Integrated construction method, device and equipment for mining transparent working face and medium

Abstract

The invention relates to the technical field of geophysics, rock mechanics, signal and information processing and artificial intelligence comprehensive application, and discloses an integrated construction method, device and equipment for a mining transparent working face and a medium, and the method comprises the following steps: obtaining geological data of a working face roadway to be constructed; simulating a first elevation value and a first spatial attribute value of a tunneled area of the roadway based on a graphic processing technology and geological data of the roadway; recognizing a geological abnormal body of the to-be-tunneled area of the roadway based on a tunneling and mining technology and geological data of the roadway, and determining a second elevation value and a second spatial attribute value of the geological abnormal body of the to-be-tunneled area of the roadway in real time by adopting an interpolation algorithm; and on the basis of the first elevation value, the first spatial attribute value, the second elevation value and the second spatial attribute value, a three-dimensional modeling tool is adopted to construct the visual mining transparent working face. According to the method, integrated construction of the mining transparent working face is clarified from mining working face real-time detection, data information processing, modeling, visualization and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of integrated applications of geophysics, rock mechanics, signal and information processing, and artificial intelligence, and particularly relates to a method, device, equipment and medium for integrally constructing a transparent working face for excavation. Background Art

[0002] With the development of intelligent coal mining technology, it is required to construct a transparent working face underground in a coal mine to provide an accurate geological model for intelligent mining. At present, there are mainly two paths for the research on the detection and modeling of the excavation and working faces: some scholars use borehole radar and cross-hole seismic to construct a transparent working face in a coal mine, which is difficult to achieve real-time monitoring and dynamic modeling; some scholars conduct research on a certain part of the detection and modeling of the excavation and working face, without systematically clarifying the method for integrally constructing the transparent working face, and cannot achieve the purpose of making the positions, shapes, structures and properties of internal intercalated gangue, faults, subsidence columns, water-rich abnormal areas, etc. visible in real time. Summary of the Invention

[0003] In view of this, the present invention provides a method, device, equipment and medium for integrally constructing a transparent working face for excavation, so as to solve the problems of difficult dynamic modeling and integrally constructing the transparent working face for excavation.

[0004] In a first aspect, the present invention provides a method for integrally constructing a transparent working face for excavation, the method comprising:

[0005] Obtaining geological data of a roadway of a working face to be constructed;

[0006] Based on graphics processing technology and the geological data of the roadway, simulating a first elevation value and a first spatial attribute value of the excavated area of the roadway;

[0007] Based on the technology of excavating and mining simultaneously and the geological data of the roadway, identifying geological anomalies in the area to be excavated of the roadway, and using an interpolation algorithm to determine in real time a second elevation value and a second spatial attribute value of the geological anomalies in the area to be excavated of the roadway;

[0008] Based on the first elevation value, the first spatial attribute value, the second elevation value and the second spatial attribute value, using a three-dimensional modeling tool to construct a visual transparent working face for excavation.

[0009] The integrated construction method of the transparent working face provided by the present invention clarifies the construction and integration process of the transparent working face platform from aspects such as real-time detection of the excavation working face, data information processing, modeling, and visualization. By widely collecting the geological data of the working face roadway, the geological conditions of the area where the roadway is located can be comprehensively understood. Using graphic processing technology, the geological data is converted into an intuitive three-dimensional model, clearly showing the terrain undulation (the first elevation value) of the excavated area and the spatial attributes such as rock characteristics and stratigraphic structure (the first spatial attribute value). The staff can clearly understand the geological characteristics of the excavated area at a glance, which is convenient for engineering quality inspection and evaluation of roadway stability, and provides a reference for subsequent excavation and mining. The technology of excavating and mining simultaneously combines with the geological data, which can monitor the geological conditions ahead in real time during the roadway excavation process and promptly detect geological anomalies. The key parameters (the second elevation value and the second spatial attribute value) of the anomaly are quickly determined through the interpolation algorithm. For areas with complex and changeable geological conditions, it is difficult for traditional geological exploration methods to comprehensively and accurately master the geological conditions of the area to be excavated. The visualized excavation transparent working face constructed by integrating various data comprehensively presents the geological information of the excavated area and the area to be excavated, achieving the effect of dynamic modeling and constructing an integrated excavation transparent working face, and solving the problem of difficult dynamic modeling and constructing an integrated excavation transparent working face.

[0010] In an alternative embodiment, the first elevation value and the first spatial attribute value of the excavated area of the working face roadway are simulated based on the graphic processing technology and the geological data of the roadway, including:

[0011] The coordinate transformation of the geological data of the roadway is performed using a digital elevation model to obtain the three-dimensional coordinate information corresponding to the geological data;

[0012] After the normalization processing and coordinate transformation of the three-dimensional coordinate information using the graphic processing technology, the first elevation value and the first spatial attribute value with a unified data format are obtained.

[0013] The integrated construction method for an excavation transparent working face provided by the present invention. The digital elevation model algorithm can uniformly convert the data originally scattered in the roadway geological data and possibly based on different local coordinate systems into three-dimensional coordinate information. This enables all geological data to be accurately positioned within a unified spatial framework. Whether it is borehole data, geological survey point data, or the geological body position information reflected by geophysical exploration, their accurate positions in the three-dimensional space can be determined. After obtaining the unified three-dimensional coordinate information, it is conducive to integrating geological data from different channels and of different types. The three-dimensional coordinate information is the basis for constructing a high-precision three-dimensional geological model and realizing a visual excavation transparent working face. The dimensions and numerical ranges of different data types in the geological data vary. Through normalization processing, all data are unified into a standard numerical interval, eliminating the influence of dimensional differences on data analysis and processing. After coordinate conversion and normalization processing, the elevation values and spatial attribute values of the excavation working face with a unified data format are obtained. This unified data format facilitates efficient processing using various graphics processing tools and data analysis software.

[0014] In an alternative embodiment, the geological data of the roadway includes geological maps, geological cross-sections, borehole data, geophysical exploration data, geological reports, groundwater data, geothermal data, and environmental geological data; identifying geological anomalies in the area to be excavated in the roadway based on the technology of excavating while mining and the geological data of the roadway, including:

[0015] Performing data preprocessing of denoising, normalization, and missing value filling on the geological maps, geological cross-sections, borehole data, geophysical exploration data, geological reports, groundwater data, geothermal data, and environmental geological data in sequence;

[0016] Performing intelligent data interpretation on the geological maps, geological cross-sections, borehole data, geophysical exploration data, geological reports, groundwater data, geothermal data, and environmental geological data after data preprocessing respectively to obtain geological features, geological structure form features, lithological features, geological resistivity features and / or seismic wave data, geological related theme features, groundwater features, geothermal features, and geological environment features respectively;

[0017] Adopting a multi-source heterogeneous information fusion inversion technology to perform feature fusion on the geological features, geological structure form features, lithological features, geological resistivity features and / or seismic wave data, geological related theme features, groundwater features, geothermal features, and geological environment features to obtain geological anomaly features, and performing geological anomaly inversion based on the geological anomaly features to obtain the geological anomalies in the area to be excavated in the roadway.

[0018] The integrated construction method for a transparent working face in mining provided by the present invention extracts rich characteristic information from various geological materials through intelligent data interpretation. Geological maps are analyzed to obtain geological characteristics, which can reveal the regional geological background and macroscopic geological structure; intelligent interpretation of geological cross-sections obtains the morphological characteristics of geological structures, clearly presenting the details of underground geological structures; interpretation of borehole data yields lithological characteristics, accurately reflecting the composition and properties of rocks; interpretation of geophysical exploration data gives geological resistivity characteristics and seismic wave data characteristics, helping to identify the distribution and anomalies of underground geological bodies; intelligent interpretation of geological reports extracts geological-related topic characteristics, summarizing the key information of regional geology; interpretation of groundwater data and geothermal data respectively gives groundwater characteristics and geothermal characteristics, reflecting the situation of underground fluids and temperature fields; interpretation of environmental geological data gives geological environmental characteristics, providing a basis for evaluating the impact of geological anomalies on the surrounding environment. The multi-source heterogeneous information fusion inversion technology is adopted to fuse the characteristics of different types of geological materials. By comprehensively analyzing information such as geological characteristics, geological structure morphological characteristics, and lithological characteristics, the characteristics of geological anomalies can be judged more comprehensively and accurately.

[0019] In an optional implementation manner, the interpolation algorithm includes the PSO-Kriging interpolation algorithm;

[0020] The real-time determination of the second elevation value and the second spatial attribute value of the geological anomaly in the area to be driven in the roadway by using the interpolation algorithm includes:

[0021] Monitoring points are set for the geological anomaly in the area to be driven in the roadway by using geological exploration tools, and the geological positions and rock physical property data of the monitoring points are obtained in real time;

[0022] The PSO-Kriging interpolation algorithm is used to perform interpolation iteration on the geological positions and rock physical property data of the monitoring points. When the iteration termination condition is met, the interpolation iteration terminates;

[0023] The geological positions and rock physical property data corresponding to the global optimal position in the interpolation iteration process are substituted into the PSO-Kriging interpolation algorithm to obtain the second elevation value and the second spatial attribute value of the geological anomaly in the area to be driven in the roadway.

