An adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures

Abstract

The present invention discloses an adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures, which relates to the fields of mine safety engineering and hydrogeological technology. Through the coordinated work of the grouting mechanism, the data monitoring system, the data acquisition and processing module and the adaptive control module, the automation and intelligence of grouting protection can be realized. By introducing the fissure roughness coefficient and the time-dependent viscosity, the flow resistance of the rough fissure and the time-varying characteristics of the slurry rheology are quantified, and the calculation error of the slurry diffusion radius is reduced. Through the joint inversion algorithm of the microseismic travel time residual and the acoustic wave velocity field, combined with the weighted robust LM algorithm to dynamically adjust the data weight, the precise positioning of the fissure is achieved. The PID gain compensation and saturation function mechanism are adopted to achieve adaptive, safe and efficient grouting. The present invention monitors the fissure dynamics in real time through multi-source data fusion technology, and dynamically optimizes the grouting parameters in combination with the intelligent algorithm, effectively suppresses complex geological interference, reduces the waste of slurry materials, and achieves efficient and accurate plugging of mining-induced fissures.

Description

Technical Field

[0001] The present invention relates to the field of mine safety engineering and hydrogeological technology, and in particular to an adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures. Background Art

[0002] During the mining process, the dynamic expansion of rock fractures under mining stress coupled with the seepage of highly pressurized water can easily trigger water inrush accidents. Traditional grouting and sealing technologies rely primarily on manual experience and discrete geological exploration data, making them difficult to adapt to the three-dimensional dynamic evolution of fracture networks and subject to problems such as delayed monitoring and extensive control. For example, application No. 202411324779.2 discloses a system and method for monitoring water-conducting fracture zones based on combined microseismic monitoring above and below the wellbore. This system optimizes the three-dimensional network structure and improves vertical positioning accuracy through combined microseismic monitoring above and below the wellbore. However, it is limited to a single data source and suffers from insufficient robustness in handling dynamic anomaly data, making it less suitable for use under complex geological conditions. Application No. 201811093419.0 discloses an intelligent grouting measurement and control system and implementation method for fractured rock masses. This system determines the slurry diffusion radius based on borehole sampling of microseismic events. However, due to the limitations of the sampling specimens, it is prone to large errors in complex geological conditions and the cost of repeated sampling is high.

[0003] Existing fracture monitoring technologies, such as borehole imaging and acoustic detection, are limited to localized, static fracture information characterization and are unable to achieve continuous, dynamic capture of the three-dimensional morphology of fractures across the entire working face. While fracture monitoring technologies such as microseismic, optical fiber, and resistivity can monitor fracture information in real time, they generally rely on single-field data inversion and lack multidimensional data fusion, resulting in insufficient positioning accuracy, weak anti-interference capabilities, and delayed dynamic response. Furthermore, conventional grouting systems often employ fixed parameter models and lack the ability to adaptively control the dynamic expansion of fracture networks. Grouting pressure, flow rate, and slurry ratio are difficult to adjust in real time based on fracture morphology and spatial location, which can easily lead to localized slurry retention or ineffective long-range diffusion, resulting in low plugging efficiency and significant material waste. Furthermore, monitoring systems and grouting devices often operate independently, with weak data interaction and collaborative control capabilities. This prevents the formation of a closed "perception-analysis-response" loop, making it difficult to address sudden seepage risks. Therefore, there is an urgent need to develop a closed-loop grouting system that integrates real-time precise monitoring, intelligent decision-making and dynamic control, and to break through the technical bottleneck of efficient identification and intelligent sealing of mining-induced fissures through the collaboration of high-precision sensing, adaptive algorithms and precise actuators.

[0004] This shows that the existing technology needs further improvement. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the purpose of the present invention is to provide an adaptive grouting control and blocking method based on real-time monitoring of mining-induced fissures, which can effectively adapt to various complex geological conditions, collect geological data in real time for data analysis, and perform adaptive grouting operations based on the analysis results, thereby realizing the automation and intelligence of grouting protection and improving mine safety.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solutions: an adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures, the grouting system adopted by which includes a grouting mechanism, a data monitoring system, a data acquisition and processing module and an adaptive control module, the method comprising the following steps: a. Collecting geological data of the mining area and its surroundings, and obtaining geological data to provide a basis for fissure monitoring, the geological data including: stratum lithology, geological structure, ground stress, original fissure aperture and aquifer location.

[0007] b. Based on the geological data, the fracture roughness coefficient and time-dependent viscosity are introduced to quantify the flow resistance of rough fractures and the time-varying rheological characteristics of slurry. The slurry diffusion radius is calculated according to formula (1): .

