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Collect screen paperboard of mine power transformer and ordinary power transformer in practical lifetime cycle to make insulation test samples, and according to the standard of power, use test means such as viscosity tester, scanning electron microscopy to compare and analyze microstructures of insulation paper such as polymerization degree, surface morphology of mine power transformer and ordinary power transformer, as well as electrical properties such as partial discharge and electrical strength; at the same time, effect of microstructure changes on electrical performances during aging was discussed. The analysis results show that the insulation defects gradually form and expand in the insulation paper during the aging process; compared with the insulation paper of ordinary power transformers, the surface morphology changes of the insulation paper of mine power transformers are more obvious, and the formed defects are more significant.In the aging process, the polymerization degree of insulation paper of ordinary power transformer and mine power transformer presents a gradual decline trend, but the decline speed of polymerization degree of mine power transformer insulation paper is faster.The operating environment of mining area is the main reason that the aging of insulation paper of mine power transformer is more serious than that of ordinary power transformer.In the process of operation, the insulation paper of mine power transformer will produce more discharge quantity, more discharge times and wider discharge phase than ordinary power transformer.In the aging process, the electrical strength of insulation paper of both ordinary power transformer and mine power transformer decreases gradually, but the electrical strength of insulation paper of mine power transformer is lower than that of ordinary power transformer.The microstructural defects of insulation paper of mine power transformers are the direct causes of the more significant changes in their electrical properties.In the process of state monitoring and maintenance of power equipment, it is suggested that the insulation state monitoring of mine power transformers should be carried out strictly according to the power standards,electrical property parameters are more suitable for insulation status monitoring and fault diagnosis of mine power transformer.

Application principle of polarization spectrum method based on recovery voltage method was introduced which was used in state detection of transformer oil-paper insulation, and a viewpoint was pointed out that main time constant of polarization spectrum curve was an important factor for judging state of transformer oil-paper insulation. Influence of charging voltage, residual charge and temperature on measurement result of polarization spectrum curve was analyzed separately with conclusions that charging voltage only influenced the maximal value of recovery voltage but did not influence main time constant of polarization spectrum curve, and residual charge and temperature would influence the main time constant. Matters needed attention were proposed that transformer should be fully discharged firstly, charging voltage should be as high as possible in range of 0-2 000 V and environmental temperature should be stable during actual application of polarization spectrum method based on recovery voltage method in state detection of transformer oil-paper insulation.

An online intelligent examination system of coal mining enterprises was proposed based on analysis of actual examination requirements of enterprise employees. A Web examination system is built firstly according to professional characteristics of the employees, and the system is optimized functionality. Secondly, GAAA algorithm integrated with genetic algorithm and ant algorithm is improved. The improved GAAA algorithm firstly updates ant colony pheromone, then searches test database by a comprehensive search of genetic algorithm and parallel distribution of ant algorithm for optimizing group volume of the database. At last, the improved GAAA algorithm is applied in the system to achieve examination of employees at anytime they like and anywhere they are and auto-generating examination paper. The practical application shows that speed of auto-generating examination paper of the system is high, repetition rate is low, the algorithm is feasible, and the system can meet practical requirements of online examination effectively and improve online examination efficiency of coal mine enterprise.

The paper introduced structure and key technologies of mine-used intrinsically safe wireless through-the-earth communication system，and analyzed working principle of the system. The system uses low-frequency electromagnetic radiation technology, digital communication technology and intrinsically safe power supply technology, which has characteristics of smaller volume, lighter weight and easy operation. The test results of prototype show that the system has realized two-way through-the-earth communication for 50 m with communication rate of about 150 bit/s and bit error rate of no larger than 0.2 %, and has a certain practical value

In view of problem that 35 kV power system of a Coal Mine often happens over-voltage at thunderstorm day, the paper analyzed causes of over-voltage, indicated that over-voltage was induced by fraction frequency resonance and the fraction frequency resonance was induced by PT and capacitance to earth of overhead line. Through analyzing parameters of resonance over-voltage of the power system, it gave corresponding reform scheme, namely replacing PT with better excitation voltammetry characteristic, adding nonlinear harmonic eliminator at neural point of high-voltage side of PT and installing intelligent resonance eliminating device with multifunction. The actual application showed that 35 kV power system has not happened resonance over-voltage with reliable running after using the reform scheme.

In view of problem of difficult location of fault existed in real time fault detection methods of powerful conveyor belt, the paper proposed an identification algorithm of joints of powerful conveyor belt based on image processing technology which takes a joint as a reference point. Firstly, based on the characteristics of joint points, a joint point is represented by a value. According to the value, upper or lower joint point could be distinguished simply. Then according to the features of joints, matching style of the longest common subsequence algorithm was modified and applied to recognize joint. The practical application showed that the algorithm has high precision and fast speed, can efficiently recognize joints of powerful conveyor belt and satisfy demand of joint locating of fault detection of powerful conveyor belt.

For problems that underground broadcasting system with analog audio broadcasting mode has poor flexibility and small voice communication range, the paper proposed design scheme of a new kind of mine-used digital broadcasting system, introduced designs of overall structure of the system, audio terminal and gateway program. The system accesses the audio terminal in industrial Ethernet, realizes packet and designated broadcasting, which solves problems of underground unicast and multicast.

Aiming at the problem of high leakage rate and false alarm rate of traditional statistical methods for abnormal fluctuation in sensor monitoring data caused by dampers opening and closing, a SSA-LSTM wind speed abnormal fluctuation detection method based on the combination of Singular Spectrum Analysis (SSA) and Long and Short-Term Memory Neural Network (LSTM) was proposed by mining the data features in the time-series data in the wind speed sensors. Firstly, SSA was used to pre-process the wind speed sensor monitoring data, and the wind speed data was decomposed into trend component, periodic component and noise component. The data noise generated by turbulent pulsation was removed via reorganizing the trend component and noise component. The LSTM parameters was then optimized, and the optimized LSTM model was used to predict the pre-processed data and obtain the reconstructed wind speed. Finally, the anomaly fraction of the monitored wind speed and reconstructed wind speed was calculated by using the logarithmic probability density function. Anomaly detection for monitoring wind speed was performed by calculating the threshold set value of training set data samples. The experimental results shown that, the removing effect for the data noise generated by turbulence pulsation via SSA was better. Removing the noise component without affecting the data fluctuation was helpful in improving the wind speed reconstruction effect and the anomaly detection accuracy. LSTM can correctly reconstruct the small amplitude wave due to turbulence pulsation without anomalous fluctuation and fits well with the actual data. The reconstruction of abnormal fluctuation segment based on historical fluctuation trend when there was abnormal fluctuation can effectively improve the accuracy of anomaly detection. Through comparative analysis, the reconstruction effect of proposed method in this paper was better than ARIMA, BP and CNN models, with an anomaly detection accuracy of 99.2% and an F1-Score of 0.97, which verified the reliability of the proposed method. The method proposed in the paper has important application value in detecting the abnormal fluctuation of wind speed caused by the opening and closing of dampers.

Studying the interaction between coal slime and flotation agents will be the hot and difficult point of flotation process strengthening. In view of the strong hydrophilic chemical structure characteristics of the surface of difficult flotation coal, this paper introduces the bio-pharmaceutical induced fit effect into the study of the interaction of polar collectors in difficult flotation coal flotation. In this paper, 3D coal molecular structure was optimized and constructed according to the results of coal sample properties. Protomol technology was used to search and represent the active pockets of coal molecules, and the optimal conformation of molecular butt between polar collector and difficult floating coal was searched in the active pockets. According to the binding energy of the optimal conformation of the interaction between polar chemicals and coal molecules, the correspondence between the molecular docking results, induced fit effect and the flotation results was analyzed. The molecular docking results and the recovery rates of refractory coal combustible are both lauryl alcohol< lauraldehyde< methyl laurate, The recovery rate of flotation fuels is positively correlated with the absolute value of molecular docking binding energy and the molecular induced binding effect of coal, which revealed the guiding effect of molecular docking on flotation reagent screening. According to the molecular docking configuration, the differences in binding energy can be attributed to the differences of π-CH interaction and steric hindrance. Furthermore, the three-dimensional space of pharmaceutical molecules was fixed and the induced fit effect between three polar collectors and coal molecules was explored by molecular mechanics simulation. It was found that methyl laurate and the active region of coal molecules could generate greater interaction, and the active region of coal molecules had stronger induction effect and inclusion of methyl laurate, so it had better effect in the flotation process. The application of molecular docking and induced fit effect technology in the field of biomedicine to the field of flotation reagents can provide technical approaches and scientific guidance for the rapid screening of flotation collectors.

Coal has made important contributions to the industrialization process of human society, and has played a key supporting role in ensuring China’s energy security and stable economic development. Since the mid-19th century, the coal-based fuel of coal, kerosene, gas and coal electricity has gradually entered the era of large-scale use. However, the traditional use of coal produces high carbon emissions, which has become a major problem in energy transition. Facing the development of ecological civilization society, the clean and efficient use of coal is imminent, and the innovation of modern coal-based energy technology is imperative. This paper proposes the definition and connotation of modern coal-based energy technology system, which is defined as the production of low-carbon energy products such as coal-based gas, coal-based oil, coal-based hydrogen and coal-based electricity, and the in-situ absorption of carbon dioxide in mining areas to form a clean and low-carbon energy production system with carbon neutrality. Its technical connotation includes coal-based gas, coal-based oil, coal-based hydrogen, coal-based electricity and dynamic carbon neutrality in mining areas, with a total of 5 technical modules, 19 technical units and 61 key technologies. The modern coal-based energy technology system will play an important role of “one main body, three supports and one breakthrough” in the future new energy system. Coal-based electricity provides the main body of electricity system stability. Coal-based oil supports the China’s oil safety. Coal-based gas supports the China’s gas safety. Coal-based hydrogen plays a supporting role in the development of hydrogen energy in China. The major breakthrough is the dynamic carbon neutral technology of coal-based energy. The paper supposes that when the ratio of non-fossil energy and low-carbon coal-based energy is maintained in the range of 2.5−3.0, coal-based energy, oil and gas and wind, water, nuclear energy can be reasonably integrated to form a new quality energy system with strong complementarity, high reliability and low carbon emissions. Based on the major breakthrough and practical application of modern coal-based energy technology, it is predicted that China’s low-carbon coal-based energy production will reach 1.02 billion −1.46 billion tons of standard coal equivalent (tce) in 2060, equivalent to 18%−24% of the national energy demand, and carbon dioxide emissions will be controlled below 500 million tons. Compared with the current energy transformation planning path based on “de coal” planning, the share of coal in our energy system can increase from 10% to more than 20%, and carbon dioxide emissions will reduce by 50%. At that time, the modern coal-based energy system has great technological innovation significance for China’s energy security and carbon dioxide emission reduction, and helps China to become a country with independent energy supply.

