Underground coal mine gas control project acceptance method, system, equipment and medium

Abstract

The invention discloses a coal mine underground gas control project acceptance method, system, equipment and medium, and relates to the field of coal mine underground gas project acceptance, the method comprises the following steps: obtaining geological layer parameters of a preset area, the geological layer parameters comprise geological layer structure parameters and gas extraction hole layout parameters, and the preset area comprises a gas extraction hole layout parameter and a gas extraction hole layout parameter; the layout parameters comprise extraction hole positions and extraction hole depths; gas extraction parameters of all the gas extraction holes in the preset area are obtained, and the gas extraction parameters comprise the gas concentration; establishing a three-dimensional space distribution model based on the gas extraction parameters; establishing a three-dimensional geologic model based on the geologic stratum parameters; and fusing the three-dimensional space distribution model and the three-dimensional geologic model to obtain a three-dimensional gas visual model, and realizing acceptance of the coal mine underground gas control project through the three-dimensional gas visual model. The acceptance inspection accuracy is improved, and potential safety hazards are reduced.

Description

Technical Field

[0001] The present application relates to the field of acceptance of underground coal mine gas projects, and in particular to an acceptance method, system, equipment and medium for underground coal mine gas control projects. Background Art

[0002] The underground gas control project in coal mines refers to a project that takes a series of technical and management measures to control and treat underground gas (i.e. methane gas) in order to ensure the life safety of miners and the safe production of mines during coal mining. The gas control project mainly includes gas monitoring, gas extraction, gas emission, ventilation management, gas control and other aspects. Through these measures, the underground gas concentration can be effectively reduced, and the occurrence of gas explosions and gas over-limit accidents can be prevented, thereby ensuring the safe production of coal mines and the life safety of miners. The acceptance of underground gas control projects in coal mines refers to a series of acceptance procedures after the completion of the underground gas control project in coal mines to ensure that the control project meets the predetermined safety standards and effects.

[0003] However, in underground coal mine gas control projects, traditional acceptance methods rely on a large amount of human resources. These acceptance tasks require on-site staff to manually collect, record, analyze and report data. At the same time, they also need to continuously monitor the operating status of the equipment and evaluate the progress of the entire project. This method that relies on manual operation requires workers to stay in the complex underground environment for a long time, greatly increasing safety risks. Summary of the invention

[0004] The purpose of this application is to provide a method, system, equipment and medium for acceptance of underground coal mine gas control projects, which can reduce safety hazards.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a method for accepting an underground coal mine gas control project. The underground coal mine gas control project extracts gas through a gas extraction hole obtained by drilling in a preset area. The underground coal mine gas control project acceptance method includes:

[0007] Acquire geological layer parameters of the preset area, wherein the geological layer parameters include geological layer structure parameters and layout parameters of the gas extraction holes, wherein the layout parameters include extraction hole positions and extraction hole depths;

[0008] Obtaining gas extraction parameters of each of the gas extraction holes in the preset area, wherein the gas extraction parameters include gas concentration;

[0009] Based on the gas extraction parameters, a three-dimensional spatial distribution model is established;

[0010] Based on the geological layer parameters, a three-dimensional geological model is established;

[0011] The three-dimensional spatial distribution model is integrated with the three-dimensional geological model to obtain a three-dimensional gas visualization model, and the acceptance of the coal mine underground gas control project is realized through the three-dimensional gas visualization model.

[0012] In the second aspect, the present application provides an acceptance system for underground coal mine gas control projects. The underground coal mine gas control project extracts gas through gas extraction holes obtained by drilling holes in a preset area. The acceptance system for underground coal mine gas control projects includes:

[0013] A first acquisition module is used to acquire geological layer parameters of the preset area, wherein the geological layer parameters include geological layer structure parameters and layout parameters of the gas extraction holes, wherein the layout parameters include extraction hole positions and extraction hole depths;

[0014] A second acquisition module is used to acquire gas extraction parameters of each gas extraction hole in the preset area, wherein the gas extraction parameters include gas concentration;

[0015] A first establishing module, used for establishing a three-dimensional spatial distribution model based on the gas extraction parameters;

[0016] A second building module is used to build a three-dimensional geological model based on the geological layer parameters;

[0017] A fusion module is used to fuse the three-dimensional spatial distribution model with the three-dimensional geological model to obtain a three-dimensional gas visualization model, and to realize the acceptance of the coal mine underground gas control project through the three-dimensional gas visualization model.

[0018] In a third aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the coal mine underground gas control project acceptance method described in any one of the above.

[0019] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the coal mine underground gas control project acceptance method described in any one of the above.

