Stress synergistic evolution of point-pillar filling stope roof health diagnosis and early warning method

Abstract

The present application relates to the technical field of mine safety monitoring and disaster early warning, and more particularly to a stress synergistic evolution point column filling stope roof health diagnosis and early warning method. The method steps are: arranging a monitoring system, setting three monitoring points in the roof rock mass directly above the point column, in the roof rock mass between adjacent point columns, and in the roof rock mass without point column support with the maximum span; collecting three-direction stress data monitored by each group of monitoring points, and synchronously recording the mining progress of the mine; determining the monitoring time window length according to the mining progress of the mine; calculating the roof danger index, which includes the load transfer ratio, the stress change synergy degree, the horizontal constraint weakening index, and the main stress change increment trajectory angle; calculating the dynamic roof health degree according to the roof danger index, and performing roof health diagnosis and grading early warning. By using the above method, the synergistic working state of the point column roof structure can be dynamically perceived, and accurate and advanced roof health diagnosis and early warning can be realized.

Description

Technical Field

[0001] This invention relates to the field of mine safety monitoring and disaster early warning technology, and in particular to a method for health diagnosis and early warning of the roof of a point-pillar type backfilling stope based on stress co-evolution. Background Technology

[0002] The point-pillar upward horizontal layered filling method is widely used due to its high efficiency, flexibility, and good safety. In this mining process, the point pillars serve as permanent support structures, forming a composite structural system with the roof strata. The long-term stability of this system is crucial for ensuring stope safety and preventing large-scale roof collapse accidents. During mining operations, roof instability not only buries equipment and interrupts production but also directly endangers the lives of workers. Therefore, achieving accurate perception and early warning of roof health status is a key technical challenge that urgently needs to be addressed in the field of mine safety production.

[0003] To prevent roof collapses from harming engineering facilities and personnel, monitoring and early warning are indispensable and effective means. Roof stability monitoring in mining areas mainly includes traditional experience-based judgment and macroscopic observation methods, instrumental monitoring methods, and numerical simulation methods. Traditional experience-based judgment often uses the "knocking on the roof" method, where miners use hammers to strike the roof and judge the integrity of the rock mass by the sound (a clear sound indicates integrity, a hollow sound indicates delamination). This method is highly subjective, relies on personal experience, cannot detect deep-seated hazards, has extremely short warning times, and carries high risks. Macroscopic deformation observation involves visually inspecting the roof for signs such as cracks, spalling, and water seepage. This method also has a time lag; by the time macroscopic phenomena appear, a disaster is often imminent. Roof displacement monitoring instruments include mechanical roof delamination meters, convergence meters, and more advanced laser rangefinders, total stations, and surveying robots. Displacement is the most direct representation of stability. However, it is essentially a result of rock mass failure rather than a cause; the warning time is still relatively short, and minute changes in displacement are difficult to detect and are easily affected by operational interference. Stress / strain monitoring directly monitors changes in stress (or strain) within the roof rock mass. Stress concentration, abnormal increases, or sudden unloading are all warning signs. Currently, vibrating wire, grating, or resistance strain gauge sensors are widely used. However, hollow inclusion stress gauges are a powerful tool for measuring stress changes in rock mass, capable of acquiring triaxial stress data. Stress changes are the driving force behind roof failure, providing a more predictive measure than displacement monitoring. However, traditional methods often focus on whether the absolute value of stress at a single point exceeds limits, failing to fully utilize the overall pattern of stress redistribution and providing insufficient identification of precursors to system instability. Microseismic / acoustic emission monitoring captures these signals through sensor arrays deployed within the rock mass for location and energy analysis. This method can directly perceive the damage process within the rock mass, offering excellent early warning capabilities. However, the system is expensive, data analysis is complex, and it is difficult to distinguish between mining blasting noise and rock mass fracture signals. Numerical simulation prediction methods establish numerical models (such as finite element method (FEM), finite difference method (FLAC), and discrete element method (DEM) of the ore body, surrounding rock, and excavation process) to calculate and analyze the stress, displacement, and plastic zone evolution of the roof during mining, predicting potential hazardous areas. This method can perform risk pre-assessment before mining and be used for design optimization. However, its accuracy heavily depends on the accuracy of rock mass mechanical parameters, which are difficult to obtain and have high dispersion, leading to frequent deviations between simulation results and actual conditions, making it difficult to use for real-time dynamic early warning.

