A method, system, device and medium for predicting horizontal surface movement in a mining area based on underground structure movement mode theory

Abstract

The present invention belongs to the technical field of mining subsidence prediction, and specifically relates to a method, system, equipment and medium for predicting surface horizontal movement in a mining area based on the theory of underground structure movement patterns. This method, through in-depth analysis of the correlation mechanism between surface horizontal movement in a mining area and movement of the overburden structure, divides surface horizontal movement into two types: tilting movement caused by tilting of the overburden structure and translational movement caused by translation of the overburden structure. The first type of horizontal movement is calculated using a probability integral method model, and the second type of horizontal movement is calculated using a proportional subsidence substitution model, thereby constructing a new system model for predicting surface horizontal movement. This model can reasonably explain the special phenomenon of surface horizontal movement in the middle of a mining area and significantly improve prediction accuracy. At the same time, the technical solution of the present invention provides a scientific basis and technical support for surface movement and deformation control, building protection and efficient resource mining in underground mining projects, and has significant technical effects and application value.

Description

Technical Field

[0001] The present invention belongs to the technical field of mining subsidence prediction, and specifically relates to a method, system, equipment and medium for predicting surface horizontal movement in a mining area based on underground structure movement mode theory. Background Art

[0002] Scholars at home and abroad have conducted extensive research on horizontal surface movement in mining areas and proposed various prediction models. Most of these models assume that horizontal surface movement is proportional to tilt deformation and that the amount of horizontal movement can be indirectly calculated using the tilt deformation. While these models explain some of the phenomena and patterns of horizontal surface movement to a certain extent, their validity has been challenged by the increasing amount of measured data.

[0003] Specifically, most existing prediction models use the probability integral method, which predicts the amount of surface horizontal movement by calculating parameters such as surface tilt deformation, horizontal movement coefficient, and working face depth. However, this method ignores the impact of mining-induced overburden structural movement on surface horizontal movement, resulting in significant deviations between the predicted results and actual observations. Particularly in the central mining area, the relationship between surface horizontal movement and tilt deformation is not simply proportional, a phenomenon that cannot be reasonably explained by traditional theoretical models.

[0004] Therefore, the existing surface horizontal movement prediction model still has the following defects:

[0005] 1. Ignoring the impact of mining-induced overburden structural movement: Most existing prediction models only consider the impact of surface tilt deformation on horizontal movement, while ignoring the important factor of mining-induced overburden structural movement. In fact, mining-induced overburden structural movement is one of the main causes of horizontal surface movement, especially at the boundaries and center of the goaf.

[0006] 2. Inaccurate predictions: Because existing prediction models ignore the impact of mining-induced overburden structural movement, their predictions often deviate significantly from actual observations. For example, they fail to account for significant horizontal movement in the center of the mining zone. This not only impacts the planning and implementation of mining projects but also poses a potential threat to the safety of surface structures.

[0007] 3. Lack of systematic research: Existing studies mostly focus on single factors or simple models, lacking systematic research on the correlation between horizontal ground movement and mining-induced overburden structural movement. This results in a limited understanding of the laws governing horizontal ground movement, making it difficult to develop effective prediction and control strategies. Summary of the Invention

[0008] The purpose of the present invention is to provide a method, system, equipment and medium for predicting surface horizontal movement in mining areas based on the theory of underground structure movement patterns, so as to solve the problem that existing prediction methods fail to fully consider the impact of mining-induced overburden structure movement on surface horizontal movement, resulting in significant deviations between prediction results and actual observation data.

[0009] The present invention achieves the above-mentioned purpose through the following technical solutions:

[0010] In a first aspect, the present invention proposes a method for predicting horizontal surface movement in a mining area based on the theory of underground structure movement patterns, the method comprising:

[0011] Identify and analyze the linkage mechanism between the horizontal ground movement in the mining area and the movement of the overburden structure, including the horizontal ground movement caused by the rotation and tilting of the structural blocks at the boundary of the goaf, and the additional horizontal ground movement caused by the double rotation and translation of the structural blocks in the middle of the goaf;

[0012] In combination with the above-mentioned correlation mechanism, the probability integral method is used to predict the horizontal surface movement caused by the rotation and tilt of the structural block, and the additional horizontal surface movement caused by the two rotations and translations of the structural block is calculated by replacing the subsidence value with a set ratio, and a surface horizontal movement prediction model is constructed based on this.

[0013] The engineering parameters of the target mining area are obtained, including the geological mining parameters of the working face and the parameters predicted by the probability integral method, and are input into the surface horizontal movement prediction model to obtain the horizontal movement value of any point on the surface; based on the horizontal movement value of any point on the surface, the surface horizontal movement of the engineering project in the target mining area is evaluated.