[0024] The integrated construction method of the mining transparent working face provided by the present invention can collect data targeted and accurately capture the characteristics of abnormal bodies by setting monitoring points in geological abnormal bodies in the area to be tunnelled in the roadway. The PSO-Kriging interpolation algorithm combines the advantages of the particle swarm optimization (PSO) algorithm and the Kriging interpolation method. When interpolating the data of the monitoring points, the particle swarm searches for the optimal parameter combination in the solution space, so that the Kriging interpolation model can better fit the monitoring point data, thereby significantly improving the interpolation accuracy. Compared with the traditional Kriging interpolation method, the PSO-Kriging interpolation algorithm can more accurately estimate the geological position and rock physical property data at unknown positions between monitoring points and reduce errors. During the iteration process of the PSO-Kriging interpolation algorithm, the global best position represents the optimal solution found in the current search process. Substituting the geological position and rock physical property data corresponding to this position into the algorithm, the obtained second elevation value and second spatial attribute value are the results after multiple rounds of optimization. This means that these values are determined on the basis of fully considering the data characteristics of the monitoring points, the spatial correlation of geological data, and the search ability of the algorithm. Compared with the unoptimized interpolation results, they have higher reliability and can more truly reflect the actual spatial characteristics of geological abnormal bodies.

[0025] In an alternative embodiment, a visual mining transparent working face is constructed based on the first elevation value, the first spatial attribute value, the second elevation value, and the second spatial attribute value by using a 3D modeling tool, including:

[0026] Constructing a static model based on the first elevation value and the first spatial attribute value by using a 3D modeling tool;

[0027] Constructing a model of the area to be tunnelled in the roadway in real time based on the second elevation value and the second spatial attribute value by using a 3D modeling tool;

[0028] Constructing a visual mining transparent working face based on the static model and the model of the area to be tunnelled in the roadway.

[0029] The integrated construction method of the mining transparent working face provided by the present invention. The first elevation value and the first spatial attribute value usually come from the geological data of the excavated area and the previous detailed geological exploration results. By constructing a static model with this, a stable and reliable basic framework can be provided for the entire mining operation. Analyze the spatial position relationship between the static model and geological structures such as the excavated roadway and fault. The second elevation value and the second spatial attribute value are obtained by means of real-time monitoring of geological anomalies and other methods during the roadway excavation process. Based on these data, a model of the area to be excavated in the roadway is constructed in real time, which can accurately reflect the dynamic changes of the current geological conditions. Integrating the static model and the model of the area to be excavated in the roadway to construct the mining transparent working face can comprehensively display the geological and engineering conditions of the entire mining area. Information such as the stratum structure, distribution of geological anomalies, and roadway layout from the completed roadway part to the area to be excavated is clearly presented on a unified platform. This comprehensiveness enables the staff to have a complete understanding of the entire mining operation, facilitating overall coordination and reasonable allocation of resources, and accurately reflecting the geological appearance of the excavated / to-be-excavated working face in real time.

[0030] In an alternative embodiment, a static model is constructed using a 3D modeling tool based on the first elevation value and the first spatial attribute value, including: screening out the coal seam elevation value, roadway elevation value, roof elevation value, and floor elevation value from the first elevation value, and at the same time screening out the rock mechanical property data and lithological characteristic data related to the coal seam, roadway, roof, and floor from the first spatial attribute value;

[0031] Based on the coal seam elevation value, roadway elevation value, roof elevation value, floor elevation value, and the rock mechanical property data and lithological characteristic data related to the coal seam, roadway, roof, and floor, a coal seam model, a roadway model, and a roof and floor model are respectively constructed using a 3D modeling tool.

[0032] The integrated construction method of the mining transparent working face provided by the present invention, based on the coal seam elevation value, roadway elevation value, roof elevation value, floor elevation value, and the rock mechanical property data and lithological characteristic data related to the coal seam, roadway, roof, and floor, respectively constructs a coal seam model, a roadway model, and a roof and floor model using a 3D modeling tool. Through the coal seam model, roadway model, and roof and floor model, the static characteristics such as the roof, roadway, coal seam, and floor can be transparently reflected, and the characteristics and spatial relationships of different geological structures can be presented more accurately.

[0033] In an alternative embodiment, a model of the area to be excavated in the roadway is constructed in real time using a 3D modeling tool based on the second elevation value and the second spatial attribute value, including:

[0034] Determine the position, shape, scale, and rock physical properties of the anomaly based on the second elevation value and the second spatial attribute value;

[0035] Use a 3D modeling tool to construct a dynamic anomaly model in real time based on the location, shape, scale, and rock physical properties of the anomaly body;

[0036] Associate the dynamic anomaly model with the roadway driving progress to determine the accurate position of the anomaly model in the area to be driven of the roadway, and obtain the model of the area to be driven of the roadway.

[0037] The integrated construction method for the transparent working face of mining and excavation provided by the present invention. The second elevation value and the second spatial attribute value are derived from the real-time monitoring data during the roadway driving process, which can timely and accurately reflect the actual situation of the geological anomaly body. A dynamic anomaly model is constructed using a 3D modeling tool based on the location, shape, scale, and rock physical properties of the anomaly body, for the purpose of converting the anomaly information into a visual model of the area to be driven of the roadway, and achieving the purpose of transparently and visually monitoring the anomaly information of the working face.

[0038] In a second aspect, the present invention provides an integrated construction device for a mining and excavation working face, which includes:

[0039] An information acquisition module for acquiring the geological data of the roadway of the working face to be constructed;

[0040] A first elevation value and first spatial attribute value simulation module for simulating the first elevation value and the first spatial attribute value of the excavated area of the roadway based on the graphics processing technology and the geological data of the roadway;

[0041] A first elevation value and first spatial attribute value determination module for identifying geological anomaly bodies in the area to be driven of the roadway based on the technology of driving and mining simultaneously and the geological data of the roadway, and using an interpolation algorithm to determine the second elevation value and the second spatial attribute value of the geological anomaly bodies in the area to be driven of the roadway in real time;

[0042] A mining and excavation transparent working face construction module for constructing a visual mining and excavation transparent working face using a 3D modeling tool based on the first elevation value, the first spatial attribute value, the second elevation value, and the second spatial attribute value.

[0043] In a third aspect, the present invention provides a computer device, including: a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the integrated construction method for the transparent working face of mining and excavation in the first aspect or any corresponding implementation manner thereof by executing the computer instructions.

[0044] In a fourth aspect, the present invention provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to cause a computer to execute the integrated construction method for the transparent working face of mining and excavation in the first aspect or any corresponding implementation manner thereof.

[0045] Fifth aspect, the present invention provides a computer program product, including computer instructions for causing a computer to execute the integrated construction method of the transparent working face for mining as described in the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0047] Figure 1 is a schematic flowchart of the integrated construction method of the transparent working face for mining according to an embodiment of the present invention;

[0048] Figure 2 is a schematic flowchart of another integrated construction method of the transparent working face for mining according to an embodiment of the present invention;

[0049] Figure 3 is a schematic flowchart of yet another integrated construction method of the transparent working face for mining according to an embodiment of the present invention;

[0050] Figure 4 is a schematic flowchart of still another integrated construction method of the transparent working face for mining according to an embodiment of the present invention;

[0051] Figure 5 is a schematic diagram of the underground data acquisition system according to an embodiment of the present invention;

[0052] Figure 6 is a topology diagram of the real-time detection and monitoring system according to an embodiment of the present invention;

[0053] Figure 7 is a hardware system architecture diagram of the visual working face platform according to an embodiment of the present invention;

[0054] Figure 8 is a comparison diagram of the static parameter model and dynamic digital twin of the tunneling working face / transparent working face according to an embodiment of the present invention;

[0055] Figure 9 is a structural block diagram of the integrated construction device for the mining working face according to an embodiment of the present invention;

[0056] Figure 10 is a schematic hardware structure diagram of the computer device according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0057] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts fall within the protection scope of the present invention.

[0058] Currently, intelligent technologies and equipment such as intelligent exploration and excavation, geophysical advanced exploration, intelligent geophysical exploration of the working face, intelligent monitoring and early warning of potential safety hazards, and highly reliable 5G in coal mines are being developed and applied. Among them, the intelligent geological guarantee system in coal mines is the basic construction content, and the core is to achieve the transparency of mine geological information. Transparent geology takes high-precision geological exploration and monitoring technologies as the core, supported by a three-dimensional geological visualization platform, to establish a high-precision model of dynamic fusion of geological and engineering data, providing basic geological guarantee for intelligent tunneling, intelligent coal mining, and intelligent safety monitoring, etc. The geological guarantee system requires complete geological exploration technologies and equipment, digital storage of geological data and engineering data, and a geological information database. The tunneling system requires the use of technologies and equipment such as drilling and geophysical exploration to conduct advanced exploration of the geological structure, hydrogeological conditions, gas, etc. in the area to be tunneled in the roadway, and the detection distance, speed, and accuracy meet the requirements of intelligent tunneling. It has the function of three-dimensional modeling of geological information of the tunneling working face and can automatically update the model based on the geological information detected and collected automatically during the normal operation of the roadway tunneling process.

[0059] The embodiments of the present invention take the exploration and drilling monitoring technologies during excavation and mining as the core, use the MySQL (Relational Database Management System) database for storage, GPU (Graphics Processing Unit) parallel processing, and Unity modeling (three-dimensional modeling) tools as means, and are supported by the hardware system of the intelligent mine transparent working face platform to establish a high-precision model of dynamic fusion of geological and engineering data, providing geological guarantee for rapid tunneling, optimization of support distance, and early prevention and control of disasters, etc.

