Tunnel water-rich sand layer tunnel hole intelligent control grouting grouting system

Abstract

This application relates to the field of tunnel engineering and discloses an intelligent grouting control system for water-rich sandy tunnels, belonging to the field of tunnel construction technology. The system includes a global perception module, a multi-source information fusion module, a collaborative control decision-making module, an execution drive module, and a closed-loop optimization module. The global perception module is used to synchronously acquire drilling rig status, grouting parameters, and formation response data; the multi-source information fusion module achieves time alignment of multi-source heterogeneous data through a unified clock source and calculates key features such as the drilling-grouting efficiency ratio and dynamic pressure gradient; the collaborative control decision-making module evaluates the grouting situation based on feature parameters and automatically selects one of the following modes—drilling-grouting master-slave collaboration, safety-priority collaboration, and global optimization collaboration—to generate a target control quantity; the execution drive module converts the control quantity into instructions to adjust hardware actions; and the closed-loop optimization module dynamically updates the adaptive filling coefficient based on the actual grouting effect deviation.

Description

Technical Field

[0001] This invention relates to the field of tunnel engineering technology, specifically to an intelligent controlled grouting system for water-rich sandy tunnels. Background Technology

[0002] In the construction of tunnels in water-rich sandy layers, grouting is a core method for reinforcing the strata and controlling soil erosion. However, current grouting operations mostly rely on manual experience or single parameter control, with a low level of intelligence, making it difficult to cope with complex and ever-changing underground environments.

[0003] First, the grouting process involves multiple physical quantities, including drilling rig mechanical actions, grout fluid transmission, and formation mechanical responses. In existing construction monitoring systems, different devices use independent controllers and different communication protocols, resulting in indeterminate data transmission delays. The lack of a unified time reference leads to temporal misalignment between drilling parameters, grouting parameters, and environmental monitoring data. This prevents the system from accurately reconstructing the causal relationship between drilling and grouting actions and formation feedback, reducing the reliability of data fusion analysis.

[0004] Secondly, existing control logic often treats drilling and grouting as independent processes, with adjustments to grouting parameters typically lagging behind changes in drilling conditions. Traditional pressure or flow rate threshold control methods struggle to identify dynamic conditions such as mismatches between grouting volume and borehole volume, or sudden abnormal pressure fluctuations. Due to a lack of quantitative perception of the coordinated drilling and grouting situation, the system cannot provide targeted, tiered intervention measures when facing complex conditions, easily leading to formation fracturing, grouting pipeline blockage, or insufficient grout filling, making it difficult to balance construction efficiency and formation safety.

[0005] Finally, the heterogeneity of geological conditions causes the response characteristics of the grouting system to be time-varying. Existing systems mostly use preset fixed parameters and lack effective feedback adjustment mechanisms. Because the control model cannot be dynamically corrected based on the actual deformation feedback of the strata, the system struggles to eliminate the deviation between the actual grouting effect and the expected target, resulting in the control accuracy of tunnel lining deformation and surface settlement failing to meet the stringent requirements of micro-disturbance construction. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides an intelligent grouting control system for tunnels in water-rich sand layers. This system solves the problems of decoupling grouting parameters from drilling status, inconsistent timing of multi-source heterogeneous data, and the inability of the system to adaptively adjust the grouting strategy based on the real-time response of the strata in existing technologies.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] The first aspect of this invention provides an intelligent controlled grouting system for tunnels in water-rich sand layers. This system includes a global perception module, a multi-source information fusion module, a collaborative control decision-making module, an execution drive module, and a closed-loop optimization module. Data connections and signal transmission channels are established between these modules.

[0009] The comprehensive sensing module is configured at the grouting operation site to acquire raw physical quantities reflecting the grouting process and the ground response. Specifically, the comprehensive sensing module includes: a drilling rig status monitoring unit for acquiring drill rod torque, drilling speed, drilling feed pressure, and drilling rate; a grouting parameter monitoring unit for acquiring real-time grouting pressure, real-time grouting flow rate, and grout density; and a ground environment response monitoring unit for acquiring minute deformations of the tunnel lining, ground pore water pressure, and surrounding soil stress.

