A method for predicting surface subsidence in coal mining considering the flow volume of aeolian sand

Abstract

The present invention relates to a method for predicting surface subsidence in coal mining that takes into account the flow of aeolian sand, and belongs to the field of surface aeolian sand flow measurement in mining subsidence basins. First, permeable sand-isolating polyester meshes with measuring nails are evenly spaced at different positions on the surface of the mining working face as aeolian sand thickness observation stations. RTK technology and steel ruler distance measurement method are used for observation to obtain surface movement deformation values and surface aeolian sand thickness change values at different positions of the surface subsidence basin under different mining degrees; then correlation analysis and multivariate linear regression are performed on the measured parameters to obtain a calculation formula for the flow of aeolian sand under the influence of mining; finally, the probability integral method is used to calculate the corresponding surface subsidence prediction value, calculate the surface subsidence value caused by the flow of aeolian sand, and calculate the actual surface subsidence of coal mining excluding the influence of the flow of aeolian sand. It is easy to implement, the calculation steps are simple, and it can effectively define the degree of influence of aeolian sand movement on surface mining subsidence in the Ordos mining area.

Description

Technical Field

[0001] The invention relates to a method for predicting surface subsidence during coal mining, and is particularly suitable for a method for predicting surface subsidence during coal mining taking into account aeolian sand flow, and belongs to the field of surface aeolian sand flow measurement in mining subsidence basins. Technical Background

[0002] Aeolian sand is a loose, sandy sediment formed by geological processes and distributed at and below the surface, modified by wind. It is widely distributed in the Ordos mining area of my country. Due to its low compressibility, low water content, and high mobility, aeolian sand is significantly transported by wind under mining conditions. Consequently, the surface subsidence characteristics of mining in aeolian sand areas differ significantly from those under conventional geological mining conditions. Specifically, these include smaller subsidence values, uplift of basin margins, and a correlation between basin characteristics and flow rate. This reduces the applicability of probability integral prediction methods in aeolian sand mining areas. Furthermore, because coal mining and aeolian sand movement jointly affect surface soil displacement, direct surface displacement and elevation measurements cannot determine the direction and volume of aeolian sand movement, making it difficult to define the extent to which aeolian sand transport in mining areas affects surface subsidence. At the same time, the Ordos Basin's coal and natural gas deposits converge in similar locations. This problem severely restricts the construction of natural gas engineering facilities in the gas-coal intersection zone and poses a safety threat to gas wells and buried pipelines. Therefore, it is urgent to accurately measure the flow of aeolian sand in subsidence areas, quantify the relationship between aeolian sand and subsidence characteristics, calculate the flow of aeolian sand throughout the basin, and accurately predict surface subsidence in mining areas.

[0003] The prior art with publication number CN106593524A discloses a method for dynamically predicting surface subsidence in solid filling mining. This method combines a time-varying subsidence model of the top plate in solid filling mining with the Knothe time function, and uses the superposition principle to accumulate the surface subsidence caused by the compression deformation of the filling body at different times, thereby establishing a set of dynamic prediction models for the surface in solid filling mining. Using the method of the present invention, the dynamic deformation value of the surface subsidence in solid filling mining that changes with time can be predicted based on parameters such as the rock formation time influence coefficient, the filling body compression deformation time influence coefficient, mining depth, mining thickness, coal seam inclination, predicted working face size, and probability integral method prediction parameters. However, this method is computationally complex and does not take into account the impact of wind and sand on the surface in a desertified environment. Therefore, the prediction accuracy is low when used in environments such as northwest my country. Summary of the Invention

[0004] In response to the problems in the above technologies, a method for measuring and calculating the thickness change of surface aeolian sand is provided, which has simple steps, high accuracy, and takes into account the impact of mining and the characteristics of aeolian sand flow.

[0005] To achieve the above technical objectives, the present invention provides a method for predicting surface subsidence in coal mining that takes into account the flow of aeolian sand, and the steps are as follows:

[0006] First, aeolian sand thickness observation stations with measuring spikes are evenly spaced at different locations on the surface of the mining face. That is, a permeable sand-isolating polyester mesh is laid at fixed distances along the strike and dip, and the mesh is fixed with long measuring spikes around the edges.