[0020] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0021] The present application provides a method, system, equipment and medium for acceptance of underground gas control projects in coal mines. The method obtains geological layer parameters of a preset area, wherein the geological layer parameters include geological layer structure parameters and layout parameters of gas extraction holes, wherein the layout parameters include extraction hole positions and extraction hole depths; and obtains gas extraction parameters of each gas extraction hole in the preset area, wherein the gas extraction parameters include gas concentration. Based on the gas extraction parameters, a three-dimensional spatial distribution model is established to achieve visualization of gas distribution. Based on the geological layer parameters, a three-dimensional geological model is established, which provides three-dimensional visualization of the geological structure and realizes an integrated display of gas distribution and geological structure. The three-dimensional spatial distribution model is integrated with the three-dimensional geological model to obtain a three-dimensional gas visualization model. In the present application, the acceptance of the underground gas control project in the coal mine is realized through the three-dimensional gas visualization model, which provides data support for the gas control project and improves the accuracy and efficiency of the acceptance of the gas control project. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0023] Figure 1 This is an application environment diagram of a coal mine underground gas control project acceptance method in one embodiment of the present application;

[0024] Figure 2 A schematic diagram of a flow chart of a method for acceptance of a coal mine underground gas control project provided in one embodiment of the present application;

[0025] Figure 3 A schematic diagram of the functional modules of a coal mine underground gas control project acceptance system provided in one embodiment of the present application;

[0026] Figure 4 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0028] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0029] The coal mine underground gas control project acceptance method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be set up separately, integrated on the server 104, or placed on the cloud or other servers. The terminal 102 can send the geological layer parameters and gas extraction parameters of the preset area to be processed to the server 104, and the server 104 receives the geological layer parameters and gas extraction parameters to be processed. For the geological layer parameters and gas extraction parameters to be processed, the server 104 establishes a three-dimensional spatial distribution model based on the gas extraction parameters, and establishes a three-dimensional geological model based on the geological layer parameters. The three-dimensional spatial distribution model is integrated with the three-dimensional geological model to obtain a three-dimensional gas visualization model.

[0030] The server 104 can feed back the obtained three-dimensional gas visualization model to the terminal 102. In addition, in some embodiments, the coal mine underground gas control project acceptance method can also be implemented by the server 104 or the terminal 102 alone, such as the terminal 102 can directly process the geological layer parameters and gas extraction parameters to be processed, or the server 104 can obtain the geological layer parameters and gas extraction parameters to be processed from the data storage system, and respectively establish a three-dimensional spatial distribution model and a three-dimensional geological model based on the geological layer parameters and gas extraction parameters to be processed, and fuse the three-dimensional spatial distribution model with the three-dimensional geological model to obtain a three-dimensional gas visualization model.

[0031] The terminal 102 may be, but is not limited to, various desktop computers, laptop computers, smart phones, tablet computers, IoT devices, and portable wearable devices. The IoT devices may be smart speakers, smart TVs, smart air conditioners, smart vehicle-mounted devices, etc. The portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers, or may be a cloud server.

[0032] In an exemplary embodiment, Figure 2 As shown, a method for acceptance of coal mine underground gas control projects is provided. The method is executed by a computer device, and can be executed by a computer device such as a terminal or a server alone, or by a terminal and a server together. In the embodiment of the present application, the method is applied to Figure 1The server 104 in the example is used as an example to illustrate the method, which includes the following steps S201 to S205. Among them:

[0033] In step S201, geological layer parameters of a preset area are obtained, wherein the geological layer parameters include geological layer structure parameters and layout parameters of gas extraction holes, wherein the layout parameters include extraction hole positions and extraction hole depths.

[0034] In one embodiment, before obtaining the layout parameters of the gas extraction holes, the coal mine underground gas control project acceptance method further includes the following sub-steps A1-A4:

[0035] A1. Generate a construction progress chart of the extraction holes according to the construction duration and construction progress of each extraction hole;

[0036] Specifically, a corresponding barcode is attached to the identification of each borehole. By scanning the barcode, the azimuth, inclination, opening position and other information of the borehole can be obtained. When gas extraction is carried out, it is usually necessary to construct thousands or even tens of thousands of boreholes. Therefore, the management of extraction boreholes becomes particularly critical. If a barcode is added to the ID card of the underground borehole, the opening position, inclination, depth and other information of the extraction hole can be easily understood through a simple scanning operation. In addition, the construction progress parameter data of the shift can be entered by scanning the code, which is helpful for single-hole management. The underground data APP acquisition module has a human biometric recognition function to verify the identity of the operator and ensure the authenticity and accuracy of the record. The APP supports the "one rod one record" recording method, which can accurately record the construction time of each drill rod, and record the opening position of each borehole by taking pictures as the basis for the original record of underground construction. The underground data APP collection module is used to obtain the construction time, location and depth of each extraction hole. Based on the construction start time and the current time, the construction duration of each extraction hole is calculated. Based on the extraction hole depth and construction duration, the construction progress of each extraction hole is calculated.

[0037] Based on the construction time and hole location data of the drill pipe, the daily, weekly and monthly drilling construction progress is calculated. Then, the gas concentration change and extraction parameter data provided by the barcode drilling management module are used to generate the extraction report of each borehole, covering the single hole life cycle, main and branch pipe extraction and other information. Then, according to the personnel operation data recorded by the underground data APP acquisition module, the attendance report of each construction worker is automatically generated to show the working hours and work tasks of each employee. Finally, according to the material usage information provided by the barcode management module and the underground data APP, the material usage and inventory change report is automatically generated to track the material in and out of the warehouse and the consumption. By automatically calculating the daily, weekly and monthly drilling construction progress, clear construction progress tracking is provided. This real-time progress management helps to adjust the construction plan in time to avoid delays and waste of resources. By accurately recording and analyzing construction data, managers can better understand the construction efficiency and progress of each stage and make more accurate decisions. Automatically generate an attendance report for each construction worker, showing the working hours and work tasks of each employee. This automated personnel management reduces the workload of manual recording and statistics and reduces the error rate. And there is no need to manually calculate and record data, which reduces workload and improves overall work efficiency.