[0010] The multi-source information fusion module is connected to the global perception module and is used to receive and process the raw physical quantities. The multi-source information fusion module is equipped with a clock synchronization unit, which uses a high-precision crystal oscillator as a unified clock source and is configured to mark all channel data of the global perception module with a unified timestamp at the time of data acquisition, in order to construct a global state vector with time consistency. The multi-source information fusion module is also equipped with a feature calculation unit, used to calculate key feature parameters based on the time-aligned data. These key feature parameters include at least the drilling-injection efficiency ratio, which characterizes the degree of matching between the grouting volume and the void volume generated in the borehole, and the pressure dynamic gradient, which characterizes the instantaneous change trend of the grouting pressure.

[0011] The collaborative control decision module is connected to the multi-source information fusion module and is used to evaluate the grouting situation and generate target control quantities based on the key feature parameters. The collaborative control decision module has three preset situational state spaces: steady-state grouting zone, risk warning zone, and emergency avoidance zone, as well as corresponding drilling-grouting master-slave collaborative mode, safety-priority collaborative mode, and global optimization collaborative mode.

[0012] The execution drive module is connected to the collaborative control decision module and includes a grouting pump controller and a drilling rig controller, used to convert the target control quantity into drive commands to adjust the actions of the hardware equipment.

[0013] The closed-loop optimization module is connected to the execution drive module and the global perception module respectively, and is used to dynamically adjust the adaptive filling coefficient in the collaborative control decision module according to the deviation between the actual grouting effect and the expected effect.

[0014] The second aspect of this invention provides a method for intelligent control grouting inside a tunnel with water-rich sand layers. This method relies on the aforementioned grouting system and achieves precise control of micro-disturbances in the grouting process through a logical closed loop of holistic perception, multi-level information fusion, multi-mode collaborative decision-making, execution-driven mechanisms, and closed-loop optimization. Specifically, the method includes the following steps:

[0015] Step S100: Construct a global dynamic perception and time synchronization mechanism

[0016] The global perception module synchronously collects drilling rig operation status data, grouting process data, and formation environment response data. Through the clock synchronization unit in the multi-source information fusion module, the collected data is time-axis aligned based on a unified clock source, eliminating timing errors caused by transmission delays. The drilling rig operation status, grouting process status, and formation environment response data are then stitched together to construct a system global state vector with strict time consistency.

[0017] Step S200: Perform multi-level information fusion and situation assessment

[0018] The multi-source information fusion module is used to perform feature-level fusion calculation on the global state vector of the system to obtain key feature parameters and evaluate the grouting status accordingly.

[0019] The specific feature calculation logic is as follows:

[0020] Calculate the drilling-grouting efficiency ratio: compare the product of the pre-treated grouting flow rate and the drilling rate and borehole cross-sectional area. This parameter is used to quantitatively describe the matching relationship between the grouting rate and the borehole new volume generation rate.

[0021] Calculate the dynamic gradient of pressure: Calculate the differential rate of change of grouting pressure based on the sampling time window. This parameter is used to capture the instantaneous fluctuation trend of pressure within a small time window.

[0022] Based on the aforementioned key characteristic parameters and formation environment response data, the system divides the current working condition into a steady-state grouting zone, a risk warning zone, or an emergency avoidance zone according to preset logical rules.

[0023] Step S300: Make multi-mode intelligent collaborative control decisions

[0024] Based on the situation assessment results, the collaborative control decision module selects one of the multiple control modes to activate and calculates the target control quantity.

[0025] When the operating condition is determined to be in the steady-state grouting zone, the drilling-grouting master-slave coordinated mode is activated. This mode follows the principle of "drilling-determined grouting," using the real-time drilling rate of the drilling rig as the master variable and the grouting flow rate as the slave variable. The system calculates the target grouting flow rate based on the drilling rate, borehole cross-sectional area, grout shrinkage compensation coefficient, and dynamically updated adaptive filling coefficient, and controls the grouting pump to track the flow rate.

