337 results about "Coal mine methane" patented technology

The invention provides a gas extraction multi-parameter monitoring method and system based on edge calculation, and relates to the technical field of coal mine gas extraction. The method comprises the following steps: arranging multi-parameter sensor nodes in drill holes, pipelines and gas gathering stations, and accessing an edge calculation unit; performing time synchronization, zero drift correction, outlier elimination and normalization on the data of the gas concentration, the negative pressure, the flow, the temperature, the humidity and the hydrogen sulfide concentration to generate feature vectors; calling a lightweight neural network model for reasoning, and outputting an extraction efficiency score and a leakage risk degree; when the risk degree exceeds the limit, an acousto-optic alarm is triggered and a speed reduction instruction is issued; when the efficiency is insufficient, the negative pressure is adjusted; compressing and encrypting the result, and reporting the result to a cloud platform through a wireless network at regular time; and the cloud performs model incremental training based on historical data and feedback, and issues an update model through hot replacement. According to the invention, local intelligent analysis, rapid early warning and dynamic adaptive optimization are realized.

The invention provides a coal mine gas extraction management and control method and system based on transparent geology, and the method comprises the following steps: integrating multi-source geological data, and constructing a transparent geological model which can reflect the actual geological condition in real time; based on geological information provided by the transparent geological model, calculating and optimizing key parameters of a drill hole in combination with coal and rock seeing parameters of a constructed drill hole to obtain preset drill hole design parameters; construction parameters and drilling parameters of drilling machine equipment are collected in real time; the drilling parameters are compared with the preset drilling design parameters; meanwhile, the drilling construction quality is analyzed and evaluated according to the construction parameters and the drilling parameters; and an extraction effect evaluation model and an extraction effect prediction model are constructed, gas parameters are collected in real time, and the gas extraction effect is evaluated. By means of the transparent geologic model, intelligent control over the whole coal mine gas extraction process is achieved.

The invention discloses a coal mine gas concentration monitoring and early warning system, relates to the technical field of safety early warning, and aims to solve the technical problems that a traditional coal mine gas concentration monitoring and early warning system is insufficient in monitoring precision and not timely in early warning, and the coal mine gas concentration monitoring and early warning system comprises a monitoring module used for monitoring the temperature, humidity, oxygen concentration and gas concentration value of the environment in real time, the temperature, the humidity, the oxygen concentration, the gas concentration value and the position data of the monitoring nodes are transmitted to a data processing module; the self-adaptive compensation module is used for receiving the temperature, humidity, oxygen concentration and gas concentration values which are transmitted by the data processing module and monitored by the monitoring nodes in real time and correcting the temperature, humidity, oxygen concentration and gas concentration values to obtain temperature, humidity, oxygen concentration and gas concentration standard values; and a data processing module. The coal mine underground gas concentration monitoring system has the advantages of accurately and comprehensively performing real-time monitoring and effective early warning on the coal mine underground gas concentration.

The invention relates to the technical field of coal mine gas disaster prediction, in particular to a while-drilling sensing coal face gas danger area division method which comprises the following steps: S1, in a detection drill hole drilling process of a coal face, detecting the gas danger area of the coal face; the method comprises the following steps: synchronously acquiring three types of parameters: direct gas parameters, drilling kinetic parameters and hole wall geophysical parameters through a measurement-while-drilling system; the measurement while drilling system comprises a sensor array arranged on a drilling tool and a data transmission module communicating with a ground data processing system. S2, performing space-time alignment and fusion analysis on the multi-source parameters acquired in the step S1, and adopting a mode recognition method based on mutation point detection and multi-parameter association; through multi-source information fusion and dynamic coupling modeling, accurate identification and graded early warning of a gas dangerous area are realized, the detection precision and early warning timeliness are improved, and a closed-loop prevention and control system integrating perception, evaluation and management and control is formed.

The invention discloses a method for rapidly and efficiently extracting coal mine gas in a broken and soft coal seam, and belongs to the technical field of coal seam gas development and coal mine gas prevention and control. According to the method, geological features of a coal mining planning area are determined, a ground U-shaped well and underground bottom-pumped rock drift layer-crossing drilling combined treatment system is deployed, and regional large-scale treatment is achieved in a well factory mode; the fracturing transformation range and the fracturing fluid distribution characteristics are detected by using a ground and underground combined micro-seismic monitoring and underground transient electromagnetic method, and the arrangement of layer-crossing drill holes is optimized; dividing the cross-layer drill holes into drainage holes and air exhaust holes, and formulating a collaborative extraction system in combination with different drainage and extraction stages; the method solves the problems that broken soft coal seam gas extraction is low in efficiency and long in period, and treatment blind areas exist, treatment time is remarkably shortened, cost is reduced, and safe and efficient production of a coal mine is guaranteed.

