In response to the problems in complex ccoal seams mining, such as tedious procedures, low production, and low efficiency, the intelligent transformation of the No. 2321-34 fully mechanized mining face is taken as the engineering background. Starting from equipment transformation, mining technology, geological conditions, and other aspects, a centralized control system (SAM) for complex condition fully mechanized mining face is constructed, which enables real-time transmission and control of hydraulic support automatic action, transportation equipment linkage, and mining site conditions. It is proposed that the fully mechanized mining face equipment should be adapted to the characteristics of complex coal seams and the key functions of the equipment should be modified accordingly. Safety technologies such as single and bidirectional mining processes in complex coal seams, rapid installation of equipment, and rapid passage through large faults were studied. Industrial practice shows that this technology can optimize the process, achieving an increase in monthly average output from 30000 tons to 65000 tons, a 116. 7% increase in output, a 52% reduction in production team members, and a 261% increase in equipment efficiency, ensuring safe production and providing reference for safe and efficient mining in similar working faces.

To address the development design of level extension for mining the No. 3-1 coal seam at Level II in Cuncaita Coal Mine, Based on constraints including geological conditions, existing development layout, and production system connectivity, research was carried out on the design of the second-level extension and production system optimization. First, the current state of the mine development layout and production system was analyzed from the aspects of industrial site arrangement, development method, transportation system, ventilation system, and drainage system. Second, the design of the second-level extension was determined by analyzing the extension development method, level division and elevation, main roadway layout, panel division, and layout of the first working face. Finally, the production system for the second level was optimized in terms of main(auxiliary) transportation system, ventilation system, and drainage system, achieving effective integration with the mine’ s existing production system. The results show that through reasonable extension development layout and scientific production system optimization, the second-level extension design of Cuncaita Coal Mine effectively improves the utilization rate of existing production systems and facilities, avoids impacts on mine production during extension construction, and can provide a scientific reference for level extension design in mines with subhorizontal coal seam groups.

To address the issue that the goaf and residual coal pillars in the upper seam of contiguous coal seams severely restrict the layout and maintenance of the mining roadways in the lower coal seam, the No. 14103 working face of Zhengli Coal Mine was taken as the research object. Theoretical analysis, numerical simulation, and field measurements were employed to study the layout of mining roadways and surrounding rock control techniques on the 14103 working face. The results indicate that: ① The maximum floor damage depth in the No. 4-1 coal seam is 11. 46 m, which exceeds the maximum spacing between the No. 4-1 and No. 4 coal seams, which is 8. 75 m. The roof of the No. 4 coal seam is damaged and broken. ② The influence width of the concentrated stress on the No. 4 coal seam from the residual coal pillars in the No. 4-1 coal seam and the mining stress in the No. 4 coal seam is 13. 20 m. ③ The degree of stress concentration and the range of the plastic zone in the surrounding rock of the No. 4 coal seam decreases as it gets further from the coal pillar, and when the distance to the residual coal pillar is 15 m, the degree of stress concentration and the range of the plastic zone tend to stabilize. The filed practice showed that, mining roadways on the No. 14103 working face shows that, with the mining roadways arranged 15 m away from the edge of the goaf in the No. 4-1 coal seam and a combined support scheme of “anchor net cable+W steel belt+reinforced ladder beam”, the surrounding rock deformation of the roadways were controlled, ensuring the safe production of the No. 4 coal seam.

The Taigemiao Mining Area of Xinjie is difficult to develop safely and efficiently because of overlapping coal and natural gas mining rights. Aiming at the problem that coal-gas overlap is difficult to develop two kinds of resources safely and efficiently, a systematic study is carried out by means of investigation, statistical induction and theoretical analysis. We study the disaster factors, disaster processes and potential risk types of natural gas Wells during coal and natural gas cross-exploitation in overlapping areas. Based on the constraint conditions of natural gas production layer, overburden aquifer, coal seam disclosure, exploitation disturbance and plugging standard, we put forward the three-dimensional whole-well optimization plugging technology. Then, we conducted field tests on abandoned natural gas Wells, and the main parameters met the requirements. Finally, we further put forward the technical system of over abandoned well and disaster prevention in the mining face. This paper has a certain practical reference significance for the safe development of coal and natural gas in the overlapping area of mineral rights in this region.