[0007] Then, real-time dynamic RTK measurement technology and steel tape distance measurement method were used to conduct long-term observations to obtain the surface movement deformation values and surface aeolian sand thickness change values Δh at different locations in the surface subsidence basin under different mining degrees. 沙 , the surface movement deformation value includes the subsidence W 测 、Tilt I 测 , curvature K 测 , horizontal movement U 测 , horizontal deformation ε 测 ;

[0008] Then the surface movement deformation value and the surface aeolian sand thickness change value Δh 沙 Correlation analysis and multiple linear regression were performed to obtain the prediction formula for the thickness change of aeolian sand under the influence of mining;

[0009] Finally, based on the probability integral prediction parameters of this mining area recorded in the mobile observation analysis report, the surface subsidence value W is estimated using the probability integral method. 预 , the surface subsidence value W caused by the flow of aeolian sand is calculated based on the established prediction formula for the thickness change of aeolian sand. 沙 , and the actual surface subsidence value W of the mining area under the condition of a single mining factor can be obtained by subtracting the two 实 .

[0010] Furthermore, aeolian sand thickness observation stations with measuring spikes are arranged at fixed intervals along the direction and inclination of the planned mining working face. The starting point of the aeolian sand thickness observation station should be in an area not disturbed by mining. The observation station adopts the method of laying a 2m×2m permeable sand-isolating polyester dense mesh on the surface to evenly cover 0.2m of soft topsoil. The permeable sand-isolating polyester dense mesh is fixed with 1m long steel measuring spikes on all sides, and the buried depth of the steel measuring spikes is >0.5m.

[0011] Furthermore, as the mining of the working face progresses, the three-dimensional coordinates C of the measuring pins of the aeolian sand thickness observation station are regularly observed. x,y,z and the change in aeolian sand thickness Δh 沙 ;

[0012] RTK coordinate point measurement is performed on the four measuring pins at each observation station to obtain the three-dimensional coordinates C of the measuring pins at all observation stations. x,y,z The average value of the X, Y, and Z axis coordinates of the four measuring pins of the observation station is used as the point coordinate value of the observation station. To represent the movement deformation eigenvalue of the grid area;

[0013] By analyzing and calculating the three-dimensional coordinate observation results of different periods at the i-th observation station, the ground movement deformation value of each observation station under different mining degrees is obtained: sinking W 测 、Tilt I 测 , curvature K 测 , horizontal movement U 测 , horizontal deformation ε 测 , the calculation formula is as follows:

[0014] 3.1. The sinking of the i-th observation station during the m-th observation:

[0015] W i =H i0 -H im

[0016] Where W n is the sinking value of the i-th observation station; H i0 ,H im are the elevations of the i-th observation station at the first and m-th observations, respectively;

[0017] 3.2. Tilt of two adjacent observation stations:

[0018]

[0019] Tilt component in the Y-axis (strike) direction:

[0020] Total tilt:

[0021] Where Δx i-i+1 is the x-coordinate difference between the i-th observation station and the i+1-th observation station; Δy i-i+1 is the y-coordinate difference between the i-th observation station and the i+1-th observation station; W i+1 ,W i represent the subsidence of the i+1th observation station and the i-th observation station respectively;

[0022] 3.3 The curvature near the i-th observation station, that is, the curvature between the i-1th observation station and the i+1th observation station:

[0023]

[0024] Where i i-1-i ,i i-i-1 represents the inclination from the i+1th observation station to the ith observation station and from the ith observation station to the i-1th observation station; Δx i+1-i ,Δy i+1-i ,Δy i-i-1They represent the x-coordinate difference and y-coordinate difference from the i+1th observation station to the i-th observation station and from the i-th observation station to the i-1th observation station, respectively;

[0025] 3.4. Horizontal movement of the i-th observation station:

[0026] Horizontal movement in the X-axis direction: U ix =X im -X i0

[0027] Horizontal movement in the Y-axis direction: U iy =Y im -Y i0

[0028] Total horizontal movement:

[0029] Where, X im ,X i0 ,Y im ,Y i0 The horizontal and vertical coordinates of the mth observation and the first observation of the i-th observation station are represented respectively;

[0030] 3.5. Horizontal deformation between the i-th observation station and the i+1 observation station:

[0031] Horizontal deformation in the X-axis direction:

[0032] Horizontal deformation along the Y axis:

[0033] Total horizontal deformation:

[0034] In the formula, (x i+1～i ) m ,(x i+1～i )0,(y i+1～i ) m ,(y i+1～i )0 represents the horizontal and vertical coordinates of the i+1th observation station and the i-th observation station at the time of m observations and the first observation, respectively.