[0004] In recent years, with the development of technology, the use of high-precision in-situ digital hollow inclusion stress gauges for monitoring internal stress in rock masses has become an important method. Existing research and practice mostly focus on judging whether the absolute stress value at the monitoring point exceeds an empirical threshold, or on simple analysis of the stress change trend at a single point. These methods can reflect the stress state of the roof to some extent, but are essentially still static and isolated evaluation modes. At the same time, these limitations lead to early warnings heavily relying on stress reaching a critical value or significant deformation already occurring, resulting in a short warning time window, an inability to reveal the mechanical mechanism of instability, difficulty in guiding effective prevention and control measures, and a high rate of false alarms and missed alarms.

[0005] In particular, when using borehole-embedded hollow cladding stress gauges, the direct and reliable monitoring data is the "triaxial stress change" generated after installation. Existing technologies fail to fully utilize the rich information contained in this dynamic data stream, lack analysis from the perspective of the overall coordinated work of the "point column-top plate" structural system, and cannot identify systemic instability precursors such as load transfer within the system and loss of coordination. Summary of the Invention

[0006] The purpose of this invention is to provide a method for health diagnosis and early warning of the roof of a point-pillar filling mine based on stress co-evolution, thereby solving the above-mentioned technical problems.

[0007] To achieve the above objectives, this invention provides a method for health diagnosis and early warning of the roof of a point-column backfilled stope based on stress co-evolution, the specific steps of which are as follows:

[0008] Step S1: Deploy the monitoring system. Set up at least one set of monitoring points on the roof of the horizontally layered filling stope on the point column type. Each set of monitoring points includes at least three monitoring points. The three monitoring points are respectively set in the roof rock body directly above the point column, in the roof rock body between adjacent point columns, and in the roof rock body without point column support at the maximum span.

[0009] Step S2: Collect stress data from each monitoring point and record the mining progress simultaneously;

[0010] Step S3: Determine the length of the monitoring time window based on the mining progress;

[0011] Step S4: Calculate the roof hazard index based on the stress data and time window length collected in step S2. The roof hazard index includes load transfer ratio, stress change synergy, horizontal constraint weakening index, and principal stress change increment trajectory angle.

[0012] Step S5: Calculate the dynamic roof health status based on the roof hazard index calculated in step S4, perform roof health diagnosis based on the dynamic roof health status, and issue graded early warnings based on the health diagnosis results.

[0013] Preferably, the vertical burial depth of the roof slab corresponding to each group of monitoring points is the same. Stress gauges are installed at the corresponding monitoring points by drilling. The monitoring points are located in the roof slab rock directly above the column, in the roof slab rock between adjacent columns, and in the roof slab rock within the largest span without column support. point, Points and At the point, the stress gauge transmits stress data to the Earth's surface via optical fiber.

[0014] Preferably, in step S4, the load transfer ratio is calculated using the following formula:

[0015] ;

[0016] in, for Load transfer ratio at any time, , as well as They are respectively point, as well as point The amount of stress change in the vertical direction relative to the initial installation state, collected by the stress gauge at any time.

[0017] The load transfer ratio is used to characterize the relative support effectiveness of a point column. When, it indicates that the point column support is effective, when When the point column support fails, the smaller the load transfer ratio, the less the support effect of the point column, and the load is transferred to the top plate with a span greater than the set value.

[0018] Preferably, in step S4, the formula for calculating the stress change synergy is as follows:

[0019] ;

[0020] in, To determine the degree of synergy in stress changes within the current monitoring time window, The function for calculating the Pearson correlation coefficient. for The rate of change of vertical stress at the point within the current monitoring time window. , for The rate of change of vertical stress at the point within the current monitoring time window. ;

[0021] When the roof is in a healthy condition When the point column fails, the stress change synergy decreases.

[0022] Preferably, in step S4, the horizontal constraint weakening index is calculated. Calculate the horizontal constraint weakening index of a single point using the data at point C, and let... The formula for calculating the horizontal constraint weakening index at a single point is as follows:

[0023] ;

[0024] in, for point Time-level constraint weakening index. and They are respectively point The stress gauge collects data relative to the initial installation state. Axial stress variation and Change in axial stress It is a fixed positive number.