The underflow concentration of the thickener in the coal preparation plant affects the operational safety of the thickener and the efficiency of the filtration system. Predicting the underflow concentration and using it for the intelligent control of the coal slime water system is of great significance. Based on the basic laws of solid settling and mass balance, a prediction algorithm for the underflow concentration and the settling velocity of coal slurry particles with different particle sizes in the thickener was constructed using online instantaneous and historical data including the flow rate and concentration of the thickener feed, the dosage of coagulant, and the flow rate and concentration of the thickener underflow, as well as offline data including coal slurry particle size distribution and optimal dosage. The algorithm was applied in a coal preparation plant to verify its accuracy. The results showed that without adding flocculant, particles <0.045 mm in size in the thickener would circulate in the system with the overflow water, while coal slurry with a particle size range of 0.045-0.125 mm would remain in the thickener as suspended solids, and particles larger than 0.125 mm would settle to the bottom; After adding medication, coal slurry of various particle sizes settles in the form of flocs. The underflow concentration prediction algorithm based on settling rate and mass balance can accurately predict the bottom flow concentration, providing a basis for decision-making in coal slurry intelligent systems.

Based on the characteristics of coal mine domestic sewage with large changes in water quality and quantity, low organic matter content and high cost of sludge disposal far away from the city, the application effect of modified AAO process ( AAO + suspended packing media process ) in coal domestic sewage treatment was analyzed. The effluent quality of the modified AAO processes is good and stable, and the amount of sludge is small. Therefore, the two modified AAO processes ( AAO + suspended packing media process ) have become the main process for coal mine domestic sewage treatment.

It is crucial to control the stability of the surrounding rock in thick loose layer thin bedrock roadway roof cuttings, and the static fracture cutting technology helps to reduce the impact of the cuttings on the stability of bedrock. In this paper, taking the engineering background of 16061 working face roof-cutting along the hollow stay lane in Zhaogu No. 1 Coal Mine as an engineering background, numerical simulation, indoor test and engineering practice are comprehensively used to reveal the mechanism of static fracturing slitting in the roof of the roadway in the mining area with thick loose layer and thin bedrock, and optimize the related process. The results show that: with the increase of expansion pressure, crushing occurs in the range of 75mm of the hole wall by tensile and shear damage of compressive stress, and the range of 75~110mm of the hole wall by compressive stress is converted into tensile stress, which produces tensile cracks in the rock within the range, and eventually the crushed area and cracks penetrate to form the weak surface of the fissure. With the increase of hole spacing, the tensile stress between the holes shows a quadratic curve type distribution, and the connectivity of plastic zone decreases at the same time, and the optimal fracturing hole spacing is determined to be 300mm.On this basis, the filling method of liquid static pressure grouting using static fracturing agent and the fast sealing method of hole sealing device are proposed for downhole top cutting, and the optimal water/dose ratio considering the fluidity and expandability of slurry is determined to be 0.5, and the process flow of static fracturing top-cutting and cutting operation is constructed. The process flow is constructed. The field industrial test shows that the time required for single-hole operation is less than 5 min, and obvious cracks appear on the inner wall of the drill hole, and the length of fracturing slit can reach 90% of the effective depth of drilling charge, and the effect of the slit can meet the demand of top-cutting in the current back-mining roadway. The research results can provide theoretical basis and practical reference for the fracturing and slitting project in the mining area with thick loose layer and thin bedrock.

