A method and system for fixed-point high-precision mapping and monitoring of surface movement and deformation in coal mining areas

Abstract

This invention belongs to the field of surveying and monitoring technology, and particularly relates to a high-precision surveying and monitoring method and system for surface movement and deformation in coal mining. Firstly, by improving the structure of the monitoring target and adding a layered displacement difference adaptive calibration structure, this invention achieves layered monitoring of bedrock and soil layers. Secondly, by combining non-uniform adaptive point distribution, it solves the problems of unstable monitoring benchmarks and unreasonable point distribution. Then, it introduces a dynamic weighted fusion algorithm related to mining progress, combined with systematic error compensation based on mechanical mechanisms, effectively eliminating non-mining interference and correcting model parameters, thus solving the defects of low calculation accuracy and data distortion. Finally, by optimizing the early warning and handling process and clarifying the hierarchical early warning linkage measures and information push mechanism, it solves the problems of poor early warning connection and delayed response. The data flow is clear, and it can be directly applied to surface movement and deformation monitoring in coal mining. It can adapt to monitoring scenarios in different mining areas and has strong practicality and promotional value.

Description

Technical Field

[0001] This invention belongs to the field of surveying and monitoring technology, specifically relating to a high-precision surveying and monitoring method and system for fixed-point mapping and monitoring of surface movement and deformation in coal mining. Background Technology

[0002] During coal mining, the movement of underground coal seams can cause surface subsidence, horizontal displacement, tilting and other deformations. If the deformation exceeds the safety threshold, it can easily lead to geological disasters such as surface collapse and cracks, threatening personnel safety and production operations. Therefore, high-precision, real-time monitoring of surface movement and deformation is the key to ensuring safe production in coal mines.

[0003] Current surveying and monitoring technologies are widely used in coal mine surface movement and deformation monitoring. Existing technologies generally follow a process of monitoring point deployment, data acquisition, data processing, and early warning response. This involves deploying monitoring markers and using GPS positioning, levels, and synthetic aperture radar to acquire deformation data. After simple calculations and error corrections, deformation parameters are calculated and anomaly warnings are issued. Some solutions introduce multi-source data fusion technology to attempt to balance monitoring accuracy and coverage. However, existing monitoring solutions still have many shortcomings and cannot meet the high-precision, real-time monitoring needs of coal mines. Specifically: Firstly, existing solutions mostly use a single-structure monitoring target, failing to achieve layered monitoring of bedrock and soil layers. This makes them susceptible to external factors such as surface disturbance and soil slippage, leading to a shift in the monitoring benchmark. Furthermore, the monitoring points are mostly evenly distributed without adaptive adjustment based on surface deformation gradients, resulting in insufficient monitoring in key areas and waste of resources in flat areas, thus failing to guarantee the comprehensiveness and accuracy of the monitoring data. Secondly, the fusion of multi-source monitoring data mostly adopts fixed weight algorithms without dynamic adjustment based on the mining progress. This makes it impossible to balance the calculation accuracy in areas of intense and gentle mining. The calculation process does not fully incorporate the mining mechanics mechanism, and abnormal interference is not thoroughly eliminated, further affecting the measurement accuracy. Third, existing error compensation only corrects for single factors such as equipment drift and temperature, without constructing a systematic compensation system. It cannot effectively eliminate interference from non-mining factors such as rainfall and non-uniform loads, resulting in distorted monitoring data and difficulty in obtaining pure mining deformation data. Moreover, the accuracy verification is singular, and the defects are more prominent in complex geological mining areas, failing to meet the monitoring needs of high precision, real-time, full coverage, and early warning.

[0004] To address the aforementioned issues, this application presents a method and system for high-precision mapping and monitoring of surface movement and deformation in coal mines. Summary of the Invention

[0005] To address the shortcomings of the prior art mentioned in the background section, this application proposes a high-precision mapping and monitoring method and system for surface movement and deformation in coal mining. Firstly, this invention improves the monitoring target structure by adding a layered displacement difference adaptive calibration structure to achieve layered monitoring of bedrock and soil layers. Secondly, it combines non-uniform adaptive point distribution to solve the problems of unstable monitoring benchmarks and unreasonable point distribution. Then, it introduces a dynamic weighted fusion algorithm related to mining progress, combined with systematic error compensation based on mechanical mechanisms, to effectively eliminate non-mining interference and correct model parameters, thus solving the defects of low calculation accuracy and data distortion. Finally, it optimizes the early warning and handling process, clarifies the hierarchical early warning linkage measures and information push mechanism, and solves the problems of poor early warning connection and delayed response, thereby addressing the issues in the background section.

[0006] Firstly, to achieve the above objectives, this application provides a method for high-precision mapping and monitoring of surface movement and deformation in coal mines, which includes the following specific steps: Step S1: Construct a three-dimensional geomechanical model of the mining area and conduct numerical simulation of mining subsidence. Based on the simulation results, determine the location of monitoring points in the area to be monitored according to the principle of non-uniform adaptive layout. Step S2: Install a combined fixed-point monitoring pile at each monitoring point. The combined fixed-point monitoring pile includes a deep bedrock marker, a shallow soil layer marker, and a surface measurement marker. Step S3: Establish a multi-source collaborative acquisition system, using the top center coordinates of the deep bedrock marker as the starting point to achieve spatiotemporal synchronization of monitoring data; Step S4: Use a multi-source collaborative acquisition system to acquire real-time observation data from each monitoring point at a preset frequency; Step S5: Construct a high-precision dynamic solution model that integrates points and surfaces, perform joint solution on real-time observation data, and output the high-frequency three-dimensional displacement sequence of each monitoring point; Step S6: Introduce an error compensation module based on mechanical mechanisms, use measured data to reverse correct the parameters of the three-dimensional geomechanical model, eliminate abnormal interference, and obtain the compensated high-precision pure surface movement deformation value. The introduction of a mechanical mechanism-based error compensation module, which uses measured data to reverse-correct the parameters of the three-dimensional geomechanical model, eliminates abnormal interference, and obtains high-precision, pure surface movement deformation values ​​after compensation, includes the following steps: Step S61: Identify and remove abnormal interferences caused by non-collection factors in the monitoring data. Non-collection factors include rainfall, temperature changes, equipment drift, and non-uniform loads. For different types of interference, corresponding correction methods are adopted. For example, temperature interference is corrected by collecting relevant environmental data through dedicated sensors, and equipment drift interference is eliminated by periodically calibrating the equipment. This ensures the accuracy of interference removal, guarantees the authenticity of the monitoring data, and lays the foundation for subsequent error compensation. Step S62: Using the rock mass elastic modulus, Poisson's ratio, and mining-induced thickness as parameters to be corrected, an iterative algorithm is used to correct the parameters. The calculated residual δ is used as the convergence criterion. Iteration stops when δ is less than or equal to a preset threshold to ensure that the model parameters are corrected in place, so that the model prediction results tend to be consistent with the measured data, thereby improving the prediction accuracy of the model. The formula for calculating the calculated residual δ is as follows: ; Where n is the number of monitoring points, Wi is the measured displacement value of the i-th monitoring point, and Wpi is the model-predicted displacement value of the i-th monitoring point; Step S63: Based on the measured data after removing interference and the corrected model parameters, the compensation calculation for the pure surface movement deformation value caused solely by coal mining activities is performed using the pure surface movement deformation value calculation formula. The compensation calculation formula for the pure surface movement deformation value is as follows: ; in, The value of pure surface movement deformation after compensation. The measured displacement value at the monitoring point. The displacement disturbance value is caused by factors other than mining. This refers to the displacement correction amount after the model parameters have been adjusted. Step S64: The root mean square error (RMSE) is used to verify the effectiveness of the compensated pure surface movement deformation value, and a high-precision pure surface movement deformation value is output to provide reliable input for subsequent deformation parameter calculation. The formula for the root mean square error (RMSE) is: ; Where n is the number of monitoring points, Let i be the pure deformation value at the i-th monitoring point. This represents the actual deformation value generated during sampling at the i-th monitoring point; Step S7: Based on the output high-precision pure surface movement deformation value, calculate the movement deformation parameters, identify abnormal areas and conduct graded early warning, realize the final application of monitoring data, and ensure the safety of coal mining.