During the coal mining process, the change in the floor stress state of coal seam will produce deformation and failure. The seam floor failure in different coal mining processes has a certain law. At present, the water disaster monitoring of coal seam floors based on the DC resistivity method mainly focuses on the resistivity response characteristics of floor deformation and damage. To investigate the temporal changes in the electrical properties of the coal seam floor during mining, this study employs the inter-hole DC perspective observation system and the time-lapse resistivity reflection coefficient method. Through numerical simulation and field tests, the study uncovers the temporal variation law of the resistivity of coal seam floor induced by mining activities. First, this paper compares the results of individual inversion and time-lapse resistivity change rates for a typical geoelectric model to validate the reliability of the inter-hole DC perspective time-lapse method. Next, considering the mining-induced damage to the coal seam floor, this paper analyzes the electrical response patterns and charac-teristics of the rise of confined water and the damage zone in the floor during the mining process. It also discusses the feasibility of using a time-lapse resistivity reflection coefficient to assess the depth of coal seam floor damage, offering a theoretical basis for field construction. Finally, , the on-site monitoring tests reveal the electrical change characteristics of coal seam floor during the coal mining process. The time-lapse resistivity reflection coefficient R is utilized to determine the damage depth of the rock layer of the working face floor, which is found to be 15 m. The study results demonstrate that the time-lapse characteristics of the resistivity of coal seam floor mining damage obtained by the inter-hole DC perspective method can mitigate the influence of formation factors and random noise in the monitoring data to a certain extent. Additionally, the time-lapse resistivity reflection coefficient can be utilized to determine the depth of coal seam floor failure. This method transforms the detection target from the single study of geological anomalies to the full life cycle dynamic monitoring of the floor damage of the working face in the process of coal mining and then realizes the detailed depiction of structural damage to the working surface floor.

Based on the green development trend and requirements of China’s coal industry, this paper analyzed the factors that coal mines consider in choosing filling mining methods and the constraints that affect the promotion of filling mining technology. According to the geographical distribution characteristics of different mining areas and the differences in filling demands, four types of priority principles of “protecting the ecological environment, protecting surface buildings, addressing coal gangue and solid waste, and improving economic efficiency” for coal mine filling mining were defined. The ecological mining goal of “building the whole process holographic intelligent ecological mine by adopting filling mining as a regulation tool to protect the ecological environment in coal mines” was put forward. Based on the finite deformation mechanical model of the roof in filling mining, the factors affecting the subsidence of target rocks in filling mining were expounded, and the supporting strength calculation and overburden deformation control equations under three filling engineering modes such as ecological environment protection, ground building protection and gangue treatment were established. In addition, the paper introduced the development status and direction of universal filling technology in coal mines in China, including solid filling of raw gangue waste, modified solid filling, gangue concrete filling, integrated mining-filling-charging, large amount of gangue filling, filling method in thin coal seam, filling method for regional protection, filling method in continuous mining roadway and other filling technologies that meet various needs of coal mines. The material preparation and transportation of different filling technologies, the characteristics of filling process and the adaptive filling equipment were described in detail. In order to realize the intelligent filling of coal mines, a comprehensive data perception system was established, which realized the intelligent process from unit to whole filling working face through spatial planning and filling effect judgment. The sensor network and artificial intelligence algorithm were combined to monitor and control the solid filling process of coal mine in real time, and improve the filling quality and filling efficiency. Coal mine filling mining will play a more important role in the long-term planning of China’s green mine construction. Strengthening the scientific and technological research of the whole process of coal mine production based on active filling, the construction of universal filling technology and process system, the development of new solid filling materials, and the research of intelligent filling mining, will help the filling mining technologies in China’s coal mines have a very broad prospect.

The MILD combustion is a combustion mode that occurs in a moderate or extremely low oxygen environment, combining the advantages of high combustion heat utilization and very low NOx emissions, and is considered by the international combustion field to be one of the cleaner combustion technologies with great potential for application. Since the relevant research began around 1990, the technology for achieving a MILD combustion of gas fuels has been relatively mature, while the research on the MILD combustion mechanism and implementation conditions of solid fuels such as coal powder and biomass is still relatively lacking. Based on the high momentum oxidizer jet, internal recirculation is achieved, eliminating the need for external high-temperature preheating to establish MILD combustion, greatly expanding the application range of MILD combustion. This paper provides an overview of the basic characteristics of MILD powder fuel combustion from the aspects of particle dispersion, heating, ignition, combustion, and pollutants. Due to the uneven dispersion and reaction of particles, the MILD combustion process of carbon-based solid fuels such as coal powder is more complex than that of gas fuels. High speed jet MILD combustion not only increases ignition delay but also expands ignition and reaction zones, requiring systematic research on the characteristics and mechanisms of each combustion stage. This paper introduces the research achievements in the theoretical design and equipment development of solid fuel MILD combustion. It is recommended to improve the existing coal-fired boiler burner, adjust the process parameters to match the MILD combustion mode, increase the residence time of coke particles to improve combustion efficiency, improve combustion stability, and suppress various pollutant emissions, including fine particulate matter, through high-precision numerical simulation. Based on the overall approach of interconnected energy systems, the coupling research between MILD combustion and various new combustion technologies should be promoted, especially strengthening the research on the co-combustion characteristics of coal powder, biomass and hydrogen, ammonia and other combustible gases, and assisting in energy transformation. Exploring the characteristics of turbulent two-phase flow, turbulent interphase heat transfer, and turbulent chemical coupling in the powder MILD combustion is crucial for deepening the understanding of powder MILD combustion. It involves multivariate analysis and high-precision simulation, which will be the focus and difficulty of future research.

The safe, green, efficient and low-carbon coal mining is the common goal of surface coal mines around the world. The development intensity and ecological carrying capacity of surface coal mine resources in China show the reverse development characteristics, and the vulnerable ecological environment areas in northwest China have become the main surface coal production areas, which makes surface coal mining and ecological environment protection become important scientific problems, ecological problems and development problems to be solved urgently. On the basis of the development situation, natural conditions and main influencing factors of surface coal mines, the connotation characteristics and overall structure of realizing the safe-green-efficiency-low-carbon mining of surface coal mines were explained. Aiming at the characteristics of the whole life cycle of pre-mining, mid-mining and post-mining of surface coal mines, in terms of four levels: safe mining technology, green mining technology, efficient mining technology and low-carbon mining technology, this paper puts forward eight key technologies including the time-limited slope control technology, the intelligent early warning decision-making technology, the new mode of transportation link, the ecological construction of mining area, the coordinated mining of adjacent mines, the intelligent mining design, the application of electric mining trucks and the ecological damage reduction at mining sources. The key work and direction of safe-green-high efficiency-low carbon cooperative mining in surface coal mines are clarified. In terms of the measures of safety-green-efficiency-low carbon co-development, regarding strengthening a top-level design, accelerating the distributed implementation, enhancing key researches, promoting personnel training, and improving standards and regulations, the paper proposes the target tasks to be accomplished in different stages in 2025, 2030 and 2035. In the new era, surface coal mines should firmly follow the development path of safe-green-high efficiency-low carbon, and realizes the high-quality development goal of surface coal mines.

Coal mining machine is the core equipment of completely automated working face, and the research and development of intelligent coal mining robot is crucial for achieving the intellectualization of fully mechanized working face. This paper comprehensively analyzes the current research status of sensing detection, position and attitude control, speed control, cutting trajectory planning, and tracking control in the coal mining machine roboticization process, and proposes five key technologies that must be solved in the development of intelligent shearer robots, including sensing and detection, pose control, velocity control, cutting trajectory planning and tracking control. Aiming at the problem of intelligent perception, this paper proposes the construction thought of a coal mining robot intelligent perception system, as well as the architecture of a coal mining robot intelligent per-ception system. The architecture of the intelligent perception system for coal mining robots is outlined, enabling a comprehensive sensing of running state, posture, environment, and so on, thereby ensuring the safe and reliable operation of intelligent coal mining robots. In terms of the position and attitude control problem of intelligent coal mining robots, the intelligent PID position and attitude control thought is proposed, along with an improved genetic algorithm-based PID pose control method, enabling precise pose control for the coal mining robot. As to the problem of velocity control, the thought of cutting load measurement based on the fusion of “force-electricity” heterogeneous data is proposed. Additionally, a neural network-based algorithm for cutting load measurement is presented, achieving an accurate load measurement. Furthermore, a traction and cutting speed adaptive control approach is proposed, including an artificial intelligence-based decision-making method for traction and cutting speed and a sliding mode control method for traction and cutting speed with disturbance rejection. This approach enables a precise and adaptive speed control for the coal mining robot. Regarding the problem of cutting trajectory planning and tracking control, the precise cutting trajectory planning thought is proposed, incorporating geological data and historical cutting data into a cutting trajectory planning model. The precise cutting trajectory tracking control thought is proposed, and an intelligent interpolation algorithm-based cutting trajectory tracking control method is given, achieving a high-precision trajectory planning and accurate tracking control for the coal mining robot. Considering the “position-attitude-velocity” collaborative control problem, the intelligent optimization idea of "position-attitude-velocity" collaborative control parameters is proposed, which utilizes an improved particle swarm optimization method based on multi-system constraints to optimize the coordinated control parameters, resulting in intelligent and efficient operation of the coal mining robot. The in-depth investigation of these five key technologies for intelligent coal mining robot provides some valuable insights for accelerating the development of high-performance, efficient, and reliable intelligent coal mining robot.

