Mining area earth surface horizontal movement prediction method, system and equipment based on underground structure movement mode theory and medium

Abstract

The invention belongs to the technical field of mining subsidence prediction, and particularly relates to a mining area earth surface horizontal movement prediction method, system and equipment based on an underground structure movement mode theory and a medium. The earth surface horizontal movement is divided into two types of inclination movement caused by inclination of an overlying strata structure and translation movement caused by translation of the overlying strata structure, a probability integral method model is used for calculating a first type of horizontal movement, a proportional subsidence substitution model is used for calculating a second type of horizontal movement, and a new earth surface horizontal movement prediction system model is constructed. The model can reasonably explain the special phenomenon of horizontal movement of the middle earth surface of the mining area, and the prediction accuracy is remarkably improved. Meanwhile, the technical scheme provides scientific basis and technical support for ground surface movement deformation control, building protection and efficient resource mining in underground mining engineering, and has remarkable technical effect and application value.

Description

Technical Field

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

[0002] At present, scholars at home and abroad have conducted extensive research on the surface horizontal movement in the mined area and proposed various prediction models. Most of these models believe that the surface horizontal movement is proportional to the tilt deformation, and the horizontal movement amount can be indirectly calculated using the surface tilt deformation value. This model explains some phenomena and laws of the surface horizontal movement to a certain extent. However, with the increase of measured data, the rationality of this model has encountered many challenges in application.

[0003] Specifically, most of the existing prediction models adopt the probability integral method, which predicts the surface horizontal movement amount by calculating parameters such as surface tilt deformation, horizontal movement coefficient, and working face mining depth. However, this method ignores the influence of the movement of the overlying strata structure in mining on the surface horizontal movement, resulting in a large deviation between the prediction result and the actual observation data. Especially in the middle of the mined area, the relationship between the surface horizontal movement and the tilt deformation is not a simple proportional relationship, which cannot be reasonably explained in the traditional theoretical model.

[0004] Therefore, the existing prediction models for surface horizontal movement still have the following defects:

[0005] 1. Ignoring the influence of the movement of the overlying strata structure in mining: Most of the existing prediction models only consider the influence of surface tilt deformation on the horizontal movement, while ignoring this important factor of the movement of the overlying strata structure in mining. In fact, the movement of the overlying strata structure in mining is one of the main reasons for the surface horizontal movement, especially at the boundary and in the middle of the goaf, this influence is particularly significant.

[0006] 2. Inaccurate prediction results: Due to ignoring the influence of the movement of the overlying strata structure in mining, the prediction results of the existing prediction models often have a large deviation from the actual observation data. For example, it cannot explain the phenomenon of a large amount of horizontal movement in the middle of the mined area. This not only affects the planning and implementation of the mining project, but also poses a potential threat to the safety of ground buildings.

[0007] 3. Lack of systematic research: Most of the existing research focuses on single factors or simple models, lacking systematic research on the correlation mechanism between the surface horizontal movement and the movement of the overlying strata structure in mining. This leads to an insufficient understanding of the laws of the surface horizontal movement and it is difficult to propose effective prediction and control strategies. Summary of the Invention

[0008] The object of the present invention is to provide a method, system, device and medium for predicting the surface horizontal movement in the mining area based on the theory of underground structure movement mode, so as to solve the problem that the existing prediction methods fail to fully consider the influence of the movement of the overlying rock structure in the mining area on the surface horizontal movement, resulting in a significant deviation between the prediction results and the actual observed data.

