Abstract:Repairing borehole by self-propelled water jet drill bits is an efficient repair technique for downhole failed boreholes,and im-proving the borehole repair efficiency of self-propelled drill bits is crucial for enhancing the efficiency of coal mine safety production.The borehole repair efficiency of self-propelled drill bits is influenced by both drilling efficiency and coal particles transport efficiency in the borehole,which are mutually constrained.To achieve the optimal borehole repair efficiency,that is to maximize drilling efficiency while ensuring basic coal particles transport ability,CFD-DEM coupling was used to study the borehole repair process under different paramet-ers.The transport patterns of coal particles under different annular ratios,jet pressures,coal particles sizes,and borehole angles were de-termined.The author established a theoretical model for the critical mass flow rate of coal debris transport under different annular ratios.The selection range of annular ratios under different jet pressures,coal particles sizes,and borehole angles was studied.The experiments on the transport patterns of coal particles in the annular space were carried out,and the experimental results are consistent with the numer-ical simulation results.The following main conclusions were obtained:the annular ratio,jet pressure,coal particles size,and borehole angle all affect the transport of coal particles in the annular space,with the annular ratio being the primary influencing factor.The flow ve-locity in the annular flow field and the pressure drop of the liquid-solid two-phase flow are the key parameters that determine the coal particles transport ability in the annular space.As the annular ratio increases,the flow velocity in the flow field first increases and then de-creases,while the pressure drop of the liquid-solid two-phase flow decreases,resulting in the coal particles transport ability first improving and then declining.The transport capacity of coal particles is positively correlated with jet pressure,and negatively correlated with coal particles size and downward slant borehole angle.The optimal borehole repair efficiency parameters under different conditions were de-termined as follows:when the jet pressure is 0-10 MPa,an annular ratio of 0.53 is selected;when the jet pressure is 10-15 MPa,an annu-lar ratio of 0.44 is selected;when the jet pressure is greater than 15 MPa,an annular ratio of 0.39-0.44 is selected.When the coal particles size is 0.5-3.0 mm,an annular ratio of 0.53-0.60 is selected;when the borehole angle is-60°-0°,an annular ratio of 0.44 is selected.The optimal borehole repair efficiency parameters provide a basis for the selection of drill bits and pipe diameter parameters under different conditions during downhole borehole repair.

Abstract:The activation of reverse faults can significantly increase the risk of rock burst,as the fault's dip angle and stiffness control the accumulation and release of energy that triggers such events.To assess the impact of varying fault dip angles and stiffness on rock burst risk in coal mines,this study uses the F16 reverse fault in Gengcun Coal Mine,located in the Yima mining area,as a case study.Through a combination of theoretical analysis,numerical simulations,and field monitoring,the study investigates how changes in fault dip angle and stiffness influence the evolution of the stress field in the working face and the activation-induced instability of the fault.The results show that when the dip angle of the reverse fault exceeds 60°,significant concentrations of shear and vertical stresses occur,increasing the slip risk coefficient(β)and making the fault more susceptible to activation.Additionally,when the fault stiffness ratio is below 1/5,the peak abutment stress ahead of the working face rises,and horizontal displacement grows nonlinearly,creating a"stress barrier"effect.This in-tensifies energy accumulation in the coal seam and elevates the risk of rock burst.Using the F16 reverse fault as an example,it is shown that the 13200 working face at Gengcun Coal Mine lies within the fault's influenced zone.Monitoring data from the F16 fault reveal that mining activities at the 13200 working face triggered the activation of the fault,leading to the concentrated release of accumulated energy in the coal-rock mass and the occurrence of five high-energy microseismic events.This study offers valuable theoretical insights and practical guidelines for predicting and preventing fault-induced rock burst.

