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.

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.

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.

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.

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.

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.

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.

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.

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.

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.