Abstract:Addressing the issues of low efficiency and inconsistent quality in traditional manual operations for shotcrete support in coal mine roadway,a composite motion mode featuring uniform lateral displacement superimposed with periodic rotation was proposed through composite trajectory planning,structural optimization,and simulation verification.Combined with vertical spray gun posture control(spraying distance of 0.8～1.2 m),the material rebound rate was reduced to within±6 mm.A multi-segment layered spraying strategy was adopted to achieve full coverage spraying on the side walls and vault.The robotic arm utilizes a multi-degree-of-freedom hydraulic drive system and a retractable protective device.Key components were verified through finite element analysis:the maximum von Mises stress of the spray gun's circle-drawing mechanism was 4.46％(37.22 MPa)of the material's yield strength,with a safety factor of 22.4,the maximum stress of the telescopic arm was 78.81 MPa,and the deformation was 1.104 nun,meeting the ISO 13849 standard.Based on experimental analysis of the working space,the robotic arm has a maximum working radius of 3 m,with the positioning error of the telescopic arm stabilized at±6 mm,exhibiting good dynamic characteristics.This effectively addresses issues such as poor adaptability to small tunnels and high rebound rates caused by sudden trajectory changes.

Abstract:In order to avoid the disadvantages of a single positioning method in the environment of coal mine underground tunnels,achieve the complementary advantages of ultra-wideband(UWB)and inertial navigation system(INS),and improve the accuracy of underground navigation positioning,a fusion positioning method based on improved Bayesian estimation was proposed when dealing with inconsistent observation data.By introducing inconsistency factors to adjust the variance in the likelihood function,the uncertainty of the data was more accurately reflected.Comparative experiments were designed in two environments,line of sight(LOS)and non-line of sight(NLOS),through simulation experiments to evaluate the performance parameters of the improved method in different environments.The results showed that the UWB positioning error remained within 0.5 m in line of sight environment,demonstrating good accuracy and stability.The INS error continued to increase,with a maximum error of 2.9 m.In non-line of sight environment,the UWB maximum error reached 2.3 m,while the INS error did not show significant changes.After fusing two positioning methods using Bayesian estimation,the maximum error in non-line of sight environments was reduced to 0.9 m,and different weight coefficients also had a certain impact on the error.The minimum errors were achieved for fUWB=0.8 and fINS=0.2,effectively reducing the impact of NLOS error on the positioning results and significantly improving the robustness and reliability of the positioning system.Compared to single UWB or INS positioning methods,the proposed fusion positioning method has a positive effect on improving positioning accuracy and suppressing path offset.

Abstract:Utilizing decoupling historical data to directly identify decoupling trends relies on data quality,and the identification efficiency is relatively low in datasets with a high degree of redundancy.To enhance the automated identification effect of coal unloading car decoupling trends,an automated identification method based on the Grey Wolf Optimization Algorithm for coal unloading car decoupling trends was proposed.The SVM algorithm was employed to classify coal unloading car decoupling trend information based on the difference in decoupling spacing,removing redundant data.The weight and classification basis values were calculated,and preliminary decoupling anomaly identification was completed through similarity sorting.The binary initialization of feature vectors was introduced using the Particle Swarm Optimization Algorithm,and a fitness function was constructed to obtain the optimal fitness value and feature components.Combining the Grey Wolf Algorithm forms the Grey Wolf Optimization Algorithm to dynamically adjust particle positions and optimize feature extraction.Based on the feature results,a recognition framework was set up to determine the probability of decoupling actions and threat levels,and calculate abnormal values for automated identification of decoupling trends.Experimental results showed that the proposed method had a high accuracy rate for car decoupling trend recognition,with a root mean square error of 0.18 and a lower mean error than comparative methods,and the highest recognition efficiency.

Abstract:Addressing the issues of heavy weight,high cost,and inconvenience for underground transportation and daily movement of mobile explosion-proof equipment,this project aims to establish a simulation model suitable for the optimal design of explosion-proof power box enclosures by studying the explosion-proof factors of coal mine-used explosion-proof power box enclosures,combining optimization theory from mathematics,establishing objective functions,determining optimization methods,and setting boundary constraints.By examining the material characteristics and mechanical properties of non-metallic materials,new materials suitable for the lightweight design of explosion-proof power box enclosures were identified.Through finite element analysis,the impact of structural types on the lightweight design of explosion-proof power box enclosures was studied[1].A lightweight design method and verification scheme for explosion-proof power box enclosures based on finite element analysis,selection of new materials,and appropriate structural types were formulated,providing a theoretical basis for future lightweight design of explosion-proof power box enclosures[2].