[0060] According to the embodiments of the present invention, an embodiment of a method for integrated construction of an excavation and mining working face is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0061] In this embodiment, a method for integrated construction of an excavation and mining working face is provided, which can be used for the hardware system of the intelligent mine transparent working face platform. The architecture diagram of the hardware system of the intelligent mine transparent working face platform is as Figure 7As shown in the figure, the architecture diagram includes five parts: the network device layer, the data layer, the data processing layer, the business application layer, and the display layer. The network device layer includes data acquisition devices (seismic geophones, microseismic geophones, and measurement electrode instruments), monitoring sub-stations, and data transmission devices. The data transmission devices include explosion-proof power supplies for mines, underground fiber optic ring networks, and optical port switches. The data layer is mainly a MySQL database, which consists of basic data such as geology, drilling, and geophysical exploration, and real-time data obtained from exploration during excavation and mining. The data processing layer includes, based on basic data such as geology, drilling, and geophysical exploration on a GPU server, combined with fault information, suspected collapse column information interpreted from surface three-dimensional seismic surveys, internal coal seam faults and collapse column information interpreted from trough wave exploration of the working face, and water-rich anomaly area information at different depths of the floor interpreted from audio electrical penetration. After normalization processing and coordinate transformation, the PSO-Kriging interpolation algorithm is used to solve the variogram parameters, fit the variogram function model, and simulate the elevation values of the coal seam, roof, and floor of the working face, reflecting attributes such as the original strata conditions, the development pattern of geological structures, and the spatial distribution range of groundwater; data obtained from exploration during excavation and mining is cleaned, transformed, and preprocessed, then intelligently interpreted, and multi-source heterogeneous information is fused to identify the types of abnormal bodies (such as the distribution of parting stones, faults, collapse columns, water-rich anomaly areas, etc.), determine the location, shape, structure, and properties of the abnormal bodies, and map in real-time the strike and throw of the fault, the stress and strain conditions of the working face, and the development height of the water-conducting fissure zone. The business application layer includes constructing geological models, roof and floor models, and abnormal body models of the driving / coal mining working face on Unity software (such as digital twin software). The display layer achieves the purpose of visualization, including large-screen monitors, PC terminals, and mobile terminals, etc., and displays the working face platform in real-time.

[0062] During actual detection, the network device layer, the data layer, the data processing layer, and the business application layer constitute an underground real-time detection system, and the specific division is as Figure 6 shown, which consists of three parts: the underground system, the transmission system, and the ground system. The underground system includes data acquisition devices, monitoring sub-stations, and data transmission devices. The data acquisition devices are mainly the devices of the network device layer, including seismic geophones, microseismic geophones, and measurement electrode instruments. The monitoring sub-stations are connected to the acquisition devices through cables. The data transmission devices are explosion-proof power supplies for mines, underground fiber optic ring networks, and optical port switches; the ground system is mainly composed of a MySQL database, a GPU server, and Unity software.

[0063] Figure 1 is a flowchart of an integrated construction method for an excavation and mining transparent working face according to an embodiment of the present invention. As Figure 1 shown, the process includes the following steps:

[0064] Step S101, obtain geological data of the roadway of the working face to be constructed.

[0065] Specifically, the working face to be constructed includes roadways, roof and floor; the geological data of the working face includes geological maps, geological profiles, borehole data, geophysical exploration data, geological reports, groundwater data, ground temperature data, environmental geological data; the spatial attribute values of the working face include geological structures, lithology, rock stratum properties, aquifer distribution and in-situ stress state; and the geological data of the obtained roadways is stored in MySQL to construct a geological information database.

[0066] During the mining or tunneling process of the working face, seismic detectors and microseismic detectors are arranged on the sidewalls (left and right sidewalls) of the roadway in the tunneling working face, seismic detectors and microseismic detectors are arranged in the two crossheadings of the working face, and rock mass electrodes are arranged on tunneling equipment such as roadheaders / mining shearers to collect seismic signals generated by coal cutters and roadheaders in real time. That is, the geological data of the roadway in the mining and tunneling working face is obtained through the data acquisition devices (seismic detectors, microseismic detectors and measuring electrode meters) of the above network equipment layer.

[0067] As Figure 6 shown, the data is transmitted to the host computer of the ground monitoring center in real time by using the data transmission equipment in the underground real-time detection system. The abnormal structure information in front of the tunneling or mining is inversed in real time by the seismic data while tunneling and mining, the stability information of the coal seam roof and floor and the development height information of the water-conducting fissure zone are obtained by interpreting the microseismic monitoring while tunneling and mining, and the abnormal body information such as the water-rich abnormal area information is obtained by inversing the electrical method while tunneling and mining. The schematic diagram of the underground data acquisition system according to the embodiment of the present invention is as Figure 5 shown.

[0068] Step S102, based on the graphics processing technology and the geological data of the roadway, simulate the first elevation value and the first spatial attribute value of the excavated area of the roadway.

[0069] Specifically, the graphics processing technology is implemented by using a graphics processing unit GPU (Graphics Processing Unit) or geographic information system (GIS) software and professional geological drawing software to perform digital processing on geological maps and geological profiles.

[0070] First, the paper drawings are scanned into high-resolution images, and image recognition technology is used to extract the line, symbol and text information in the drawings and convert it into vector data. For example, extract the fault lines and stratigraphic dividing lines in the geological map, and the stratigraphic boundaries and tectonic forms in the geological profile. Through coordinate calibration, the data of different drawings is unified into the same geographic coordinate system to ensure the accuracy of the spatial position.

[0071] For the first elevation value, the terrain elevation data of the area is extracted based on the generated DEM (Digital Elevation Model, DEM) model and the actual location information of the tunnel excavated area. By analyzing the geological profile, the vertical position of different strata in the excavated area is determined to further refine the first elevation value. For the first spatial attribute value, the correspondence between rock attributes and spatial positions is established based on the description of rock types and lithological characteristics in the geological data and the physical property test data of the core in the drilling data. Using interpolation algorithms, such as the PSO-Kriging interpolation algorithm (ParticleSwarm Optimization-Kriging interpolation algorithm), the spatial attribute values of the rock such as hardness, porosity, and permeability are filled on the spatial grid of the excavated area, so as to obtain a comprehensive first spatial attribute value distribution. During the simulation process, the parameters are continuously verified and adjusted to ensure that the simulation results are consistent with the actual geological conditions. For example, the rock hardness value obtained by simulation is compared with the hardness value of the actual drill core test, and the error is controlled within a reasonable range to ensure the reliability of the simulation data.

[0072] That is, after the known sample points of the original stratum of the mining face are normalized and the coordinates are transformed based on the graphics processing unit GPU, the elevation value and spatial attribute value of the mining face are simulated using the PSO-Kriging interpolation algorithm.

[0073] Step S103, based on the mining-as-you-go technology and the geological data of the tunnel, the geological anomaly body in the tunnel to be excavated area is identified, and the second elevation value and the second spatial attribute value of the geological anomaly body in the tunnel to be excavated area are determined in real time by using an interpolation algorithm.

[0074] Specifically, during the tunnel excavation process, the mining-as-you-dig technology is adopted, and the geological conditions ahead are monitored in real time using geological radars and geological detection equipment built into the TBM (Tunnel Boring Machine) shield. Geological radars detect underground geological structures by emitting high-frequency electromagnetic waves and receiving reflected waves. When encountering geological anomalies such as faults, caves, and broken zones, the characteristics of the reflected waves will change significantly. By analyzing the waveform, amplitude, frequency and other parameters of the reflected waves, combined with the stratigraphic information in the geological data, the existence of geological anomalies can be identified.

[0075] Once a geological anomaly is identified, multiple monitoring points are arranged around the anomaly, and the geological positions and rock physical property data of the monitoring points are obtained through geological exploration equipment, such as elevation, resistivity, seismic wave velocity, etc. The PSO-Kriging interpolation algorithm is used to process the monitoring point data. The PSO algorithm optimizes the parameters in the Kriging interpolation method, such as the nugget effect, sill value, and range of the variogram, by simulating the foraging behavior of bird flocks. The Kriging interpolation method is based on the theory of regionalized variables and uses the spatial autocorrelation structure of the monitoring point data to perform an optimal unbiased estimation of the points to be interpolated. During the iteration process, the positions and velocities of the particles are continuously adjusted to find the optimal parameter combination, so that the interpolation result can more accurately reflect the true situation of the geological anomaly. When the iteration termination conditions are met, such as reaching the maximum number of iterations or the fitness value converges, the parameters corresponding to the global best position are substituted into the Kriging interpolation model to calculate the second elevation value and the second spatial attribute value of the geological anomaly in the area to be driven in the roadway, and the spatial characteristic information of the geological anomaly is updated in real time.

[0076] Step S104, based on the first elevation value, the first spatial attribute value, the second elevation value, and the second spatial attribute value, a visual mining transparent working face is constructed using a 3D modeling tool.

[0077] Specifically, the 3D modeling tool uses the digital twin software Unity to create a 3D model. Based on the elevation value and spatial attribute value of the mining working face, the digital twin software Unity is used to create a 3D model, construct a terrain model, a roof and floor model, and an anomaly model of the driven area of the roadway, etc., map the three-dimensional geological structure, and add appropriate colors, compositions, and structures according to the lithology distribution of the rock strata to accurately reflect the geological appearance of the driving / mining working face in real time.