The invention provides coal seam multi-section type directional fracturing and permeation increasing equipment and method, and relates to the technical field of coal mine gas treatment and coal seam gas exploitation, the coal seam multi-section type directional fracturing and permeation increasing equipment comprises a machine body, a propelling mechanism, a fracturing pipe and a liquid inlet mechanism, and a plurality of sets of directional assemblies are arranged outside the fracturing pipe at equal intervals; and the fixing mechanism is used for directionally spraying the high-pressure water to the fixed direction in the coal seam and comprises a limiting component arranged on the propelling mechanism and used for limiting the fracturing pipe stretching into the fracturing seam and a connecting component arranged on the limiting component and used for locking the fracturing pipe. High-pressure water can be directionally jetted to the fixed direction in a coal seam fracturing hole, the situation that due to the fact that the high-pressure water is jetted at will, a large number of cracks are generated on the soft portion of the coal seam, and consequently permeation increasing is uneven is avoided, in addition, a fracturing pipe stretching into the fracturing hole can be fixed, and the situation that the permeation increasing effect is affected due to the fact that the fracturing pipe shakes when equipment runs is avoided.

According to the open pit coal mine methane emission monitoring equipment, the pretreatment device, the sampling air pump and the CH4 analyzer are arranged through the mounting column, and the stability of the mounting column is ensured through the base of the triangular structure support. The pretreatment device is a three-stage progressive filtering unit, dust and steam in the open pit coal mine gas can be removed, and the obtained sample gas can be cleaner and drier and is appropriate in temperature. By utilizing suction force generated by the sampling air pump, air enters an optical cavity of the CH4 analyzer after being treated by the pretreatment device. The CH4 analyzer further comprises a laser and a CH4 optical analysis module, the laser emits a laser beam with a specific wavelength to the optical cavity, and multiple reflections are formed in the optical cavity, so that the effective optical path of the laser beam reaches a preset range; the CH4 optical analysis module measures the concentration of methane in the sample gas by detecting the light intensity change of the laser beam after the laser beam passes through the optical cavity containing the sample gas. According to the scheme, the methane emission condition of the open pit coal mine can be accurately monitored.

The invention discloses a coal face upper corner gas block extraction system which comprises an advancing mechanism, an extraction mechanism and a control mechanism. The extraction mechanism realizes goaf state monitoring and gas extraction; and the control mechanism controls the received signal to perform data analysis and processing, and reasonably issues an extraction instruction. The invention further discloses a coal face upper corner gas block extraction method. The method comprises the steps that coal face goaf extraction parameters are determined; installing an extraction system on site; starting each electric appliance part; completing information collection and processing to obtain an analysis result; a related action instruction is given according to the analysis result, adjustment of the extraction position is completed, and then gas extraction of the current area is completed; when the gas concentration of the goaf meets the safety standard, it is confirmed that extraction is completed. The invention belongs to the technical field of coal mine gas extraction and solves the problems that existing extraction equipment is unreasonable in structure and cannot extract gas in time.

The invention relates to the technical field of coal mine gas concentration prediction, in particular to a coal mine gas concentration time sequence prediction method and system based on LSTM. The method comprises the following steps: collecting multi-source data such as a mining machine pose time sequence, a micro-seismic monitoring event sequence and roadway environment monitoring, constructing a damage-permeability evolution equation by combining geological information, inverting a coal-rock mass dynamic stress damage field, calculating a gas dynamic permeability field and a gushing source intensity field, and finally predicting the gushing source intensity field by combining a space-time prediction model with historical data. And predicting future gas concentration distribution. And real-time space positioning of the coal mine gas emission source is realized.

The invention relates to a coal anisotropy-based cross-layer drilling gas extraction productivity prediction method, which belongs to the technical field of coal mine gas disaster prevention and control, and comprises the following steps: quantifying the sensitivity weight of a permeability main control factor, determining the evolution law of permeability under the action of different effective stresses and coal structures, and determining the permeability evolution law; determining a coal body permeability anisotropy multi-factor response mechanism; establishing a hole periphery effective stress field space function taking a radial distance, a tangential distance and an annular angle as variables, constructing a hole periphery permeability anisotropy space distribution model of the crossing drill hole, and establishing a stress-damage-seepage multi-field coupling mechanism and a permeability anisotropy time-space evolution model of a drill hole unloading area; and analyzing inter-hole interference characteristics of a plurality of cross-layer drilling extraction gas migration flow fields, a cross-layer drilling group extraction interference effect and a bedding seepage control productivity prediction model, clarifying a scale effect of a group hole topological structure and a productivity marginal decline rule, and constructing a three-dimensional cross-layer drilling group extraction productivity prediction model controlled in a bedding direction.