[0007] Based on the above scheme, the preferred method is as follows: the non-uniform adaptive layout principle and the specific operation of constructing the three-dimensional geomechanical model in step S1 are as follows: Non-uniform adaptive deployment principle: Based on the numerical simulation results of mining subsidence, the spacing between monitoring points is reduced in areas of predicted severe surface movement and deformation, and the spacing between monitoring points is increased in areas of gentle deformation gradient. At the same time, the number of monitoring points is increased in key areas such as surface crack zones, mining boundary corners, and stop mining lines to ensure full coverage and no omissions in monitoring key deformation areas. Three-dimensional geomechanical model construction: The model is constructed using professional numerical simulation software. Relevant geological and mining parameters of the mining area are input, and the model is calibrated to ensure that the numerical simulation results are consistent with the actual mining subsidence patterns, providing a scientific and accurate theoretical basis for the layout of monitoring points.

[0008] Based on the above scheme, the specific structure and installation requirements of the combined fixed-point monitoring piles in step S2 are as follows: Structural Requirements: The deep bedrock marker, shallow soil marker, and surface measurement marker adopt a coaxial structure to strictly ensure the coaxiality of the three. Each is equipped with a suitable measurement target, which can realize synchronous and high-precision measurement of the relative displacement between the three markers. At the same time, an innovative adaptive calibration structure for layered displacement difference is added. An elastic buffer component and displacement sensing unit are added between the shallow soil marker and the deep bedrock marker to collect the relative displacement difference between the two markers in real time and automatically calibrate the coupling error between soil settlement and bedrock displacement. This solves the technical pain point of traditional coaxial monitoring piles that cannot distinguish the independent deformation of soil and bedrock and are prone to coupling interference, further improving the monitoring accuracy. Installation requirements: Deep bedrock markers should be anchored into stable bedrock, using appropriate anchoring methods to ensure anchoring reliability and prevent surface disturbance from affecting the benchmark. Shallow soil markers should be buried to a suitable soil depth, avoiding loose topsoil layers to ensure monitoring stability. Surface measurement markers should be equipped with a forced centering structure to improve measurement accuracy. An anti-disturbance protection structure should be installed on the outside of the pile to effectively avoid interference from various external factors such as mining compression, soil slippage, and frost heave, ensuring the long-term stable operation of the monitoring piles.

[0009] Based on the above scheme, in step S3, the top center coordinates of the deep bedrock marker are used as the starting point to achieve spatiotemporal synchronization of monitoring data. The specific operation is as follows: By using a professional time synchronization module to unify the measurement time benchmark, the time synchronization of each monitoring device is ensured, the spatiotemporal consistency of multi-source monitoring data is guaranteed, and the foundation is laid for subsequent data fusion and calculation. The three-dimensional coordinates of all monitoring points are uniformly converted to an independent engineering coordinate system with the deep bedrock marker as the origin. At the same time, the conversion method between this independent engineering coordinate system and the national geodetic coordinate system is provided to improve the universality and practicality of the monitoring data. Regularly conduct stability self-checks on deep bedrock benchmarks. If the test results exceed the preset error threshold, immediately recalibrate the benchmarks to continuously ensure the stability and reliability of the monitoring benchmarks, providing core support for high-precision monitoring.

[0010] Based on the above scheme, the preferred embodiment of the multi-source collaborative acquisition system includes a continuously operating reference station, automated monitoring equipment, surface deformation monitoring unit, and data transmission module. Each unit works together to achieve point-surface collaborative monitoring. The continuously operating reference station provides an absolute coordinate benchmark, ensuring the absolute accuracy of the monitoring data; the automated monitoring equipment has automatic calibration, automatic observation, and automatic data uploading functions, used for high-precision relative displacement measurement, improving monitoring efficiency and accuracy; the surface deformation monitoring unit is used to achieve comprehensive monitoring of surface deformation in the area to be monitored, taking into account both point and area coverage; the data transmission module ensures that monitoring data is uploaded in real time and stably, avoiding data loss or delay, and providing timely and reliable data support for subsequent data processing.

[0011] Based on the above scheme, the specific solution method of the high-precision dynamic solution model for point-surface fusion constructed in step S5 is as follows: a. Adaptive filtering combined with interpolation algorithm is adopted to achieve deep fusion of point monitoring data and surface monitoring data, giving full play to the advantages of high precision of point monitoring and full coverage of surface monitoring. An innovative dynamic weight adaptive adjustment algorithm related to mining progress is introduced. According to the mining advance speed and working face position, the fusion weight of point monitoring data and surface monitoring data is dynamically adjusted in real time. In areas with rapid mining advance, the weight of point monitoring is increased to 60%-70%, and in areas with gentle mining advance, the weight of surface monitoring is increased to 55%-65%. This solves the problem that traditional fixed weight fusion cannot adapt to the dynamic changes of mining and is prone to calculation deviation. It is used to improve the calculation accuracy of different mining stages. b. Based on the accuracy characteristics of point monitoring data and area monitoring data, scientifically assign reasonable fusion weights to both to further improve the accuracy of the fusion solution results; c. During the solution process, preset criteria are used to remove outliers from the observed data, and reasonable spatiotemporal constraints are set to effectively avoid the impact of outliers on the solution results and ensure the reliability of the solution results. d. Output high-frequency three-dimensional displacement sequences of each monitoring point, taking into account both high accuracy and high frequency of monitoring, to meet the needs of real-time monitoring of surface deformation in coal mining.