[0014] Furthermore, the identification and analysis of the correlation mechanism between the horizontal surface movement of the mining area and the movement of the mining overburden structure also includes:

[0015] Identify and determine the first source and characteristics of surface horizontal movement. Based on the translation effect caused by the rotation and tilt of structural blocks at the boundary of the goaf, determine that the portion of surface horizontal movement caused by the tilt of structural blocks is concentrated in the boundary area of ​​the goaf, is symmetrical, and is proportional to the surface tilt deformation.

[0016] Also, identify and determine the second type of source and characteristics of horizontal surface movement. Based on the translation effect caused by two rotational translations of the structural block in the middle of the goaf, determine that the part of horizontal surface movement caused by the translation of the structural block is mainly located in the middle of the mining area, along the direction of advancement of the working face, and is proportional to the surface subsidence.

[0017] Furthermore, the construction of the surface horizontal movement prediction model includes:

[0018] (1) Using the probability integral method formula, the surface horizontal movement u caused by the tilt of the structural block is calculated based on the surface tilt deformation, horizontal movement coefficient and working face mining depth parameters. T (x), the expression is:

[0019] u T (x)=b·r·i(x)=H·b·i(x) / tanβ

[0020] Where i(x) is the surface tilt deformation; b is the horizontal movement coefficient; H is the mining depth of the working face; tanβ is the tangent value of the main influencing angle of the working face in the probability integral parameter; r is the main influencing radius;

[0021] (2) The additional horizontal movement is calculated by using the set proportional sinking value W(x,y) instead of the original value. The translational movement of multiple structural blocks within the affected area is accumulated to obtain the additional horizontal movement u of the surface point. m (x,y), the expression is:

[0022] u m (x,y)=C·W(x,y)

[0023] Where W(x,y) is the subsidence value of any surface point (x,y); the proportional coefficient C is set according to the working face thickness, lithology, working face depth and advancement speed, and is specifically between 0.1 and 0.3;

[0024] (3) The horizontal movement caused by the tilt of the structural block and the additional horizontal movement caused by the translation of the structural block are superimposed to obtain the total horizontal movement u(x,y) of the surface point, which is expressed as:

[0025] u(x,y)=u T (x,y)+C·W(x,y),

[0026] Furthermore, the prediction method further includes:

[0027] Under the condition of super-full mining, the additional horizontal movement value in the middle of the mining area reaches the maximum. The maximum additional horizontal movement value in the middle of the mining area is calculated using the maximum subsidence value. The expression is:

[0028]

[0029] u c It is the horizontal movement in the middle of the mining area. W is the maximum additional horizontal movement value of the mining area; max is the maximum surface subsidence value in the mining area;

[0030] And, based on the total horizontal movement u(x, y), determine the horizontal movement extreme value u of the surface directionmax , the expression is:

[0031]

[0032] in, is the maximum horizontal movement of the surface, is the maximum additional horizontal movement value;

[0033] And based on the surface trend horizontal movement extreme value U max Assess the horizontal surface movement of the engineering site in the target mining area.

[0034] In a second aspect, the present invention proposes a system for predicting horizontal surface movement in a mining area based on the theory of underground structure movement patterns, which is applied to execute any of the above-mentioned prediction methods. The system comprises:

[0035] The first analysis module is used to identify and analyze the correlation mechanism between the horizontal movement of the ground surface in the mining area and the movement of the overburden structure caused by mining, wherein the correlation mechanism includes the horizontal movement of the ground surface caused by the rotation and tilting of the boundary structure blocks of the goaf, and the additional horizontal movement of the ground surface caused by the double rotation and translation of the structure blocks in the middle of the goaf;

[0036] a model building module for predicting the horizontal surface movement caused by the rotation and tilt of the structural block by using a probability integral method in combination with the association mechanism, and for calculating the additional horizontal surface movement caused by the two rotations and translations of the structural block by replacing the subsidence value with a set ratio, thereby constructing a model for predicting the horizontal surface movement;

[0037] The prediction output module inputs the engineering parameters of the target mining area, including the geological mining parameters of the working face and the probability integral parameters, and inputs them into the surface horizontal movement prediction model to obtain the horizontal movement value of any point on the surface; based on the horizontal movement value of any point on the surface, the surface horizontal movement of the target mining area engineering is evaluated.

