Multi-level monitoring and early warning method and device for rock burst based on coal mine tunnel deformation

Abstract

The present disclosure relates to a multi-level monitoring and early warning method and device for rock burst based on coal mine tunnel deformation. The method comprises: obtaining the three-dimensional coordinate data and historical data of the surrounding rock of the coal mine tunnel to be monitored at the current time node, and using the three-dimensional coordinate data to generate a contour model of the surrounding rock of the coal mine tunnel to be monitored at the current time node; using the three-dimensional coordinate data and historical data to determine the degree of imbalance in the time change and the degree of incoordination in the space change of the energy corresponding to each grid in the contour model; using the degree of imbalance and incoordination corresponding to the grid to determine the rock burst hazard coefficient, and outputting early warning information based on the rock burst hazard coefficient; when the rock burst hazard coefficient of the grid does not meet the first preset condition, performing hierarchical grid division processing on the grid, and returning to execute the step of obtaining the three-dimensional coordinate data of the surrounding rock of the coal mine tunnel to be monitored and the calculation step. This solution improves the accuracy and timeliness of rock burst warning.

Description

Technical Field

[0001] The present disclosure relates to the technical field of coal mining, and in particular to a multi-level monitoring and early warning method and device for rock burst based on coal mine tunnel deformation. Background Art

[0002] Rock burst is one of the major hazards facing deep coal mining in my country, yet timely and accurate monitoring and early warning are currently lacking. In mines experiencing rock burst, over 90% of rock bursts occur in mining tunnels. Before a rock burst occurs, the tunnels deform due to changes in stress and energy. Therefore, rock burst monitoring and early warning can be achieved based on this deformation information.

[0003] At present, the traditional method of using tunnel deformation to monitor rock burst is simply to determine whether the deformation degree of the tunnel exceeds the preset value to determine the danger of rock burst. However, due to the irregular changes in stress and energy, the deformation degree of the tunnel also has the characteristics of irregular changes, resulting in this single assessment method. It is difficult to accurately and timely monitor and warn of rock burst. Summary of the Invention

[0004] In order to overcome the problems existing in the related art, the present disclosure provides a multi-level monitoring and early warning method and device for rock burst based on coal mine tunnel deformation.

[0005] According to a first aspect of an embodiment of the present disclosure, a multi-level monitoring and early warning method for rock burst based on coal mine roadway deformation is provided, comprising:

[0006] Obtaining three-dimensional coordinate data and historical data of surrounding rock of a coal mine roadway to be monitored at a current time node, and generating a roadway surrounding rock contour model of the surrounding rock of the coal mine roadway to be monitored at the current time node using the three-dimensional coordinate data; the roadway surrounding rock contour model includes a plurality of grids; the size of each of the plurality of grids corresponds to a grid level to which the grid belongs; the grid level is less than or equal to N; N is an integer greater than 1; the historical data includes historical three-dimensional coordinate data and historical contour model of the surrounding rock of the coal mine roadway to be monitored;

[0007] Using the three-dimensional coordinate data and the historical data, determining the degree of unevenness in temporal variation and the degree of incoordination in spatial variation of energy corresponding to each grid in the roadway surrounding rock contour model; the energy is the energy accumulated by the grid in the corresponding area of ​​the surrounding rock of the coal mine roadway to be monitored due to stress deformation;

[0008] For each grid, using the degree of imbalance and the degree of incoordination corresponding to the grid, determine the rock burst risk coefficient of the grid, and output warning information based on the rock burst risk coefficient;

[0009] Storing the three-dimensional coordinate data and the roadway surrounding rock contour model in the historical data;

[0010] If a grid whose rock burst hazard coefficient does not meet the first preset condition exists among the multiple grids, hierarchical grid division processing is performed on the grid to obtain a plurality of K-level grids, and the step of obtaining the three-dimensional coordinate data of the surrounding rock of the coal mine roadway to be monitored is performed again; K is an integer less than or equal to N+1;

[0011] When the rock burst hazard coefficients of the plurality of grids all satisfy the first preset condition, the process returns to the step of obtaining the three-dimensional coordinate data of the surrounding rock of the coal mine roadway to be monitored.

[0012] According to a second aspect of an embodiment of the present disclosure, a multi-level monitoring and early warning device for rock burst based on coal mine tunnel deformation is provided, comprising:

[0013] A generating unit is configured to obtain three-dimensional coordinate data and historical data of surrounding rock of a coal mine roadway to be monitored at a current time node, and generate a roadway surrounding rock contour model of the surrounding rock of the coal mine roadway to be monitored at the current time node using the three-dimensional coordinate data; the roadway surrounding rock contour model includes a plurality of grids; the size of each of the plurality of grids corresponds to a grid level to which the grid belongs; the grid level is less than or equal to N; N is an integer greater than 1; the historical data includes historical three-dimensional coordinate data and historical contour model of the surrounding rock of the coal mine roadway to be monitored;

[0014] a determination unit, configured to determine, using the three-dimensional coordinate data and the historical data, a degree of imbalance in temporal variation and a degree of incoordination in spatial variation of energy corresponding to each grid in the roadway surrounding rock contour model; the energy being energy accumulated by the grid in a corresponding area of ​​the surrounding rock of the coal mine roadway to be monitored due to deformation caused by stress;

[0015] An early warning unit is configured to determine, for each grid, a rock burst risk coefficient of the grid using the degree of imbalance and the degree of incoordination corresponding to the grid, and output early warning information based on the rock burst risk coefficient;

[0016] A storage unit, configured to store the three-dimensional coordinate data and the roadway surrounding rock contour model in the historical data;

[0017] a division unit configured to, if a grid having a rock burst hazard coefficient that does not satisfy a first preset condition exists among the plurality of grids, perform hierarchical grid division processing on the grids to obtain a plurality of K-level grids, and return to execute the step of obtaining the three-dimensional coordinate data of the surrounding rock of the coal mine roadway to be monitored; K is an integer less than or equal to N+1;

[0018] The execution unit is used to return to the step of obtaining the three-dimensional coordinate data of the surrounding rock of the coal mine tunnel to be monitored when the rock burst hazard coefficients of the multiple grids all meet the first preset condition.

[0019] According to a third aspect of an embodiment of the present disclosure, an electronic device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method described in any one of the first aspects is implemented.

[0020] According to a fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method according to any one of the first aspects is implemented.

[0021] According to a fifth aspect of an embodiment of the present disclosure, a computer program product is provided, comprising a computer program, wherein the computer program implements the method as described in any one of the first aspects when executed by a processor.

[0022] The technical solution provided by the embodiments of the present disclosure may include the following beneficial effects: obtaining the three-dimensional coordinate data and historical data of the surrounding rock of the coal mine roadway to be monitored at the current time node, and using the three-dimensional coordinate data to generate the roadway surrounding rock contour model of the surrounding rock of the coal mine roadway to be monitored at the current time node; using the three-dimensional coordinate data and historical data to determine the degree of imbalance in time change and the degree of incoordination in space change of energy corresponding to each grid in the roadway surrounding rock contour model; for each grid, using the degree of imbalance and incoordination corresponding to the grid, determining the rock burst hazard coefficient of the grid, and outputting warning information based on the rock burst hazard coefficient; using the three-dimensional coordinate data to generate the rock burst hazard model of the surrounding rock of the coal mine roadway to be monitored at the current time node; using the three-dimensional coordinate data and historical data to determine the degree of imbalance in time change and the degree of incoordination in space change of energy corresponding to each grid in the rock burst contour model; using the degree of imbalance and incoordination corresponding to the grid to determine the rock burst hazard coefficient of the grid, and outputting warning information based on the rock burst hazard coefficient; using the three-dimensional coordinate data to generate the rock burst hazard coefficient of the coal mine roadway to be monitored at the current time node ... and the tunnel surrounding rock contour model are stored in the historical data; in the case where there are grids in multiple grids whose rock burst hazard coefficient does not meet the first preset condition, the grids are hierarchically divided into multiple K-level grids, and the steps of obtaining the three-dimensional coordinate data of the surrounding rock of the coal mine tunnel to be monitored and the corresponding analysis and early warning work are returned to execute, so that the degree of imbalance in the energy change in time and the degree of incoordination in space can be continuously judged according to the deformation of the surrounding rock of the coal mine tunnel to be monitored, so as to comprehensively judge the location and degree of rock burst hazard in the tunnel surrounding rock, thereby improving the accuracy and timeliness of rock burst early warning. In addition, the use of a multi-level grid division method to evaluate the rock burst hazard degree at different locations in the tunnel surrounding rock can effectively reduce the amount of calculation, improve the calculation efficiency, and thus improve the timeliness of the early warning.

[0023] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0025] Figure 1 The present invention is a flowchart showing a multi-level monitoring and early warning method for rock burst based on coal mine tunnel deformation according to an exemplary embodiment.

[0026] Figure 2 This is a cross-sectional profile diagram before processing proposed according to an embodiment of the present disclosure.

[0027] Figure 3 It is a processed cross-sectional profile diagram proposed according to an embodiment of the present disclosure.

[0028] Figure 4 It is a schematic diagram of a benchmark morphology of tunnel surrounding rock proposed according to an embodiment of the present disclosure.

[0029] Figure 5 It is a schematic diagram of calculating the first level of surrounding rock deformation according to an embodiment of the present disclosure.

[0030] Figure 6 It is a schematic diagram of calculating the second-level surrounding rock deformation according to an embodiment of the present disclosure.

[0031] Figure 7 It is a schematic diagram of calculating the surrounding rock convergence area proposed according to an embodiment of the present disclosure.

[0032] Figure 8 Schematic diagram of grid division and anchor points proposed according to an embodiment of the present disclosure.

[0033] Figure 9 This is a schematic diagram of a multi-level grid division proposed according to an embodiment of the present disclosure.

[0034] Figure 10 This is a schematic diagram of hierarchical regional affiliation proposed according to an embodiment of the present disclosure.

[0035] Figure 11 It is a schematic diagram of the hierarchical division process proposed according to an embodiment of the present disclosure.

[0036] Figure 12 The present invention is a block diagram showing a multi-level monitoring and early warning device for rock burst based on coal mine tunnel deformation according to an exemplary embodiment.

[0037] Figure 13 The present invention is a block diagram of an apparatus for a multi-level monitoring and early warning method of rock burst based on coal mine tunnel deformation according to an exemplary embodiment.

[0038] Reference numerals

[0039] 1-Main side; 2-Secondary side; 3-Top plate; 4-Bottom plate; 5-Measured tunnel section; 6-Initial tunnel section; 7-Anchor point A; 8-Anchor point B; 9-Anchor point C; 10-Anchor point D; 11-Grid; 12-Anchor point. DETAILED DESCRIPTION

[0040] Exemplary embodiments will be described in detail herein, examples of which are illustrated in the accompanying drawings. In the following description, when referring to the drawings, like numbers in different figures represent like or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present invention, as detailed in the appended claims.