The invention provides a large model and retrieval enhanced intelligent gas risk studying, judging and handling method and device.The method comprises the steps that a gas over-limit alarm semantic description text is obtained, and structured risk elements are extracted through a large language model subjected to instruction fine adjustment; mapping the risk elements into standard terms based on a gas over-limit risk standardized ontology model; executing multi-dimensional weighted retrieval in the coal mine safety domain knowledge base according to a standardized result, calculating a comprehensive correlation score by combining semantics, ontology, regulations, cases and trend consistency, and screening knowledge fragments; and finally, constructing a scenario semantic context, driving the large language model to perform causal reasoning and generating a risk disposal strategy. Through ontology standardization and a multi-dimensional retrieval mechanism, the problems of insufficient specialty and illusion of a general model are solved, accurate study and judgment and scientific disposal of the coal mine gas risk are realized, and it is ensured that the finally generated risk disposal strategy has a clear regulation source and data support.

The invention discloses a coal mine methane emission estimation method based on backward Lagrange random particle simulation. The method comprises the following steps: S1, acquiring satellite methane concentration monitoring data, meteorological data, EDGAR emission list data and GFEI global fuel development emission list data of a research area; s2, selecting a pixel as an observation point, obtaining an influence factor of methane emission of a virtual emission point pixel on the methane concentration of the observation point pixel through a backward Lagrangian random particle simulation model by utilizing meteorological data to reversely track the motion trail of particles, and constructing a source receptor matrix according to the influence factor; s3, the Bayesian methane emission estimation model carries out observation and prior constraint based on the objective function to obtain posterior emission data of the research area. According to the method, the source receptor matrix is constructed by using the motion trail of the meteorological data reverse tracking particles, and the Bayesian methane emission estimation model performs observation and prior constraint based on the target function to obtain posterior emission data of the research area, so that high-precision methane emission inversion estimation of the coal mine in the research area is realized.

The invention provides a coal mine gas risk virtual deduction early warning method and system based on multi-source information fusion, and belongs to the technical field of gas risk early warning. The method comprises the steps that firstly, geological, mining and environment multi-source data are collected, and after preprocessing and feature extraction, high-dimensional risk feature vectors are fused and constructed; then, the vector is used for driving a virtual working face system containing mining, ventilation and gas emission intelligent agents to perform evolution, a Monte Carlo tree search algorithm is used for prospectively deducing a future multi-step state, and the risk entropy of each path is calculated; and finally, generating a dynamic risk probability graph based on a deduction result, and solving a Pareto optimal decision set giving consideration to safety, efficiency and economy through multi-objective optimization. According to the method, the conversion of the gas risk from passive monitoring to active early warning is realized, the problem of early warning hysteresis is effectively solved, and advanced and accurate scientific decision support is provided for gas disaster prevention and control through risk visualization and spatial positioning.

A high-position drilling and coal mining face gas extraction-treatment dynamic collaborative prediction method belongs to the technical field of coal mine gas extraction and treatment, and comprises the following steps: firstly, screening out physical parameters influencing a goaf gas extraction effect and an upper corner gas treatment effect according to a porous medium multi-field coupling theory and a field actual working condition; corresponding parameters are collected in real time to form a time sequence data set; and secondly, multivariable input and multivariable collaborative prediction are carried out by adopting a mixed LSTM-Transform method, and an online learning module is adopted, so that the dynamic capture capability of a complex multivariable time sequence mode in an underground coal mine is remarkably improved, and extraction-treatment dynamic collaborative prediction is carried out on high-position drilling and coal mining surface gas. According to the method, the gas extraction effect and the accuracy, stability and real-time performance of upper corner gas result prediction can be effectively improved, meanwhile, optimization of gas extraction pressure parameters can be achieved, and reference is provided for the high-position drilling gas extraction technology.