Aiming at gas control in strong outburst soft coal seam, there is a serious problems of hole block and methane accumulation and serious orifice and gas overflow frequently. In order to ensure the safety of regional gas management, through match the full spiral pneumatic directional drilling tool, research on technical parameters of pneumatic directional hole forming and coal cutting technology of soft coal seam with pressure relief, a set of pneumatic directional drilling supporting coal cutting pressure relief technology is formed to carry out advanced pressure relief, the field tests have been carried out in JIU Lishan Mine. Test shows that the use of pneumatic directional drilling technology in advance pressure relief drilling can effectively solve the problem of plugging and spraying holes in soft coal seams, no obvious orifice was found during the test. Through a variety of coal cutting technology combination application, the dry weight of coal per meter is more than 0.1t, effectively increase the pressure relief space and improved the gas extraction effect. In the first three months of the monitoring period, the net volume of gas extraction in a single hole exceeded 22,000 square meters, the theoretical gas pre-pumping rate of the control range is 37.97 , it provides a safety guarantee for the subsequent regional gas control.

Given the dearth of resulting verification ways for the effect of grouting treatment within the water injury space of thick loose layer, a joint uphole-downhole multi-indicator verification methodology is planned to verify the result of grouting treatment on the seam roof by scrutiny parameters like the core observation of grouting layer level, the water level of formation before and once grouting treatment, the output from downhole release borehole, water porosity of stratum, and flowing of slurry injection from downhole borehole. The results show that the grouting treatment has achieved the expected goal and also the operating face has safe recovery conditions. throughout the later workings recovery, no roof dripping development occurred within the well, which is in keeping with the verification conclusion, achieved safe mining at the operating face. The results of the study will give a reference for the verification of the result of suspension treatment within the roof space beneath similar conditions.

Aiming at the risk of water inflow in the evaluation of hydrogeological conditions for coal gasification projects, combining with the hydrogeological conditions of a research area in northern Xinjiang, we analyzed the water source of the gasification cavity, studied the safety thickness standard of the aquiclude in the roof and floor of the gasification coal seam, and discussed the combination characteristics of the floor aquifer/ aquiclude and the gasification safety. The results show that the hydrogeological conditions in the study area are generally favorable for underground coal gasification, and the internal water inflow is 0. 27 m³ / t, which poses a very limited threat to the safety production of the gasification cavity. In the case of no fresh water recharge in the surface or underground outcrop area, the external water in the roof and floor aquifer of the gasification coal seam is main influence factor. Combining with the previous research results and the conditions in this study area, it is relatively safe when the roof aquiclude thickness is over 36 m, and it is basically safe when the thickness is over 42 m; It is relatively safe when the floor aquiclude thickness is over 20 m, and it is basically safe when the thickness is over 30 m. It is concluded that the coal measure aquifer will not pose a threat to the safety of the gasification cavity in underground gasification at most of the well points in the study area. When the thickness of the floor aquiclude combination is less than 30 m and the thickness of the floor aquifer is greater than 30 m, the water inflow of the gasification cavity may exceed the safe value.

Aiming at the problem of severe mine pressure in retaining roadway during simultaneous mining of close-distance coal seams, taking the 9102 and 10102 working faces of Jiaokou Coal Mine in Shanxi Province as the engineering background, the mechanical model of simultaneous mining of close-distance coal seams and the mechanical model of roof cutting and retaining roadway are established. Through theoretical analysis, numerical simulation, industrial test and other methods, the coupling weakening law of mining distance and roof cutting height on the stress of surrounding rock of retaining roadway is clarified. The reasonable mining staggered distance and roof cutting parameters are determined : the mining staggered distance is 30m, the roof cutting height is 6m ( the layer spacing is 10m ) and 11m ( the layer spacing is 15m ). The field test results show that when the interlayer spacing is 15 m, the roof deformation of the top cutting side of the 10102 transportation gateway is 71.61 mm, which is reduced by 38.2 %, and the hydraulic support pressure at the end of the working face is 25.47 MPa, which is reduced by 25.8 %, indicating that the optimization effect is good. The research results can provide theoretical basis and engineering reference for the roof cutting and roadway retaining technology under similar conditions.