[0012] Based on the above scheme, the preferred embodiment, which calculates the movement deformation parameters based on the output high-precision pure surface movement deformation values, identifies abnormal areas for graded early warning, and realizes the final application of monitoring data to ensure coal mine safety, includes the following steps: Step S71: Calculate the displacement deformation parameters, which include the settlement Fa, horizontal displacement Fb, tilt value Fc, curvature Fd, and horizontal deformation value Fe. The calculation formulas for the settlement Fa, horizontal displacement Fb, tilt value Fc, curvature Fd, and horizontal deformation value Fe are as follows: ; Where Za is the initial elevation of the monitoring point, and Zt is the elevation of the monitoring point at time t; ; Where Xa and Ya are the initial planar coordinates of the monitoring point, and Xt and Yt are the planar coordinates of the monitoring point at time t; ; Where W1 and W2 are the subsidence amounts of two adjacent monitoring points, and L is the horizontal distance between two adjacent monitoring points; ; Wherein, G1 and G2 are the inclination values ​​of two adjacent monitoring segments, and S is the average horizontal distance between two adjacent monitoring segments; ; Where U1 and U2 are the horizontal displacements of two adjacent monitoring points, and L is the horizontal distance between two adjacent monitoring points; Step S72: Based on the calculation results of the above-mentioned moving deformation parameters, combined with the surface moving deformation law and the geological conditions of the mining area, a scientific threshold for identifying abnormal areas is set, and areas that meet the threshold conditions are accurately identified as abnormal areas and multi-level early warnings are issued. Step S73: Synchronously push the early warning information to the monitoring terminal and relevant personnel through the data transmission module; Step S74: For different levels of early warning, formulate corresponding joint response measures. Level 1 early warning focuses on data monitoring and encryption. Level 2 early warning initiates on-site inspection and equipment re-inspection. Level 3 early warning stops related operations in the mining area, organizes personnel evacuation, and activates the emergency response plan to achieve early detection and early handling of risks and ensure the safety of coal mining.

[0013] Secondly, this application provides a high-precision mapping and monitoring system for fixed-point surface movement and deformation in coal mines, which specifically includes: a monitoring point deployment subsystem, a multi-source collaborative acquisition subsystem, a data processing and calculation subsystem, and an analysis and early warning subsystem; The monitoring point deployment subsystem includes a combined fixed-point monitoring pile, which is a coaxial structure. Each monitoring point is equipped with an interference correction device and an anti-disturbance protection device. The deployment density of the monitoring piles conforms to the non-uniform adaptive deployment principle, providing a stable monitoring carrier for high-precision monitoring. The multi-source collaborative acquisition subsystem includes a continuously operating reference station, automated monitoring equipment, a surface deformation monitoring unit, and a data transmission module. The continuously operating reference station provides an absolute coordinate benchmark to ensure the absolute accuracy of the monitoring data; the automated monitoring equipment has automatic calibration, automatic observation, and automatic data uploading functions, used for high-precision relative displacement measurement, improving monitoring efficiency and accuracy; the surface deformation monitoring unit is used to achieve comprehensive monitoring of surface deformation in the area to be monitored, taking into account both point and area coverage; the data transmission module ensures that the monitoring data is uploaded in real time and stably, avoiding data loss or delay, and providing timely and reliable data support for subsequent data processing; The data processing and calculation subsystem includes a data synchronization module, a point-area fusion calculation module, and a dynamic error compensation module. The data synchronization module is used to unify the time base and calculate the coordinates, and periodically perform self-checks on the stability of the reference points; the point-surface fusion solution module is used to output high-frequency three-dimensional displacement sequences using solution algorithms; the dynamic error compensation module is used to use error compensation methods and formulas to reverse correct model parameters, eliminate interference, output clean deformation data, and complete validity verification. The analysis and early warning subsystem includes a deformation parameter calculation module, a four-dimensional visualization module, and a hierarchical early warning module. The deformation parameter calculation module is used to accurately calculate various movement deformation parameters; the four-dimensional visualization module is used to display the spatiotemporal evolution process of surface movement deformation in real time, making it easier for staff to intuitively grasp the deformation patterns; the graded early warning module is used to identify abnormal areas, issue early warning information according to preset early warning standards, and link emergency response measures.

[0014] Thirdly, this application provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the aforementioned method for high-precision mapping and monitoring of surface movement and deformation in coal mining by calling computer programs stored in the memory.

[0015] Fourthly, this application provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the above-described method for high-precision mapping and monitoring of surface movement and deformation in coal mining.

