Abstract:Coal mine gas explosion accident will not only produce a huge shock wave,but also produce a large number of toxic and harm-ful gas CO,which seriously affects the mine safety production environment.In order to achieve the dual protection of explosion suppres-sion and gas ablation,CuO-CeO2 composite oxide was used as CO catalyst and CaO was used as CO2 adsorbent.The catalytic adsorption composite powder CuO-CeO2/CaO doped with CaO was prepared by the combination of solid phase impregnation and thermal dispersion.The effects of H2O and CaO doping amount on the catalytic adsorption performance were investigated by heating and isothermal gas reac-tion experiments.The physical and chemical structures of CuO-CeO2/CaO were characterized by X-ray diffractometer,X-ray photoelec-tron spectrometer,Raman spectrometer and scanning electron microscope.The explosion suppression and gas ablation properties of differ-ent powders were analyzed by 20 L spherical explosion tester and gas chromatograph.The results show that the doping of CaO reduces the negative effects of H2O and CO2 on CuO-CeO2/CaO,promotes the formation of surface oxygen vacancies and the interaction between Cu-Ce,and then improves the CO catalytic performance,so that it can completely oxidize CO at about 120℃.When the doping amount of CaO is 15%,its CO catalytic performance and CO2 adsorption are the highest.Compared with equal mass Al2O3 and CuO-CeO2 powders,CuO-CeO2/CaO composite powders have stronger explosion suppression and gas ablation ability.The specific performance is that after adding CuO-CeO2/CaO,the maximum explosion pressure,maximum pressure rise rate and deflagration index of gas explosion reach the lowest,which are 0.483 MPa,7.60 MPa/s and 2.1 MPa·m/s,respectively,and the elimination rates of CO and CO2 reach the highest,which are 89.1%and 95.3%,respectively.The study confirmed that the composite powder CuO-CeO2/CaO can eliminate CO and CO2 by its catalytic adsorption,and reduce the gas explosion pressure by interrupting the chain reaction,dilution asphyxiation and endo-thermic effect of adsorption products,which provides a new idea for reducing the risk of gas explosion.

Abstract:The water environment governance and restoration in closed coal-mine areas serves as a vital foundation for the sustainable de-velopment of the mining area's ecological environment.The key lies in the identification of characteristic pollutants within the groundwa-ter environment of the mining area.In the Junlian Mining Area on the southern margin of the Sichuan Basin,the Longtan Coal-measure is exploited.The overlying Triassic and underlying Permian strata are both distributed with relatively thick carbonate rocks.The discharge of pollutants in the water gushing from the Longtan Coal-measure strata of closed mines has exerted an impact on the karst groundwater en-vironment.A characteristic pollutant identification system for closed coal-mine areas is established.Through hydrochemical characterist-ic analysis methods,hydrogen-oxygen isotope methods,and principal component analysis methods,the source-indicating properties of pollution indicators in the water gushing from the Longtan Coal-measure strata are analyzed and quantified.The pollution attributes are quantified using the analytic hierarchy process,and the pollution degree is quantified by the sub-item pollution index method.The quanti-fication results are weighted and integrated by the subjective-objective comprehensive weighting method for comparative analysis,thereby enabling the identification of characteristic pollutants among the pollution indicators of the water gushing from closed mines.The results indicate that the pollution indicators in the water gushing from closed mines mainly originate from the water-rock interaction res-ulting from the weathering and dissolution of carbonate rocks,silicate rocks,and their ore-bearing components,as well as the residues of mining activities.In the study area,the pollution indicators iron and manganese possess attribute characteristics such as strong toxicity,non-degradability,and weak mobility.Their enrichment is likely to have an impact on the local water environment,while CODCr and sulfate with relatively high migration intensity are prone to polluting the regional water environment.Among the pollution indicators,iron,manganese,CODCr,and sulfate exhibit significant pollution degrees.Ultimately,iron,manganese,CODCr,and sulfate,which have a relat-ively large proportion of the comprehensive weight,are identified as the characteristic pollutants in the water gushing from closed mines in the study area.They require key monitoring and treatment.Meanwhile,by combining the identification results with the karst hydrogeolo-gical conditions,four genetic models of characteristic pollutants are proposed,namely the"coal gangue leaching and infiltration type",the"goaf water-rock interaction type",the"oxidation of mining facilities type",and the"composite type".This research plays a guiding role in the groundwater pollution treatment in the Junlian mining area on the southern margin of the Sichuan Basin and also provides ideas for the identification of characteristic pollutants in groundwater-polluted areas of similar mining regions.

Abstract:Specialized vehicles in mining often use heavy-duty solid rubber tires or polyurethane-filled tires,which exhibit significantly different tire-road contact mechanisms and operating environments compared to traditional road vehicles.Consequently,conventional tire models are difficult to apply directly,and the complex nonlinear characteristics of these vehicles complicate the acquisition of tire forces.To address this,a reduced-order cascading sliding mode observer for articulated special mining vehicles is proposed,enabling accurate es-timation of longitudinal and lateral tire forces with lower costs and reduced computational resource consumption.The eight-degree-of-free-dom dynamic model of the articulated vehicle is organized and decoupled to describe its dynamic characteristics.Based on this,a reduced-order cascade sliding mode observer is designed using a sliding mode control algorithm,incorporating a saturation function to reduce chat-tering.Typical operational scenarios for mining articulated transport vehicles are designed,including smooth step circular steering and al-ternating folding-and-unfolding for dynamic steering experiments.Validation experiments are conducted on an articulated vehicle test plat-form,where relevant operational data are collected to reconstruct and estimate tire forces in the Matlab/Simulink environment,followed by comparative analysis.The root mean square error(ERMS)and root mean square percentage error(ERMS,P)metrics are introduced to evaluate the precision of the tire force cascading observer.Results indicate that the sliding mode-based reduced-order cascading observer features fast convergence,with the ERMS,P of tire force estimates under both conditions remaining within 15%,while the ERMS,P of lateral force estim-ates for the rear vehicle not exceeding 8%,effectively capturing and reprodu cing the dynamic variations in tire forces.

