A coal wall spalling grading early warning method based on coal wall energy index

Abstract

The application discloses a coal wall spalling grading early warning method based on a coal wall energy index, relates to the technical field of coal wall spalling early warning, and comprises the following steps: arranging a borehole stress meter on the surface of a coal wall to be measured, recording borehole stress change data, analyzing and processing the borehole stress change data, and obtaining a stress distribution state; arranging a displacement monitoring system in front of the coal wall to be measured, collecting coal wall displacement data, analyzing and processing the coal wall displacement data, and obtaining a coal wall displacement state; based on the stress distribution state and the coal wall displacement state, a current coal wall energy distribution characteristic is constructed; meanwhile, the energy distribution characteristic of a coal wall damage critical point is obtained according to actual sample parameters of the coal wall; and the current coal wall energy distribution characteristic is compared with the energy distribution characteristic of the coal wall damage critical point, so that the comparison result is taken as a spalling grading early warning result.

Description

Technical Field

[0001] This invention relates to the field of coal wall spalling early warning technology, and specifically to a graded early warning method for coal wall spalling based on coal wall energy indicators. Background Technology

[0002] With the widespread application of mechanized coal mining and the upgrading of coal mining equipment, the advance speed of coal faces has accelerated, and the production capacity of coal mines has continuously increased. Although the increase in production capacity brings greater economic benefits, the accelerated advance speed of the working face also increases the probability of coal face spalling, threatening the safe production of the mine. Therefore, predicting coal face spalling in mines is of great significance. Currently, methods for predicting coal face spalling include single-factor monitoring and forecasting, mechanical model analysis, fault tree analysis, grey GM model prediction, and fuzzy evaluation methods. Single-factor monitoring and forecasting methods are highly susceptible to the influence of monitoring equipment parameters, lack verification from other factors, and have poor accuracy. Fault tree analysis is difficult to predict overall changes after a change in one factor. Grey GM model prediction has weak ability to handle random changes in variables and cannot express the relationships between different variables. Fuzzy evaluation methods are difficult to process data accurately, and the prediction results are prone to deviation. Summary of the Invention

[0003] To overcome the above-mentioned shortcomings, this invention provides a method for classifying and warning of coal face spalling based on coal face energy indicators. This invention combines the two factors of coal face stress and coal face strain to obtain the current energy distribution characteristics of the coal face and the energy distribution characteristics of the critical point of coal face failure. By comparing the current energy distribution characteristics of the coal face with the energy distribution characteristics of the critical point of coal face failure, the classification and warning standards are quantified, thereby enabling the prediction of coal face spalling. Compared with the prior art, this method has a wide range of applications, is more accurate in identification, and can predict coal face spalling under various geological conditions.

[0004] On the one hand, a method for classifying and early warning of coal wall spalling based on coal wall energy index is provided, including the following steps:

[0005] Borehole stress gauges are installed on the surface of the coal wall to be tested to record borehole stress change data. The borehole stress change data are analyzed and processed to obtain the stress distribution state. A displacement monitoring system is set up in front of the coal wall to be tested to collect coal wall displacement data. The coal wall displacement data is analyzed and processed to obtain the coal wall displacement state.

[0006] Based on the stress distribution state and the coal wall displacement state, the current coal wall energy distribution characteristics are constructed; at the same time, the energy distribution characteristics of the coal wall failure critical point are obtained based on the actual sample parameters of the coal wall.

[0007] The energy distribution characteristics of the current coal face are compared with the energy distribution characteristics of the critical point of coal face failure, and the comparison results are used as the results of the graded early warning of coal face collapse.

[0008] Preferably, the installation of borehole stress gauges specifically includes the following steps:

[0009] Several measuring lines perpendicular to the roof are marked on the surface of the coal wall to be tested, and the measuring lines are arranged at equal intervals.

[0010] A plurality of boreholes are laid out on the measuring line, wherein the opening direction of any one of the boreholes is perpendicular to the surface of the coal seam, and the plurality of boreholes on any one of the measuring lines are laid out at equal intervals.

[0011] A stress gauge is installed in any one of the boreholes, and the stress gauges are installed at the same depth.

[0012] Preferably, the analysis and processing of borehole stress variation data specifically includes the following steps:

[0013] Acquire stress gauge data, grid the coal wall to be tested to obtain the measurement grid, and use each stress gauge position as a sampling point;

[0014] The measurement grid is divided into several square grids with a side length of 0.5m, and the grid vertices are used as points to be estimated;

[0015] Based on the search strategy, suitable sampling points are selected in the measurement grid, and the stress value of the point to be estimated is calculated using the Kriging interpolation method.