[0008] (1).

[0009] In formula (1), P is the grouting pressure; t is the slurry diffusion time; σ t is the tensile strength of the rock mass; τ0 is the yield stress; μ(t) is the time-dependent viscosity; ω eff is the effective crack opening.

[0010] c. Install the grouting system and set the initial grouting pressure P0 and the maximum grouting pressure P max and the initial concentration of the slurry C0; the received data is preprocessed by the data acquisition and processing module; the obtained data is transmitted to the adaptive control module, and the multi-dimensional fracture characteristic parameter data of the fracture position and fracture opening are obtained through the multi-physical field coupling inversion algorithm, and a three-dimensional fracture network topology model is simultaneously constructed for grouting strategy optimization.

[0011] d. Based on the weighted robust LM algorithm and Huber loss function, different weights are assigned to the multi-dimensional crack characteristic parameter data and dynamically adjusted to reduce the impact of abnormal data, thereby further accurately optimizing the crack location.

[0012] e. The adaptive control module adjusts the grouting pressure and slurry concentration in real time according to the obtained crack position, crack opening and slurry filling rate, and sends a grouting instruction to the grouting mechanism to grout the cracks through the grouting mechanism.

[0013] In the above-mentioned adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures, in step c, the fissure position is obtained by formula (2) through the multi-physics field coupling inversion algorithm.

[0014] (2).

[0015] In formula (2), F(x) is the joint objective function; α, β, and γ are the weight coefficients for balancing microseismic, acoustic wave data, and model smoothness, respectively; is the observed travel time of the i-th microseismic sensor; (x) is the theoretical travel time of the i-th microseismic sensor; is the standard deviation of microseismic travel time data; is the standard deviation of the fiber speed data; is the measured value of the acoustic wave velocity at the j-th optical fiber measurement position; (x) is the calculated value of the acoustic wave velocity at the jth optical fiber measurement position; is the robust loss function; i is the i-th microseismic sensor; is the total number of microseismic sensors; is the total number of optical fiber sensor measurement positions; j is the jth optical fiber sensor measurement position; is the gradient of the acoustic wave velocity field.

[0016] In the above-mentioned adaptive grouting control and plugging method based on real-time monitoring of mining-induced fractures, in step c, the fracture aperture is obtained by optical fiber strain and temperature compensation inversion, and the specific formula is shown in Equation (3).

[0017] (3).

[0018] In formula (3), ω is the crack aperture; E is the elastic modulus of the rock mass; ε(x) is the distributed strain measured by the optical fiber; ΔT is the temperature change; λ is the thermal expansion coefficient of the rock mass; and L is the length of the crack-affected zone.

[0019] In the above-mentioned adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures, in step e, the adjustment of the grouting pressure is calculated according to formula (4).

[0020] (4).

[0021] In formula (4): P(t) is the real-time grouting pressure; ΔP flow is the flow resistance; K p is the PID control gain of the filling rate deviation; η target is the target filling rate; η(t) is the real-time filling rate; sat is the saturation function; K ω is the crack opening compensation gain; ω critis the critical opening threshold; ω(t) is the real-time crack opening; ReLU(ω crit -ω(t)) is the rectified linear unit function, ReLU(ω crit -ω(t))=max[0,(ω crit -ω(t))].

[0022] In the above-mentioned adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures, in step e, the slurry concentration is adjusted according to formula (5).

[0023] (5).

[0024] In formula (5): C(t) is the real-time slurry concentration; C base is the water-cement ratio benchmark value, which is 0.8:1; ω ref is the reference opening, which is 1mm; a is the opening influence index (usually a=2, the larger the opening, the higher the concentration); b is the weight coefficient of the filling rate change rate; tanh is the limit function that limits the concentration adjustment range; k is the fill rate change rate sensitivity coefficient; dη / dt is the real-time change rate of the fill rate.

[0025] The above-mentioned adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures, the grouting mechanism mainly includes a silo, a water tank, a first stirring tank, a second stirring tank, a mixing tank, a grouting pipe and a water glass solution storage tank; the first stirring tank and the second stirring tank are used for stirring and processing to form slurries of different concentrations; the mixing tank is provided with an agitator and a concentration monitor to control and prepare the slurry of the required concentration.