[0009] The present invention realizes the above object through the following technical solutions:

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

[0011] Identifying and analyzing the correlation mechanism between the surface horizontal movement in the mining area and the movement of the overlying rock structure in the mining area, where the correlation mechanism includes the surface horizontal movement caused by the rotation and inclination of the structural blocks at the goaf boundary, and the additional surface horizontal movement caused by the two rotations and translations of the structural blocks in the middle of the goaf;

[0012] Combining the correlation mechanism, using the probability integral method to predict the surface horizontal movement amount caused by the rotation and inclination of the structural blocks, and combining a set proportion of the subsidence value to substitute and calculate the additional surface horizontal movement amount caused by the two rotations and translations of the structural blocks, and constructing a surface horizontal movement prediction model based on this;

[0013] Obtaining the engineering parameters of the target mining area, including the geological mining parameters of the working face and the prediction parameters of the probability integral method, and inputting them into the surface horizontal movement prediction model to obtain the horizontal movement value of any point on the surface; evaluating the surface horizontal movement situation of the engineering surface in the target mining area based on the horizontal movement value of any point on the surface.

[0014] Further, the identifying and analyzing the correlation mechanism between the surface horizontal movement in the mining area and the movement of the overlying rock structure in the mining area further includes:

[0015] Identifying and determining the first type of source and characteristics of the surface horizontal movement, and based on the translation effect generated by the rotation and inclination of the structural blocks at the goaf boundary, determining that the part of the surface horizontal movement caused by the inclination of the structural blocks is concentrated in the goaf boundary area and is symmetric, and is proportional to the surface inclination deformation;

[0016] And, identifying and determining the second type of source and characteristics of the surface horizontal movement, and based on the translation effect generated by the two rotations and translations of the structural blocks in the middle of the goaf, determining that the part of the surface horizontal movement caused by the translation of the structural blocks is mainly located in the middle of the mining area, along the working face advancing direction, and is proportional to the surface subsidence.

[0017] Further, the constructing the surface horizontal movement prediction model includes:

[0018] (1) Using the probability integral method formula, according to the surface tilt deformation, horizontal movement coefficient, and working face mining depth parameters, calculate the surface horizontal movement amount u T (x) caused by the tilt of the structural block. 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 working face mining depth; tanβ is the tangent of the main influence angle in the probability integral parameters; r is the main influence radius;

[0021] (2) Use the subsidence value W(x,y) at a set ratio to calculate the additional horizontal movement amount, and accumulate the translational movement amounts of multiple structural blocks within the influence range to obtain the additional horizontal movement amount u m (x,y) of the surface point. 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 value of the proportionality coefficient C is set according to the working face coal thickness, lithology, working face mining depth, and advancing speed, specifically between 0.1 and 0.3;

[0024] (3) Superimpose the horizontal movement amount caused by the tilt of the structural block and the additional horizontal movement amount caused by the translation of the structural block to obtain the total horizontal movement amount u(x,y) of the surface point. The expression is:

[0025] u(x,y) = u T (x,y) + C·W(x,y),

[0026] Furthermore, the prediction method further includes:

[0027] Under the condition of over-sufficient mining, the additional horizontal movement value in the middle of the mining area reaches the maximum. Use the maximum subsidence value to calculate the maximum additional horizontal movement value in the middle of the mining area The expression is:

[0028]

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

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

[0031]

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

[0033] And based on the extreme value U of the horizontal surface movement along the strike of the surface max evaluate the horizontal surface movement of the engineering surface in the target mining area.

[0034] Second aspect, the present invention proposes a surface horizontal movement prediction system based on the theory of underground structure movement mode, which is applied to execute the prediction method described in any one of the above, and the system includes:

[0035] The first analysis module is used to identify and analyze the correlation mechanism between the surface horizontal movement in the mining area and the movement of the overlying strata structure in the mining area. The correlation mechanism includes the surface horizontal movement caused by the rotation and inclination of the boundary structural blocks in the goaf, and the additional surface horizontal movement caused by the two rotations and translations of the middle structural blocks in the goaf;

[0036] The model construction module is used to combine the correlation mechanism, adopt the probability integral method to predict the surface horizontal movement amount caused by the rotation and inclination of the structural blocks, and combine the settlement value of a set ratio to substitute and calculate the additional surface horizontal movement amount caused by the two rotations and translations of the structural blocks, and construct a surface horizontal movement prediction model based on this;

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

[0038] Furthermore, the model construction module includes:

[0039] The correlation mechanism analysis unit is used to analyze and determine in detail the correlation mechanism between the surface horizontal movement in the mining area and the movement of the overlying strata structure in the mining area;

[0040] The probability integral method application unit is used to calculate the surface horizontal movement amount and surface settlement value caused by the inclination of the structural blocks according to the surface tilt deformation, horizontal movement coefficient and working face mining depth parameters;

[0041] The additional horizontal movement calculation unit is used to calculate the additional horizontal movement by substituting the settlement of a set ratio;

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

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

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

[0045] wherein, the processor is configured to execute the instructions to implement the prediction method as described in any one of the above.

[0046] In a fourth aspect, the present invention provides a computer-readable storage medium, when the instructions in the computer-readable storage medium are executed by a processor of an electronic device, enabling the electronic device to execute the prediction method as described in any one of the above.

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

[0048] 1. By deeply identifying and analyzing the complex correlation mechanism between the ground surface horizontal movement in the mining area and the movement of the overlying strata structure during mining, especially considering the double influence of the rotation and inclination of the boundary structural blocks in the goaf and the two-time rotation and translation of the middle structural blocks on the ground surface horizontal movement, the present invention constructs a more accurate prediction model for the ground surface horizontal movement. This technical solution significantly improves the prediction accuracy of the ground surface horizontal movement, 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 the ground surface horizontal movement, but also designs a complete set of system, device and storage medium implementation schemes, enabling this method to be efficiently and conveniently applied to actual projects. Through the integrated system module design, including functions such as correlation mechanism analysis, probability integral method application, additional horizontal movement calculation and total horizontal movement prediction, the present invention realizes the automation and intelligence of the ground surface horizontal movement prediction, effectively reducing human errors and improving work efficiency. At the same time, using advanced electronic devices and storage media ensures the accuracy and traceability of the 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 is a flowchart of a method for predicting the ground surface horizontal movement in the mining area based on the theory of underground structure movement mode provided by the present invention;

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

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

[0053] Figure 4 It is a position map of the layout of some observation stations and the 1414 working face of Guqiao Mine in the case of the present invention;

[0054] Figure 5 It is a subsidence fitting map of the 1414 working face of Guqiao Mine in the case of the present invention;

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

[0056] Figure 7 It is a position map of the layout of some observation stations and the 205 working face of Longde Mine in the case of the present invention;

[0057] Figure 8 It is a subsidence fitting map of the 205 working face of Longde Mine in the case of the present invention;

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

[0059] Figure 10 It is a position map of the layout of some observation stations and the 4201 working face of Majialiang Mine in the case of the present invention;

[0060] Figure 11 It is a subsidence fitting map of the 4201 working face of Majialiang Mine in the case of the present invention;

[0061] Figure 12 It is a horizontal movement fitting map of the 4201 working face of Majialiang Mine in the case of the present invention. Detailed implementation manners

[0062] The following further describes the present application in detail with reference to the accompanying drawings. It is necessary to point out here that the following specific implementation manners are only used to further illustrate the present application and cannot be understood as limiting the protection scope of the present application. Those skilled in the art can make some non-essential improvements and adjustments to the present application according to the above application content.

[0063] Example 1

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

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

[0066] Identify and analyze the correlation mechanism between the surface horizontal movement in the mining area and the movement of the overlying strata structure. The correlation mechanism includes the surface horizontal movement caused by the rotation and inclination of the structural blocks at the goaf boundary, and the additional surface horizontal movement caused by the two rotations and translations of the structural blocks in the middle of the goaf.

[0067] Furthermore, the correlation mechanism for identifying and analyzing the surface horizontal movement in the mining area and the movement of the overlying strata structure also includes:

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

[0069] And, identify and determine the second type of source of the surface horizontal movement. Based on the translation effect generated by the two rotations and translations of the structural blocks in the middle of the goaf, it is determined that the part of the surface horizontal movement caused by the translation of the structural blocks is mainly located in the middle of the mining area, along the working face advancing direction, and is proportional to the surface subsidence.