[0016] Compared with the prior art, the beneficial effects of the present invention are: I. Adopting the principle of non-uniform adaptive deployment, and combining the results of numerical simulation of mining subsidence, the monitoring points are densely distributed in areas with severe deformation and sparsely distributed in areas with gentle deformation. At the same time, key areas such as crack zones and boundary corners are covered. This not only ensures the monitoring accuracy of key areas, but also avoids the waste of monitoring resources, ensuring the comprehensiveness and relevance of monitoring. It adapts to the actual situation of the surface deformation gradient difference in the mining area. An innovative adaptive calibration structure for layered displacement difference is added to effectively distinguish the independent deformation of soil layers and bedrock, eliminate coupling interference, and further improve the monitoring accuracy. This is different from the single monitoring mode of traditional coaxial monitoring piles. Second, the top center coordinates of the deep bedrock marker are used as the starting point and anchored into the stable bedrock to effectively avoid the impact of surface disturbance. At the same time, a self-checking mechanism for the stability of the benchmark point is set up, and the benchmark is calibrated regularly to ensure the long-term stability of the monitoring benchmark. In addition, an independent engineering coordinate system is established and a conversion method with the national geodetic coordinate system is provided to improve the universality and practicality of the monitoring data and provide core support for high-precision monitoring. Third, by constructing a multi-source collaborative acquisition system, clarifying the functional division of each acquisition device, achieving spatiotemporal synchronization through professional time synchronization, and using adaptive filtering combined with interpolation algorithms to achieve deep fusion of point and area data, we can give full play to the advantages of high precision of point monitoring and full coverage of area monitoring, improve the integrity and accuracy of monitoring data, take into account both monitoring accuracy and coverage, and innovatively introduce a dynamic weight adaptive adjustment algorithm related to mining progress to achieve dynamic adaptation of fusion weight with mining progress, thus solving the problem of calculation deviation in traditional fixed weight fusion. Fourth, by introducing an error compensation module based on mechanical mechanisms, not only can the interference of various non-mining factors be eliminated, but also the parameters of the three-dimensional geomechanical model can be corrected in reverse through measured data, forming a closed loop of simulation-monitoring-correction-verification, and obtaining pure mining deformation data. This effectively solves the problem of data distortion in existing technologies and can meet the high-precision monitoring needs of coal mining. Fifth, by quantifying surface deformation parameters through professional calculation formulas, accurately identifying abnormal areas, establishing a multi-level early warning mechanism, clarifying the identification standards for abnormal areas and early warning linkage measures, ensuring timely early warning response, quickly detecting abnormal surface deformation and initiating emergency response, effectively preventing safety accidents caused by mining-induced surface deformation, and effectively ensuring safe production in coal mines. Moreover, it does not involve complex special equipment, the data flow is clear, and it can be directly applied to monitoring surface movement and deformation in coal mines. It can be adapted to monitoring scenarios in different mining areas and has strong practicality and promotional value. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram of the overall process of a high-precision mapping and monitoring method for surface movement and deformation in coal mining according to the present invention. Figure 2 This is a flowchart illustrating step S6 in a method for high-precision mapping and monitoring of surface movement and deformation in coal mining according to the present invention. Figure 3 This is a schematic diagram of the framework of a high-precision mapping and monitoring system for surface movement and deformation in coal mining, according to the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1 To address the technical problems raised in the background art, this application provides a preferred embodiment: such as Figure 1 - Figure 3 As shown, a method for high-precision mapping and monitoring of surface movement and deformation in coal mines includes the following specific steps: Step S1: Construct a three-dimensional geomechanical model of the mining area and conduct numerical simulation of mining subsidence. Based on the simulation results, determine the location of monitoring points in the area to be monitored according to the principle of non-uniform adaptive layout. Step S2: Install a combined fixed-point monitoring pile at each monitoring point. The combined fixed-point monitoring pile includes a deep bedrock marker, a shallow soil layer marker, and a surface measurement marker. Step S3: Establish a multi-source collaborative acquisition system, using the top center coordinates of the deep bedrock marker as the starting point to achieve spatiotemporal synchronization of monitoring data; Step S4: Use a multi-source collaborative acquisition system to acquire real-time observation data from each monitoring point at a preset frequency; Step S5: Construct a high-precision dynamic solution model that integrates points and surfaces, perform joint solution on real-time observation data, and output the high-frequency three-dimensional displacement sequence of each monitoring point; Step S6: Introduce an error compensation module based on mechanical mechanisms, use measured data to reverse correct the parameters of the three-dimensional geomechanical model, eliminate abnormal interference, and obtain the compensated high-precision pure surface movement deformation value. The introduction of a mechanical mechanism-based error compensation module, which uses measured data to reverse-correct the parameters of the three-dimensional geomechanical model, eliminates abnormal interference, and obtains high-precision, pure surface movement deformation values ​​after compensation, includes the following steps: Step S61: Identify and remove abnormal interferences caused by non-collection factors in the monitoring data. Non-collection factors include rainfall, temperature changes, equipment drift, and non-uniform loads. For different types of interference, corresponding correction methods are adopted. For example, temperature interference is corrected by collecting relevant environmental data through dedicated sensors, and equipment drift interference is eliminated by periodically calibrating the equipment. This ensures the accuracy of interference removal, guarantees the authenticity of the monitoring data, and lays the foundation for subsequent error compensation. Step S62: Using the rock mass elastic modulus, Poisson's ratio, and mining-induced thickness as parameters to be corrected, an iterative algorithm is used to correct the parameters. The calculated residual δ is used as the convergence criterion. Iteration stops when δ is less than or equal to a preset threshold to ensure that the model parameters are corrected in place, so that the model prediction results tend to be consistent with the measured data, thereby improving the prediction accuracy of the model. The formula for calculating the calculated residual δ is as follows: ; Where n is the number of monitoring points, Wi is the measured displacement value of the i-th monitoring point, and Wpi is the model-predicted displacement value of the i-th monitoring point; Step S63: Based on the measured data after removing interference and the corrected model parameters, the compensation calculation for the pure surface movement deformation value caused solely by coal mining activities is performed using the pure surface movement deformation value calculation formula. The compensation calculation formula for the pure surface movement deformation value is as follows: ; in, The value of pure surface movement deformation after compensation. The measured displacement value at the monitoring point. The displacement disturbance value is caused by non-mining factors, and the displacement correction amount is after the model parameters are corrected. Step S64: The root mean square error (RMSE) is used to verify the effectiveness of the compensated pure surface movement deformation value, and a high-precision pure surface movement deformation value is output to provide reliable input for subsequent deformation parameter calculation. The formula for the root mean square error (RMSE) is: ; Where n is the number of monitoring points, Let i be the pure deformation value at the i-th monitoring point. This represents the actual deformation value generated during sampling at the i-th monitoring point; Step S7: Based on the output high-precision pure surface movement deformation value, calculate the movement deformation parameters, identify abnormal areas and conduct graded early warning, realize the final application of monitoring data, and ensure the safety of coal mining.

[0020] The advantages of this embodiment compared to the prior art are as follows: First, by improving the structure of the monitoring target and adding a layered displacement difference adaptive calibration structure, layered monitoring of bedrock and soil layers can be achieved. Second, by combining non-uniform adaptive point distribution, the problems of unstable monitoring benchmarks and unreasonable point distribution can be solved. Then, by introducing a dynamic weight fusion algorithm related to mining progress and combining it with systematic error compensation based on mechanical mechanisms, non-mining interference can be effectively eliminated, model parameters can be corrected, and the defects of low solution accuracy and data distortion can be solved. Finally, by optimizing the early warning and handling process and clarifying the hierarchical early warning linkage measures and information push mechanism, the problems of poor early warning connection and delayed response can be solved.

[0021] Furthermore: In an optional embodiment, the specific operations of the non-uniform adaptive layout principle and the construction of the three-dimensional geomechanical model in step S1 are as follows: Non-uniform adaptive deployment principle: Based on the numerical simulation results of mining subsidence, the spacing between monitoring points is reduced in areas of predicted severe surface movement and deformation, and the spacing between monitoring points is increased in areas of gentle deformation gradient. At the same time, the number of monitoring points is increased in key areas such as surface crack zones, mining boundary corners, and stop mining lines to ensure full coverage and no omissions in monitoring key deformation areas. Three-dimensional geomechanical model construction: The model is constructed using professional numerical simulation software. Relevant geological and mining parameters of the mining area are input, and the model is calibrated to ensure that the numerical simulation results are consistent with the actual mining subsidence patterns, providing a scientific and accurate theoretical basis for the layout of monitoring points.

[0022] The advantages of this embodiment compared to the prior art are as follows: It adopts a non-uniform adaptive layout principle, combines the results of mining subsidence numerical simulation, and densifies the layout of monitoring points in areas with severe deformation and sparsely distributes them in areas with gentle deformation. At the same time, it covers key areas such as crack zones and boundary corners, which not only ensures the monitoring accuracy of key areas, but also avoids the waste of monitoring resources, ensuring the comprehensiveness and relevance of monitoring. It adapts to the actual situation of surface deformation gradient differences in mining areas, and innovatively adds a layered displacement difference adaptive calibration structure, which effectively distinguishes the independent deformation of soil layers and bedrock, eliminates coupling interference, and further improves monitoring accuracy, which is different from the single monitoring mode of traditional coaxial monitoring piles.

[0023] In an optional embodiment, the specific structure and installation requirements of the combined fixed-point monitoring piles described in step S2 are as follows: Structural Requirements: The deep bedrock marker, shallow soil marker, and surface measurement marker adopt a coaxial structure to strictly ensure the coaxiality of the three. Each is equipped with a suitable measurement target, which can realize synchronous and high-precision measurement of the relative displacement between the three markers. At the same time, an innovative adaptive calibration structure for layered displacement difference is added. An elastic buffer component and displacement sensing unit are added between the shallow soil marker and the deep bedrock marker to collect the relative displacement difference between the two markers in real time and automatically calibrate the coupling error between soil settlement and bedrock displacement. This solves the technical pain point of traditional coaxial monitoring piles that cannot distinguish the independent deformation of soil and bedrock and are prone to coupling interference, further improving the monitoring accuracy. Installation requirements: Deep bedrock markers should be anchored into stable bedrock, using appropriate anchoring methods to ensure anchoring reliability and prevent surface disturbance from affecting the benchmark. Shallow soil markers should be buried to a suitable soil depth, avoiding loose topsoil layers to ensure monitoring stability. Surface measurement markers should be equipped with a forced centering structure to improve measurement accuracy. An anti-disturbance protection structure should be installed on the outside of the pile to effectively avoid interference from various external factors such as mining compression, soil slippage, and frost heave, ensuring the long-term stable operation of the monitoring piles.