Aiming at the problems of insufficient real-time performance and low positioning accuracy in the leakage diagnosis of heating pipe network in Inner Mongolia Shuangxin Mining Co., Ltd., this paper proposes a comprehensive grading heating pipe network leakage diagnosis method combining CUSUM algorithm and BP neural network algorithm. This method constructs a real-time leakage diagnosis and positioning system by combining CUSUM algorithm and BP neural network. Firstly, based on the real-time monitoring data of the secondary network 's make-up water flow, the CUSUM algorithm is combined with the simulation model of the heating pipe network to realize the first-level diagnosis of leakage occurrence and leakage. Subsequently, combined with the pipeline network operation data and simulation model data, the BP neural network algorithm is used to perform secondary diagnosis of the leakage location. The application effect of the system shows that the leakage / non-leakage accuracy and leakage location detection accuracy of the No.3 building heat exchange station, the auxiliary wellhead heat exchange station and the boiler room heat exchange station of Shuangxin Mining Co., Ltd.all reach 100 %. The system response delay time is less than 2 minutes, and the average response time is less than 1 minute. The research results provide a new solution for the intelligent leakage diagnosis of industrial heating pipe network, which has important practical application value and has positive reference significance for ensuring heating safety and reducing energy consumption.

Due to the complex underground environment of coal mines, water influx drives the movement of silt and sand, which can cause irregular fluctuations in the water level of the water tank, interfere with water level measurement, and increase the error of detection results. To this end, a mine water level detection method based on multi-sensor fusion and DeepLabv3+algorithm is proposed. Firstly, select ultrasonic liquid level sensors, input type liquid level sensors, temperature sensors, and CCD visual sensors to obtain data on the changes in the water level height of the mine water tank; Then, frequency domain feature correction is applied to the sensing signal, and the mixed Kalman particle filter algorithm is used to fuse the collected multi-sensor data; Finally, using the DeepLabv3+algorithm to process the fused data, a water level detection model based on DeepLabv3+is constructed to achieve water level detection. Through experiments, it is known that whether in the stage of rising or falling water level, the proposed method's detection results for water level height are very close to the actual results, with an error of no more than 0.2 m. The detection range can reach over 9.7 m3, and the detection accuracy can be maintained at 78~89 %. Under the condition of gradually increasing interference values, the error for water level detection in the water tank is 0.21~0.35 m, with high detection accuracy and good application effect.

In order to improve the recovery rate of coal resources and dispose of a large amount of coal-based solid waste, based on the integration of excavation and filling of inter-surface coal pillars, considering the influence of curing age on the strength and bearing capacity of the filling body, the evolution law of the strength of the filling body with age under different cement contents was studied through laboratory tests. It was found that the cement content was positively correlated with the strength of the filling body, and the strength of the filling body increased exponentially with the age. According to the difference of the strength of the filling body, the bearing state of the filling body to the roof was divided into three stages : short-term bearing, medium-term bearing and long-term bearing. By establishing the collaborative bearing model of backfill-roof with different strength at different ages, the roof deflection equations of each region in the process of ' excavation-filling ' are given. A numerical simulation model of backfill-roof collaborative bearing was established by FLAC3 D. The effects of cement content, excavation-filling distance and excavation-filling speed on the stress of backfill and roof subsidence were analyzed, and the evolution law of backfill-roof collaborative bearing under different excavation distances in the process of ' excavation-filling ' was explored.The results show that in the process of ' excavation-filling ' of inter-surface coal pillars, the higher the cement content and the smaller the excavation-filling spacing, the faster the strength formation time of the filling body, the greater the vertical stress of the filling body and the less the roof subsidence. The faster the excavation and filling speed is, the shorter the curing age of the filling body in the filling area is, the lower the strength is, the worse the bearing effect is, and the plastic zone of the filling body and the roadway roof is seriously damaged. With the increase of tunneling distance, the maximum subsidence velocity of roof decreases gradually, and the cooperative bearing structure of backfill-roof tends to be stable gradually.

