A coal mine filling mining fault activation prediction and water inrush early warning method and system

Abstract

The present application relates to the technical field of coal mine safety mining and mine water disaster prevention, and specifically discloses a coal mine filling mining fault activation prediction and water inrush early warning method and system, which comprises the following steps: obtaining basic data such as mining and filling parameters of a target working face, fault hydrogeological parameters and aquiclude parameters; establishing a numerical simulation model and extracting related parameters such as fault mechanics response parameters, permeability coefficients and effective aquiclude thicknesses; constructing mining-filling coupling disturbance quantity and establishing a fault activation index, a fault slip recursive model, a fault permeability enhancement model, an aquiclude weakening model and a water inrush early warning index model based on the disturbance quantity; and the present application is suitable for fault activation risk identification, water inrush risk grading early warning and filling parameter optimization under filling mining conditions.

Description

Technical Field

[0001] This invention relates to the field of coal mine safety mining and mine water hazard prevention technology, and in particular to a method and system for predicting fault activation and providing early warning of water inrush during coal mine backfilling mining. Background Technology

[0002] In coal mining, faults are not only important geological structures controlling the stability of the surrounding rock, but also significant potential channels for confined water to flow into the mining area, roadways, or goaf. As the working face advances, mining disturbances cause stress redistribution near the fault, manifested as increased shear stress at the fault plane, reduced normal constraint, and decreased effective normal stress. Under the pressure of confined water, the effective normal stress at the fault plane further decreases. If the actual shear stress at the fault plane exceeds its shear strength, the fault may undergo shear slip or combined tension-shear activation. After fault activation, the degree of fracture opening, permeability, and hydraulic connectivity with the aquifer may all increase, potentially inducing mine water inrush accidents.

[0003] Backfilling mining can reduce the risk of fault activation by timely supporting the roof, controlling overburden movement, and mitigating mining disturbance. However, in actual engineering, there are complex coupling effects among backfilling rate, backfilling step distance, coal seam thickness, working face advance distance, fault distance, and confined water pressure. In existing technologies, some evaluation methods mainly use static indicators such as water inrush coefficient, floor aquitard thickness, and floor failure depth, which can reflect the overall water resistance of the floor to a certain extent, but are difficult to directly characterize the changes in fault stress state, slip activation process, permeability enhancement process, and effective aquitard weakening process under backfilling mining conditions.

[0004] In existing fault activation and water inrush prediction models, some formulas characterize filling constraints, mining-induced transmission, fault activation, enhanced permeability, and weakening of aquitards separately. The formulas are relatively scattered and it is difficult to form a unified criterion for engineering applications. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method and system for predicting fault activation and providing early warning of water inrush during coal mine backfilling mining. By incorporating backfilling process parameters, mining disturbance parameters, fault mechanical parameters, and hydrogeological parameters into a unified model, the invention enables the prediction of fault activation status, early warning of water inrush risk, and optimization of backfilling parameters under coal mine backfilling mining conditions.

[0006] On the one hand, a method for predicting fault activation and providing early warning of water inrush during coal mine backfilling mining is provided, including: Acquire and verify the basic data of the target working face, the fault to be evaluated, and the confined aquifer; Based on the verified basic data, a numerical simulation model is established; multiple sets of simulation conditions are set to obtain the fault response parameters under each condition; and the model parameters are determined according to the fault response parameters. Based on the verified basic data and the model parameters, a mining-filling coupling disturbance quantity is established; based on the mining-filling coupling disturbance quantity, a fault activation discrimination model is established, the fault activation index is calculated, and the fault activation state is determined. Establish an evolution model of the water-conducting channel after fault activation and determine the evolution results of the water-conducting channel; Based on the fault activation index and the evolution results of the water-conducting channel, the water inrush early warning index and water inrush risk level are determined; Based on the fault activation state and the water inrush risk level, the filling parameters are optimized, and a safety control scheme is formed.

[0007] Preferably, the step of establishing the sampling-filling coupling disturbance based on the verified basic data and the model parameters is as follows: First, the mining scale, disturbance propagation, propagation accumulation, and filling constraints are uniformly characterized as the mining-filling coupled disturbance quantity; Next, the mining-filling coupled disturbance quantity is established. The calculation formula is as follows: in, This refers to the disturbance caused by the mining-filling coupling. Coal seam thickness; The shortest distance from the working face to the fault; This is a mining-induced impact scale parameter, used to characterize the attenuation scale of mining-induced disturbances propagating along space; The distance the working face advances; The filling rate; For filling step distance.

[0008] Preferably, the step of establishing a fault activation discrimination model based on the mining-filling coupling disturbance, calculating the fault activation index, and determining the fault activation state is as follows: First, based on the initial shear stress of the fault, the shear stress increment coefficient, and the mining-filling coupled disturbance, a fault shear stress growth model is established to characterize the process by which mining disturbance enhances the fault shear driving force. An effective normal stress response model is established based on the initial normal stress of the fault, the confined water pressure near the layer, the normal unloading coefficient, and the mining-filling coupled disturbance. Based on the effective normal stress response model, a fault shear strength model is established; based on the fault surface shear stress growth model and the fault shear strength model, the fault activation index is calculated. ; The fault activation state is determined based on the fault activation index: when When the fault shear stress is lower than the shear strength, the fault is in an inactive state; when At that time, the fault is in a critical activation state; when When the fault shear stress exceeds the shear strength, the fault enters an activated state.

[0009] Preferably, the method further includes: determining the critical disturbance boundary based on the mining-filling coupled disturbance amount, and establishing filling parameter control conditions; the process is as follows: The mining-filling coupling disturbance corresponding to the transition of a fault from an inactive state to a critically activated state is defined as the critical activation disturbance of the fault, and a disturbance discrimination rule is established. The calculation formula of the mining-filling coupling disturbance is combined with the critical activation disturbance, and under the condition that other parameters are determined, the critical filling rate control condition and the critical step distance control condition are calculated respectively. A coordinated approach is formed based on the critical filling rate, critical step distance, or working face advance distance: if the actual filling rate meets the control requirements and the actual step distance does not exceed the critical filling rate, the current scheme can be used as the fault stability control scheme; if either condition is not met, the filling rate should be increased, the filling step distance should be shortened, or the working face advance distance parameter should be adjusted.

[0010] Preferably, the process of establishing an evolution model of the water-conducting channel after fault activation and determining the evolution results of the water-conducting channel is as follows: Determine the initiation conditions for the evolution of the water-conducting channel; when the fault activation index exceeds the critical value, the fault enters the water-conducting channel evolution stage; An activation excess term is introduced. When the activation excess term is no greater than 1, there is no continuous accumulation of fault slip. When the activation excess term is greater than 1, a fault slip recursive model is established. The cumulative slip of the fault is calculated by combining the slip development coefficient and the working face advance distance. Based on the cumulative slip of the fault and the slip-permeability coupling coefficient, a permeability coefficient amplification model is established to obtain the permeability coefficient after fault activation. Based on the cumulative slip of the fault and the slip-water-barrier weakening coefficient, a water-barrier capacity weakening model is established to obtain the effective water-barrier thickness after fault activation. The cumulative slip of the fault, the permeability coefficient after fault activation, and the effective aquitard thickness after fault activation together constitute the evolution result of the water-conducting channel.