[0038] A2. Calculate the coverage between the extraction holes, identify the uncovered areas, and generate a blank zone distribution map through the uncovered areas;

[0039] A3. Compare the construction progress of each extraction hole with the preset construction progress to identify the extraction holes with abnormal progress;

[0040] A4. Mark potential problem areas through the blank zone distribution map and the extraction holes with abnormal progress, and re-construct the potential problem areas.

[0041] Specifically, according to the construction duration and construction speed of each drainage hole, a construction progress chart of the drainage hole is generated, and the current construction status of each drainage hole is displayed through the construction progress chart. The drainage hole position and drainage hole depth are obtained from the above data as the layout parameters of the gas drainage hole.

[0042] The construction speed formula for each extraction hole is as follows:

[0043]

[0044] Among them, V i represents the construction speed of the ith extraction hole; S i represents the total depth of the ith extraction hole; T i represents the total construction time of the ith extraction hole, T Oik represents the time consumed by the i-th extraction hole for the k-th drilling, with a total of n drillings; F(S i ,Hi ,P i ) represents the resistance function of the extraction hole. The resistance function represents the resistance of the rock formation due to the hardness H during the drilling process. i , total drilling depth S i , Drilling rig performance i Resistance caused by factors; E i Represents the mechanical efficiency of the i-th borehole, and the unit is dimensionless (real number between 0 and 1, 1 represents the highest efficiency). The construction progress chart is used to intuitively display the current construction status of each borehole, which is conducive to the relevant personnel to make quick adjustment decisions, thereby improving the transparency and efficiency of construction management. By tracking the construction time and hole location of each drill rod, the entire construction process can be accurately recorded and analyzed, which helps to reduce human errors and improve construction accuracy.

[0045] Furthermore, the calculation formula for the coverage between the extraction holes is as follows:

[0046]

[0047] Among them, Z * (P) represents the attribute value at the estimated point P, such as gas concentration and rock hardness; Z(P i ) represents a known point P i The attribute value of i Represents the weight coefficient, satisfying n represents the number of known points.

[0048] By calculating the coverage between the extraction holes, identifying the uncovered areas, and generating a blank zone distribution map, the areas in the underground area that are not covered by the extraction holes are displayed, marking the areas that require further construction. Then, according to the construction plan, the construction progress of each borehole is set, and the actual construction progress of each borehole is compared with the preset construction progress to calculate the progress deviation. The progress deviation calculation formula is as follows:

[0049]

[0050] Among them, D i represents the progress deviation of the i-th extraction hole, D i If it is a positive value, it indicates delay, D i If it is a negative value, it means early; T actual,i represents the actual construction time of the i-th extraction hole; T plan,i Represents the expected construction time of the ith extraction hole.

[0051] Calculate the mean of schedule deviation through statistical analysis method Mean The calculation formula is as follows:

[0052]

[0053] Wherein, N represents the total number of extraction holes.

[0054] Standard deviation D The calculation formula is as follows:

[0055]

[0056] By applying statistical analysis methods, boreholes with abnormal progress deviations can be identified, which indicate abnormal conditions in the construction process. By detecting blank zones and progress anomalies in drilling construction and marking potential problem areas, it is helpful to promptly discover potential problems in construction and avoid safety hazards and reduced construction efficiency. By integrating the geographic location and depth of the boreholes into a three-dimensional geological model, the system can accurately identify uncovered areas to ensure comprehensive construction coverage and avoid omissions.

[0057] The geological layer structure parameters are used to describe the physical characteristics and spatial distribution of underground geological bodies. The geological layer structure parameters include but are not limited to rock layer type, rock layer thickness, rock layer dip, rock layer strike and dip, faults and folds, fracture development, permeability, and porosity. Rock layer type refers to the type of rock existing at different depths, such as coal seams, sandstone, shale, etc. Rock layer thickness refers to the thickness of each rock layer in the vertical direction, which helps to understand the relative position between the layers. Rock layer dip refers to the angle of inclination of the rock layer, which indicates the degree of inclination of the rock layer relative to the horizontal plane, affecting the drilling design and construction difficulty. Rock layer strike indicates the direction in which the rock layer extends, and rock layer dip indicates the direction in which the rock layer surface tilts downward. Faults and folds are used to record the fault position and fold morphology in the area. Faults and folds can significantly change the stress state of the underground and affect the gas flow path. Permeability is used to indicate the ability of rock to allow fluid to pass through, which is directly related to whether gas can be effectively extracted from coal seams. Porosity is used to indicate the proportion of pores inside the rock, and porosity affects the gas storage capacity.