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: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: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:Aiming at the unfavorable environmental factors such as low brightness of artificial light source and dense distribution of coal gangue in coal mine underground,which lead to the problems of feature extraction difficulty and low localization accuracy of existing coal gangue detection algorithms,a real-time segmentation method of coal gangue based on adaptive low illumination image enhancement is proposed,which consists of CG-IENet(Coal Gangue Image Enhancement Network)and CG-TSNet(Coal Gangue Target Segmentation Network).The CG-IENet is based on the CycleGAN network model framework,which optimizes the design of the encoder,feature extrac-tion network and decoder in the generator network through the attention mechanism,and adopts PatchGAN as the discriminator network to achieve adaptive picture quality enhancement of low illumination coal gangue images,so as to better retain the surface texture information of the coal gangue.The CG-TSNet is based on the DeepLabV3+network model framework,which introduces the lightweight backbone network MobileNetV2 and the neck network SPS-ASPP module in the encoder,and combines the feature fusion module,the attention mechanism,and the dynamic sampling in the decoder,which improves the model segmentation accuracy and reduces the model complex-ity effectively at the same time,it enables faster processing speeds and lower energy consumption for easy deployment of edge-based com-puting devices.The experimental results show that CG-IENet improves 47.86%,61.20%,14.30%,31.77%and 23.68%on average in the peak signal-to-noise ratio,structural similarity index,information fidelity criterion,entropy and gray mean,respectively,compared with the other low illumination image enhancement models,and the mean chromaticity error is as low as 1.18.The three-dimensional gray scale distribution graph and gray scale histogram are used to visually compare and analyze the various models,which finally shows that CG-IENet has the best enhancement effect,which can better improve the brightness of the image to avoid color distortion while retaining the detailed information of the image.CG-TSNet has the highest mean intersection over union,mean pixel accuracy,pixel accuracy,and F1-Score(F1)metrics,91.76%,95.84%,96.85%,and 95.04%,respectively,and the best overall detection performance when compared to the other four semantic segmentation models,such as HRNet,UNet,and PSPNet,on the basis of the guaranteed model memory of 4.567 MB.The model can be adapted to the complex working conditions in underground coal mines,thus realizing accurate and efficient sorting of coal gangue.

Abstract:To address the high deployment cost and limited disaster resilience of downhole wireless positioning systems,an active down-hole target positioning method is proposed based on an improved ConvNeXt network and panoramic vision technology.The method con-sists of two stages:Offline training and online positioning.In the offline training stage,the downhole environment is divided into regions,and panoramic image data are collected to construct a multi-scale training dataset through data augmentation.Based on the improved Con-vNeXt network,an area positioning model and a fine positioning model are trained separately,where the area model provides coarse-grained position estimation and the fine model achieves precise localization.During the online positioning stage,a panoramic camera mounted on a mobile device continuously captures environmental images.After image stitching and enhancement preprocessing,the area positioning model first determines the target's regional range,and the corresponding fine positioning model is then invoked for real-time localization.Experimental results demonstrate that the combination of 0.5 m area positioning and 0.1 m fine positioning achieves an accur-acy of 94%.With the integration of the CoordAttention module,the accuracy further increases to 95%,representing a 14.67%improve-ment over conventional single-step methods.Compared with MobileNetV3(91%)and ResNet(92.33%),the improved ConvNeXt net-work exhibits superior performance.Furthermore,the proposed method maintains strong robustness against typical downhole disturbances such as illumination variation,motion blur,personnel movement,and dust interference,achieving 95.33%accuracy on the 616 roadway dataset collected from the Yangchangwan Coal Mine of the National Energy Group Ningxia Coal Industry Company Limited.The study provides a low-cost,robust,and easily deployable positioning solution for intelligent downhole mobile platforms such as autonomous vehicles and robots.

Abstract:As the coal industry accelerates its transition towards intelligent transformation,video image-based object detection and hazard identification technologies,with advantages of non-contact,visualization,and high real-time performance,are increasingly becoming a key support for enhancing mine safety and production efficiency.This study survey focuses on the innovation and application requirements of video image intelligent analysis technologies in the context of the coal industry's intelligent transformation.It conducts a systematic study on the current state of intelligent construction in complex mining environments,potential safety hazards,existing advanced target detec-tion and hazard identification methods,as well as technical challenges,supported by practical application cases.The study first examines the current state of construction of mine video surveillance systems,the diversity and complexity of safety hazards,and elucidates the ne-cessity and application value of machine vision technology in underground environments;Subsequently,it compares and analyzes the dif-ferences and application value between traditional image processing methods and deep learning-based object detection and recognition technologies in terms of detection accuracy,robustness,and computational efficiency.The study focuses on exploring the adaptability and limitations of mainstream detection models in severe underground mine scenarios such as low illumination,high dust and fog,noise inter-ference,and occlusion.On this basis,combined with the construction and application cases of existing mine video datasets,the role of datasets in model training,performance evaluation,and generalization capability enhancement is analyzed,and the deployment perform-ance of these methods in typical tasks such as coal flow transportation monitoring,violation behavior recognition,operation equipment hazard detection and safety warning in fully mechanized mining faces is further discussed.Finally,the survey summarizes the challenges that current technologies still face,including limited adaptability to complex environments,data imbalance and annotation difficulties,con-straints of real-time computing resources,and instability in long-term behavior tracking.Future research directions are outlined,including generalization learning,multi-modal complementary fusion,large-scale semantic modeling,edge-cloud collaborative computing,and data privacy and security protection.Through systematic review and in-depth analysis,this study provides structured theoretical references and technical route support for the continuous innovation and practical implementation of mine video image intelligent analysis technology,thereby enhancing coal mine safety monitoring,hazard warning,and emergency response systems toward higher levels of intelligence and intrinsic safety.