In view of the intelligentization of coal mine roadway excavation, this paper discusses the current development status of four major categories of intelligent fast excavation equipment, including continuous mining machine, excavation and anchor machine, full-section excavation system, and anchor excavation machine, analyzes the applicability of the four major categories of intelligent fast excavation equipment with the geological conditions, proposes some key technological issues for the realization of intelligent coal mine excavation which need to be resolved, and also explores the information transmission and intelligent analysis technology, intelligent perception technology, precise positioning and navigation technology, autonomous stereotyped directional cutting technology, remote and autonomous cutting control technology of road-header and multi-level and multi-process intelligent cooperative control technology, as they are the basis for the realization of intelligent roadway excavation. Based on the key technological issues needed to be solved in the mine roadway excavation under the complex geological conditions, the paper puts forward the design method of systematic analysis, modular design and optimal combination of functions, according to the functional requirements of the excavation operation and the requirements of the excavation process. A multi-level digital twin architecture of virtual control and virtual-reality combination is studied based on the multi-dimensional information reproduction of heading equipment, environment, and geological structure to realize the remote control of road-heading machine. A control method that integrates single-machine intelligence, system synergism, and synergism of underground intelligent control and surface remote monitoring is proposed. A new type of flexible advance support technology without repetitive crushing, multi-stage telescopic cutting technology of cutting section, and multi-rig parallel operation technology of intelligent anchoring unit have been developed, and a new type of combined unit for rapid roadway heading operation with a parallel operation of excavating, supporting, anchoring, transporting, and exploring processes has been also developed, and a flexible parallel operation technology of excavation robot, advance support robot, anchoring robot, and auxiliary transportation robot group has been proposed. A data-driven multi-machine, multi-process collaborative control behavior planning and decision-making method is proposed. In addition, it is proposed to construct a complete coal mine underground cross-system full-temporal-spatial information digital sensing system, build a data sensing intelligent monitoring platform with multi-parameter, multi-scale and full-temporal-spatial characteristics, that integrates the production state of underground site, spatial information of roadway, state of heading equipment, and risk information, etc., and realize a real-time communication between virtual system and actual tunneling system, so as to realize the intelligent and less-manned heading through data-driven planning and analysis.

The safety in the coal-producing mines in China is continuously improving, but coal and gas outburst accidents still occur. The prediction of coal and gas outbursts allows the scientific application of outburst prevention measures, which can ensure the safe coal mining to a certain extent. Machine learning is an interdisciplinary field involving probability theory, statistics, and computer science, which can explore the nonlinear relationship between outburst accidents and its associated indicators. The application of machine learning in coal and gas outburst prediction has received relatively widespread attention, and with the rapid progress of artificial intelligence and computer technology, it will play a greater role in the field of outburst prediction. Therefore, this paper provides a comprehensive review of the research on machine learning in coal and gas outburst prediction, analyzes the difficulties in outburst prediction and prospects its development direction. Firstly, the paper provides a brief overview of the research status on the hypothesis, occurrence mechanism, and prediction index selection of coal and gas outbursts. Then, it summarizes the research progress in the field of outburst prediction, including the application of support vector machines, neural networks, extreme learning machines, and ensemble learning algorithms. In addition, it also points out the existing problems in the current research, such as imbalanced samples, missing data indicators, and small sample sizes. Finally, the paper gives an outlook on the developments of coal and gas outburst prediction based on machine learning, including improving algorithm performance, optimizing feature engineering, and increasing sample size. With the continuous improvement of computer performance, more powerful models may be proposed, which can further improve the prediction accuracy of outburst accidents.

The fragile ecological environment in the western coal mining areas of China, compounded by intensive mining activities, has led to water and soil erosion, soil degradation, and damaged root systems. With a low plant water use efficiency, the ecological restoration becomes challenging, making the improvement of water use efficiency a key aspect in the ecological restoration or reconstruction of western mining areas. Soil water is a critical factor limiting the ecological restoration of arid and semi-arid coal mining areas, as it connects atmospheric water, surface water, groundwater, and vegetation growth, serving as an important carrier for water circulation and nutrient transport. Efficient and rational utilization of soil water is crucial to the success of ecological restoration. Therefore, investigating plant root water utilization strategies plays a significant role in the ecological restoration of western coal mining areas. This paper analyzes the main research methods of plant water use at home and abroad, compares the advantages and disadvantages of different methods, and reviews the corresponding research progress. In the damaged ecological environments of arid and semi-arid coal mining areas, the application of plant-microbe combined microbial remediation technology can improve plant water use efficiency and enhance plant water use strategies. At the same time, the microbial inoculation reduces the proportion of water absorption by plants from shallow soil layers, effectively increasing the absorption and utilization of water from deep soil layers by plants, thereby enhancing plant water use efficiency. This enables the inoculated plants to exhibit a higher ecological adaptability in the arid and semi-arid coal mining areas. This paper analyzes the current research progress and existing problems of plant water use in the western coal mining areas, discusses the improvement of water use strategies through microbial remediation in mining areas, and proposes the impact of different plant combinations on water use strategies and their research focuses in the ecological restoration of western arid coal mining areas. This lays a solid foundation for achieving green, sustainable, and high-quality development in the arid and semi-arid coal mining areas, and has important ecological application value.

The first and currently only Jurassic coal seam mining floor Baotashan sandstone water inrush and well flooding accident occurred in the New Shanghai No. 1 Coal Mine in Shanghai Miao Mining Area, Inner Mongolia. This paper researched the water inrush risk assessment method and prevention and control technology of the Baotashan sandstone in the Jurassic coal seam mining floor, which is highly water-rich. Firstly, it is clear that the water inrush source of the "11.25" accident is the Baotashan sandstone aquifer in the lower part of the Jurassic Yan'an formation, and the water barrier between the coal seam and the floor Baotashan sandstone has the characteristics of low strength, low softening coefficient and poor cementation, so it belongs to geological soft rock. Secondly, a water inrush evaluation system was established using “aquifer thickness, aquifer water richness, aquifer permeability, aquifer water pressure and the effective thickness of the 18 coal floor aquifer” as the main indicators, and the water inrush of the Baotashan sandstone aquifer was the dangerous zones are divided into three types: safety zone (32.21%), threat zone (37.53%) and dangerous zone (30.26%), and the accuracy of the evaluation model was verified through the “11.25” water inrush accident. Finally, combined with the engineering geological characteristics of the floor aquifer, the method of “fault grouting to form a local restricted boundary+group hole water release” was used to prevent and control Baotashan sandstone water inrush. It was set that “Water drainage begins until drilling site #1 exits work, the 2#, 3#, and 4# drilling fields continue the water drainage work until 3# exits work, and the 2# and 4# drilling sites continue to drain water until the model is replenished and balanced.” According to the specification, the maximum curtain permeability coefficient after grouting is 2×10−2 m/d, When the curtain permeability coefficient after fault grouting is 2×10−2 − 2×10−8 m/d, the drainage volume is 4.02×10−4 m3 − 3.478×10−4 m3. The proportion of safe areas in the mining area is 43.34%−67.37% respectively. Combining the grouting cost, drained water volume and safe area, when the curtain permeability coefficient is not greater than 2×10−4 m/d, can effectively ensure the safety and technical and economic benefits of the mine. The combined technology of fault grouting local restriction boundary+water drainage can effectively prevent and control sandstone water damage in Baotashan. The research work in this paper is of great significance and engineering practice value for the prevention and control of floor water in the Jurassic Coalfield development in western China.

Fractured soft and low permeability coalbed is commonly developed in China, which restricts the increase of single well gas production and industrial development of coalbed methane (CBM). Indirect fracturing is a kind of fracturing method to communicate with coal seams by creating vertical fractures in the neighboring layers and thus achieve effective coal seam transformation, which can solve disadvantages such as drilling collapse, coal dust production, fracturing fluid filtration loss and thin coal seam thickness. In this paper, physical simulation experiments and extended finite element numerical simulation analysis of indirect fracturing are used to reveal the factors influencing the fracture expansion of indirect fracturing in the coal seam roof and to clarify the fracture expansion mechanism in order to provide guidance for indirect fracturing technology. The indirect fracturing experiments under the influence of direct fracturing of coal seam and different fracture initiation location, vertical stress and construction displacement show that high fracture initiation pressure is more likely to produce long fractures, and the influence of primary fractures is significantly reduced; however, the farther the fracture initiation point is from the coal seam, the more energy is required for fracture initiation, and high fracture pressure will cause crushing damage to the coal seam; under large construction displacement, the fracture initiation pressure is correspondingly increased, the fracture initiation time becomes shorter, and the influence of primary fractures becomes smaller. The degree of impact of primary fracture becomes smaller. Under the condition of model parameter setting in this paper，the numerical simulation results considering the parameters of ground stress, fracture initiation location, rock mechanics and construction displacement show that the maximum horizontal principal stress and vertical stress difference is 3 MPa, and the combination of coal and roof elastic modulus difference

Data governance capability is fundamental to coal mine intelligence construction. It could accelerate the intelligent construction of coal mines and promote the digital transformation of the coal industry so as to building a modern energy system in digital China. This paper therefore discusses the theory and methods of improving data governance capability for intelligent coal mines. Specifically, this study analyzes its strategic demands of intelligent coal mine construction on data governance and offers a working definition for data governance capability for intelligent coal mines. Then an evaluative system is proposed for the evaluation of data governance capability for intelligent coal mines. Further, by drawing on capability maturity theory, this study establishes a maturity model that specifies the improvement path of data governance capability for intelligent coal mines. Finally, based on the PDCA cycle theory, this paper puts forward strategies for improving data governance capability for intelligent coal mines, in order to 1)supplement existing theories of data governance capability enhancement, and 2)provide references for future practices of data governance.