[0058] In step S202, the gas extraction parameters of each gas extraction hole in the preset area are obtained, wherein the gas extraction parameters include the gas concentration of the extraction hole;

[0059] Specifically, gas concentration sensors, flow meters and other necessary monitoring equipment are installed in each gas extraction hole to monitor gas concentration and extraction volume in real time. Automated data recording devices or systems, such as PLC (programmable logic controller), are used to automatically record and store data from sensors. A stable and reliable communication network is built to ensure that on-site monitoring equipment can be seamlessly connected to the central control system or cloud server to achieve real-time data transmission. The changes in gas concentration are continuously monitored and recorded through gas concentration sensors installed in the borehole. The sensors should have high sensitivity and fast response characteristics to capture instantaneous changes. The total amount of gas extracted from each extraction hole is accurately measured using a flow meter. As needed, a volume flow meter or a mass flow meter can be selected, depending on the project requirements. The start and end time of each extraction operation is automatically recorded to calculate the total extraction time. This can be done through a timer integrated into the extraction system or automatically by the control system. The collected raw data is preprocessed to remove outliers and noise interference to ensure data quality. Data from different sources (such as concentration, flow, time, etc.) are integrated together to form a unified data set for subsequent analysis.

[0060] In step S203, a three-dimensional spatial distribution model is established based on the gas extraction parameters;

[0061] In one embodiment, step S203 includes the following sub-steps S2031-S2032:

[0062] S2031. Establishing a three-dimensional space grid based on geological layer parameters, wherein the three-dimensional space grid includes a plurality of grid nodes;

[0063] S2032. Calculate the grid point gas concentration at multiple grid nodes, interpolate the grid point gas concentration value to each grid node of the three-dimensional space grid, and obtain a three-dimensional space distribution model. The three-dimensional space distribution model is used to represent the change of gas concentration with the position of the geological layer.

[0064] Specifically, a three-dimensional spatial grid model is established, which represents the preset area underground in the coal mine. This network can be a regular cubic network, or the network size and shape can be adjusted according to specific needs. The position of each grid node can be represented by a three-dimensional coordinate (x, y, z). For each grid node in this three-dimensional grid, the gas concentration value at the node will be calculated based on the distance to the adjacent gas concentration extraction hole and the corresponding weight through an interpolation algorithm. The interpolation algorithm can choose the inverse distance weighted method or the Kriging interpolation method. The algorithm can comprehensively consider the extraction hole data and the node position relationship.

[0065] For example, the inverse distance weighted method is used to calculate the gas concentration value at the node, and the calculation formula is as follows:

[0066]

[0067] Where C(x, y, z) represents the predicted value of gas concentration at the grid node (x, y, z), and C i represents the gas concentration value of the i-th extraction hole; d i It represents the spatial distance from the ith drainage hole to the target node; p represents the weight index of the distance, which is usually 2; n represents the number of adjacent gas drainage holes.

[0068] After calculating the gas concentration value of each grid node, the gas concentration data collected at different time points are applied to each node of the entire three-dimensional grid through the interpolation method. In this way, the change of gas concentration at different times with the position of the formation is displayed in the form of a time series, thus providing intuitive data support for coal mine safety monitoring.

[0069] In one embodiment, the coal mine underground gas control project acceptance method further includes the following steps:

[0070] S206, obtaining real-time gas concentration data;

[0071] S207, mapping the real-time gas concentration data to the grid nodes of the three-dimensional space grid;

[0072] S208. For each of the grid nodes, calculate the difference between the predicted gas concentration and the actual gas concentration;

[0073] S209. Evaluate the accuracy of the three-dimensional spatial distribution model based on the difference value.

[0074] Specifically, for each grid node, calculate its gas concentration prediction value C pred With the actual value C real The difference value D between them is calculated as follows:

[0075] D=|C pred -C real |;

[0076] The accuracy of the model is evaluated by calculating the mean and standard deviation of the difference values ​​of all grid nodes and the error between the predicted value and the actual value (such as mean square error MSE). A threshold alarm mechanism is set to issue an alarm when the difference value of some nodes exceeds the preset value to prevent accidents.

[0077] In step S204, a three-dimensional geological model is established based on the geological layer parameters.

[0078] In one embodiment, step S204 includes the following sub-steps S2041-S2044:

[0079] S2041. Establishing a stratigraphic sequence table based on geological layer parameters;

[0080] S2042. Identify complex geological body data based on geological layer parameters;

[0081] S2043, generating a three-dimensional geometric unit of a complex geological body according to the complex geological body data;

[0082] S2044. Based on the stratigraphic sequence table, the three-dimensional geometric units of the complex geological body are gradually expanded outward to simple geological units until the entire preset area is covered, thereby establishing a three-dimensional geological model.