[0038] Furthermore, the model building module includes:

[0039] Correlation mechanism analysis unit, used to analyze and determine in detail the correlation mechanism between the horizontal movement of the surface in the mining area and the movement of the overburden structure;

[0040] The probability integral method application unit is used to calculate the surface horizontal movement and surface subsidence value caused by the tilt of the structural block based on the surface tilt deformation, horizontal movement coefficient and working face mining depth parameters;

[0041] An additional horizontal movement calculation unit, used for calculating the additional horizontal movement by using a set proportion of sinking instead;

[0042] The total horizontal movement calculation unit is used to superimpose the horizontal movement caused by the tilt of the structural block and the additional horizontal movement caused by the translation of the structural block to obtain the total horizontal movement of the surface point.

[0043] In a third aspect, the present invention provides an electronic device, comprising:

[0044] a processor; a memory for storing instructions executable by the processor;

[0045] The processor is configured to execute the instructions to implement any of the estimation methods described above.

[0046] In a fourth aspect, the present invention proposes a computer-readable storage medium, which, when the instructions in the computer-readable storage medium are executed by a processor of an electronic device, enables the electronic device to execute any of the above-mentioned prediction methods.

[0047] The beneficial effects of the present invention are:

[0048] 1. This invention constructs a more accurate surface movement prediction model by thoroughly identifying and analyzing the complex correlation between surface horizontal movement in the mining area and the movement of the overburden structure. Specifically, it considers the dual effects of rotation and tilt of the boundary blocks of the goaf and the double rotation and translation of the central blocks on surface horizontal movement. This technical solution significantly improves the accuracy of surface horizontal movement prediction, providing a more reliable scientific basis and technical support for surface subsidence control, building protection, and efficient resource extraction in underground mining projects.

[0049] 2. The present invention not only proposes an innovative method for predicting surface horizontal movement, but also designs a complete set of system, equipment and storage medium implementation plans, so that the method can be efficiently and conveniently applied in actual projects. Through the integrated system module design, including correlation mechanism analysis, probability integral method application, additional horizontal movement calculation and total horizontal movement prediction functions, the present invention realizes the automation and intelligence of surface horizontal movement prediction, effectively reduces human error and improves work efficiency. At the same time, the use of advanced electronic equipment and storage media ensures the accuracy and traceability of prediction data, providing a solid technical guarantee for the safe and efficient operation of underground mining projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A flow chart of a method for predicting horizontal surface movement in a mining area based on the theory of underground structure movement patterns provided by the present invention;

[0051] Figure 2 A schematic structural diagram of a system for predicting horizontal surface movement in a mining area based on the theory of underground structure movement patterns provided by the present invention;

[0052] Figure 3 A structural schematic diagram of an electronic device provided by the present invention;

[0053] Figure 4 This is the layout of some observation stations in the case of this invention and the location map of the 1414 working face of Guqiao Mine;

[0054] Figure 5 This is the fitting diagram of the sinking of the 1414 working face of Guqiao Mine in the case of this invention;

[0055] Figure 6 This is the horizontal movement fitting diagram of the 1414 working face of Guqiao Mine in the case of the present invention;

[0056] Figure 7 This is a diagram of the layout of some observation stations and the location of the 205 working face of the Longde Mine in the case of this invention;

[0057] Figure 8 This is the fitting diagram of the sinking of the 205 working face of the Longde Mine in the case of the present invention;

[0058] Figure 9 This is the fitting diagram of the horizontal movement of the 205 working face of the Longde Mine in the case of the present invention;

[0059] Figure 10 This is the layout of some observation stations and the location of the Majialiang 4201 working face in the case of this invention;

[0060] Figure 11 This is the fitting diagram of the sinking of the Majialiang 4201 working face in the case of the present invention;

[0061] Figure 12 This is the fitting diagram of the horizontal movement of the Majialiang 4201 working surface in the case of the present invention. DETAILED DESCRIPTION

[0062] The present application is described in further detail below in conjunction with the accompanying drawings. It is necessary to point out that the following specific implementation methods are only used to further illustrate the present application and cannot be understood as limiting the scope of protection of the present application. Technicians in this field can make some non-essential improvements and adjustments to the present application based on the above application content.

[0063] Example 1

[0064] like Figure 1 As shown, this embodiment proposes a method for predicting horizontal surface movement in a mining area based on the theory of underground structure movement patterns, and the method includes the following steps:

[0065] S1. Identify and analyze the association mechanism:

[0066] Identify and analyze the linkage mechanisms between the horizontal ground movement in the mining area and the movement of the overburden structure. The linkage mechanisms include the horizontal ground movement caused by the rotation and tilting of the structural blocks at the boundary of the goaf, and the additional horizontal ground movement caused by the double rotation and translation of the structural blocks in the middle of the goaf.