[0024] In an optional embodiment, step S3 uses the top center coordinates of the deep bedrock marker as the starting point to achieve spatiotemporal synchronization of the monitoring data. The specific operation is as follows: By using a professional time synchronization module to unify the measurement time benchmark, the time synchronization of each monitoring device is ensured, the spatiotemporal consistency of multi-source monitoring data is guaranteed, and the foundation is laid for subsequent data fusion and calculation. The three-dimensional coordinates of all monitoring points are uniformly converted to an independent engineering coordinate system with the deep bedrock marker as the origin. At the same time, the conversion method between this independent engineering coordinate system and the national geodetic coordinate system is provided to improve the universality and practicality of the monitoring data. Regularly conduct stability self-checks on deep bedrock benchmarks. If the test results exceed the preset error threshold, immediately recalibrate the benchmarks to continuously ensure the stability and reliability of the monitoring benchmarks, providing core support for high-precision monitoring.

[0025] The advantages of this embodiment compared to the prior art are as follows: using the top center coordinates of the deep bedrock marker as the starting reference, anchoring into stable bedrock, effectively avoiding the influence of surface disturbance, setting up a self-checking mechanism for the stability of the reference point, periodically calibrating the reference, ensuring the long-term stability of the monitoring reference, establishing an independent engineering coordinate system and providing a conversion method with the national geodetic coordinate system, improving the universality and practicality of the monitoring data, and providing core guarantee for high-precision monitoring.

[0026] In one optional embodiment, the multi-source collaborative acquisition system includes a continuously operating reference station, automated monitoring equipment, a surface deformation monitoring unit, and a data transmission module. The units work together to achieve point-to-surface collaborative monitoring. The continuously operating reference station provides an absolute coordinate benchmark, ensuring the absolute accuracy of the monitoring data; the automated monitoring equipment has automatic calibration, automatic observation, and automatic data uploading functions, used for high-precision relative displacement measurement, improving monitoring efficiency and accuracy; the surface deformation monitoring unit is used to achieve comprehensive monitoring of surface deformation in the area to be monitored, taking into account both point and area coverage; the data transmission module ensures that monitoring data is uploaded in real time and stably, avoiding data loss or delay, and providing timely and reliable data support for subsequent data processing.

[0027] The advantages of this embodiment compared to the prior art are as follows: by constructing a multi-source collaborative acquisition system, the functional division of each acquisition device is clearly defined, spatiotemporal synchronization is achieved through professional time synchronization, and deep fusion of point and area data is achieved by using adaptive filtering combined with interpolation algorithms. This fully leverages the advantages of high precision in point monitoring and full coverage in area monitoring, improving the integrity and accuracy of monitoring data while balancing monitoring accuracy and coverage. Furthermore, it innovatively introduces a dynamic weight adaptive adjustment algorithm related to mining progress, enabling the fusion weight to dynamically adapt to the mining progress, thus solving the problem of calculation deviation in traditional fixed-weight fusion.

[0028] Furthermore: In an optional embodiment, the specific solution method for the high-precision dynamic solution model of point-surface fusion constructed in step S5 is as follows: a. Adaptive filtering combined with interpolation algorithm is adopted to achieve deep fusion of point monitoring data and surface monitoring data, giving full play to the advantages of high precision of point monitoring and full coverage of surface monitoring. An innovative dynamic weight adaptive adjustment algorithm related to mining progress is introduced. According to the mining advance speed and working face position, the fusion weight of point monitoring data and surface monitoring data is dynamically adjusted in real time. In areas with rapid mining advance, the weight of point monitoring is increased to 60%-70%, and in areas with gentle mining advance, the weight of surface monitoring is increased to 55%-65%. This solves the problem that traditional fixed weight fusion cannot adapt to the dynamic changes of mining and is prone to calculation deviation. It is used to improve the calculation accuracy of different mining stages. b. Based on the accuracy characteristics of point monitoring data and area monitoring data, scientifically assign reasonable fusion weights to both to further improve the accuracy of the fusion solution results; c. During the solution process, preset criteria are used to remove outliers from the observed data, and reasonable spatiotemporal constraints are set to effectively avoid the impact of outliers on the solution results and ensure the reliability of the solution results. d. Output high-frequency three-dimensional displacement sequences of each monitoring point, taking into account both high accuracy and high frequency of monitoring, to meet the needs of real-time monitoring of surface deformation in coal mining.

[0029] It should be noted that point monitoring data is collected every hour by automated monitoring equipment such as measuring robots, while area monitoring data is acquired by time-series InSAR satellites according to the revisit period.

[0030] In an optional embodiment, based on the output high-precision pure surface movement deformation values, movement deformation parameters are calculated, and abnormal areas are identified for graded early warning, realizing the final application of monitoring data and ensuring coal mine safety, including the following steps: Step S71: Calculate the displacement deformation parameters, which include the settlement Fa, horizontal displacement Fb, tilt value Fc, curvature Fd, and horizontal deformation value Fe. The calculation formulas for the settlement Fa, horizontal displacement Fb, tilt value Fc, curvature Fd, and horizontal deformation value Fe are as follows: ; Where Za is the initial elevation of the monitoring point, and Zt is the elevation of the monitoring point at time t; ; Where Xa and Ya are the initial planar coordinates of the monitoring point, and Xt and Yt are the planar coordinates of the monitoring point at time t; ; Where W1 and W2 are the subsidence amounts of two adjacent monitoring points, and L is the horizontal distance between two adjacent monitoring points; ; Wherein, G1 and G2 are the inclination values ​​of two adjacent monitoring segments, and S is the average horizontal distance between two adjacent monitoring segments; ; Where U1 and U2 are the horizontal displacements of two adjacent monitoring points, and L is the horizontal distance between two adjacent monitoring points; Step S72: Based on the calculation results of the above-mentioned moving deformation parameters, combined with the surface moving deformation law and the geological conditions of the mining area, a scientific threshold for identifying abnormal areas is set, and areas that meet the threshold conditions are accurately identified as abnormal areas and multi-level early warnings are issued. Step S73: Synchronously push the early warning information to the monitoring terminal and relevant personnel through the data transmission module; Step S74: For different levels of early warning, formulate corresponding joint response measures. Level 1 early warning focuses on data monitoring and encryption. Level 2 early warning initiates on-site inspection and equipment re-inspection. Level 3 early warning stops related operations in the mining area, organizes personnel evacuation, and activates the emergency response plan to achieve early detection and early handling of risks and ensure the safety of coal mining.