[0035] The change in aeolian sand thickness Δh is obtained by measuring the distance between the ground surface and the polyester mesh with a millimeter steel ruler and subtracting the initial cover soil thickness. 沙 , select 4 to 8 undulating locations in each permeable sand-isolating polyester mesh to measure the height, and take the average value of the results as the change value of the aeolian sand thickness at the i-th observation station Considering the influence of seasonal wind speed and precipitation, observations should be continued for 1 year / 12 periods or more;

[0036] Furthermore, the ground displacement values W at different locations under different mining conditions are测 , I 测 , K 测 、U 测 , ε 测 and the change in aeolian sand thickness Δh 沙 By obtaining the correlation analysis and linear regression between the two, a method for predicting the flow of aeolian sand at any position in the entire basin with respect to the surface movement deformation value is obtained;

[0037] The regression formula of aeolian sand flow under the influence of mining is as follows:

[0038] Δh 沙 =v1W 测 +v2I 测 +v3K 测 +v4U 测 +v5ε 测 +b

[0039] Where W is the surface subsidence value; I is the surface inclination value; K is the surface curvature deformation value; U is the surface horizontal movement value; ε is the surface horizontal deformation value; v1, v2, v3, v4, and v5 are correlation coefficients obtained by inversion from existing measurement results; and b is a constant term.

[0040] Furthermore, combined with the mining plan of the mining area, the mining engineering plan and the drilling histogram data, the relevant information of the planned mining working face was collected and sorted out, including the working face width a, face length b, mining depth H, mining thickness m, inclination angle α, and the information of prediction parameters, including the subsidence coefficient q, the main influence angle tangent tanβ, the inflection point offset S, the mining influence propagation angle θ, etc. The probability integral method was used to predict the surface movement and deformation of the working face mining, and the surface movement and deformation prediction values W at different locations were obtained. 测 , I 测 , K 测 、U 测 , ε 测 ;

[0041] The prediction formula of the probability integral method is:

[0042] 5.1. Subsidence value W(x,y) of any point A(x,y)

[0043] W(x,y)=W cm C′ x C′ y

[0044] in:

[0045]

[0046] Where: W cm Indicates the maximum surface subsidence under full mining conditions, W cm=mqcosα; m represents the thickness of the mined coal seam; q represents the surface subsidence coefficient; α represents the inclination angle of the coal seam; C′ x , C′ y It is expressed as the subsidence distribution coefficient of the point to be determined at the projection point on the strike and dip main sections; l and L represent the strike length and the calculated mining width in the dip direction on the surface after the inflection point of the mining area is shifted; r, r1, and r2 represent the main influencing radii in the strike, downhill, and uphill directions, respectively.

[0047] 5.2. Any point A(x,y) on the surface Direction tilt deformation value for:

[0048]

[0049] Where: T(x,y) max Indicates the maximum tilt value of the point to be found, Indicates the angle between the maximum tilt value and the OX axis, that is, the angle of rotation in the counterclockwise direction, T x , T y It represents the tilt deformation value of the point to be determined after superposition at the projection point along the strike and dip main sections.

[0050] 5.3. Any point A(x, y) on the surface Directional curvature deformation for:

[0051]

[0052] Where: K(x,y) max , K(x,y) min Represents the maximum and minimum curvature deformation values of the point to be determined; K x , K y It represents the curvature value of the point to be determined along the strike and dip after superposition at the projection of the main section.

[0053] 5.4. Any point A(x,y) on the surface Horizontal movement value in the direction for:

[0054]

[0055] Where: Expressed as the angle between the maximum horizontal movement direction and the OX axis,

[0056] U x 、U y They are respectively expressed as the horizontal movement values of the point to be determined along the strike and dip at the projection point of the main section.