[0041] The terms used in the present disclosure are only for the purpose of describing specific embodiments and are not intended to limit the present disclosure. The singular forms "a", "an" and "the" used in the present disclosure and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0042] It should be understood that although the terms first, second, third, etc. may be used to describe various information in the embodiments of the present disclosure, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of the embodiments of the present disclosure, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0043] Furthermore, the various forms of processes shown in the embodiments of this disclosure may be used to reorder, add, or delete steps. For example, the steps described in this application may be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved. This is not a limitation herein.

[0044] Rock burst is one of the major hazards facing deep coal mining in my country, yet timely and accurate monitoring and early warning are currently lacking. In mines experiencing rock burst, over 90% of rock bursts occur in mining tunnels. Before a rock burst occurs, the tunnels deform due to changes in stress and energy. Therefore, rock burst monitoring and early warning can be achieved based on this deformation information.

[0045] The most commonly used method for measuring roadway surrounding rock deformation is the "cross" measuring point method. Workers typically use a tape measure to measure the movement of the roadway's sides, roof, and floor at specially designated measuring stations. Data collection is typically conducted once or twice a week, with measuring stations spaced 100 to 300 meters apart. While this method offers advantages such as ease of operation and convenience, it also suffers from large manual measurement errors, low reliability, poor data continuity, small data volumes, and low measurement accuracy. Furthermore, the station locations are set based on empirical data, which can be somewhat unreliable and easily misses roadway surrounding rock deformation data in areas at risk of impact. With advances in measuring instruments, laser scanning technology has gradually replaced manual measurement for roadway surrounding rock deformation monitoring. This method offers advantages such as high monitoring accuracy, a wide monitoring range, high intelligence, low cost, and significantly improved data reliability and continuity. However, its disadvantages include large data volumes, time-consuming computations, and low computational efficiency. Furthermore, in many cases, manual data entry is still required from acquisition to storage, potentially subject to data entry errors, duplications, omissions, and lags. Furthermore, these monitoring methods only capture relative deformation measurements of the roadway surrounding rock, failing to capture absolute deformation measurements.

[0046] In addition, the traditional method of using tunnel deformation to monitor rock burst is simply to determine whether the deformation degree of the tunnel exceeds the preset value to determine the danger of rock burst. However, due to the irregular changes in stress and energy, the deformation degree of the tunnel also has the characteristics of irregular changes, resulting in this single assessment method. It is difficult to accurately and timely monitor and warn of rock burst.

[0047] In order to solve the above problems, the present invention provides a multi-level monitoring and early warning method and device for rock burst based on coal mine roadway deformation, which obtains the three-dimensional coordinate data and historical data of the surrounding rock of the coal mine roadway to be monitored at the current time node, and uses the three-dimensional coordinate data to generate a roadway surrounding rock contour model of the surrounding rock of the coal mine roadway to be monitored at the current time node; uses the three-dimensional coordinate data and historical data to determine the uneven degree of energy change in time and the incoordination degree of energy change in space corresponding to each grid in the roadway surrounding rock contour model; for each grid, uses the uneven degree and incoordination degree corresponding to the grid to determine the rock burst hazard coefficient of the grid, and outputs the rock burst hazard coefficient based on the rock burst hazard coefficient. Early warning information; storing the three-dimensional coordinate data and the tunnel surrounding rock contour model in the historical data; in the case where there are grids in multiple grids whose rock burst hazard coefficient does not meet the first preset condition, hierarchical grid division is performed on the grid to obtain multiple K-level grids, and the steps of obtaining the three-dimensional coordinate data of the surrounding rock of the coal mine tunnel to be monitored and the corresponding analysis and early warning work are returned to execute, so that the degree of imbalance in the energy change in time and the degree of incoordination in space can be continuously judged according to the deformation of the surrounding rock of the coal mine tunnel to be monitored, so as to comprehensively judge the location and degree of rock burst hazard in the tunnel surrounding rock, thereby improving the accuracy and timeliness of rock burst warning. In addition, the use of a multi-level grid division method to evaluate the rock burst hazard degree at different locations in the tunnel surrounding rock can effectively reduce the amount of calculation, improve the calculation efficiency, and thus improve the timeliness of the warning.

[0048] Figure 1 FIG. 1 is a flow chart showing a multi-level monitoring and early warning method for rock burst based on coal mine tunnel deformation according to an exemplary embodiment. Figure 1 As shown, it should be noted that the multi-level monitoring and early warning method for rock burst based on coal mine roadway deformation of the embodiment of the present disclosure is applied to the multi-level monitoring and early warning device for rock burst based on coal mine roadway deformation. Figure 1 As shown, the method may include the following steps:

[0049] Step 101: obtain the three-dimensional coordinate data and historical data of the surrounding rock of the coal mine roadway to be monitored at the current time node, and generate a roadway surrounding rock contour model of the surrounding rock of the coal mine roadway to be monitored at the current time node using the three-dimensional coordinate data.

[0050] Among them, the tunnel surrounding rock contour model includes multiple grids; the size of each of the multiple grids corresponds to the grid level to which the grid belongs; the grid level is less than or equal to N; N is an integer greater than 1; the historical data includes the historical three-dimensional coordinate data and historical contour model of the coal mine tunnel surrounding rock to be monitored.

[0051] In one embodiment, a guide rail can be set along the direction of the tunnel to be monitored (or manual handheld monitoring can be used), and a three-dimensional laser scanner can be used to scan and collect monitoring data in real time and upload it (including the three-dimensional coordinate data of the surrounding rock of the coal mine tunnel to be monitored). The data content can also specifically include: real-time monitoring time, monitoring location, scanning frequency, scanning accuracy, and scanning range.

[0052] As a possible example, a cross-section profile of a tunnel can be established based on the above monitoring data. First, based on the three-dimensional coordinate data of the original points, every two adjacent points can be connected into a line segment. The line segments are continuously connected to obtain a cross-section profile of the tunnel, such as Figure 2 Then, considering the local data loss caused by the obstruction of pipelines and cables in the tunnel, Bezier curve interpolation calculation is used to eliminate local sharp shapes (such as significant protrusions and recesses), perform difference calculation, and perform smooth correction processing on the tunnel contour curve to obtain the following: Figure 3 The processed cross-sectional contour diagram is shown; finally, the cross-sectional contour diagrams of multiple consecutive positions are combined to form the above-mentioned tunnel surrounding rock contour model. Pipelines and cables can be added to the tunnel surrounding rock contour model to increase the visual effect.

[0053] Step 102 : using the three-dimensional coordinate data and the historical data, determining the uneven degree of energy change in time and the uncoordinated degree of energy change in space corresponding to each grid in the tunnel surrounding rock contour model.

[0054] The energy is the energy accumulated in the grid in the corresponding area of ​​the surrounding rock of the coal mine roadway to be monitored due to deformation caused by stress.

[0055] It should be noted that when a sudden release of energy at a certain location in the surrounding rock of a monitored coal mine roadway causes rock burst, it can cause instantaneous roof subsidence, floor heaving, and side heaving. The speed at which deformation changes in time and space can reflect the speed of energy change. Therefore, the temporal imbalance and spatial incoordination of roadway surrounding rock deformation can reflect the development state of rock burst. By monitoring the spatiotemporal deformation characteristics of the roadway, rock burst can be effectively monitored and warned.

[0056] In one embodiment, the historical data may include the benchmark morphological data of the tunnel surrounding rock. The benchmark morphology of the tunnel surrounding rock refers to the position coordinates and dimensions of the original tunnel surrounding rock engineering structure before the tunnel is excavated and formed and before it is affected by mining stress and before deformation occurs. Determination of the benchmark morphology of the tunnel surrounding rock is the primary task in carrying out calculation and analysis of the deformation and displacement of the tunnel surrounding rock. The simplest and most effective way to determine the benchmark morphology of the tunnel surrounding rock is to conduct a three-dimensional laser scanning patrol immediately after the tunnel is excavated and formed to obtain the benchmark morphology of the tunnel surrounding rock. However, due to the tight arrangement of construction procedures on site, the acquisition and preservation of basic data are often neglected. The key target of monitoring and early warning is the absolute amount of deformation and displacement of the tunnel surrounding rock, not the relative amount. Therefore, if Figure 4 As shown, the following method can be used to confirm the benchmark shape of the tunnel surrounding rock: the default initial tunnel section 6 is a rectangle, which is formed by connecting the outermost points of the four sides of the measured tunnel section 5.

[0057] For example, at time T0, the position coordinates P of anchor point 1, anchor point 2, and anchor point 3 are obtained by scanning. 00 (x 00 、y 00 、z 00 ), P 10 (x 10 、y 10 、z 10 ), P 20 (x 20 、y 20 、z 20 ), according to the positions of anchor point 1, anchor point 2, and anchor point 3, adjacent points are connected and interpolated using Bezier curves to obtain the real-time three-dimensional space coordinate set S0 of the tunnel. S0 is a coordinate data set composed of the position coordinates (x, y, z) of all monitoring points in the main side, auxiliary side, bottom plate, and top plate of the tunnel three-dimensional space; at time T1, the above work is repeated to obtain the position coordinates P01 (x 01 、y 01 、z 01 ), P 11 (x 11 、y 11 、z 11 ), P 21 (x 21 、y 21 、z 21 ), at time T1, repeat the above steps to obtain the three-dimensional space coordinate set S1 of the tunnel.

[0058] In the disclosed embodiment, the degree of surface displacement of the tunnel surrounding rock can be represented by two indicators: the surface displacement amount of the surrounding rock and the surrounding rock convergence area.

[0059] In one example, the displacement of the surrounding rock surface can be determined as follows:

[0060] like Figure 5 The first-level surrounding rock deformation calculation diagram is shown. It is assumed that the surface displacement of the tunnel surrounding rock is perpendicular to the initial tunnel section 6. When the tunnel surrounding rock contour model is meshed at the first level, the deformation at the center point of the grid, that is, the anchor point (anchor point A7, anchor point B8, anchor point C9, anchor point D10) is the length of the vertical intersection line between the point and the measured tunnel section 5. The anchor points of the tunnel main wall 1, auxiliary wall 2, top plate 3, and bottom plate 4 are shown in the figure (the tunnel main wall 1, auxiliary wall 2, top plate 3, and bottom plate 4 are all a grid (grid 1, grid 2, grid 3, grid 4) as a whole, that is, the first level). After measurement and calculation, the displacements of anchor point A7, anchor point B8, anchor point C9, and anchor point D10 are 327mm, 337mm, 173mm, and 88mm respectively; as shown in the figure below: Figure 6 The figure shows the second-level grid division to obtain grid 5 to grid 12 and their corresponding anchor points.