[0011] Preferably, based on the fault activation index and the evolution results of the water-conducting channel, a water inrush early warning index is determined, and risk levels are classified; the process is as follows: A flood warning index is determined based on the fault activation index, the permeability coefficient amplification factor, and the degree of weakening of the aquitard. The permeability coefficient amplification factor is the ratio of the permeability coefficient after fault activation to the initial permeability coefficient. The degree of weakening of the aquitard is the ratio of the effective aquitard thickness after fault activation to the initial effective aquitard thickness. The flood inrush warning index is compared with preset first, second, and third thresholds to classify the risk level: when the flood inrush warning index is less than the first threshold, it is low risk; when the flood inrush warning index exceeds the first threshold but is less than the second threshold, it is medium risk; when the flood inrush warning index exceeds the second threshold but is less than the third threshold, it is high risk; and when the flood inrush warning index exceeds the third threshold, it is extremely high risk.

[0012] Preferably, the filling parameters are optimized based on the fault activation state and the risk level of water inrush, and a safety control scheme is formed.

[0013] The filling rate, filling step distance, and working face advance control parameters are taken as variables to be optimized. For each group of candidate backfilling schemes, the mining-backfilling coupled disturbance, fault activation index, cumulative fault slip, permeability coefficient, effective aquitard thickness, and water inrush warning index are calculated sequentially. When a candidate scheme meets the following conditions: the amount of mining-backfilling coupling disturbance does not exceed the critical disturbance boundary, the fault activation index is lower than the critical activation state, and the water inrush warning index is at the allowable risk level, the scheme is considered as the recommended backfilling mining scheme; when a candidate scheme causes the amount of mining-backfilling coupling disturbance to exceed the critical disturbance boundary or the water inrush warning index to enter a higher risk level, the scheme is considered to need to be adjusted. If the risk is mainly caused by excessive disturbance from mining-filling coupling, prioritize increasing the filling rate or shortening the filling step distance; if the risk is mainly caused by water pressure leading to a reduction in effective normal constraint, coordinate with drainage and pressure reduction; if the risk is mainly caused by increased fault water conductivity, combine with grouting reinforcement or advanced treatment; and convert the model output into engineering control actions. Output the optimization results.

[0014] On the other hand, a coal mine backfilling mining fault activation prediction and water inrush early warning system is provided, including: The data acquisition module acquires and verifies the basic data of the target working face, the fault to be evaluated, and the confined aquifer. The numerical simulation model module establishes a numerical simulation model based on the verified basic data; sets multiple sets of simulation conditions and obtains the fault response parameters under each condition; and determines the model parameters based on the fault response parameters. The mining-filling coupling disturbance module establishes the mining-filling coupling disturbance quantity based on the verified basic data and the model parameters; based on the mining-filling coupling disturbance quantity, it establishes a fault activation discrimination model, calculates the fault activation index, and determines the fault activation state. The fault activation prediction module establishes an evolution model of the water-conducting channel after fault activation and determines the evolution results of the water-conducting channel. The water inrush early warning module determines the water inrush early warning index and water inrush risk level based on the fault activation index and the evolution results of the water-conducting channel; it optimizes the filling parameters based on the fault activation state and the water inrush risk level, and forms a safety control scheme.

[0015] Furthermore, an electronic device is also provided, including: Memory, used for non-transitory storage of computer-readable instructions; and Processor, for executing the computer-readable instructions, When the computer-readable instructions are executed by the processor, they perform the method described in the first aspect above.

[0016] In another aspect, a storage medium is also provided for non-transitory storage of computer-readable instructions, wherein when the non-transitory computer-readable instructions are executed by a computer, the method described in the first aspect is performed.

[0017] The above technical solution has the following advantages or beneficial effects: This invention constructs a mining-filling coupled disturbance quantity D, which integrates coal seam thickness, filling rate, filling step distance, working face advance distance, and fault distance into a single disturbance characterization quantity, making the model structure more focused. Based on the effective stress principle and the relationship between fault shear strength, a fault activation index is established, and the fault activation judgment is transformed into an engineering-usable control threshold through the critical disturbance boundary, facilitating the optimization of filling parameters.

[0018] This invention unifies fault slippage, enhanced permeability, and weakening of the effective aquitard into the evolution process of the activated water-conducting channel, enabling the water inrush early warning index to comprehensively characterize fault activation and water inrush risk. Moreover, the parameters can be determined through numerical simulation or field monitoring data, making it suitable for fault activation risk identification, water inrush risk classification and early warning, and backfilling scheme optimization under backfilling mining conditions.

[0019] This invention provides a method for predicting fault activation and providing early warning of water inrush risk, which uses numerical simulation and field monitoring data as parameters, mining-filling coupled disturbance intensity as the core variable, and fault activation index and water inrush early warning index as output results. Attached Figure Description

[0020] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0021] Figure 1 This is an overall flowchart of a method for predicting fault activation and providing early warning of water inrush in coal mine backfilling mining, provided by an embodiment of this disclosure. Figure 2 A schematic diagram of the numerical simulation model and key variables provided in the embodiments of this disclosure; Figure 3 A fitting diagram of the relationship between the mining-filling coupled disturbance and the fault stress response provided in the embodiments of this disclosure; Figure 4 A graph showing the fitting relationship between cumulative fault slip and amplified permeability, and weakened aquitard layer, provided in an embodiment of this disclosure. Figure 5 The evolution curves of fault activation and water inrush early warning during the propulsion process provided in this embodiment of the disclosure; Figure 6 This is a zoning diagram for the fill rate-step spacing optimization provided in the embodiments of this disclosure; Figure 7 Flowchart for constructing the tomographic activation prediction model provided in the embodiments of this disclosure; Figure 8 A flowchart illustrating the construction of a water inrush early warning model based on activation results, as provided in this embodiment of the disclosure; Figure 9 This is a schematic diagram illustrating the model variable relationships and criteria provided in the embodiments of this disclosure. Detailed Implementation

[0022] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0023] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments of the invention. The terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0024] In this embodiment of the invention, "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Furthermore, in the description of this invention, "multiple" refers to two or more.

[0025] Furthermore, to facilitate a clear description of the technical solutions of the embodiments of the present invention, the terms "first" and "second" are used in the embodiments of the present invention to distinguish identical or similar items with essentially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and the terms "first" and "second" are not necessarily different.

[0026] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0027] Example 1 Reference Figure 1 This application discloses a method for predicting fault activation and providing early warning of water inrush during coal mine backfilling mining, comprising: Step 1: Obtain and verify the basic data of the target working face, the fault to be evaluated, and the confined aquifer.