Abstract:In coal mining activities,periodic mining disturbances cause fractured rock mass to bear cyclic loads.In this paper,cyclic load-ing and unloading tests of fractured sandstone under different loading and unloading amplitudes are carried out,and the mechanical charac-teristics,deformation and failure characteristics,acoustic emission response characteristics and damage evolution rules of fractured sand-stone under cyclic loading and unloading are analyzed.The mechanism of strengthening and deterioration of mechanical properties of frac-tured sandstone under cyclic load is revealed from the aspect of macro and micro structural changes.The results show that:① With the in-crease of cyclic loading and unloading amplitude,the peak load,elastic modulus and peak strain of fractured sandstone increase first and then decrease;After cyclic loading and unloading with the amplitude of 40%uniaxial compressive strength(σ0)and 60%σ0,the strength of sandstone is high,the time of deformation localized misplaced momentum surge is relatively late,and the final damage degree of sand-stone is severe.When the cyclic amplitude increases to 80%σ0,the localized misplaced momentum is relatively active during loading and unloading.② The sliding friction between particles leads to more acoustic emission events in the samples with 40%σ0 and 60%σ0 amp-litude.When the cyclic amplitude is increased to 80%σ0,the large scale nascent fissure occurs in the sample,and high amplitude acoustic emission events occur.The AF/RA value of the specimen indicates that the final failure type of the specimen after cyclic loading changes from tensile failure to shear failure with the increase of cyclic amplitude.③ Combined with the SEM analysis of the fracture section of fractured sandstone,a generalized model of strength strengthening and deterioration mechanism of fractured sandstone under cyclic load-ing and unloading is proposed:fracture effect of weak structure and compaction and consolidation effect under medium and low amplitude disturbance lead to compaction and severe failure of fractured sandstone;Under the disturbance of high amplitude,the shear crack grows when the sandstone is loaded and the tension crack develops when it is unloaded.④ There is a threshold value between 60%σ0 and 80%σ0,when the cyclic amplitude exceeds this threshold value,the damage variable of sandstone increases rapidly,and the dissipative energy and the proportion of dissipative energy increase gradually with the increase of the cyclic amplitude.The research results can provide data ref-erence for monitoring,warning and prevention of coal and rock dynamic disasters.

Abstract:The influence of mechanical properties of the sealing material and grouting parameters on the coupling deformation of coal-sealing material in the sealing section of gas extraction borehole is still unclear,which is the main factor restricting the improvement of sealing performance of deep coal seam borehole.Based on the structural characteristics of coal-sealing material in borehole sealing section,by introducing the coupling strength factor χ of coal-sealing material,the coupling mechanical model of coal-sealing material in borehole sealing section was established by using Mohr-Coulomb criterion.The analytical solutions of the stress,displacement,plastic zone radius and fracture zone radius of the sealing material and coal were derived,and the calculation method of the leakage area in borehole sealing section was obtained.Then,the influence of the factors such as the cohesion of the sealing material,the supporting force and borehole radi-us on the radius of plastic zone and fracture zone of coal-sealing material in the sealing section was studied.The effects of supporting force,cohesion of sealing material and coupling strength factor χ of coal-sealing material on the leakage area and sealing performance of borehole were discussed.The mechanism of coupling strength factor χ of coal-sealing material affecting borehole sealing performance was clarified.Then,the numerical simulation method was used to verify the total plastic zone area of the coal-sealing material in the sealing section.Finally,the field test and theoretical calculation results of the total leakage area were compared and analyzed through the gas ex-traction borehole sealing engineering practice.According to the variation law of gas extraction pure volume and gas extraction concentra-tion,the optimization scheme of borehole sealing parameters was proposed.The results showed that the cohesion of the sealing material,the supporting force and the borehole radius had little influence on the radius of the fracture zone of the sealing material,but had a great in-fluence on the radius of the fracture zone of the coal.The leakage area of the coal in the sealing section was significantly larger than that of the sealing material,and the factors such as the cohesion of the sealing material,the supporting force,the borehole radius and the coupling strength factor χ of the coal-sealing material had a greater influence on the leakage area of the coal.The leakage area of the coal was the main factor affecting the sealing performance of borehole.With the increase of the cohesion of the sealing material,the supporting force and the coupling strength factor χ of coal-sealing material,the leakage area of the coal decreased and the sealing performance of the bore-hole was improved.The coupling strength factor χ of coal-sealing material was related to the elastic modulus and Poisson's ratio of the sealing material,When En/μn＞Em/μm,the constraint stress factor λ of the sealing material to the coal was greater than 0,and the coal was compressed and deformed in the contact zone.At this time,χ>1,resulting in an increase in the ultimate compressive stress borne by the coal in the contact zone,which led to the decrease in the radius of the coal fracture zone and the leakage area,and the improvement of the sealing performance of the borehole.The larger the elastic modulus of the sealing material and the smaller the Poisson's ratio of the seal-ing material,the higher the sealing performance of the borehole.The simulation results of the total plastic zone area and the field test res-ults of the leakage area were basically consistent with the theoretical calculation results,and the theoretical model had high reliability.Based on the analysis of gas extraction pure volume and gas extraction concentration,it is proposed that when the borehole radius is 47 mm,the sealing material with coupling strength factor of 1.25 and cohesion of 1.5 MPa should be selected,and the grouting sealing pres-sure should not be less than 1 MPa.When the borehole radius is 56.5 mm and 66.5 mm,the sealing material with coupling strength factor of 1.46 and cohesion of 2.5 MPa should be selected,and the grouting sealing pressure should not be less than 1.5 MPa,which provides a strong guarantee for ensuring the sealing performance of the borehole.