[0067] Furthermore, identifying and analyzing the correlation mechanism between the horizontal surface movement of the mining area and the movement of the overburden structure also includes:

[0068] Identify and determine the first source of surface horizontal movement. Based on the translation effect caused by the rotation and tilt of the structural blocks at the boundary of the goaf, determine that the part of the surface horizontal movement caused by the tilt of the structural blocks is concentrated in the boundary area of ​​the goaf, is symmetrical, and is proportional to the surface tilt deformation.

[0069] Also, the second source of horizontal surface movement is identified and determined. Based on the translation effect caused by two rotational translations of the structural block in the middle of the goaf, it is determined that the part of the horizontal surface movement caused by the translation of the structural block is mainly located in the middle of the mining area, along the direction of advancement of the working face, and is proportional to the surface subsidence.

[0070] S2. Construct a surface horizontal movement prediction model:

[0071] Combined with the correlation mechanism, the probability integral method is used to estimate the surface horizontal movement caused by the rotation and tilt of the structural block, and the additional surface horizontal movement caused by the two rotations and translations of the structural block is calculated by replacing the subsidence value with a set ratio. The proportional coefficient C value is set according to the working face thickness, lithology, working face depth and advancement speed, and is specifically between 0.1 and 0.3;

[0072] The horizontal movement caused by the tilt of the structural block and the additional horizontal movement caused by the translation of the structural block are superimposed to obtain the total horizontal movement of the surface point, and the surface horizontal movement prediction model is constructed based on this.

[0073] S3. Obtain and enter project parameters:

[0074] The engineering parameters of the target mining area are obtained, including the working face address, mining conditions and probability integral parameters, and are input into the surface horizontal movement prediction model to obtain the horizontal movement value of any point on the surface; based on the horizontal movement value of any point on the surface, the surface horizontal movement of the target mining area engineering is evaluated.

[0075] S4. Evaluation and Verification:

[0076] The horizontal movement of the target mining area is evaluated based on the horizontal movement value of any point on the surface. Under the condition of super-full mining, the additional horizontal movement value in the middle of the mining area reaches the maximum, and the maximum additional horizontal movement value in the middle of the mining area is calculated using the maximum subsidence value. The extreme value of the horizontal movement of the surface strike u is determined based on the total horizontal movement. max, and based on this extreme value, the horizontal movement of the engineering surface in the target mining area is evaluated. The model parameters are adjusted and optimized based on the verification results.

[0077] The steps of identifying and analyzing associations in this embodiment include:

[0078] (1) Identify and determine the first source of horizontal surface movement:

[0079] The translation effect caused by the rotation and tilt of the structural blocks at the boundary of the goaf was analyzed, and it was determined that the part of the surface horizontal movement caused by the tilt of the structural blocks was mainly concentrated in the boundary area of ​​the goaf.

[0080] Through observation data and numerical simulation results, the proportional relationship between surface horizontal movement and surface tilt deformation was verified, and it was determined that this part of the horizontal movement was symmetrical.

[0081] (2) Identify and determine the second source of horizontal surface movement:

[0082] The translation effect caused by two rotational translations of the structural block in the middle of the goaf was analyzed, and it was determined that the part of the surface horizontal movement caused by the translation of the structural block was mainly located in the middle of the mining area.

[0083] Through observation data and numerical simulation results, the proportional relationship between surface horizontal movement and surface subsidence is verified, and the distribution of this part of horizontal movement along the advancing direction of the working face is determined.

[0084] In order to deeply analyze the correlation mechanism between the horizontal movement of the mining area and the movement of the overburden structure, this paper adopts a numerical simulation method. The specific process is as follows:

[0085] (1) Model construction:

[0086] A geomechanical model is constructed based on the geological and mining parameters of the mining area. This model should accurately reflect the movement patterns of the overburden structure during mining. Reasonable boundary and initial conditions are set in the model to ensure the accuracy of the numerical simulation.

[0087] (2) Numerical simulation:

[0088] Use geomechanical analysis software (such as FLAC3D, UDEC, etc.) to perform numerical simulation of the geomechanical model.

[0089] During the simulation process, attention was paid to the changes in the movement of the overburden structure caused by mining, especially the generation mechanism and influencing factors of the rotation, tilt and translation effects of the structural blocks.

[0090] Record the changes in key parameters such as surface horizontal movement, surface tilt deformation, etc. during the simulation process for subsequent analysis.

[0091] (3) Result analysis:

[0092] The numerical simulation results are compared and analyzed with the observation data to verify the accuracy of the numerical simulation.