The invention discloses a coal mine gas cloud contour infrared spectrum inversion method. The method comprises the following steps: 1, simulating an underground gas cloud formation environment; 2, acquiring infrared image data containing gas cloud by using an infrared spectrum detection device; step 3, carrying out de-noising processing on the infrared image data; 4, performing temperature drift correction and radiation calibration on the denoised infrared image, and converting a DN value into radiation brightness; 5, based on the multi-frame de-noised image, performing target detection and contour extraction on the gas cloud by using a Methane-YOLO model, performing multi-view geometric matching of feature points, performing adjustment optimization of three-dimensional coordinates in combination with a bundle method, generating a point cloud model, and reconstructing a curved surface; 6, based on the three-layer radiation transmission model and the Lambert-Beer law, inverting the gas concentration; and step 7, based on the CEEMDAN-VMD secondary decomposition and CNN-LSTM hybrid network, carrying out joint training on the space contour and time sequence data, and carrying out three-dimensional space concentration distribution prediction.

The invention discloses a fractured zone gas extraction technology optimization method based on absolute gas emission amount, and relates to the technical field of coal mine gas extraction, and the method comprises the following specific steps: constructing a coal seam mining three-dimensional stratum model, reproducing a coal seam excavation overlying strata fracture dynamic development process, representing an overlying strata void ratio spatio-temporal evolution law by using an image processing technology, and obtaining a fractured zone gas extraction result. Obtaining an overlying strata void ratio distribution function; the permeability distribution is deduced, the gas emission amount of the working face is calculated, the gas seepage process in a fracture network is simulated, and a fractured zone gas control targeted area is delineated; a linkage control rule of extraction technical parameters on gas emission, migration and distribution is disclosed, and a fissure zone gas extraction technical library is constructed; and defining an absolute gas emission critical threshold applicable to the extraction technology, constructing a multi-factor hierarchical extraction technology optimization judgment criterion taking the absolute gas amount as a core and considering an occurrence mode, a coal mining method and a ventilation mode, and further providing an adaptive extraction technical scheme and a parameter optimization suggestion for a specific working face. According to the method, differentiated treatment of gas emission of the working face is achieved, the coal mine gas extraction effect is effectively improved, and a reference basis is provided for selecting a gas extraction technology according to local conditions.

1. Name of the designed product: coal mine gas extraction pipe elbow (series appearance). 2. Use of the designed product: used for the flow direction change of gas in the pipeline. 3. Design points of the designed product: in shape. 4. Picture or photo that best shows the design points: design 1 perspective view. 5. Design 1 is designated as the basic design.

The invention discloses a gas extraction and roadway environment parameter collaborative prediction system and method, belongs to the technical field of coal mine gas extraction and safety monitoring, and aims at improving the precision and accuracy of gas concentration prediction and improving the working face gas extraction efficiency and safety. The system comprises a wind speed acquisition system, a fire beam tube monitoring system, a high-position drilling gas extraction monitoring system, a corner gas concentration monitoring system, a PLC (programmable logic controller) and a computer. A partial differential physical equation and related information of boundary conditions and initial value conditions of the partial differential physical equation are integrated into a loss function of a full-connection neural network, a neural network model approaching a partial differential equation solution is obtained through learning, a mapping relation between gas extraction parameters and extraction effects is established, flow characteristics of gas in a coal mine tunnel are accurately simulated and predicted, and the gas extraction efficiency is improved. And gas over-limit early warning can be carried out, so that a guarantee is provided for safe production of a stope face.

The invention discloses a method and a device for determining the gas content of a coal body by using tunneling face gas emission parameter inversion, and relates to the technical field of coal mine gas detection and safety. The method comprises the following steps: acquiring gas concentration, wind speed, roadway section parameters, geological parameters and environmental parameters of a tunneling face through a multi-parameter dynamic acquisition system; on the basis of the collected parameters, gas emission quantity characteristic values are calculated according to drilling operation shifts and non-drilling operation shifts through a dynamic inversion algorithm, and the gas content of the coal body in the current area is inversed; a coal sample is collected through an underground one-stop measuring system, the accurate gas content is measured, and parameters of a dynamic inversion algorithm are optimized; and inputting the multi-source data into an intelligent inversion and early warning system to obtain a predicted value of the gas content in front of the tunneling face and a gas outburst risk level, and adjusting the acquisition frequency and an inversion model. A measurement closed loop is formed, the measurement accuracy and timeliness of the gas content are improved, and the safety of coal mine tunneling operation is guaranteed.