[0083] Specifically, geological layer parameters include geological layer structural parameters and gas extraction hole layout parameters. Based on geological attributes such as rock type, mineral composition, faults, and folds, statistical analysis or machine learning algorithms are used to screen out potential complex geological bodies. The spatial position and geometric morphology of complex geological bodies are reconstructed based on borehole data and geological profiles. The boundary characteristics, internal structure and relationship of complex geological bodies with other geological units are analyzed. For undrilled areas, spatial interpolation algorithms such as Kriging and inverse distance weighted methods are used to estimate the boundary position. According to the borehole depth and geological layer thickness, regular three-dimensional grids are generated to accurately represent the depth distribution of complex geological bodies. According to the complex geological body data, three-dimensional geometric units of complex geological bodies are generated. A finer grid size is used inside the complex geological body to capture its complex internal structure; while the grid spacing can be appropriately relaxed in the periphery. The grid density is automatically adjusted according to the irregularity of the geological body to ensure that the model can reflect details without being too complex. The outer surface of the complex geological body is generated using a triangulated network. Fill the internal space to create a complete three-dimensional geometric morphology. Assign corresponding geological attributes to each grid node, such as rock type, gas concentration, etc., and compare the generated three-dimensional geometric units of complex geological bodies with actual observation data to verify the accuracy of the model. Start with the most complex geological body and gradually expand to the surrounding simpler geological units to ensure the consistency and logic of the model. According to the depositional order in the stratigraphic sequence table, expand the model in sequence, build it layer by layer from the bottom to ensure that the layers are clear and in line with the actual geological laws. Starting from the most complex geological body at the bottom, gradually expand the model upward until all known stratigraphic units are covered. Perform appropriate smoothing between layers to eliminate possible mutations or discontinuities. Ensure that the boundaries between complex geological bodies and surrounding stratigraphic units are seamlessly connected to avoid dislocation or overlap. Integrate the stratigraphic units and complex geological body models into a complete three-dimensional geological model to ensure that there are no omissions or duplications.

[0084] In one embodiment, step S2041 includes the following sub-steps B1-B4:

[0085] B1. Based on geological layer parameters, the geological layers are preliminarily divided to obtain a preliminary geological framework, and the relative positions and levels of the geological layers are determined through the preliminary geological framework;

[0086] B2, arranging the geological layers in the preliminary geological framework in the order of deposition time to establish a stratigraphic sequence framework;

[0087] B3. Based on the geological layer parameters, obtaining geometric parameters of each geological layer, wherein the geometric parameters include geological layer thickness and geological layer boundary;

[0088] B4. Establish a stratigraphic sequence table based on the stratigraphic sequence framework and geometric parameters of the geological layers.

[0089] Specifically, data from different sources are standardized to ensure that all data can be analyzed and compared in a unified coordinate system. This process includes removing outliers and duplicate records in the data to ensure the accuracy and reliability of the data. According to rock types, structural characteristics and other geological factors, the boundaries between different strata are identified to preliminarily divide the stratigraphic units. I can choose to use radioisotope dating technology or other geochronological methods to determine the relative chronological order of the formation of each layer. After the chronological order is determined, a suitable datum is selected as a reference point. This datum can be the elevation of the ground or a specific depth. The location and properties of each rock layer are constructed in order from shallow to deep, thus forming a preliminary stratigraphic sequence map. Next to each layer, the specific geological parameters are detailed and a brief explanatory text is attached to facilitate understanding and analysis. In addition, fault lines and fold symbols are inserted at appropriate locations to intuitively display the characteristics of geological structures. For those special geological phenomena, such as caves and mud intrusions, special annotations need to be made at the corresponding levels to ensure that these important information will not be overlooked.

[0090] In step S205, the three-dimensional spatial distribution model is integrated with the three-dimensional geological model to obtain a three-dimensional gas visualization model, and the acceptance of the coal mine underground gas control project is realized through the three-dimensional gas visualization model.

[0091] In one embodiment, the above step S205 includes the following sub-steps:

[0092] S2051. Establishing a feature vector based on the grid node, the feature vector includes three-dimensional coordinates, gas concentration data and geological layer attributes, and the grid point corresponds to the gas extraction hole;

[0093] S2052, establishing a three-dimensional feature matrix based on all feature vectors of the preset area;

[0094] S2053. Input the three-dimensional feature matrix into the deep learning model, train the deep learning model, and obtain a three-dimensional gas visualization model.

[0095] Specifically, the entire preset area is divided into regular three-dimensional grids according to the geological structure characteristics of the mine and the layout of the boreholes. This division method ensures that each grid unit has clear spatial coordinates (x, y, z), thereby giving each grid node its precise position (x, y, z) in three-dimensional space, and these coordinate values ​​are used as part of the feature vector. By using sensors or other monitoring equipment, real-time or historical gas concentration data corresponding to each grid node can be obtained. In order to further enhance the information content of the feature vector, the corresponding geological layer attributes are assigned to each grid node in combination with the stratigraphic sequence table. These attributes include rock type, permeability, porosity, etc., providing detailed information about the geological structure, thereby enriching the content of the characteristic phase. In order to ensure the authenticity and representativeness of the data, the data of each grid node comes from the nearest gas extraction hole, which means that there is an accurate correspondence between the grid node and the actual gas extraction hole. By collecting the feature vectors of all grid nodes, a complete data set is formed. These feature vectors are arranged in spatial order to construct a three-dimensional feature matrix, in which each row represents a grid node and each column represents a feature, such as x-coordinate, y-coordinate, z-coordinate, gas concentration, geological layer attributes, etc. For those grid nodes that are not directly measured, spatial interpolation algorithms such as Kriging and inverse distance weighted method are used to estimate their eigenvalues ​​to fill in the data gaps. If the feature dimension is high, dimensionality reduction techniques such as principal component analysis (PCA) may be used to reduce redundant information and improve the efficiency of model training. The three-dimensional feature matrix is ​​divided into training set, validation set and test set, usually in a ratio of 70%:15%:15%, which can be adjusted appropriately according to the actual amount of data.