[0026] When the working condition is determined to be in a risk warning zone or emergency avoidance zone, the safety priority coordination mode is activated. This mode performs graded responses based on the dynamic pressure gradient and the severity of formation deformation: under the first-level response, the drilling rate is kept constant and the grouting flow rate is reduced; under the second-level response, both the grouting flow rate and drilling rate are reduced; under the third-level response, the target values ​​of flow rate and drilling rate are set to zero and pressure relief operations are triggered to ensure the safety of the formation and structure.

[0027] When operating in a multi-hole synchronous operation scenario, the global optimization collaborative mode is activated. This mode establishes an optimization objective function with the goal of minimizing the weighted sum of the difference between the actual deformation and the target deformation at each monitoring point, and introduces grouting pressure as a constraint condition, to solve for the optimal flow rate quota for each grouting hole.

[0028] Step S400: Execute control commands

[0029] The execution drive module receives the target control quantity, converts it into a specific hardware drive signal, and adjusts the speed of the grouting pump motor and the valve opening of the drilling rig hydraulic system, thereby realizing real-time intervention in the grouting process at the physical level.

[0030] Step S500: Implement closed-loop optimization and adaptive adjustment

[0031] The closed-loop optimization module is used to monitor the actual deformation response of the formation to the grouting operation in real time, and calculate the grouting effect deviation between the actual deformation value and the expected deformation value. Based on this deviation, the system uses an iterative algorithm to correct the adaptive filling coefficient in the drilling-grouting master-slave collaborative mode online. The updated coefficient is used for the control decision calculation in the next moment, thereby giving the system the ability to continuously learn and adapt to changes in geological conditions.

[0032] This invention provides an intelligent controlled grouting system for tunnels in water-rich sand layers. It offers the following advantages:

[0033] 1. This invention solves the problem of data timing misalignment caused by transmission delays in heterogeneous controllers of drilling rigs, grouting pumps, and environmental monitoring equipment by configuring a clock synchronization unit based on a unified clock source in the multi-source information fusion module. This mechanism can mark all channel data with a unified millisecond-level timestamp, ensuring strict alignment of drilling actions, grout flow characteristics, and formation response data in the time dimension, thereby eliminating phase lag in the data fusion process and providing a reliable data foundation for subsequent accurate calculation of key coupling characteristics such as the drilling-grouting efficiency ratio.

[0034] 2. This invention utilizes the drilling-to-grouting efficiency ratio and dynamic pressure gradient as the basis for situation assessment, constructing a multi-mode control strategy that includes drilling-to-grouting master-slave coordination, safety-priority coordination, and global optimization coordination. Under steady-state conditions, the system adheres to the principle of drilling-based grouting, ensuring precise matching between the grout injection volume and the borehole cutting volume, preventing cavities caused by insufficient grouting or fracturing caused by excessive grouting. When detecting sudden pressure changes or abnormal formation deformation, the system can automatically switch to a graded response safety mode for intervention, effectively balancing the grouting filling quality with the safety of the construction process.

[0035] 3. This invention incorporates a closed-loop optimization module, which iteratively updates the adaptive filling coefficient in the control model online based on the deviation between the actual deformation response of the strata to the grouting operation and the expected target. This dynamic adjustment mechanism reduces the system's reliance on preset parameters and human experience, enabling it to adapt to the variability of water-rich sandy geological conditions. By continuously refining the control strategy, it achieves precise control over micro-disturbances in tunnel lining deformation and surface settlement. Attached Figure Description

[0036] Figure 1 This is a structural diagram of the present invention;

[0037] Figure 2 This is a flowchart of the present invention.

[0038] Among them, 100 is the global perception module; 110 is the drilling rig status monitoring unit; 120 is the grouting parameter monitoring unit; 130 is the formation environment response monitoring unit; 200 is the multi-source information fusion module; 300 is the collaborative control decision module; 400 is the execution drive module; 410 is the grouting pump controller; 420 is the drilling rig controller; and 500 is the closed-loop optimization module. Detailed Implementation

[0039] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] Example:

[0041] Please see the appendix Figure 1 This invention provides an intelligent grouting system for water-rich sandy tunnels. The system includes a global sensing module 100, a multi-source information fusion module 200, a collaborative control decision-making module 300, an execution drive module 400, and a closed-loop optimization module 500. These modules establish data connections and signal transmission channels via industrial fieldbus or Ethernet.