[0061] In another example, Figure 7 As shown, the surrounding rock convergence area can be determined by the following methods:

[0062] The blank area between the initial tunnel section 6 (i.e., the surrounding rock benchmark form) and the measured tunnel section 5 in the same grid is the generalized surrounding rock convergence area. Specifically in the calculation, as shown in the figure, the monitoring level is the first level, and the tunnel main wall, auxiliary wall, top plate, and bottom plate are all a grid as a whole (grid 1, grid 2, grid 3, grid 4). Grid 1, grid 2, grid 3, and grid 4 each have 4 convergence area indicators in their corresponding areas. The convergence areas of grid 1, grid 2, grid 3, and grid 4 are 555312mm respectively after measurement and calculation. 2 、225030mm 2 、957926mm 2 、429385mm 2 .

[0063] As an example of a possible implementation, the surrounding rock convergence area is calculated. From time T0 to time T1, the three-dimensional coordinate data of the surrounding rock of the coal mine roadway to be monitored changes from S0 to S1. The roadway surrounding rock contour model is divided into m grids. The grid area can be calculated based on the coordinates corresponding to the grid area in the coordinate data set. Assuming that the grid is located on the bottom plate (XY direction), the area calculation formula of grid G1 at time T0 is as follows:

[0064]

[0065] Among them, P10 represents the anchor point corresponding to the grid G1 at time T0. During the integral calculation, the coordinate set contained in the P10 grid is extracted from the three-dimensional space coordinate set of the roadway for integral calculation. Since the area projection of the G1 grid is mainly reflected in the xy direction, the projection integral calculation is performed on the xy direction surface.

[0066] Correspondingly, if the G1 grid is located in the secondary side (XZ direction), the area calculation formula of the grid G1 at time T0 is as follows:

[0067]

[0068] The following example calculates the area convergence of grid G1 from time T0 to time T1:

[0069] R11=R1 11 -R1 10 .

[0070] In some embodiments of the present disclosure, step 102 may specifically include the following steps:

[0071] Step a1: for each grid, determine the geometric center point of the grid as the anchor point of the grid.

[0072] In one embodiment, Figure 8 As shown, in order to further reduce the amount of monitoring of massive data, the center position of each grid 11 is used as the anchor point 12, and monitoring is performed based on the anchor point 12, that is, the deformation displacement of the anchor point 12 is represented as the deformation displacement of the grid 11 area.

[0073] Step a2: for each anchor point, using the three-dimensional coordinate data and historical three-dimensional coordinate data of the anchor point, determine the displacement of the anchor point, determine the first imbalance degree of the displacement change in time, and determine the first incoordination degree of the displacement change in space.

[0074] In one embodiment, the displacement of the anchor point can be determined based on the difference between the three-dimensional coordinate data of the anchor point and the historical three-dimensional coordinate data, the first imbalance degree of the displacement change in time can be determined based on the change of the displacement over time, and the first incoordination degree of the displacement change in space can be determined based on the difference between the displacement of the anchor point and the displacement of other anchor points.

[0075] In some embodiments of the present disclosure, the method of determining the displacement of the anchor point and determining the first degree of unevenness of the temporal change of the displacement using the three-dimensional coordinate data and historical three-dimensional coordinate data of the anchor point proposed in step a2 may specifically include the following steps:

[0076] Using the three-dimensional coordinate data and the historical three-dimensional coordinate data, determine the displacement between the first position coordinate and the second position coordinate of the anchor point; the first position coordinate is the position coordinate of the anchor point at the current time node; the second position coordinate is the position coordinate of the grid at the previous adjacent time node;

[0077] The following formula is used to calculate the displacement change equilibrium anomaly coefficient of the anchor point over time:

[0078]

[0079] Among them, TAC ij is the displacement change equilibrium anomaly coefficient of the i-th anchor point at the j-th time node, the j-th time node is the current time node, D ij is the displacement of the i-th anchor point at the j-th time node (the method for determining the displacement can adopt the method proposed in the embodiment of the present disclosure, which will not be described in detail here), is the average displacement of the i-th anchor point at the 0-j time nodes, n = 1, 2, ..., j, LD is the limit value of the displacement of the surrounding rock of the coal mine roadway to be monitored. For areas without obvious dynamic phenomena, LD is taken as 1.2maxD ij For regions with weak dynamics, LD is set to 1.1maxD ij For areas with strong dynamic phenomena, LD takes maxD ij .

[0080] The following formula is used to calculate the anomaly coefficient of the displacement gradient change balance of the anchor point over time:

[0081]

[0082] GTD ij =D ij -D i(j-1)

[0083]

[0084] Among them, TGC ij is the displacement gradient change balance anomaly coefficient of the i-th anchor point at the j-th time node, is the average displacement gradient of the i-th anchor point at the 0-j time nodes, n = 1, 2, 3, ..., j, LGTD is the time displacement gradient limit of the surrounding rock of the coal mine roadway to be monitored, and for areas without obvious dynamic phenomena, 1.2max GTD is taken ij For areas with weak dynamics, LGTD takes 1.1maxGTD ij For areas with strong dynamic phenomena, LGTD takes maxGTD ij .GTD ijis the gradient between the displacement of the i-th anchor point at the j-1th time node and the displacement of the j-th time node;

[0085] A weighted sum is performed on the displacement change balance anomaly coefficient of the anchor point over time and the displacement gradient change balance anomaly coefficient of the anchor point over time to obtain a first imbalance index value for indicating a first imbalance degree of the displacement change over time.

[0086] In one embodiment, the first imbalance index value TC for indicating the first imbalance degree of the displacement amount changing over time is ij It can be calculated using the following formula:

[0087] TC ij =a1×TAC ij +b1×TGC ij

[0088] Among them, TC ij is the first imbalance index value of the displacement of the i-th anchor point at the j-th time node, a1 and b1 are the weight coefficients of the two coefficients, both of which are 0.5, TC is the data set, which represents the degree of imbalance of the displacement deformation of the i-th anchor point at the j-th moment obtained in real time during the monitoring time interval, TC ij The maximum value is 1, and the minimum value may be negative, depending on the measured data. ij A negative value indicates that the energy in the monitoring area is released and the pressure is unloaded; TC ij A positive value indicates that the energy in the monitoring area is concentrated and the pressure is gradually increasing.

[0089] In some embodiments of the present disclosure, determining the first degree of incoordination of the spatial variation of the displacement amount proposed in step a2 may specifically include the following steps:

[0090] The following formula is used to calculate the displacement coordination anomaly coefficient of the anchor point in space:

[0091]

[0092] Among them, SAC ij is the coordinate anomaly coefficient of the displacement change of the i-th anchor point in space at the j-th time node, D ij is the displacement, is the average displacement value of all anchor points in the roadway surrounding rock contour model corresponding to the jth time node, which are at the same level as the i-th anchor point; m is the number of all anchor points in the roadway surrounding rock contour model corresponding to the jth time node, which are at the same level as the i-th anchor point; LD is the displacement limit value corresponding to the surrounding rock of the coal mine roadway to be monitored, and its value is the same as above;

[0093] The following formula is used to calculate the coordination anomaly coefficient of the displacement gradient change of the anchor point in space:

[0094]

[0095] GSD ij =D ij -D (i-1)j

[0096]

[0097] Among them, SGC ij is the coordination anomaly coefficient of the displacement gradient change of the i-th anchor point in space at the j-th time node, is the average displacement gradient of all anchor points in the same layer as the i-th anchor point in the roadway surrounding rock contour model. LGSD is the spatial displacement gradient change limit value corresponding to the surrounding rock of the coal mine roadway to be monitored. For areas without obvious dynamic phenomena, LGSD is taken as 1.2maxGSD. ij For areas with weak dynamics, LGSD is set to 1.1maxGSD ij For areas with strong dynamic phenomena, LGSD takes maxGSD ij , GSD ij is the gradient between the displacement of the i-th anchor point and the displacement of the i-1-th anchor point; the i-1-th anchor point is the anchor point adjacent to the i-th anchor point;

[0098] A weighted sum is performed on the coordination anomaly coefficient of the displacement change of the anchor point in space and the coordination anomaly coefficient of the displacement gradient change of the anchor point in space to obtain a first incoordination index value for representing a first incoordination degree of the displacement change in space.

[0099] In one embodiment, the first incompatibility index value SC for indicating the first incompatibility degree of the spatial variation of the displacement amount is ij It can be calculated using the following formula:

[0100] SC ij =a2×SAC ij +b2×SGC ij

[0101] Among them, SC ij is the first incoherence index value of the displacement of the i-th anchor point at the j-th time node in space. a2 and b2 are the weight coefficients of the two coefficients, both of which are set to 0.5. SC is a data set that represents the degree of spatial incoherence of the displacement deformation of all anchor points obtained in real time at the j-th time node. ij The maximum value is 1, and the minimum value may be negative, depending on the measured data. ijA negative value indicates that the energy in the monitoring area is released and the pressure is unloaded; SC ij A positive value indicates that the energy in the monitoring area is concentrated and the pressure is gradually increasing.

[0102] Step a3, for each grid, using the tunnel surrounding rock contour model of the current time node and the historical contour model of the previous adjacent time node, determine the convergence area of ​​the grid corresponding area, as well as determine the second imbalance degree of the convergence area change in time and determine the second incoordination degree of the convergence area change in space.

[0103] In one embodiment, the tunnel surrounding rock contour model can be used to calculate the convergence area of ​​the grid corresponding area, and the first imbalance degree of the temporal change of the convergence area can be determined based on the change of the convergence area over time. The first incoordination degree of the spatial change of the displacement can be determined based on the difference between the convergence area of ​​the grid corresponding area and the convergence areas of other grids in the same level.

[0104] In some embodiments of the present disclosure, the historical data also includes the historical convergence area corresponding to each grid at each historical time node. The second unevenness degree of the temporal change of the convergence area proposed in step a3 may specifically include the following steps:

[0105] The following formula is used to calculate the anomaly coefficient of the time-varying equilibrium of the grid convergence area:

[0106]

[0107]

[0108] Among them, TRAC ij is the time-varying equilibrium anomaly coefficient of the convergence area corresponding to the i-th grid at the j-th time node, the j-th time node is the current time node, R ij is the convergence area corresponding to the i-th grid at the j-th time node, is the average value of the convergence area of ​​the i-th grid at the 0-j time nodes, n = 1, 2, ..., j, LR is the limit value of the convergence area corresponding to the surrounding rock of the coal mine roadway to be monitored, and for areas without obvious dynamic phenomena, LR is taken as 1.2maxR ij For areas with weak dynamics, LR takes 1.1maxR ij For areas with strong dynamic phenomena, LR takes maxR ij ;

[0109] The following formula is used to calculate the anomaly coefficient of the time-varying equilibrium of the grid convergence area gradient:

[0110]

[0111] GTR ij =R ij -R i(j-1)

[0112]

[0113] Among them, TRGC ij is the time-varying equilibrium anomaly coefficient of the convergence area gradient corresponding to the i-th grid at the j-th time node, is the average value of the convergence area gradient corresponding to the i-th grid at the 0-j time nodes, LGTR is the time-varying limit value of the convergence area gradient corresponding to the surrounding rock of the coal mine roadway to be monitored. For areas without obvious dynamic phenomena, LGTR is taken as 1.2maxGTR ij For areas with weak dynamics, take 1.1maxGTR ij For areas with strong dynamic phenomena, LGTR takes maxGTR ij ;GTR ij is the temporal gradient of the convergence area of ​​the i-th grid between the j-1th time node and the j-th time node;

[0114] A weighted sum is performed on the balance anomaly coefficient of the temporal change of the convergence area of ​​the grid and the balance anomaly coefficient of the temporal change of the convergence area gradient of the grid to obtain a second imbalance index value for representing a second imbalance degree of the temporal change of the convergence area of ​​the grid.