[0057] 5.5. Any point A(x,y) on the surface Horizontal deformation value of the direction for:

[0058]

[0059]

[0060] Where: ε(x,y) max ,ε(x,y) min Expressed as the maximum and minimum horizontal deformation values of the point to be determined; Indicates the angle between the maximum horizontal deformation direction and the OX axis, ε x , ε y It is expressed as the horizontal deformation value superimposed on the projection of the main section along the strike and dip of the point to be determined.

[0061] Furthermore, based on the probability integral prediction value of surface movement and deformation, combined with the established formula for the change of aeolian sand thickness, the impact of aeolian sand flow on surface subsidence can be deduced:

[0062] W 沙 =v1W 预 +v2I 预 +v3K 预 +v4U 预 +v5ε 预 +b

[0063] And the actual surface subsidence value W of coal mining after eliminating the influence of aeolian sand flow can be calculated. 实 :

[0064] W 实 =W 预 -W 沙 .

[0065] Beneficial effects: This method realizes the precise measurement of aeolian sand flow rate affected by mining on the basis of considering natural factors and coal mining factors, constructs a model relationship between surface movement deformation index and aeolian sand flow rate, and can realize the precise calculation of aeolian sand flow rate based on the prediction of the probability integral method commonly used in mining areas. It can provide technical support for defining the impact of aeolian sand on coal mining subsidence and implementing precise protection of buildings (structures) in gas-coal intersection areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 Schematic diagram of the effect of aeolian sand flow on the scope and degree of subsidence in an embodiment of the present invention;

[0067] Figure 2Schematic diagram of a device for measuring the flow of aeolian sand at different locations in a surface subsidence basin under coal mining according to an embodiment of the present invention; specifically, a top view and an oblique view of the installation of a water-permeable, sand-isolating polyester fine mesh;

[0068] Figure 3 It is a schematic diagram of the method for measuring and calculating the flow of aeolian sand in a coal mining subsidence basin according to the present invention. DETAILED DESCRIPTION

[0069] The present invention will be further described in detail below with reference to the figures and specific implementation process:

[0070] like Figure 1 and Figure 2 As shown in the figure, the present invention provides a method for predicting surface subsidence in coal mining that takes into account the flow of aeolian sand. First, aeolian sand thickness observation stations with measuring spikes are evenly spaced at different locations on the surface of the mining working face. That is, a permeable sand-isolating polyester dense mesh is laid at a fixed distance along the strike and dip, and the mesh is fixed with long measuring spikes around it. Then, RTK measurement technology and steel ruler distance measurement method are used to conduct long-term observations to obtain surface movement deformation values (sinking W) at different locations ignoring the influence of aeolian sand flow. 测 、Tilt I 测 , curvature K 测 , horizontal movement U 测 , horizontal deformation ε 测 ) and the change in surface aeolian sand thickness Δh 沙 ; Then the surface movement deformation value and the surface aeolian sand thickness change value Δh 沙 Correlation analysis and multivariate linear regression were performed to obtain the calculation formula for the flow of aeolian sand under the influence of mining; finally, based on the established formula, the corresponding surface subsidence prediction value W was calculated using the probability integral method. 预 The surface subsidence value W caused by the flow of aeolian sand can be calculated based on the established prediction formula for the thickness change of aeolian sand. 沙 , and can calculate the flow rate Δh after removing the aeolian sand 沙 The actual surface subsidence affected by coal mining W 实 .

[0071] like Figure 3 The specific steps shown are:

[0072] Step 1: First, place aeolian sand thickness observation stations with measuring spikes at regular intervals (50m) along the strike and inclination of the planned mining face. The starting point of the observation station should be in an area not disturbed by mining. The observation station is constructed by laying a 2m×2m permeable sand-isolating polyester mesh on the surface and evenly covering it with 0.2m of soft topsoil. The mesh is fixed with 1m long steel measuring spikes (buried at a depth of >0.5m).