How to realize safe and efficient intelligent mining of rock burst coal seam is an important industrial technical problem. This paper systematically analyzes the distribution characteristics, mining status and development trend of rock burst mine in China, and deeply analyzes the main mining problems faced by rock burst mine. From the aspects of regional ground stress monitoring and inversion, mine development layout optimization, coal pillar size optimization, combined depressurization up and down well, displacement and filling mining, separated layer grouting, etc., the development status of rock burst mine life cycle prevention and control technology is described. In view of the difficult problem of roadway rock burst prevention and control, the collaborative intelligent adaptive anti-impact support technology and equipment for all roadways with rock burst are developed. The energy absorption anti-impact hydraulic support is used to achieve the effect of strong support for roadway surrounding rock under normal condition and rapid displacement and energy absorption during the impact process. Based on intelligent migration device of support, monitoring and warning system of support and intelligent design method of all roadway collaborative adaptive anti-impact support, the prevention and control system of intelligent energy absorption support of roadway under rock burst is constructed. This paper analyzes the anti-shock principle of the intelligent mining system of coal face, proposes to predict and warn the location and probability of rock burst by monitoring and analyzing the mining stress of surrounding rock and the fracture structure of overlying rock, based on 3D geological model and big data algorithm, etc., and carry out intelligent linkage control on the supporting posture and supporting force of hydraulic support and the cutting speed of shearer through the intelligent mining system. Realize the intelligent mining of coal face and the intelligent prevention and control of rock burst. From the aspects of intelligent monitoring of stope stress and overburden structure, construction of rock burst disaster database, classification prediction and early warning of rock burst disaster, this paper analyzes the research and development focus of intelligent rock burst prevention and control technology, and puts forward the composition and overall structure of mine rock burst monitoring and early warning system. From the aspects of top-level design, key technology, intelligent and accurate crisis relief and effect evaluation, the technical path and research and development direction of realizing safe and efficient intelligent mining of coal seam with rock burst in China are put forward.

This is an essay in the field of mining engineering. In the current new energy development strategy under the new situation, lithium is an indispensable key raw material to support the development of the new energy vehicle industry and promote the new energy revolution. It is positioned as one of China's 24 national strategic mineral resources, and its strategic position is extremely important. The safety of lithium resources and the continuous supply of lithium mineral products are related to the healthy and stable development of many industries and the national economy in China. China is rich in lithium resources. However as the world's largest consumer of lithium resources and producer of lithium batteries, lithium is highly dependent on foreign countries, and there are hidden dangers in the supply system. It is urgent to improve the safety and security of China's lithium resources. Based on the combing and research on the distribution of lithium resources at home and abroad and the supply and demand situation of lithium mineral products, this paper analyzes and elaborates on the main problems and causes faced by China's lithium resources. This paper analyzes the main problems faced by China's lithium resources and their causes, and puts forward opinions and suggestions on the development and utilization, scientific and technological research, industrial structure, institutional mechanism, personnel construction, market regulation, overseas strategy and other aspects in order to increase production of lithium resources and maintain supply and stability, which provides useful reference for ensuring the safety and stability of China's lithium resources and the healthy and orderly development of lithium mining industry.

According to the limiting factors of vertical shaft blasting construction and explosive controlled conditions, combined with the characteristics of the existing cutting technology, this paper puts forward the carbon dioxide two-step cylindrical cut blasting technology. First of all , this paper introduce the principle of carbon dioxide blasting technology and the structure of carbon dioxide blasting device ,expounds the core idea of two-step cylindrical cut.“two-step” refers to a description of the cut form from two dimensions of “time and space”. The rock in the cut area is divided into two steps with different depths, and the blasting sequence of the cut hole is divided into two different stages. At the same time, the cut hole is arranged into two rings with different diameters of the double cylinder shape, the center of the cut ring is arranged with a empty hole, the first-order cut hole in the inner ring, while the second-order cut hole in the outer ring, two cut holes are inclined to the center hole at a certain Angle, so that the top area of the cylinder is large and the bottom area is small. The first-order cut hole is blasting first, and the second-order cut hole is blasting later. This two-step cylindrical cut fully combines the advantages of “two-step” and “cylindrical cutting”, that the center hole provides weak free surface and compensation space for the blasting hole, while the first-order and the second-order cut hole are surrounded by a double cylinder.In this case the blasting is carried out in two stages, which effectively combines the shallow blasting and deep blasting, reduces the clamping force of the rock during the second blasting, expands the area of cutting cavity, and improves the blasting effect. Secondly, by analyse the principle of two-step cylindrical cut blasting technology, and deduce the shear resistance formula of cut blasting and the dynamic formula of blasting cavity，and determine the basic conditions for rock ejection from the cavity under the static action of carbon dioxide explosion gas.At last, by comparing the field application effects of dynamite straight cut blasting and carbon dioxide two-step cut blasting, indicate that the two methods have small difference in the three post-detonation indicators of circulating drill footage, hole utilization rate and cut cavity volume, which further proves that the carbon dioxide two-step cylindrical cut blasting technology is suitable for vertical shaft drilling. It provides a new technical way for vertical shaft cut blasting.

At present, intelligent coal caving in high gas fully mechanized top coal caving face is facing many problems, mainly including poor recognition accuracy of coal gangue, incomplete control research on coal flow and gas concentration, cumbersome design and development of follow-up process, and slow response of control system.In order to solve these problems, this paper developed a cloud side collaborative intelligent coal caving control system based on 5G communication.The system includes 5G network, cloud server, edge processor, terminal execution equipment, etc.It has a high data transmission speed, control response speed and data processing capability.Based on the analysis of fully mechanized coal caving process parameters and intelligent coal caving process flow, elaborates the four key technologies of intelligent coal caving the coal gangue identification technology, big block coal identification and coal flow load balance technology, gas safety linkage control technology, and digital twin technology of coal caving following machine.The application test was carried out in Baode 81309 fully mechanized top coal caving face.After the intelligent fully mechanized top coal caving technology was adopted, the top coal recovery rate increased from 86% to 93%, the coal gangue rate decreased from 21% to 15%, the total production efficiency increased by 10%, and the number of coal caving operators decreased from 3 to 4 to 1 to 2.The cloud edge collaborative intelligent coal caving control system based on 5G communication developed in this paper and its key technologies can also be extended to other fully mechanized coal caving faces, which is of great value for reducing personnel and increasing efficiency and safe and efficient mining of coal mines.

The real-time monitoring and tracking system of mine moving targets is an essential part of the construction of smart mines. The appearance of downhole inspection robots can realize the real-time monitoring of operators, but the existence of uneven lighting, coal dust interference and other factors lead to the traditional image detection algorithm can not accurately detect operators. Based on this, this paper proposes an improved YOLOv5s and DeepSORT algorithm for downhole personnel detection and tracking that can be deployed in downhole inspection robots. Firstly, the data set was made by using the video recorded by the surveillance camera and inspection robot, and then the improved YOLOv5s network was used to identify the underground personnel: Considering that the detection and tracking algorithm for downhole personnel contains complex network structure and huge parameter volume, which limits the response speed of the detection model, this paper uses an improved lightweight network ShuffleNetV2 to replace the original YOLOv5s backbone network CSP-Darknet53. Meanwhile, in order to reduce the interference of complex image background and improve the attention of operators, Transformer self-attention module is integrated into the ShuffleNetV2. Secondly, the FPN+PAN structure in Neck is replaced by BiFPN structure in order to effectively fuse multi-scale features and effectively transmit inference information. Then, improved DeepSORT was used to encode and track personnel: considering that the underground environment was dark, with low illumination and no texture, it was difficult for DeepSORT to effectively extract personnel's appearance information, so DeepSORT's small and medium residual network was replaced by deeper convolution to enhance DeepSORT's appearance information extraction ability. Finally, the improved algorithm is verified by open pedestrian data set and self-built underground personnel detection and tracking data set. The results show that compared with the original YOLOv5s model, the average detection accuracy of the improved detection model is increased by 5.2%, the number of parameters is reduced by 41%, and the speed is increased by 21%. The improved YOLOv5s-DeepSORT downhole personnel tracking method has a precision of 89.17% and a speed of 67FPS, which can be effectively deployed in downhole inspection robots to realize real-time detection and tracking of operators.