[0078] The integrated construction method of the mining transparent working face provided in this embodiment clarifies the construction and integration process of the transparent working face platform from aspects such as real-time detection of the mining working face, data information processing, modeling, and visualization. By widely collecting the geological data of the working face roadway, the geological conditions of the area where the roadway is located can be comprehensively understood. Using graphics processing technology, the geological data is converted into an intuitive three-dimensional model, clearly showing the terrain undulation (the first elevation value) of the excavated area and the spatial attributes (the first spatial attribute value) such as rock characteristics and stratigraphic structure. The staff can clearly understand the geological characteristics of the excavated area at a glance, which is convenient for engineering quality inspection and evaluating the stability of the roadway, providing a reference for subsequent tunneling and mining. The technology of tunneling and mining while extracting combined with geological data can real-time monitor the geological conditions ahead during the roadway tunneling process and timely detect geological anomalies. The key parameters (the second elevation value and the second spatial attribute value) of the anomaly are quickly determined through the interpolation algorithm. For areas with complex and changeable geological conditions, it is difficult for traditional geological exploration methods to comprehensively and accurately master the geological conditions of the area to be tunneled. The visualized mining transparent working face constructed by integrating various data comprehensively presents the geological information of the excavated area and the area to be tunneled, achieving the effect of dynamic modeling and constructing an integrated mining transparent working face.

[0079] In this embodiment, an integrated construction method of a mining transparent working face is provided, which can be used for the hardware system of the transparent working face platform of an intelligent mine. Figure 2 It is a flowchart of the integrated construction method of the mining transparent working face according to the embodiment of the present invention, as Figure 2 shown, and this process includes the following steps:

[0080] Step S201, obtain the geological data of the roadway of the working face to be constructed. For details, please refer to Figure 1 Step S101 of the shown embodiment, which will not be elaborated here.

[0081] Step S202, simulate the first elevation value and the first spatial attribute value of the excavated area of the roadway based on the graphics processing technology and the geological data of the roadway.

[0082] Specifically, the above step S202 includes:

[0083] Step S2021, perform coordinate transformation on the geological data of the roadway using a digital elevation model to obtain the three-dimensional coordinate information corresponding to the geological data.

[0084] The above-mentioned digital elevation model focuses on integrating the discretely distributed elevation data in the geographic space into a continuous terrain surface model. Comprehensively collect elevation-related data in the tunnel geological data, including contour data in geological maps, elevation values marked on geological profiles, and stratigraphic depth information recorded in drilling data. Use the Geographic Information System (GIS) software platform to carry out coordinate conversion. Import the carefully prepared data in the early stage into the software, accurately set the coordinate system parameters according to the actual geographical location of the tunnel, and ensure that it is completely matched with the actual geodetic coordinate system or the coordinate system used in engineering construction. During the entire conversion process, the GIS software will automatically use the interpolation algorithm to fit the data to ensure that the generated terrain surface is continuous and smooth, and produce accurate three-dimensional coordinate information.

[0085] Step S2022, after normalizing and converting the three-dimensional coordinate information using a graphics processing technique, a first elevation value and a first spatial attribute value in a unified data format are obtained.

[0086] Specifically, three-dimensional coordinate information contains multiple types of data, and their respective dimensions and numerical ranges vary greatly. The resistivity values in geophysical exploration data may fluctuate between tens and thousands of ohm meters, while the core lengths in drilling data are usually measured in meters, which are relatively small values. This difference can seriously interfere with subsequent data processing and analysis processes, resulting in inaccurate results and low efficiency. Normalization processing aims to uniformly map various types of data to a standard numerical interval, generally selecting the [0,1] or [-1,1] interval, so as to eliminate the impact of the dimension on the data and make different types of data comparable at the same scale.

[0087] While normalizing, use professional geological mapping software (such as MapGIS, ArcGIS, etc.) or general image processing software (such as Photoshop, etc., which can be used for geological data processing after secondary development) to perform coordinate conversion operations on the three-dimensional coordinate information. Geological maps and related data from different channels and based on different coordinate systems are unified into a coordinate system consistent with the three-dimensional coordinate system generated by the DEM algorithm in the previous text with the help of coordinate calibration, projection transformation and other technical means. For example, a geological map uses an old version of the local coordinate system. By querying the professional coordinate conversion parameter table and entering the corresponding parameters in the software, the coordinate transformation is completed, so that it can be seamlessly connected with the overall three-dimensional coordinate system to obtain the first elevation value and the first spatial attribute value.

[0088] Step S203, based on the mining-as-you-go technology and the geological data of the tunnel, the geological anomaly body in the tunnel to be excavated area is identified, and the second elevation value and the second spatial attribute value of the geological anomaly body in the tunnel to be excavated area are determined in real time by using an interpolation algorithm.

[0089] Specifically, the address data of the roadway includes geological maps, geological profiles, borehole data, geophysical exploration data, geological reports, groundwater data, geothermal data, and environmental geological data; the interpolation algorithm includes the PSO-Kriging interpolation algorithm.

[0090] Among them, the geological data information of the mining and excavation working face can reflect the stratum conditions, the development form of geological structures, the spatial distribution range of groundwater, etc. Specifically, the coal seam information, roadway information, roof information, and floor information of the mining and excavation working face include the positions, scales, and properties of the roof, roadway, coal seam, and floor, as well as the fault information and suspected collapse column information interpreted by 3D surface seismic, the internal coal seam faults and collapse column information interpreted by trough wave exploration of the working face, and the water-rich anomaly area information at different depths of the floor interpreted by audio-frequency electrical penetration.

[0091] The above step S203 includes:

[0092] Step S2031, perform data preprocessing of denoising, normalization, and missing value filling on the geological maps, geological profiles, borehole data, geophysical exploration data, geological reports, groundwater data, geothermal data, and environmental geological data in sequence.

[0093] Performing denoising processing on various types of geological data can effectively remove the noise data generated due to equipment failures, environmental interferences, etc. For example, the electromagnetic interference noise in geophysical exploration data, the abnormal values in borehole data caused by unstable measuring instruments, etc. After removing the noise, the data can more truly reflect the actual geological situation and provide a reliable basis for subsequent analysis. Normalization processing eliminates the differences in the dimensions and numerical ranges of different data types, enabling coordinate data in geological maps, core length data in borehole data, water level data in groundwater data, etc. to be compared and analyzed on the same scale, improving the accuracy and reliability of data processing. Missing value filling ensures the integrity of the data and avoids deviations in the analysis results caused by the missing of some data. For example, in a geological profile, if some formation thickness data is missing, more accurate analysis of the formation structure and variation law can be carried out after filling.

[0094] Step S2032, perform intelligent data interpretation on the geological maps, geological profiles, borehole data, geophysical exploration data, geological reports, groundwater data, geothermal data, and environmental geological data after data preprocessing respectively, and obtain geological features, geological structure morphological features, lithological features, geological resistivity features and / or seismic wave data, geological related theme features, groundwater features, geothermal features, and geological environment features respectively.

[0095] Specifically, through intelligent data interpretation, rich characteristic information is extracted from various geological data. Geological maps are analyzed to obtain geological characteristics, which can reveal the regional geological background and macroscopic geological structure; intelligent interpretation of geological cross-sections obtains the morphological characteristics of geological structures, clearly presenting the details of underground geological structures; interpretation of borehole data yields lithological characteristics, accurately reflecting the composition and properties of rocks; interpretation of geophysical exploration data reveals geological resistivity characteristics and seismic wave data characteristics, helping to identify the distribution and anomalies of underground geological bodies; intelligent interpretation of geological reports extracts geological-related theme characteristics, summarizing the key information of regional geology; interpretation of groundwater data and geothermal data respectively obtains groundwater characteristics and geothermal characteristics, reflecting the situation of underground fluids and temperature fields; interpretation of environmental geological data reveals geological environmental characteristics, providing a basis for evaluating the impact of geological anomalies on the surrounding environment.

[0096] Step S2033: Adopt the multi-source heterogeneous information fusion inversion technology to fuse the characteristics of geological characteristics, geological structure morphological characteristics, lithological characteristics, geological resistivity characteristics and / or seismic wave data, geological-related theme characteristics, groundwater characteristics, geothermal characteristics, and geological environmental characteristics to obtain the characteristics of geological anomalies, and perform geological anomaly inversion based on the characteristics of geological anomalies to obtain the geological anomalies in the area to be tunnelled in the roadway.

[0097] Specifically, adopt the multi-source heterogeneous information fusion inversion technology to fuse the characteristics of different types of geological data. By comprehensively analyzing various information such as geological characteristics, geological structure morphological characteristics, and lithological characteristics, the characteristics of geological anomalies can be judged more comprehensively and accurately. For example, a single geophysical exploration data may only find an area with resistivity anomalies underground, but it cannot determine its specific geological nature. By fusing and analyzing with the lithological characteristics of borehole data and the structural morphological characteristics of geological cross-sections, it can be more accurately judged whether the abnormal area is a geological anomaly such as a fault fracture zone or a karst cave.

[0098] Step S2034: Set monitoring points for the geological anomalies in the area to be tunnelled in the roadway through geological detection tools, and obtain the geological positions and rock physical property data of the monitoring points in real time.