[0093] Based on the numerical simulation results, the correlation mechanism between the horizontal surface movement and the movement of the overburden structure caused by mining is deeply analyzed, including the influence of the rotation, tilt and translation effects of the structural blocks on the horizontal surface movement.

[0094] Combined with the laboratory simulation results of similar materials, the reliability and accuracy of the numerical simulation results are further verified.

[0095] In summary, this paper, through precise and continuous observation data collection and preprocessing, coupled with numerical simulation using geomechanical analysis software, has deeply analyzed the correlation between horizontal surface movement in mining-induced areas and the movement of overburden structures. This process provides the scientific basis and technical support for the construction of an accurate model for predicting horizontal surface movement.

[0096] Further preferably, constructing a surface horizontal movement prediction model includes:

[0097] (1) Using the probability integral method formula, the surface horizontal movement u caused by the tilt of the structural block is calculated based on the surface tilt deformation, horizontal movement coefficient and working face mining depth parameters. T (x), the expression is:

[0098] u T (x)=b·r·i(x)=H·b·i(x) / tanβ

[0099] Where i(x) is the surface tilt deformation; b is the horizontal movement coefficient; H is the mining depth of the working face; tanβ is the tangent value of the main influencing angle of the working face in the probability integral parameter; r is the main influencing radius;

[0100] (2) The additional horizontal movement is calculated by using the set proportional sinking value W(x,y) instead of the original value. The translational movement of multiple structural blocks within the affected area is accumulated to obtain the additional horizontal movement u of the surface point. m (x,y), the expression is:

[0101] u m (x,y)=C·W(x,y)

[0102] Where W(x,y) is the subsidence value of any surface point (x,y); the proportional coefficient C is set according to the working face thickness, lithology, working face depth and advancement speed, and is specifically between 0.1 and 0.3;

[0103] (3) The horizontal movement caused by the tilt of the structural block and the additional horizontal movement caused by the translation of the structural block are superimposed to obtain the total horizontal movement u(x,y) of the surface point, which is expressed as:

[0104] u(x,y)=u T (x,y)+C·W(x,y),

[0105] Further preferably, the estimation method further comprises:

[0106] Under the condition of super-full mining, the additional horizontal movement value in the middle of the mining area reaches the maximum. The maximum additional horizontal movement value in the middle of the mining area is calculated using the maximum subsidence value. The expression is:

[0107]

[0108] u c It is the horizontal movement in the middle of the mining area. W is the maximum additional horizontal movement value of the mining area; max is the maximum surface subsidence value in the mining area;

[0109] And, based on the total horizontal movement u(x,y), determine the horizontal movement extreme value U of the surface direction max , the expression is:

[0110]

[0111] in, is the maximum horizontal movement of the surface, is the maximum additional horizontal movement value;

[0112] And based on the horizontal movement of the extreme value U max Assess the horizontal surface movement of the engineering site in the target mining area.

[0113] Based on the above-described embodiments, the prediction method of the present invention systematically analyzes the sources, mechanisms, and patterns of horizontal movement and constructs a prediction model, addressing the inability of traditional models to explain horizontal movement in the center of a mining zone. By identifying and analyzing the correlation between surface horizontal movement in the mining zone and the movement of the overburden structure, the accuracy of the prediction is improved.

[0114] Combine Figure 2 Based on the same inventive concept, this embodiment also proposes a system for predicting horizontal surface movement in a mining area based on the theory of underground structure movement patterns, which is used to implement the above-mentioned prediction method. The system includes:

[0115] The first analysis module 40 is used to identify and analyze the correlation mechanism between the horizontal movement of the ground surface in the mining area and the movement of the overburden structure caused by mining, including the horizontal movement of the ground surface caused by the rotation and tilting of the boundary structure blocks of the goaf, and the additional horizontal movement of the ground surface caused by the double rotation and translation of the structure blocks in the middle of the goaf;

[0116] The model building module 41 is used to combine the correlation mechanism, use the probability integration method to predict the surface horizontal movement caused by the rotation and tilt of the structural block, and use the subsidence value of the set ratio to replace the calculation of the additional surface horizontal movement caused by the two rotations and translations of the structural block, and thus build a surface horizontal movement prediction model;

[0117] The prediction output module 42 is used to obtain the engineering parameters of the target mining area, including the working face address parameters, mining parameters and the measured data of the surface movement observation station, and input them into the surface horizontal movement prediction model to obtain the horizontal movement value of any point on the surface; based on the horizontal movement value of any point on the surface, the surface horizontal movement of the target mining area engineering is evaluated.