[0026] The above-mentioned adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures is provided with a triangular plug and an intelligent universal nozzle on the grouting pipe. The triangular plug is used to seal the slurry, and the intelligent universal nozzle is arranged in a triangle. A micro servo motor and an angle sensor are provided in the intelligent universal nozzle for realizing 360° omnidirectional rotation in the horizontal plane and ±50° pitch angle adjustment in the vertical direction; the data monitoring system includes a first density meter, a second density meter, a pressure meter, a flow meter, a viscometer, an optical fiber sensor and a microseismic pickup instrument. The first density meter and the second density meter are respectively connected to the first mixing tank and the second mixing tank. The optical fiber sensor is located in the borehole and is staggered with the intelligent universal nozzle, and is isolated from grouting interference by a fixing device.

[0027] The above-mentioned adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures, the microseismic pickup instrument is buried in the stratum and distributed in an elliptical shape on the surface above the working face; the data acquisition and processing module includes a fiber optic demodulator and a microseismic data acquisition station, and the fiber optic demodulator is connected to the fiber optic sensor through an optical cable.

[0028] The above-mentioned adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures, the adaptive control module includes a central control unit, and the central control unit contains an analysis and feedback module. The received data is inverted through the analysis and feedback module to obtain the mining-induced fissure position, fissure opening, and grouting pressure, and the grouting pressure and material ratio are adjusted in real time according to the data fed back during the grouting process.

[0029] The above-mentioned adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures, the boreholes are arranged in a hexagonal shape, the optical fiber sensor is fixed to the inner wall of the borehole by a fixing device; several intelligent universal nozzles are provided; and a nano-anti-corrosion coating is provided on the surface of the optical fiber sensor.

[0030] In the above-mentioned adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures, in step e, when there is no significant change in the grouting pressure, the grouting flow rate is reduced to 10-20% of the initial grouting flow rate, and grouting is stopped when there is no increase in the real-time opening of the fissures through continuous monitoring.

[0031] Compared with the existing technology, the present invention brings the following beneficial technical effects: The present invention provides an adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures. Based on geological data, the fracture roughness coefficient and time-dependent viscosity are introduced to quantify the flow resistance of rough fractures and the time-varying characteristics of slurry rheology. The slurry diffusion radius is further calculated, which greatly reduces the error in the calculation of the slurry diffusion radius. The microseismic travel time residual and the acoustic wave velocity field are jointly inverted by the weighted robust LM algorithm to dynamically adjust the data weights to achieve precise fracture positioning. The PID gain compensation and saturation function mechanism are used to achieve adaptive, safe and efficient grouting.

[0032] The present invention can realize automation and intelligence of grouting protection through the mutual cooperation of the grouting mechanism, the data monitoring system, the data acquisition and processing module and the adaptive control module.

[0033] The present invention adopts a three-dimensional heterogeneous staggered layout scheme of optical fiber sensors and intelligent universal nozzles to reduce the sensor signal distortion rate to below 2%. The adaptive control module can invert the received data into parameters such as the mining fracture position, fracture aperture, and grouting pressure, and can adjust the grouting pressure and material ratio in real time based on the data feedback during the grouting process.

[0034] In summary, the present invention provides an adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures, which achieves efficient and accurate plugging of mining-induced fissures under complex geological conditions through multi-source data fusion analysis and intelligent feedback closed-loop mechanism. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a schematic diagram of the grouting mechanism structure required for the present invention.

[0036] Figure 2 It is a structural diagram of the data monitoring system, data acquisition and processing module and adaptive control module of the present invention.

[0037] Figure 3 This is a schematic diagram of the arrangement of the optical fiber sensor of the present invention.

[0038] Figure 4 Schematic diagram of the spatial arrangement of the grouting pipe and optical fiber in the borehole.

[0039] Figure 5 Flow chart of the method of the present invention.

[0040] In the figure: 1-upper aquiclude, 2-aquifer, 3-water-conducting fracture zone, 4-coal seam, 5-silo, 6-water tank, 7-first mixing tank, 8-second mixing tank, 9-first density meter, 10-second density meter, 11-first grouting pump, 12-second grouting pump, 13-first regulating valve, 14-second regulating valve, 15-mixing tank, 16-water glass solution storage tank, 17-third regulating valve, 18-fourth regulating valve, 19-intelligent grouting pipeline, 20- The third grouting pump, 21-pressure gauge, 22-flow meter, 23-viscometer, 24-pipeline regulating valve, 25-fiber optic demodulator, 26-central control unit, 27-microseismic data acquisition station, 28-cable, 29-microseismic pickup, 30-drilling, 31-triangular plug, 32-intelligent universal nozzle, 33-micro servo motor, 34-fiber optic sensor, 35-fixing device, 36-grouting pipe, 37-optical cable, 38-external thread, 39-stop line. DETAILED DESCRIPTION

[0041] The present invention proposes an adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures. In order to make the advantages and technical solutions of the present invention clearer and more specific, the present invention is further described below in conjunction with specific embodiments.