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

[0071] Combined with the correlation mechanism, use the probability integral method to predict the surface horizontal movement amount caused by the rotation and inclination of the structural blocks, and combine the set proportion of the subsidence value to replace and calculate the additional surface horizontal movement amount caused by the two rotations and translations of the structural blocks. The value of the proportionality coefficient C is set according to the mining thickness of the working face, lithology, mining depth of the working face and advancing speed, specifically between 0.1 and 0.3.

[0072] Superimpose the horizontal movement amount caused by the inclination of the structural blocks and the additional horizontal movement amount caused by the translation of the structural blocks to obtain the total horizontal movement amount of the surface point, and construct a prediction model for the surface horizontal movement based on this.

[0073] S3. Obtain and input engineering parameters:

[0074] Obtain the engineering parameters of the target mining area, including the mining conditions of the working face address and the probability integral parameters, and input them into the prediction model of the surface horizontal movement to obtain the horizontal movement value of any point on the surface; evaluate the surface horizontal movement situation of the target mining area project based on the horizontal movement value of any point on the surface.

[0075] S4. Evaluation and verification:

[0076] Evaluate the surface horizontal movement situation of the target mining area project 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. Use the maximum subsidence value to calculate the maximum additional horizontal movement value in the middle of the mining area. Determine the extreme value u of the surface strike horizontal movement based on the total horizontal movement amount max, and evaluate the horizontal movement of the engineering ground surface in the target mining affected area based on this extreme value. Adjust and optimize the model parameters according to the verification results.

[0077] For the identification and analysis of associated steps in this embodiment, it includes:

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

[0079] Analyze the translation effect generated by the rotation and inclination of structural blocks at the goaf boundary, and determine that the part of the ground surface horizontal movement caused by the inclination of structural blocks is mainly concentrated in the goaf boundary area.

[0080] Verify the proportional relationship between the ground surface horizontal movement and the ground surface tilt deformation through the observed data and numerical simulation results, and determine that this part of the horizontal movement is symmetric.

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

[0082] Analyze the translation effect generated by the two rotations and translations of structural blocks in the middle of the goaf, and determine that the part of the ground surface horizontal movement caused by the translation of structural blocks is mainly located in the middle of the mining affected area.

[0083] Verify the proportional relationship between the ground surface horizontal movement and the ground surface subsidence through the observed data and numerical simulation results, and determine that this part of the horizontal movement is distributed along the working face advancing direction.

[0084] In order to deeply analyze the correlation mechanism between the ground surface horizontal movement in the mining affected area and the movement of overlying strata structures in mining, the present invention adopts the method of numerical simulation. The specific process is as follows:

[0085] (1) Model construction:

[0086] According to the geological parameters and mining parameters of the mining affected area, construct a geomechanical model. This model should be able to accurately reflect the law of the movement of overlying strata structures in mining. Set reasonable boundary conditions and initial conditions in the model to ensure the accuracy of numerical simulation.

[0087] (2) Numerical simulation:

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

[0089] During the simulation process, pay attention to the changes in the movement of overlying strata structures in mining, especially the generation mechanism and influencing factors of the rotation, inclination and translation effects of structural blocks.

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

[0091] (3) Result analysis:

[0092] Compare the numerical simulation results with the observed data for comparative analysis to verify the accuracy of the numerical simulation.

[0093] Based on the numerical simulation results, deeply analyze the correlation mechanism between the surface horizontal movement and the movement of the overlying strata structure during mining, including the influence of the rotation, inclination, and translation effects of structural blocks on the surface horizontal movement.

[0094] Combined with the results of laboratory similar material simulation experiments, further verify the reliability and accuracy of the numerical simulation results.

[0095] In summary, through precise and continuous observation data collection and preprocessing, as well as the numerical simulation process based on geomechanics analysis software, the present invention deeply analyzes the correlation mechanism between the surface horizontal movement in the mining area and the movement of the overlying strata structure during mining. This process provides a scientific basis and technical support for constructing an accurate prediction model of surface horizontal movement.