[0028] S1: Obtain and verify the basic data of the target working face, the fault to be evaluated, and the confined aquifer; The basic data includes at least the coal seam thickness, filling rate, filling step distance, working face advance distance, shortest distance from the working face to the fault, pressure of confined water near the fault, initial stress of the fault, fault strength parameters, initial permeability coefficient of the fault, and initial effective water barrier thickness.

[0029] This invention focuses on acquiring and verifying basic data related to the target working face, faults, and confined aquifers, forming an initial parameter system for fault activation prediction and water inrush early warning; including: S11: Determine the evaluation object and spatial boundaries. First, determine the spatial relationship between the target working face, the fault to be evaluated, and the confined aquifer, and use the target fault as the direct evaluation object for fault activation prediction and water inrush early warning. The spatial boundaries should at least include the working face advancement range, the fault influence range, the range of the bottom aquitard, the influence range of the aquifer, and the range of the infill body. Through this step, the risks of mining sources, disturbance propagation paths, fault response locations, and water-conducting channel formation in subsequent models are uniformly incorporated into the same evaluation framework.

[0030] S12: Obtain geological and structural data. Obtain coal seam occurrence conditions and coal seam thickness. Fault attitude, fault displacement, development of fault fracture zones, and shortest distance from the working face to the fault. and the initial thickness of the effective waterproof layer The above data describes the basic conditions for the generation of mining disturbance, the geometric conditions for the propagation of disturbance to the fault, and the initial state of the underlying water-tight structure. Specific values ​​are shown in Table 1.

[0031] Table 1 Basic Data Values

[0032] S13: Obtain hydrogeological data. Obtain the confined water pressure near the fault. Location of the aquifer, aquifer recharge conditions, and hydraulic connection characteristics between the fault and the aquifer. Confined water pressure. Effective normal constraints are used to correct fault planes; the connectivity between the aquifer and the fault is used to determine whether a water-conducting channel may form after fault activation. This step emphasizes that water pressure is not used as the sole criterion for water inrush, but rather participates in the early warning assessment in conjunction with fault stress state, permeability, and water-tightness.

[0033] S14: Obtain mining and backfilling process data. Obtain the backfilling rate. , filling step distance Working face advance distance The method of dividing the advancement phases and the temporal characteristics of the constraint effect of the filling body. Filling rate. Characterizes the adequacy of the support provided by the filling material to the goaf; filling step distance. Characterizes the timeliness of backfilling and support intervention after the formation of the goaf; working face advance distance. This characterizes the cumulative development process of mining disturbances. The above parameters are used to construct the mining-filling coupled disturbance quantity.

[0034] S15: Obtain fault mechanics and seepage parameters. Obtain the initial shear stress of the fault. Initial normal stress of the fault Fault-level cohesion internal friction angle of the fracture surface Initial permeability coefficient of the fault Parameters such as the initial shear stress of the fault. and the initial normal stress of the fault Used to characterize the stress state of the fault before mining; fault plane cohesion. and the internal friction angle of the fracture surface Used to characterize the shear strength of a fault; initial permeability coefficient of the fault. These parameters are used to characterize the water conductivity of faults in their unactivated or initial state. They are determined by a combination of indoor tests, in-situ field tests, geostress inversion, and initial equilibrium results from numerical simulations.

[0035] S16: Perform data verification and inventory processing. Verify the dimensions, time reference, and spatial location of data from boreholes, geological profiles, hydrological observation wells, field logging, test results, backfill design, and monitoring systems. For data from multiple sources for the same parameter, use a combination of experimental values, field inversion values, and simulated correction values ​​to determine the correct value. After verification, generate a basic data inventory, which will serve as input for subsequent modeling, parameter fitting, and early warning judgment.

[0036] Step 2: Based on the verified basic data, establish a numerical simulation model; set multiple sets of simulation conditions and obtain the fault response parameters under each condition; determine the model parameters according to the fault response parameters.

[0037] S2: Establish a numerical simulation model based on the verified basic data, set multiple sets of simulation conditions, and obtain the fault response parameters under each condition.

[0038] Based on the verified basic data in S1, a numerical simulation model under mining-filling conditions was established to extract fault stress, slip, permeability, and aquitard response parameters. Specifically: S21: Establish a model including key geological units. Based on the basic data obtained in step S1, establish a numerical simulation model including coal seams, roof, floor, faults, confined aquifers, and backfill bodies. The model is not intended to replace the prediction formula of this invention, but rather to obtain the response characteristics of faults under different mining-backfilling conditions and to provide samples for model parameter calibration. See the model diagram and variable relationships below. Figure 2 .

[0039] S22: Set the equivalent description method for faults and backfill bodies. Faults can be described using weak-face contact elements, interface elements, or equivalent weak-zone elements, enabling them to represent shear slip, changes in normal constraint, and changes in permeability. Backfill bodies can be applied according to a phased mining and phased filling approach, allowing the model to reflect the engineering sequence of initial mining disturbance followed by backfill constraint. This setting is used to capture the inhibitory effect of filling rate and step distance on fault activation.

[0040] S23: Set simulated operating conditions. Focus on filling rate. , filling step distance Working face advance distance and distance from working face to fault Multiple working conditions were set up. Different working conditions were used to identify the effects of weakened filling constraints, cumulative enhancement from mining, and spatial distance attenuation on the fault response. The purpose of setting the working conditions was to cover the main state range of the fault from unactivated to critically activated to activated development. The specific working conditions and response results based on the actual conditions of this mine are shown in Table 2. Table 2 Fault response parameters under different simulation conditions

[0041] S24: Extract fault response parameters. Under each simulation condition, extract the incremental shear stress on the fault plane in the region adjacent to the fault. Effective normal stress reduction Fault slip Fault permeability coefficient and the effective waterproof layer thickness Response parameters, among which, Characterizing the growth of shear driving force, The normal closure constraint is reduced. Characterizing slip accumulation after fault activation, Characterizing changes in water conductivity, Characterizes the remaining water-resistant capacity.

[0042] S25: Assess the rationality of the response trend. Compare the response changes under multiple working conditions. If the fault shear stress increment, effective normal unloading, and activation index increase as the filling rate decreases, the step distance increases, the advance distance increases, or the fault distance decreases, then the simulated response is consistent with the fault activation mechanism of filling mining. If there are deviations in local working conditions, corrections need to be made based on fault geometry, boundary constraints, strength development of the filling body, and water pressure boundaries.

[0043] S3: Determine the model parameters based on the fault response parameters.

[0044] The model parameters are determined based on the fault response parameters extracted from S24. The model parameters include at least the following: mining impact scale parameters, shear stress increment coefficient, normal unloading coefficient, slip development coefficient, slip-permeability coupling coefficient, and slip-impermeable layer weakening coefficient.

[0045] S31: Determine the source of parameters. Mining-induced impact scale parameters. Shear stress increment coefficient Normal unloading coefficient Slip development coefficient Slip-permeability coupling coefficient and slip-impermeable layer weakening coefficient It is determined through fitting numerical simulation results, inversion of field monitoring data, or joint inversion of numerical simulation results and field monitoring data.