[0099] Specifically, in the area to be tunnelled in the roadway, carefully design the layout of monitoring points around the geological anomalies. According to the scale, shape and possible change trend of the anomalies, arrange the monitoring points evenly at a certain interval. For large and complex geological anomalies, such as large fault fracture zones or large karst cave groups, the interval of monitoring points is relatively small, possibly 3 - 5 meters; for relatively regular and small-scale anomalies, the interval can be appropriately increased to 5 - 10 meters. Ensure that the monitoring points can fully cover the surrounding area of the anomalies and accurately capture the changes in their geological characteristics. For example, arrange monitoring points in the strike and dip directions of the fault fracture zone to obtain geological information at different positions.

[0100] In step S2035, the PSO-Kriging interpolation algorithm is used to perform interpolation iteration on the geological location and rock physical property data of the monitoring points. When the iteration termination condition is met, the interpolation iteration terminates.

[0101] The PSO-Kriging interpolation algorithm combines the particle swarm optimization (PSO) algorithm and the Kriging interpolation method. The PSO algorithm simulates the foraging behavior of a bird flock, regarding each solution as a particle in the search space. The particle flies in the space at a certain speed, and its speed is adjusted according to its own historical best position (pbest) and the group historical best position (gbest). The Kriging interpolation method is based on the theory of regionalized variables. It describes the spatial autocorrelation structure of geological data through the variogram and uses the data of known monitoring points to perform the optimal unbiased estimation of the points to be interpolated.

[0102] Particle swarm initialization: Determine the size of the particle swarm, which is usually set to 20 - 50 particles according to the number of monitoring points and the complexity of the problem. The dimension of the particle corresponds to the number of parameters of the Kriging variogram. For example, if the nugget effect, sill value, and range are 3 parameters, then the particle dimension is 3. The initial position of the particle is randomly generated within a reasonable parameter value range.

[0103] Fitness value calculation: For each particle, substitute the parameter values corresponding to its position into the Kriging interpolation model. Using the geological location and rock physical property data of the monitoring points, calculate the predicted value of the unknown position of the geological anomaly in the area to be driven through the Kriging interpolation formula. Taking the prediction of the second elevation value as an example, according to the elevation data and spatial positions of the monitoring points, combined with the variogram parameters corresponding to the particle, calculate the elevation predicted value of the unknown point. Then, compare the predicted value with the actual value obtained through other independent geological exploration methods (such as the actual value obtained by an advanced borehole). Use the mean square error (MSE) between the two as the fitness value. The smaller the MSE, the more accurate the Kriging interpolation result under the parameter settings corresponding to this particle, and the higher the fitness value.

[0104] Particle position and speed update: According to the current position, speed, its own historical best position (pbest), and the group historical best position (gbest) of the particle, update according to the speed and position update formulas of the PSO algorithm. By continuously iterating and updating the position and speed of the particle, make the particle move in the direction of a higher fitness value.

[0105] Iterative termination condition judgment: Set the maximum number of iterations, which is generally determined to be 200 - 500 times based on experience and computing resources. At the same time, when the population optimal fitness value changes less than a certain threshold (such as 0.001) in a continuous number of iterations (such as 10 - 20 times), it is considered that the algorithm converges and the iteration is terminated. For example, if the change in the population optimal fitness value is less than 0.001 in 15 consecutive iterations, the iteration process is stopped and the next step of calculation is entered.

[0106] Step S2036: Substitute the geological position and rock physical property data corresponding to the population optimal position in the interpolation iteration process into the PSO - Kriging interpolation algorithm to obtain the second elevation value and the second spatial attribute value of the geological anomaly in the area to be driven of the roadway.

[0107] Parameter substitution and calculation: After the interpolation iteration terminates, substitute the geological position and rock physical property data corresponding to the population optimal position (i.e., the optimal Kriging variogram parameters) into the PSO - Kriging interpolation algorithm. For the calculation of the second elevation value, use the elevation data of the monitoring points, the geological position, and the optimal parameters to calculate the accurate elevation value of the unknown position of the geological anomaly in the area to be driven of the roadway through the Kriging interpolation formula. For the second spatial attribute value, such as rock hardness, porosity, etc., similarly, based on the relevant data of the monitoring points and the optimal parameters, use the Kriging interpolation method to calculate. For example, according to the rock hardness data and spatial positions of the monitoring points, combined with the optimal variogram parameters, calculate the rock hardness values at different positions inside the anomaly.

[0108] Step S204: Based on the first elevation value, the first spatial attribute value, the second elevation value, and the second spatial attribute value, use a 3D modeling tool to construct a visual mining and excavation transparent working face. For details, please refer to Figure 1 Step S104 of the embodiment shown, which will not be elaborated here.

[0109] The integrated construction method for the transparent working face in mining provided in this embodiment extracts rich feature information from various geological data through intelligent data interpretation. Geological maps are analyzed to obtain geological features, which can reveal the regional geological background and macroscopic geological structure; the intelligent interpretation of geological profiles obtains the morphological features of geological structures, clearly presenting the details of underground geological structures; the interpretation of borehole data obtains lithological features, accurately reflecting the composition and properties of rocks; the interpretation of geophysical exploration data yields geological resistivity features and seismic wave data features, which helps to identify the distribution and anomalies of underground geological bodies; the intelligent interpretation of geological reports extracts geological-related theme features, summarizing the key information of regional geology; the interpretation of groundwater data and geothermal data respectively obtains groundwater features and geothermal features, reflecting the situation of underground fluids and temperature fields; the interpretation of environmental geological data yields geological environment features, providing a basis for evaluating the impact of geological anomalies on the surrounding environment. The multi-source heterogeneous information fusion inversion technology is adopted to fuse the features of different types of geological data. By comprehensively analyzing information such as geological features, geological structure morphological features, and lithological features, the characteristics of geological anomalies can be judged more comprehensively and accurately. By setting monitoring points for geological anomalies in the area of the roadway to be driven, data can be collected specifically, and the characteristics of the anomalies can be accurately captured. The PSO-Kriging interpolation algorithm combines the advantages of the particle swarm optimization (PSO) algorithm and the Kriging interpolation method. When interpolating the data of the monitoring points, the particle swarm searches for the optimal parameter combination in the solution space, enabling the Kriging interpolation model to better fit the data of the monitoring points, thereby significantly improving the interpolation accuracy.

[0110] In this embodiment, an integrated construction method for the transparent working face in mining is provided, which can be used for the hardware system of the transparent working face platform in an intelligent mine. Figure 3 It is a flowchart of the integrated construction method for the transparent working face in mining according to the embodiment of the present invention, as Figure 3 shown. The process includes the following steps:

[0111] Step S301, obtain the geological data of the roadway of the working face to be constructed. For details, please refer to Figure 2 Step S201 of the embodiment shown, which will not be elaborated here.

[0112] Step S302, based on the graphics processing technology and the geological data of the roadway, simulate the first elevation value and the first spatial attribute value of the excavated area of the roadway. For details, please refer to Figure 2 Step S202 of the embodiment shown, which will not be elaborated here.

[0113] Step S303, based on the technology of excavating and mining simultaneously and the geological data of the roadway, identify the geological anomalies in the area of the roadway to be driven, and use the interpolation algorithm to determine the second elevation value and the second spatial attribute value of the geological anomalies in the area of the roadway to be driven in real time. For details, please refer to Figure 2Step S203 of the illustrated embodiment will not be elaborated herein.

[0114] Step S304: Based on the first elevation value, the first spatial attribute value, the second elevation value, and the second spatial attribute value, use a 3D modeling tool to construct a visual mining transparent working face.

[0115] Specifically, the above step S304 includes:

[0116] Step S3041: Based on the first elevation value and the first spatial attribute value, use a 3D modeling tool to construct a static model.

[0117] In some optional embodiments, the above step S3041 includes:

[0118] Step a1: Screen out the coal seam elevation value, roadway elevation value, roof elevation value, and floor elevation value from the first elevation value. At the same time, screen out the rock mechanical property data and lithological characteristic data related to the coal seam, roadway, roof, and floor from the first spatial attribute value.

[0119] Specifically, screen the data related to the coal seam, roadway, roof, and floor from the first spatial attribute value. For the coal seam, collect its rock mechanical property data, such as the hardness, compressive strength, tensile strength, etc. of the coal seam. These data usually come from the test results of coal core samples in the laboratory. The lithological characteristic data includes the coal quality type of the coal seam (such as anthracite, bituminous coal, etc.) and the coal rock composition (vitrain, bright coal, dull coal, etc.), which can be obtained from geological reports and relevant research materials. For the roadway, screen the rock mechanical property data of the roadway surrounding rock, such as the hardness, elastic modulus, Poisson's ratio, etc. of the rock. These data are crucial for evaluating the stability of the roadway. The lithological characteristic data includes the rock type of the surrounding rock (such as sandstone, shale, limestone, etc.) and its structural characteristics (such as bedding and joint development), which can be obtained through geological maps and on-site geological surveys. For the roof and floor, obtain their rock mechanical property data, such as the flexural strength of the roof and the bearing capacity of the floor, as well as the lithological characteristic data, such as the lithological combination and thickness of the roof and floor rocks.

[0120] Step a2: Based on the coal seam elevation value, roadway elevation value, roof elevation value, floor elevation value, and the rock mechanical property data and lithological characteristic data related to the coal seam, roadway, roof, and floor, use a 3D modeling tool to construct a coal seam model, a roadway model, and a roof and floor model respectively.