[0115] In one embodiment, the second imbalance index value TRCij used to represent the second imbalance degree of the convergence area of ​​the grid over time can be calculated using the following formula:

[0116] TRC ij =a3×TRAC ij +b3×TRGC ij

[0117] Among them, TRC ij is the second imbalance indicator value of the convergence area change of the i-th grid at the j-th time node. a3 and b3 are the weight coefficients of the two coefficients, both of which are set to 0.5. TRC is a data set that represents the degree of imbalance of the convergence area change of the i-th grid at the j-th time node during the monitoring time interval, obtained in real time.

[0118] TRC ij The maximum value is 1, and the minimum value may be negative, depending on the measured data. ij A negative value indicates that the energy in the monitoring area is released and the pressure is unloaded; TRC ijA positive value indicates that the energy in the monitoring area is concentrated and the pressure is gradually increasing.

[0119] In some embodiments of the present disclosure, the historical data also includes the historical convergence area corresponding to each grid at each historical time node. The second degree of incoordination of the spatial variation of the convergence area proposed in step a3 may specifically include the following steps:

[0120] The following formula is used to calculate the spatial variation coordination anomaly coefficient of the grid's convergence area:

[0121]

[0122] Among them, SRAC ij is the spatial variation coordination anomaly coefficient of the convergence area corresponding to the i-th grid at the j-th time node, R ij is the convergence area, is the average convergence area of ​​all grids at the same level as the i-th grid in the roadway surrounding rock contour model corresponding to the j-th time node, m is the number of all grids at the same level as the i-th grid in the roadway surrounding rock contour model corresponding to the j-th time node, LSR is the convergence area limit value corresponding to the grid area of ​​this level of the coal mine roadway surrounding rock to be monitored, and for areas without obvious dynamic phenomena, 1.2maxR is taken. ij For regions with weak dynamics, take 1.1maxR ij For areas with strong dynamic phenomena, take maxR ij ;

[0123] The following formula is used to calculate the spatial variation coordination anomaly coefficient of the convergence area gradient of the grid:

[0124]

[0125] GSR ij =R ij -R (i-1)j

[0126]

[0127] Among them, SRGC ij is the spatial variation coordination anomaly coefficient of the convergence area gradient corresponding to the i-th anchor point at the j-th time node, is the average value of the convergence area gradient of all grids at the same level as the i-th grid in the roadway surrounding rock contour model. LGSR is the spatial variation limit of the convergence area gradient corresponding to the surrounding rock of the coal mine roadway to be monitored. For areas without obvious dynamic phenomena, 1.2maxGSR is taken. ij For areas with weak dynamics, take 1.1maxGSRij For areas with strong dynamic phenomena, take maxGSR ij ;

[0128] GSR ij is the gradient between the convergence area of ​​the i-th grid and the convergence area of ​​the i-1-th grid; the i-1-th grid is the grid adjacent to the i-th grid;

[0129] A weighted sum is performed on the coordination anomaly coefficient of the spatial variation of the convergence area of ​​the grid and the coordination anomaly coefficient of the spatial variation of the convergence area gradient of the grid to obtain a second incoordination index value for representing a second incoordination degree of the spatial variation of the convergence area of ​​the grid.

[0130] In one embodiment, the second inconsistency index value SRC is used to represent the second inconsistency degree of the convergence area of ​​the grid varying in space. ij It can be calculated using the following formula:

[0131] SRC ij =a4×SRAC ij +b4×SRGC ij

[0132] Among them, SRC ij is the second incoherence index value of the convergence area of ​​the i-th grid at the j-th time node, a4 and b4 are the weight coefficients of the two coefficients, both of which are 0.5. ij For the dataset, it represents the degree of spatial incoordination of the convergence area of ​​all regions obtained in real time at the jth time node. ij The maximum value is 1, and the minimum value may be negative, depending on the measured data. ij A negative value indicates that the energy in the monitoring area is released and the pressure is unloaded; SRC ij A positive value indicates that the energy in the monitoring area is concentrated and the pressure is gradually increasing.

[0133] Step a4: determining the temporal imbalance degree and spatial incoordination degree of energy corresponding to each grid in the tunnel surrounding rock contour model based on the first imbalance degree, the first incoordination degree, the second imbalance degree and the second incoordination degree.

[0134] Step 103 : for each grid, using the degree of imbalance and the degree of incoordination corresponding to the grid, determine the rock burst risk coefficient of the grid, and output warning information based on the rock burst risk coefficient.

[0135] In one embodiment, the rock burst risk coefficient can be calculated based on the imbalance and incoordination levels corresponding to the grids, and corresponding warning information can be output based on the value of the rock burst risk coefficient.

[0136] In some embodiments of the present disclosure, step 103 may specifically include the following steps:

[0137] Step b1, calculating the average of the first imbalance degree, the first incoordination degree, the second imbalance degree, and the second incoordination degree to determine the rock burst risk coefficient;

[0138] In one embodiment, the rock burst risk factor C of a grid can be determined using the following formula: ij :

[0139]

[0140] Among them, when TC ij , SC ij 、TRC ij 、SRC ij When it is a negative value, it is taken as 0 when it is put into the formula. For example, when TC ij , SC ij 、TRC ij 、SRC ij The values ​​are 0.3, 0.4, 0.5, and 0.6 respectively, then C ij =(0.3+0.4+0.5+0.6) / 4=0.45; when TC ij , SC ij 、TRC ij 、SRC ij The values ​​are -2, 0.4, -1, and 0.6 respectively, then C ij =(0+0.4+0+0.6) / 4=0.25. In addition, when C ij ≥C1 (the C1 value is determined based on the on-site historical monitoring data and can generally be taken as 0.5), hierarchical grid division processing is performed; otherwise, hierarchical grid division processing is not performed.

[0141] Step b2: When the size of the grid corresponding to the anchor point is larger than the preset minimum grid division size, determine the level to which the grid belongs, determine the target warning level corresponding to the anchor point according to the first mapping relationship based on the level, and output warning information according to the target warning level.

[0142] The first mapping relationship includes a mapping relationship between a grid level, a plurality of first rock burst risk coefficient intervals and a warning level.

[0143] Step b3: when the size of the grid corresponding to the anchor point is equal to the minimum grid division size, determine the target warning level corresponding to the anchor point according to the second mapping relationship, and output warning information according to the target warning level.

[0144] The first mapping relationship includes mapping relationships between multiple second rock burst risk coefficient intervals and warning levels.

[0145] It should be noted that according to relevant industry regulations, the rock burst hazard warning evaluation results are divided into four categories: no rock burst hazard area, weak rock burst hazard area, medium rock burst hazard area, and strong rock burst hazard area. Combined with the warning index value range of 0 to 1, referring to the corresponding relationship between the index value range and the rock burst hazard in the rock burst comprehensive index method, the warning result judgment standard is determined as shown in Table 1. When the grid length is divided to the minimum, according to C ij The value determines the shock hazard.

[0146] Table 1 includes the warning result judgment standard table of the first mapping relationship

[0147] Serial number <![CDATA[C ij Value]]> Impact hazard 1 0～0.25 No impact hazard 2 0.25～0.5 Weak impact hazard 3 0.5～0.75 Moderate impact hazard 4 0.75～1 High impact hazard

[0148] During actual on-site rock burst hazard monitoring, due to varying geological and mining conditions, even when the grid has not been divided to its minimum level, rock burst hazards may still exist in that area. To address the shortcomings of Table 1, supplementary index early warning assessment results are shown in Table 2. In practice, the results of Table 2 may conflict with those of Table 1. Based on the principle of conservative risk prediction, a higher risk level should be selected for assessment and prevention.

[0149] Table 2 includes the warning result judgment standard table of the second mapping relationship

[0150]

[0151]

[0152] Explanation: For example, when a grid undergoes four consecutive hierarchical meshing processes, the cell length reaches its minimum during the fourth hierarchical meshing process. In this case, the warning criteria in Table 10-1 are met. For example, if the warning coefficient is 0.6, Table 10-1 indicates a moderate impact risk, while Table 2 indicates no impact risk. These two results conflict.

[0153] Table 2. Explanation of the criteria for determining early warning results: The continuous hierarchical grid division processing times of 4, 5, and 6 are examples. Specific values ​​for field applications should be determined based on historical monitoring data analysis and calculation results or other means. For example, based on historical monitoring results, when the continuous hierarchical grid division processing times is 6, a rock burst occurs. At this time, when the continuous hierarchical grid division processing times are 6, the values ​​0-0.25, 0.25-0.5, 0.5-0.75, and 0.75-1 indicate the early warning results, respectively: no rock burst risk, weak rock burst risk, moderate rock burst risk, and strong rock burst risk. Then, the number of continuous hierarchical grid division processing times 6 is decremented by 1, that is, when the number of continuous hierarchical grid division processing times is 5, 0~0.5, 0.5~0.75, and 0.75~1 respectively represent the warning results as: no impact risk, weak impact risk, and moderate impact risk; then, the number of continuous hierarchical grid division processing times 6 is decremented by 2, that is, when the number of continuous hierarchical grid division processing times is 4, 0~0.75 and 0.75~1 respectively represent the warning results as: no impact risk and weak impact risk.

[0154] Step 104: store the three-dimensional coordinate data and the tunnel surrounding rock contour model in the historical data.

[0155] Step 105, when there is a grid among the multiple grids whose rock burst hazard coefficient does not meet the first preset condition, hierarchical grid division processing is performed on the grid to obtain multiple K-level grids, and the process returns to the step of obtaining the three-dimensional coordinate data of the surrounding rock of the coal mine roadway to be monitored.

[0156] Here, K is an integer less than or equal to N+1.

[0157] It can be understood that this round of hierarchical grid division processing belongs to the N+1th round, so the maximum value of the levels of all grids is N+1. Since in this embodiment, only the grids whose impact rock pressure hazard coefficient does not meet the first preset condition are grid divided each time, for a single grid, the level to which it belongs is increased by 1 after each division. Therefore, the levels corresponding to the multiple K-level grids obtained by the hierarchical grid division processing of the grid may be N+1, or may be less than N+1.