[0046] S32: Fitting the scale parameters of the influence of mining The fault response index was determined by fitting the relationship between the mining-filling coupled disturbance amount under different working face advance distances and different working face-to-fault distances. Specifically, fault response indices were selected under different advance distances and different fault distances, and the relationship between the response index and the mining distance attenuation term and the advance disturbance accumulation term was established. The relationship was then determined based on the principle of minimum error. . It reflects the spatial scale of the propagation of mining impacts to faults and determines the sensitivity of different fault locations to the advancement of the working face.

[0047] Fault response indicators include one or more of the following: shear stress increment of the fault plane, change in effective normal stress of the fault plane, fault slip, change in fault permeability coefficient, and change in effective aquitard thickness.

[0048] S33: Fitted shear stress increment coefficient and normal unloading coefficient Based on the increase in shear stress at the fracture surface Effective normal stress reduction With coupling disturbance Determine the relationship between them. and : (1) (2) In the formula, This reflects the amplification effect of the disturbance on the shear drive enhancement; This reflects the amplifying effect of the disturbance on the weakening of the normal closure constraint. Both factors jointly determine... Fault activation index The direction and extent of the impact.

[0049] Furthermore, the increase in shear stress at the fault plane Effective normal stress reduction Specifically: (3) (4) in, This represents the increment of shear stress at the fracture surface. The effective normal stress reduction at the fault plane. This is a mining-filling coupled disturbance; This refers to the shear stress at the fault plane after mining. This represents the initial shear stress of the fault. This represents the effective normal stress of the fault plane after mining. This represents the initial normal stress of the fault. This refers to the pressure of the confined water near the fault. This is the shear stress increment coefficient; This is the normal unloading coefficient.

[0050] S34: Fitting the slip-permeability coupling coefficient and fault slip. Based on the fault slip... With permeability coefficient magnification factor The relationship between them, and the amount of fault slip. With the reduction amount of the effective waterproof layer Determine the relationship between them. and : (5) (6) in, Used to characterize the sensitivity of increased permeability caused by fault slip; Used to characterize the sensitivity of aquitard thickness reduction caused by fault slip. Slip development coefficient. The value can be determined by fitting the relationship between the incremental fault slip within the propulsion increment and the activation excess term. The fitting curve and parameter results are shown below. Figure 3 , Figure 4 And Table 3.

[0051] Table 3 Model parameter fitting results

[0052] Slip-permeability coupling coefficient Through fault slip The fitting relationship between the coefficient of permeability and the change in permeability was determined.

[0053] Slip-impermeable layer weakening coefficient Through fault slip The fitting relationship between the effective water-resistant layer thickness and the reduction in thickness was determined.

[0054] S35: Verify model applicability. After completing parameter fitting, apply the model under different operating conditions. , , , and The changing trends are compared with simulation results and field monitoring results. If the model can reflect the overall trend of increased fault shear stress, decreased effective normal constraint, slip accumulation, increased permeability, and weakened aquitard, then the model is considered suitable for the target working face; if the deviation is large, the fault geometry, hydraulic boundary, filling strength, or parameter values ​​are corrected.

[0055] Step 3: Based on the verified basic data and the model parameters, establish the mining-filling coupling disturbance quantity; based on the mining-filling coupling disturbance quantity, establish the fault activation discrimination model, calculate the fault activation index, and determine the fault activation state.

[0056] S4: Based on the verified basic data and model parameters, establish the mining-filling coupling disturbance quantity; based on the mining-filling coupling disturbance quantity, establish a fault activation discrimination model, calculate the fault activation index, and determine the fault activation state.

[0057] Based on the verified basic data and model parameters, the mining-filling coupling disturbance quantity is constructed: specifically, based on the coal seam thickness influence term, mining distance attenuation term, advance disturbance accumulation term, and filling constraint weakening term, the mining-filling coupling disturbance quantity is constructed. . As an equivalent disturbance variable, it is used to describe the combined effect intensity on the fault after the mining disturbance at the working face is transmitted to the fault location. The larger the value, the stronger the mining-filling coupling disturbance experienced by the fault, and the higher the probability that the fault will enter an activated state.

[0058] Mining-filling coupled disturbance The specific calculation formula is as follows: (7) in, This refers to the disturbance caused by the mining-filling coupling. It is the coal seam thickness, i.e., the coal seam thickness influence item, which is used to characterize the influence of coal seam thickness on the intensity of mining disturbance; The shortest distance from the working face to the fault; This is a mining-induced impact scale parameter, used to characterize the attenuation scale of mining-induced disturbances propagating along space; The distance the working face advances; The filling rate; For filling step distance; It is the mining distance attenuation term, used to characterize the distance attenuation of mining disturbances as they propagate from the working face to the fault. It is the cumulative disturbance term, used to characterize the accumulation of disturbances generated as the working face advances; It is a filling constraint weakening term, used to characterize the combined constraint effect of filling rate and filling step distance on mining disturbance.

[0059] Specifically: in formula (7) This reflects the fundamental contribution of the mining space size to the disturbance intensity. The greater the coal seam thickness, the larger the goaf formed under the same filling and advancing conditions, and the more significant the impact on stress redistribution near the roof, floor, and faults. This item is used to incorporate the size of the mining target itself into the disturbance amount.

[0060] In formula (7) This is used to reflect the spatial attenuation of mining disturbances as they propagate from the working face to the fault. As mining disturbances propagate outwards, the attenuation is typically not linear. Near-field disturbances are strong, while far-field disturbances attenuate rapidly, approaching background levels after a certain distance. , ; , Using an exponential decay function to characterize the phenomenon is more consistent with the actual laws of change.

[0061] In formula (7) It is used to reflect the process of disturbances gradually accumulating and stabilizing during the advancement of the working face. It satisfies... , ; , In the early stages of advancement, this indicator reflects the gradual establishment of disturbances; after sufficient advancement, this indicator tends to stabilize, indicating that the incremental impact of further advancement on the target fault is slowing down.

[0062] In formula (7) Used to characterize the restraining effect of the filling material on mining disturbances. Filling ratio The higher the level, the more adequate the support for the goaf; the filling step distance The smaller the value, the more timely the infill support intervention; both factors together reduce the disturbance. This factor enables the model to simultaneously reflect the impact of infill rate and infill step distance on fault stability.

[0063] The aforementioned mining distance attenuation term, advance disturbance accumulation term, and filling constraint weakening term all employ exponential functions to characterize the nonlinear process in which mining disturbances attenuate as the distance from the working face to the fault increases, accumulate and tend to stabilize as the working face advances further, and the filling constraint effect strengthens as the filling rate increases and weakens as the filling step distance increases. The characterization of each part is based on practical engineering experience, mine strata movement, mining impact propagation, and nonlinear attenuation and saturation characterization methods in filling mining control.