[0073] Step 2: As the mining progresses, periodically (30 days) observe the coordinates, elevation, and thickness changes of the measuring pins. x,y,z Adopt RTK measurement method and take the average value of the three-dimensional coordinate measurement values of the four measuring pins as the coordinate value of the i-th observation point Change in aeolian sand thickness Δh 沙 Use a millimeter steel ruler to measure the distance between the ground surface and the polyester mesh. Select 4 to 8 places with undulating changes in the grid to measure the height. The average value of the results is taken as the change value of the aeolian sand thickness Δh at the i-th observation station. i Taking into account the influence of seasonal wind speed and precipitation, observations should be continued for 1 year (12 periods) or more;

[0074] Step 3: Collect the change in surface aeolian sand thickness Δh 沙 The observation results are compared with the measured surface deformation values (subsidence W 测 、Tilt I 测 , curvature K 测 , horizontal movement U 测 , horizontal deformation ε 测 ) and conduct correlation analysis. Based on the correlation analysis, multiple linear regression is performed to obtain the surface aeolian sand flow rate Δh under the influence of mining. 沙 The calculation formula is:

[0075] Δh 沙 =v1W 测 +v2I 测 +v3K 测 +v4U 测 +v5ε 测 +b

[0076] The form of the multivariate linear regression formula is shown in the text. The calculation process is performed using existing software such as MATLAB, and the process is not given here.

[0077] Step 4: Combined with the mining plan, mining engineering plan and drilling histogram data of the mining area, collect and organize the relevant information of the planned mining working face, including the working face width a, face length b, mining depth H, mining thickness m, inclination angle α, and prediction parameter information, including subsidence coefficient q, main influence angle tangent tanβ, inflection point offset S, mining influence propagation angle θ and other information. By predicting the surface movement and deformation of the planned mining working face under similar geological conditions in the mining area, the surface movement and deformation prediction values (subsidence W) at different positions of the planned working face can be obtained. 预 、Tilt I 预 , curvature K 预 , horizontal movement U 预 , horizontal deformation ε 预), and then bring the predicted value of the planned working face into the calculation formula of the aeolian sand flow obtained in step 3, and then calculate the subsidence value W caused by the aeolian sand flow at any position on the surface after the planned mining working face is mined. 沙 , and the flow rate of Δh after removing the aeolian sand can be calculated 沙 The actual surface subsidence affected by coal mining W 实 .in:

[0078] W 沙 =v1W 预 +v2I 预 +v3K 预 +v4U 预 +v5ε 预 +b

[0079] W 实 =W 预 -W 沙

[0080] Where: v1, v2, v3, v4, v5, b are known quantities, which are obtained by inversion in step 3.

Claims

1. A method for predicting surface subsidence in coal mining taking into account the flow of aeolian sand, characterized by Here are the steps: First, aeolian sand thickness observation stations with measuring spikes are evenly spaced at different locations on the surface of the mining face. That is, a permeable sand-isolating polyester mesh is laid at fixed distances along the strike and dip, and the mesh is fixed with long measuring spikes around the edges. Then, real-time dynamic RTK measurement technology and steel tape distance measurement method were used to conduct long-term observations to obtain the surface movement deformation values and surface aeolian sand thickness change values Δh at different locations in the surface subsidence basin under different mining degrees. 沙 , the surface movement deformation value includes the surface subsidence value W 测 , surface tilt value I 测 , surface curvature deformation value K 测 , surface horizontal movement value U 测 , surface horizontal deformation value ε 测 ; Then the surface movement deformation value and the surface aeolian sand thickness change value Δh 沙 Correlation analysis and multiple linear regression were performed to obtain the prediction formula for the thickness change of aeolian sand under the influence of mining; Finally, based on the probability integral prediction parameters of this mining area recorded in the mobile observation analysis report, the surface subsidence value W is estimated using the probability integral method. 预 , surface tilt value prediction value I 预 , surface curvature deformation prediction value K 预 , predicted value of surface horizontal movement U 预 , predicted value of surface horizontal deformation ε 预 , the surface subsidence value W caused by the flow of aeolian sand is calculated based on the established prediction formula for the thickness change of aeolian sand. 沙 , through the formula W 实 =W 预 -W 沙 The actual surface subsidence value W of the mining area under the condition of a single mining factor is obtained 实 .