[0096] In one embodiment, the above step S2053 includes the following sub-steps C1-C4:

[0097] C1. Inputting the three-dimensional feature matrix into the input layer to obtain the three-dimensional feature matrix including the initial feature map;

[0098] C2, inputting the three-dimensional feature matrix including the initial feature map into the convolution layer to obtain the three-dimensional feature matrix including the convolution feature map, wherein the convolution feature map extracts local features in the three-dimensional feature matrix through a convolution operation;

[0099] C3, inputting the three-dimensional feature matrix including the convolution feature map into the pooling layer, and obtaining the three-dimensional feature matrix including the pooling feature map by downsampling the convolution feature map;

[0100] C4. Inputting the three-dimensional feature matrix including the pooled feature map into a fully connected layer, mapping the pooled features to an output space through a fully connected operation, and obtaining the three-dimensional gas visualization model.

[0101] Specifically, the three-dimensional feature matrix is ​​converted into a four-dimensional tensor format. This process involves normalizing the data to ensure the consistency and accuracy of the data in subsequent processing. Through the preliminary mapping of the input layer, the original feature information can be effectively retained to form an initial feature map. Multiple 3D filters are defined, and the parameters of these filters include stride and padding to meet different feature extraction requirements. Through convolution operations, local features are extracted from the input data. After these local features are processed, a new three-dimensional feature matrix containing the convolution feature map is generated. In order to further extract key information and reduce the data dimension, the maximum pooling method is selected, and the appropriate pooling window size and stride are set. The convolution feature map is downsampled to generate a new three-dimensional feature matrix. The pooled feature maps in these matrices are more compact while retaining key information, which is very beneficial for subsequent processing. In order to input these feature maps into the fully connected layer, the pooled three-dimensional feature matrix is ​​flattened and converted into a one-dimensional vector (Flattening). In the fully connected layer, the pooled features are mapped to the output space through the application of linear transformation and activation function, realizing the transformation from low-level features to high-level semantic features. Based on the output of the fully connected layer, a complete three-dimensional gas visualization model is constructed, which can not only intuitively display the gas concentration distribution at various locations in the mining area or underground structure, but also provide strong technical support for gas monitoring and safety management.

[0102] Based on the same inventive concept, the embodiment of the present application also provides a system for implementing the above-mentioned coal mine underground gas control project acceptance. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above-mentioned method, so the specific limitations in one or more embodiments of the coal mine underground gas control project acceptance system provided below can refer to the limitations of the coal mine underground gas control project acceptance method above, and will not be repeated here.

[0103] In an exemplary embodiment, Figure 3 As shown, a coal mine underground gas control project acceptance system is provided, including:

[0104] A first acquisition module 410 is used to acquire geological layer parameters of the preset area, wherein the geological layer parameters include geological layer structure parameters and layout parameters of gas extraction holes, wherein the layout parameters include extraction hole positions and extraction hole depths;

[0105] A second acquisition module 420 is used to acquire gas extraction parameters of each gas extraction hole in the preset area, wherein the gas extraction parameters include gas concentration;

[0106] A first establishing module 430, for establishing a three-dimensional spatial distribution model based on the gas extraction parameters;

[0107] A second building module 440 is used to build a three-dimensional geological model based on the geological layer parameters;

[0108] The fusion module 450 is used to fuse the three-dimensional spatial distribution model with the three-dimensional geological model to obtain a three-dimensional gas visualization model, and to realize the acceptance of the coal mine underground gas control project through the three-dimensional gas visualization model.

[0109] As an optional implementation, the first establishing module 430 includes:

[0110] A second establishing module is used to establish a three-dimensional space grid based on the geological layer parameters, wherein the three-dimensional space grid includes a plurality of grid nodes;

[0111] An interpolation module is used to calculate the gas concentration values ​​at multiple grid nodes, and interpolate the gas concentration values ​​to each grid node of the three-dimensional space grid to obtain a three-dimensional space distribution model, which represents the change of gas concentration with the position of the geological layer.

[0112] As an optional implementation method, the coal mine underground gas control project acceptance system also includes:

[0113] The third acquisition module is used to obtain real-time gas concentration data;

[0114] A mapping module, used for mapping the real-time gas concentration data to the grid nodes of the three-dimensional space grid;

[0115] A calculation module, used for calculating the difference between the predicted value of gas concentration and the actual value of gas concentration for each grid node;

[0116] An evaluation module is used to evaluate the accuracy of the three-dimensional spatial distribution model based on the difference value.

[0117] As an optional implementation, the second establishing module 440 includes:

[0118] A third establishing module is used to establish a stratigraphic sequence table based on the geological layer parameters;

[0119] An identification module, used for identifying complex geological body data based on the geological layer parameters;

[0120] A generating module, used for generating a three-dimensional geometric unit of a complex geological body according to the complex geological body data;

[0121] The expansion module is used to gradually expand the three-dimensional geometric units of the complex geological body to simple geological units based on the stratigraphic sequence table until the entire preset area is covered, thereby establishing a three-dimensional geological model.