[0158] For example, if Figure 9 As shown in the figure, the first level grid is divided into 4 monitoring areas (grid 1, grid 2, grid 3, grid 4, for example, the length and width of the grid are both 2m, and the area of ​​each grid is 4m 2In practice, the tunnel height is about 4m, the width is about 5m, and the tunnel strike length is about 3000. The hierarchical grid division is mainly based on the tunnel strike length, for example, the strike length is divided into 100m, 80m, 50m, 20m, 10m, and 5m in sequence. During real-time monitoring, it was found that the impact risk level of the third grid was aggravated (that is, the impact ground pressure risk coefficient corresponding to the third grid did not meet the first preset condition). Subsequently, the third grid was divided into four areas (grid 5, grid 6, grid 7, grid 8, for example, the grid length was divided into 1m, and the area of ​​each grid was divided into 1m). 2 ). As above, it is further found that the impact risk of grid 7 is aggravated, and then grid 7 is divided into 4 areas (grid 9, grid 10, grid 11, grid 12, for example, the grid length is divided into 0.5m, and each grid area is divided into 0.25m 2 ). Then the 4th level and 5th level division are carried out, and so on. Among them, the affiliation of the hierarchical division areas is as follows Figure 10 shown.

[0159] It should be noted that due to the large amount of tunnel scanning data (more than 3,000 data points for each section, and the daily data volume can reach gigabytes), directly applying massive data for calculation, analysis, monitoring and early warning will lead to a series of problems: First, the response time for data storage, query, extraction, insertion, and update will increase significantly, squeezing computing resources, reducing computing speed, causing obvious delay effects, and limiting early warning effects; second, insufficient data storage space will affect the normal operation of the database and may cause system crashes; third, data backup and recovery are difficult and time-consuming, disk fragmentation is serious, and maintenance costs and hardware resources are increased; fourth, data consistency issues may also occur, especially in concurrent transaction processing.

[0160] To address these technical issues, the following approaches are commonly used: first, data partitioning and parallel computing: dividing large-scale data into smaller partitions makes computing tasks easier to manage and execute. Parallel computing allows for simultaneous processing of multiple data partitions, accelerating computational speed. Second, data compression algorithms are employed to reduce data storage requirements. Third, distributed systems are employed to store massive amounts of data across multiple nodes, achieving high throughput and scalability. Fourth, streaming computing is employed to process streaming data in real time, reducing latency and improving computational efficiency.

[0161] The above-mentioned means only increase the data processing capacity from the perspective of data storage and calculation algorithms, so as to reduce the processing difficulty caused by the maintenance and calculation of massive data. However, it does not solve the problem of how to obtain the deformation of the tunnel surrounding rock based on the monitoring data in a timely and accurate manner, and appropriately reduce the monitoring data to improve the monitoring efficiency. Therefore, the present invention adopts a method of multi-level grid division of the tunnel surrounding rock contour model, and gradually divides the grid into layers according to the increasing degree of spatiotemporal deformation in the monitoring area, thereby improving the monitoring accuracy and monitoring frequency while reducing the amount of data, so as to reduce the processing difficulty caused by the operation and maintenance and calculation of massive monitoring data, effectively ensure the monitoring accuracy of long-distance complex tunnels, reduce unnecessary repeated operations in areas without impact hazards, and improve monitoring accuracy and timeliness.

[0162] In some embodiments of the present disclosure, step 105 may specifically include the following steps:

[0163] Step c1: when there is a grid with a rock burst risk coefficient greater than a preset threshold among multiple grids, the grid with the rock burst risk coefficient greater than the preset threshold is determined as a target grid.

[0164] Step c2: determine the size of the target grid.

[0165] Step c3: According to the size of the target grid, the target grid is divided into multiple K-level grids.

[0166] Among them, the target grid is the K-1 level grid.

[0167] In one embodiment, when there is at least one grid among multiple grids whose rock burst hazard factor is greater than a preset threshold, the at least one grid is determined as a target grid, and for each target grid, the size of the target grid is determined. According to the size of the target grid, the target grid is meshed to obtain multiple K-level grids.

[0168] It is understandable that, since each pair of grids is divided once, the level of the divided grid increases by one level compared to the level of the divided grid. For example, after dividing a grid of level 1, four grids of level 2 can be obtained.

[0169] In some embodiments of the present disclosure, step c3 may specifically include the following steps:

[0170] Step c31 : when the size of the target grid is larger than the preset size, the target grid is divided into multiple K-level grids according to an extension direction perpendicular to the surrounding rock of the monitored coal mine roadway.

[0171] The preset size is larger than the preset minimum grid division size.

[0172] In one embodiment, when the length of the target grid in the extension direction of the tunnel surrounding rock is greater than a first preset length, the target grid is meshed according to the strike direction perpendicular to the monitored coal mine tunnel surrounding rock, that is, the density of the grid is increased along the extension direction of the tunnel surrounding rock to obtain multiple K-level grids.

[0173] Step c32: when the size of the target grid is smaller than or equal to the preset size and larger than the minimum grid division size for the first time, determining the location of the target grid;

[0174] When the location is the roof or floor of the surrounding rock of the coal mine roadway to be monitored, the target grid is divided into multiple K-level grids in a direction parallel to the strike direction of the monitored coal mine roadway; and

[0175] When the location is the main side or secondary side of the surrounding rock of the coal mine roadway to be monitored, the target grid is divided into multiple K-level grids according to the direction parallel to the strike of the monitored coal mine roadway.

[0176] In one embodiment, when the length of the target grid in the extension direction of the tunnel surrounding rock is less than or equal to the first preset length for the first time, the position of the target grid is determined, for example, Figure 9 As shown in the figure, the target grid may be located at any position in the main wall, auxiliary wall, roof or floor. When the target grid is located at the roof or floor, the target grid is meshed in a direction parallel to the strike of the monitored coal mine roadway; when the target grid is located at the main wall or auxiliary wall, the target grid is meshed in a direction parallel to the strike of the monitored coal mine roadway.

[0177] For example, if Figure 11 The fourth level of grid division is that after the length of the target grid in the extension direction of the tunnel surrounding rock is less than or equal to 5m for the first time, if the target grid is at the roof or bottom plate position, the target grid is grid divided in the direction parallel to the strike of the monitored coal mine tunnel; if the target grid is at the main wall or auxiliary wall position, the target grid is grid divided in the direction parallel to the strike of the monitored coal mine tunnel.

[0178] Further, such as Figure 11 As shown, level 0: undivided;

[0179] First-level grid division: the roof, floor, main side and auxiliary side are divided into 2 grids, and the overall monitoring network of the tunnel includes 8 grids;

[0180] Second level grid division: the left grids of the roof, floor, main side and auxiliary side are divided into three grids, and the overall monitoring network of the tunnel includes 12 grids.

[0181] The third level of grid division: the left grid of the roof, floor, main side and auxiliary side is divided into three grids. The overall monitoring network of the tunnel includes 20 grids.

[0182] Fourth level grid division: 1 local grid for roof, floor, and sidewall. The length of the warning grid in the x-direction or z-direction is less than 5m; therefore, the corresponding grid division direction is the y-direction or z-direction. At this time, there are 6 grids for the roof, 6 grids for the floor, 6 grids for the sidewall, and 5 grids for the secondary sidewall. The overall monitoring network of the tunnel includes 23 grids.

[0183] The fifth level of grid division: a certain grid in the tunnel main wall is warned and divided. At this time, the main wall grids are 7, and the roof, floor and auxiliary wall remain unchanged. The overall monitoring network of the tunnel includes 24 grids;

[0184] The sixth level of grid division: a certain grid in the main wall of the tunnel is warned and divided. At this time, there are 8 grids in the main wall, and the top plate, bottom plate and auxiliary wall remain unchanged. The overall monitoring network of the tunnel includes 25 grids.

[0185] Step c33: When the size of the target grid is not smaller than or equal to the preset size for the first time and is larger than the minimum grid division size, the target grid is grid-divided according to the direction perpendicular to the direction of the monitored coal mine roadway to obtain multiple K-level grids.

[0186] It can be understood that, since the target grid size is less than 5m for the first time, the target grid has been meshed in a direction parallel to the strike of the monitored coal mine tunnel or in a direction of inclination of the monitored coal mine tunnel. In order to be able to divide the target grid mainly based on the strike direction of the surrounding rock of the monitored coal mine tunnel, when the target grid size is not less than or equal to the preset size for the first time and is greater than the minimum grid division size, the target grid is meshed in a direction perpendicular to the strike direction of the coal mine tunnel to be monitored to obtain multiple K-level grids.

[0187] Step c34: when the size of the target grid is less than or equal to the minimum grid division size, the target grid is not subjected to grid division processing.

[0188] In one embodiment, when the size of the target grid is smaller than or equal to the minimum grid division size, grid division processing of the target grid is stopped.

[0189] In one embodiment, the X direction can be defined as the strike direction of the coal mine roadway to be monitored (0-3000m, the direction of the working face), the Y direction as the dip direction (0-5m), and the Z direction as the vertical direction (0-5m). On-site rock burst monitoring requires determining the rock burst hazard in the X direction so that corresponding measures can be taken in a timely manner. In addition, it is also necessary to evaluate the rock burst hazard in the Y direction and compare and analyze the rock burst hazard in the area near the main wall or the secondary wall, or to evaluate the rock burst hazard in the Z direction and compare and analyze the rock burst hazard in the area near the roof or the floor.

[0190] Therefore, the principles for selecting the hierarchical division direction and determining the division grid length are:

[0191] When performing hierarchical meshing on the grid, the grid is first divided in the X direction, and the Y and Z directions are not divided;

[0192] During the monitoring process, hierarchical grid division is performed in real time on grids with a rock burst hazard coefficient greater than a preset threshold based on the rock burst hazard coefficient calculated in real time. The division is still performed in the X direction until the length of the grid in the X direction is less than or equal to 5m. When the grid needs to be divided again, the division direction is adjusted to the Y direction. Subsequently, when the grid is divided again based on the rock burst hazard coefficient, the division direction is adjusted to the X direction. Thereafter, when the grid is divided again based on the rock burst hazard coefficient, the division direction is fixed to the X direction.

[0193] When the length of the grid in the X direction is less than or equal to 1 m, the grid division process is stopped.

[0194] In some embodiments of the present disclosure, the method proposed in step 102 of using the three-dimensional coordinate data and the historical contour model to determine the uneven degree of temporal variation and the inharmonious degree of spatial variation of energy corresponding to each grid in the roadway surrounding rock contour model may specifically include the following steps:

[0195] For each grid, select target historical round data that matches the grid and the level to which the grid belongs from the historical round data;

[0196] Using the three-dimensional coordinate data and the target historical contour model, the uneven degree of energy change in time and the inharmonious degree of energy change in space corresponding to each grid in the tunnel surrounding rock contour model diagram are determined.

[0197] It should be noted that after each new tunnel surrounding rock contour model is generated based on the latest collected three-dimensional coordinate data, only the grids with higher rock burst risk factors are divided. Therefore, some grids are not divided and their levels remain unchanged, while the divided grids are decomposed into multiple higher-level grids. In order to ensure the rationality and accuracy of the evaluation of the uneven degree of temporal change and the incoordination degree of spatial change of the energy corresponding to the grid, it is necessary to select target historical round data that matches the grid and the level to which the grid belongs from the historical round data for evaluation, that is, select historical data from the historical data in which the level to which the grid belongs is in the same state as the current level to which the grid belongs, so as to evaluate the grid.