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

[0097] (1) Using the probability integral method formula, calculate the surface horizontal movement amount u T (x) caused by the inclination of the structural block according to the surface tilt deformation, horizontal movement coefficient, and working face mining depth parameters. 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 working face mining depth; tanβ is the tangent of the main influence angle in the probability integral parameter; r is the main influence radius;

[0100] (2) Use the subsidence value W(x,y) at a set ratio to calculate the additional horizontal movement amount, and accumulate the translational movement amounts of multiple structural blocks within the influence range to obtain the additional horizontal movement amount u m (x,y) of the surface point. 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 value of the proportionality coefficient C is set according to the mining thickness of the working face, lithology, working face mining depth, and advancing speed, specifically between 0.1 and 0.3;

[0103] (3) Superimpose the horizontal displacement caused by tilting the structural block and the additional horizontal displacement caused by translating the structural block to obtain the total horizontal displacement u(x, y) of the ground surface point, and the expression is:

[0104] u(x, y) = u T (x, y) + C·W(x, y),

[0105] Further preferably, the prediction method further includes:

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

[0107]

[0108] u c is the horizontal displacement in the middle of the mined area, is the maximum additional horizontal displacement value in the mined area; W max is the maximum ground surface subsidence value in the mined area;

[0109] And, determine the extreme value U of the horizontal displacement along the strike of the ground surface based on the total horizontal displacement u(x, y) max The expression is:

[0110]

[0111] Among them, is the maximum horizontal displacement of the ground surface, is the maximum additional horizontal displacement value;

[0112] And evaluate the horizontal displacement of the engineering ground surface in the target mined area based on the extreme value U of the horizontal displacement along the strike of the ground surface max

[0113] According to the above embodiments, the prediction method in the present invention systematically analyzes the sources, mechanisms and laws of horizontal displacement, constructs a prediction model, and solves the problem that the traditional model cannot explain the horizontal displacement phenomenon in the middle of the mined area. By identifying and analyzing the correlation mechanism between the horizontal displacement of the ground surface in the mined area and the movement of the overlying strata structure in the mined area, the accuracy of prediction is improved.

[0114] Combined with Figure 2 , based on the same inventive concept, this embodiment also proposes a prediction system for the horizontal displacement of the ground surface in the mined area based on the theory of the movement mode of underground structures, which is applied to execute the prediction method as described above. The system includes:

[0115] ​The first analysis module 40 is used to identify and analyze the correlation mechanism between the surface horizontal movement in the mining area and the movement of the overlying strata structure. The correlation mechanism includes the surface horizontal movement caused by the rotation and inclination of the boundary structural blocks in the goaf, and the additional surface horizontal movement caused by the two rotations and translations of the central structural blocks in the goaf.

[0116] The model construction module 41 is used to combine the correlation mechanism, use the probability integral method to predict the surface horizontal movement caused by the rotation and inclination of the structural blocks, and combine a set proportion of the subsidence value to substitute and calculate the additional surface horizontal movement caused by the two rotations and translations of the structural blocks, and thus construct 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; evaluate the surface horizontal movement of the engineering in the target mining area based on the horizontal movement value of any point on the surface.

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

[0119] It can be understood that the model construction module 41 further includes a correlation 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 correlation mechanism in detail, calculate the surface horizontal movement caused by the inclination of the structural blocks, calculate the additional horizontal movement, and superimpose to obtain the total horizontal movement.

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

[0121] The correlation mechanism analysis unit 411 is used to analyze and determine the correlation mechanism between the surface horizontal movement in the mining area and the movement of the overlying strata structure in detail.

[0122] The probability integral method application unit 412 is used to calculate the surface horizontal movement caused by the inclination of the structural blocks according to the surface tilt deformation, horizontal movement coefficient, and working face mining depth parameters.