Abstract:The length-to-diameter ratio has a significant impact on the mechanical properties and energy evolution of rock samples under impact loads,and the current constitutive model for rock damage that considers the coupling of length-to-diameter ratio and strain rate still needs to be improved.The split Hopkinson pressure bar(SHPB)system was used to conduct dynamic compression tests with four length-to-diameter ratios(0.4,0.6,0.8,1.0)and five levels of impact air pressure(0.2-0.6 MPa).The relationships between parameters such as strength,deformation,and energy with length-to-diameter ratio were analyzed.The theoretical slopes of reflection energy,transmission en-ergy,fragmentation energy,and incident energy have been derived.Based on the Weber distribution and D-P criterion,a damage con-stitutive model considering the coupling of length-to-diameter ratio and strain rate was established.The research results show that:① The dynamic stress-strain curve of sandy mudstone specimens under impact loads can be divided into the compaction stage,quasi-elastic stage,plastic stage,and failure stage.Within the range of impact air pressure involved in the experiment,the dynamic strength growth factor is positively correlated with the aspect ratio,while the softening coefficient is negatively correlated with the aspect ratio.② With the in-crease in length-to-diameter ratio,the energy density of specimen fragmentation decreases.As the length-to-diameter ratio of the sample increases from 0.4 to 1.0,the proportion of reflected energy increases from 19%to 31%,the proportion of transmitted energy decreases from 37%to 21%,and the proportion of dissipated energy ranges from 43%to 48%.By fitting the experimental data,it was found that there is a positive correlation between reflected energy,transmitted energy,dissipated energy,and incident energy.Based on the interface reflection coefficient λ of stress waves transmitted from the incident bar to the specimen,the theoretical slopes of reflected energy,trans-mitted energy,dissipated energy,and incident energy are are derived as λ10,(1-λ6)2 and 1-λ10-(1-λ6)2,respectively.③ Based on the dynamic strength obtained from experiments and its function with strain rate and length-to-diameter ratio,the initial constitutive model derived from the Weber distribution and D-P criterion was modified.The resulting damage constitutive model shows good consistency with the experimental curves and can be used to characterize the dynamic mechanical properties of sandy mudstone.

Abstract:Most Simultaneous Localization and Mapping(SLAM)systems that utilize tightly coupled laser-inertial odometry are often un-der-constrained in underground coal mines,leading to mapping failures and hindering the direct deployment of robots in operational front-lines.This paper analyzes the factors contributing to odometry drift in degraded environments,elucidating the mechanisms by which un-structured point clouds induce drift.We propose a targeted detection method for unstructured regions and a two-step denoising approach that includes filtering and interpolation to address dust and fog.An adaptive tightly coupled odometry system is developed,incorporating a factor that characterizes the state of unstructured areas.In a test environment reverse-engineered from the WHU-TLS Tunnel dataset,our system achieves an EAP-ERMS of approximately 0.40 m,an EAP-Mean of 0.37 m,a ERP-ERMS of 0.015 m,and an ERP-Mean of 0.011 m,outperforming other methods significantly.For engineering applications with Ultra-Wide Band devices,we use a nonlinear optimization method to maintain global odometry poses,constructing a factor graph with unstructured state constraints,UWB factors,and loop closure factors.By performing parallel global optimization on all factors,high-precision global localization and mapping are achieved.In a kilo-meter-scale simulated tunnel with UWB signals,the continuous mapping results show an EAP-ERMS of 1.48 m,an EAP-Mean of 1.32 m,an ERP-ERMS of 0.026 m,and an ERP-Mean of 0.013 m.In a 2 000 m-long,loop-free field test at Cuncaota Coal Mine,the EAP-ERMS was 15.64 m,the EAP-Mean was 14.53 m,the ERP-ERMS was 0.198 m,and the ERP-Mean was 0.037 m,demonstrating the system's potential for practic-al engineering applications.Our SLAM system,built with a 16-line LiDAR and a 6-axis IMU that meet explosion-proof standards,provides accurate mapping in degraded scenarios,significantly advancing the practical application of coal mine robots.