Abstract:Addressing the issues of large directional impact,poor control accuracy,and susceptibility to jamming in traditional spool valves within the hydraulic system of coal winning machines under complex working conditions,a systematic comparative study was conducted on the internal flow field characteristics of spool valves based on their actual working conditions.This study employed a combination of computational fluid dynamics(CFD)simulation and experimental verification.The valve cores with three different throttle groove structures were compared,namely conical,U-shaped,and triangular.The research results indicated that the triangular groove valve core could effectively enhance the accuracy of flow control,providing valuable insights for the subsequent optimization design and series development of hydraulic spool valves for coal winning machines.

Abstract:Addressing the issue of the inapplicability of socket-and-spigot concrete pipes in the construction of new coal roadway crossings using the hole-in-place spiral jacking method in coal mine shafts,a new pipe joint structure tailored for spiral transportation was designed,satisfying three core requirements.Firstly,providing effective thrust transmission for the tunneling machine.Secondly,achieving synchronous and reliable support underground.Thirdly,eliminating the risk of spiral friction sparks through wear-resistant coatings on the inner wall,while optimizing the connection method to enhance construction efficiency.The design incorporates a rapid end flange connection,optimizes the structure of the connection part,and adds grouting holes to minimize the interference of bench coal accumulation on propulsion.Based on ANSYS finite element analysis software and combined with the spiral jacking construction process,the mechanical properties of the pipe joint under different working conditions were simulated,and the optimal structural solution was determined through parametric analysis.The designed new pipe joint structure meets the expected goals in terms of thrust transmission,support stability,and wear resistance and explosion prevention.The flange connection and grouting hole design significantly reduce the propulsion resistance caused by coal accumulation.The finite element analysis results showed that the structure had high safety and adaptability under complex loads,while also being economical.The proposed pipe joint structure effectively addresses the limitations of traditional pipes in the spiral jacking process.Through mechanical optimization and process adaptation,it significantly improves tunneling efficiency and provides reliable technical support for efficient and safe construction in coal mine shafts.

Abstract:In order to grasp the real-time physical health status of underground personnel and the safety status of the surrounding environment,a portable monitoring device for physiological and environmental parameters of personnel entering the mine was designed and developed,using STM32F103C8T6 as the main controller,HDXZ-30102 as the heart rate and blood oxygen monitoring module,MQ-2 as the gas monitoring module,and NTC thermistor as the body temperature monitoring module,along with a buzzer module.It achieves real-time monitoring of heart rate,blood oxygen,body temperature,and combustible gases(environmental parameters).An upper computer system was developed based on LabVIEW,and data was transmitted to the upper computer through ZigBee wireless communication technology,enabling analysis,display,alarm,and storage.Testing of the functions of each module showed that this device was economical,portable,safe,and reliable,providing theoretical and technical basis for the innovative application of multi-source information fusion technology for underground personnel and environment in the field of coal mine safety.

Abstract:To enhance the intelligence level of manual coal caving,a caving control method based on image segmentation was proposed.By analyzing the difference between coal blocks and gangue under different illuminations,the illumination value with the maximum difference was selected for image acquisition.Combined with the actual underground production conditions,a dust removal algorithm based on dark channel was proposed.A semantic segmentation model with dual task heads for gangue and foreground was designed to classify pixels in the image into foreground and gangue.After obtaining the classification results,the mixed gangue rate was calculated by calculating the proportion of the gangue region in the foreground region,and a closing threshold was set to achieve intelligent control of the coal caving process.The trained segmentation model was deployed on the 81202 working face,and the segmentation accuracy of the model was verified to meet the actual production requirements through testing the segmentation results.With the mixed gangue rate closing threshold set at 20％,the ash analyzer was used to detect the coal quality of the 8 cuts after deploying the model.The results showed that the mixed gangue rate was 17.6％,proving that the proposed control method could meet the production control accuracy requirements.

Abstract:With the continuous improvement of coal mine safety production requirements,mine-used flameproof power equipment,as a key component of the underground electrical system in coal mines,has its shell design and pressure resistance performance directly related to the safe and stable operation of the equipment.The study aims to explore the design principles and pressure resistance performance of the shell of mine-used flameproof power equipment.By combining theoretical analysis,simulation verification of the strength of three commonly used reinforcement ribs,and experimental verification,an in-depth study was conducted on the pressure resistance performance of the power equipment shell.A design method for the power equipment shell that combines thin plate theory with finite element analysis was proposed.This method can effectively predict and optimize the pressure resistance performance of the shell.The pressure resistance and sealing performance of the box shell were verified through a 1.5 MPa water pressure test,and no plastic deformation was observed after withstanding high pressure for 1 minute.The research results have important theoretical and practical value for improving the safety and reliability of mine-used flameproof power equipment.