[0042] In the description of this application, words such as "first" and "second" are used only to distinguish different objects and do not limit the quantity or execution order. In addition, words such as "first" and "second" do not necessarily mean different. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions.

[0043] Combine Figures 1 to 4As shown, the grouting system used in the present invention includes a grouting mechanism, a data monitoring system, a data acquisition and processing module, and an adaptive control module. The grouting mechanism can automatically perform grouting operations on the target rock layer; the data monitoring system can obtain real-time information about changes in the strata and fractures during the mining process, as well as the grouting status, and transmit this information to the ground data acquisition and processing module; the data acquisition and processing module can transmit the received data to the adaptive control module after preliminary processing; the adaptive control module has built-in analysis and feedback functions, and can invert parameters such as the mining fracture location, fracture aperture, and grouting pressure based on the received data. It can also adjust the grouting pressure and material ratio in real time based on the data fed back during the grouting process.

[0044] like Figure 1 As shown in the figure, an upper aquiclude 1, an aquifer 2, a water-conducting fracture zone 3, a coal seam 4, and a stop-production line 39 are shown. The grouting mechanism includes a silo 5, a water tank 6, a first mixing tank 7, a second mixing tank 8, a first grouting pump 11, a second grouting pump 12, a third grouting pump 20, a first regulating valve 13, a second regulating valve 14, a third regulating valve 17, a fourth regulating valve 18, a mixing tank 15, a water glass solution storage tank 16, an intelligent grouting pipeline 19, a pipeline regulating valve 24 and a grouting pipe 36.

[0045] The raw materials required for grouting are first stirred in the first and second mixing tanks to form slurries of different concentrations. The first and second grouting pumps 11 and 12 then transport the slurries via pipelines to the mixing tank 15. The slurry flowing from the mixing tank 15 is mixed with the solution from the water glass solution storage tank 16 and then injected into the target fissures via the intelligent grouting pipeline 19 by the third grouting pump 20. The connecting pipelines between the mixing tank and the first and second mixing tanks are equipped with first, second, third, and fourth regulating valves 13, 14, 17, and 18, each containing an intelligent control module, to control the slurry ratio. The pipeline regulating valve 24 on the intelligent grouting pipeline is used to adjust the slurry flow rate in each grouting pipe. External threads 38 connect the intelligent grouting pipeline to the grouting pipe. The grouting pipe 36 is equipped with a triangular plug 31 and an intelligent universal nozzle 32. The triangular plug seals the slurry, while the intelligent universal nozzle 32 is arranged in a triangular pattern to avoid blind spots in the grouting process, which can lead to substandard grouting results. The mixing tank is equipped with an agitator and concentration monitor to control the slurry's desired concentration. The grouting pipe 36 is designed with multiple rows of intelligent universal nozzles 32. These nozzles, equipped with a built-in micro-servo motor 33 and a high-precision angle sensor, enable 360° horizontal rotation and ±50° vertical pitch adjustment. The nozzles open and close with millisecond-level response via a piezoelectric ceramic actuator.

[0046] The data monitoring system includes a first density meter 9, a second density meter 10, a pressure meter 21, a flow meter 22, a viscometer 23, an optical fiber sensor 34 and a microseismic seismometer 29; the first density meter 9 and the second density meter 10 are respectively connected to the first mixing tank 7 and the second mixing tank 8 to monitor the slurry concentration output by them; the pressure meter 21, the flow meter 22 and the viscometer 23 are located between the third grouting pump 20 and the intelligent grouting pipeline 19, and are used to monitor the grouting pressure, flow and viscosity respectively; the optical fiber sensor 34 is located in the borehole 30 and is staggered with the intelligent universal nozzle, and is isolated from grouting interference by a fixing device 35; the microseismic seismometer 29 is buried in the stratum and distributed in an elliptical shape on the surface above the working face to avoid ground noise and accurately capture changes in rock stratum stress.

[0047] Furthermore, the fixture body comprises a metal indexing ring base with slots spaced 120 degrees apart to secure the fiber optic sensor. An electro-hydraulic servo-driven anchor claws keep the sensor in close contact with the borehole wall. A buffer layer absorbs vibration energy between the sensor and the fixture. The outer layer is protected by a fluororubber seal and epoxy resin injection, creating a dual barrier for water and corrosion resistance. The data acquisition and processing module includes a fiber optic demodulator 25 and a microseismic data acquisition station 27. The fiber optic demodulator 25 is connected to the fiber optic sensor via an optical cable 37, transmitting the optical signal to the central control unit 26 after photoelectric conversion. The microseismic data acquisition station 27 collects and stores analog signals from the microseismic pickup 29 via cable 28, filtering, noise reduction, and analog-to-digital conversion before uploading them to the control center.