The invention relates to the technical field of coal mine security and protection, in particular to a coal mine gas detection and early warning intelligent control system based on the 5G communication technology. The invention aims to provide a coal mine gas detection and early warning intelligent control system based on a 5G communication technology in order to overcome the defects existing in an existing coal mine underground working face coal mine gas detection and control system. The system is suitable for effectively detecting the concentration of the combustible gas on the working face in the coal mining process, accurately, intelligently and quickly reducing the concentration of the combustible gas exceeding the set concentration, and transmitting the real-time concentration of each detection point on the working face to the central control system for display. The gas detector can conveniently and directly check the gas concentration of each gas detection point in a monitoring room, time and labor are saved, the safety is good, and the gas detector is convenient to popularize and use. And life and property safety of workers on the mine working face is guaranteed.

The invention relates to the technical field of coal mine gas geological disaster prevention and control and intelligent identification, and discloses an underground coal mine gas geological abnormal body intelligent identification and grading early warning method and system, and the method comprises the steps: S1, collecting multi-source heterogeneous monitoring data in an underground coal mine target region, and carrying out the standardization processing and time-space reference unification; s2, constructing a multi-dimensional feature fingerprint database based on a historical or accumulated standardized data set; s3, acquiring real-time multi-source monitoring data for the current tunneling process or detection process, and extracting features of the real-time multi-source monitoring data; based on the multi-dimensional feature fingerprint database, adopting an evidence theory to carry out fusion calculation on a plurality of extracted real-time feature evidences to obtain a comprehensive confidence identification result of a specific type of gas geology anomalous body existing in a front unrevealed area; and S4, generating graded early warning information according to the comprehensive confidence identification result and a preset risk grade threshold. According to the invention, advanced identification, risk assessment and targeted early warning of geological disasters such as underground gas outburst are realized.

The invention discloses a large-dip-angle coal seam group coal roadway strip advanced fracturing and gas extraction method, and relates to the technical field of coal mine gas extraction. The method comprises the following steps: arranging a crossing hydraulic fracturing drill hole in an overlying first coal seam roadway to form an anti-reflection crack; a directional long drill hole of the coal seam is formed in the position of a to-be-tunneled roadway of the underlying coal seam, and strip advanced fracturing is formed based on the fracture extending direction; and ordered connection of drilling construction, gas pre-pumping, roadway tunneling and simultaneous tunneling and pumping is realized through closed-loop operation. The drilling distance, the hole sealing length and the pump injection parameters are optimized, the gas extraction period is remarkably shortened, the coal wall gas emission amount is reduced, and the tunneling efficiency is improved. According to the method, the problems of low gas extraction efficiency and high safety risk of the large-dip-angle coal seam group are effectively solved through a combination mode of gas extraction and strip advanced fracturing, the method is suitable for various coal seam conditions, and the safety and sustainability of coal mine production are remarkably improved.

The invention relates to the technical field of coal mine gas control and CO2 geological storage, and particularly discloses a soft coal seam dynamic fracture self-adaptive CO2 displacement-anti-reflection integrated system which comprises a dynamic fracture monitoring unit, a CO2 collaborative anti-reflection unit, a self-adaptive regulation and control unit and a safety protection unit. The dynamic fracture monitoring unit is used for capturing coal seam fracture development dynamics and gas injection process parameters in real time; the self-adaptive regulation and control unit is in communication connection with the dynamic fracture monitoring unit, and the CO2 synergistic anti-reflection unit is in control connection with the self-adaptive regulation and control unit and is used for realizing CO2 enhanced anti-reflection displacement; the safety protection unit is used for guaranteeing system operation safety. According to the method, real-time adaptation of the coal seam fracture state and the injection-production parameters is achieved, the problems that in a traditional fixed parameter mode, the displacement efficiency attenuation is fast, and the coal body stability is poor are solved, the CH4 recovery rate and the CO2 storage rate are increased, and the safety and high efficiency of soft coal seam gas control operation are guaranteed.

The invention discloses a coal seam gas nitrogen injection flow-increasing enhanced extraction effect evaluation method, which realizes accurate quantitative evaluation of a nitrogen injection displacement effect through a method of combining standard displacement efficiency experimental determination and actual displacement efficiency dynamic calculation. The problem that the nitrogen injection flow increasing effect cannot be objectively evaluated and dynamically optimized in the prior art is effectively solved; through a displacement range determination method and a multi-parameter real-time monitoring mechanism aiming at different mine geological conditions, the environmental adaptability of the evaluation system is remarkably improved; by combining a closed-loop optimization strategy constructed by a deep learning model, nitrogen injection parameters can be automatically adjusted and the extraction trend can be predicted according to real-time data, the gas extraction efficiency is improved while safe production of a mine is guaranteed, the nitrogen injection operation cost is reduced, and efficient and reliable technical support is provided for comprehensive treatment of coal mine gas.