As coal mines and underground engineering projects extend into deep and geologically complex regions, the application of Tunnel Boring Machine (TBM) in rapid roadway excavation has become increasingly widespread. However, highly variable and complex geological conditions often lead to severe equipment load fluctuations, accelerated cutter wear, and reduced excavation efficiency, which significantly hinder the stable and efficient operation of TBM. Therefore, it is essential to establish an accurate boreability prediction and rock mass classification method to provide a scientific basis for TBM parameter optimization and construction planning. This study proposes an intelligent prediction model—GWO-VMD-SSA-LSTM—by integrating Grey Wolf Optimization (GWO), Variational Mode Decomposition (VMD), Sparrow Search Algorithm (SSA), and Long Short-Term Memory (LSTM) networks. The model enables accurate prediction of TBM boreability and quantitative classification of surrounding rock. Results show that the model achieves excellent performance on the test set, with a MAE of 0.4324, RMSE of 0.6005, MAPE of 1.5486%, and R2 of 0.9527, significantly outperforming other comparison models in terms of accuracy and generalization ability. Furthermore, a rock mass classification system based on the Field Penetration Index (FPI) was developed, enabling rapid determination of boreability levels. Engineering validation demonstrates that the method effectively reflects excavation difficulty across various lithologies and provides intelligent decision-making support for TBM tunneling in complex geological conditions, offering significant practical value for advancing intelligent excavation in coal mine roadways.

In response to the intermittent separation type water and sand inrush problem caused by the mining of weakly cemented strata in the western Jurassic coalfield, taking the water and sand inrush disaster in the New Shanghai No.1 coal mine as an example, a water and sand inrush start-up test device was used to design 25 sets of water and sand inrush start-up tests under static and dynamic water pressure conditions. Using the single factor analysis method, the influence of clay layer thickness, water head height, crack width, crack angle, and particle size on the initiation of water and sand inrush was studied. The range analysis was used to quantify the effect of each main controlling factor on the initiation of water and sand inrush.On this basis, the influence of different gas injection and pressure compensation methods on the initiation of water and sand inrush was analyzed through membership degree comparison and water and sand inrush disaster time, revealing the mechanism of water and sand inrush disaster in the process of separation and water collection. The results showed that the initial water head height and crack width are positively correlated with the initiation of water sand bursts, while the thickness of clay layers is negatively correlated with the initiation of water sand bursts. The proportion of the influence of clay layer thickness, water head height, crack width, crack angle, and particle size on the initiation of water sand bursts is 39.4%, 27.3%, 12.1%, 12.1%, and 9.1%, respectively. The order of the impact of static and dynamic water pressure on water sand burst is continuous gas injection pressure>intermittent gas injection pressure>static water pressure. The research results can provide reference and guidance for the prevention and control of water and sand inrush disasters in weakly cemented roof.

Aiming at the problems of complex deformation and failure of surface in fully mechanized top coal caving mining of shallow buried extra-thick coal seam, and lack of measured research on surface subsidence law in Xialiyuan Mining area, the research methods that combined field measurements and theoretical analysis were used in 40201 working face, then the surface movement destruction forms and regional spatio-temporal characteristics were analyzed, and the surface subsidence rule under was summarized, moreover the prediction method of surface movement and deformation in shallow buried extra-thick coal seam mining was optimized. The results showed that the surface movement deformation was severe in the mining of shallow-buried extra-thick coal seam, and the surface subsidence basin was formed rapidly. And the subsidence basin could be divided into the dense area of step cracks in the middle of goaf, the tensile fracture area on both sides of the boundary, and the outer continuous deformation area, and along the advancing direction of the working face, the step fracture boundary would lag behind the working face by about 28m, while the pull fracture boundary would precede the working face by 5.7~18.4m. And the deformation was severe, the duration was short in the active period of surface movement, and the subsidence accounted for 89%~94% of the total subsidence. The zonal probability integral method could be used to predict the surface movement and deformation of shallow buried extra-thick coal seam, and this method had good applicability.