[0064] Table 2 shows the D values ​​corresponding to different combinations of filling rates, filling step distances, working face advance distances, and working face to fault distances in all calculation results obtained through the mining-filling coupling disturbance calculation formula; Table 4 shows the D values ​​corresponding to each advance distance stage during the working face advance process; and Table 5 shows the D values ​​corresponding to different filling parameter optimization schemes. The D values ​​in the above tables can be directly consulted and referenced in subsequent model parameter fitting, fault activation discrimination, and water inrush risk assessment stages.

[0065] Table 4 Calculation results of fault activation and water inrush early warning during working face advancement

[0066] Table 5. Fault activation and water inrush early warning results under different filling schemes

[0067] Furthermore, based on the mining-filling coupled disturbance, the process of fault shear stress growth and normal constraint weakening is characterized, a fault activation discrimination model is established, the fault activation index is calculated, and the fault activation state is determined. This includes: S41: Based on the initial shear stress of the fault, the shear stress increment coefficient, and the mining-filling coupled disturbance, a shear stress growth model for the fault plane is established. This is done after obtaining the mining-filling coupled disturbance. Subsequently, a fault shear stress growth model was established to characterize the process by which mining disturbances enhance the fault shear driving force. (8) In the formula, This refers to the shear stress at the fault plane after mining. This represents the initial shear stress of the fault. This is the shear stress increment coefficient, reflecting the unit disturbance amount. The degree of sensitivity to the resulting shear stress increase. Formula (8) reflects this. The larger the value, the stronger the shear drive on the fault plane.

[0068] S42: Based on the initial normal stress of the fault, the confined water pressure near the fault layer, the normal unloading coefficient, and the mining-filling coupled disturbance, an effective normal stress response model is established. The shear capacity of the fault depends not only on the strength of the fault plane material but also on the effective normal constraint. Mining unloading and confined water pressure jointly reduce the effective normal stress of the fault plane; therefore, the following model is established: (9) In the formula, This represents the effective normal stress of the fault plane after mining. This represents the initial normal stress of the fault. This refers to the pressure of the confined water near the fault. This is the normal unloading coefficient, reflecting the unit disturbance amount. The degree of weakening of the effective normal constraint caused by this. Formula (9) reflects this. Increased water pressure can reduce fault closure constraints.

[0069] S43: Based on the effective normal stress response model, establish the fault shear strength model. According to the Mohr-Coulomb strength criterion, the shear strength of the fault plane... Represented as: (10) In the formula, The cohesive force at the fracture surface; The internal friction angle of the fracture surface; ·tan( The frictional shear component contributed by the effective normal stress is denoted as . This formula shows that when the effective normal stress decreases, the frictional shear component of the fault plane decreases simultaneously, making it easier for the fault to transition from a stable state to an active state.

[0070] S44. Based on the fault plane shear stress growth model and the fault shear strength model, the fault activation index is calculated. To unify shear driving force and shear capacity into a single criterion, the fault activation index is calculated. : (11) In the formula, The fault activation index is used to characterize how close the actual shear stress at the fault plane is to the shear strength. The larger the value, the closer the fault shear drive is to or exceeds the shear strength. The cohesive force at the fracture surface; The internal friction angle of the fracture surface.

[0071] S45, based on the fault activation index, determines the fault activation state. When When the fault shear stress is lower than the shear strength, the fault is in an inactive state; when At that time, the fault is in a critical activation state; when When the fault shear stress exceeds the shear strength, the fault enters an activated state.

[0072] Under different working conditions The value and state discrimination results are shown in Table 2 and Table 4.

[0073] Furthermore, it also includes: determining the critical disturbance boundary based on the mining-filling coupled disturbance amount, and establishing filling parameter control conditions.

[0074] S5: Based on the mining-filling coupled disturbance, determine the critical disturbance boundary and establish filling parameter control conditions. The process is as follows: Define the mining-filling coupled disturbance corresponding to the transition of the fault from an inactive state to a critically activated state as the critical activation disturbance of the fault and establish a disturbance discrimination rule; combine the calculation formula of the mining-filling coupled disturbance with the critical activation disturbance, and under the condition that the other parameters are determined, calculate the critical filling rate control conditions and critical step distance control conditions respectively; form a coordinated approach based on the critical filling rate, critical step distance, or working face advance distance: if the actual filling rate meets the control requirements and the actual step distance does not exceed the critical filling rate, the current scheme can be used as the fault stability control scheme; if any condition is not met, the filling rate should be increased, the filling step distance shortened, or the working face advance distance parameter adjusted.

[0075] The critical disturbance boundary is the critical disturbance boundary at which a fault transitions from a stable state to a critical activation state. The filling parameter control conditions are the safety control conditions for the filling rate, filling step distance, or working face advance distance.

[0076] The critical disturbance boundary is determined and the filling parameter control conditions are established, specifically as follows: S51: Define the critical disturbance boundary. The mining-filling coupled disturbance amount corresponding to the transition of the fault from an inactive state to a critically activated state is defined as the critical activation disturbance amount of the fault. . It is a threshold used for engineering control, which transforms the fault activation judgment from "stress-intensity comparison" to "disturbance-threshold comparison".

[0077] S52: Deriving the critical activation disturbance of the fault Expression. Let the expression in formula (11) be... Upon reaching the critical state, we obtain: (12) In the formula, This represents the critical activation disturbance of the fault. The numerator indicates the safety margin of the fault's shear strength relative to the initial shear stress before the disturbance; the denominator represents the disturbance amount. The combined sensitivity to the increase in shear drive and the weakening of normal constraints, such as Figure 7 As shown.

[0078] S53: Establish rules for judging disturbance quantities. When At that time, the mining-filling coupled disturbance was insufficient to activate the fault; when At that time, the fault is in a critical activation state; when At this point, the fault enters an activated state. This discrimination rule can be used to quickly determine whether the current backfilling mining scheme will trigger the risk of fault activation.

[0079] S54: Establish critical filling rate control conditions. Given the coal seam thickness, advance distance, fault distance, mining influence scale parameters, and filling step distance, the critical filling rate can be calculated using formula (7). : (13) In the formula, This parameter represents the filling rate at which the fault reaches the critical activation boundary. It is used to determine whether the existing filling rate is sufficient to inhibit fault activation. The actual filling rate of the target working face... When the above conditions are met, the filling rate is considered to meet the requirements for fault stability control.

[0080] S55: Establish critical step distance control conditions. Under the given filling rate, the critical filling step distance can be calculated by formula (7). : (14) In the formula, This parameter is the upper limit of the step size allowed to prevent the fault from exceeding the critical disturbance boundary at a given filling rate. It is used to determine whether the filling intervention is timely enough.

[0081] S56: A coordinated control approach is formed based on the critical filling rate, critical step distance, or working face advance distance. If the actual filling rate meets the control requirements and the actual step distance does not exceed the critical filling rate, the current scheme can be used as a fault stability control scheme; if any condition is not met, the filling rate should be increased, the filling step distance shortened, or the working face advance distance parameter should be adjusted in conjunction.

[0082] The critical boundary and optimization partitioning results are shown in Table 5. Figure 6 .

[0083] Step 4: Establish an evolution model of the water-conducting channel after fault activation and determine the evolution results of the water-conducting channel.

