetic separation was adopted, and the full process closed-circuit test was carried out. The Ag, Pb and Zn grades of the Ag−Pb−Zn mixed concentrate obtained by the test are 3 010.80 g/t, 5.39% and 2.37%, respectively, and the recovery rates are 83.35%, 89.61% and 77.55%, respectively. The Fe grade and recovery rate of the Fe concentrate are 60.97% and 8.01%, respectively, and the total Fe recovery rate is 71.89%. The Mn grade and recovery rate of Mn concentrate are 18.30% and 76.38%, respectively. The tailings yield of the full process is 50.23%, and the Ag, Pb and Zn grades of the tailings are 35.07 g/t, 0.055% and 0.068%, respectively. By using copper sulfate as an activator and butyl xanthate+ammonium dibutyl dithiophosphate as a collectors in Ag−Pb−Zn mixed flotation, the process has realized the comprehensive recovery of Ag, Pb and Zn with high recovery rates, as well as the effective recovery of Fe and Mn, additionally, the backwater can be reused in production.

In order to promote the leaching of Ca and Mg elements in anorthite, a strain hzt-1′ with good adaptability to anorthite was screened from the soil of Jialiangshan, Fangshan County, Lvliang City, Shanxi Province. It was identified as Phyllobacterium myrsinacearum. The optimum growth conditions of the strain and the optimum leaching conditions of anorthite in Czapek Medium were investigated. The optimum growth conditions of strain hzt-1′ are as follows: pH of 6, liquid volume of 80 mL, inoculation volume of 7%, glucose as the best carbon source (20 g/L), and NaNO₃ as the best nitrogen source (1 g/L). The optimum leaching conditions of strain hzt-1′ are as follows: pH of 6, inoculation volume of 3%, pulp mass concentration of 20 g/L, and liquid volume of 100 mL. Under these conditions, the leaching rates of Ca²⁺ and Mg²⁺ in anorthite are 50.3% and 39.91%, respectively. The strain promotes the dissolution of anorthite through proton exchange and complexation, accelerates the leaching of Ca²⁺ and Mg²⁺, and thus improves the utilization rate of anorthite and other mineral resources. This study can provide a new strain for efficient leaching of silicate minerals.

As an environmentally friendly material, gold-tailings-based concrete has a wide range of potential applications. However, the complexity of the material composition of gold-tailings-based concrete, traditional prediction methods of compressive strength are often difficult to capture the nonlinear correlation and multivariate coupling characteristics within the material, resulting in insufficient prediction accuracy. Thus, a strength prediction model for gold-tailings-based concrete was proposed based on a deep learning binary fusion model (DP), a fusion Convolutional Neural Network (CNN) and a Gated Recurrent Unit (GRU). Firstly, the mineral, chemical composition and particle size distribution of gold tailings were analyzed, and their leaching toxicity was tested according to relevant standards to ensure their safety and stability as concrete materials. Subsequently, the gold tailings concrete dataset was constructed through experiments and applied to the training and validation of the model. In order to further verify the predictive ability of the model, it was applied to real engineering cases. The results show that the proposed model exhibits high accuracy in both the training and testing process, and is capable of effectively predicting the compressive strength of the gold-tailings-based concrete. The actual engineering cases show that the error range between the predicted and measured compressive strength of concrete with 20%−40% gold tailings is −4.1%−5.7%, which further proves the potential of the model to be applied in engineering practice.