[0025] Preferably, in step S4, the horizontal constraint weakening index is calculated. ,comprehensive point, Points and The horizontal constraint weakening index of the point data calculation system makes The formula for calculating the horizontal constraint weakening index of the system is as follows:

[0026] ;

[0027] in, This represents the index of horizontal constraint weakening in the system. , as well as These are the horizontal constraint weight coefficients, and , , as well as They are respectively , as well as point The time-level constraint weakening index.

[0028] The horizontal constraint weakening index characterizes the degree of horizontal stress relief corresponding to the increase in vertical stress, and the horizontal constraint weakening index is negatively correlated with the horizontal constraints that maintain the stability of the roof.

[0029] Preferably, in step S4, with The trajectory angle of the principal stress change increment is calculated from the data at the points. The formula for calculating the trajectory angle of the principal stress change increment is as follows:

[0030] ;

[0031] in, The trajectory angle of the principal stress change increment. for The unit vector representing the direction of the maximum principal stress change increment at any given moment. For time intervals, for The unit vector of the direction of the maximum principal stress change increment;

[0032] according to , as well as The value determines the direction of the maximum principal stress change increment; the trajectory angle of the principal stress change increment characterizes the damage to the top structure. During the stable stage of the top plate, the trajectory angle of the principal stress change increment is a stable value. When damage occurs inside the top plate, the trajectory angle of the principal stress change increment jumps.

[0033] Preferably, in step S5, the roof hazard index, composed of the normalized load transfer ratio, stress change synergy, horizontal constraint weakening index, and principal stress change increment trajectory angle, is converted into dynamic roof health using a weighted geometric mean model. The formula for calculating the dynamic roof health is as follows:

[0034] ;

[0035] in, For the dynamic health of the roof slab, , , as well as All are health weighting coefficients;

[0036] , , as well as After normalization, they are respectively The load transfer ratio, stress change synergy, horizontal constraint weakening index, and principal stress change increment trajectory angle are all considered.

[0037] Preferably, in step S5, a graded early warning is issued based on the health diagnosis results as follows:

[0038] when When the time is right, it indicates that the top plate is in a healthy state;

[0039] when When this occurs, it indicates that the roof is in a sub-healthy state, triggering a blue alert.

[0040] when When this occurs, it indicates that the roof is in a potential risk condition, and a yellow alert is activated.

[0041] when When this occurs, it indicates that the roof is in a dangerous condition, and an orange alert is activated.

[0042] when When this occurs, it indicates that the top plate is in a critical state of instability, and a red alert is activated.

[0043] Therefore, the above-mentioned method for health diagnosis and early warning of point-column backfilled mining area using stress co-evolution has the following beneficial effects:

[0044] (1) Completely get rid of the dependence on the absolute stress of the original rock, which is difficult to obtain accurately, and directly use the most reliable monitoring data to carry out the co-evolution of mining stress, thereby improving the accuracy of early warning.

[0045] (2) From the perspective of the point column-top plate system, the system health is diagnosed by analyzing the relative relationship and linkage of the triaxial stress changes at the top plate above the point column, the top plate between the point columns, and the top plate of the large span, rather than looking at the data of a single point in isolation, so as to improve the accuracy of early warning.

[0046] (3) The instability mechanism of the roof is reflected by multiple indicators, namely load transfer ratio, stress change coordination degree, horizontal constraint weakening index and principal stress change increment trajectory angle, which improves the instability precursor and its sensitivity, and can provide early warning time much earlier than stress value exceeding the limit. The fusion of multiple indicators can be mutually verified, which greatly reduces the risk of false alarms and missed alarms.

[0047] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0048] Figure 1 This is a flowchart of the stress-coordinated evolution method for health diagnosis and early warning of the roof of a point-column type filling stope according to the present invention.

[0049] Figure 2 This is a diagram showing the drilling setup at point A in this embodiment;

[0050] Figure 3 This is a diagram showing the drilling setup at point B in this embodiment;

[0051] Figure 4 This is a diagram showing the drilling setup at point C in this embodiment; Detailed Implementation

[0052] In the description of this invention, it should be noted that the terms "upper," "lower," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product is in use. They are used only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," and "connect" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0053] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0054] The specific application of this embodiment in a mine is as follows:

[0055] Deposit type: Medium-thick layered skarn copper deposit, buried at a depth of approximately -450 meters;

[0056] Ore body conditions: The ore body has an average thickness of 25 meters and dips sharply. The roof is marble and the floor is hornfels. It has moderate stability (uniaxial compressive strength of approximately 100 MPa) and relatively well-developed joints.