[0122] As an optional implementation, the third establishment module includes:

[0123] A preliminary division module is used to perform preliminary division of the geological layer based on the geological layer parameters to obtain a preliminary geological framework, and determine the relative position and level of each geological layer through the preliminary geological framework;

[0124] An arrangement module, used to arrange the geological layers in the preliminary geological framework in the order of deposition time to establish a stratigraphic sequence framework;

[0125] An obtaining module, used for obtaining geometric parameters of each of the geological layers based on the geological layer parameters, wherein the geometric parameters include geological layer thickness and geological layer boundary;

[0126] The fourth establishing module is used to establish a stratigraphic sequence table based on the stratigraphic sequence framework and the geometric parameters of the geological layer.

[0127] As an optional implementation, the fusion module 450 includes:

[0128] A fifth establishing module, for establishing a feature vector based on the grid node, the feature vector including three-dimensional coordinates, gas concentration data and geological layer attributes, the grid point corresponding to the gas extraction hole;

[0129] A sixth establishing module, used for establishing a three-dimensional feature matrix based on all the feature vectors of the preset area;

[0130] A training module is used to input the three-dimensional feature matrix into a deep learning model, train the deep learning model, and obtain the three-dimensional gas visualization model.

[0131] As an optional implementation, the training module includes:

[0132] A first input module, used for inputting the three-dimensional feature matrix into the input layer to obtain the three-dimensional feature matrix including an initial feature map;

[0133] A second input module is used to input the three-dimensional feature matrix including the initial feature map into the convolution layer to obtain the three-dimensional feature matrix including the convolution feature map, wherein the convolution feature map extracts local features in the three-dimensional feature matrix through a convolution operation;

[0134] A third input module is used to input the three-dimensional feature matrix including the convolution feature map into the pooling layer, and obtain the three-dimensional feature matrix including the pooling feature map by downsampling the convolution feature map;

[0135] The fourth input module is used to input the three-dimensional feature matrix including the pooled feature map into the fully connected layer, map the pooled feature to the output space through a fully connected operation, and obtain the three-dimensional gas visualization model.

[0136] As an optional implementation method, the coal mine underground gas control project acceptance system also includes:

[0137] The report generation module is used to automatically generate construction progress reports, sampling reports, personnel attendance and material usage reports based on the data provided by the underground data APP collection module and barcodes.

[0138] Specifically, the gas control project construction project will have daily, weekly and monthly progress reports based on the progress of drilling construction, single-hole life cycle reports and extraction reports based on the gas extraction situation, personnel attendance and management reports based on the personnel situation, and relevant material reports based on the material warehousing and usage. After this series of reports has realized the automatic generation function, it can not only save the manpower cost of the project department, but also grasp the construction situation of the project in real time.

[0139] As an optional implementation method, the coal mine underground gas control project acceptance system also includes:

[0140] The employee management module is used to handle the onboarding procedures for new employees according to the preset standardized process.

[0141] Specifically, the connection between the employee management module and the mobile APP ensures that all employee information and processes can be synchronized in real time, reducing delays and errors in information transmission. The process includes filling in personal information, uploading relevant certificates, signing necessary contracts and security agreements, etc. At the same time, the employee management module automatically generates a digital file for each new employee. When an employee resigns, the employee management module will handle the resignation procedures according to the preset process, including inventorying and returning equipment, terminating permissions, and canceling accounts. The system transfers the employee's file from the active state to the resignation archive and retains it for a certain period of time for reference. After the new employee joins the company, the employee management module will automatically generate and send the login token of the mobile APP. When the employee resigns, the employee management module will automatically cancel the login token of his mobile APP. The system automatically generates a digital file for each new employee, reducing the workload and error rate of manual entry, and ensuring the integrity and accuracy of employee information.

[0142] As an optional implementation method, the coal mine underground gas control project acceptance system also includes:

[0143] The material and logistics management module is used to determine whether materials need to be replenished.

[0144] Specifically, the current inventory status is obtained and the equipment usage, location and status information is obtained from the barcode drilling management module. By comparing the current material inventory with the preset safety inventory threshold, the system can accurately determine whether materials need to be replenished to avoid insufficient inventory affecting the construction progress. Inventory materials include but are not limited to office supplies and labor protection supplies.

[0145] As an optional implementation method, the coal mine underground gas control project acceptance system also includes:

[0146] The automatic warning module is used to compare the received analysis results with the warning rules to send a warning signal.

[0147] Specifically, the automatic warning module notifies relevant personnel through one or more of SMS, email, sound alarm or visual display. By setting warning rules based on historical data, the system can learn and draw on past experience, establish warning standards that are more in line with actual conditions, and improve the accuracy and effectiveness of warnings.

[0148] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store geological layer parameters and gas extraction parameters. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for accepting a coal mine underground gas control project is implemented.

[0149] Those skilled in the art will understand that Figure 4The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0150] In an exemplary embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0151] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0152] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0153] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0154] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0155] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0156] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0157] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for acceptance of underground coal mine gas control projects, characterized in that: The acceptance method of underground coal mine gas control project includes: Acquire geological layer parameters of a preset area, wherein the geological layer parameters include geological layer structure parameters and layout parameters of gas extraction holes, wherein the layout parameters include extraction hole positions and extraction hole depths; Obtaining gas extraction parameters of each gas extraction hole in the preset area, wherein the gas extraction parameters include gas concentration of the extraction hole; Based on the gas extraction parameters, a three-dimensional spatial distribution model is established; Based on the geological layer parameters, a three-dimensional geological model is established; The three-dimensional spatial distribution model is integrated with the three-dimensional geological model to obtain a three-dimensional gas visualization model, and the acceptance of the coal mine underground gas control project is realized through the three-dimensional gas visualization model.