[0031] The advantages of this embodiment compared to existing technologies are as follows: it quantifies surface deformation parameters through professional calculation formulas, accurately identifies abnormal areas, establishes a multi-level early warning mechanism, clarifies the identification standards for abnormal areas and early warning linkage measures, ensures timely early warning response, can quickly detect abnormal surface deformation and initiate emergency response, can effectively prevent safety accidents caused by mining-induced surface deformation, can effectively guarantee safe production in coal mines, and does not involve complex special equipment. The data flow is clear and can be directly applied to the monitoring of surface movement and deformation in coal mines. It can be adapted to monitoring scenarios in different mining areas and has strong practicality and promotional value.

[0032] In specific implementation: First, collect geological and mining parameters such as coal seam burial depth, rock mass elastic modulus, and Poisson's ratio of the target mining area. Use FLAC3D software to construct a three-dimensional geomechanical model to simulate the mining subsidence process. Set up monitoring points according to the non-uniform adaptive principle. Set the spacing between points in areas with severe deformation to 50m, in areas with gentle deformation to 100m, and in crack zones and at the stop mining line to 30m. Then, a combined fixed-point monitoring pile is installed at each monitoring point. The deep bedrock marker is anchored 10m into the stable bedrock, and the shallow soil marker is buried 5m deep. A rubber buffer assembly and displacement sensing unit are added between the two to achieve layered displacement calibration. A protective sleeve is installed on the outside of the pile to prevent disturbance. Next, a multi-source collaborative acquisition system was built. Based on the continuously operating reference station, the automated monitoring equipment collected data once every hour. Time and space synchronization was achieved through GPS time synchronization, and the data was uploaded to the processing terminal via a wireless transmission module. Secondly, a dynamic weighting algorithm related to the mining progress is adopted to determine the weights of point monitoring and surface monitoring, and the data is jointly calculated. Through the error compensation module, the interference of rainfall and temperature is eliminated, the rock mass mechanical parameters are iteratively corrected, the calculation residual is controlled within ±0.5mm, and the pure deformation data is output. Finally, based on the high-precision pure surface movement deformation values ​​output, movement deformation parameters are calculated. Then, based on the calculation results of movement deformation parameters, combined with the surface movement deformation patterns and geological conditions of the mining area, a scientific threshold for identifying abnormal areas is set. Areas that meet the threshold conditions are accurately identified as abnormal areas and multi-level early warnings are issued. At the same time, the early warning information is synchronously pushed to the monitoring terminal and relevant personnel through the data transmission module. Secondly, corresponding linkage and response measures are formulated for different levels of early warning. Level 1 early warning focuses on data monitoring encryption, Level 2 early warning initiates on-site inspection and equipment re-inspection, and Level 3 early warning stops relevant operations in the mining area, organizes personnel evacuation, and activates the emergency response plan, so as to achieve early detection and early handling of risks and ensure the safety of coal mining.

[0033] Example 2 Based on the same inventive concept as in Embodiment 1, such as Figure 1 As shown in the figure, this embodiment provides a high-precision mapping and monitoring system for fixed-point surface movement and deformation in coal mines, which specifically includes: a monitoring point deployment subsystem, a multi-source collaborative acquisition subsystem, a data processing and calculation subsystem, and an analysis and early warning subsystem; The monitoring point deployment subsystem includes a combined fixed-point monitoring pile, which is a coaxial structure. Each monitoring point is equipped with an interference correction device and an anti-disturbance protection device. The deployment density of the monitoring piles conforms to the principle of non-uniform adaptive deployment, providing a stable monitoring carrier for high-precision monitoring. The multi-source collaborative acquisition subsystem includes a continuously operating reference station, automated monitoring equipment, surface deformation monitoring unit, and data transmission module; The continuously operating reference station provides an absolute coordinate benchmark to ensure the absolute accuracy of the monitoring data; the automated monitoring equipment has automatic calibration, automatic observation, and automatic data uploading functions, used for high-precision relative displacement measurement, improving monitoring efficiency and accuracy; the surface deformation monitoring unit is used to achieve comprehensive monitoring of surface deformation in the area to be monitored, taking into account both point and area coverage; the data transmission module ensures that the monitoring data is uploaded in real time and stably, avoiding data loss or delay, and providing timely and reliable data support for subsequent data processing; The data processing and calculation subsystem includes a data synchronization module, a point-area fusion calculation module, and a dynamic error compensation module; The data synchronization module is used to unify the time base and calculate the coordinates, and periodically perform self-checks on the stability of the reference points; the point-surface fusion solution module is used to output high-frequency three-dimensional displacement sequences using solution algorithms; the dynamic error compensation module is used to use error compensation methods and formulas to reverse correct model parameters, eliminate interference, output clean deformation data, and complete validity verification. The analysis and early warning subsystem includes a deformation parameter calculation module, a four-dimensional visualization module, and a graded early warning module; The deformation parameter calculation module is used to accurately calculate various movement deformation parameters; the four-dimensional visualization module is used to display the spatiotemporal evolution process of surface movement deformation in real time, making it easier for staff to intuitively grasp the deformation patterns; the graded early warning module is used to identify abnormal areas, issue early warning information according to preset early warning standards, and link emergency response measures.

[0034] The parameters and steps for implementing the corresponding functions of each unit module in the above-described high-precision mapping and monitoring system for surface movement and deformation in coal mining according to the present invention can be referred to the parameters and steps in the embodiments of the method for high-precision mapping and monitoring of surface movement and deformation in coal mining described above, and will not be repeated here.

[0035] Example 3 Based on the same inventive concept as Embodiment 1, this embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the above-described method for high-precision mapping and monitoring of surface movement and deformation in coal mining by calling the computer program stored in the memory.

[0036] It should be noted that all computer programs for a method of high-precision mapping and monitoring of surface movement and deformation in coal mining are implemented using the C language.

[0037] Example 4 Based on the same inventive concept as in Embodiment 1, this embodiment proposes a computer-readable storage medium having an erasable and rewritable computer program stored thereon. When a computer program runs on a computer device, it causes the computer device to execute the aforementioned method for high-precision mapping and monitoring of surface movement and deformation in coal mining.

[0038] For example, computer-readable storage media can be read-only memory, random access memory, read-only optical disc, magnetic tape, floppy disk, and optical data storage devices.

[0039] The various embodiments in this invention are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. In particular, the embodiments for IoT devices and media are relatively simple in description because they are fundamentally similar to the method embodiments; relevant parts can be referred to the descriptions in the method embodiments.

[0040] The systems, media, and methods provided in the embodiments of the present invention are in one-to-one correspondence. Therefore, the systems and media also have similar beneficial technical effects as their corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the systems and media will not be repeated here.

[0041] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0042] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0043] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0044] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0045] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0046] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0047] Computer-readable media include both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0048] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. The above are merely embodiments of the present invention and are not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the present invention should be included within the scope of the claims of the present invention.