[0048] The adaptive control module includes a central control unit, which contains an analysis and feedback module. The analysis and feedback module inverts the received data into the mining crack position, crack opening, and grouting pressure, and adjusts the grouting pressure and material ratio in real time based on the data fed back during the grouting process.

[0049] The following is a detailed description of the adaptive grouting control and plugging method based on real-time monitoring of mining cracks. Figure 5 As shown, the specific steps include: Step 1. After collecting and studying the geological data of the mining area and its surrounding areas, use microseismic, geological radar, remote sensing and other monitoring technologies to scan the strata to obtain the lithology, geological structure, and ground stress of the strata, determine the aperture of the original fracture and the location of the aquifer, and integrate the information to prepare a geological exploration report, thereby providing a scientific basis for the subsequent layout of fracture monitoring equipment.

[0050] Step 2: Calculate the slurry diffusion radius using formula (1).

[0051] (1).

[0052] In formula (1): R is the slurry diffusion radius; P maxis the maximum grouting pressure; t is the slurry diffusion time; σ t is the tensile strength of the rock mass; τ0 is the yield stress; μ is the plastic viscosity; ω0 is the crack opening.

[0053] Furthermore, since the actual crack wall is not smooth and the roughness will increase the flow resistance, the crack roughness coefficient C is introduced. r , corrected effective crack opening .

[0054] Furthermore, since the slurry viscosity increases with the hydration reaction, which affects the diffusion process, the time-dependent viscosity is introduced. , which indicates that the viscosity changes with time.

[0055] Therefore, the final calculation formula for the slurry diffusion radius is as shown in formula (2).

[0056] (2).

[0057] In formula (2), P is the grouting pressure; t is the slurry diffusion time; σ t is the tensile strength of the rock mass; τ0 is the yield stress; μ(t) is the time-dependent viscosity; ω eff is the effective crack opening.

[0058] Step 3: Based on the previous geological survey results and the maximum diffusion radius of the slurry, the surface interval above the target layer is 0.85 times R max Boreholes 30 are drilled underground to the water-conducting fracture zone, arranged in a hexagonal pattern. Fiber optic sensors 34 and grouting pipes 36 are placed at different levels within the same borehole. During drilling, fiber optic sensors 34 are secured to the borehole wall with a fixture, maintaining a vertical distance of 1.5 times the borehole diameter from the grouting pipe. Physical isolation and electromagnetic shielding are employed to prevent signal distortion during the grouting process. Microseismic sensors 29 are arranged in an elliptical pattern along the periphery of the working face. The sensors are embedded in stable rock formations deep within the formation, maintaining a minimum vertical distance of 15 meters from the surface to avoid interference from ground construction vibrations.

[0059] Furthermore, the grouting pipe 36 is designed with multiple rows of grouting nozzles at different levels. The nozzle is an intelligent universal nozzle 32 with a built-in micro servo motor 33 and a high-precision angle sensor, which can achieve 360° omnidirectional rotation in the horizontal plane and ±50° pitch angle adjustment in the vertical direction. The opening and closing of the nozzle is achieved with millisecond-level response through a piezoelectric ceramic actuator.

[0060] Furthermore, the fiber optic sensor 34 and the intelligent universal nozzle 32 are arranged in a stereoscopic, staggered configuration and fixed to the borehole wall in a 120-degree equiangular ring. They are reinforced with a fixing device and a shock-absorbing buffer layer. The sensor assembly is coated with a nano-anti-corrosion coating, and the axial spacing between it and the grouting nozzle maintains a vertical safety distance of 1.5 times the borehole diameter.

[0061] Furthermore, the optical fiber sensor 34 is specifically a distributed acoustic fiber sensor (DAS), a distributed temperature fiber sensor (DTS) and a Bragg grating strain sensor (FBG), which are integrated together in an armored manner.

[0062] Step 4: Complete the system assembly.

[0063] Step 5: Set the initial grouting pressure P0 and the maximum grouting pressure P max and the initial concentration of slurry C0, where P0=σ t +σ v , P max =σ t +σ h , where σ v is the vertical stress, σ h The fiber optic demodulator 25 and microseismic data acquisition station 27 preprocess the received data by removing noise interference and outliers through multi-stage signal processing chain wavelet threshold denoising algorithm, time-frequency domain feature classification technology, and STA / LTA methods.