Based on three kinds of fly ash content (15%, 20%, 25%) and three kinds of cement content (6%, 8%, 10%), cubic specimens with side lengths of 40, 50, 70.7 and 100 mm were prepared to investigate the effect of size on the damage characteristics and energy evolution of the filled bodies. The results show that when the size of the filling body is certain, the strength of the filling body with 20% fly ash content and 10% cement content is the highest, and the compressive strength of the filling body shows the law of “increasing first and then decreasing” with the increase of the size, and it reaches the peak value of 19.85MPa when the size is 70.7mm. The modulus of elasticity of the filling body was positively correlated with the size, and with the increase of the specimen size, the damage form changed from tensile damage to X-type shear damage. The energy characteristics of filling bodies of different sizes under uniaxial compression are similar, the elastic energy dominates before reaching the maximum stress, and the dissipated energy rises after reaching the maximum stress, and with the increase of size, the energy storage limit and bearing capacity of the filling body show the trend of increasing and then decreasing, and the curve of elastic-energy consumption ratio changes from stable to rising, which can be used as a basis for the destruction of the filling body.

During coal mining operations, coal pillars are subjected to cyclic loading-unloading, leading to instability and potential water inrush disasters. This process is accompanied by plastic flow, during which the permeability of coal exhibits significant dependence on loading paths. In this study, cyclic loading-unloading permeability tests were conducted on shear-yielded coal samples from Changcheng No.1 Mine under varying confining pressures. The evolution of permeability under full stress-strain and plastic flow conditions was systematically investigated, and the underlying mechanisms were revealed through microstructural analysis. The results indicate that, 1）Permeability evolves in three distinct phases: elastic phase (Permeability decreases due to the closure of primary fractures), elastoplastic phase (Permeability gradually recovers, reaching its maximum at peak stress), and residual flow phase (Permeability declines as axial strain continues to increase); 2) Permeability evolution under cyclic loading exhibits two-phase characteristics: During unloading, permeability increases with decreasing axial strain. During reloading, permeability initially increases and then decreases. At the same axial strain, permeability during unloading is lower than during loading, forming an elliptical hysteresis loop that indicates irreversible damage accumulation; 3) Permeability shows a decreasing trend with increasing confining pressure; 4) Based on 2D SEM images, an optimized simulated annealing algorithm was used to reconstruct 3D pore-fracture models of the samples before and after testing. Characterization of the 3D pore-fracture structure parameters provided microstructural insights into the permeability changes under different confining pressures.

In order to improve the degree of CBM exploration and development in the northeast of Qinshui Basin, the coal reservoir thickness and buried depth of 31 mines in the region were collected, and the a and b values, reservoir pressure, gas content, permeability, gas saturation, critical desorption pressure and porosity of coal samples were measured by isothermal adsorption test, pressure recovery curve method, calculation deduction and porosity test. Based on the structural and hydrogeological background, this paper systematically analyzes the CBM geological characteristics and the law of accumulation and accumulation in the study area, and establishes a multi-level CBM development selection evaluation index system from the perspective of CBM enrichment factors, and carries out application in the No.15 coal seam of Taiyuan Formation in the study area, and divides the favorable CBM development blocks. The results show that: No. 15 coal seam in this area has higher metamorphic conditions, with sandy mudstone and mudstone as the main surface and roof. The thickness of coal seam is between 4.30 and 8.25 m, and the average burial depth is 389 m, which belongs to medium-shallow burial depth. The average gas content is 9.37 m3/t, the adsorption capacity is strong, the average Langley pressure is 36.65 m3/t, the average permeability and porosity are poor, the average permeability is 0.029 mD, the average porosity is 5%; Coal seam gas enrichment is mainly controlled by the depth of coal seam. Compared with shallow coal seam, the thickness and porosity of deep coal reservoir have little change, and the coal reservoir pressure, gas content and Langley pressure are higher, so they have better coal seam gas storage capacity. The CBM development potential in the study area is divided into 4 categories, among which the deep buried coal seams in Pingxi and Yangquan areas are the dominant exploration and development blocks. Low Langley pressure, permeability, gas saturation and critical desorption pressure are the main disadvantages of future CBM development. The research has a certain guiding significance to the exploration and development practice of coalbed methane in the northeast of Qinshui Basin.