[0057] The original rock stress field is dominated by tectonic stress, with the maximum horizontal principal stress direction being N30°E and the magnitude being approximately 20-25 MPa.

[0058] Mining method: Point-pillar type upward horizontal layered filling method.

[0059] Specific parameters: The ore body is 30 meters wide, and the point pillars are 4m×4m in size, arranged irregularly, and placed in low-grade ore bodies as much as possible. The center-to-center distance between the point pillars is 12 meters. After each layer (5-6 meters high) is mined, full tailings cemented backfilling is used.

[0060] like Figure 1 As shown, a method for health diagnosis and early warning of the roof of a point-column backfilling stope based on stress co-evolution is described, with the following specific steps:

[0061] Step S1: Deploy the monitoring system. At least one set of monitoring points is installed on the roof of the horizontally layered filling stope using a point-column system. Each set includes at least three monitoring points, located in the roof rock directly above the point column, in the roof rock between adjacent point columns, and in the roof rock without point column support at the maximum span. The vertical burial depth of the roof corresponding to each set of monitoring points is the same. Stress gauges (in this embodiment, inclusion stress gauges) are installed at the corresponding monitoring points by drilling. The monitoring points in the roof rock directly above the point column, in the roof rock between adjacent point columns, and in the roof rock within a span greater than a set value are respectively... point, Points and point.

[0062] Point: Represents the direct supporting effect of the point column. This is a stress concentration point, a key response point reflecting whether the point column effectively bears the load and whether it yields. For example... Figure 2 As shown.

[0063] Point: Represents the bending effect of the roof slab. The force here is primarily bending, making it a key area for monitoring whether the roof slab experiences harmful bending, tensile cracking, or shear failure. For example... Figure 3 As shown.

[0064] Point: Represents the maximum load and potential instability risk of the roof structure. This is the location with the largest span, the most unfavorable stress, and the weakest point of the roof slab. For example... Figure 4 As shown.

[0065] Table 1 shows the statistical data of the construction of the installation holes for the segmented stress monitoring gauge.

[0066] Table 1. Statistical Table of Construction Data for Installation Holes of 4017m Segmented Stress Monitoring Gauge

[0067]

[0068] Figures 2-4 As shown in the figure, the black area represents the geological copper ore body, the gray area represents the mining area, and the arrows indicate the locations of boreholes.

[0069] Step S2: Collect stress data (triaxial stress, divided into stresses in the x, y, and z axes) from each monitoring point at a frequency of 10 minutes per measurement. The stress gauge transmits the stress data to the ground surface via optical fiber. Simultaneously, record the mining progress.

[0070] Step S3: Determine the length of the monitoring time window based on the progress of mining operations.

[0071] Step S4: Calculate the roof hazard index based on the stress data and time window length collected in step S2. The roof hazard index includes load transfer ratio, stress change synergy, horizontal constraint weakening index, and principal stress change increment trajectory angle.

[0072] The formula for calculating the load transfer ratio is as follows:

[0073] ;

[0074] in, for Load transfer ratio at any time, , as well as They are respectively point, as well as point The amount of stress change in the vertical direction relative to the initial installation state, collected by the stress gauge at any time.

[0075] The load transfer ratio is used to characterize the relative support effectiveness of point columns. The denominator reflects the trend of total load variation in the mid-span of the roof slab, and the numerator reflects the share of load variation borne by the point column. When, it indicates that the point column support is effective, when When the point column support fails, the smaller the load transfer ratio, the less support the point column provides, and the load is transferred to the top slab in the large span area.

[0076] The formula for calculating the degree of synergy in stress variation is as follows:

[0077] ;

[0078] in, The degree of synergy of stress changes within the current monitoring time window (4 hours in this example) The function for calculating the Pearson correlation coefficient. for The rate of change of vertical stress at the point within the current monitoring time window. , for The rate of change of vertical stress at the point within the current monitoring time window. When the roof is in a healthy condition, When a point column fails, the stress change synergy decreases. The rate of change at point A slows down or becomes negative (unloading), while the rate of change at point C accelerates, causing the SCS to decrease or even become negative. This is a very strong warning signal of system instability.