[0198] For example, the level of a certain grid at time t4, t5, and t6 is level 3, and the level at time t3 is level 2. When evaluating the grid at time t6 (that is, determining the degree of imbalance in the temporal change and the degree of incoordination in the spatial change of the energy corresponding to the grid), it is necessary to select the historical data of the grid at time t4 and t5 from the historical data, that is, to select all the historical data of the grid at level 3.

[0199] Step 106 , when the rock burst hazard coefficients of the plurality of grids all satisfy the first preset condition, return to the step of obtaining the three-dimensional coordinate data of the surrounding rock of the coal mine roadway to be monitored.

[0200] It should be noted that there is no distinction in the order in which step 105 and step 106 are executed.

[0201] It is understandable that it is possible that the rock burst hazard coefficients of all grids in the tunnel surrounding rock contour model are low. In this case, there is no need to divide the grids, and the step of returning to obtain the three-dimensional coordinate data of the coal mine tunnel surrounding rock to be monitored can be performed.

[0202] According to the multi-level monitoring and early warning of rock burst based on coal mine roadway deformation proposed in the embodiment of the present disclosure, by obtaining the three-dimensional coordinate data and historical data of the surrounding rock of the coal mine roadway to be monitored at the current time node, the three-dimensional coordinate data is used to generate a roadway surrounding rock contour model of the surrounding rock of the coal mine roadway to be monitored at the current time node; the three-dimensional coordinate data and historical data are used to determine the imbalance degree of energy change in time and the incoordination degree of energy change in space corresponding to each grid in the roadway surrounding rock contour model; for each grid, the rock burst hazard coefficient of the grid is determined using the imbalance degree and incoordination degree corresponding to the grid, and a warning is output based on the rock burst hazard coefficient. Warning information; storing the three-dimensional coordinate data and the tunnel surrounding rock contour model in historical data; when there are grids in multiple grids whose rock burst hazard coefficient does not meet the first preset condition, hierarchical grid division is performed on the grid to obtain multiple K-level grids, and the step of obtaining the three-dimensional coordinate data of the surrounding rock of the coal mine tunnel to be monitored is returned to execute. In this way, the degree of imbalance in energy changes in time and the degree of incoordination in space can be continuously judged according to the deformation of the surrounding rock of the coal mine tunnel to be monitored, so as to comprehensively judge the location and degree of rock burst hazard in the tunnel surrounding rock, thereby improving the accuracy and timeliness of rock burst warning. In addition, the use of a multi-level grid division method to evaluate the rock burst hazard degree at different locations in the tunnel surrounding rock can effectively reduce the amount of calculation, improve the calculation efficiency, and thus improve the timeliness of the warning.

[0203] Figure 12 This is a block diagram of a multi-level monitoring and early warning device for rock burst based on coal mine tunnel deformation according to an exemplary embodiment. Figure 12 The device includes a generating unit 1201, a determining unit 1202, an early warning unit 1203, a storage unit 1204, a dividing unit 1205 and an executing unit 1206.

[0204] The generation unit 1201 is configured to obtain three-dimensional coordinate data and historical data of the surrounding rock of the coal mine roadway to be monitored at a current time node, and generate a roadway surrounding rock contour model of the surrounding rock of the coal mine roadway to be monitored at the current time node using the three-dimensional coordinate data; the roadway surrounding rock contour model includes a plurality of grids; the size of each of the plurality of grids corresponds to a grid level to which the grids belong; the grid level is less than or equal to N; N is an integer greater than 1; and the historical data includes historical three-dimensional coordinate data and historical contour models of the surrounding rock of the coal mine roadway to be monitored;

[0205] The determining unit 1202 is configured to determine the unevenness of the energy change in time and the incoordination of the energy change in space corresponding to each grid in the roadway surrounding rock contour model using the three-dimensional coordinate data and historical data; the energy is the energy of the grid in the area corresponding to the surrounding rock of the coal mine roadway to be monitored;

[0206] The early warning unit 1203 is configured to determine the rock burst risk factor of each grid by using the imbalance and incoordination corresponding to the grid, and output early warning information based on the rock burst risk factor;

[0207] The storage unit 1204 is used to store the three-dimensional coordinate data and the roadway surrounding rock contour model in the historical data;

[0208] The division unit 1205 is configured to, if a grid whose rock burst hazard coefficient does not meet the first preset condition exists among the multiple grids, perform hierarchical grid division processing on the grids to obtain a plurality of K-level grids, and return to the step of obtaining the three-dimensional coordinate data of the surrounding rock of the coal mine roadway to be monitored; K is an integer less than or equal to N+1;

[0209] The execution unit 1206 is configured to return to the step of obtaining the three-dimensional coordinate data of the surrounding rock of the coal mine roadway to be monitored when the rock burst hazard coefficients of the plurality of grids all meet the first preset condition.

[0210] In some embodiments of the present disclosure, the determining unit 1202 may be specifically configured to:

[0211] For each grid, the geometric center point of the grid is determined as the anchor point of the grid;

[0212] For each anchor point, using the three-dimensional coordinate data and historical three-dimensional coordinate data of the anchor point, determining a displacement of the anchor point, a first degree of imbalance in temporal variation of the displacement, and a first degree of incoordination in spatial variation of the displacement;

[0213] For each grid, the tunnel surrounding rock contour model at the current time node and the historical contour model at the previous adjacent time node are used to determine the convergence area of ​​the grid corresponding region, the second imbalance degree of the convergence area change in time, and the second incoordination degree of the convergence area change in space.

[0214] Based on the first imbalance degree, the first incoordination degree, the second imbalance degree and the second incoordination degree, the imbalance degree of energy changing in time and the incoordination degree of energy changing in space corresponding to each grid in the tunnel surrounding rock contour model are determined.

[0215] In some embodiments of the present disclosure, the determining unit 1202 may further be configured to:

[0216] Using the three-dimensional coordinate data and the historical three-dimensional coordinate data, determine the displacement between the first position coordinate and the second position coordinate of the anchor point; the first position coordinate is the position coordinate of the anchor point at the current time node; the second position coordinate is the position coordinate of the grid at the previous adjacent time node;

[0217] The following formula is used to calculate the displacement change equilibrium anomaly coefficient of the anchor point over time:

[0218]

[0219] Among them, TAC ij is the displacement change equilibrium anomaly coefficient of the i-th anchor point at the j-th time node, the j-th time node is the current time node, D ij is the displacement of the i-th anchor point at the j-th time node, is the average displacement of the i-th anchor point at the 0-j time nodes, n = 1, 2, …, j, LD is the limit value of the displacement of the surrounding rock of the coal mine roadway to be monitored;

[0220] The following formula is used to calculate the anomaly coefficient of the displacement gradient change balance of the anchor point over time:

[0221]

[0222] GTD ij =D ij -D i(j-1)

[0223]

[0224] Among them, TGC ij is the displacement gradient change balance anomaly coefficient of the i-th anchor point at the j-th time node, is the average displacement gradient of the i-th anchor point at the 0-j time nodes, n = 1, 2, ..., j, LGTD is the time displacement gradient limit value of the surrounding rock of the coal mine roadway to be monitored, GTD ij is the gradient between the displacement of the i-th anchor point at the j-1th time node and the displacement of the j-th time node;

[0225] A weighted sum is performed on the displacement change balance anomaly coefficient of the anchor point over time and the displacement gradient change balance anomaly coefficient of the anchor point over time to obtain a first imbalance index value for indicating a first imbalance degree of the displacement change over time.

[0226] In some embodiments of the present disclosure, the determining unit 1202 may further be configured to:

[0227] The following formula is used to calculate the coordinate anomaly coefficient of the displacement change of the anchor point in space:

[0228]

[0229]

[0230] Among them, SAC ijis the coordinate anomaly coefficient of the displacement change of the i-th anchor point in space at the j-th time node, D ij is the displacement, is the average displacement value of all anchor points in the roadway surrounding rock contour model corresponding to the jth time node, which are at the same level as the i-th anchor point; m is the number of all anchor points in the roadway surrounding rock contour model corresponding to the jth time node, which are at the same level as the i-th anchor point; LD is the displacement limit value corresponding to the surrounding rock of the coal mine roadway to be monitored;

[0231] The following formula is used to calculate the coordination anomaly coefficient of the displacement gradient change of the anchor point in space:

[0232]

[0233] GSD ij =D ij -D (i-1)j

[0234] Among them, SGC ij is the coordination anomaly coefficient of the displacement gradient change of the i-th anchor point in space at the j-th time node, is the average displacement gradient of all anchor points in the same layer as the i-th anchor point in the roadway surrounding rock contour model, LGSD is the spatial displacement gradient change limit value corresponding to the surrounding rock of the coal mine roadway to be monitored, and GSD ij is the gradient between the displacement of the i-th anchor point and the displacement of the i-1-th anchor point; the i-1-th anchor point is the anchor point adjacent to the i-th anchor point;

[0235] A weighted sum is performed on the coordination anomaly coefficient of the displacement change of the anchor point in space and the coordination anomaly coefficient of the displacement gradient change of the anchor point in space to obtain a first incoordination index value for representing a first incoordination degree of the displacement change in space.

[0236] In some embodiments of the present disclosure, the determining unit 1202 may further be configured to:

[0237] Determining a second uneven degree of temporal variation of the convergence area includes:

[0238] The following formula is used to calculate the anomaly coefficient of the time-varying equilibrium of the grid convergence area:

[0239]

[0240] Among them, TRAC ij is the time-varying equilibrium anomaly coefficient of the convergence area corresponding to the i-th grid at the j-th time node, the j-th time node is the current time node, R ijis the convergence area corresponding to the i-th grid at the j-th time node, is the average value of the convergence area of ​​the i-th grid at the 0-j time nodes, n = 1, 2, …, j, LR is the limit value of the convergence area corresponding to the surrounding rock of the coal mine roadway to be monitored;

[0241] The following formula is used to calculate the anomaly coefficient of the time-varying equilibrium of the grid convergence area gradient:

[0242]

[0243] GTR ij =R ij -R i(j-1)

[0244]

[0245] Among them, TRGC ij is the time-varying equilibrium anomaly coefficient of the convergence area gradient corresponding to the i-th grid at the j-th time node, is the average displacement gradient of the convergence area corresponding to the i-th grid at the 0-j time nodes, LGTR is the time-varying limit value of the convergence area gradient corresponding to the surrounding rock of the coal mine roadway to be monitored, and GTR ij is the temporal gradient of the convergence area of ​​the i-th grid between the j-1th time node and the j-th time node;

[0246] A weighted sum is performed on the balance anomaly coefficient of the temporal change of the convergence area of ​​the grid and the balance anomaly coefficient of the temporal change of the convergence area gradient of the grid to obtain a second imbalance index value for representing a second imbalance degree of the temporal change of the convergence area of ​​the grid.