[0016] Preferably, a displacement monitoring system is installed in front of the coal face to be tested. When collecting coal face displacement data, the specific steps include:

[0017] A monitoring camera is installed to monitor the coal wall to be tested. The monitoring camera is installed perpendicular to the coal wall to be tested, and the shooting range of the monitoring camera covers the coal wall to be tested.

[0018] First, a layer of black pigment is sprayed onto the coal wall to be tested, and then white pigment is sprayed onto the surface of the black pigment to create scattered spots.

[0019] Adjust the monitoring camera parameters to achieve the best imaging effect on the coal wall under test.

[0020] Preferably, when analyzing and processing the coal wall displacement data to obtain the coal wall displacement state, the following steps are also included:

[0021] The displacement data of the coal wall to be measured is obtained by using image data collected by monitoring cameras and a displacement monitoring system based on digital image correlation.

[0022] After filtering the displacement data, the displacement state of the coal wall to be tested is calculated using the Kriging interpolation method.

[0023] Preferably, the construction of the current coal wall energy distribution characteristics specifically includes the following steps:

[0024] The total energy at each estimated point of the coal wall to be tested is calculated, and the total energy data at each estimated point is analyzed and processed by the Kriging interpolation method to obtain the energy distribution state of the coal wall to be tested.

[0025] The energy distribution state is visualized to obtain the energy distribution characteristics of the coal wall to be tested.

[0026] Preferably, the following formula is used to calculate the total energy at each point to be estimated on the coal face:

[0027]

[0028] Where U is the total energy at the point to be estimated in the coal wall to be tested, is the stress value at the i-th point to be estimated at time t, and is the strain value at the i-th point to be estimated at time t.

[0029] Preferably, when obtaining the energy distribution characteristics of the coal wall failure critical point based on actual sample parameters of the coal wall, the specific steps include:

[0030] Coal samples were obtained from the upper, middle and lower parts of the coal wall to be tested and processed into standard specimens. The physical parameters of the standard specimens were determined, including the specimen elastic modulus, total energy, elastic deformation energy and dissipated energy of the specimen.

[0031] A digital working face model is established based on the physical parameters of standard specimens. The excavation method is simulated on the digital working face model based on the actual excavation process to obtain the excavation simulation results. Based on the excavation simulation results, the energy distribution characteristics of the critical point of coal wall failure are obtained.

[0032] In a second aspect, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the coal wall spalling classification and early warning method based on coal wall energy index.

[0033] Thirdly, a non-transitory computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the coal wall spalling classification and early warning method based on coal wall energy index.

[0034] The beneficial effects of this invention are reflected in:

[0035] This invention combines the two factors of coal face stress and coal face strain to derive the current energy distribution characteristics of the coal face and the energy distribution characteristics of the critical point of coal face failure. By comparing the current energy distribution characteristics of the coal face with the energy distribution characteristics of the critical point of coal face failure, a quantitative and graded early warning standard is established to predict coal face spalling. Compared with existing technologies, this invention has a wider range of applications, higher accuracy, and can predict coal face spalling under various geological conditions. Attached Figure Description

[0036] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0037] Figure 1 A flowchart of a coal wall spalling classification and early warning method based on coal wall energy index provided by the present invention;

[0038] Figure 2 A schematic diagram of the borehole location arrangement for a coal wall spalling classification and early warning method based on coal wall energy index provided by the present invention;

[0039] Figure 3 A schematic diagram of the arrangement of monitoring cameras for a coal wall spalling classification and early warning method based on coal wall energy index provided by the present invention;

[0040] Legend: 1-Coal body, 2-Coal wall to be measured, 3-Borehole, 4-Measurement line, 5-Overburden, 6-Hydraulic support, 7-Monitoring camera. Detailed Implementation

[0041] The embodiments of the technical solution of the present invention will now be described in detail with reference to the accompanying drawings. These embodiments are merely illustrative of the technical solution of the present invention and are therefore intended to limit the scope of protection of the present invention.

[0042] It should be noted that, unless otherwise stated, the technical or scientific terms used in this application should have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0043] In Example 1, as Figure 1 As shown, a method for classifying and early warning of coal wall spalling based on coal wall energy index includes the following steps:

[0044] Borehole stress gauges are installed on the surface of the coal wall 2 to be tested to record the borehole stress change data. The borehole stress change data are analyzed and processed to obtain the stress distribution state. A displacement monitoring system is set up in front of the coal wall 2 to collect the coal wall displacement data. The coal wall displacement data is analyzed and processed to obtain the coal wall displacement state.