[0123] The additional horizontal movement calculation unit 413 is used to substitute and calculate the additional horizontal movement by using a set proportion of the subsidence value, and accumulate the translation movement amounts of multiple structural blocks within the influence range to obtain the additional horizontal movement amount of the surface point.

[0124] The total horizontal displacement calculation unit 414 is configured to superimpose the horizontal displacement caused by the inclination of the structural block and the additional horizontal displacement caused by the translation of the structural block to obtain the total horizontal displacement of the ground surface point.

[0125] The following verifies the prediction method in this embodiment by combining an engineering case.

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

[0127] The 1414 working face in Guqiao Mine has a strike length of 2167 m, a dip length of 251 m, a mining height of 2.8 m, an average mining depth of 748 m, and an average dip angle of 4°. The mining process lasted for 340 days, and the average coal cutting speed was 6.28 m / d. Fully mechanized coal mining was adopted, with the method of mining the full height at one time, and the roof was managed by the fully caving method. Two observation lines were arranged on the ground surface. One ML line was arranged along the strike direction, and one MS line was arranged along the dip direction. The relative position relationship between the observation lines and the working face is as Figure 3 shown. Through a large number of monitoring, the final subsidence and horizontal displacement curves of the ground surface points along the strike and dip observation lines are as Figure 4 shown.

[0128] Using the geological and mining parameters of the 1414 working face in Guqiao Mine and the measured surface strike horizontal displacement values, the differences in the fitting effects between the probability integral method and the surface horizontal displacement prediction model in the present invention are compared. As Figure 5 and 6 shown.

[0129] From Figure 5 it can be seen that the predicted subsidence value 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%. This shows that the subsidence prediction model and prediction parameters of the probability integral method are relatively accurate. Figure 6 In

[0130] the probability integral method predicts that the horizontal displacement is basically symmetric, which is significantly inconsistent with the measured data. The RMSE of the horizontal displacement fitting is 206 mm, and the relative error is 27.5%. Taking the calculated additional horizontal displacement with C = 0.18 and superimposing it with the predicted result of the probability integral method, the calculation result of the model of the present invention can well fit the systematic horizontal displacement in the middle of the mining area, and the positive and negative extreme values of the horizontal displacement at the inflection point boundary of the working face are relatively consistent with the measured horizontal displacement data. The RMSE of the horizontal displacement fitting is 53 mm, and the relative error is 7.1%, which greatly improves the application effect of the model.

[0131] The strike length of the 205 working face in Longde Mine is 3,640 m, the dip length is 300 m, the mining depth of the working face is 228 m, the average coal seam thickness is 3.5 m, and the coal seam dip angle is <1°. A strike semi-basin observation line A01 - A55 was arranged on one side of the open-off cut, and the working measurement points are all 10 m apart. The movement and deformation data of the observation station were obtained through leveling and total station plane observation methods. The layout of the observation station and the working face position are as Figure 7 shown.

[0132] Using the traditional probability integral method prediction method and the prediction method of the present invention, the fitting effects of the two in horizontal movement are as Figure 8 and 9 shown.

[0133] From Figure 8 the fitting effect, it can be seen that the predicted subsidence value by the probability integral method fits well with the measured subsidence data. The RMSE of subsidence fitting is 50 mm, and the relative error is 2.4%. This shows that the subsidence prediction model and prediction parameters of the probability integral method are relatively accurate. Figure 9 In

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

[0135] The strike length of the 4201 working face in Majialiang Mine is 1,740 m, the dip length is 250 m, the mining depth of the working face is 630 m, and the coal seam thickness is 9.24 m, which is a horizontal coal seam. A surface movement observation station was arranged along the strike of the working face on one side of the stoping line. The distance between the observation stations is 25 m, and the subsidence and horizontal movement values of the observation stations were obtained through daily observations. The relative position relationship between the observation station and the working face is as Figure 10 shown.

[0136] Using the traditional probability integral method prediction method, the comparison effect between the surface movement and deformation curve obtained by fitting and the measured deformation curve is as Figure 11 and 12 shown.