The coal gasification fine slag has high porosity and large specific surface area, which can be used as an adsorption material, and the coal gasification wastewater with a high content of phenol and ammonia nitrogen can be reused in the mineral flotation process. In order to realize the resource utilization of coal gasification waste, flotation experiments were carried out in the clean water system and the simulated wastewater system to explore the effect of phenol and ammonia nitrogen on the flotation of coal gasification fine slag. The results showed that the flotation effect was optimal under the experimental conditions when the pulp concentration was 40g/L, the collector diesel content was 18kg/t，and the foaming agent MIBC was 12kg/t in the conventional clean water flotation system，and the flotation concentrate yield was 41.94%, the concentrate ash was 30.65%, and the flotation perfection index was 53.50%. In the simulated wastewater system, phenol and ammonia nitrogen were beneficial to promote the flotation of coal gasification fine slag, which was mainly because phenol could improve the collision and adhesion probability between coal gasification fine slag particles and collectors, and ammonia nitrogen was conducive to the selective capture of residual carbon components, thereby comprehensively improved the flotation effect. The flotation effect of coal gasification fine slag in the mixed solution with phenol concentration of 4000mg/L and ammonia nitrogen concentration of 5000mg/L was the best. Compared with conventional flotation, the flotation concentrate yield increased to 49.72%, the concentrate ash decreased to 28.74%, and the flotation perfection index increased by 13.91% to 67.41%.

Abstract: Low temperature retorting tar yield is a key index to evaluate oil-rich coal. Accurate and efficient prediction of tar yield is of great significance for the evaluation and clean, efficient development and utilization of oil-rich coal resources.. In order to improve the accuracy and efficiency of prediction of tar yield, in view of the multivariate nonlinear complex relationship between coal, rock and coal quality indexes, the characteristic parameters affecting tar yield are divided into three combinations of strong, strong + medium, strong + medium + weak by screening 129 groups of borehole data with complete coal, rock and coal quality indexes in Lianghuai coalfield through correlation analysis. The correlation analysis was conducted to determine the hydrogen-to-carbon ratio, hydrogen content, vitrinite reflectance, volatile matter, and tar yield were most strongly correlated, while the oxides of calcium, magnesium, iron, silicon, aluminum, and fixed carbon were moderately correlated with tar yield. Other indicators had weaker correlations through Pearson correlation coefficient method. The characteristic parameters affect tar yield were divided into three parameter combinations: strong, strong+medium, and strong+medium+weak, and a combination optimization algorithm prediction model based on PSO-GA-BP. Different parameter combinations were trained using machine learning, and the actual application effects of different prediction models were compared and analyzed.The results show that the best fitness of the sample data of the strong + medium feature parameter combination is the largest in the training process, and the absolute coefficient R2, root mean square error RMSE and mean absolute error MAE are better than other feature parameter combinations with better performance and training status. The PSO-GA-BP combined optimization algorithm has the smallest error, and has more advantages in improving the prediction accuracy and data fitting effect of tar yield compared with BP, GA-BP and PSO-BP algorithm. The PSO-GA-BP is applied to the prediction of tar yield of extended sample collected in roadway, and the prediction model shows good generalization ability combined algorithm model established by drilling. The establishment of a complete and comprehensive database of oil-rich coal rock and coal quality is the basis and prerequisite for further improving the model learning ability and forecasting effect through advanced intelligent algorithms.