Claims

1. A method for high-precision mapping and monitoring of surface movement and deformation in coal mines, characterized in that, Includes the following steps: Step S1: Construct a three-dimensional geomechanical model of the mining area and conduct numerical simulation of mining subsidence. Based on the simulation results, determine the location of monitoring points in the area to be monitored according to the principle of non-uniform adaptive layout. Step S2: Install a combined fixed-point monitoring pile at each monitoring point. The combined fixed-point monitoring pile includes a deep bedrock marker, a shallow soil layer marker, and a surface measurement marker. Step S3: Establish a multi-source collaborative acquisition system, using the top center coordinates of the deep bedrock marker as the starting point to achieve spatiotemporal synchronization of monitoring data; Step S4: Use a multi-source collaborative acquisition system to acquire real-time observation data from each monitoring point at a preset frequency; Step S5: Construct a high-precision dynamic solution model that integrates points and surfaces, perform joint solution on real-time observation data, and output the high-frequency three-dimensional displacement sequence of each monitoring point; Step S6: Introduce an error compensation module based on mechanical mechanisms, use measured data to reverse correct the parameters of the three-dimensional geomechanical model, eliminate abnormal interference, and obtain the compensated high-precision pure surface movement deformation value. The introduction of a mechanical mechanism-based error compensation module, which uses measured data to reverse-correct the parameters of the three-dimensional geomechanical model, eliminates abnormal interference, and obtains high-precision, pure surface movement deformation values ​​after compensation, includes the following steps: Step S61: Identify and remove abnormal interferences caused by non-collection factors in the monitoring data. Non-collection factors include rainfall, temperature changes, equipment drift, and non-uniform loads. For different types of interference, corresponding correction methods are adopted. For example, temperature interference is corrected by collecting relevant environmental data through dedicated sensors, and equipment drift interference is eliminated by periodically calibrating the equipment. This ensures the accuracy of interference removal, guarantees the authenticity of the monitoring data, and lays the foundation for subsequent error compensation. Step S62: Using the rock mass elastic modulus, Poisson's ratio, and mining-induced thickness as parameters to be corrected, an iterative algorithm is used to correct the parameters. The calculated residual δ is used as the convergence criterion. Iteration stops when δ is less than or equal to a preset threshold to ensure that the model parameters are corrected in place, so that the model prediction results tend to be consistent with the measured data, thereby improving the prediction accuracy of the model. The formula for calculating the calculated residual δ is as follows: ； Where n is the number of monitoring points, Wi is the measured displacement value of the i-th monitoring point, and Wpi is the model-predicted displacement value of the i-th monitoring point; Step S63: Based on the measured data after removing interference and the corrected model parameters, the compensation calculation for the pure surface movement deformation value caused solely by coal mining activities is performed using the pure surface movement deformation value calculation formula. The compensation calculation formula for the pure surface movement deformation value is as follows: ； in, The value of pure surface movement deformation after compensation. The measured displacement value at the monitoring point. The displacement disturbance value is caused by factors other than mining. This refers to the displacement correction amount after the model parameters have been adjusted. Step S64: The root mean square error (RMSE) is used to verify the effectiveness of the compensated pure surface movement deformation value, and a high-precision pure surface movement deformation value is output to provide reliable input for subsequent deformation parameter calculation. The formula for the root mean square error (RMSE) is: ； Where n is the number of monitoring points, Let i be the pure deformation value at the i-th monitoring point. This represents the actual deformation value generated during sampling at the i-th monitoring point; Step S7: Based on the output high-precision pure surface movement deformation value, calculate the movement deformation parameters, identify abnormal areas and conduct graded early warning, realize the final application of monitoring data, and ensure the safety of coal mining.

2. The method for high-precision mapping and monitoring of surface movement and deformation in coal mining according to claim 1, characterized in that: The specific operations for the non-uniform adaptive layout principle and the construction of the three-dimensional geomechanical model in step S1 are as follows: Non-uniform adaptive deployment principle: Based on the numerical simulation results of mining subsidence, the spacing between monitoring points is reduced in areas of predicted severe surface movement and deformation, and the spacing between monitoring points is increased in areas of gentle deformation gradient. At the same time, the number of monitoring points is increased in key areas such as surface crack zones, mining boundary corners, and stop mining lines to ensure full coverage and no omissions in monitoring key deformation areas. Three-dimensional geomechanical model construction: The model is constructed using professional numerical simulation software. Relevant geological and mining parameters of the mining area are input, and the model is calibrated to ensure that the numerical simulation results are consistent with the actual mining subsidence patterns, providing a scientific and accurate theoretical basis for the layout of monitoring points.

3. The method for high-precision mapping and monitoring of surface movement and deformation in coal mining as described in claim 1, characterized in that: The specific structure and installation requirements of the combined fixed-point monitoring piles mentioned in step S2 are as follows: Structural Requirements: The deep bedrock marker, shallow soil marker, and surface measurement marker adopt a coaxial structure to strictly ensure the coaxiality of the three. Each is equipped with a suitable measurement target, which can realize synchronous and high-precision measurement of the relative displacement between the three markers. At the same time, an innovative adaptive calibration structure for layered displacement difference is added. An elastic buffer component and displacement sensing unit are added between the shallow soil marker and the deep bedrock marker to collect the relative displacement difference between the two markers in real time and automatically calibrate the coupling error between soil settlement and bedrock displacement. This solves the technical pain point of traditional coaxial monitoring piles that cannot distinguish the independent deformation of soil and bedrock and are prone to coupling interference, further improving the monitoring accuracy. Installation requirements: Deep bedrock markers should be anchored into stable bedrock, using appropriate anchoring methods to ensure anchoring reliability and prevent surface disturbance from affecting the benchmark. Shallow soil markers should be buried to a suitable soil depth, avoiding loose topsoil layers to ensure monitoring stability. Surface measurement markers should be equipped with a forced centering structure to improve measurement accuracy. An anti-disturbance protection structure should be installed on the outside of the pile to effectively avoid interference from various external factors such as mining compression, soil slippage, and frost heave, ensuring the long-term stable operation of the monitoring piles.

4. The method for high-precision mapping and monitoring of surface movement and deformation in coal mining according to claim 1, characterized in that: In step S3, the top center coordinates of the deep bedrock marker are used as the starting point to achieve spatiotemporal synchronization of the monitoring data. The specific operation is as follows: By using a professional time synchronization module to unify the measurement time benchmark, the time synchronization of each monitoring device is ensured, the spatiotemporal consistency of multi-source monitoring data is guaranteed, and the foundation is laid for subsequent data fusion and calculation. The three-dimensional coordinates of all monitoring points are uniformly converted to an independent engineering coordinate system with the deep bedrock marker as the origin. At the same time, the conversion method between this independent engineering coordinate system and the national geodetic coordinate system is provided to improve the universality and practicality of the monitoring data. Regularly conduct stability self-checks on deep bedrock benchmarks. If the test results exceed the preset error threshold, immediately recalibrate the benchmarks to continuously ensure the stability and reliability of the monitoring benchmarks, providing core support for high-precision monitoring.