[0084] S6: Based on the fault slip recursive model, permeability coefficient amplification model, and water-impermeability weakening model, establish a water-conducting channel evolution model after fault activation and determine the water-conducting channel evolution results; the process is as follows: determine the water-conducting channel evolution initiation conditions; when the fault activation index exceeds the critical value, the fault enters the water-conducting channel evolution stage; An activation excess term is introduced. When the activation excess term is no greater than 1, there is no continuous accumulation of fault slip. When the activation excess term is greater than 1, a fault slip recursive model is established. The cumulative slip of the fault is calculated by combining the slip development coefficient and the working face advance distance. Based on the cumulative slip of the fault and the slip-permeability coupling coefficient, a permeability coefficient amplification model is established to obtain the permeability coefficient after fault activation. Based on the cumulative slip of the fault and the slip-water-barrier weakening coefficient, a water-barrier capacity weakening model is established to obtain the effective water-barrier thickness after fault activation. The cumulative slip of the fault, the permeability coefficient after fault activation, and the effective aquitard thickness after fault activation together constitute the evolution result of the water-conducting channel.

[0085] Specifically: S61: Determine the initiation conditions for the evolution of the water-conducting channel. When the fault activation index... When the stress does not exceed the critical value, the fault mainly exhibits a stable or critical state where the stress approaches the strength; when Once the critical value is exceeded, the fault may experience continuous slippage, fracture opening, increased permeability, and weakening of the effective aquitard, thus entering the water-conducting channel evolution stage.

[0086] S62: Establish a recursive model for fault slip. To describe the slip accumulation process after fault activation, the following model is established: (15) (16) In the formula, This represents the cumulative slip of the fault. The distance the working face advances; This is the slip development coefficient; = This is the activation overlimit term. This term is used to distinguish between the unactivated stage of the fault and the post-activated slip development stage.

[0087] S63: Explain the activation excess term. When hour, A value of 0 indicates that the fault has not exceeded its shear strength, and the slip does not enter the continuous accumulation stage; when hour, Pick Follow The increase in the value of the fault slip indicates that the rate of slip development accelerates as the degree of exceedance increases. This avoids artificially introducing slip accumulation in an inactive state.

[0088] S64: Establish a permeability amplification model. Fault slippage causes fractures to open, connectivity to increase, and water flow channels to expand; therefore, a permeability amplification model is established: (17) In the formula, The permeability coefficient after fault activation; The initial permeability coefficient of the fault; is the slip-permeability coupling coefficient. Equation (17) reflects the amplification effect of slip accumulation on water conductivity.

[0089] S65: Establish a model to weaken the water-resistant capacity. Fault slip may reduce the effective thickness of the water-resistant layer, therefore, the following model is established: (18) In the formula, The effective thickness of the waterproof layer after fault activation; This is the initial effective waterproof layer thickness; This is the slip-impermeability weakening coefficient. Formula (18) reflects the weakening effect of slip accumulation on impermeability, and is expressed through... or Ensure effective waterproof layer thickness It remains positive and has physical meaning.

[0090] The recursive calculation results are shown in Table 4, and the evolution curves are shown in Table 5. Figure 5 .

[0091] Step 5: Based on the fault activation index and the evolution results of the water-conducting channel, determine the water inrush early warning index and classify the risk level. For example... Figure 8-9 As shown.

[0092] S7: Based on the fault activation index and the evolution results of the water-conducting channel, determine the water inrush warning index and the water inrush risk level. The process is as follows: Based on the fault activation index, the permeability coefficient amplification factor, and the degree of weakening of the aquitard, determine the water inrush warning index; the permeability coefficient amplification factor is the ratio of the permeability coefficient after fault activation to the initial permeability coefficient; the degree of weakening of the aquitard is the ratio of the effective aquitard thickness after fault activation to the initial effective aquitard thickness; The flood inrush warning index is compared with preset first, second, and third thresholds to classify the risk level: when the flood inrush warning index is less than the first threshold, it is low risk; when the flood inrush warning index exceeds the first threshold but is less than the second threshold, it is medium risk; when the flood inrush warning index exceeds the second threshold but is less than the third threshold, it is high risk; and when the flood inrush warning index exceeds the third threshold, it is extremely high risk.

[0093] S71: Determine the components of water inrush risk. Water inrush risk is jointly determined by the degree of fault mechanical activation, the degree of enhancement of fault water conductivity, and the remaining capacity of the effective aquitard. Therefore, fault activation cannot be used as the sole basis for early warning, nor can the permeability coefficient or aquitard thickness be used as a single criterion.

[0094] S72: Constructing a Water Inrush Early Warning Index Based on the fault activation index Permeability coefficient magnification factor And the degree of weakening of the waterproof layer ,Establish: (19) In the formula, The flood warning index; Characterizes the degree of fault mechanical activation; Characterizes the degree of increase in fault permeability; Characterizes the degree of weakening of the effective waterproof layer. The larger the value, the closer the fault is to or beyond the activated state, the stronger its water-conducting capacity and the weaker its water-sealing capacity.

[0095] S73: Substituting the fault activation index, the permeability coefficient amplification model, and the water-impermeability weakening model into the formula, a comprehensive expression is formed. That is, substituting formulas (17) and (18) into formula (19), we obtain: (20) In the formula, This is a flood inrush early warning index used to comprehensively characterize the degree of fault activation, the degree of increase in fault permeability, and the degree of weakening of the effective aquitard. This formula unifies fault activation, slip accumulation, increased permeability, and weakening of the aquitard into a single early warning index, facilitating comparisons between different advancement stages or different filling schemes.

[0096] S74: Determine the risk classification threshold. The classification threshold can be determined based on historical water inrush data, numerical simulation results, field monitoring data, or mine safety management requirements. , and .

[0097] when The risk level is currently low. when The risk level is currently medium. when This is a high-risk situation; when This is at an extremely high risk. in, , and These are the grading thresholds determined based on historical water inrush data, numerical simulation results, on-site monitoring data, or mine safety management requirements.

[0098] S75: Output early warning results. Calculate item by item according to the advancement stage or filling plan. The system outputs the corresponding risk level of sudden water inrush. Specific risk classification results are shown in Tables 4 and 5.

[0099] Step Six: Based on the fault activation state and water inrush risk level, optimize the filling parameters and formulate a safety control plan. The process involves using the filling rate, filling step distance, and working face advancement control parameters as variables to be optimized. For each group of candidate backfilling schemes, the mining-backfilling coupled disturbance, fault activation index, cumulative fault slip, permeability coefficient, effective aquitard thickness, and water inrush warning index are calculated sequentially. When a candidate scheme meets the following conditions: the amount of mining-backfilling coupling disturbance does not exceed the critical disturbance boundary, the fault activation index is lower than the critical activation state, and the water inrush warning index is at the allowable risk level, the scheme is considered as the recommended backfilling mining scheme; when a candidate scheme causes the amount of mining-backfilling coupling disturbance to exceed the critical disturbance boundary or the water inrush warning index to enter a higher risk level, the scheme is considered to need to be adjusted. If the risk is mainly caused by excessive disturbance from mining-filling coupling, prioritize increasing the filling rate or shortening the filling step distance; if the risk is mainly caused by water pressure leading to a reduction in effective normal constraint, coordinate with drainage and pressure reduction; if the risk is mainly caused by increased fault water conductivity, combine with grouting reinforcement or advanced treatment; and convert the model output into engineering control actions. Output the optimization results.