[0042] The global sensing module 100 is configured at the grouting operation site to acquire raw physical quantities reflecting the grouting process and the ground response. Specifically, the global sensing module 100 includes a drilling rig status monitoring unit 110, a grouting parameter monitoring unit 120, and a ground environment response monitoring unit 130. The drilling rig status monitoring unit 110 is installed at the drilling rig's power head and propulsion mechanism, and is equipped with a torque sensor for acquiring drill rod torque, a speed sensor for acquiring drilling speed, a pressure sensor for acquiring feed pressure, and a displacement sensor for acquiring drilling rate. The grouting parameter monitoring unit 120 is installed at the grouting pipeline and pump body, and is equipped with a pressure transmitter for acquiring real-time grouting pressure, an electromagnetic flowmeter for acquiring grouting flow rate, and a density meter for acquiring grout density. The ground environment response monitoring unit 130 is deployed in the tunnel lining and surrounding soil, and is equipped with a laser displacement gauge for acquiring minute deformations of the lining, a piezometer for acquiring pore water pressure in the ground, and an earth pressure cell for acquiring soil stress.

[0043] The multi-source information fusion module 200 is connected to the global sensing module 100 and is used to receive and process raw physical quantity data. The multi-source information fusion module 200 is internally equipped with a clock synchronization unit, which uses a unified clock source to timestamp all sensor data at the millisecond level to achieve time alignment of multi-source heterogeneous data. The multi-source information fusion module 200 is also equipped with a feature calculation unit, used to calculate key feature parameters based on the time-aligned data. These key feature parameters include the drilling-to-grouting efficiency ratio, which characterizes the degree of matching between the grouting volume and the borehole volume. ) and the dynamic pressure gradient characterizing the instantaneous change trend of grouting pressure ( ).

[0044] The collaborative control decision module 300 is connected to the multi-source information fusion module 200 and is used to assess the current grouting situation based on key characteristic parameters and generate control commands. The collaborative control decision module 300 has three preset situational states: a steady-state grouting zone, a risk warning zone, and an emergency avoidance zone, as well as three corresponding control mode logics. The three control modes include a drilling-grouting master-slave collaborative mode, a safety-priority collaborative mode, and a global optimization collaborative mode. Based on the input drilling-grouting efficiency ratio and pressure dynamic gradient value, the collaborative control decision module 300 determines the current situational region, selects one to activate the corresponding control mode logic, and calculates the target control quantity.

[0045] The execution drive module 400 is connected to the collaborative control decision module 300, receiving target control quantities and driving hardware device actions. The execution drive module 400 includes a grouting pump controller 410 and a drilling rig controller 420. The grouting pump controller 410 adjusts the speed of the grouting pump motor via a frequency converter to track the target grouting flow rate or pressure. The drilling rig controller 420 adjusts the drilling rig's advance and slewing speeds via hydraulic proportional valves to execute collaborative control commands.

[0046] The closed-loop optimization module 500 is connected to the execution drive module 400 and the global perception module 100 to form a feedback loop. The closed-loop optimization module 500 is used to calculate the deviation between the actual grouting effect and the expected effect, and dynamically adjust the adaptive filling coefficient in the collaborative control decision module 300 according to the deviation.

[0047] This invention also provides a method for intelligent grouting control inside tunnels with water-rich sand layers. This method relies on the aforementioned intelligent grouting control system, and achieves precise control of micro-disturbances in the grouting process through a logical closed loop of omni-channel perception, multi-level information fusion, multi-mode collaborative decision-making, execution-driven processes, and closed-loop optimization. The specific implementation steps are as follows:

[0048] Step S100: Construct a global dynamic perception and time synchronization mechanism

[0049] This step specifically involves the synchronous acquisition, signal conditioning, and vectorization of data on drilling rig operating status, grouting process parameters, and formation environment response. Its core objective is to address the issues of isolated data and temporal misalignment among subsystems in traditional grouting operations, providing a data foundation with strict temporal consistency for subsequent multi-source information fusion. The specific implementation steps can be further divided into S110 to S140.