[0045] Based on the stress distribution state and the coal wall displacement state, the current coal wall energy distribution characteristics are constructed; at the same time, the energy distribution characteristics of the coal wall failure critical point are obtained based on the actual sample parameters of the coal wall.

[0046] The energy distribution characteristics of the current coal face are compared with the energy distribution characteristics of the critical point of coal face failure, and the comparison results are used as the results of the graded early warning of coal face collapse.

[0047] To achieve graded early warning of coal face spalling disasters, the key is to determine the current energy distribution state of the coal face and the energy distribution state at the time of coal face failure. To determine the current energy distribution state, it is necessary to first obtain the displacement characteristics and stress distribution characteristics of each part of the coal face. To obtain energy-based critical parameters for coal face failure, laboratory experiments and numerical simulation experiments are required. In this embodiment, by combining the two factors of coal face stress and strain, the current energy distribution characteristics of the coal face and the energy distribution characteristics of the critical point of coal face failure are obtained. By comparing the current energy distribution characteristics with the energy distribution characteristics of the critical point of coal face failure, the graded early warning standards are quantified, enabling the prediction of coal face spalling. Compared with existing technologies, this method has a wider range of applications, higher accuracy, and can predict coal face spalling under various geological conditions.

[0048] like Figure 2 As shown, more specifically, the installation of borehole stress gauges includes the following steps:

[0049] A number of measuring lines 4 perpendicular to the top plate are divided on the surface of the coal wall 2 to be tested, and the number of measuring lines 4 are arranged at equal intervals.

[0050] A plurality of boreholes 3 are arranged on the measuring line 4, wherein the opening direction of any one of the boreholes 3 is perpendicular to the surface of the coal seam, and the plurality of boreholes 3 on any measuring line 4 are arranged at equal intervals.

[0051] A stress gauge is installed in any one of the boreholes 3, and the stress gauges are installed at the same depth.

[0052] Here, measuring line 4 is arranged vertically to the roof on the side of the coal wall in the roadway of coal body 1, with a spacing of 2m between adjacent measuring lines 4; the spacing of boreholes 3 on the same measuring line 4 is 1m, and the depth of borehole 3 is 0.5 times the length of the working face cut; the spacing of stress gauges in boreholes on the same measuring line 4 is 1m, and the stress gauges in different boreholes 3 are installed at the same depth.

[0053] More specifically, the analysis and processing of borehole stress variation data includes the following steps:

[0054] Acquire stress gauge data, grid the coal wall to be tested 2 to obtain the measurement grid, and use each stress gauge position as a sampling point;

[0055] The measurement grid is divided into several square grids with a side length of 0.5m, and the grid vertices are used as points to be estimated;

[0056] Based on the search strategy, suitable sampling points are selected in the measurement grid, and the stress value of the point to be estimated is calculated using the Kriging interpolation method.

[0057] The search strategy is as follows: Based on the actual situation, a search distance of 0.7m is selected, with a search angle tolerance of 90°. The lower left corner of the coal face is chosen as the search starting point, and all points within the range to be estimated are included in the calculation. After the calculation is completed, other points within the range are used as the starting point for calculation, and this process is repeated until the stress of all points to be estimated is calculated.

[0058] The search range is determined based on the density of the measured grid. Screening can avoid distant points from affecting the calculation results and improve the calculation accuracy.

[0059] If the selected sampling points are C(1,1) to C(3,3), construct the following equations using the sampling points, and find the coefficients λ1, λ2, and λ3 of the equation system:

[0060]

[0061] Using the polygon estimation method, the weight value of the sampling point closest to the point to be estimated is determined according to the following formula:

[0062]

[0063] After obtaining the weight values, calculate the stress value of the point to be estimated using the following formula:

[0064] σ 网 =λ·σ 近

[0065] Where, σ 网 σ is the stress value at the grid vertex, λ is the weight value of the point to be estimated from the nearest sampling point, and σ is the stress value at the grid vertex. 近 The value is the stress value of the point to be estimated from the nearest sampling point.