Abstract:Addressing the issues of low reliability in the current grease injection lubrication method for coal miners,high labor intensity in manual grease injection,and potential safety hazards,research has been conducted on drive control technology for centralized grease injection lubrication systems,branch grease injection quantity distribution and precise control technology,design and development of the structure of centralized grease injection lubrication systems,and grease injection control systems.An automatic centralized grease injection lubrication system for coal miners has been developed,implementing a dual control strategy of automatic grease injection via remote control and system-timed grease injection.The grease injection time and cycle of the electronic control system can be configured parameterized,allowing users to customize the corresponding parameters according to actual working conditions and production needs.The results showed that the automatic grease injection electronic control system improved the lubrication effect of the lubricated components of coal miners,reduced the labor intensity and safety risks for maintenance personnel,and enhanced maintenance efficiency.

Abstract:As the development of mineral resources extends deeper,traditional rock tunnel driving methods face challenges in terms of efficiency,safety,and cost.The TBM(full-face hard rock tunnel boring machine),as an efficient and safe mechanized driving equipment,demonstrates great potential in the construction of rock tunnels in deep mines.In response to the complex mining and geological conditions in deep mines,research on TBM construction technology has been conducted,including large-piece simulation transportation technology,component"four-standard"lowering technology,small chamber assembly technology,pipe jacking launching technology,driving technology,and complete machine withdrawal technology.The aim is to improve the applicability and efficiency of TBM in the construction of rock tunnels in deep mines,providing reference experience for similar projects.

Abstract:In response to the problems of large errors and poor real-time performance in the straightness monitoring of scraper conveyors in coal mine underground working faces,a scraper conveyor straightening system was developed based on fiber bragg grating(FBG)curvature sensors through theoretical analysis,model construction,and scheme design.Firstly,a scraper conveyor attitude model was constructed.Secondly,real-time body attitude data was collected using FBG curvature sensors,and combined with LSTM neural network to predict straightening parameters,ultimately achieving a dynamic straightening process of"perception correction straightening prediction correction".Engineering practice has shown that after 3 straightening treatments,the initial straightness deviation of the scraper conveyor decreased from 322 mm to 152 mm,a decrease of 53％,reaching the allowable range.This study not only solves the technical problem of real-time monitoring and straightening of the straightness of scraper conveyors,but also provides effective support for the automation and intelligent development of coal mine fully mechanized mining faces,and has significant promotion and application value.

Abstract:There are safety hazards such as gas accumulation,fire spread,and trapped personnel in blind tunnels underground in coal mines.Currently,the management of blind tunnels mainly relies on regular inspections by staff.Therefore,there are many problems such as inconvenient,untimely,and inaccurate parameter monitoring,inability to stop illegal intrusion behavior in a timely manner,and occupation of tile inspection personnel.To solve the above problems and achieve unmanned inspection of blind tunnels in coal mines,a safety monitoring system for blind tunnels in coal mines has been designed.The system has remote monitoring and control functions,and can monitor real-time parameters such as temperature,water level,pressure difference,CO concentration,CO2 concentration,CH4 concentration,etc.of the blind tunnel environment.Through the upper computer configuration system,the blind tunnel environment parameter limit alarm was realized and the control facilities were activated to eliminate hidden dangers.By remotely monitoring the flow of people around the blind alley through a video system,timely alarms can be issued for underground personnel who violate regulations and invade the blind alley.Through experimental verification,the system is able to complete preset functions,which helps to improve the intelligent level of blind roadway management in coal mines.

Abstract:Addressing the frequent malfunctions encountered in the operation of travel boxes of coal winning machine,such as severe wear of drive and travel wheels and poor lubrication of open transmission system bearings,we have conducted an in-depth exploration of maintenance-free technology for the transmission system,focusing on two aspects:the addition of an automatic gear oil dripping device and the structural optimization design of key components such as the travel box housing and gear assembly.The effectiveness of the maintenance-free technology has been verified through field use,and the improved design has significantly enhanced the reliability of the travel box during production.

Abstract:Aiming at the problem that the evolution law of hard roof breaking under different mining spaces is not clear,multiple mining faces in a mining area of 11 coal seam in a coal mine were taken as the engineering background,and uses the combination of microseismic monitoring and theoretical deduction to analyze the breaking characteristics of hard roof under different mining spaces.The evolution model of roof breaking was constructed,and the atypical breaking mechanism of hard roof under different mining spaces was obtained.The results showed that with the expansion of mining space,the strength of ground pressure in the mining space decreased during the first weighting period.At the same time,the breaking span of the high hard roof decreases and finally breaks synchronously with the lower basic roof,which is also the reason for the decrease of the strength of ground pressure,under the mechanical environment of four-side fixed support,especially when the inclined span is small,the ultimate bearing capacity of the roof is large and the breaking span is large.In the mechanical environment of three sides fixed and one side simply supported,the increase of the inclined span destroys the bearing capacity of the roof,which leads to the decrease of the strike breaking span of the high hard roof.The research results provide a theoretical basis for the safe and efficient mining of deep mines.