Abstract:Traditional steel arches have high weight,low bearing capacity,and high construction labor intensity,making it difficult to meet the safety and efficiency requirements of complex underground engineering.Taking the deep soft rock roadway as engineering back-ground,a new type of lightweight and high strength arch is developed by using high strength and high toughness steel.The bearing capa-city comparison tests of the new arch and the traditional U36 steel arch are carried out by using the full-scale arch test system,the deforma-tion failure mode and bearing characteristics of the arches are clarified.In terms of arch steel performance,compared with the traditional U36 steel arch,the yield strength of the steel used in the new arch is increased by 97%,and yield elongation is increased by 41.9%.In terms of arch bearing characteristic,when the overall weight of the new arch is reduced by 33.3%,its ultimate bearing capacity is increased by 20.1%,the stable slip resistance is increased by 111.5%.In terms of deformation and failure characteristics,compared with the tradition-al U36 arch,the average in-plane deformation under ultimate bearing state is reduced by 16.4%,and the maximum strain position of the new and U36 arches is at the arch roof or leg.This indicates that the new arch has the characteristics of lightweight,high strength,high res-istance,and stable slip.On this basis,the field application of the new arch is carried out,and the continuous monitoring results show that the average installation time of the new arch is reduced by 40.5%compared to the U36 steel arch.The maximum deformation of the new arch is 63 mm,the maximum stress is 101.3 MPa,and there is no obvious local buckling and out-of-plane instability,the safety reserve is high.The convergence deformation of surrounding rock is basically stable after 30 days,and the overall stress performance is roof,shoulder,waist.The new arch has good characteristics in bearing capacity and on-site construction efficiency,which provides a more lightweight and high-strength support form for the design of deep mine arch.

Abstract:Leakage airflow in goafs is a key factor inducing the oxidation,self-heating,and spontaneous combustion of residual coal.Vari-ations in leakage airflow velocity directly affect oxygen supply,heat accumulation,and gas migration,thereby determining the develop-ment intensity and spatial distribution of spontaneous combustion within the goaf.To reveal the influence of leakage airflow velocity on the oxidation behavior of residual coal,six groups of different leakage airflow velocities were tested using a programmed temperature-rise oxidation kinetics apparatus.The oxygen consumption rate,heat release intensity,and apparent activation energy of lignite from Puhe Coal Mine were systematically measured,and their variations with temperature were analyzed.Meanwhile,based on a 10 m×5 m×1 m phys-ical similarity goaf model,25 monitoring points were arranged under a constant intake airflow velocity of 0.52 m/s to analyze the spatial distribution characteristics of airflow velocity,temperature,and CO volume fraction inside the goaf and to investigate the influence of the non-uniform leakage airflow field on the coupled thermo-gas field.The results indicate that leakage airflow velocity has a significant im-pact on the oxygen consumption rate,heat release intensity,and apparent activation energy of coal.Comprehensive analysis of the six tested velocities shows that the oxidation and heat accumulation characteristics are most pronounced at 0.37 m/min;at 170℃,the oxygen consumption rate reaches 2.80×10-7 mol/(cm3·s),and the heat release intensity reaches 1.66×10-2 J/(cm3·s).Physical similarity ex-periments show that when the intake airway velocity is 0.52 m/s,the initial high-temperature point appears near the face-adjacent area close to the intake corner,then gradually extends toward the return airway and migrates deeper into the goaf,eventually forming a relat-ively stable high-temperature zone with a local airflow velocity of 0.33 m/min.The CO volume fraction field exhibits a high degree of cor-respondence with the temperature field;regions of high CO volume fraction are mainly distributed around the high-temperature point and its downwind side,showing a synergistic spatial feature of heat source-CO enrichment.These findings reveal the key influence of leakage airflow velocity on the oxidation of residual coal and the development of spontaneous combustion in goafs from both oxidation kinetics and thermo-gas field evolution perspectives.The results provide scientific support for predicting,early warning,and preventing goaf fires in mining faces.

Abstract:In underground mining operations,the generation of a substantial quantity of coal dust is a common occurrence.To mitigate the potential adverse effects of coal dust on the working environment,miners'ealth,and mechanical equipment,a simulation experimental platform for synergistic dust suppression using acoustic waves and water spray was utilized.The distribution characteristics of the acoustic field at different angles,the dust suppression efficiency for total dust and PM10 coal dust,and the variation of coal dust concentration with the acoustic wave angle were investigated using a multi-channel sound power testing system,a TSI8533 aerosol monitor,a coal mine dust sampler,and a scanning electron microscope.The influence of the acoustic wave propagation angle on the dust suppression effect was ex-plored.Additionally,the agglomeration characteristics of coal dust by spray droplets under different angles were comparatively analyzed.The results indicate that as the acoustic wave angle increases,the acoustic field distribution initially converges towards the upper part of the roadway.When acoustic wave angle is greater than or equal to 60°,the acoustic pressure level of the sound field begins to shift down-ward.The total dust is predominantly distributed in the middle area of the simulated roadway,while PM10 particles are primarily concen-trated in the upper-middle area of the simulated roadway.The results demonstrate that as the acoustic wave angle increases,the total dust concentration initially rises and then declines.The highest dust suppression efficiency is achieved when acoustic wave angle is 0°,with the efficiency increasing from 74.80%for water spray alone to 85.97%.For PM10,the concentration initially decreases and then increases with the increase in acoustic wave angle,with the lowest concentration occurring at an acoustic wave angle of 30°.The dust suppression effect of acoustic waves combined with water spray is optimal at this angle.Compared with water spray alone,the dust suppression efficiencies for PM1,PM2.5,PM4 and PM10 are increased by 31.10%,31.87%,33.49%and 30.90%,respectively.The results further show that as the acoustic wave angle increases,the total dust concentration initially increases and then decreases.The highest dust suppression efficiency is achieved when the acoustic wave angle is 0°,with the efficiency increasing from 74.80%for water spray alone to 85.97%.For PM10,the concentration initially decreases and then increases with the increase in the acoustic wave angle.The lowest concentration occurs at an acoustic wave angle of 30°.The agglomeration effect of PM10 is the best at this angle,with the most small particles attached and the ag-glomerate size reaching up to 36 μm.The study elucidates the mechanism by which the acoustic wave angle affects the dust suppression effect of water spray,thereby providing a theoretical basis for the field application of the combination of acoustic waves and water spray.