In response to the prediction dilemma caused by insufficient data for newly built distributed photovoltaic power stations, this paper proposes a hybrid prediction method based on polynomial fitting-LSTM. This method first preprocesses the weather and power data, and selects characteristic indicators with high correlation through Pearson correlation coefficient analysis. In the prediction stage, the method adopts a multi-level strategy: first, analyze the recent power data and use polynomial fitting to establish a normalized trend model; secondly, build an LSTM peak prediction model to obtain the power peak of the target day, and multiply the two to obtain a preliminary prediction result; finally, correct the preliminary prediction value by building an LSTM residual prediction model to obtain the final power prediction curve. Taking a distributed photovoltaic power station in actual operation as an example for verification, the results show that the hybrid prediction method can effectively improve the prediction accuracy of newly built photovoltaic power stations, and provide a practical solution to the problem of photovoltaic power generation power prediction under the condition of limited data. This method combines traditional polynomial fitting technology with deep learning models, and further optimizes the prediction results by introducing a residual correction mechanism. Key Words：Photovoltaic power generation; Power prediction; Polynomial fitting; Long short-term memory network

The low willingness of coal mine employees to work underground has become a significant cause of structural underemployment in coal mines at the micro level. Utilizing the DEMATEL-ISM method and incorporating Maslow's hierarchy of needs theory, this study analyzes the factors affecting coal mine employees' willingness to work underground from five dimensions of needs: physiological, safety, social belonging, esteem, and self-actualization. By constructing an influence matrix through expert scoring, the study examines the impact degree, influenced degree, centrality, and causality of each factor, deriving the hierarchical structure of influencing factors. The results indicate that employees' willingness to work underground is influenced by twelve factors, which can be categorized into a three-tier hierarchical model. Limited career prospects emerge as the core influencing factor, while low or unfair underground treatment is not an absolute determinant. Coal mine enterprises need to gain a deeper understanding of employee needs, focusing more on the underground work experience, job satisfaction, and career development of their employees. This focus is crucial for improving the willingness of employees to work underground from a micro perspective.

In pursuit of the “Dual Carbon” objectives, facilitating the coal mining industry's efficient execution of carbon reduction initiatives is paramount. This article explores the equilibrium and stable strategies among various stakeholders by establishing an evolutionary game model involving government departments, coal mining enterprises, recycling enterprises, and coal mine workers. The impact of varying parameters on the strategic choices of each stakeholder is then simulated using Matlab software. Research indicates that the ideal equilibrium point for this four-party evolutionary game system is (0,1,1,1). Increasing the bonuses provided by government departments to coal mining enterprises and intensifying government supervision both serve to promote carbon reduction behaviors within the coal mining industry. Enhancing the rewards for employees who actively participate in carbon reduction initiatives can effectively boost their motivation. However, increasing the entrusted funds to coal mining enterprises does not encourage them to adopt proactive carbon reduction strategies. In conclusion, recommendations are proposed from the perspectives of government departments, coal mining enterprises, and recycling and reuse enterprises.

Digital twin technology serves as the cornerstone for real-time monitoring and bidirectional mapping in intelligent coal mining. Current digital twin creation methods predominantly rely on commercial software such as Unity3D (U3D) and Unreal Engine (UE), which are entirely dependent on foreign technologies. These approaches face bottlenecks in handling complex coal mining scenarios, including excessively large model sizes and poor real-time interactivity on web platforms. To address these challenges, this paper proposes a lightweight method for constructing a WebGL-based digital twin model of three key machines in intelligent mining faces. By integrating glTF format conversion and a progressive mesh merging algorithm, the method preserves critical geometric features (achieving a compression rate of up to 95.3%) while employing octree-based ray picking, device-adaptive rendering strategies, and hardware-performance matching to create lightweight geometric models for complex equipment. Experimental results demonstrate that this approach significantly reduces model initialization and rendering time, enhances rendering frame rates, and exhibits excellent compatibility with mainstream browsers. This work provides a lightweight, compatible, and self-controllable technical pathway for building intelligent digital twins in coal mining, ensuring both efficiency and intellectual property autonomy.