[0050] S110: Collect drilling rig operating status data and construct drilling rig operating status vector.

[0051] The drilling rig condition monitoring unit 110 acquires mechanical motion parameters in real time through sensor arrays deployed at key parts of the drilling rig. Specifically:

[0052] The drill pipe torque is measured using a torque sensor mounted on the output shaft of the power head. ;

[0053] Drilling speed is measured using a rotary encoder or Hall sensor mounted on the end of the rotary motor. ;

[0054] Hydraulic values ​​are collected using a pressure transmitter connected to the hydraulic circuit of the propulsion cylinder, and the drilling feed pressure is calculated by converting the cylinder piston area. ;

[0055] The displacement of the power head is monitored in real time using a draw-wire displacement sensor or a laser rangefinder, and the drilling rate is obtained by differentiating the time. .

[0056] The above four physical quantities constitute the drilling rig operating state vector at time t. ,Right now:

[0057]

[0058] The specific selection and installation method of the above sensors can be chosen by those skilled in the art based on the drilling rig model and on-site working conditions. The hardware connection method is a well-known technology in this field and will not be described in detail here.

[0059] S120: Collect grouting process data and construct the grouting process state vector.

[0060] Grouting parameter monitoring unit 120 focuses on monitoring the dynamic characteristics of the fluid in the pipeline. Specifically:

[0061] A high-frequency pressure transmitter is installed near the borehole opening in the grouting pipeline (to reduce the impact of pipeline friction on the measurement results) to obtain the real-time grouting pressure. ;

[0062] An electromagnetic flow meter is installed at the outlet of the grouting pump to obtain the real-time grouting flow rate. ;

[0063] Install an online density meter (such as a Coriolis mass flow meter) at the inlet of the mixing tank or grouting pump to obtain the slurry density. .

[0064] The above three physical quantities constitute the grouting process state vector at time t. ,Right now:

[0065]

[0066] By monitoring the slurry density in real time, the system can identify fluctuations in the water-cement ratio, ensuring the consistency of the injected medium.

[0067] S130: Collect formation environmental response data and construct formation and environmental response vectors.

[0068] The formation environment response monitoring unit 130 is used to capture the impact of grouting behavior on the surrounding medium. Specifically:

[0069] Laser displacement gauges or fiber optic sensors deployed at tunnel segment joints or key structural points are used to monitor minute deformations in the tunnel lining. ;

[0070] Monitoring formation pore water pressure using pore water pressure gauges pre-embedded deep in the formation ;

[0071] Using earth pressure cells to monitor the stress in the surrounding soil .

[0072] The three physical quantities mentioned above constitute the formation and environment response vector at time t. ,Right now:

[0073]

[0074] This vector reflects the mechanical response of the formation to grouting disturbance and is an important basis for judging whether the grouting is excessive or insufficient.

[0075] S140: Perform high-precision time synchronization and global state vector construction

[0076] Given the controllers and data transmission protocols of drilling rigs, grouting pumps, and environmental monitoring equipment (such as Modbus, CAN bus, analog signal 4), Due to the discrepancy (20mA), the arrival time of the data stream at the fusion module often exhibits nondeterministic delays. To address this issue, the system configures a data acquisition card based on an FPGA or a high-real-time embedded system at the input of the multi-source information fusion module 200. This acquisition card incorporates a high-precision crystal oscillator as a unified clock source.

[0077] At the moment of data acquisition, the acquisition card immediately adds a uniform millisecond-level timestamp to the sampled data of all channels. Instead of waiting for the data to be transmitted to the host computer before timestamping, the system eliminates timing errors caused by transmission delays. Based on this unified timestamp, the system aligns and concatenates the data from the three sub-vectors at the same time t to construct the system's global state vector. :

[0078]

[0079] In the formula, This is a comprehensive state matrix at time t that includes all information related to drilling, grouting, and environmental response. This represents the transpose of a matrix. The vector... As the basic input for subsequent multi-level information fusion and situation assessment, it ensures the temporal consistency of causal logic in subsequent calculations.