Abstract:Under the background of large consumption of coal resources,difficult disposal of oily sludge and serious environmental pollu-tion,in order to realize the resourceful and clean utilization of oily sludge,coal resources can be comprehensively utilized while disposing of oily sludge in a safe and efficient way by mixing and molding oily sludge and coal.Therefore,the coal fuel prepared by mixing oily sludge and coal was investigated,with relaxation density,relaxation ratio,crushing resistance,and water permeability resistance as the physical property indexes,to explore the optimal molding conditions of oily sludge briquette.The combustion characteristics of oily sludge briquettes under different addition ratios and heating rates were analyzed by thermogravimetric analysis,and the emission characteristics of pollutants in incineration flue gas were analyzed by flue gas analyzer.The results showed that when 20%-40%of oily sludge was added,the molding pressure was 20 MPa,and the moisture content of the mixed raw materials was 10%,the relaxation density of oily sludge bri-quette increased to more than 1 g/cm3,and the resistance to crushing was more than 90%.The physical properties of the coal became bet-ter,and the molding effect was better.The addition of oily sludge effectively improved the ignition performance and combustion character-istics of coal.When 40%of oily sludge was added,the calorific value of the produced coal fuel was 19.43 MJ/kg,and the stable combus-tion characteristic index was the largest,which was 3.10×10-5%/(min·℃2).In addition,increasing the reaction temperature can contrib-ute to the emission of NO and SO2.When the reaction temperature is 900℃and below,the emission of NO and SO2 can be better con-trolled without affecting the emission concentration of PAHs and heavy metals,which is lower than the limit value of pollutant emission standard.The mixing of oily sludge and coal is an effective way to realize energy saving and emission reduction.The addition of oily sludge reduces the ignition temperature of the coal,the burn-out temperature,and improves the combustion performance while effectively controlling the emission of pollutants.

Abstract:A study on the spatiotemporal evolution of the water conducted zone(WCZ)in thick loose layers under a unilateral mined-out area is conducted to overcome challenges such as the complexity of WCZ development and limitations of existing prediction methods.A prediction model for the WCZ development height is proposed,incorporating the pre-damage effect from the existing mined-out area.The research is based on the 866 working face of a coal mine in Huaibei Mining Area.A combined theoretical analysis and field monitoring ap-proach is adopted,and a"working face-coal pillar-adjacent mining area"three-in-one monitoring system for overburden deformation is es-tablished using distributed fiber-optic technology.A quantitative determination index for the WCZ development height is formulated based on the gradient distribution of overburden deformation,and a prediction model for the development height of the WCZ under unilateral mined-out area conditions is proposed.Results show that the spatial heterogeneity of the overburden is significant.The subsidence of the mining area exhibits a composite deformation mode dominated by residual subsidence and mining-induced subsidence.The working face area is mainly controlled by dynamic mining disturbance,while the coal pillar zone exhibits stress lag characteristics.The development height of the WCZ is determined by analyzing the inflection point in the cumulative absolute deformation contribution rate curve obtained from distributed fiber optic monitoring,along with the deformation characteristics at various depths.The maximum height is identified as 77 m.After mining stabilizes,the absolute deformation of the rock layers in the WCZ accounts for 87%of the total deformation.A double-zone deformation mode,characterized by upper compression and lower tension,is formed at a depth of-280 m in the existing mining area,causing detachment of the underlying rock layers.A prediction method for the WCZ height that considers the pre-damage effect of the uni-lateral mined-out area is proposed based on the key stratum theory and slab theory.The overburden is divided into upper and lower rock layers using the key stratum theory,and a failure criterion model is established based on slab theory.The predicted development height of the WCZ for the 866 working face is 71 m,with a relative error of only 8.4%compared to the measured value.