[0064] Step 6: The pre-processed structured data is transmitted to the central control unit 26 via industrial Ethernet. Multi-dimensional fracture characteristic parameters such as fracture position and fracture aperture are obtained through the multi-physics field coupling inversion algorithm, and a three-dimensional fracture network topology model is simultaneously constructed for grouting strategy optimization.

[0065] The location of mining-induced fractures is located by joint inversion of microseismic monitoring data and fiber optic acoustic wave velocity field. The specific calculation method is as follows.

[0066] (1) Calculation of microseismic travel time residuals.

[0067] (3).

[0068] Where: is the theoretical travel time (calculated value) of the i-th station; x, y, z are the three-dimensional coordinates of the earthquake source (crack); x i ,y i , z i is the three-dimensional coordinate of the i-th microseismic sensor; v p is the propagation velocity of P waves in the rock mass; t0 is the time when the microseismic event occurs.

[0069] (2) Acoustic wave velocity field modeling.

[0070] (4).

[0071] Where: is the calculated value of the acoustic velocity at the jth optical fiber measurement position; v0 is the acoustic velocity of the intact rock mass; k is the fracture damage coefficient; L is the fracture influence radius.

[0072] (3) Velocity gradient regularization.

[0073] (5).

[0074] (4) Joint inversion of microseismic travel time residuals and acoustic wave velocity field to determine the target fracture location.

[0075] (6).

[0076] Where: F(x) is the joint objective function (the residual function to be minimized); α, β, γ are weight coefficients (balancing microseismic and acoustic wave data with model smoothness); is the observed travel time of the i-th microseismic sensor; (x) is the theoretical travel time of the i-th microseismic sensor (depending on the crack position x); is the standard deviation of microseismic travel time data; is the measured velocity value of the j-th optical fiber measurement position; (x) is the calculated value of the acoustic wave velocity at the jth optical fiber measurement position; Standard deviation of the sound velocity data; is the gradient of the acoustic wave velocity field.

[0077] The mining-induced fracture aperture is inverted through optical fiber strain and temperature compensation, and the specific calculation is as follows.

[0078] (7).

[0079] Where: E is the elastic modulus of the rock mass; ε(x) is the distributed strain measured by the optical fiber (strain distribution along the optical fiber length x); ΔT is the temperature change (relative to the reference temperature); λ is the thermal expansion coefficient of the rock mass; and L is the length of the fracture affected zone.

[0080] Step 7: Based on the improved weighted robust LM algorithm and Huber loss function, different weights are assigned to the monitoring data and dynamically adjusted to reduce the impact of abnormal data, thereby further accurately optimizing the crack location.

[0081] (1) Define the robust loss function—Huber loss function.

[0082] (8).

[0083] Where: ρ(r) is the robust loss function; c is the residual threshold, c = 1.345σ (σ is the standard deviation of the residual of the current iteration, covering 95% of the normally distributed data).

[0084] (2) Dynamically adjust the weight coefficient.

[0085] (9).

[0086] (10).

[0087] (11).

[0088] Where: η ms , η ac is the microseismic / acoustic data anomaly index (η+1 when the residual exceeds 3σ), which can automatically reduce the weight when the data is abnormal to improve robustness; N, M are the number of microseismic stations and acoustic wave measurement points; N valid , M valid is the number of effective microseismic events and the number of effective acoustic wave measurement points; I(•) is the indicator function (abnormal data judgment), 1 is abnormal, 0 is normal; ω ms ,ω ac is the benchmark weight of microseismic / acoustic wave data (percentage of valid data); is the maximum norm of the velocity field gradient.

[0089] (3) Use the weighted robust LM algorithm to iterate the equation.

[0090] (12).

[0091] Where: J is the Jacobian matrix (including microseismic and acoustic wave partial derivatives); W is the diagonal weight matrix; λ is the adaptive damping factor (initial value 0.1, dynamically adjusted during iteration); r is the residual vector.

[0092] (13).

[0093] (14).

[0094] (15).

[0095] The final crack target position calculation formula is as follows.

[0096] (16).

[0097] Step 8: The adaptive control module adjusts the grouting pressure and slurry concentration in real time according to the inverted fracture position, fracture aperture and slurry filling rate, and sends a grouting instruction to the grouting mechanism. The specific steps are as follows.