[0080] Step S200: Perform multi-level information fusion and situation assessment

[0081] The system receives the raw data transmitted in step S100, filters and cleans it, and then calculates key feature parameters at the feature-level fusion level. These key feature parameters include the drilling-to-injection efficiency ratio. and pressure dynamic gradient .

[0082] Drilling efficiency ratio This is used to characterize the degree of matching between the grouting volume and the void volume generated in the borehole; its calculation formula is as follows:

[0083]

[0084] In the formula, Let be the grouting flow rate at time t. Let be the drilling rate at time t. is the cross-sectional area constant of the drill rod or borehole.

[0085] Dynamic pressure gradient : Used to quantify the instantaneous change trend of grouting pressure to identify the risk of fracturing or channel blockage, its calculation formula is:

[0086]

[0087] In the formula, The grouting pressure at the current moment, The grouting pressure at the previous sampling time. This represents the sampling time window.

[0088] Based on the aforementioned characteristic parameters, the system constructs a situation assessment function. The current working condition is divided into a steady-state grouting zone, a risk warning zone, or an emergency evacuation zone. The specific division logic is based on a preset pressure gradient threshold (…). ) and fill factor boundary ( )Sure.

[0089] Step S300: Make multi-mode intelligent collaborative control decisions

[0090] The system outputs the situation assessment results based on step S200. It automatically activates the drilling-injection master-slave collaborative mode, the safety-priority collaborative mode, or the global optimization collaborative mode, and calculates the target control quantity. .

[0091] Drilling Master-Slave Collaborative Mode (ModeA):

[0092] This mode is activated when the operating condition is determined to be in the "steady-state grouting zone". In this mode, the control logic is primarily based on the drilling status, with grouting parameters dynamically adjusted to calculate the target grouting flow rate. The formula is:

[0093]

[0094] In the formula, For adaptive fill factor, This is the slurry shrinkage compensation coefficient.

[0095] Security-first collaboration mode (ModeB):

[0096] This mode is activated when the operating condition is determined to be in the "risk warning zone" or "emergency avoidance zone." It is based on the pressure gradient. and strata deformation The severity of the risk triggers a tiered response. The system outputs target control variables based on the risk level. :

[0097]

[0098] The specific response logic is as follows:

[0099] Level 1 response: When detected When the drilling rate exceeds the warning threshold but does not reach the critical value, the system maintains the current drilling rate. Keep the flow rate unchanged and reduce it to the set value from the previous moment. of times ( ), to smooth out pressure fluctuations;

[0100] Level 2 response: When detected When the critical threshold is exceeded, the system determines that there is a risk of fracturing or severe blockage, and simultaneously reduces the grouting flow rate to [a certain value]. ( ), and reduce the drilling rate to ( (and even suspend drilling to reduce further disturbance to the formation);

[0101] Level 3 response: When formation deformation is detected. Exceeding the limit When the system triggers an emergency stop command, it sets the flow rate and drilling speed to zero (i.e., the control quantity is (0,0)) and outputs a signal to drive the electromagnetic pressure relief valve to open, releasing the pressure inside the hole and preventing damage to the lining structure.

[0102] Global Optimization Collaboration Mode (ModeC):

[0103] This mode is activated when the system is configured for multi-hole synchronous grouting operations. It establishes an objective function that minimizes the total settlement control error. :

[0104]

[0105] In the formula, The number of grouting holes for coordinated operation, For the first The weighting coefficient of each monitoring point and The first The actual deformation of a point versus the target deformation. This is the penalty factor for pressure constraints. The system allocates the flow rate quota for each grouting hole by solving this objective function.