Currently, algorithms such as support vector machine (SVM) and random forest (RF) are less applied in the field of coal mine roadway support. The paper studies the applicability of different machine learning models for support parameter design.Thus a higher performance model would be established to achieve reasonable and scientific design of anchor bolt support. Firstly, it is suggested to establish an intelligent prediction database for coal mine roadway support. Through on-site research, questionnaire survey, and literature search, the coal mine roadway samples are collected. The data is processed using methods such as filling in missing values, modifying outliers in box charts, and removing local abnormal factors to establish a coal roadway support database. The paper proposes a coal roadway support parameter prediction model based on synthetic minority oversampling technique (SMOTE) - genetic algorithm (GA) - SVM. The data in the database is divided into training and testing sets. The SMOTE technology is used to balance training samples, and improve the model's fitting capability for minority class samples. The training process uses GA to globally optimize the hyperparameters of SVM, further improving the overall performance of the model. The test results show that the classificaton precision of the SMOTE-GA-SVM model reaches 83.8%, which is 21.8% higher than the traditional SVM model. The machine learning methods such as SVM, artificial neural network (ANN), RF, AdaBoost (ADA), and naive Bayesian classifier (NBC) are introduced into the prediction of coal roadway anchor support parameters. The corresponding support parameter prediction models are established. The comparison results showed that the best to worst prediction models are ranked as SMOTE-GA-SVM, RF, GA-ANN, SVM, NBC, and ADA, with an average classificaton precision of 69.9%. The result verifies the feasibility of machine learning methods in predicting the parameters of coal roadway bolt support. The SMOTE-GA-SVM model is applied in Shanxi Huobaoganhe Coal Mine Co., Ltd., with a precision of 87.5% and strong applicability and reliability.

The central and western coal resources have the highest degree of enrichment and superior development conditions in China. With the improvement of mining efficiency, the disturbance of high-intensity and large-mining-height mining mode to groundwater system also increases. In particular, the groundwater in the aquifer outside the disturbance range of the water-conducting fracture zone gradually participates in the mine water inflow process during the coal mining. Such mode leads to a series of problems such as large deviation of mine water inflow prediction, inaccurate evaluation of water inflow risk and unclear water hazard prevention measures, which brings great hidden risks to the current mine water hazard prevention and control. In this paper, a derivative mode of dynamic water inrush is summarized. With the coal mining, the evolution of groundwater system caused by overburden failure will induce new disaster sources, resulting in different forms of water inrush. Its connotation is to change the basis of defining the derivative dynamic water inrush model from the traditional static analysis before mining to the dynamic evaluation considering the change in the whole mining cycle. The derived dynamic water inrush model of the mine can be preliminarily divided into three categories, namely, “skylight leakage type”, “bed separation disaster type” and “channel permeability increase type”. This paper mainly discusses the derivative dynamic water inrush mode of “skylight leakage type”. Taking the Shanxi Yushen mining area, a shallow buried coal seam mining area with high strength and large mining height, as an example, the disaster-pregnant conditions of “skylight supply type” derivative disasters are discussed in depth. Through supplementary analysis of water-richness and hydraulic connection strength of indirect water-filled aquifer, the comprehensive evaluation of water inrush risk in roof aquifer is achieved, and the evaluation method system of disaster derivative model is put forward. Through the transformation of mining mode, the active prevention and control system is constructed. A passive prevention and control system is constructed by multi-objective advance drainage before mining and local grouting after mining. By further refining the mine water inrush disaster model, optimizing the evaluation system and establishing comprehensive prevention and control technology, it provides a scientific basis for the protection of groundwater resources and safe low-carbon mining in ecologically fragile areas.

The fully mechanized mining face adopting pre-driven recovery room is prone to large roof deformation at the final mining stage, which will lead to support crushing accidents. Based on the three main roof failure forms after longwall face entered recovery room, this paper established different mechanical models for roof sag of the recovery room. By analyzing energy release and work process in roof deformation, this paper obtained the immediate roof sag of recovery room under different main roof failure forms. Taking the large roof deformation and support crushing accident of recovery room in the N14201 longwall face of Zhangjiamao Coal Mine as example for analysis, this paper analyzed the influencing factors of the models and found that the main roof break position, the thickness of key block and its overlying strata, the rotation angle of key block and the supporting intensity have significant impact on the roof sag of recovery room. The research results confirmed that the reason for the support crushing accident in N14201 longwall face of Zhangjiamao Coal Mine: the main roof is broken within 4~6 m above the protective coal pillar, and the main key stratum is broken and unstable due to the mining of upper 3-1 coal seam.

High-voltage electric pulse(HVEP)drilling has become a new and efficient rock breaking method, which is also the research focus in the field of drilling speed increase. To probe into rock breaking mechanism of high voltage electric pulse, this study establishes a two-dimensional numerical model of multi-physical field coupling electric breakdown of single pair of electrodes. The model reproduces the generation of plasma channels in homogeneous red sandstone from the coupling of current field, electric breakdown field and circuit field. This paper analyzes the effect of electrode pair angle, voltage and electrode spacing on rock electrical breakdown(that is, the formation of plasma channel in rock). The model includes the circuit structure parameters of pulse tool, the occurrence and development of electrical breakdown, and the relationship between electrical breakdown intensity and time. Results indicate that the plasma channel begins to sprout from the partial area near the top of the discharge electrode and develops towards the partial weak dielectric strength. With the voltage value of loading pulse increasing gradually, the time of electrical breakdown decreases gradually; comparatively, the equivalent failure volume of rock model increases gradually, and there is a positive correlation between them. On the precondition that the rock can be electrically broken, increasing the electrode spacing can improve the rock breaking efficiency of high voltage electric pulse. The equivalent failure volume of rock shows significant fluctuations during the gradual increase of electrode inclination angle of discharge electrode, and its extreme value mostly appears in the range of electrode inclination angle of 35°~ 55°. To further promote the industrial application of high-voltage electric pulse rock breaking, this paper proposes a three-dimensional numerical model of multi-physical field coupling dynamic electric breakdown of red sandstone based on two-dimensional model, reproducing the appearance of the fracture crater in the rock during the rock breaking process with electrode bit. At the same time, the self-designed coaxial electrode bit is selected for experiments of electric breakdown, and the laboratory experimental results of electric breakdown confirm the simulation experimental results.

In order to scientifically evaluate the impact risk of steeply inclined extra-thick coal seam in folded area and provide theoretical guidance for the prevention and control of rock burst, a numerical model including folds is established in this paper based on the prevention and control of rock burst in south mining area of Wudong Coal Mine. With the help of multiple linear regression and CASRock engineering software, the back analysis of ground stress field of steeply-inclined extra-thick coal seam in folded area of Wudong Mine is carried out. Taking B1+2 coal seam as the research object, the stress data in coal seam, roof and floor are extracted, the stress-cover depth variation curve is plotted, the distribution characteristics of pre-mining stress field are explored, and the risk assessment index related to pre-mining stress is determined. According to the back analysis data of in-situ stress and previous research results, the evaluation indexes of burst risk are determined from the aspects of geological factors and mining conditions. The static weights of 7 geological factors and 5 mining conditions are obtained by Analytic Hierarchy Process. By substituting the static weight into the dynamic weight calculation formula and combining with the traditional comprehensive index method, the risk assessment of B1+2 panel at +500 m level in the south area of Wudong Mine is carried out. According to the rockburst risk classification table, the burst risk of this panel is medium, which is consistent with the conclusion of the geological report, and the rationality of the method was verified. This method is used to estimate the burst risk of coal seam with different depths. Control group is chosen, using the traditional comprehensive risk index method to evaluate the burst of the same area, the results show that the method to obtain the risk ratings were higher than the traditional methods, approach of this paper highlights the risk factors in the evaluation index, overcoming the other indicators evaluation error caused by the interference factors.

It has always been a common demand to stay away from the harsh environment with narrow space, numerous devices, complex operation process, and hidden hazards, and realize intelligent unmanned mining in the coal industry. To achieve this goal, it is very necessary for us to develop an effective theory of vision computing for underground coalmine applications. Its main task is to build effective models or frameworks for perceiving, describing, recognizing and understanding the environment of underground coalmine, and let intelligent equipment get 3D environment information in coalmine from images or videos. To effectively develop this theory and make it better for intelligent development of coalmine, this paper first analyzed the similarities and differences about computer vision and visual computing in coalmine, and proposed its composition architecture. And then, this paper introduced in detail the key technologies involved in visual computing in coalmine including visual perception and light field computing, feature extraction and feature description, semantic learning and vision understanding, 3D vision reconstruction, and sense computing integration and edge intelligence, which is followed by typical application cases of visual computing in coalmines. Finally, the development trend and prospect of underground visual computing in coalmine was given. In this section, this paper focused on concluding the key challenges and introducing two valuable applications including coalmine Augmented Reality/Mixed Reality and parallel intelligent mining. With the breakthrough of underground vision computing, it will play a more and more important role in the intelligent development of coal mines.

Ultra wideband (UWB) radar life detection technology has the advantages of low power consumption, good penetration, and high confidentiality. It is beneficial for improving the survival rate of trapped personnel after disasters. This paper systematically summarizes the research progress and current status of UWB radar life detection technology both domestically and internationally. According to the different forms of transmitted signals, UWB radar life detection technology is divided into continuous wave radar life detection technology and pulse wave radar life detection technology. The principles and application advantages of the two detection technologies are introduced respectively. Based on the respective features of continuous wave radar life detection technology and pulse wave radar life detection technology, this paper analyzes the key technologies of UWB radar life detection from three perspectives: detection signal transmission, echo signal preprocessing, and life signal extraction and analysis, and summarizes the research status of the three key technologies. The paper proposes prospects for the research on UWB radar life detection technology. The technology breaks through the hardware performance of life detector transceivers, improves the transmission signal bandwidth, and optimizes RF power amplification technology to increase the detection distance through walls. The technology comprehensively utilizes multiple feature extraction methods and intelligent pattern classification methods, as well as new generation information technologies such as artificial intelligence, big data, and cloud computing, to improve the precision of target recognition. The technology develops a human target recognition and positioning equipment based on multi input multi output radar and a high-precision distributed networked fully polarized UWB radar life detector to enhance the dimension of detection results.