[0098] (1) According to the target crack position, the angle of the intelligent universal nozzle is adjusted, and grouting is performed with the initial grouting pressure P0 and the initial slurry concentration C0. The grouting pressure is gradually increased to perform splitting grouting, forming a unidirectional crack from the nozzle to the mining crack.

[0099] (2) When the slurry reaches the mining fracture position, the grouting pressure and slurry concentration are adjusted in real time according to the mining fracture opening and slurry filling rate. The specific formula is as follows.

[0100] (17).

[0101] Where: P(t) is the real-time grouting pressure; ΔP flow is the flow resistance; K p is the PID control gain of the filling rate deviation (MPa / %); η target is the target filling rate, which is 95%; η(t) is the real-time filling rate; sat is the saturation function (limiting the adjustment range); K ω is the crack opening compensation gain (MPa / mm); ω crit is the critical opening threshold; ω(t) is the real-time crack opening; ReLU(ω crit -ω(t)) is the rectified linear unit function, ReLU(ω crit -ω(t))=max[0,(ω crit -ω(t))].

[0102] Furthermore, the saturation function is:

[0103] (18).

[0104] The slurry concentration is achieved by adjusting the water-cement ratio in real time. The specific dynamic adjustment method is shown in the following formula.

[0105] (19).

[0106] Where: C(t) is the real-time slurry concentration; C base is the water-cement ratio benchmark value, which is 0.8:1; ω ref is the reference opening, which is 1mm; a is the opening influence index (usually a=2, the larger the opening, the higher the concentration); b is the weight coefficient of the filling rate change rate; tanh is the limit function that limits the concentration adjustment range; k is the fill rate change rate sensitivity coefficient; dη / dt is the real-time change rate of the fill rate.

[0107] Furthermore, the slurry can be quickly solidified by adjusting the ratio of the water glass solution.

[0108] (3) When there is no significant change in the grouting pressure, the grouting flow rate Q(t) drops to 10%~20% of the initial flow rate, and the real-time crack opening ω(t) is continuously monitored and shows no increase, stop grouting and flush the pipeline with clean water to prevent the slurry from solidifying and clogging the pipeline.

[0109] Furthermore, if the pressure exceeds P max If the phenomenon lasts for 10 seconds or the filling efficiency drops suddenly (e.g., drops by more than 5% within 1 minute), the machine should be shut down immediately and the grouting mechanism should be checked.

[0110] In summary, the present invention uses multi-source data fusion technology to monitor the dynamics of cracks in real time, and combines intelligent algorithms to dynamically optimize grouting parameters, effectively overcoming complex geological interference, reducing slurry waste, improving grouting efficiency and quality, and achieving precise sealing of mining-induced cracks.

[0111] Parts not described in the present invention can be implemented by referring to the existing technology.

[0112] Those skilled in the art should recognize that the above embodiments are merely intended to illustrate the present application and are not intended to limit the present application. As long as they are within the spirit of the present application, appropriate changes and modifications to the above embodiments are within the scope of protection claimed in the present application.