[0118] It should be noted here that each module in the above-mentioned prediction system corresponds to steps S1 to S3 in implementing the above-mentioned prediction method, and the instances and application scenarios implemented by multiple modules and corresponding steps are the same, but are not limited to the contents disclosed in the above-mentioned embodiment 1.

[0119] It can be understood that the model construction module 41 also includes an association mechanism analysis unit 411, a probability integral method application unit 412, an additional horizontal movement calculation unit 413 and a total horizontal movement calculation unit 414, which are respectively used to analyze and determine the association mechanism in detail, calculate the surface horizontal movement caused by the tilt of the structural block, calculate the additional horizontal movement, and superimpose to obtain the total horizontal movement.

[0120] Further preferably, the model building module includes:

[0121] The correlation mechanism analysis unit 411 is used to analyze and determine the correlation mechanism between the horizontal movement of the mining area surface and the movement of the mining overburden structure;

[0122] The probability integral method application unit 412 is used to calculate the surface horizontal movement caused by the tilt of the structural block based on the surface tilt deformation, the horizontal movement coefficient and the working face mining depth parameter;

[0123] The additional horizontal movement calculation unit 413 is configured to calculate the additional horizontal movement by using the subsidence value of a set ratio instead of calculating the additional horizontal movement, accumulating the translational movement of multiple structural blocks within the influence range, and obtaining the additional horizontal movement of the surface point;

[0124] The total horizontal movement calculation unit 414 is used to superimpose the horizontal movement caused by the tilt of the structural block and the additional horizontal movement caused by the translation of the structural block to obtain the total horizontal movement of the surface point.

[0125] The prediction method in this embodiment is verified below with reference to an engineering case.

[0126] 1. Verification of the Guqiao 1414 working face observation station

[0127] The 1414 working face of Guqiao Mine has a strike length of 2167m, a dip length of 251m, a mining height of 2.8m, an average mining depth of 748m, and an average dip angle of 4°. The mining process lasted 340 days, with an average recovery rate of 6.28m / d. Comprehensive mechanized coal mining was adopted, with the method of mining the entire height at one time and the roof being managed by the full caving method. Two observation lines were laid on the surface, one ML line along the strike direction and one MS line along the dip direction. The relative position relationship between the observation line and the working face is as follows: Figure 3 Through a large amount of monitoring, the final surface point sinking and horizontal movement curve along the strike and dip observation line is obtained as shown in Figure 4 shown.

[0128] Using the geological mining parameters and measured surface horizontal movement values ​​of the 1414 working face of Guqiao Mine, the difference in fitting effect between the probability integral method and the surface horizontal movement prediction model of the present invention is compared. Figure 5 and 6 shown.

[0129] from Figure 5 It can be seen that the subsidence value predicted by the probability integral method fits well with the measured subsidence data. The RMSE of the subsidence fitting is 40 mm, and the relative error is 2.2%, indicating that the subsidence prediction model and parameters of the probability integral method are relatively accurate. Figure 6 The horizontal movement predicted by the medium probability integral method is basically symmetrical, which is obviously inconsistent with the measured data. The RMSE of the horizontal movement fitting is 206mm, and the relative error is 27.5%. The additional horizontal movement calculated by taking C = 0.18 and superimposing it with the predicted results of the probability integral method to obtain the calculation results of the model of the present invention can well fit the systematic horizontal displacement in the middle of the mining area. The positive and negative extremes of the horizontal movement at the inflection point boundary of the working face are relatively consistent with the measured horizontal movement data. The RMSE of the horizontal movement fitting is 53mm, and the relative error is 7.1%, which greatly improves the application effect of the model.

[0130] 2. Verification of the Longde 205 working face observation station

[0131] The strike length of the 205 working face of Longde Mine is 3640m, the dip length is 300m, the working face mining depth is 228m, the average coal seam thickness is 3.5m, and the coal seam dip angle is <1°. A semi-basin observation line A01 to A55 is arranged on the side of the cut hole of the working face, and the working point spacing is 10m. The movement deformation data of the observation station is obtained by leveling and total station plane observation. The layout of the observation station and the working face position are as follows: Figure 7 shown.

[0132] The traditional probability integral method and the prediction method of the present invention are used to compare the fitting effects of the two on horizontal movement. Figure 8 and 9 shown.