[0079] In step S4 of this embodiment, the horizontal constraint weakening index of a single point is calculated using the data at point C. Taking point C as an example, point C (located at the center of a large-span region) is the location most prone to horizontal constraint weakening. Let... The formula for calculating the horizontal constraint weakening index at a single point is as follows:

[0080] ;

[0081] in, for point Time-level constraint weakening index. and They are respectively point The stress gauge collects data relative to the initial installation state. Axial stress variation and Change in axial stress It is a fixed positive number.

[0082] The horizontal constraint weakening index characterizes the degree of horizontal stress relief corresponding to the increase in vertical stress, and the horizontal constraint weakening index is negatively correlated with the horizontal constraints that maintain the stability of the roof.

[0083] The formula for calculating the trajectory angle of the principal stress change increment is as follows:

[0084] ;

[0085] in, The trajectory angle of the principal stress change increment. for The unit vector representing the direction of the maximum principal stress change increment at any given moment. For time intervals, for The direction of the maximum principal stress change increment is the unit vector; according to , as well as The value determines the direction of the maximum principal stress change increment. The trajectory angle of the principal stress change increment characterizes the damage to the top structure. During the stable stage of the top plate, the trajectory angle of the principal stress change increment is a stable value. When micro-damage occurs inside the top plate (such as crack penetration), the trajectory angle of the principal stress change increment jumps and shows a peak, which characterizes the earliest micro-signs of structural damage.

[0086] Step S5: Calculate the dynamic health of the roof based on the roof hazard index calculated in step S4, perform roof health diagnosis based on the dynamic health of the roof, and issue graded early warnings based on the health diagnosis results.

[0087] The roof dynamic health is calculated using a weighted geometric mean model, which combines the normalized load transfer ratio, stress change synergy, horizontal constraint weakening index, and principal stress change increment trajectory angle. The formula for calculating the roof dynamic health is as follows:

[0088] ;

[0089] in, For the dynamic health of the roof slab, , , as well as All are weighting coefficients; , , as well as After normalization, they are respectively The load transfer ratio, stress change synergy, single-point horizontal constraint weakening index, and principal stress change increment trajectory angle are all considered.

[0090] The following tiered early warning systems are implemented based on health diagnosis results:

[0091] when When the time is right, it indicates that the top plate is in a healthy state.

[0092] when When this occurs, it indicates that the top plate is in a sub-healthy state, triggering a blue alert.

[0093] when When this occurs, it indicates that the roof is in a potential risk condition, and a yellow alert is activated.

[0094] when When this occurs, it indicates that the roof is in a dangerous condition, and an orange alert is activated.

[0095] when When this occurs, it indicates that the top plate is in a critical state of instability, and a red alert is activated.

[0096] The response measures for each warning level are shown in Table 2.

[0097] Table 2 Response measures for each warning level

[0098]

[0099] The changes in triaxial stress monitored during the five monitoring periods are shown in Table 3.

[0100] Table 3. Changes in triaxial stress monitored during the five monitoring periods

[0101]

[0102] Calculate the load transfer ratio, stress change synergy, horizontal constraint weakening index, and principal stress change increment trajectory angle at four time points.

[0103] The calculated load transfer ratios are 3.50, 1.857, 1.325, and 0.765. The load transfer ratio continuously decreases from 3.50 to 0.765. The load transfer ratio is less than 1 at the fourth moment, indicating that the load has been completely transferred from the point column (point A) to the large span area (point C), and the point column support has failed.

[0104] The calculation results of the stress variation synergy degree are as follows: This indicates that the rate of stress change at point A (point column) is decreasing (or even negative), while the rate of stress change at point C (large span) is increasing. The two responses are completely opposite, and the system's synergy has been completely destroyed, which is a strong signal of instability.

[0105] The horizontal constraint weakening index results are: -0.18°, -0.022, 0.05 and 0.082. The horizontal constraint weakening index changes from negative to positive and finally increases to 0.082, indicating that from the moment it becomes positive, the horizontal stress changes from loading to unloading, and the degree of unloading intensifies with the increase of vertical load, and the horizontal constraint capacity is significantly weakened.

[0106] Taking the data at point C as an example, the four calculated angles of the principal stress increment trajectory are: 0°, 12°, 6°, and 3.5°. The principal stress increment trajectory angle is larger at the second moment because the stress state changes significantly from the initial state to significant load bearing. Afterward, the angle decreases and stabilizes at a lower level. At the third and fourth moments, the direction of the maximum principal stress does not deviate drastically, and the stress path is relatively stable.