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

[0138] Combined with Figure 3 , in another embodiment of the present invention, an electronic device 50 is further proposed, including:

[0139] A processor 51; a memory 52 for storing instructions executable by the processor;

[0140] Wherein, the processor 51 is configured to execute instructions to implement the prediction method as described above.

[0141] In another embodiment of the present invention, a computer-readable storage medium is further proposed. When the instructions in the computer-readable storage medium are executed by the processor 51 of the electronic device 50, the electronic device 50 can execute the prediction method as described above.

[0142] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part 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 devices. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wirelessly (such as infrared, wireless, microwave, etc.). The computer-readable storage medium may be any available medium that the computer can access or a data storage device such as a server or data center that includes one or more integrated available media. The available media may be magnetic media (for example, floppy disks, hard disks, magnetic tapes), optical media (for example, DVDs), or semiconductor media (for example, solid state disk (SSD)).

[0144] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. A professional technician can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of this application.

[0145] The above embodiments are only used to illustrate the technical solutions of this application, rather than to limit them; although this application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and 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 this 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 correlation mechanism between the horizontal movement of the ground surface in the mining area and the movement of the overburden structure, including the horizontal movement of the ground surface caused by the rotation and tilt 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; Combined with the above-mentioned correlation mechanism, the probability integral method is used to predict the horizontal movement of the ground surface caused by the rotation and tilt of the structural block, and the additional horizontal movement of the ground surface caused by the two rotations and translations of the structural block is calculated by replacing the subsidence value with a set ratio, and a new system model for predicting the horizontal movement of the ground surface 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 the parameters 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. A method for predicting horizontal surface movement in a mining area based on underground structure movement mode theory according to claim 1, characterized in that: The identification and analysis of the correlation mechanism between the horizontal movement of the surface 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, and is symmetrical and proportional to the deformation of the surface tilt. Also, the second source of horizontal surface movement is identified and determined, and 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 advancement direction 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 method of constructing a surface horizontal movement prediction model comprises: (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: u T (x)=b·r·i(x)=H·b·i(x) / tanβ Among them, 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; (2) The additional horizontal movement u caused by the accumulation of translational movement is calculated by using the set proportional sinking value W(x,y) instead of m (x,y), the expression is: u m (x,y)=C·W(x,y) Wherein, W(x,y) is the subsidence value of any surface point (x,y); the proportional coefficient C value is set according to the thickness of the working face, lithology, working face mining depth and advancement speed, and is specifically between 0.1 and 0.3; (3) Horizontal movement u caused by tilting the structural block T (x, y) and the additional horizontal movement u caused by the translation of the structural block m (x, y) are superimposed to obtain the total horizontal movement of the surface point u(x, y), which is expressed as: u(x,y)=u T (x,y)+C·W(x,y), 4. 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 also includes: 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 expression is: 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; And, based on the total horizontal movement u(x, y), determine the horizontal movement extreme value u of the surface trend max , 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, the horizontal movement extreme value u max Assess the horizontal movement of the engineering surface 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 also includes: Comparing the measured data of 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 in that: Applied to perform 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 association mechanism between the horizontal movement of the surface of the mining area and the movement of the mining overburden structure, wherein the association mechanism includes the horizontal movement of the surface caused by the rotation and tilt of the boundary structure block of the goaf area, and the additional horizontal movement of the surface caused by the two rotation and translation of the structure block in the middle of the goaf area; A model building module is used to combine the association mechanism, use the probability integration method to predict the surface horizontal movement caused by the rotation and tilt of the structural block, and replace the calculation of the additional surface horizontal movement caused by the two rotations and translations of the structural block with the subsidence value of the set ratio, and thereby construct a surface horizontal movement prediction model; 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 engineering project in the target mining area is evaluated.

7. A system for predicting horizontal surface movement in mining areas based on underground structure movement mode theory according to claim 6, characterized in that: The model building module includes: The correlation mechanism analysis unit is used to analyze and determine 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 according to 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 estimation method according to any one of claims 1 to 5.

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