5. The method for high-precision mapping and monitoring of surface movement and deformation in coal mining according to claim 1, characterized in that: The multi-source collaborative acquisition system includes a continuously operating reference station, automated monitoring equipment, surface deformation monitoring unit, and data transmission module. The units work together to achieve point-surface collaborative monitoring. The continuously operating reference station provides an absolute coordinate benchmark, ensuring the absolute accuracy of the monitoring data; the automated monitoring equipment has automatic calibration, automatic observation, and automatic data uploading functions, used for high-precision relative displacement measurement, improving monitoring efficiency and accuracy; the surface deformation monitoring unit is used to achieve comprehensive monitoring of surface deformation in the area to be monitored, taking into account both point and area coverage; the data transmission module ensures that monitoring data is uploaded in real time and stably, avoiding data loss or delay, and providing timely and reliable data support for subsequent data processing.

6. The method for high-precision mapping and monitoring of surface movement and deformation in coal mining according to claim 1, characterized in that: The specific solution method of the high-precision dynamic solution model of point-surface fusion constructed in step S5 is as follows: a. Adaptive filtering combined with interpolation algorithm is adopted to achieve deep fusion of point monitoring data and surface monitoring data, giving full play to the advantages of high precision of point monitoring and full coverage of surface monitoring. An innovative dynamic weight adaptive adjustment algorithm related to mining progress is introduced. According to the mining advance speed and working face position, the fusion weight of point monitoring data and surface monitoring data is dynamically adjusted in real time. In areas with rapid mining advance, the weight of point monitoring is increased to 60%-70%, and in areas with gentle mining advance, the weight of surface monitoring is increased to 55%-65%. This solves the problem that traditional fixed weight fusion cannot adapt to the dynamic changes of mining and is prone to calculation deviation. It is used to improve the calculation accuracy of different mining stages. b. Based on the accuracy characteristics of point monitoring data and area monitoring data, scientifically assign reasonable fusion weights to both to further improve the accuracy of the fusion solution results; c. During the solution process, preset criteria are used to remove outliers from the observed data, and reasonable spatiotemporal constraints are set to effectively avoid the impact of outliers on the solution results and ensure the reliability of the solution results. d. Output high-frequency three-dimensional displacement sequences of each monitoring point, taking into account both high accuracy and high frequency of monitoring, to meet the needs of real-time monitoring of surface deformation in coal mining.

7. The method for high-precision mapping and monitoring of surface movement and deformation in coal mining according to claim 1, characterized in that: The process involves calculating movement deformation parameters based on the output high-precision pure surface movement deformation values, identifying abnormal areas for graded early warning, and realizing the final application of monitoring data to ensure coal mine safety. This includes the following steps: Step S71: Calculate the displacement deformation parameters, which include the settlement Fa, horizontal displacement Fb, tilt value Fc, curvature Fd, and horizontal deformation value Fe. The calculation formulas for the settlement Fa, horizontal displacement Fb, tilt value Fc, curvature Fd, and horizontal deformation value Fe are as follows: ； Where Za is the initial elevation of the monitoring point, and Zt is the elevation of the monitoring point at time t; ； Where Xa and Ya are the initial planar coordinates of the monitoring point, and Xt and Yt are the planar coordinates of the monitoring point at time t; ； Where W1 and W2 are the subsidence amounts of two adjacent monitoring points, and L is the horizontal distance between two adjacent monitoring points; ； Wherein, G1 and G2 are the inclination values ​​of two adjacent monitoring segments, and S is the average horizontal distance between two adjacent monitoring segments; ； Where U1 and U2 are the horizontal displacements of two adjacent monitoring points, and L is the horizontal distance between two adjacent monitoring points; Step S72: Based on the calculation results of the above-mentioned moving deformation parameters, combined with the surface moving deformation law and the geological conditions of the mining area, a scientific threshold for identifying abnormal areas is set, and areas that meet the threshold conditions are accurately identified as abnormal areas and multi-level early warnings are issued. Step S73: Synchronously push the early warning information to the monitoring terminal and relevant personnel through the data transmission module; Step S74: For different levels of early warning, formulate corresponding joint response measures. Level 1 early warning focuses on data monitoring and encryption. Level 2 early warning initiates on-site inspection and equipment re-inspection. Level 3 early warning stops related operations in the mining area, organizes personnel evacuation, and activates the emergency response plan to achieve early detection and early handling of risks and ensure the safety of coal mining.

8. A high-precision mapping and monitoring system for fixed-point surface movement and deformation in coal mining, which is based on the high-precision mapping and monitoring method for fixed-point surface movement and deformation in coal mining as described in any one of claims 1-7, characterized in that, Specifically, it includes: a monitoring point deployment subsystem, a multi-source collaborative acquisition subsystem, a data processing and calculation subsystem, and an analysis and early warning subsystem; The monitoring point deployment subsystem includes a combined fixed-point monitoring pile, which is a coaxial structure. Each monitoring point is equipped with an interference correction device and an anti-disturbance protection device. The deployment density of the monitoring piles conforms to the non-uniform adaptive deployment principle, providing a stable monitoring carrier for high-precision monitoring. The multi-source collaborative acquisition subsystem includes a continuously operating reference station, automated monitoring equipment, a surface deformation monitoring unit, and a data transmission module. The continuously operating reference station provides an absolute coordinate benchmark to ensure the absolute accuracy of the monitoring data; the automated monitoring equipment has automatic calibration, automatic observation, and automatic data uploading functions, used for high-precision relative displacement measurement, improving monitoring efficiency and accuracy; the surface deformation monitoring unit is used to achieve comprehensive monitoring of surface deformation in the area to be monitored, taking into account both point and area coverage; the data transmission module ensures that the monitoring data is uploaded in real time and stably, avoiding data loss or delay, and providing timely and reliable data support for subsequent data processing; The data processing and calculation subsystem includes a data synchronization module, a point-area fusion calculation module, and a dynamic error compensation module. The data synchronization module is used to unify the time base and calculate the coordinates, and periodically perform self-checks on the stability of the reference points; the point-surface fusion solution module is used to output high-frequency three-dimensional displacement sequences using solution algorithms; the dynamic error compensation module is used to use error compensation methods and formulas to reverse correct model parameters, eliminate interference, output clean deformation data, and complete validity verification. The analysis and early warning subsystem includes a deformation parameter calculation module, a four-dimensional visualization module, and a hierarchical early warning module. The deformation parameter calculation module is used to accurately calculate various movement deformation parameters; the four-dimensional visualization module is used to display the spatiotemporal evolution process of surface movement deformation in real time, making it easier for staff to intuitively grasp the deformation patterns; the graded early warning module is used to identify abnormal areas, issue early warning information according to preset early warning standards, and link emergency response measures.

9. An electronic device, comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor, characterized in that: the processor executes a high-precision mapping and monitoring method for fixed-point surface movement and deformation in coal mining as described in any one of claims 1-7 by calling the computer program stored in the memory.

10. A computer-readable storage medium, characterized in that: The system stores instructions that, when executed on a computer, cause the computer to perform a high-precision mapping and monitoring method for surface movement and deformation in coal mining as described in any one of claims 1-7.

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