Insulation is considered the weakest link in electrical equipment. The combined effects of special working conditions in coal mines and aging factors such as electrical, thermal, and mechanical stresses make it difficult to determine the aging mechanism and evaluate the condition of EPDM insulation for high-voltage cables used in mines. This paper introduces the basic performance and aging factor types of EPDM insulation for high-voltage mobile flexible cables used in coal mines. Based on the physical, chemical, mechanical, and electrical properties of EPDM under the influence of multiple aging factors, the aging mechanism of EPDM is proposed. This paper summarizes the basic principles and existing problems of online monitoring methods for insulation resistance, partial discharge, dielectric loss factor, and temperature of mining high-voltage cables. The paper summarizes the current research status of insulation status evaluation methods for mining high-voltage cables. The paper introduces the evaluation methods for insulation status of multi parameter based on improved radar map and single parameter based on dielectric loss mining high-voltage cables. To cope with the development of coal mine intelligence, on the one hand, it is suggested to do research on intelligent perception and control of mining electrical equipment to compensate for the lack of state perception and state evaluation feature quantities. On the other hand, it is necessary to study lightweight models or algorithms to reduce the computational complexity, parameter quantity, and analysis time of intelligent terminals near devices. It improves the feasibility of state evaluation technology, and lays the foundation for achieving intelligent analysis and decision-making.

The in-situ monitoring technology for overburden movement in mining has the features of adapting to complex geological conditions in deep shaft high pressure water and thick coal seam mining, multi layer dynamic monitoring, and high-precision remote real-time online transmission. It provides effective data support for mining enterprises to carry out roof disaster prevention and control. Starting from the practical background of coal mining application, this paper systematically reviews the development process, technological progress, and application effects of in-situ monitoring technology for overburden movement in mining. Based on the development history of mining pressure theory and overburden movement monitoring technology in China, this paper comprehensively introduces the important stages of in-situ monitoring technology for overburden movement in mining. It elaborates on the theoretical innovation and technological breakthroughs achieved by this technology in three aspects: multidimensional real-time collaborative monitoring, unmanned online monitoring, and deep rock movement monitoring. Based on the monitoring engineering examples of coal mines such as Bulianta Coal Mine, Tongxin Coal Mine, and Gaojiabao Coal Mine, the effectiveness of in-situ monitoring technology for overburden movement in mining is demonstrated in practical engineering applications. The application prospects of this technology in different types of mining areas and research fields are discussed. It is pointed out that the development trend of in-situ monitoring technology for overburden movement in mining is precision, intelligence, and integration, namely optimizing sensor performance and layout plans to improve monitoring precision and accuracy, using artificial intelligence, big data, and Internet of things technology to achieve automatic analysis and prediction, combining the in-situ monitoring technology with other technologies to form a complete monitoring system.

5G technology is the foundation for achieving intelligent mining construction. In response to the problem of difficult interoperability between mining 5G intelligent terminals and control platforms among different manufacturers, it is necessary to unify and standardize the data exchange and sharing process in the 5G system. The deployment architecture of '5G+intelligent mining' is proposed. The mining 5G intelligent terminals can interact and share data with servers containing control platforms through 5G base stations, switches, and 5G core networks in coal mines. This paper introduces the message types, message transmission formats, message composition, and message connection methods transmitted in the mining 5G system. For specific application scenarios in the mining field, the data in the mining 5G system is divided into voice data, video data, sensor data, and control data. The data types transmitted by the mining 5G intelligent terminal in different application scenarios are provided. This paper analyzes the basic transmission capabilities that mining 5G intelligent terminals and control platforms should have to meet data interaction. It is pointed out that the process of data interaction between mining 5G intelligent terminals and control platforms includes device information query and reporting, device upgrade, log collection, alarm issuance and processing, and platform configuration issuance and processing. It proposes the participating entities, security levels, and processes for data sharing of mining 5G intelligent terminals (including data aggregation, application, authorization, provision, and feedback). By implementing standardized processes, while ensuring communication reliability, the data exchange and sharing process under the '5G+intelligent mine' system architecture has been simplified to accelerate the intelligent construction of mines.

This is an essay in the field of mining engineering. Deep-sea rare earth rich deposit, as a potential rare earth resource, are an important supplement to land rare earth resources and may become one of the first deep-sea minerals to be exploited. In this paper, four deep-sea REE rich deposit (REE rich deposits in the western Pacific Ocean, the southeast Pacific Ocean, the middle and east Pacific Ocean, and the Middle Indian Ocean basin-Wharton Basin.) are analyzed. This paper summarizes the basic resource characteristics of deep-sea rare earth rich deposit (such as large total reserves, large distribution differences, and the main occurrence mineral is biological apatite), and reviews two methods (acid leaching-extraction separation technology and separation-flotation method) used in the separation and extraction of deep-sea REE. The result shows that the acid leaching-extraction separation technology has the disadvantages of low recovery of REE and excessive acid consumption. The separation of sediment samples before flotation operation can achieve efficient enrichment of REE in deposit under the condition of low acid consumption, which is an important development direction to separate and extract REE resources from deep-sea REE rich deposit. Based on this, it is suggested to strengthen the research and development related to efficient classification of deep-sea REE rich deposit resources and in-situ mining and leaching technology in the future.

This is an essay in the field of mining engineering, which takes Panxi vanadium-titanium magnetite associated sulfur resources as the research object, and expounds its comprehensive utilization path and its low-carbon development significance. Sulfur is one of the typical associated elements of Panxi vanadium-titanium magnetite, and it is also a port element of the emerging industrial chain of food-resource-energy in the double carbon era. Based on the endowment conditions of Panxi vanadium-titanium-magnetite associated resources and the occurrence status of sulfur minerals, this paper analyzes the current situation and characteristics of associated sulfur resources, and uses the mining and dressing industry chain of vanadium-titanium magnetite to discuss the possible environmental impact of sulfur in the process of comprehensive utilization. The comprehensive utilization potential analysis is discussed from two aspects of mineral product demand and comprehensive utilization maturity risk assessment. Under the circumstances that associated sulfur resources are facing the challenge of green and low-carbon development, this paper puts forward comprehensive utilization suggestions from the three aspects of planning top-level design, technical research, and production line promotion, aiming to promote the development of the sulfur industry guided by the principle of green and low-carbon, Focus on promoting carbon reduction and pollution reduction through source sulfur selection production line intervention. The research in this paper can provide new ideas and specific suggestions for the comprehensive utilization of sulfur resources associated with vanadium-titanium magnetite, environmental planning and low-carbon development.

Under mining conditions, the micro crack structure of the composite strata of the coal seam floor affects the uplift and seepage of the groundwater in the underlying high water pressure aquifer, and its complexity is of great significance for the prediction and early warning of the water disaster in the coal seam floor. In this paper, a total of 57 groups of rock samples extracted from three adjacent mines in the east of Pingdingshan Coalfield are taken as the object. Based on the comprehensive information of SEM image acquisition and N2 adsorption test, the fissure ratio of rock stratum area, equivalent crack diameter of rock stratum, fractal dimension value of fissure area, specific surface area, crevice volume and its fractal dimension are the main controlling factors. Using entropy weighted TOPSIS mathematical model, the complexity of the micro fracture structure of the composite rock stratum between the Ji16-17 coal seam and the Cambrian limestone top interface is quantitatively evaluated. The results show that the micro crack structure of the composite strata in the floor of the Ji16-17 coal seam is very simple, simple, medium, complex and extremely complex, accounting for 25.00%, 21.43%, 39.29%, 7.14% and 7.14% respectively. The micro crack structure of the composite strata in the study section is relatively uncomplicated; Compared with the four rock sections, the order of the quantitative mean value of the complexity of the rock stratum micro fracture structure is: L1−L2 limestone section>L5−L7 limestone section>sandstone section>bauxite mudstone section. The complexity of the rock stratum micro fracture structure better reflects the development of the rock stratum fracture. The paper considers the coupling effect of multiple factors on the composite rock stratum, realizes the quantitative classification and zoning discrimination of the micro crack structure in the vertical section of the composite rock stratum, which is of great significance for accurately describing the aquifer performance of the composite rock stratum in the coal seam floor and scientifically guiding the prevention and control of the water hazard in the coal seam floor.

The existing mine pressure prediction models are mostly single prediction models that rely on fixed length time series features. It is difficult to accurately capture the composite features of mine pressure time series data, which affects the accuracy of mine pressure prediction. To solve this problem, an ensemble learning mine pressure prediction method based on variable time series shift Transformer-long short-time memory (LSTM) is proposed. Based on the Laida criterion and Lagrange polynomial method, the outlier values in the mine pressure monitoring data are eliminated, and the missing values are inserted. Then normalized preprocessing is performed. The paper proposes a variable time series shift strategy to divide mine pressure time series data at different scales. It avoids potential data shift issues that may exist in fixed length time series. On this basis, the ensemble learning mine pressure prediction model based on Transformer-LSTM is constructed. By combining the attention mechanism and the accurate time series feature representation capability, the dynamic features of the mine pressure change law are captured at multiple levels. The voting algorithm of ensemble learning is used to jointly predict the mine pressure data to overcome the limitations of a single prediction model. The experimental results show that the voting algorithm of ensemble learning can reduce the volatility of mean absolute error (MAE) and root mean square error (RMSE) of mine pressure prediction. It effectively reduces the sensitivity impact of different scale feature series to the mine pressure prediction results. Compared with the Transformer model, the MAE of the Transformer-LSTM model's prediction results on two roof mine pressure datasets of fully mechanized working faces improves by 8.9% and 9.5% respectively, and the RMSE has increased by 12.7% and 16.5% respectively. The above indexes are also higher than those of back propagation (BP) neural network model and LSTM model. The method proposed in the paper effectively improves the accuracy of mine pressure prediction.