[0106] Step S400: Execute control commands

[0107] The system will calculate the target control quantity obtained in step S300. This is converted into a specific hardware drive signal. Specifically, the target grouting flow rate is... The frequency commands are converted into those of the grouting pump inverter to adjust the motor speed; the target drilling parameters are converted into proportional valve opening signals of the drilling rig hydraulic system to adjust the propulsion speed and rotation torque, thereby achieving real-time intervention in the grouting process at the physical level.

[0108] Step S500: Implement closed-loop optimization and adaptive adjustment

[0109] The system monitors the actual response of the formation to the grouting operation in real time and calculates the deviation of the grouting effect. Based on this deviation, the system uses an iterative algorithm to update the adaptive filling coefficient in the drilling-injection master-slave collaborative mode in step S300 online. The updated formula is:

[0110]

[0111] In the formula, For learning rate, This is a symbolic function. (Updated) It will be stored and used in the next moment. The system performs control decision calculations, thereby enabling it to continuously learn and adapt to changes in geological conditions.

[0112] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A grouting system for intelligent controlled grouting inside a water-rich sandy tunnel, characterized in that, The system includes: The global sensing module (100) is configured at the grouting operation site to acquire the original physical quantities reflecting the grouting process and the formation response; The multi-source information fusion module (200) is connected to the global perception module (100) and is used to receive the original physical quantities and process them. The multi-source information fusion module (200) is equipped with a clock synchronization unit and a feature calculation unit, which are used to establish the time consistency of the data and calculate key feature parameters, respectively. The collaborative control decision module (300) is connected to the multi-source information fusion module (200) and is used to evaluate the grouting situation and generate target control quantities based on the key feature parameters. The collaborative control decision module (300) is preset with drilling and grouting master-slave collaborative mode, safety priority collaborative mode and global optimization collaborative mode. The execution drive module (400), connected to the collaborative control decision module (300), includes a grouting pump controller (410) and a drilling rig controller (420), for converting the target control quantity into drive commands to adjust the action of the hardware equipment; The closed-loop optimization module (500) is connected to the execution drive module (400) and the global perception module (100) respectively, and is used to dynamically adjust the control parameters in the collaborative control decision module (300) according to the deviation between the actual grouting effect and the expected effect.

2. The grouting system for intelligent controlled grouting in water-rich sandy tunnels according to claim 1, characterized in that, The global perception module (100) specifically includes: The drilling rig status monitoring unit (110) is equipped with a torque sensor for collecting drill rod torque, a speed sensor for collecting drilling speed, a pressure sensor for collecting drilling feed pressure, and a displacement sensor for collecting drilling rate. The grouting parameter monitoring unit (120) is equipped with a pressure transmitter for collecting real-time grouting pressure, an electromagnetic flowmeter for collecting real-time grouting flow, and a density meter for collecting grout density. The formation environment response monitoring unit (130) is equipped with a laser displacement meter for collecting minute deformations of the tunnel lining, a piezometer for collecting pore water pressure in the formation, and an earth pressure cell for collecting stress in the surrounding soil.

3. The grouting system for intelligent controlled grouting in water-rich sandy tunnels according to claim 1, characterized in that, The specific configuration of the multi-source information fusion module (200) is as follows: The clock synchronization unit is equipped with a high-precision crystal oscillator as a unified clock source, which is used to mark millisecond-level timestamps for all channel data of the global perception module (100) at the time of data acquisition, so as to construct a global state vector with time consistency. The key feature parameters used by the feature calculation unit to calculate include at least: the drilling efficiency ratio, which characterizes the degree of matching between the grouting volume and the void volume generated by the borehole, and the pressure dynamic gradient, which characterizes the instantaneous change trend of the grouting pressure.

4. The grouting system for intelligent controlled grouting in water-rich sandy tunnels according to claim 1, characterized in that, The configuration logic of the collaborative control decision module (300) is as follows: It is pre-defined with three situational spatial states: steady-state grouting zone, risk warning zone, and emergency evacuation zone; When in the steady-state grouting zone, the drilling-grouting master-slave collaborative mode is activated. This mode is configured with follow-up control logic with drilling rate as the master variable and grouting flow rate as the slave variable. When in a risk warning zone or emergency evacuation zone, the safety priority collaborative mode is activated. This mode is configured with a graded intervention logic based on the dynamic pressure gradient and the degree of formation deformation.