The invention relates to a coal mine gas inspection collaborative decision-making system and method based on multi-agent reinforcement learning, and belongs to the field of coal mine safety informatization. According to the system, gas concentration in a roadway and roadway structure parameters are collected in real time through a sensor by utilizing an inspection robot; the edge computing layer performs data processing and analysis by using an improved MADDPG algorithm framework to realize dynamic task allocation; the digital twinning system evaluates an environmental risk coefficient by using a grey correlation analysis module, performs dynamic path planning based on a roadway three-dimensional digital twinning model, and constructs a three-dimensional dynamic gas diffusion prediction model based on an LSTM network; and decision execution and feedback: distributing a decision result to the inspection robot for execution, and correcting the pose and environmental parameters of the robot in real time through Kalman filtering. According to the method, gas monitoring can be automatically completed under complex geological conditions, the method has good adaptability and predictive capacity, and the coal mine gas inspection efficiency and accuracy are improved.

The present application belongs to the field of coal mine safety and coal gas utilization, and discloses a gas mixing control system for preventing freezing of a gas heat accumulation and oxidation shaft, which comprises a mixing device, a gas flow regulating valve, a mixed gas concentration measuring sensor and a controller. The mixed gas concentration measuring sensor is provided as at least two, and the control concentration value used by the controller is obtained by taking the arithmetic mean of the measured values of each mixed gas concentration measuring sensor. The control system uses the concentration difference between the upper and lower limits of the mixed gas concentration as a buffer zone, and continuously adjusts the opening of the low-concentration gas flow regulating valve at a certain frequency based on the mixed gas concentration monitoring value within a set time period, so that the mixed gas concentration is smoothly adjusted to the set operating target value. The present application also relates to a gas mixing control method.

The invention provides a method and system for quantitatively analyzing a coal mine methane emission reduction treatment policy, and relates to the technical field of data mining and informatization planning, and the method comprises the steps: obtaining text data of the coal mine methane emission reduction treatment policy; calling a large language model to analyze the policy text data, and extracting structured policy element evaluation in the policy text data to generate corresponding quantitative evaluation information; the quantitative evaluation information and the multi-source monitoring data of the coal mine methane are subjected to space-time alignment matching, a policy-monitoring associated data set is generated, and the policy-monitoring associated data set is used for driving or verifying a quantitative evaluation technical model of coal mine methane emission. By applying the scheme, quantitative analysis of the coal mine methane emission reduction governance policy can be objectively and efficiently realized, and accurate mapping and dynamic association between policy semantic information and objective monitoring data are realized.

1. The name of the design product: coal mine gas detection equipment shell (portable). 2. The use of the design product: the design product is used for the shell of coal mine gas detection equipment. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

The invention discloses a coal mine methane leakage early warning method and system based on a wireless sensor network, and relates to the technical field of leakage early warning. The method comprises the following steps: deploying a sparse sensor network in a coal mine area, and constructing a coal mine cloud picture; real-time data of a coal mine area are collected and transmitted back to the central control processor; if the real-time data represents that no leakage exists, but the real-time data is in a metastable critical state, carrying out directional sensing management by calling a mobile sensing component in the sparse sensing network; if the real-time data represents that leakage exists, a leakage verification assembly is triggered, the data are synchronized to a coal mine cloud picture, cloud picture network screening and superposition state definition based on leakage events are carried out, and leakage data are determined and leakage early warning management is carried out based on superposition state collapse of candidate leakage paths by introducing a walking operator. The technical problem that in the prior art, coal mine methane leakage monitoring depends on a fixed sensing point, and the leakage state cannot be dynamically tracked is solved, and the technical effect of coal mine methane leakage dynamic positioning is achieved.

The present application belongs to the technical field of coal mine safety engineering, and particularly relates to a gas extraction blind area detection method and system based on three-dimensional space analysis and intelligent algorithm. The method is based on the secondary development of the AutoCAD platform. The system calls the AutoCAD ActiveX interface through VBA programming, realizes the automatic import of the extraction drilling data and three-dimensional modeling, and adopts the Bezier interpolation algorithm to construct the coal seam model under the influence of gas extraction. The present application realizes the automatic and high-precision detection of the gas extraction blind area, has high detection accuracy, greatly reduces the manual detection error, improves the coal mine gas control efficiency, and provides intelligent technical support for the prevention and control of gas disasters.