[0121] Specifically, for the construction of the coal seam model: Select a professional 3D modeling tool, such as Surpac software for geological modeling or the general 3D modeling software 3ds Max (combined with a geological modeling plugin). Create a new project file in the software and set appropriate units and coordinate systems to ensure consistency with the actual geological data. Taking Surpac software as an example, import the filtered coal seam elevation value data, and use the "Create Triangulation" function of the software to connect the elevation points of the coal seam roof and floor into a triangulation to form a preliminary surface model of the coal seam. Then, according to the lithological characteristic data of the coal seam, assign corresponding materials and colors to the model. For example, set the anthracite coal seam to a black and shiny material, and the bituminous coal seam to a dark gray and relatively rough material. By distinguishing the materials and colors, visually display the coal seams of different coal quality types. Use the "Attribute Assignment" function of the software to associate the rock mechanical property data (such as hardness, compressive strength, etc.) of the coal seam with the corresponding parts in the model for subsequent mechanical analysis and simulation.

[0122] For the construction of the roadway model: In the same 3D modeling environment, construct the roadway model according to the filtered roadway elevation value data. If the roadway shape is regular (such as rectangular, arched), use the "Extrusion" or "Lofting" function of the software to create a 3D solid model of the roadway based on the coordinates and elevation of the roadway centerline and the cross-sectional shape parameters of the roadway. For example, in 3ds Max software, use the "Line" tool to draw the roadway centerline, and then through the "Extrusion" modifier, stretch the centerline into a roadway entity according to the cross-sectional dimensions of the roadway (such as the width and height of a rectangular roadway). For roadways with complex shapes, the roadway contour line in the CAD drawing can be imported, and then use the "Surface Modeling" function of the modeling tool to convert the contour line into a roadway model. According to the lithological characteristic data of the roadway surrounding rock, add a support structure model to the roadway model. For example, if the surrounding rock is sandstone and bolt support is used, add a bolt model to the wall surface of the roadway model, and adjust the length, diameter, and distribution density of the bolts to make it conform to the actual support design. At the same time, according to the rock mechanical property data of the surrounding rock, set the physical properties of the roadway model, such as density, elastic modulus, etc., for roadway stability analysis.

[0123] Construction of roof and floor model: The roof and floor models are constructed based on the selected roof and floor elevation data. In Surpac software, the "Create TIN" function is also used to construct the elevation points of the roof and floor into TIN surface models. According to the lithological characteristic data of the roof and floor, different materials and colors are set for the model to distinguish the roof and floor and rock layers of different lithologies. For example, the sandstone roof is set to a yellow, rough material, and the shale floor is set to a gray, relatively smooth material. According to the rock mechanical property data of the roof and floor, the corresponding mechanical parameters are assigned to the model, such as the bending strength of the roof and the bearing capacity of the floor. The "Boolean operation" function of the modeling tool is used to reasonably combine and connect the roof and floor models with the coal seam model and the roadway model. For example, the roof model is placed above the coal seam model, and the floor model is placed below the coal seam model to ensure that the spatial position relationship between the models is accurate and form a complete geological model system.

[0124] Based on the elevation values and spatial attribute values of the coal seam, tunnel, roof and floor of the mining face, three-dimensional modeling tools are used to construct coal seam models, tunnel models and roof and floor models respectively. Figure 7 shown.

[0125] The integrated construction method of the mining working face provided in this embodiment uses a three-dimensional modeling tool to construct the excavation coal seam model, tunnel model and roof and floor model respectively based on the elevation values and spatial attribute values of the coal seam, tunnel, roof and floor of the mining working face. The excavation coal seam model, tunnel model and roof and floor model can transparently reflect the static characteristics of the roof, tunnel, coal seam, floor, etc.

[0126] Step S3042, based on the second elevation value and the second spatial attribute value, a three-dimensional modeling tool is used to construct a model of the area to be excavated in real time.

[0127] In some optional implementations, the above step S3042 includes:

[0128] Step b1, determining the position, shape, scale and rock physical properties of the abnormal body based on the second elevation value and the second spatial attribute value.

[0129] Specifically, during the tunnel excavation process, the second elevation value and the second spatial attribute value data are acquired in real time through geological radar, TBM shield's built-in detection equipment and other advanced geological detection instruments.

[0130] Determine the location of the anomaly: Utilize the reflected wave characteristics of the geological radar data, analyze the arrival time and amplitude change of the reflected wave through signal processing algorithms, determine the distance and direction between the anomaly and the detection equipment, and accurately calculate the three-dimensional coordinate position of the anomaly in the area to be excavated in the tunnel.

[0131] Inference of the shape and scale of anomalies: Analyze the distribution range and intensity changes of reflected waves in geological radar data, as well as the spatial changes of rock physical properties obtained by detection equipment, to infer the shape and scale of anomalies. For anomalies such as caves, if the geological radar reflected waves show strong and concentrated reflections in a certain area, and the reflection range presents circular or elliptical characteristics, the shape of the cave can be preliminarily inferred. By measuring the size of the area covered by the reflected waves, combined with the geological conditions and the accuracy of the detection equipment, the scale parameters such as the diameter and height of the cave are estimated. For linear anomalies such as faults, the parameters such as the strike, dip and drop of the fault are determined according to the detected location and range of the sudden change in rock physical properties and the linear characteristics of the geological radar reflected waves, thereby depicting the shape and scale of the fault.

[0132] Analysis of rock physical properties: In-depth analysis of rock physical property data obtained by TBM shield detection equipment. By measuring rock resistivity, seismic wave velocity, density and other parameters, combined with rock physics principles, the rock type and rock physical properties of the anomaly are inferred. For example, different rock types have different resistivity ranges. By comparing the measured resistivity values with the known rock resistivity database, it is determined whether the rock type of the anomaly is sandstone, shale or limestone. At the same time, based on the propagation characteristics of seismic waves in different rocks, such as speed and attenuation, the physical properties of the rock, such as hardness and porosity, are further determined.

[0133] Exemplarily, the information of abnormal bodies during excavation and mining is taken as an example to illustrate, which includes the abnormal structure information ahead of excavation or mining obtained by seismic inversion during excavation and mining, the stability information of coal seam roof and floor and the development height information of water-conducting fracture zones interpreted by microseismic monitoring during excavation and mining, and the water-rich abnormal area information obtained by electrical inversion during excavation and mining.

[0134] Taking the example of the abnormal structure information in front of the tunneling or mining face obtained by the seismic inversion during tunneling and mining, using the seismic waves generated when the roadheader cuts the coal wall and rock as the seismic source, continuously collecting seismic wave data in the roadway for a long time, and preprocessing the collected seismic wave data, including steps such as denoising and filtering to improve the data quality. Then, through the high-resolution pulsing algorithm for the seismic signals during tunneling, the multi-wavefield joint inversion of the seismic signals during tunneling is used to obtain the propagation velocity (wave velocity), and the physical properties of the underground medium are analyzed using the propagation velocity (wave velocity) of the seismic waves. By comparing the changes in the seismic wave velocities at different depths or different positions, the density changes of the underground medium and possible geological structures such as faults can be inferred. The results of the velocity analysis and density inversion are comprehensively interpreted, combined with other information such as geology, 3D seismic, geophysical exploration, surveying, and boreholes, and the dynamic intelligent imaging technology for seismic waves during tunneling is used to finally determine the contour and properties of the underground faults. The development height of the water-conducting fissure zone is monitored in real time by microseismic during tunneling and mining, and a prediction model for the development height of the water-conducting fissure zone is established using multiple non-linear regression. For the water-rich abnormal area, the preprocessed data is inversely calculated using the electrical method inversion algorithm to obtain the resistivity distribution map of the underground medium. The low resistivity area usually indicates rich water, that is, the water-rich abnormal area.

[0135] Step b2, based on the position, shape, scale, and petrophysical properties of the abnormal body, use a 3D modeling tool to construct a dynamic abnormal body model in real time.

[0136] Specifically, the 3D modeling tool uses the digital twin software Unity. The digital twin software Unity is used to perform 3D dynamic modeling on the position, shape, structure, and properties of the abnormal body to obtain a dynamic abnormal body model. As the roadway tunneling progresses, the geological exploration equipment continuously obtains new data on the second elevation value and the second spatial attribute value. The modeling tool updates the abnormal body model in real time according to the new data. When a new boundary point of the abnormal body is detected, or the petrophysical properties change, the modeling tool automatically adjusts the shape, scale, and physical properties of the abnormal body model.

[0137] The comparison diagram of the static model and the dynamic digital twin of the tunneling face / transparent face according to the embodiment of the present invention is as Figure 8 shown.

[0138] Step b3, correlate the dynamic abnormal body model with the roadway tunneling progress to determine the accurate position of the abnormal body model in the area to be tunneled in the roadway, and obtain the model of the area to be tunneled in the roadway.

[0139] Specifically, by installing sensors on the roadway tunneling equipment, the progress of roadway tunneling is monitored in real time, including information such as the tunneling distance, direction, and time. For example, displacement sensors are installed on the TBM tunneling machine to measure the distance the tunneling machine advances in real time; gyroscopes and compasses are installed to monitor changes in the tunneling direction. These tunneling progress data are synchronously recorded and transmitted together with the second elevation value and second spatial attribute value data obtained by the geological exploration equipment. The coordinate system of the dynamic abnormal body model is unified with the coordinate system of the roadway tunneling progress. Taking the starting point of roadway tunneling as the coordinate origin, the direction of the coordinate axis is determined according to the tunneling direction. The coordinates of the abnormal body model are converted to the same coordinate system as the roadway tunneling, so as to accurately correlate the positions of the two. For example, if the abnormal body model is established in a certain local coordinate system, its coordinates are converted to the global coordinate system with the starting point of roadway tunneling as the origin through the coordinate conversion formula. According to the tunneling progress data, the position of the abnormal body model in the area to be tunneled in the roadway is updated in real time. When the roadway has been tunneled a certain distance, the coordinates of the abnormal body model relative to the new roadway tunneling position are calculated according to the tunneling direction and distance, ensuring that the abnormal body model is always located at the correct position in the area to be tunneled.