Abstract:To address the technical challenge of manually adjusting dust control parameters in long-term the fully mechanized excavation working face,which leads to an inability to sustain optimal dust suppression effects,this paper adopts a research approach combining the-oretical analysis,laboratory experiments,and on-site mining tests.It investigates the monitoring methods for the optimal dust control para-meters—axial and radial airflow,as well as the distance between axial and radial air outlets and the coal wall—along with the intelligent regulation algorithms and mechanisms for axial and radial airflow control parameters.The study concludes with an intelligent regulation technology for axial and radial airflow that couples online monitoring of total dust control airflow and axial airflow with automatic adjust-ment of axial ventilation area.Additionally,it develops an intelligent regulation technology for the distance between axial and radial air outlets and the coal wall,which integrates laser sensor ranging with adaptive movement of pneumatic single-rail hoist sliding carts to ad-just the air outlet positions.These advancements solve the persistent challenge of ensuring optimal dust control parameters in the fully mechanized excavation working face.Laboratory and on-site mining tests demonstrate that the intelligent adjustable range for the ratio of axial to radial airflow in the fully mechanized excavation working face is 0.29-2.94,with an intelligent regulation error of-0.09-0.04 m for the distance between axial and radial air outlets and the coal wall.When the optimal dust control parameter ratio of axial to radial air-flow is 0.3,and the distances between axial and radial air outlets and the coal wall are 6 m and 16 m respectively,the dust suppression effi-ciency at the fully mechanized excavation operator's position and 10 m behind the machine consistently maintains 97.0%-97.5%and 96.4%-97.1%,achieving an average dust suppression efficiency of 97.2%and 96.8%in the working face.These results yield effective dust control outcomes,providing a new intelligent parameter regulation technology for managing occupational dust hazards in coal mining fully mechanized excavation working face.

Abstract:In the current energy landscape,coal serves as a pivotal supporting energy source in China's industrialization process,and the energy structure dominated by coal will remain stable for a long period.Therefore,ensuring coal mine safety production is of paramount importance,and the intelligent construction of coal mines has become the core pathway to achieve to achieve this goal and guarantee effi-cient and safe operations.In this process,video analysis and recognition technology for coal mine safety production plays an indispensable role,and its in-depth development is a key technical pillar for ensuring the high-quality development of the coal industry.However,the special underground environmental conditions pose severe challenges.Due to the uneven illumination from artificial light sources,images captured by video surveillance generally exhibit poor conditions such as low illumination,poor contrast,severe noise interference,and missing details.These issues seriously interfere with the precise execution of subsequent key tasks such as target detection and semantic segmentation,thus posing a huge threat to real-time monitoring and effective early warning of coal mine safety production,and becoming critical challenges to be urgently addressed in the intelligent construction of coal mines.In view of this,a comprehensive and in-depth re-view of image enhancement methods in low-light environments of mines is of extremely important strategic significance.This study first systematically combs traditional low-light image enhancement methods,including histogram equalization,gamma correction,wavelet transform,Retinex decomposition,and fusion-based methods.These methods are carefully classified according to their principles,imple-mentation processes,and application effects,while the advantages and limitations of each method are deeply analyzed,providing import-ant experience and theoretical basis for follow-up research.Furthermore,it focuses on deep learning-based low-light image enhancement methods for mines,which are accurately divided into supervised and unsupervised categories according to the learning paradigm.For typ-ical algorithms in each category,their innovations,advantages,and disadvantages are elaborated in detail,offering a comprehensive and in-depth technical analysis for field research.In addition,this study comprehensively summarizes common datasets and evaluation metrics for low-light image enhancement,clarifies the characteristics and application scopes of different datasets,summarizes the construction of mine low-light datasets,and conducts experimental comparative analyses of traditional methods and deep learning-based methods based on this.Finally,by closely integrating the urgent needs of coal mine intelligent development with industry trends,it analyzes the current dilemmas and challenges faced by low-light image enhancement in mines from multiple dimensions,and proposes reasonable prospects for future de-velopment directions.The goal is to provide comprehensive guidance for the continuous innovation and wide application of low-light im-age enhancement technology in coal mines,and help the coal industry achieve safe,efficient,and sustainable development in the intelli-gent era.

Abstract:Video surveillance is one of the important means of coal mine safety monitoring,and the poor quality of video surveillance im-ages affects the accuracy of the video surveillance system due to the influence of illumination,dust and water mist,so it is of great signific-ance to study the mine low-illumination image enhancement algorithm.To address the problems of texture feature loss and colour distor-tion during the enhancement of extremely dark low-illumination images in coal mines,an unsupervised mine low-illumination image en-hancement algorithm EMGAN based on the improved EnlightenGAN is proposed.Firstly,in the generator network,the original U-Net model is replaced by the ResU-Net model,and the residual linking mechanism is added to enhance the feature transmission ability,effect-ively alleviate the gradient disappearance problem in training,retain the detail information in the image,and introduce an efficient multi-scale attention module for cross-space learning in the down-sampling phase of the network to improve the feature extraction ability of the network in complex environments;secondly,construct a dual discriminator network based on the PatchGAN,which discriminates the global and local regions of the image respectively,and efficiently balances the overall image brightness and contrast;finally,the joint loss function is designed to combine the perceptual loss and colour consistency loss to avoid colour distortion.Based on the self-constructed coal mine underground dataset for validation,the mean,standard deviation,information entropy,average gradient,peak signal-to-noise ra-tio,and structural similarity of the improved algorithm are improved by an average of 6.84%,24.88%,7.54%,8.30%,27.40%,and 10.85%,respectively.The experimental results show that the algorithm improves the brightness and contrast of the extremely dark and low-illumination image of the mine while retaining the texture feature information of the image and avoiding the colour distortion phenomenon,which effectively improves the quality of the image and provides a more reliable basis for the subsequent video monitoring and analysis.