[0066] like Figure 3 As shown, more specifically, when a displacement monitoring system is installed in front of the coal wall to be measured 2 to collect coal wall displacement data, the specific steps include:

[0067] A monitoring camera 7 is installed to monitor the coal wall 2 under test. The monitoring camera 7 is installed perpendicular to the coal wall 2 under test, and the shooting range of the monitoring camera 7 covers the coal wall 2 under test.

[0068] First, a layer of black pigment is sprayed onto the coal wall 2 to be tested, and then white pigment is sprayed onto the surface of the black pigment to create scattered spots.

[0069] Adjust the parameters of monitoring camera 7 to achieve the best imaging effect on the coal wall 2 under test.

[0070] To ensure the monitoring effect of the camera on the coal wall, a hydraulic support 6 is used to support the overlying rock 5 on top of the coal body 1. The camera is installed on the hydraulic support 6 so that the camera's shooting position is at the upper half of the coal wall 2 to be tested, resulting in better imaging effect of the coal wall 2 to be tested. The parameters that can be adjusted for the monitoring camera 7 here include the camera resolution and aperture parameters.

[0071] More specifically, the analysis and processing of coal wall displacement data to obtain the coal wall displacement state also includes the following steps:

[0072] The image data collected by the monitoring camera 7 is used to obtain the displacement data of the coal wall 2 to be measured by the digital image correlation displacement monitoring system;

[0073] After filtering the displacement data, the displacement state of the coal wall 2 to be tested was calculated using the Kriging interpolation method.

[0074] After obtaining displacement data, it is necessary to compare it with previous displacement monitoring results and filter out unreasonable displacement monitoring values ​​caused by monitoring system errors to make the calculation results more accurate. Unreasonable data are generally values ​​that deviate significantly from previous displacement monitoring results.

[0075] Digital image correlation (DIC) utilizes binocular stereo vision technology to measure the three-dimensional coordinates, displacement, and strain of an object's surface during deformation by tracking speckle images on the surface. It is mainly used for measuring and acquiring information such as strain, deformation, displacement, amplitude, and modality across the entire field. Before and after deformation, the movement of geometric points on the object's surface generates displacement. By using relevant algorithms to determine the corresponding geometric points before and after deformation, the displacement state of the coal wall 2 to be measured can be obtained.

[0076] More specifically, the steps involved in constructing the current coal wall energy distribution characteristics are as follows:

[0077] The total energy at each estimated point of the coal wall 2 to be tested is calculated, and the total energy data at each estimated point is analyzed and processed by the Kriging interpolation method to obtain the energy distribution state of the coal wall 2 to be tested.

[0078] The energy distribution state is visualized to obtain the energy distribution characteristics of the coal wall 2 to be tested.

[0079] More specifically, when calculating the total energy at each estimated point on the coal face 2, the following formula is used:

[0080]

[0081] Where U is the total energy at the estimated point of the coal wall 2 to be tested, is the stress value at the i-th estimated point at time t, and is the strain value at the i-th estimated point at time t.

[0082] More specifically, when obtaining the energy distribution characteristics of the critical point of coal wall failure based on actual sample parameters of the coal wall, the following steps are included:

[0083] Coal samples were obtained from the upper, middle and lower parts of the coal wall 2 to be tested and processed into standard specimens. The physical parameters of the standard specimens were determined, including the specimen elastic modulus, total energy, elastic deformation energy and dissipated energy of the specimens.

[0084] Based on the physical parameters of the standard specimen, a digital working face model was established using FLAC 3D finite difference numerical simulation software. The excavation method was simulated on the digital working face model based on the actual excavation process to obtain the excavation simulation results. Based on the excavation simulation results, the energy distribution characteristics of the critical point of coal wall failure were obtained.

[0085] The elastic modulus of the standard specimen is obtained by the following formula:

[0086]

[0087] In the formula, Δσ 弹 Δε represents the stress change of the specimen during the elastic phase. 弹 This represents the strain change of the specimen during the elastic phase.

[0088] The total energy of the standard specimen is calculated using the following formula:

[0089]

[0090] The elastic deformation energy of the standard specimen is obtained by the following formula:

[0091]

[0092] The dissipation energy of the standard specimen is obtained by the following formula:

[0093] U1 = U - U0

[0094] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the coal wall spalling classification and early warning method based on coal wall energy index.

[0095] A non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the coal wall spalling classification and early warning method based on coal wall energy index.