5. The grouting system for intelligent controlled grouting in water-rich sandy tunnels according to claim 1, characterized in that, The specific functions of the closed-loop optimization module (500) are as follows: The difference between the actual and expected values ​​of minute deformations in the tunnel lining is calculated in real time as the deviation of the grouting effect; The adaptive filling coefficient in the collaborative control decision module (300) is iteratively updated based on the grouting effect deviation, and the updated adaptive filling coefficient is fed back to the collaborative control decision module (300) for calculation at the next moment.

6. A method for intelligent control of grouting inside a tunnel with water-rich sand layers, characterized in that, This method is performed based on the grouting system as described in any one of claims 1 to 5, and includes the following steps: Step S100: The drilling rig operating status data, grouting process data and formation environment response data are synchronously collected using the global perception module (100), and a global state vector is constructed through time axis alignment processing by the clock synchronization unit. Step S200: Calculate key characteristic parameters, including drilling-injection efficiency ratio and pressure dynamic gradient, using the multi-source information fusion module (200), and assess the current grouting situation as a steady-state grouting zone, a risk warning zone, or an emergency avoidance zone based on the key characteristic parameters. Step S300: Based on the evaluation results, the collaborative control decision module (300) selects one of the following modes for activation: drilling master-slave collaborative mode, safety priority collaborative mode, and global optimization collaborative mode, and calculates the target control quantity according to the control logic of the activated mode. Step S400: Receive the target control quantity using the execution drive module (400) and drive the grouting pump and drilling rig to perform corresponding actions; Step S500: Use the closed-loop optimization module (500) to monitor the actual response of the formation to the grouting operation, and dynamically update the adaptive filling coefficient based on the deviation between the actual response and the expected value.

7. The method according to claim 6, characterized in that, In step S200, the calculation logic for the key feature parameters is as follows: The drilling efficiency ratio is calculated by dividing the pre-processed real-time grouting flow rate by the product of the drilling rate and the borehole cross-sectional area. The dynamic pressure gradient is calculated as follows: the difference between the grouting pressure at the current moment and the grouting pressure at the previous sampling moment is calculated, and the difference is divided by the sampling time window width.

8. The method according to claim 6, characterized in that, In step S300, when the drilling-injection master-slave collaborative mode is activated, the calculation of the target control quantity specifically includes: The current grouting zone is determined to be in a steady state. The real-time drilling rate of the drilling rig is the main variable, and the grouting flow rate is the secondary variable. The target grouting flow rate is obtained by multiplying the real-time drilling rate, borehole cross-sectional area, preset grout shrinkage compensation coefficient, and adaptive filling coefficient dynamically updated by step S500. The grouting pump speed is adjusted by the grouting pump controller (410) to track the target grouting flow rate, and the grouting pressure is kept as a non-actively controlled monitoring variable.

9. The method according to claim 6, characterized in that, In step S300, when the security-priority cooperative mode is activated, the calculated target control quantity specifically performs the following hierarchical response: Level 1 Response: When in a risk warning zone and only the dynamic pressure gradient exceeds the limit, maintain the drilling rate unchanged and reduce the grouting flow rate by the first proportion; Secondary response: When the dynamic pressure gradient exceeds the critical threshold, the grouting flow rate is reduced by a second proportion, and the drilling rate is reduced by a third proportion, wherein the second proportion is less than the first proportion. Level 3 response: When the minute deformation of the tunnel lining exceeds the limit allowable value, the target values ​​of grouting flow rate and drilling rate are both set to zero, and a pressure relief operation is triggered.

10. The method according to claim 6, characterized in that, In step S300, when the global optimization cooperative mode is activated, the calculation of the target control quantity specifically includes: A multi-pore collaborative objective function is established, which optimizes the minimization of the weighted sum of the difference between the actual deformation and the target deformation at each monitoring point, and introduces the total grouting pressure as a penalty term. Solve the objective function to obtain the flow rate quota for each grouting hole as the target control quantity.

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