Abstract:The gas extraction of high extraction tunnel is an effective means to control the gas outflow from the high-gas comprehensive discharge working face,but with the increasing mining intensity of the working face after the intelligent transformation,the amount of gas outflow accumulating in the upper corner increases significantly,and it is difficult to solve the problem of gas accumulation in the upper corner effectively with the conventional high extraction lane.The article proposes the use of reverse hole connecting high pumping lane technology to manage the gas in the working face with high gas outflow.Based on the characteristics of the No.15 coal seam of Changshun Coal Industry in Yangquan Mining Area,a numerical model is established,and the pumping characteristics of the reverse hole connecting high pumping lane are studied and determined,which is compared with that of the conventional high pumping lane,and the leakage law of the mining air space and the gas transport law of the working face are analyzed,and the influence of the connecting drill hole on the man-agement of the gas is clarified.At the same time,a field test was carried out in 15101 general-purpose working face.The results of the study show that:by increasing the negative pressure of pumping,the conventional gas control technology for the high extraction tunnel can strengthen the effect of gas control,reduce the gas volume fraction in the upper corner from 4.68%to 0.94%,and form a"concave"shaped gas volume fraction zone inside the mining hollow area,but this technology cannot completely solve the problem of the upper corner;the use of the reversed borehole linking After adopting the gas control technology of the high extraction lane,the gas extraction effect is obvi-ously strengthened,the gas volume fraction in the upper corner is significantly reduced,the gas volume fraction rapid growth area in the working face is reduced from 164-200 m to 192-200 m,the gas volume fraction rise area in the return wind side of the extraction zone is increased from 0-100 m to 0-130 m,and the maximum value of the gas volume fraction in the upper corner is reduced from 0.980%to 0.441%;Reverse Hole Connection Reverse hole connection can realize full-cycle gas extraction on the return side of the working face,not only pre-extraction of local coal seam gas before mining,but also diversion of the return corner during mining,and short-term extraction of the empty area after mining.The results of field test show that after adopting the gas management technology of reversed-hole connecting high pumping lane,the gas volume fraction of the working face is reduced obviously and the effect is stable,and the average values of the daily maximum volume fraction of the methane sensor T0 in the upper corner and the methane sensor T2 in the return-air lane are reduced from 0.70%and 0.51%to 0.20%and 0.33%,respectively,with the reduction rate of 71.43%and 35.29%;and the pure volume of pumping in the high pumping lane increased from an average of 26.81 m3/min to 29.86 m3/min,an increase of 11.38%.

Abstract:In open-pit mining operations,safe mining is critical to ensuring the smooth progression of production processes.However,obstacle detection in open-pit mines confronts severe challenges arising from complex environments.Traditional visual algorithms fail to meet the demands of complex open-pit mining scenarios,as intricate road conditions,indistinct road status under low light,and frequent occurrences of severe weather severely disrupt detection accuracy.Additionally,cluttered mine backgrounds,characterized by intertwined mechanical equipment,accumulations,and undulating terrain,coupled with the presence of diverse obstacle types,highlight significant limitations of traditional algorithms.The adaptability and robustness of existing improved algorithms in open-pit mine environments also require further enhancement.To achieve accurate and efficient detection of open-pit mine obstacles,ensure mine transportation safety,and overcome the bottlenecks of traditional algorithms,a cross-modal detection model—Mamba-YOLO-World—was proposed based on the YOLO architecture.This model employs multi-modal information,integrating text and image data to enhance detection accuracy and obstacle detection performance under complex conditions.The MambaFusion-PAN architecture was introduced for in-depth analysis to optimize the fusion of multi-modal data,enabling precise extraction of key features from road obstacles.Leveraging a state space model to capture intrinsic inter-modal correlations,the model achieves comprehensive detection of complex open-pit mining environments.Further-more,PENet was integrated,which decomposes input images into sub-images of varying resolutions via Laplacian pyramids to capture global context,strengthens textures through edge branches,and significantly improves detection capabilities under dim lighting conditions.A combined text-image loss function was also introduced to boost the training accuracy of the model.A dataset was constructed by select-ing and organizing 6 000 images,with corresponding text information generated;these were integrated to form the foundational dataset.Techniques such as image enhancement,denoising,cropping,and scaling were applied to provide high-quality data support for the experi-ments.Comparative tests were conducted between the Mamba-YOLO-World model integrated with PENet and mainstream algorithms in-cluding YOLOv8x and YOLOv9e.The results demonstrated that the proposed model exhibited significant advantages in core metrics such as mAP@50,precision,and recall,with an mAP@50 of 64.8%.In-depth analysis revealed that PENet notably improved low-light detec-tion performance,while the combined loss function provided robust support for the training of multi-modal data.The results indicated that although the Mamba-YOLO-World model integrated with PENet exhibits slightly higher computational complexity,its accuracy advant-ages are evident.Compared with traditional algorithms,it enhances model adaptability and robustness through multi-modal data fusion,thus providing a cross-modal obstacle detection method for open-pit mining.