Abstract:Addressing the issues in the automotive rapid loading control system,such as limited precision in matching loading capacity with vehicle traction speed and inadequate continuous and stable control over loading capacity,a rapid loading process control system based on IMC-PID was designed.Firstly,the automotive rapid loading process and the principle of internal model control were analyzed.Then,an internal model control method was employed to establish a first-order time-delay system loading model for the automotive rapid loading process,and the PID control parameters were processed using first-order Pade approximation.Finally,simulation and experimental analysis were conducted.The analysis results indicated that the system could control the loading time to be completed within 35 seconds,enhancing the loading speed and continuous loading capability during the dynamic loading process.

Abstract:Aiming at the problem of insufficient automation in durability testing of existing filling pump testing platforms,a flow self balancing filling pump testing platform was designed.Based on the combination of centrifugal pump and sleeve plunger valve,PID control technology was used to dynamically adjust the valve core position and control the outlet flow rate of the centrifugal pump,achieving dynamic balance between the outlet and return flow rates of the filling pump.A testing method based on preliminary testing was proposed to determine the optimal opening of the sleeve plunger valve and use it as the initial parameter for formal testing,optimizing the flow self balancing control function.This study has certain guiding significance for the construction of the filling pump testing platform and the optimization of its durability test.

Abstract:Coal mine full-face tunneling boring machines play a pivotal role in underground coal mine construction.With technological advancements,intelligent upgrades have become a crucial direction for enhancing their efficiency and adaptability.This study focuses on the empowerment of full-face tunneling boring machines through DeepSeek,an advanced artificial intelligence technology.By integrating DeepSeek's powerful natural language processing,machine learning,and data analysis capabilities,we delve into its application modes and effectiveness in various aspects of full-face tunneling boring machines,such as intelligent decision-making,fault diagnosis,and construction optimization.Research indicated that DeepSeek could perform real-time analysis of massive data during the tunneling process,accurately predicting equipment failure risks and providing early warnings and solutions for maintenance.In terms of construction decision-making,it can quickly generate efficient and reasonable tunneling parameters and construction plans based on geological conditions,engineering requirements,and other information,significantly improving construction efficiency and quality while reducing construction costs.Furthermore,DeepSeek aids in building an intelligent knowledge graph for full-face tunneling boring machines,enabling rapid retrieval and application of knowledge and advancing the intelligentization process of underground engineering construction.This study provides new technical paths and theoretical support for the intelligent development of full-face tunneling boring machines,promising widespread promotion and application in practical engineering and bringing profound changes to the field of underground engineering.

Abstract:The mining TBM has a complex structure,high integration,and limited internal space.Based on practical engineering experience in domestic coal mine TBM construction,field research across multiple mining areas has revealed that the fluid pipelines of domestic coal mine double-shield TBM were mostly arranged in the form of hoses.This has always been a pain point in the development of the TBM,affecting aspects such as overall pipeline design,installation,maintenance,and aesthetics.Taking the modular double-shield TBM as the research object,according to the relevant parameter requirements of the fluid system and combined with the actual on-site working conditions,the steel pipes were selected and designed.Based on the principle of component design,the pipeline layout was carried out in the model using Solid Edge,incorporating some hoses.The relevant mechanical properties of the pipelines were analyzed,and a combined installation process of soft and hard pipes was proposed.This significantly improves the assembly efficiency,maintenance,service life,and aesthetics of the fluid pipelines in mining TBM.

Abstract:Underground hazardous information encompasses multi-dimensional aspects such as gas concentration,geological activity,and personnel status,making it challenging to comprehensively perceive such information in coal mine underground.To address this information perception dilemma,a multi-sensor approach for hazardous information perception in coal mine underground was proposed.By meticulously analyzing the operational links of the mine,constructing an initial hazard source database,and defining and adjusting the objective function to quantify risks,the most pressing major hazard sources in coal mine underground were ultimately identified.Through the integration of various hazardous information in coal mine underground using multi-sensor technology,a feature signal fusion and conversion method was employed to efficiently extract multi-dimensional data.By integrating multiple sensors,it is possible to simultaneously capture multi-dimensional information such as gas concentration,geological activity,and personnel status,compensating for the limitations of single sensors and providing a more comprehensive environmental perception.By calculating the weight vector and combining multi-sensor data fusion with L1 regularization,accurate calculation and optimization of the weights for hazardous information perception in coal mine underground were achieved,ultimately classifying risk levels based on the weight values.Experimental results showed that the sensitivity of hazardous information perception using the multi-sensor method consistently remained above 90％,with a false negative rate below 1％.Therefore,it is demonstrated that the multi-sensor method provides precise and comprehensive dynamic risk assessment technical support for mine safety prevention and control.