[0140] The integrated construction method for the mining face provided in this embodiment is based on the abnormal body information during tunneling and mining, and uses a three-dimensional modeling tool to construct a dynamic abnormal body model, aiming to convert the abnormal body information into a visual model of the area to be tunneled in the roadway, and achieve the purpose of transparently and visually monitoring the abnormal body information of the mining face.

[0141] Step S3043, construct a visual mining transparent working face based on the static model and the model of the area to be tunneled in the roadway.

[0142] Specifically, the digital twin software Unity is used to perform three-dimensional dynamic modeling on the static model and the dynamic abnormal body model to obtain a visual working face platform.

[0143] The integrated construction method for the mining face provided in this embodiment is based on a three-dimensional modeling tool to construct a visual working face model, which can map the three-dimensional geological structure of the mine, achieve the purpose of dynamically constructing the working face model, and also achieve the purpose of making the positions, shapes, structures, and properties of internal gangue, faults, collapse columns, water-rich abnormal areas, etc. visible in real time, providing conditions for adding appropriate colors, compositions, and structures according to the distribution of rock formations and lithologies in the subsequent process, and accurately reflecting the geological appearance of the tunneling / caving face in real time.

[0144] As one or more specific application embodiments of the present invention, in combination with Figure 4 The integrated construction method for the mining face provided by the present invention is further described in detail as follows:

[0145] Step S401, collect the information of the roof, roadway, coal seam, floor position, scale and properties of the target working face, as well as the fault information, suspected subsided column information from the ground three-dimensional seismic interpretation, the internal coal seam faults and subsided column information from the trough wave exploration interpretation of the working face, and the water-rich anomaly area information at different depths of the floor from the audio electrical penetration interpretation, etc., to obtain the information that can reflect the original stratum conditions, the development form of geological structures, the spatial distribution range of groundwater, etc.;

[0146] Step S402, collect in real time the abnormal structure information in front of the tunneling or mining obtained by seismic inversion during the tunneling / coal mining process of the target working face, the information on the stability of the coal seam roof and floor and the development height of the water-conducting fissure zone interpreted by microseismic monitoring during tunneling and coal mining, and the water-rich anomaly area information obtained by electrical method inversion during tunneling and coal mining, etc.

[0147] Step S403, store the original stratum information of the tunneling / coal mining working face and the abnormal body information collected in real time into the relational database management system MySQL to construct a dynamic geological information database for the working face.

[0148] Step S404, based on the original stratum information of the target working face, use PSO-Kriging interpolation to solve the variogram parameters, fit the variogram function model, simulate the elevation values of the coal seam, roadway, roof and floor of the working face, and use Unity software to realize the visualization of the three-dimensional model of the occurrence form of the coal seam, roadway, roof and floor of the working face. Dynamically correct the model based on the abnormal body information collected in real time to construct a dynamic geological model.

[0149] Step S405, build an intelligent mine transparent working face platform based on geological drilling, underground data acquisition system, transmission system, MySQL database, graphics processing unit GPU and digital twin software Unity three-dimensional dynamic modeling. As Figure 5 、 Figure 6 and Figure 7 shown.

[0150] The integrated construction method for the excavation and coal mining working face provided in this embodiment realizes the transparency of the roof, floor and coal seam, and the positions, forms, structures and properties of the internal parting stones, faults, subsided columns, water-rich anomaly areas, etc. can be seen in real time. The strike and throw of the faults, the internal stress and strain conditions of the working face and the development height of the water-conducting fissure zone are monitored in real time, which solves the problems of traditional exploration that requires suspending the tunneling operation, and is difficult to monitor in real time and dynamically model, etc. in the construction of the transparent working face, and provides geological guarantee for rapid tunneling, support distance optimization and disaster prevention in advance.

[0151] In this embodiment, an integrated construction device for an excavation working face is further provided. This device is used to implement the above-mentioned embodiments and preferred implementation manners, and those that have been described will not be repeated. As used hereinafter, the term "module" can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0152] This embodiment provides an integrated construction device for an excavation working face. As Figure 9 shown, it includes:

[0153] A geological data acquisition module 901, which is used to acquire the geological data of the roadway of the working face to be constructed.

[0154] A first elevation value and first spatial attribute value simulation module 902, which is used to simulate the first elevation value and the first spatial attribute value of the excavated area of the roadway based on graphic processing technology and the geological data of the roadway;

[0155] A second elevation value and second spatial attribute value determination module 903, which is used to identify geological anomalies in the area to be excavated of the roadway based on the technology of excavating and mining simultaneously and the geological data of the roadway, and use the interpolation algorithm to determine the second elevation value and the second spatial attribute value of the geological anomalies in the area to be excavated of the roadway in real time.

[0156] A working face construction module 904, which is used to construct a visual excavation transparent working face based on the first elevation value, the first spatial attribute value, the second elevation value, and the second spatial attribute value by using a three-dimensional modeling tool.

[0157] Among them, the information acquisition module 901 can be embedded in the network device layer of the intelligent mine transparent working face platform hardware system to acquire information.

[0158] The first elevation value and first spatial attribute value simulation module 902 and the second elevation value and second spatial attribute value determination module 903 can be embedded in the data processing layer of the intelligent mine transparent working face platform hardware system to process data.

[0159] The working face construction module 904 can be embedded in the service application layer of the intelligent mine transparent working face platform hardware system to construct a model.

[0160] In some optional implementation manners, the first elevation value and first spatial attribute value simulation module 902 includes:

[0161] A three-dimensional coordinate determination unit, which is used to perform coordinate transformation on the geological data of the roadway by using a digital elevation model to obtain the three-dimensional coordinate information corresponding to the geological data;

[0162] The first elevation value and first spatial attribute value simulation unit is configured to perform normalization processing and coordinate transformation on three-dimensional coordinate information using graphics processing technology, and then obtain the first elevation value and first spatial attribute value with a unified data format.

[0163] In some alternative embodiments, the address data of the roadway includes geological maps, geological cross-sections, borehole data, geophysical exploration data, geological reports, groundwater data, geothermal data, and environmental geological data. The second elevation value and second spatial attribute value determination module 903 includes:

[0164] The data preprocessing unit is configured to perform data preprocessing on geological maps, geological cross-sections, borehole data, geophysical exploration data, geological reports, groundwater data, geothermal data, and environmental geological data in sequence, including denoising processing, normalization processing, and missing value filling.

[0165] The data intelligent interpretation unit is configured to perform data intelligent interpretation on the geological maps, geological cross-sections, borehole data, geophysical exploration data, geological reports, groundwater data, geothermal data, and environmental geological data after data preprocessing respectively, and obtain geological features, geological structure morphological features, lithological features, geological resistivity features and / or seismic wave data, geological related theme features, groundwater features, geothermal features, and geological environment features respectively.

[0166] The geological anomaly body construction unit for the roadway area to be driven is configured to perform feature fusion on geological features, geological structure morphological features, lithological features, geological resistivity features and / or seismic wave data, geological related theme features, groundwater features, geothermal features, and geological environment features using a multi-source heterogeneous information fusion inversion technology to obtain geological anomaly body features, and perform geological anomaly body inversion based on the geological anomaly body features to obtain the geological anomaly body in the roadway area to be driven.

[0167] In some alternative embodiments, the interpolation algorithm includes the PSO-Kriging interpolation algorithm; the second elevation value and second spatial attribute value determination module 903 further includes:

[0168] The monitoring point setting and data acquisition unit is configured to set monitoring points on the geological anomaly body in the roadway area to be driven through geological exploration tools, and obtain the geological location and rock physical property data of the monitoring points in real time.

[0169] The interpolation calculation unit is configured to perform interpolation iteration on the geological location and rock physical property data of the monitoring points using the PSO-Kriging interpolation algorithm, and when the iteration termination condition is satisfied, the interpolation iteration terminates.

[0170] The second elevation value and second spatial attribute value determination unit is configured to substitute the geological location and rock physical property data corresponding to the population optimal position in the interpolation iteration process into the PSO-Kriging interpolation algorithm to obtain the second elevation value and second spatial attribute value of the geological anomaly body in the area to be driven of the roadway.

[0171] In some alternative embodiments, the working face construction module 904 includes:

[0172] The static model construction unit is configured to construct a static model using a three-dimensional modeling tool based on the first elevation value and the first spatial attribute value.

[0173] The anomaly body model construction unit is configured to construct a model of the area to be driven of the roadway in real time using a three-dimensional modeling tool based on the second elevation value and the second spatial attribute value.

[0174] The working face platform construction unit is configured to construct a transparent mining and excavation working face based on the static model and the model of the area to be driven of the roadway.

[0175] In some alternative embodiments, the static model construction unit includes:

[0176] The data extraction sub-unit is configured to screen out the coal seam elevation value, roadway elevation value, roof elevation value, and floor elevation value from the first elevation value, and at the same time screen out the rock mechanical property data and lithological characteristic data related to the coal seam, roadway, roof, and floor from the first spatial attribute value.