[0107] In this situation, the trajectory angle of the principal stress change increment may not be the most important early warning indicator. If the trajectory angle is large and there is a sudden and huge directional deflection, it indicates that the stress mechanism of the top plate at point C has changed fundamentally (e.g., from the compression bending of the plate to the bending of the cantilever beam), which is usually a sign of the formation of macroscopic cracks inside.

[0108] The normalization process for load transfer ratio, stress change synergy, horizontal constraint weakening index, and principal stress change increment trajectory angle is as follows:

[0109] , hour, .

[0110] , hour, , hour, .

[0111] The threshold is set to 0.1.

[0112] .

[0113] The results of the normalization process are shown in Table 4.

[0114] Table 4 Normalization results at each time point

[0115]

[0116] , , as well as Both are 0.25.

[0117] At time T1: The roof's dynamic health level is 0.975, and the roof's status is healthy.

[0118] At time T2: The roof's dynamic health level is 0.775, indicating that the roof is in a sub-healthy state, and a blue alert is activated.

[0119] At time T3: The roof's dynamic health level is 0.700, indicating that the roof is in a sub-healthy state, and a blue alert is activated.

[0120] At time T4: The roof dynamic health status is 0.438, indicating that there is a potential risk to the roof. A yellow warning is activated, an alarm is issued, and safety personnel are required to immediately analyze the cause, strengthen monitoring of the roof at this location, and prepare to stop mining in the danger zone.

[0121] Example 2:

[0122] The difference between this embodiment and Embodiment 1 is that in step S4, the horizontal constraint weakening index is calculated. ,comprehensive point, Points and The horizontal constraint weakening index of the point data calculation system makes The formula for calculating the horizontal constraint weakening index of the system is as follows:

[0123]

[0124] in, This represents the index of horizontal constraint weakening in the system. , as well as These are the horizontal constraint weight coefficients, and , , as well as They are respectively , as well as point The time-level constraint weakening index. At its maximum, the weakening of constraints at this point is directly related to overall instability; Second highest A point failure means the collapse of the supporting system; The lower level indicates local instability.

[0125] Using the monitoring data from the above case (the triaxial stress changes at points A, B, and C between time T0 and T4), the horizontal constraint weakening coefficient takes into account the combined influence of points A, B, and C.

[0126] Formula for calculating the dynamic health of the roof slab:

[0127] ;

[0128] Since the mining disturbances at times T1 and T2 are relatively small, only times T3 and T4 will be used as examples.

[0129] The calculation result is:

[0130] At time T3: the roof's dynamic health is 0.489, falling between 0.4 and 0.6, and the system should trigger a yellow alert. At this point, although... ,but and It is already in a high-risk state, with poor system coordination and weakened horizontal constraints.

[0131] At time T4: the dynamic health of the roof is 0.253, and the system should trigger an orange alert. , , as well as The values ​​were 0.235, 0.963, 0.984, and 0.804, respectively. This confirms that the load transfer was complete, and all indicators are at extremely high risk levels; multiple indicators together confirm that the system is in a dangerous state.

[0132] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for health diagnosis and early warning of the roof of a point-column backfilling stope based on stress co-evolution, characterized in that, The specific steps are as follows: Step S1: Deploy the monitoring system. Set up at least one set of monitoring points on the roof of the horizontally layered filling stope on the point column type. Each set of monitoring points includes at least three monitoring points. The three monitoring points are respectively set at point A in the roof rock mass directly above the point column, point B in the roof rock mass between adjacent point columns, and point C in the roof rock mass without point column support at the maximum span. Step S2: Collect triaxial stress data from each monitoring point and record the mining progress simultaneously; Step S3: Determine the length of the monitoring time window based on the mining progress; Step S4: Calculate the roof hazard index based on the stress data and time window length collected in step S2. The roof hazard index includes load transfer ratio, stress change synergy, horizontal constraint weakening index, and principal stress change increment trajectory angle. Stress variation synergy When the roof is in a healthy condition When the point column fails, the stress change synergy decreases. Horizontal constraint weakening index It is negatively correlated with the horizontal constraints that maintain roof stability; by The trajectory angle of the principal stress change increment is calculated from the data at the points. The formula for calculating the trajectory angle of the principal stress change increment is as follows: ； in, The trajectory angle of the principal stress change increment. for The unit vector representing the direction of the maximum principal stress change increment at any given moment. For time intervals, for The unit vector of the direction of the maximum principal stress change increment; according to , as well as The value determines the direction of the maximum principal stress transformation increment; and They are respectively point The stress gauge collects data relative to the initial installation state. Axial stress variation and Axial stress variation for point The stress change in the vertical direction relative to the initial installation state is collected by the stress gauge at all times. The trajectory angle of the principal stress change increment represents the damage to the top structure. During the stable stage of the top plate, the trajectory angle of the principal stress change increment is a stable value. When damage occurs inside the top plate, the trajectory angle of the principal stress change increment jumps. The roof hazard index is composed of the normalized load transfer ratio, stress change synergy, horizontal constraint weakening index, and principal stress change increment trajectory angle, using a weighted geometric mean model. Step S5: Calculate the dynamic roof health status based on the roof hazard index calculated in step S4, perform roof health diagnosis based on the dynamic roof health status, and issue graded early warnings based on the health diagnosis results.