Mine communication is an indispensable part of the intelligent development of coal mines. This paper analyzes the advantages and disadvantages of different communication systems and technologies in different development stages of wireless communication in underground coal mines. It is concluded that 5G and WiFi6 currently have significant technological advantages and good applicability in terms of transmission rate, delay, reliability, and user capacity. They are the mainstream solutions for mine wireless communication technology in recent years. This paper discusses the problems in underground wireless communication system construction and the corresponding development directions. ① Technological convergence issues. Different scenarios have different requirements for bandwidth, delay, power consumption and reliability. A single communication technology can not meet the requirements of all application scenarios in coal mines. It is necessary to select appropriate communication technology according to the actual application situation to meet the application requirements. Different technologies are integrated through protocol converters, gateways and other devices to form an integrated communication network platform for technological convergence above the ground and underground. ② System integration issues. Since each system is provided by different manufacturers, and the communication protocol and hardware interface are inconsistent, it is difficult to truly realize the data sharing of each system in the mine. It is necessary to provide standard interfaces, open network architecture, and unified user data to provide interconnection and inter-working functions for monitoring, emergency, production, and other systems. It is further required to provide unified data messages to enable data transmission with low delay, high concurrency, real-time, and synchronization within each system. ③ Device power consumption issues. The existing mine 5G base station and other equipment can only be made into a single flameproof product due to their high power consumption. The equipment is bulky, large, and difficult to install and maintain, which restricts the popularization of 5G technology in coal mine. Low-power design can be started from the main chip, RF module, and power amplifier module.

While giving full play to the role of coal energy security supply, it is an important proposition related to national energy security and overall development to realize green and safe mining and clean and low-carbon utilization of coal resources. This paper analyzes the influence of changes in the international development environment on the China’s utilization of oil and gas resources in the international market, and studies the rigid demand for energy supply in China. Based on the current situation of energy development and utilization with coal as the main energy source in China and following the fundamental requirements of building a harmonious modernization between man and nature, this paper puts forward the green and low-carbon development direction and path of coal industry in the process of realizing the goal of “dual carbon”. ① China’s external dependence on oil and gas resources exceeds 70% and 40% respectively, and its strategic reserves are insufficient. Under the background of profound changes in the international situation, the uncertainty of using oil and gas resources in the international market increases, and the external risks of national energy security have increased. ② Building a modern country will inevitably lead to the rigid growth of energy demand. At present, it is difficult for new energy sources to replace fossil energy safely and effectively, and the main energy position of fossil energy will be difficult to change in the short term. ③ Comparing with the “dual carbon” goal, the proportion of coal consumption before the peak shows a continuous downward trend, and the total consumption will usher in an inflection point. After the peak, the main energy position of coal will be weakened, but the role of strategic mineral resources and coal-based raw materials will be further highlighted. ④ Driven by the goal of “dual carbon”, the basic national conditions with coal as the main energy source determine that coal will continue to undertake the important mission of energy security supply and further play the role of strategic mineral resource as raw material. However, the high carbon resource attribute of coal determines that the development and utilization of coal will face the dual pressures of ensuring supply and reducing carbon emissions. Therefore, in order to serve the high-quality economic and social development, which requires security and green and low-carbon energy supply, it must be based on the current characteristics of energy production and supply with coal as the main energy source and new energy as the supplement at this stage, and take the new progress of ecological civilization construction as the fundamental principle. The research on the key technologies should be enhanced such as the technologies of coal mining and ecological carbon sink, CO2 geological storage in deep coal seams and coal mined-out areas, and collaborative development and utilization of new energy in coal mining areas, which will support the high-quality development of the China's coal industry with technological innovation under the goal of “dual carbon”.

CBM reservoir is a typical fracture-controlled gas reservoir, and the scale of fracturing and fracture-filling effect have decisive control on gas well productivity. In order to reveal the influence mechanism of the hydraulic fracturing effect of CBM vertical wells on the productivity effect of gas wells, taking the Haishiwan Mining Area of Yaojie, Gansu as an example, this paper focuses on reporting the fracturing effect of coal reservoirs under the form of vertical well development and its understanding of the constraints on productivity. the result shows: ① The fracture pressure of CBM well mainly feeds back the characteristics of the wellbore cement sheath rather than the mechanical properties of the coal reservoir. From the fracturing curve of this well, the fracture pressure is not obvious, indicating that the thickness of the cement sheath in the wellbore annulus is moderate, and the cement sheath is relatively easy to rupture during hydraulic fracturing. The energy of the injected fracturing fluid is mainly used to prop up the coal cracks; ② It can be seen from the fracturing curve that the propagation pressure of the hydraulic fractures(HF) in this well is relatively high, indicating that the structure of coal reservoir is relatively fragmented and coal fines are developed. In addition, there are multiple wave morphological features in the fracture propagation stage of the fracturing curve, indicating that multiple secondary fractures are propped up. On the whole, the HF in this well are relatively complex, and it is speculated that branched secondary fractures develop on both sides of the main HF. ③ Serious sand plugging occurred after sand injection in this well. The main reason was that the fracturing fluid in the coal reservoir was lost due to the loss of the fracturing fluid in the near-wellbore area, resulting in the formation of wedges by proppant de-sanding in the HF, which made subsequent proppant injection difficult. It is related to the coal fines of primary fractures and the development of a small amount of tectonic coal fines; ④ The fracturing microseismic monitoring data show that the main HF of the coal reservoir in this well are NE 50°, and the coal rock microseismic events are more active in the northeast direction, indicating that the natural fracture (NF) of the coal reservoir is more developed in this direction; Based on the observation results of fracturing and mineback, this paper proposes a division plan for the effective propped area, the actual fracture area and the rock mass disturbance area of HF. It is believed that the actual half-length of the HF in the coal reservoir of this well is less than 20 m, the half-length of the effectively propped HF is less than 5 m, and The small amount of fracturing fluid injected, the formation of wedges by proppant de-sanding induced by fracturing fluid-loss, and the sand plugging caused by coal fines accumulation are the main factors for the short fractures in the coal reservoir of this well; ⑤ Combined with the law of coalbed methane productivity, it is considered that the gas reservoir management and drainage system in this well is reasonable,However, the effective propped HF in the coal reservoir are too short, and the coal fines migration in the coal reservoir leads to the rapid decline of the conductivity of the near-well HF, which is the key restricting mechanism for the productivity of gas wells.It is recommended to increase the injection volume of fracturing fluid, appropriately increase the flow rate of fracturing fluid, reduce the proppant-sand ratio, and focus on controlling fracturing fluid leak-off and the formation of screenout wedges in the hydraulic fracturing of coal reservoirs in the later stage.The coal seam in this area has a large burial depth and high stress, and the realization of large-scale fracture propped is the key to coal reservoir fracturing. Meanwhile, the reservoir is dry and the fracturing fluid is seriously leak-off, the CO2 pre-fracturing test can be carried out.

The utilization of underground space in abandoned mines is a key direction supported by the coal industry. By combining underground space utilization, flood storage, and heat supply in winter, this paper proposes a comprehensive utilization model of flood storage and heat extraction in the abandoned mine, based on three technologies: ground flood diversion, underground flood storage and heat pump. This paper addresses the concept, key technologies and scientific issues of the model. The distribution of abandoned mines in China and its relationship with precipitation distribution were analyzed. The potential for flood and energy storage in abandoned mine was also studied. Results showed that 13 provinces, including Anhui, Henan, and Shandong province, can utilize approximately 60 million cubic meters of underground space and store nearly 6 volumes of West Lake water, making it suitable for engineering demonstration of flood storage and heat extraction in abandoned mines. Among them, five abandoned mines in Huainan mining area can utilize approximately 300 000 cubic meters of underground space, with energy storage capacity of up to 94 500 GJ that can meet the heating demand of 210 000 square meters. Taking Qishan Mine as an example, a scheme was designed based on ground flood diversion and storage, underground water storage, and mine water extraction and utilization. According to preliminary calculations, the heating power of Qishan Mine can reach 6 835 kW which can provide heating for 136 700 square meters of buildings, reduce carbon dioxide emissions by about 5 330 tons, and save 3.507 5 million yuan. This demonstrates the feasibility of flood and energy storage in abandoned underground space. Research showed that the comprehensive utilization model of flood storage, energy storage, and heat extraction in abandoned mines can not only effectively utilize the underground space of abandoned mines but also alleviate local flood disasters during the flood season. It can develop low-grade clean energy in mine water and has certain significance in improving the added value of underground space utilization in abandoned mines and promoting the utilization of underground space in abandoned mines.

As a device for timely rescue after disasters, life detectors play an irreplaceable role in locating, exploring, and searching for living organisms. This paper analyzes the working principles, technical features, usage scenarios, advantages and disadvantages of the currently used life detectors. The detectors include radar life detectors, audio life detectors, infrared life detectors, and other types of life detectors. Combined with practical applications, this paper points out the problems of the above life detectors. ① The detection technology is single and the comprehensive integration is low. ② The detection methods are traditional and equipment intelligence is insufficient. ③ The parts of the detector are not standardized, making equipment maintenance difficult. ④ Some life detectors have a relatively large structure and are inconvenient to carry, which affects rescue efficiency. In response to the existing shortcomings and problems, the development trends of life detectors are proposed. ① It is suggested to improve the integration level of life detectors. It is suggested to design life detection devices that use multi-source fusion to collect information, and use multiple information sources to obtain and detect life information. ② It is suggested to improve the intelligence level of life detectors, give them partial autonomy in decision-making, and reduce errors in life detection caused by improper operation by operators. ③ It is suggested to design modular life detectors and develop relevant standard procedures to standardize the components of the same type of life detector. It will reduce the difficulty of repair and maintenance of life detectors. ④ It is suggested to improve the circuit board design precision of the life detector, fully utilize spatial structure, reduce volume and improve portability without reducing the functionality of the life detector.