[0133] from Figure 8 The fitting effect shows that the subsidence value predicted by the probability integral method is well fitted with the measured subsidence data. The RMSE of the subsidence fitting is 50 mm, and the relative error is 2.4%, indicating that the subsidence prediction model and parameters of the probability integral method are relatively accurate. Figure 9 The traditional probability integral horizontal movement prediction model performed poorly in this case and was unable to explain and calculate the horizontal displacement in the center of the mining zone. The calculated horizontal movement fitting RMSE was 179 mm, with a relative error of 24.0%. The proposed model can more accurately calculate the additional horizontal movement in the center of the mining zone, with an RMSE of 50 mm and a relative error of 6.7%, effectively improving the prediction accuracy.

[0134] 3. Verification of the Majialiang 4201 working face observation station

[0135] The 4201 working face of Majialiang Mine has a strike length of 1740m, a dip length of 250m, a working face mining depth of 630m, and a coal seam thickness of 9.24m, which is a horizontal coal seam. A surface mobile observation station was set up along the working face strike on one side of the stop mining line, with an observation station spacing of 25m. The sinking and horizontal movement values ​​of the observation station were obtained through daily observation. The relative position relationship between the observation station and the working face is shown in the figure below. Figure 10 shown.

[0136] The comparison between the fitted surface movement deformation curve and the measured deformation curve using the traditional probability integral method is shown in the following figure. Figure 11 and 12 shown.

[0137] from Figure 11 It can be seen that the predicted subsidence data of the observation station calculated using the traditional probability integral method is consistent with the measured data. The subsidence fitting RMSE is 135 mm, and the relative error is 2.7%, indicating that the probability integral method subsidence prediction model and predicted parameters are relatively accurate. Figure 12There is horizontal movement in the middle of the mining area along the advancement direction, and the horizontal movement value is about 1000mm. The traditional probability integral horizontal movement prediction model has a poor fitting effect in this project, and cannot explain and calculate the horizontal movement in the middle. The extreme value calculation of the horizontal movement on the side of the stop mining line is also significantly larger. The overall fitting horizontal movement RMSE = 621mm, and the relative error reaches 61.1%. The prediction model in the present invention can more accurately calculate the additional horizontal movement in the middle of the mining area. The calculated surface horizontal movement RMSE = 99mm, with a relative error of 9.8%, which effectively improves the prediction accuracy of the model.

[0138] Combine Figure 3 In another embodiment of the present invention, an electronic device 50 is provided, comprising:

[0139] Processor 51; Memory 52 for storing processor executable instructions;

[0140] The processor 51 is configured to execute instructions to implement the above-mentioned prediction method.

[0141] In yet another embodiment of the present invention, a computer-readable storage medium is provided. When instructions in the computer-readable storage medium are executed by the processor 51 of the electronic device 50, the electronic device 50 is enabled to execute the above-mentioned estimated method.

[0142] In the above embodiments, all or part of the embodiments may be implemented using software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments may be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present invention are generated in whole or in part.

[0143] The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated therein. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0144] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0145] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for predicting horizontal surface movement in a mining area based on the theory of underground structure movement patterns, characterized in that: The method comprises: Identify and analyze the linkage mechanism between the horizontal ground movement in the mining area and the movement of the overburden structure, including the horizontal ground movement caused by the rotation and tilting of the structural blocks at the boundary of the goaf, and the additional horizontal ground movement caused by the double rotation and translation of the structural blocks in the middle of the goaf; In combination with the above-mentioned correlation mechanism, the probability integral method is used to predict the horizontal surface movement caused by the rotation and tilt of the structural block, and the additional horizontal surface movement caused by the two rotations and translations of the structural block is calculated by replacing the subsidence value with a set ratio, and a surface horizontal movement prediction model is constructed based on this. The engineering parameters of the target mining area are obtained, including the mining parameters of the working face address and the parameters predicted by the probability integral method, and are input into the surface horizontal movement prediction model to obtain the horizontal movement value of any point on the surface; based on the horizontal movement value of any point on the surface, the surface horizontal movement of the target mining area is evaluated.

2. The method for predicting horizontal surface movement in a mining area based on the theory of underground structure movement patterns according to claim 1 is characterized in that: The identification and analysis of the correlation mechanism between the horizontal surface movement of the mining area and the movement of the mining overburden structure also includes: Identify and determine the first source of surface horizontal movement. Based on the translation effect caused by the rotation and tilt of the structural blocks at the boundary of the goaf, determine that the part of the surface horizontal movement caused by the tilt of the structural blocks is concentrated in the boundary area of ​​the goaf, is symmetrical, and is proportional to the surface tilt deformation. Also, the second source of horizontal surface movement is identified and determined. Based on the translation effect caused by two rotational translations of the structural block in the middle of the goaf, it is determined that the part of the horizontal surface movement caused by the translation of the structural block is mainly located in the middle of the mining area, along the direction of advancement of the working face, and is proportional to the surface subsidence.