2. The method for health diagnosis and early warning of point-column backfilling stope based on stress co-evolution as described in claim 1, characterized in that: The monitoring points in each group correspond to the same vertical burial depth of the top plate. Stress gauges are installed at the corresponding monitoring points by drilling, and the stress gauges transmit stress data to the ground surface via optical fiber.

3. The method for health diagnosis and early warning of point-column backfilling stope based on stress co-evolution as described in claim 2, characterized in that, In step S4, the load transfer ratio is calculated using the following formula: ； in, for Load transfer ratio at any time, , as well as They are respectively point, as well as point The amount of stress change in the vertical direction relative to the initial installation state, collected by the stress gauge at any time. The load transfer ratio is used to characterize the relative support effectiveness of a point column. When, it indicates that the point column support is effective, when When the point column support fails, the smaller the load transfer ratio, the less the support effect of the point column, and the load is transferred to the top plate with a span greater than the set value.

4. The method for health diagnosis and early warning of point-column backfilling stope based on stress co-evolution as described in claim 3, characterized in that, In step S4, the formula for calculating the stress change synergy is as follows: ； in, To determine the degree of synergy in stress changes within the current monitoring time window, The function for calculating the Pearson correlation coefficient. for The rate of change of vertical stress at the point within the current monitoring time window. , for The rate of change of vertical stress at the point within the current monitoring time window. .

5. The method for health diagnosis and early warning of point-column backfilling stope based on stress co-evolution as described in claim 4, characterized in that, In step S4, the horizontal constraint weakening index is calculated. Calculate the horizontal constraint weakening index of a single point using the data at point C, and let... The formula for calculating the horizontal constraint weakening index at a single point is as follows: ； in, for point Time-level constraint weakening index. and They are respectively point The stress gauge collects data relative to the initial installation state. Axial stress variation and Axial stress variation It is a fixed positive number.

6. The method for health diagnosis and early warning of point-column backfilling stope according to claim 4, characterized in that, In step S4, the horizontal constraint weakening index is calculated. ,comprehensive point, Points and The horizontal constraint weakening index of the point data calculation system makes The formula for calculating the horizontal constraint weakening index of the system is as follows: ； in, This represents the index of horizontal constraint weakening in the system. , as well as These are the horizontal constraint weight coefficients, and , , as well as They are respectively , as well as point The time-level constraint weakening index.

7. The method for health diagnosis and early warning of the roof of a point-column backfilling stope based on stress co-evolution as described in claim 6, characterized in that, In step S5, the dynamic roof health status is converted through the roof hazard index. The formula for calculating the dynamic roof health status is as follows: ； in, For the dynamic health of the roof slab, , , as well as All are health weighting coefficients; , , as well as After normalization, they are respectively The load transfer ratio, stress change synergy, horizontal constraint weakening index, and principal stress change increment trajectory angle are all considered.

8. The method for health diagnosis and early warning of the roof of a point-column type backfilled stope based on stress co-evolution as described in claim 7, characterized in that, In step S5, the following graded warnings are issued based on the health diagnosis results: when When the time is right, it indicates that the top plate is in a healthy state; when When this occurs, it indicates that the roof is in a sub-healthy state, triggering a blue alert. when When this occurs, it indicates that the roof is in a potential risk condition, and a yellow alert is activated. when When this occurs, it indicates that the roof is in a dangerous condition, and an orange alert is activated. when When this occurs, it indicates that the top plate is in a critical state of instability, and a red alert is activated.

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