[0177] The sub-model construction sub-unit is configured to construct a coal seam model, a roadway model, and a roof and floor model respectively using a three-dimensional modeling tool based on the coal seam elevation value, roadway elevation value, roof elevation value, floor elevation value, and the rock mechanical property data and lithological characteristic data related to the coal seam, roadway, roof, and floor.

[0178] In some alternative embodiments, the anomaly body model construction unit includes:

[0179] The preprocessing sub-unit is configured to determine the position, shape, scale, and rock physical properties of the anomaly body based on the second elevation value and the second spatial attribute value.

[0180] The anomaly body model construction sub-unit is configured to construct a dynamic anomaly body model in real time using a three-dimensional modeling tool based on the position, shape, scale, and rock physical properties of the anomaly body.

[0181] The area to be driven of the roadway model construction sub-unit is configured to associate the dynamic anomaly body model with the roadway driving progress to determine the accurate position of the anomaly body model in the area to be driven of the roadway, and obtain the model of the area to be driven of the roadway.

[0182] The further function descriptions of the above-mentioned respective modules and units are the same as those in the corresponding above-mentioned embodiments, and will not be elaborated herein.

[0183] The integrated construction device for the mining face in this embodiment is presented in the form of functional units. Here, the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and a memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0184] The embodiment of the present invention also provides a computer device having the above Figure 9 shown integrated construction device for the transparent mining face.

[0185] Please refer to Figure 10 , Figure 10 which is a schematic structural diagram of a computer device provided by an optional embodiment of the present invention. As Figure 10 shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including a high-speed interface and a low-speed interface. Each component communicates with each other using different buses and can be installed on a common motherboard or installed in other ways as needed. The processor can process instructions executed within the computer device, including instructions stored in the memory or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a set of blade servers, or a multi-processor system). Figure 10 In

[0186] one processor 10 is taken as an example.

[0187] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0188] The memory 20 may include a program storage area and a data storage area. The program storage area may store an operating system and application programs required for at least one function. The data storage area may store data created according to the use of the computer device and the like. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some alternative embodiments, the memory 20 may optionally include a memory remotely provided with respect to the processor 10, and these remote memories may be connected to the computer device through a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0189] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk, or a solid-state drive; the memory 20 may further include a combination of the above types of memories.

[0190] The computer device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30, and the output device 40 may be connected through a bus or other means. Figure 10 Taking connection through a bus as an example.

[0191] The input device 30 may receive input digital or character information, and generate key signal inputs related to the user settings and function controls of the computer device, such as a touch screen, a keypad, a mouse, a trackpad, a touchpad, a pointing stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 may include a display device, an auxiliary lighting device (e.g., an LED), and a tactile feedback device (e.g., a vibration motor), etc. The above-mentioned display device includes, but is not limited to, a liquid crystal display, a light-emitting diode, a display, and a plasma display. In some alternative embodiments, the display device may be a touch screen.

[0192] Embodiments of the present invention also provide a computer-readable storage medium. The methods according to the embodiments of the present invention can be implemented in hardware, firmware, or be implemented as computer code that can be recorded on a storage medium, or be implemented by downloading over a network from an original storage in a remote storage medium or a non-transitory machine-readable storage medium and will be stored in a local storage medium, so that the methods described herein can be stored as such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code, and when the software or computer code is accessed and executed by the computer, the processor, or the hardware, the methods shown in the above embodiments are implemented.

[0193] Although embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. An integrated construction method for an excavation transparent working face, characterized in that The method includes: Obtaining the geological data of the roadway of the working face to be constructed; Based on the graphic processing technology and the geological data of the roadway, simulating the first elevation value and the first spatial attribute value of the excavated area of the roadway; Based on the technology of excavating and mining simultaneously and the geological data of the roadway, identifying the geological anomalies in the area to be excavated of the roadway, and using the interpolation algorithm to determine the second elevation value and the second spatial attribute value of the geological anomalies in the area to be excavated of the roadway in real time; Based on the first elevation value, the first spatial attribute value, the second elevation value and the second spatial attribute value, constructing a visual mining and excavation transparent working face by using a 3D modeling tool.

2. The method according to claim 1, characterized in that, The simulating the first elevation value and the first spatial attribute value of the excavated area of the working face roadway based on the graphic processing technology and the geological data of the roadway includes: Using a digital elevation model to perform coordinate transformation on the geological data of the roadway to obtain the 3D coordinate information corresponding to the geological data; After performing normalization processing and coordinate transformation on the 3D coordinate information by using the graphic processing technology, obtaining the first elevation value and the first spatial attribute value with a unified data format.

3. The method according to claim 1, wherein The geological data of the roadway includes geological maps, geological cross-sections, borehole data, geophysical exploration data, geological reports, groundwater data, geothermal data and environmental geological data; The identifying the geological anomalies in the area to be excavated of the roadway based on the technology of excavating and mining simultaneously and the geological data of the roadway includes: Performing data preprocessing of denoising, normalization and missing value filling on the geological maps, geological cross-sections, borehole data, geophysical exploration data, geological reports, groundwater data, geothermal data and environmental geological data in sequence; Performing intelligent data interpretation on the geological maps, geological cross-sections, borehole data, geophysical exploration data, geological reports, groundwater data, geothermal data and environmental geological data after data preprocessing respectively to obtain geological features, geological structure morphological features, lithological features, geological resistivity features and / or seismic wave data, geological related theme features, groundwater features, geothermal features and geological environment features respectively; Using the multi-source heterogeneous information fusion inversion technology to perform feature fusion on the geological features, geological structure morphological features, lithological features, geological resistivity features and / or seismic wave data, geological related theme features, groundwater features, geothermal features and geological environment features to obtain the geological anomaly features, and performing geological anomaly inversion based on the geological anomaly features to obtain the geological anomalies in the area to be excavated of the roadway.

4. The method according to claim 1, characterized in that The interpolation algorithm includes the PSO-Kriging interpolation algorithm; The using the interpolation algorithm to determine the second elevation value and the second spatial attribute value of the geological anomalies in the area to be excavated of the roadway in real time includes: Setting monitoring points for the geological anomalies in the area to be excavated of the roadway through geological exploration tools, and obtaining the geological positions and rock physical property data of the monitoring points in real time; Using the PSO-Kriging interpolation algorithm to perform interpolation iteration on the geological positions and rock physical property data of the monitoring points, and when the iteration termination condition is met, the interpolation iteration terminates; Substitute the geological location and petrophysical property data corresponding to the global optimal position in the interpolation iteration process into the PSO-Kriging interpolation algorithm to obtain the second elevation value and the second spatial attribute value of the geological anomaly in the area where the roadway is to be driven.

5. The method according to claim 1, characterized in that, Constructing a visual mining and excavation transparent working face based on the first elevation value, the first spatial attribute value, the second elevation value, and the second spatial attribute value, including: Constructing a static model based on the first elevation value and the first spatial attribute value using a 3D modeling tool; Constructing a model of the area where the roadway is to be driven in real time based on the second elevation value and the second spatial attribute value using a 3D modeling tool; Constructing a visual mining and excavation transparent working face based on the static model and the model of the area where the roadway is to be driven.

6. The method according to claim 5, characterized in that, Constructing a static model based on the first elevation value and the first spatial attribute value using a 3D modeling tool, including: Screen out the coal seam elevation value, roadway elevation value, roof elevation value, and floor elevation value from the first elevation value, and at the same time screen out the rock mechanics property data and lithological characteristic data related to the coal seam, roadway, roof, and floor from the first spatial attribute value; Construct a coal seam model, a roadway model, and a roof and floor model respectively using a 3D modeling tool based on the coal seam elevation value, roadway elevation value, roof elevation value, floor elevation value, and the rock mechanics property data and lithological characteristic data related to the coal seam, roadway, roof, and floor.

7. The method according to claim 5, characterized in that, Constructing a model of the area where the roadway is to be driven in real time based on the second elevation value and the second spatial attribute value using a 3D modeling tool, including: determining the position, shape, scale, and petrophysical properties of the anomaly based on the second elevation value and the second spatial attribute value; Constructing a dynamic anomaly model in real time using a 3D modeling tool based on the position, shape, scale, and petrophysical properties of the anomaly; Associate the dynamic anomaly model with the roadway driving progress to determine the accurate position of the anomaly model in the area where the roadway is to be driven, and obtain the model of the area where the roadway is to be driven.

8. An integrated construction device for an excavation transparent working face, characterized in that, The device includes: An information acquisition module for acquiring geological data of the roadway of the working face to be constructed; A first elevation value and first spatial attribute value simulation module for simulating the first elevation value and the first spatial attribute value of the excavated area of the roadway based on graphics processing technology and the geological data of the roadway; A first elevation value and first spatial attribute value determination module for identifying geological anomalies in the area where the roadway is to be driven based on the following-mining technology and the geological data of the roadway, and using an interpolation algorithm to determine the second elevation value and the second spatial attribute value of the geological anomalies in the area where the roadway is to be driven in real time; A mining and excavation transparent working face construction module for constructing a visual mining and excavation transparent working face using a 3D modeling tool based on the first elevation value, the first spatial attribute value, the second elevation value, and the second spatial attribute value.

9. A computer device, characterized in that, Including: A memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to execute the integrated construction method of the mining and excavation transparent working face according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a computer to execute the integrated construction method of the transparent working face for mining according to any one of claims 1 to 7.

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