[0100] The optimization scheme includes: given the geological and hydrological conditions of the target working face, changing the filling rate, filling step distance or working face advance distance respectively, calculating the corresponding mining-filling coupled disturbance, fault activation index and water inrush early warning index, and selecting the parameter combination that meets the requirements of fault inactivation and water inrush risk level as the recommended filling mining scheme.

[0101] S8: Optimize filling parameters and formulate a control scheme. S81: Determine the variables to be optimized. After determining the geological, hydrological, and fault strength conditions of the target working face, determine the filling rate. , filling step distance and working face propulsion control parameters As the primary optimization variable, drainage and pressure reduction, grouting reinforcement, and advanced exploration can also be included as auxiliary control measures in the scheme comparison when necessary.

[0102] S82: Establish the scheme calculation process. For each group of candidate filling schemes, calculate the mining-filling coupled disturbance amount sequentially. Fault activation index Fault slip Permeability coefficient Effective waterproof layer thickness and the flood warning index This process allows different options to be compared on the same evaluation scale.

[0103] S83: Determine the criteria for recommending a solution. When a candidate solution satisfies... Not exceeding the critical disturbance boundary Below the activation critical state and When the risk level is within the acceptable range, this scheme is recommended as the backfilling mining scheme; when the candidate scheme leads to... Exceeding the critical disturbance boundary or If the risk level is elevated, the plan is considered to need adjustment.

[0104] S84: Forms the direction of parameter adjustment. If the risk is mainly due to... If the risk is caused by excessive pressure, priority can be given to increasing the filling rate or shortening the filling step distance; if the risk is mainly caused by the reduction of effective normal constraint due to water pressure, drainage and pressure reduction can be combined; if the risk is mainly caused by the enhanced water conductivity of the fault, grouting reinforcement or advanced treatment can be combined. This step converts the model output into engineering control actions.

[0105] S85: Output optimization results. Table 5 shows the results of fault activation and water inrush early warning under different filling schemes. The optimization zoning for filling rate-step distance is shown in [reference needed]. Figure 6 .

[0106] Example Implementation Results: A closed-loop evaluation process is established. Through the above steps, this example establishes a closed-loop evaluation process encompassing "basic data acquisition - numerical model construction - coupled disturbance quantity construction - fault activation identification - critical boundary control - water-conducting channel evolution - water inrush risk early warning - backfilling scheme optimization." This process connects mining disturbances, backfilling constraints, fault mechanical state, and water hazard risk into a continuous model chain.

[0107] This model demonstrates comprehensiveness. Compared to evaluation methods that only use the water inrush coefficient, the thickness of the bottom aquitard, or a single fault stress index, this embodiment can simultaneously reflect the continuous changes in fault shear stress growth, effective normal constraint reduction, slip accumulation, enhanced permeability, and decreased aquitard capacity, thereby improving the completeness of fault activation and water inrush risk assessment under backfilling mining conditions.

[0108] This demonstrates the applicability of the method to the project. In field applications, the example data in the table can be replaced with measured data from the target mine, numerical simulation results, or a combination of both. Furthermore, the risk classification threshold can be adjusted according to the mine's safety management requirements. Therefore, this method can be used for fault activation risk identification, water inrush risk classification and early warning, and backfilling parameter optimization in different mines, faults, and under different backfilling mining conditions.

[0109] Example 2 This embodiment provides a coal mine backfilling mining fault activation prediction and water inrush early warning system; The data acquisition module acquires and verifies the basic data of the target working face, the fault to be evaluated, and the confined aquifer. The numerical simulation model module establishes a numerical simulation model based on the verified basic data; sets multiple sets of simulation conditions and obtains the fault response parameters under each condition; and determines the model parameters based on the fault response parameters. The mining-filling coupling disturbance module establishes the mining-filling coupling disturbance quantity based on the verified basic data and the model parameters; The fault activation prediction module establishes a fault activation discrimination model based on the mining-filling coupled disturbance, calculates the fault activation index, and determines the fault activation status. The water inrush early warning module establishes an evolution model of the water-conducting channel after fault activation and determines the evolution result of the water-conducting channel; based on the fault activation index and the evolution result of the water-conducting channel, it determines the water inrush early warning index and the water inrush risk level; based on the fault activation state and the water inrush risk level, it optimizes the filling parameters and forms a safety control scheme.

[0110] Example 3 This embodiment also provides an electronic device, including: one or more processors, one or more memories, and one or more computer programs; wherein, the processor is connected to the memory, and the one or more computer programs are stored in the memory. When the electronic device is running, the processor executes the one or more computer programs stored in the memory to cause the electronic device to perform the method described in Embodiment 1.

[0111] Example 4 This embodiment also provides a computer-readable storage medium for storing computer instructions, which, when executed by a processor, complete the method described in Embodiment 1.

[0112] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for predicting fault activation and providing early warning of water inrush during coal mine backfilling mining, characterized in that, include: Acquire and verify the basic data of the target working face, the fault to be evaluated, and the confined aquifer; A numerical simulation model is established based on the verified basic data. Set up multiple sets of simulated working conditions and obtain the fault response parameters under each working condition; determine the model parameters based on the fault response parameters. Based on the verified basic data and the model parameters, a mining-filling coupled disturbance quantity is established. Specifically, firstly, the mining scale, disturbance propagation, propagation accumulation, and filling constraints are uniformly represented as a mining-filling coupled disturbance quantity; then, the mining-filling coupled disturbance quantity is established. The calculation formula is as follows: in, This refers to the disturbance caused by the mining-filling coupling. Coal seam thickness; The shortest distance from the working face to the fault; This is a mining-induced impact scale parameter, used to characterize the attenuation scale of mining-induced disturbances propagating along space; The distance the working face advances; The filling rate; For filling step distance; Based on the mining-filling coupled disturbance, a fault activation discrimination model is established to calculate the fault activation index and determine the fault activation state. Establish an evolution model of the water-conducting channel after fault activation and determine the evolution results of the water-conducting channel; Based on the fault activation index and the evolution results of the water-conducting channel, the water inrush early warning index and water inrush risk level are determined; Based on the fault activation state and the water inrush risk level, the filling parameters are optimized, and a safety control scheme is formed.