2. The method for acceptance of underground coal mine gas control project according to claim 1, characterized in that: The three-dimensional spatial distribution model is established based on the gas extraction parameters, including: Based on the geological layer parameters, a three-dimensional space grid is established, wherein the three-dimensional space grid includes a plurality of grid nodes; Calculate the grid point gas concentration at multiple grid nodes, interpolate the grid point gas concentration to each grid node of the three-dimensional space grid, and obtain the three-dimensional space distribution model, which is used to represent the change of gas concentration with the position of the geological layer.

3. The method for acceptance of underground coal mine gas control project according to claim 2, characterized in that: The coal mine underground gas control project acceptance method also includes: Obtain real-time gas concentration data; Mapping the real-time gas concentration data to the grid nodes of the three-dimensional space grid; For each of the grid nodes, calculating the difference between the predicted value of gas concentration and the actual value of gas concentration; The accuracy of the three-dimensional spatial distribution model is evaluated based on the difference value.

4. The method for acceptance of underground coal mine gas control project according to claim 1, characterized in that: The step of establishing a three-dimensional geological model based on the geological layer parameters includes: Based on the geological layer parameters, a stratigraphic sequence table is established; Based on the geological layer parameters, identifying complex geological body data; Generating a three-dimensional geometric unit of a complex geological body according to the complex geological body data; Based on the stratigraphic sequence table, the three-dimensional geometric units of the complex geological body are gradually expanded outward to simple geological units until the entire preset area is covered, thereby establishing the three-dimensional geological model.

5. The method for acceptance of underground coal mine gas control project according to claim 4, characterized in that: The step of establishing a stratigraphic sequence table based on the geological layer parameters comprises: Based on the geological layer parameters, the geological layer is preliminarily divided to obtain a preliminary geological framework, and the relative position and level of each geological layer are determined through the preliminary geological framework; Arranging each of the geological layers in the preliminary geological framework in the order of deposition time to establish a stratigraphic sequence framework; Based on the geological layer parameters, geometric parameters of each geological layer are obtained, wherein the geometric parameters include geological layer thickness and geological layer boundary; A stratigraphic sequence table is established based on the stratigraphic sequence framework and the geometric parameters of the geological layers.

6. The method for acceptance of underground coal mine gas control project according to claim 3, characterized in that: The step of fusing the three-dimensional spatial distribution model with the three-dimensional geological model to obtain a three-dimensional gas visualization model includes: Establishing a feature vector based on the grid node, the feature vector including three-dimensional coordinates, gas concentration data and geological layer attributes, the grid point corresponding to the gas extraction hole; Establishing a three-dimensional feature matrix based on all the feature vectors of the preset area; The three-dimensional feature matrix is ​​input into a deep learning model, and the deep learning model is trained to obtain the three-dimensional gas visualization model.

7. The method for acceptance of underground coal mine gas control project according to claim 6, characterized in that: The deep learning model includes an input layer, a convolution layer, a pooling layer and a fully connected layer. The three-dimensional feature matrix is ​​input into the deep learning model, and the deep learning model is trained to obtain the three-dimensional gas visualization model, including: Inputting the three-dimensional feature matrix into the input layer to obtain the three-dimensional feature matrix including the initial feature map; Inputting the three-dimensional feature matrix including the initial feature map into the convolution layer to obtain the three-dimensional feature matrix including the convolution feature map, wherein the convolution feature map extracts local features in the three-dimensional feature matrix through a convolution operation; Inputting the three-dimensional feature matrix including the convolution feature map into the pooling layer, and obtaining the three-dimensional feature matrix including the pooling feature map by downsampling the convolution feature map; The three-dimensional feature matrix including the pooled feature map is input into the fully connected layer, and the pooled feature is mapped to the output space through a fully connected operation to obtain the three-dimensional gas visualization model.

8. A coal mine underground gas control project acceptance system, characterized in that: The coal mine underground gas control project acceptance system includes: A first acquisition module is used to acquire geological layer parameters of a preset area, wherein the geological layer parameters include geological layer structure parameters and layout parameters of gas extraction holes, wherein the layout parameters include extraction hole positions and extraction hole depths; A second acquisition module is used to acquire gas extraction parameters of each gas extraction hole in the preset area, wherein the gas extraction parameters include gas concentration; A first establishing module is used to establish a three-dimensional spatial distribution model based on the gas extraction parameters; A second building module is used to build a three-dimensional geological model based on the geological layer parameters; A fusion module is used to fuse the three-dimensional spatial distribution model with the three-dimensional geological model to obtain a three-dimensional gas visualization model, and to realize the acceptance of the coal mine underground gas control project through the three-dimensional gas visualization model.

9. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the coal mine underground gas control project acceptance method described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the coal mine underground gas control project acceptance method described in any one of claims 1-7 are implemented.

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