2. The method for predicting surface subsidence in coal mining taking into account the flow of aeolian sand according to claim 1, characterized in that: Aeolian sand thickness observation stations with measuring spikes are arranged at fixed intervals along the direction and inclination of the planned mining working face. The starting point of the aeolian sand thickness observation station should be in an area not disturbed by mining. The observation station adopts the method of laying 2m×2m permeable sand-isolating polyester dense mesh on the surface to evenly cover 0.2m soft topsoil. The permeable sand-isolating polyester dense mesh is fixed with 1m long steel measuring spikes on all sides, and the buried depth of the steel measuring spikes is >0.5m.

3. The method for predicting surface subsidence in coal mining taking into account the flow of aeolian sand according to claim 1, characterized in that: As the mining of the working face progresses, the three-dimensional coordinates C of the measuring pins of the aeolian sand thickness observation station are regularly observed. x,y,z and the change in aeolian sand thickness Δh 沙 ; RTK coordinate point measurement is performed on the four measuring pins at each observation station to obtain the three-dimensional coordinates C of the measuring pins at all observation stations. x,y,z The average value of the X, Y, and Z axis coordinates of the four measuring pins of the observation station is used as the point coordinate value of the observation station. To represent the moving deformation eigenvalue of the grid area; By analyzing and calculating the three-dimensional coordinate observation results of different periods at the i-th observation station, the surface movement deformation value of each observation station under different mining degrees is obtained: the surface subsidence value W 测 , surface tilt value I 测 , surface curvature deformation value K 测 、 Surface horizontal movement value U 测 , surface horizontal deformation value ε 测 , the calculation formula is as follows: 3.

1. Subsidence of the i-th observation station during the m-th observation: Where W i is the sinking value of the i-th observation station; H im are the elevations of the i-th observation station at the first and m-th observations, respectively; 3.

2. Tilt between two adjacent observation stations: Tilt component in the X-axis direction: Tilt component in the Y-axis direction: Total tilt: Where Δx i-i+1 is the x-coordinate difference between the i-th observation station and the i+1-th observation station; Δy i-i+1 is the y-coordinate difference between the i-th observation station and the i+1-th observation station; W i+1 ,W i represent the subsidence of the i+1th observation station and the i-th observation station respectively; 3.3 The curvature near the i-th observation station, that is, the curvature between the i-1th observation station and the i+1th observation station: Where i +1-i ,i i-i-1 They represent the inclination from the i+1th observation station to the ith observation station and from the ith observation station to the i-1th observation station respectively; Δx i+1-i ,Δx i-i-1 ,Δy i+1-i ,Δy i-i-1 They represent the x-coordinate difference and y-coordinate difference from the i+1th observation station to the i-th observation station and from the i-th observation station to the i-1th observation station, respectively; 3.

4. Horizontal movement of the i-th observation station: Horizontal movement in the X-axis direction: U ix =X im -X i0 Horizontal movement in the Y-axis direction: U iy =Y im -Y i0 Total horizontal movement: Where, X im ,X i0 ,Y im ,Y i0 The horizontal and vertical coordinates of the mth observation and the first observation of the i-th observation station are represented respectively; 3.

5. Horizontal deformation between the i-th observation station and the i+1 observation station: Horizontal deformation in the X-axis direction: Horizontal deformation along the Y axis: Total horizontal deformation: In the formula, (x i+1-i ) m ,(y i+1-i ) m They represent the horizontal and vertical coordinate differences between the i+1th observation station and the i-th observation station at the m-th observation time, (x i+1-i )0,(y i+1-i )0 respectively represent the horizontal and vertical coordinate differences between the i+1th observation station and the i-th observation station at the time of the first observation; The change in aeolian sand thickness Δh is obtained by measuring the distance between the ground surface and the polyester mesh with a millimeter steel ruler and subtracting the initial cover soil thickness. 沙 , select 4 to 8 undulating places in each permeable sand-isolating polyester mesh to measure the height, and take the average value of the results as the change value of the aeolian sand thickness at the i-th observation station Taking into account the influence of seasonal wind speed and precipitation, continuous observation is carried out for one year or more.