2. The method for predicting fault activation and providing early warning of water inrush in coal mine backfilling mining according to claim 1, characterized in that, The fault activation discrimination model is established based on the mining-filling coupling disturbance, and the fault activation index is calculated to determine the fault activation state; specifically: First, based on the initial shear stress of the fault, the shear stress increment coefficient, and the mining-filling coupled disturbance, a fault shear stress growth model is established to characterize the process by which mining disturbance enhances the fault shear driving force. An effective normal stress response model is established based on the initial normal stress of the fault, the confined water pressure near the layer, the normal unloading coefficient, and the mining-filling coupled disturbance. Based on the effective normal stress response model, a fault shear strength model is established; based on the fault surface shear stress growth model and the fault shear strength model, the fault activation index is calculated. ; The fault activation state is determined based on the fault activation index: when When the fault shear stress is lower than the shear strength, the fault is in an inactive state; when At that time, the fault is in a critical activation state; when When the fault shear stress exceeds the shear strength, the fault enters an activated state.

3. The method for predicting fault activation and providing early warning of water inrush during coal mine backfilling mining according to claim 1, characterized in that, Also includes: Based on the mining-filling coupled disturbance, the critical disturbance boundary is determined, and the filling parameter control conditions are established; the process is as follows: The mining-filling coupling disturbance amount corresponding to the transition of a fault from an inactive state to a critically activated state is defined as the critical activation disturbance amount of the fault, and a disturbance amount discrimination rule is established. The calculation formula of the mining-filling coupling disturbance amount is combined with the critical activation disturbance amount, and under the condition that the other parameters are determined, the critical filling rate control condition and the critical step distance control condition are calculated in reverse respectively. Based on the critical filling rate, critical step distance, or working face advance distance, a coordinated approach is formed: if the actual filling rate meets the control requirements and the actual step distance does not exceed the critical filling rate, the current scheme can be used as a fault stability control scheme; if any condition is not met, the filling rate should be increased, the filling step distance shortened, or the working face advance distance parameter should be adjusted in conjunction.

4. The method for predicting fault activation and providing early warning of water inrush during coal mine backfilling mining according to claim 1, characterized in that, The process involves establishing an evolution model of the water-conducting channel after fault activation and determining the evolution results of the water-conducting channel. Determine the initiation conditions for the evolution of the water-conducting channel; when the fault activation index exceeds the critical value, the fault enters the water-conducting channel evolution stage; An activation excess term is introduced. When the activation excess term is no greater than 1, there is no continuous accumulation of fault slip. When the activation excess term is greater than 1, a fault slip recursive model is established. The cumulative slip of the fault is calculated by combining the slip development coefficient and the working face advance distance. Based on the cumulative slip of the fault and the slip-permeability coupling coefficient, a permeability coefficient amplification model is established to obtain the permeability coefficient after fault activation. Based on the cumulative slip of the fault and the slip-water-barrier weakening coefficient, a water-barrier capacity weakening model is established to obtain the effective water-barrier thickness after fault activation. The cumulative slip of the fault, the permeability coefficient after fault activation, and the effective aquitard thickness after fault activation together constitute the evolution result of the water-conducting channel.

5. The method for predicting fault activation and providing early warning of water inrush during coal mine backfilling mining according to claim 1, characterized in that, Based on the fault activation index and the evolution results of the water-conducting channel, the water inrush early warning index and water inrush risk level are determined; the process is as follows: A flood inrush warning index is determined based on the fault activation index, the permeability coefficient amplification factor, and the degree of weakening of the aquitard; the permeability coefficient amplification factor is the ratio of the permeability coefficient after fault activation to the initial permeability coefficient. The degree of weakening of the waterproof layer is the ratio of the effective waterproof layer thickness after fault activation to the initial effective waterproof layer thickness; The flood inrush warning index is compared with preset first, second, and third thresholds to classify the risk level: when the flood inrush warning index is less than the first threshold, it is low risk; when the flood inrush warning index exceeds the first threshold but is less than the second threshold, it is medium risk; when the flood inrush warning index exceeds the second threshold but is less than the third threshold, it is high risk; and when the flood inrush warning index exceeds the third threshold, it is extremely high risk.

6. The method for predicting fault activation and providing early warning of water inrush during coal mine backfilling mining according to claim 1, characterized in that, Based on the fault activation state and water inrush risk level, the filling parameters were optimized, and a safety control plan was formulated: Specifically: The filling rate, filling step distance, and working face advance control parameters are taken as variables to be optimized. For each group of candidate backfilling schemes, the mining-backfilling coupled disturbance, fault activation index, cumulative fault slip, permeability coefficient, effective aquitard thickness, and water inrush warning index are calculated sequentially. When a candidate scheme meets the following conditions: the amount of mining-backfilling coupling disturbance does not exceed the critical disturbance boundary, the fault activation index is lower than the critical activation state, and the water inrush warning index is at the allowable risk level, the scheme is considered as the recommended backfilling mining scheme; when a candidate scheme causes the amount of mining-backfilling coupling disturbance to exceed the critical disturbance boundary or the water inrush warning index to enter a higher risk level, the scheme is considered to need to be adjusted. If the risk is mainly caused by excessive disturbance from mining-filling coupling, prioritize increasing the filling rate or shortening the filling step distance; if the risk is mainly caused by water pressure leading to a reduction in effective normal constraint, coordinate with drainage and pressure reduction; if the risk is mainly caused by increased fault water conductivity, combine with grouting reinforcement or advanced treatment; and convert the model output into engineering control actions. Output the optimization results.

7. A coal mine backfilling mining fault activation prediction and water inrush early warning system, characterized in that, include: The data acquisition module acquires and verifies the basic data of the target working face, the fault to be evaluated, and the confined aquifer. A numerical simulation model module is established. Based on the verified basic data, a numerical simulation model is established; multiple sets of simulation conditions are set, and the fault response parameters under each condition are obtained; the model parameters are determined according to the fault response parameters. The mining-filling coupled disturbance module establishes the mining-filling coupled disturbance quantity based on the verified basic data and the model parameters. Specifically, firstly, the mining scale, disturbance propagation, propagation accumulation, and filling constraints are uniformly represented as the mining-filling coupled disturbance quantity; then, the mining-filling coupled disturbance quantity is established. The calculation formula is as follows: in, This refers to the disturbance caused by the mining-filling coupling. Coal seam thickness; The shortest distance from the working face to the fault; This is a mining-induced impact scale parameter, used to characterize the attenuation scale of mining-induced disturbances propagating along space; The distance the working face advances; The filling rate; For filling step distance; The fault activation prediction module establishes a fault activation discrimination model based on the mining-filling coupled disturbance, calculates the fault activation index, and determines the fault activation status. The water inrush early warning module establishes an evolution model of the water-conducting channel after fault activation and determines the evolution result of the water-conducting channel; based on the fault activation index and the evolution result of the water-conducting channel, it determines the water inrush early warning index and the water inrush risk level; based on the fault activation state and the water inrush risk level, it optimizes the filling parameters and forms a safety control scheme.

8. A computer-readable storage medium having a program stored thereon, characterized in that, When executed by the processor, the program implements the steps in the method for predicting fault activation and providing early warning of water inrush in coal mine filling mining as described in any one of claims 1-6.

9. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the method for predicting fault activation and providing early warning of water inrush in coal mine filling mining as described in any one of claims 1-6.

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