Abstract:The complex underground coal mine environment suffers from poor illumination,high humidity,and suspended dust-condi-tions that easily form water mist and glare.These factors lead to the loss of high-frequency information and blurring of edge details in cap-tured images,while also superimposing noise interference.To improve mine image quality and address the challenge of synergistically suppressing noise and restoring details in mine scene super-resolution reconstruction,a mine image super-resolution reconstruction meth-od based on multi-path adaptive information enhancement is proposed.Methodologically,a Residual Multi-path Feature Aggregation Block(RMFAB)is designed first,leveraging residual learning and a Multi-path Adaptive Convolution Network(MACN)to fully utilize features from different paths,significantly enhancing the modeling capability for both global and local high-frequency information.Second,a Multi-attention Fusion Module is introduced to focus on high-frequency information across channel and spatial dimensions,im-proving feature representation.Finally,a Large Kernel Perception Block(LKPA)is constructed,employing multi-scale convolution to ex-pand the receptive field and fuse hierarchical features,optimizing texture and structural details.Experimental results on the public CMUID mine dataset demonstrate that the proposed method outperforms existing state-of-the-art algorithms in both Peak Signal-to-Noise Ratio(PSNR)and Structural Similarity(SSIM).Particularly at a scaling factor of 4,the algorithm achieves PSNR improvements of 2.88,2.04,1.94,1.52,0.53,0.36 dB over Bicubic,CRAFT-SR,PAN,ESRGCNN,DiVANet,and SMAFNet,respectively.Corresponding SSIM im-provements are 4.32%,3.37%,3.20%,2.74%,3.19%,1.08%.The method achieves refined extraction and fusion of multi-level features in mine images,effectively suppressing noise interference while restoring complex texture features.This enhances the super-resolution recon-struction quality of mine images,thus contributing to intelligent perception in coal mine environments.

Abstract:Hydraulic fracturing is a widely used physical rock-breaking method to address the challenges in cutting hard rocks.However,conventional water-based fracturing typically generates fractures propagating perpendicular to the minimum principal stress direction,res-ulting in limited fractures quantity and simplistic morphology,which restricts rock-breaking efficiency and productivity in mining opera-tions.To enhance rock fragmentation effectiveness,this study proposes a novel gel fracturing technique.Based on the self-developed true triaxial hydraulic fracturing simulation experiment system of coal and rock mass,pure water fracturing,gel fracturing after pure water frac-turing and gel fracturing experiments with different mass fractions were carried out.An electronic pressure recorder was employed for real-time monitoring of specimen rupture pressures,enabling comparative analysis of pressure evolution patterns and corresponding fracturing behaviors.By comparing and analyzing the macroscopic fractures characteristics of the test block,the fractures propagation law of gel fracturing was explored,and the rock breaking mechanism of gel fracturing was revealed.The key findings demonstrate that:①Gel frac-turing significantly increases fractures density,enhancing total fractures length per unit area by 92.71%-216.67%and fractures density by 92.7%-216.97%,while creating more complex fractures networks;②Prolonged and substantial pressure fluctuations during gel fractur-ing represent mechanical responses to complex fractures formation;③Gel fracturing reduces rock fragment size while enlarging fractures apertures,generating significantly more branch fractures than water fracturing,with markedly superior rock-breaking performance;④Higher gel concentration correlates with increased branch fractures and more pronounced fracturing dynamics.These results confirm that gel fracturing fundamentally alters conventional fractures propagation patterns through temporary sealing of initial fractures by block-ing agents during fractures initiation and extension phases.This mechanism modifies stress distribution in weak zones to initiate new frac-tures,achieving substantially better rock fragmentation than water fracturing.The findings provide theoretical support for optimizing hy-draulic fracturing techniques in hard rock excavation.

Abstract:The complexity and variability of underground environments pose severe challenges to safe production,making video surveil-lance a key technological means to ensure operational safety.Visible light and thermal infrared images play important roles in under-ground monitoring due to their respective advantages.However,the inherent limitations of single-modal images fail to meet the require-ments for information completeness in intelligent underground monitoring.Therefore,fusing heterogeneous images to achieve comple-mentary advantages is an effective solution to the aforementioned problems.Aiming at the issues of poor lighting adaptability,local fea-ture loss,and artifact interference in traditional fusion algorithms in the special underground environment,a dual-encoder fusion algorithm for heterogeneous underground images based on low-light correction is proposed.First,to avoid the confusion caused by a single encoder when extracting features from heterogeneous images,leading to insufficient retention of original image information in the fused image,separate visible light and thermal infrared encoders based on convolutional neural networks and Transformer architectures are designed,re-spectively,to effectively extract the features of the original heterogeneous images.Then,to mitigate the local feature loss in fused images caused by uneven lighting in underground environments,a selective lighting feature enhancement module is designed to improve the visu-al quality of low-illumination areas.Next,a parallel global and local feature extraction module is designed to capture both macro semantic information and micro detail information of images,thereby enhancing the feature richness of the fused images.Finally,to alleviate the ar-tifact interference in fused images,a low-light correction loss function guided by lighting information is proposed to assist the decoder in dynamically adjusting fusion weights,thereby enhancing the fused image's ability to retain complementary information from heterogen-eous images.To verify the advantages of the proposed algorithm,it was compared with nine fusion detection algorithms using a self-built dataset.The experimental results show that the proposed fusion algorithm can effectively mitigate local information loss caused by uneven lighting,reduce artifact interference in the fused results,and enhance the information completeness of the fused images.Compared with the contrast algorithms,the proposed algorithm shows significant advantages in five core indicators:spatial frequency,average gradient,spectral correlation difference,visual information fidelity,and correlation coefficient.Moreover,the fused images are more consistent with human visual perception in terms of visual effects.