3. The method for predicting horizontal surface movement in a mining area based on the theory of underground structure movement patterns according to claim 2 is characterized in that: The constructing of the surface horizontal movement prediction model includes: (1) Using the probability integral method formula, the surface horizontal movement caused by the tilt of the structural block is calculated based on the surface tilt deformation, horizontal movement coefficient and working face mining depth parameters. , the expression is: ； in, The ground surface is tilted and deformed; is the horizontal shift coefficient; Mining depth for working face ； is the tangent value of the main influencing angle of the working surface in the probability integral parameter; is the main impact radius; (2) Use a set proportion of sinking value Instead of calculating the additional horizontal movement caused by the accumulation of translation movement , the expression is: ； in, For any surface point The sinking value; proportional coefficient The value is set according to the working face mining thickness, lithology, working face mining depth and advancement speed, specifically between 0.1 and 0.3; (3) Horizontal movement caused by tilting the structural block and the additional horizontal movement caused by the translation of the structural block Superposition is performed to obtain the total horizontal movement of the surface points , the expression is: 。 4. The method for predicting horizontal surface movement in a mining area based on the theory of underground structure movement patterns according to claim 3 is characterized in that: The estimation method further includes: Under the condition of super-full mining, the additional horizontal movement value in the middle of the mining area reaches the maximum. The maximum additional horizontal movement value in the middle of the mining area is calculated using the maximum subsidence value. , the expression is: ； in, , It is the horizontal movement in the middle of the mining area. is the maximum additional horizontal movement value of the mining area; is the maximum surface subsidence value in the mining area; And, based on the total horizontal movement Determine the extreme horizontal movement of the surface , the expression is: ； in, , is the maximum horizontal movement of the ground surface caused by the rotation and tilt of the structure, which can be calculated using traditional methods. is the maximum additional horizontal movement value; And based on the surface trend horizontally move the extreme value Assess the horizontal surface movement of the engineering site in the target mining area.

5. The method for predicting horizontal surface movement in a mining area based on the theory of underground structure movement patterns according to claim 1 is characterized in that: The estimation method further includes: Comparing the measured data from the surface movement observation station with the horizontal movement value of any point on the surface, verifying the accuracy of the model by calculating the prediction error and analyzing the error distribution characteristics, and evaluating the applicability of the model under different geological and mining conditions; And, based on the validation results, the model parameters are adjusted and optimized to improve the prediction accuracy.

6. A system for predicting horizontal surface movement in mining areas based on the theory of underground structure movement patterns, characterized by: Applied to executing the prediction method according to any one of claims 1 to 5, the system comprises: The first analysis module is used to identify and analyze the correlation mechanism between the horizontal movement of the ground surface in the mining area and the movement of the overburden structure caused by mining, wherein the correlation mechanism includes the horizontal movement of the ground surface caused by the rotation and tilting of the boundary structure blocks of the goaf, and the additional horizontal movement of the ground surface caused by the double rotation and translation of the structure blocks in the middle of the goaf; a model building module for predicting the horizontal surface movement caused by the rotation and tilt of the structural block by using a probability integral method in combination with the association mechanism, and for calculating the additional horizontal surface movement caused by the two rotations and translations of the structural block by replacing the subsidence value with a set ratio, thereby constructing a model for predicting the horizontal surface movement; The prediction output module inputs the engineering parameters of the target mining area, including the geological mining parameters of the working face and the probability integral parameters, and inputs them into the surface horizontal movement prediction model to obtain the horizontal movement value of any point on the surface; based on the horizontal movement value of any point on the surface, the surface horizontal movement of the target mining area engineering is evaluated.

7. The system for predicting horizontal surface movement in mining areas based on the theory of underground structure movement patterns according to claim 6 is characterized in that: The model building module includes: Correlation mechanism analysis unit, used to analyze and determine in detail the correlation mechanism between the horizontal movement of the surface in the mining area and the movement of the overburden structure; The probability integral method application unit is used to calculate the surface horizontal movement and surface subsidence value caused by the tilt of the structural block based on the surface tilt deformation, horizontal movement coefficient and working face mining depth parameters; An additional horizontal movement calculation unit, used for calculating the additional horizontal movement by using a set proportion of sinking instead; The total horizontal movement calculation unit is used to superimpose the horizontal movement caused by the tilt of the structural block and the additional horizontal movement caused by the translation of the structural block to obtain the total horizontal movement of the surface point.

8. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the estimation method according to any one of claims 1 to 5.

9. A computer-readable storage medium, characterized in that When the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the estimated method according to any one of claims 1 to 5.

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