Claims

1. An adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures, wherein the grouting system used comprises a grouting mechanism, a data monitoring system, a data acquisition and processing module, and an adaptive control module, characterized in that: The method comprises the following steps: a. Collect geological data from the mining area and its surrounding areas to provide a basis for fracture monitoring. The geological data include: stratum lithology, geological structure, geostress, primary fracture aperture and aquifer location; b. Based on the geological data, the fracture roughness coefficient and time-dependent viscosity are introduced to quantify the flow resistance of the rough fracture and the time-varying rheological characteristics of the slurry, and the slurry diffusion radius R(t) is calculated according to formula (1); In formula (1), P is the grouting pressure; t is the slurry diffusion time; σ t is the tensile strength of the rock mass; τ0 is the yield stress; μ(t) is the time-dependent viscosity; ω eff is the effective crack opening; c. Install the grouting system and set the initial grouting pressure P0 and the maximum grouting pressure P max and the initial slurry concentration C0; the received data is preprocessed by the data acquisition and processing module; the obtained data is transmitted to the adaptive control module, and the multi-dimensional fracture characteristic parameter data of the fracture position and fracture opening are obtained through the multi-physics field coupling inversion algorithm, and a three-dimensional fracture network topology model is simultaneously constructed for grouting strategy optimization; d. Based on the weighted robust LM algorithm and Huber loss function, different weights are assigned to the multi-dimensional crack characteristic parameter data and dynamically adjusted to reduce the impact of abnormal data, thereby further accurately optimizing the crack location; e. The adaptive control module adjusts the grouting pressure and slurry concentration in real time according to the obtained fracture position, fracture aperture and slurry filling rate, and sends a grouting instruction to the grouting mechanism to inject grout into the fracture; In step c, the crack position is obtained by multi-physics field coupling inversion algorithm using formula (2): In formula (2), F(x) is the joint objective function; α, β, and γ are the weight coefficients for balancing microseismic, acoustic wave data, and model smoothness, respectively; is the observed travel time of the i-th microseismic sensor; is the theoretical travel time of the i-th microseismic sensor; σ ms is the standard deviation of microseismic travel time data; σ as is the standard deviation of the fiber speed data; is the measured value of the acoustic wave velocity at the j-th optical fiber measurement position; is the calculated value of the acoustic wave velocity at the jth optical fiber measurement position; ρ is the robust loss function; i is the i-th microseismic sensor; N is the total number of microseismic sensors; M is the total number of optical fiber sensor measurement positions; is the gradient of the acoustic wave velocity field; The crack aperture is obtained by inversion of optical fiber strain and temperature compensation. The specific formula is shown in formula (3): In formula (3), ω is the crack opening; E is the elastic modulus of the rock mass; ε(x) is the distributed strain measured by the optical fiber; ΔT is the temperature change; λ is the thermal expansion coefficient of the rock mass; L is the length of the crack influence zone; In step e, the grouting pressure is adjusted according to formula (4): In formula (4): P(t) is the real-time grouting pressure; P0 is the initial grouting pressure; ΔP flow is the flow resistance; K p is the PID control gain of the filling rate deviation; η target is the target filling rate; η(t) is the real-time filling rate; sat is the saturation function; K ω is the crack opening compensation gain; ω crit is the critical opening threshold; ω(t) is the real-time crack opening; ReLU(ω crit -ω(t)) is the rectified linear unit function, ReLU(ω crit -ω(t))=max[0,(ω crit -ω(t))]; The slurry concentration is adjusted according to formula (5): In formula (5): C(t) is the real-time slurry concentration; C base is the water-cement ratio reference value; ω ref is the reference opening; a is the opening influence index; b is the filling rate change rate weight coefficient; tanh is the limit function limiting the concentration adjustment range; k is the filling rate change rate sensitivity coefficient; dη / dt is the real-time filling rate change rate.

2. The adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures according to claim 1 is characterized by: The grouting mechanism mainly includes a silo, a water tank, a first stirring tank, a second stirring tank, a mixing tank, a grouting pipe and a water glass solution storage tank; the first stirring tank and the second stirring tank are used for stirring and processing to form slurries of different concentrations; the mixing tank is provided with an agitator and a concentration monitor to control and prepare the slurry of the required concentration.

3. The adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures according to claim 2 is characterized by: The grouting pipe is provided with a triangular plug and an intelligent universal nozzle. The triangular plug is used to seal the slurry. The intelligent universal nozzle is arranged in a triangle. A micro servo motor and an angle sensor are provided in the intelligent universal nozzle to achieve 360° omnidirectional rotation in the horizontal plane and ±50° pitch angle adjustment in the vertical direction. The data monitoring system includes a first density meter, a second density meter, a pressure meter, a flow meter, a viscometer, an optical fiber sensor and a microseismic pickup instrument. The first density meter and the second density meter are connected to the first mixing tank and the second mixing tank respectively. The optical fiber sensor is located in the borehole and is staggered with the intelligent universal nozzle, and is isolated from grouting interference by a fixing device.

4. The adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures according to claim 3 is characterized by: The microseismic pickup instrument is buried in the stratum and distributed in an elliptical shape on the surface above the working face; the data acquisition and processing module includes a fiber optic demodulator and a microseismic data acquisition station, and the fiber optic demodulator is connected to the fiber optic sensor via an optical cable; the borehole is arranged in a hexagonal shape, and the fiber optic sensor is fixed to the inner wall of the borehole by a fixing device; a number of intelligent universal nozzles are provided; and a nano-anti-corrosion coating is provided on the surface of the fiber optic sensor.

5. The adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures according to claim 4 is characterized in that: The adaptive control module includes a central control unit, which contains an analysis and feedback module. The analysis and feedback module inverts the received data into the mining crack position, crack opening, and grouting pressure, and adjusts the grouting pressure and material ratio in real time based on the data fed back during the grouting process.

6. The adaptive grouting control and plugging method based on real-time monitoring of mining-induced fissures according to claim 1 is characterized by: In step e, when there is no significant change in the grouting pressure, the grouting flow rate is reduced to 10-20% of the initial grouting flow rate, and the grouting is stopped when there is no increase in the real-time crack opening through continuous monitoring.

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