4. The method for predicting surface subsidence in coal mining taking into account the flow of aeolian sand according to claim 3, characterized in that: The ground movement deformation value W at different locations under different mining conditions is obtained. 测 , I 测 , K 测 、U 测 , ε 测 and the change in aeolian sand thickness Δh 沙 By obtaining the correlation analysis and linear regression between the two, a method for predicting the flow of aeolian sand at any position in the entire basin with respect to the surface movement deformation value is obtained; The regression formula of aeolian sand flow under the influence of mining is as follows: Δh 沙 =v1W 测 +v2I 测 +v3K 测 +v4U 测 +v5ε 测 +b Where W 测 is the surface subsidence value, I 测 is the surface tilt value, K 测 is the surface curvature deformation value, U 测 is the horizontal movement value of the surface, ε 测 is the horizontal deformation value of the surface; v1, v2, v3, v4, and v5 are correlation coefficients, which are obtained by inversion of existing measurement results; and b is a constant term.

5. The method for predicting surface subsidence in coal mining taking into account the flow of aeolian sand according to claim 4, characterized in that: Combined with the mining plan of the mining area, the mining engineering plan and the drilling histogram data, the relevant information of the planned mining working face is collected and sorted, including the working face width a, face length b', mining depth H, mining thickness m, coal seam inclination α, and the prediction parameter information, including the surface subsidence coefficient q, the main influence angle tangent tanβ, the inflection point offset S, and the mining influence propagation angle θ. The probability integral method is used to predict the surface movement and deformation of the working face mining, and the surface subsidence value prediction value W at different locations is obtained. 预 , surface tilt value prediction value I 预 , surface curvature deformation prediction value K 预 , predicted value of surface horizontal movement U 预 , predicted value of surface horizontal deformation ε 预 ; The prediction formula of the probability integral method is: 5.

1. Subsidence value W(x,y) of any point A(x,y) W(x,y)=W cm C′ x C′ y in: Where: W cm Indicates the maximum surface subsidence under full mining conditions, W cm =mq cosα; m represents the thickness of the mined coal seam; q represents the surface subsidence coefficient; α represents the inclination angle of the coal seam; C' x , C' y It is expressed as the subsidence distribution coefficient of the point to be determined at the projection point on the strike and dip main sections; L is the calculated mining distance on the surface in the strike or dip direction after the inflection point of the mining area is translated; r is the main impact radius; 5.

2. Any point A(x,y) on the surface Direction tilt deformation value for: Where: T(x,y) max Indicates the maximum tilt value of the point to be found, Indicates the angle between the maximum tilt value and the OX axis, that is, the angle of rotation in the counterclockwise direction, T x , T y represents the tilt deformation value of the target point after superposition at the projection point along the strike and dip main sections, 5.

3. Any point A(x, y) on the surface Directional curvature deformation for: Where: K(x,y) max , K(x,y) min Represents the maximum and minimum curvature deformation values of the point to be determined; K x , K y It represents the curvature value of the target point along the strike and dip after superposition at the projection of the main section; 5.

4. Any point A(x,y) on the surface Horizontal movement value in the direction for: Where: Expressed as the angle between the maximum horizontal movement direction and the OX axis, U x 、U y They are respectively expressed as the horizontal movement values of the point to be determined along the strike and dip at the projection point of the main section, 5.

5. Any point A(x,y) on the surface Horizontal deformation value of the direction for: Where: ε(x,y) max ,ε(x,y) min Expressed as the maximum and minimum horizontal deformation values of the point to be determined; ε x , ε y It represents the horizontal deformation value superimposed along the strike and dip of the point to be determined at the projection of the main section.

6. The method for predicting surface subsidence in coal mining taking into account the flow of aeolian sand according to claim 5, characterized in that: Based on the probability integral prediction value of surface movement and deformation, combined with the established formula for the change of aeolian sand thickness, the impact of aeolian sand flow on surface subsidence can be deduced: W 沙 =v1W 预 +v2I 预 +v3K 预 +v4U 预 +v5ε 预 +b The actual surface subsidence value W of coal mining can be calculated after removing the influence of aeolian sand flow. 实 : IN 实 =In 预 -IN 沙 。

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