[0096] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A method for classifying and early warning of coal wall spalling based on coal wall energy index, characterized in that, The steps include the following: Borehole stress gauges are installed on the surface of the coal wall to be tested to record borehole stress change data. The borehole stress change data are analyzed and processed to obtain the stress distribution state. A displacement monitoring system is set up in front of the coal wall to be tested to collect coal wall displacement data. The coal wall displacement data is analyzed and processed to obtain the coal wall displacement state. Based on the stress distribution state and the coal wall displacement state, the current coal wall energy distribution characteristics are constructed; at the same time, the energy distribution characteristics of the coal wall failure critical point are obtained based on the actual sample parameters of the coal wall. The energy distribution characteristics of the current coal face are compared with the energy distribution characteristics of the critical point of coal face failure, and the comparison results are used as the early warning results for coal face flaring. The installation of borehole stress gauges specifically includes the following steps: Several measuring lines perpendicular to the roof are marked on the surface of the coal wall to be tested, and the measuring lines are arranged at equal intervals. A plurality of boreholes are laid out on the measuring line, wherein the drilling direction of any one of the boreholes is perpendicular to the coal seam surface, and the plurality of boreholes on any one of the measuring lines are laid out at equal intervals. A stress gauge is installed in any one of the boreholes, and the stress gauges are installed at the same depth. The analysis and processing of borehole stress variation data specifically includes the following steps: Acquire stress gauge data, grid the coal wall to be tested to obtain the measurement grid, and use each stress gauge position as a sampling point; The measurement grid is divided into several square grids with a side length of 0.5m, and the grid vertices are used as points to be estimated. Based on the search strategy, suitable sampling points are selected in the measurement grid, and the stress value of the point to be estimated is calculated using the Kriging interpolation method. The search strategy is as follows: 0.7m is selected as the search distance according to the actual situation, the search angle tolerance is given as 90°, the grid point at the lower left corner of the coal wall is selected as the search starting point, all points to be estimated within the range are included in the calculation, and after the calculation is completed, other points within the range are used as the calculation starting point, and this process is repeated until the stress of all points to be estimated is calculated. The search range is determined according to the density of the measurement grid. When obtaining the energy distribution characteristics of the critical point of coal wall failure based on actual sample parameters of the coal wall, the specific steps include: Coal samples were obtained from the upper, middle and lower parts of the coal wall to be tested and processed into standard specimens. The physical parameters of the standard specimens were determined, including the specimen elastic modulus, total energy, elastic deformation energy and dissipated energy of the specimen. A digital working face model is established based on the physical parameters of standard specimens. The excavation method is simulated on the digital working face model based on the actual excavation process to obtain the excavation simulation results. Based on the excavation simulation results, the energy distribution characteristics of the critical point of coal wall failure are obtained. The specific steps involved in constructing the current coal wall energy distribution characteristics are as follows: The total energy at each estimated point of the coal wall to be tested is calculated, and the total energy data at each estimated point is analyzed and processed using the Kriging interpolation method to obtain the energy distribution state of the coal wall to be tested. The energy distribution state is visualized to obtain the energy distribution characteristics of the coal wall to be tested. The following formula is used to calculate the total energy at each point to be estimated on the coal face: in, This represents the total energy at the point to be estimated on the coal face to be tested. For the first One point to be estimated is... Stress value at time 10:00 For the first One point to be estimated is... The strain value at any given moment.

2. The method for graded early warning of coal wall spalling based on coal wall energy index according to claim 1, characterized in that, When setting up a displacement monitoring system in front of the coal face to be tested and collecting coal face displacement data, the specific steps include: A monitoring camera is installed to monitor the coal wall to be tested. The monitoring camera is installed perpendicular to the coal wall to be tested, and the shooting range of the monitoring camera covers the coal wall to be tested. First, a layer of black pigment is sprayed onto the coal wall to be tested, and then white pigment is sprayed onto the surface of the black pigment to create scattered spots. Adjust the monitoring camera parameters to achieve the best imaging effect on the coal wall under test.

3. The method for graded early warning of coal wall spalling based on coal wall energy index according to claim 2, characterized in that, The analysis and processing of coal wall displacement data to obtain the coal wall displacement state also includes the following steps: The displacement data of the coal wall to be measured is obtained by using image data collected by monitoring cameras and a displacement monitoring system based on digital image correlation. After filtering the displacement data, the displacement state of the coal wall to be tested is calculated using the Kriging interpolation method.

4. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the coal wall spalling classification and early warning method based on coal wall energy index as described in any one of claims 1 to 3.

5. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the coal wall spalling classification and early warning method based on coal wall energy index as described in any one of claims 1 to 3.

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