Currently, the intelligent construction of coal mines is in a transitional exploration period from primary to intermediate and advanced intelligence. The independent innovation capability of existing intelligent equipment still needs to be strengthened. The core technologies are bottleneck problems. The reliability problem under complex underground storage conditions is prominent. It is of great significance to use the new generation of information technology to promote the digital transformation and upgrading of coal mine equipment, and to promote safe, efficient, and green coal mining through digitization and intelligence. This paper reviews the evolution process of intelligent development of coal mining technology and equipment in China. This paper analyzes the production characteristics of each stage of coal mining. It is considered that the coal mine intelligence has completely changed the coal production mode. The production factors are mainly intelligent equipment, intelligent systems, and compound technical talents. They have essentially improved the level of safe and efficient production of coal mines, and helped the coal mines to reduce personnel, increase safety and improve efficiency. Among them, intelligent coal mine equipment is the core element of coal mine intelligence. Considering the demand for the digital and intelligent transformation and development of future coal mine equipment, we have explored the path of integrating the new generation of information technology and coal mine equipment. It uses equipment as an intelligent carrier. It endows the equipment with humanized intelligent capabilities such as intelligent perception and analysis, intelligent judgment and reasoning, intelligent decision-making and control, intelligent diagnosis and learning through the new generation of information technology. The system architecture of the Internet of things, 5G, big data, cloud computing, and artificial intelligence technology enabling intelligent perception, intelligent transmission, intelligent analysis, intelligent computing and intelligent decision-making of coal mine equipment has been constructed. The paper analyzes the theoretical, technical, and talent challenges in the development of digital intelligence in coal mining equipment. The paper proposes suggestions for the development of digital intelligence in coal mining equipment. Consolidating the foundation is the priority. It is necessary to build a top-level design theoretical system for intelligent coal mining equipment, strengthen key core technology research, accelerate the construction of new infrastructure, and consolidate the foundation of intelligent coal mining development. The intelligent technology for coal mining equipment and special application scenarios in coal mines develop in collaboration and coupling. It is suggested to meet the on-site needs of coal mines, form the intelligent technology for coal mine specific scenarios, and explore innovative models of equipment digital intelligence integration. The intelligent technology and green mining technology integrate and develop. It is suggested to create digital, intelligent, and green equipment. It is suggested to develop new models of intelligent, efficient, and low-carbon coal mining, and promote energy conservation and consumption reduction in coal production. It is suggested to establish a sound system for cultivating intelligent talents in coal mines, cultivate interdisciplinary and composite talents, and enhance talent reserves for the construction of intelligent coal mines.

The conveyor belt and driving device are the main components of the belt conveyor and are the high-risk areas for faults. Taking conveyor belt faults and driving device faults as the starting point, this paper analyzes the mechanisms of conveyor belt deviation, slipping, damage, stacking and scattering, as well as the faults of the driving device roller, idler and reducer. It focuses on the research progress of knowledge-driven and data-driven fault diagnosis methods for belt conveyors. Based on the knowledge processing technology, the knowledge-driven method realizes the unification of symbol processing and numerical processing, the unification of reasoning process and algorithm process. It mainly includes expert system and fault tree analysis. The data-driven method uses machine learning and data mining techniques to analyze and process historical data. It establishes diagnostic models, and achieves fault diagnosis purposes. It mainly includes support vector machines (SVM), comparison method, and diagnosis methods based on sound and vision. This paper analyzes the current challenges and future development trend of belt conveyor fault diagnosis methods. ① The historical fault data and real-time data should be combined to infer equipment health. The early minor faults should be predicted so as to remind the staff to carry out predictive maintenance. ② The correlation between coupling faults of belt conveyors should be revealed. The emerging technologies such as artificial intelligence should be used to study joint diagnosis methods for coupling faults. ③ The multimodal machine learning technology should be utilized to study the mechanism of multimodal information fusion and utilization of belt conveyors. Fault diagnosis methods for multimodal information fusion of belt conveyors needs to develop. ④ The fault knowledge graph and the belt conveyor domain knowledge should be combined to realize the belt conveyor equipment fault tracking and fault early warning. Through the knowledge query, knowledge reasoning and auxiliary decision-making functions, the capability of fault handling and precise mining of potential fault risks of equipment can be improved.

Mine air stopping is a key facility separating production systems from abandoned ones. Ensuring full lifecycle risk management is of great significance for ensuring safe production. Based on the current status of comprehensive control technology for mine air stopping, the shortcomings of the existing air stopping management mode are analyzed from two aspects: static attribute information management and dynamic information monitoring. The paper puts forward the concept of intelligent management and control in the full lifecycle of air stopping. It indicates the overall construction path of air stopping risk monitoring and early warning based on big data strategy of the Internet of Things (IoT)+Artificial Intelligence (AI)+Cloud Platform (CP), and integrated with cloud-edge architecture. The IoT platform is applied to access digital monitoring and linkage control equipment for air stopping units, achieving transparency in the full lifecycle control of air stopping. The method focuses on the evolution signs of air stopping information and efficient edge computing. It deploys mobile terminals, edge computers and other field terminals to adapt to online prediction and advance warning of air stopping service status. In the smart cloud, the virtual reality scenario of a distributed mine air stopping and its full lifecycle evolution characteristics are reconstructed iteratively in real time with multi-source fused information and digital twin models at the core. The paper analyzes key theories and and model construction methods, including the physical-digital driving mode of evolution information in air stopping environments, the multi-source heterogeneous data fusion model of air stopping perception information, the edge detection and hierarchical intelligent warning of air stopping anomalies, and the emergency intelligent decision-making and collaborative prevention and control throughout the entire lifecycle of air stopping. The physical and functional architecture of an air stopping full lifecycle safety risk monitoring and warning system based on the IoT is designed. The on-site embedded air stopping multi-parameter integrated monitoring sensors and supporting intelligent hosts are developed. The early sensing and monitoring and warning methods for air stopping risks are proposed to achieve digital empowerment and effectively promote the construction of smart mines.

This paper reviews the general situation of the development and innovation practice of China's coal industry in the past 50 years promoted and witnessed by the Journal of Mine Automation from coal mine mechanization to automation and intelligence. This paper expounds on the innovation process of coal mine automation and intelligence. It focuses on the analysis of the research and development and practice of coal mine information infrastructure, automation and intelligent equipment and systems. The integration and unified hosting of heterogeneous networks is the information foundation for coal mine automation and intelligence. On the basis of the continuous maturity of the heterogeneous network of the backbone network and access network, the wired communication transmission rate has reached over 10 Gibit/s. The wireless communication technologies such as 5G and WiFi6 have been widely applied, providing a reliable communication platform for the intelligent construction of coal mines. Wired communication, wireless communication, IP broadcasting, personnel locaiton monitoring system, and video monitoring system are integrated to build a multi-network integrated communication system, achieving integrated carrier network and unified location service. The development of intelligent automation equipment in coal mines is rapid. It explores adaptive cutting technology based on transparent geology, automatic coal release control technology on the basis of technologies such as memory cutting of coal mining machines and automatic following and moving of hydraulic brackets at coal mining working face. On the basis of achieving profiling cutting, positioning navigation, and remote control, the excavation working face has made breakthroughs in technologies such as drilling anchor integration, multi-machine collaboration, and cutting template planning of roadheader based on geological model, achieving good results. The development of intelligent equipment for coal flow transportation systems is supported by intelligent variable frequency energy-saving transmission. The integrated research and application of coal mine robots are achieved. The mature application of inspection robots is obtained. The breakthroughs in intelligent auxiliary operation robots are achieved. The development of a multi-scene robot cluster scheduling and command system forms a robot cluster. The automation and intelligent construction of coal mines have officially entered the stage of intelligent mine comprehensive control from single system automation, comprehensive mine automation, and the Internet of Things. The realization of intelligent perception, intelligent self-control, high-speed transmission, collaborative control, and intelligent decision-making is an inevitable requirement for the development of intelligence. The paper proposes key directions for the iterative development of coal mine intelligent technology, including the establishment of high-precision transparent geological models, the normal and reliable operation of unmanned operating systems, the construction of intelligent compatibility and collaboration mechanisms for coal mine giant systems, the intelligent collaborative control of the entire process of 'excavation, mining, transportation, washing, and sales', and the optimization of a flexible coal production and supply system.

This paper introduces the evolution and development process of coal fire and its features. This paper expounds on the detection mechanism and research progress of four layers of space exploration technology divided according to the different spatial positions of detectors. The technologies include underground, surface, aerial, and aerospace detection methods. The paper analyzes the advantages and disadvantages of the above four detection technologies. The existing research problems are pointed out. ① The detection precision is insufficient and it is difficult to accurately delineate the acquisition range. ② The detection technology is outdated, and it is difficult to accurately detect high-temperature points in fire areas. ③ The detection method is single and cannot accurately determine the specific information of underground coal fire combustion. In view of the new features of underground coal fire, such as concealment, coupling and complexity, the development directions of underground coal fire detection technology are proposed. ① The detection instrument data needs to be finely processed, so as to improve the sensitivity of magnetic difference to temperature, the detection precision of the resistivity method, the feature extraction rate and the result precision of the infrared detection method. ② It is suggested to utilize high-tech equipment to serve coal fire detection technology. ③ It is suggested to improve the collaborative utilization of multi-level detection technology. Firstly, large-scale fire detection is carried out using the four th level aerospace remote sensing technology to obtain the basic spatial distribution features of underground coal fire anomalies. Secondly, further exploration is carried out using the third level aerial remote sensing detection technology to obtain the specific spatial distribution of underground coal fires. Finally, a more detailed distribution of high-temperature points in the coal field fire area is obtained by using the surface detection technology and underground detection technology at the second level and the first level to supply and verify. ④ It is suggested to develop 3D visual and dynamic monitoring and early warning of coal field fire areas. 3D inversion and joint inversion imaging are performed by use of data from four different levels of detection technology. Based on the imaging results, visual monitoring and early warning of coal fire development and spread are carried out, so as to achieve active prevention and control of underground coal fine disasters.