[0247] In some embodiments of the present disclosure, the determining unit 1202 may further be configured to:

[0248] The following formula is used to calculate the spatial variation coordination anomaly coefficient of the grid's convergence area:

[0249]

[0250] Among them, SRAC ij is the spatial variation coordination anomaly coefficient of the convergence area corresponding to the i-th grid at the j-th time node, R ij is the convergence area, is the average convergence area of ​​all grids at this level corresponding to the jth time node, m is the total number of grids at the same level as the i-th grid in the roadway surrounding rock contour model corresponding to the jth time node, and LSR is the convergence area limit value corresponding to the grid area at this level of the coal mine roadway surrounding rock to be monitored;

[0251] The following formula is used to calculate the spatial variation coordination anomaly coefficient of the convergence area gradient of the grid:

[0252]

[0253] GSR ij =R ij -R (i-1)j

[0254]

[0255] Among them, SRGC ij is the spatial variation coordination anomaly coefficient of the convergence area gradient corresponding to the i-th anchor point at the j-th time node, is the average value of the convergence area gradient of all grids in the same level as the i-th grid in the roadway surrounding rock contour model diagram, LGSR is the spatial variation limit of the convergence area gradient corresponding to the surrounding rock of the coal mine roadway to be monitored, and GSR ij is the gradient between the convergence area of ​​the i-th grid and the convergence area of ​​the i-1-th grid; the i-1-th grid is the grid adjacent to the i-th grid;

[0256] A weighted sum is performed on the coordination anomaly coefficient of the spatial variation of the convergence area of ​​the grid and the coordination anomaly coefficient of the spatial variation of the convergence area gradient of the grid to obtain a second incoordination index value for representing a second incoordination degree of the spatial variation of the convergence area of ​​the grid.

[0257] In some embodiments of the present disclosure, the early warning unit 1203 may be specifically configured to:

[0258] Calculate the average of the first imbalance degree, the first incoordination degree, the second imbalance degree and the second incoordination degree to determine the rock burst risk coefficient;

[0259] When the size of the grid corresponding to the anchor point is larger than a preset minimum grid division size, determining the level to which the grid belongs, determining the target warning level corresponding to the anchor point according to a first mapping relationship based on the level, and outputting warning information according to the target warning level; the first mapping relationship includes a mapping relationship between the grid level, a plurality of first rock burst hazard coefficient intervals, and the warning level;

[0260] When the size of the grid corresponding to the anchor point is equal to the minimum grid division size, the target warning level corresponding to the grid is determined according to the second mapping relationship, and the warning information is output according to the target warning level; the first mapping relationship includes a mapping relationship between multiple second impact rock pressure hazard factor intervals and warning levels.

[0261] In some embodiments of the present disclosure, the dividing unit 105 may be specifically configured to:

[0262] In the case where there is a grid with a rock burst risk coefficient greater than a preset threshold value among multiple grids, the grid with the rock burst risk coefficient greater than the preset threshold value is determined as a target grid;

[0263] Determine the size of the target grid;

[0264] According to the size of the target grid, the target grid is meshed to obtain multiple K-level grids; the target grid is a K-1 level grid.

[0265] In some embodiments of the present disclosure, the dividing unit 1205 may further be used to:

[0266] When the size of the target grid is larger than the preset size, the target grid is meshed according to the strike direction perpendicular to the surrounding rock of the monitored coal mine roadway to obtain multiple K-level grids; the preset size is larger than the preset minimum meshing size;

[0267] When the size of the target grid is less than or equal to the preset size and greater than the minimum grid division size for the first time, the location of the target grid is determined, and the target grid is grid-divided in the direction parallel to the direction of the monitored coal mine roadway to obtain multiple K-level grids.

[0268] When the size of the target grid is not smaller than or equal to the preset size for the first time and is larger than the minimum grid division size, the target grid is grid-divided according to the direction perpendicular to the strike of the monitored coal mine roadway to obtain multiple K-level grids;

[0269] When the size of the target grid is smaller than or equal to the minimum grid division size, the target grid is not subjected to grid division processing.

[0270] In some embodiments of the present disclosure, the determining unit 1202 may further be configured to:

[0271] For each grid, select target historical round data that matches the grid and the level to which the grid belongs from the historical round data;

[0272] Using the three-dimensional coordinate data and the target historical contour model, the uneven degree of energy change in time and the inharmonious degree of energy change in space corresponding to each grid in the tunnel surrounding rock contour model diagram are determined.

[0273] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0274] According to the multi-level monitoring and early warning device for rock burst based on coal mine tunnel deformation proposed in the embodiment of the present disclosure, by obtaining the three-dimensional coordinate data and historical data of the surrounding rock of the coal mine tunnel to be monitored at the current time node, the three-dimensional coordinate data is used to generate a tunnel surrounding rock contour model of the surrounding rock of the coal mine tunnel to be monitored at the current time node; the three-dimensional coordinate data and historical data are used to determine the degree of imbalance in time change and the degree of incoordination in space change of energy corresponding to each grid in the tunnel surrounding rock contour model; for each grid, the degree of imbalance and incoordination corresponding to the grid is used to determine the rock burst hazard coefficient of the grid, and the rock burst hazard coefficient is output based on the rock burst hazard coefficient. Early warning information; storing the three-dimensional coordinate data and the tunnel surrounding rock contour model in the historical data; in the case where there are grids in multiple grids whose rock burst hazard coefficient does not meet the first preset condition, hierarchical grid division is performed on the grid to obtain multiple K-level grids, and the step of obtaining the three-dimensional coordinate data of the surrounding rock of the coal mine tunnel to be monitored is returned to execute, so that the degree of imbalance in energy changes in time and the degree of incoordination in space can be continuously judged according to the deformation of the surrounding rock of the coal mine tunnel to be monitored, so as to comprehensively judge the location and degree of rock burst hazard in the tunnel surrounding rock, thereby improving the accuracy and timeliness of rock burst warning. In addition, the use of a multi-level grid division method to evaluate the rock burst hazard degree at different locations in the tunnel surrounding rock can effectively reduce the amount of calculation, improve the calculation efficiency, and thus improve the timeliness of the warning.

[0275] Figure 13 This is a block diagram illustrating an apparatus for a multi-level monitoring and early warning method for rockburst based on coal mine tunnel deformation, according to an exemplary embodiment. For example, apparatus 1300 may be an electronic device, such as a mobile phone, computer, digital broadcast terminal, messaging device, game console, tablet device, medical device, fitness device, personal digital assistant, etc.

[0276] Reference Figure 13 , device 1300 may include one or more of the following components: a processing component 1302 , a memory 1304 , a power component 1306 , a multimedia component 1308 , an audio component 1310 , an input / output (I / O) interface 1312 , a sensor component 1314 , and a communication component 1316 .

[0277] Processing component 1302 generally controls the overall operation of device 1300, such as operations associated with display, phone calls, data communications, camera operation, and recording operations. Processing component 1302 may include one or more processors 1320 to execute instructions to perform all or part of the steps of the aforementioned methods. In addition, processing component 1302 may include one or more modules to facilitate interaction between processing component 1302 and other components. For example, processing component 1302 may include a multimedia module to facilitate interaction between multimedia component 1308 and processing component 1302.

[0278] The memory 1304 is configured to store various types of data to support the operations of the device 1300. Examples of such data include instructions for any application or method operating on the device 1300, contact data, phone book data, messages, pictures, videos, etc. The memory 1304 can be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0279] The power component 1306 provides power to the various components of the device 1300. The power component 1306 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the device 1300.

[0280] The multimedia component 1308 includes a screen that provides an output interface between the device 1300 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, slides, and gestures on the touch panel. The touch sensor can not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 1308 includes a front camera and / or a rear camera. When the device 1300 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera can receive external multimedia data. Each front camera and rear camera can be a fixed optical lens system or have a focal length and optical zoom capability.

[0281] The audio component 1310 is configured to output and / or input audio signals. For example, the audio component 1310 includes a microphone (MIC) that is configured to receive external audio signals when the device 1300 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may be further stored in the memory 1304 or transmitted via the communication component 1316. In some embodiments, the audio component 1310 further includes a speaker for outputting audio signals.

[0282] I / O interface 1312 provides an interface between processing component 1302 and peripheral interface modules, such as a keyboard, click wheel, buttons, etc. These buttons may include, but are not limited to, a home button, volume buttons, a start button, and a lock button.

[0283] Sensor assembly 1314 includes one or more sensors for providing various aspects of the status assessment of device 1300. For example, sensor assembly 1314 can detect the open / closed state of device 1300, the relative positioning of components, such as the display and keypad of device 1300. Sensor assembly 1314 can also detect changes in the position of device 1300 or a component of device 1300, the presence or absence of user contact with device 1300, the orientation or acceleration / deceleration of device 1300, and changes in the temperature of device 1300. Sensor assembly 1314 can include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 1314 can also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 1314 can also include an accelerometer, a gyroscope, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0284] The communication component 1316 is configured to facilitate wired or wireless communication between the device 1300 and other devices. The device 1300 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 1316 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 1316 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0285] In an exemplary embodiment, the apparatus 1300 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described methods.

[0286] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 1304 including instructions, which can be executed by the processor 1320 of the apparatus 1300 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0287] In an exemplary embodiment, a computer program product is also provided, comprising a computer program, which implements the above method when executed by the processor 1320 of the apparatus 1300 .

[0288] Other embodiments of the present invention will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the invention that follow from the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the invention being indicated by the following claims.

[0289] It should be understood that the present invention is not limited to the exact construction described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A multi-level monitoring and early warning method for rock burst based on coal mine tunnel deformation, characterized in that: include: Obtaining three-dimensional coordinate data and historical data of surrounding rock of a coal mine roadway to be monitored at a current time node, and generating a roadway surrounding rock contour model of the surrounding rock of the coal mine roadway to be monitored at the current time node using the three-dimensional coordinate data; the roadway surrounding rock contour model includes a plurality of grids; the size of each of the plurality of grids corresponds to a grid level to which the grid belongs; the grid level is less than or equal to N; N is an integer greater than 1; the historical data includes historical three-dimensional coordinate data and historical contour model of the surrounding rock of the coal mine roadway to be monitored; Using the three-dimensional coordinate data and the historical data, determining the degree of unevenness in temporal variation and the degree of incoordination in spatial variation of energy corresponding to each grid in the roadway surrounding rock contour model; the energy is the energy accumulated by the grid in the corresponding area of ​​the surrounding rock of the coal mine roadway to be monitored due to stress deformation; For each grid, using the degree of imbalance and the degree of incoordination corresponding to the grid, determine the rock burst risk coefficient of the grid, and output warning information based on the rock burst risk coefficient; Storing the three-dimensional coordinate data and the roadway surrounding rock contour model in the historical data; If a grid whose rock burst hazard coefficient does not meet the first preset condition exists among the multiple grids, hierarchical grid division processing is performed on the grid to obtain a plurality of K-level grids, and the step of obtaining the three-dimensional coordinate data of the surrounding rock of the coal mine roadway to be monitored is performed again; K is an integer less than or equal to N+1; When the rock burst hazard coefficients of the plurality of grids all meet the first preset condition, returning to the step of obtaining the three-dimensional coordinate data of the surrounding rock of the coal mine roadway to be monitored; The method of using the three-dimensional coordinate data and the historical data to determine the uneven degree of temporal variation and the inharmonious degree of spatial variation of energy corresponding to each grid in the tunnel surrounding rock contour model includes: For each grid, determining the geometric center point of the grid as the anchor point of the grid; For each anchor point, using the three-dimensional coordinate data and historical three-dimensional coordinate data of the anchor point, determining a displacement of the anchor point, a first degree of imbalance in temporal variation of the displacement, and a first degree of incoordination in spatial variation of the displacement; For each grid, using the tunnel surrounding rock contour model at the current time node and the historical contour model at the previous adjacent time node, determine a convergence area of ​​a region corresponding to the grid, determine a second imbalance degree of temporal variation of the convergence area, and determine a second incoordination degree of spatial variation of the convergence area; Determining, based on the first imbalance degree, the first incoordination degree, the second imbalance degree, and the second incoordination degree, the imbalance degree of energy change in time and the incoordination degree of energy change in space corresponding to each grid in the tunnel surrounding rock contour model; The determining of the displacement of the anchor point by using the three-dimensional coordinate data and the historical three-dimensional coordinate data of the anchor point, and the determining of a first uneven degree of temporal change of the displacement, include: Determine the displacement between a first position coordinate and a second position coordinate of the anchor point using the three-dimensional coordinate data and the historical three-dimensional coordinate data; the first position coordinate is the position coordinate of the anchor point at the current time node; the second position coordinate is the position coordinate of the grid at the previous adjacent time node; The following formula is used to calculate the displacement change equilibrium anomaly coefficient of the anchor point over time: in, is the displacement change equilibrium anomaly coefficient of the i-th anchor point at the j-th time node, where the j-th time node is the current time node. is the displacement of the i-th anchor point at the j-th time node, is the average displacement of the i-th anchor point at the 0-j time nodes, n=1, 2, ..., j, is the displacement limit value of the surrounding rock of the coal mine roadway to be monitored; The following formula is used to calculate the anomaly coefficient of the displacement gradient change balance of the anchor point over time: in, is the displacement gradient change balance anomaly coefficient of the i-th anchor point at the j-th time node, is the average displacement gradient of the i-th anchor point at the 0-j time nodes, n=1, 2, 3, ..., j, is the time displacement gradient limit value of the surrounding rock of the coal mine roadway to be monitored, is the gradient between the displacement of the i-th anchor point at the j-1th time node and the displacement of the j-th time node; Performing a weighted summation of the displacement change balance anomaly coefficient of the anchor point over time and the displacement gradient change balance anomaly coefficient of the anchor point over time to obtain a first imbalance index value representing a first imbalance degree of the displacement change over time; The determining of the first degree of incoordination of the spatial variation of the displacement comprises: The following formula is used to calculate the coordinate anomaly coefficient of the displacement change of the anchor point in space: in, is the coordinate anomaly coefficient of the displacement change of the i-th anchor point in space at the j-th time node, D ij is the displacement, is the average displacement of all anchor points in the roadway surrounding rock contour model corresponding to the jth time node, which are at the same level as the i-th anchor point; m is the number of all anchor points in the roadway surrounding rock contour model corresponding to the jth time node, which are at the same level as the i-th anchor point; is the displacement limit value corresponding to the surrounding rock of the coal mine roadway to be monitored; The following formula is used to calculate the coordination anomaly coefficient of the displacement gradient change of the anchor point in space: in, is the coordination anomaly coefficient of the displacement gradient change of the i-th anchor point in space at the j-th time node, is the average displacement gradient of all anchor points in the tunnel surrounding rock contour model that are at the same level as the i-th anchor point, is the spatial displacement gradient change limit value corresponding to the surrounding rock of the coal mine roadway to be monitored, is the gradient between the displacement of the i-th anchor point and the displacement of the i-1-th anchor point; the i-1-th anchor point is the anchor point adjacent to the i-th anchor point; Performing a weighted summation of the coordinate anomaly coefficient of the spatial displacement change of the anchor point and the coordinate anomaly coefficient of the spatial displacement gradient change of the anchor point to obtain a first incoordination index value for representing a first incoordination degree of the spatial change of the displacement; Wherein, when there is a grid whose rock burst hazard coefficient does not meet the first preset condition among the multiple grids, hierarchical grid division processing is performed on the grid to obtain multiple K-level grids, including: If there is a grid with a rock burst risk coefficient greater than a preset threshold value among the plurality of grids, determining the grid with the rock burst risk coefficient greater than the preset threshold value as a target grid; determining a size of the target grid; According to the size of the target grid, the target grid is meshed to obtain a plurality of K-level grids; the target grid is a K-1 level grid.

2. The multi-level monitoring and early warning method for rock burst based on coal mine tunnel deformation according to claim 1 is characterized in that: The historical data also includes the convergence area corresponding to each grid at each historical time node; Determining a second unevenness degree of the temporal change of the convergence area includes: The following formula is used to calculate the time-varying equilibrium anomaly coefficient of the convergence area of ​​the grid: in, is the time-varying equilibrium anomaly coefficient of the convergence area corresponding to the i-th grid at the j-th time node, where the j-th time node is the current time node. is the convergence area corresponding to the i-th grid at the j-th time node, is the average value of the convergence area of ​​the i-th grid at the 0-j time nodes, n=1,2,…,j, is the limit value of the convergence area corresponding to the surrounding rock of the coal mine roadway to be monitored; The following formula is used to calculate the time-varying equilibrium anomaly coefficient of the convergence area gradient of the grid: in, is the time-varying equilibrium anomaly coefficient of the convergence area gradient corresponding to the i-th grid at the j-th time node, is the average displacement gradient of the convergence area corresponding to the i-th grid at the 0-j time nodes, is the time-varying limit value of the convergence area gradient corresponding to the surrounding rock of the coal mine roadway to be monitored, is the temporal gradient of the convergence area of ​​the i-th grid between the j-1th time node and the j-th time node; A weighted sum is performed on the balance anomaly coefficient of the temporal change of the convergence area of ​​the grid and the balance anomaly coefficient of the temporal change of the convergence area gradient of the grid to obtain a second imbalance index value for representing a second imbalance degree of the temporal change of the convergence area of ​​the grid.

3. The multi-level monitoring and early warning method for rock burst based on coal mine tunnel deformation according to claim 2 is characterized in that: The determining of the second degree of incoordination of the spatial variation of the convergence area comprises: The following formula is used to calculate the spatial variation coordination anomaly coefficient of the convergence area of ​​the grid: in, is the spatial variation coordination anomaly coefficient of the convergence area corresponding to the i-th grid at the j-th time node, is the convergence area, is the average convergence area of ​​all grids in this level corresponding to the j-th time node, m is the total number of grids in the same level as the i-th grid in the roadway surrounding rock contour model corresponding to the j-th time node, is the convergence area limit value corresponding to the grid area of ​​the current level of the surrounding rock of the coal mine roadway to be monitored; The following formula is used to calculate the spatial variation coordination anomaly coefficient of the convergence area gradient of the grid: in, is the spatial variation coordination anomaly coefficient of the convergence area gradient corresponding to the i-th anchor point at the j-th time node, is the average convergence area gradient of all grids in the tunnel surrounding rock contour model that are at the same level as the i-th grid, is the spatial variation limit of the convergence area gradient corresponding to the surrounding rock of the coal mine roadway to be monitored, is the gradient between the convergence area of ​​the i-th grid and the convergence area of ​​the i-1-th grid; the i-1-th grid is the grid adjacent to the i-th grid; A weighted sum is performed on the coordination anomaly coefficient of the spatial variation of the convergence area of ​​the grid and the coordination anomaly coefficient of the spatial variation of the convergence area gradient of the grid to obtain a second incoordination index value for representing a second degree of incoordination of the spatial variation of the convergence area of ​​the grid.

4. The multi-level monitoring and early warning method for rock burst based on coal mine tunnel deformation according to claim 1 is characterized in that: Determining the rock burst risk coefficient of the grid by utilizing the imbalance degree and the incoordination degree corresponding to the grid, and outputting warning information based on the rock burst risk coefficient, includes: Calculating an average of the first imbalance degree, the first incoordination degree, the second imbalance degree, and the second incoordination degree to determine the rock burst hazard coefficient; When the size of the grid corresponding to the anchor point is larger than a preset minimum grid division size, determining the level to which the grid belongs, determining a target warning level corresponding to the grid based on the level according to a first mapping relationship, and outputting warning information according to the target warning level; the first mapping relationship includes a mapping relationship between the grid level, a plurality of first rock burst hazard factor intervals, and the warning level; When the size of the grid corresponding to the anchor point is equal to the minimum grid division size, the target warning level corresponding to the anchor point is determined according to the second mapping relationship, and the warning information is output according to the target warning level; the first mapping relationship includes a mapping relationship between multiple second impact rock pressure hazard factor intervals and warning levels.

5. The multi-level monitoring and early warning method for rock burst based on coal mine tunnel deformation according to claim 1 is characterized in that: The target grid is subjected to a mesh division process according to the size of the target grid to obtain a plurality of K-level grids, including: In the case where the size of the target grid is larger than a preset size, the target grid is meshed according to a direction perpendicular to the strike direction of the surrounding rock of the monitored coal mine roadway to obtain a plurality of K-level grids; the preset size is larger than a preset minimum meshing size; When the size of the target grid is smaller than or equal to the preset size and larger than the minimum grid division size for the first time, the target grid is grid-divided in a direction parallel to the strike direction of the monitored coal mine roadway to obtain a plurality of K-level grids; When the size of the target grid is not smaller than or equal to the preset size and is larger than the minimum grid division size for the first time, the target grid is grid-divided according to the direction perpendicular to the monitored coal mine roadway to obtain a plurality of K-level grids; When the size of the target grid is smaller than or equal to the minimum grid division size, no grid division process is performed on the target grid.

6. The multi-level monitoring and early warning method for rock burst based on coal mine tunnel deformation according to claim 1 is characterized in that: The method of using the three-dimensional coordinate data and the historical contour model to determine the uneven degree of temporal variation and the inharmonious degree of spatial variation of energy corresponding to each grid in the tunnel surrounding rock contour model includes: For each grid, selecting target historical profile data that matches the grid and the level to which the grid belongs from the historical profile data; The three-dimensional coordinate data and the target historical contour model are used to determine the uneven degree of energy change in time and the uncoordinated degree of energy change in space corresponding to each grid in the tunnel surrounding rock contour model diagram.

7. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

9. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the computer program implements the method according to any one of claims 1 to 6.

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