Micro-disturbance grouting method and system suitable for metro tunnel in operation period

Abstract

The present application belongs to the technical field of tunnel maintenance, and discloses a micro-disturbance grouting method and system suitable for subway tunnels in operation period, which comprises a stratum-tube piece coupling response model based on multi-source data, which is used to represent the nonlinear relationship between grouting parameters and tube piece displacement; a plurality of candidate grouting parameter combinations are generated by an optimization algorithm and input into the model for virtual trial grouting simulation to obtain a predicted displacement curve; the optimal grouting parameter combination is screened out by taking the operation allowable deformation threshold as a constraint; the grouting equipment is controlled to perform the operation according to the optimal parameters, and the tube piece displacement is monitored in real time; when the model predicts that the threshold will be reached soon, the load reduction or breathing mode is started, and correction is carried out when the change rate just starts to increase, which makes the actual tube piece uplift or settlement can be controlled in a very small range, far below the safety threshold required by the operator, and truly realizes the micro-disturbance or even zero-disturbance target in the operation period, ensuring the absolute safety of rail transit operation.

Description

Technical Field

[0001] This invention relates to the field of tunnel maintenance technology, and in particular to a micro-disturbance grouting method and system suitable for subway tunnels in operation. Background Technology

[0002] With the rapid development of urban rail transit, subway tunnels often experience structural defects such as settlement, misalignment, and voids behind the tunnel walls during long-term operation. Grouting reinforcement is necessary to restore structural stability and safety without interrupting operation. Traditional grouting techniques for the operational period mostly adopt a "monitoring-feedback" control mode, that is, monitoring tunnel deformation through sensors and adjusting grouting pressure and flow rate accordingly. However, tunnel structural systems are highly nonlinear, time-varying, and uncertain. The relationship between grouting pressure and segment displacement is not a simple linear one; its response is influenced by multiple factors such as ground moisture content, porosity, and void distribution. Traditional methods suffer from a significant "feedback lag": by the time the monitoring system detects displacement changes, the tunnel structure has often already undergone irreversible micro-deformation, potentially posing a threat to track geometric smoothness and train safety.

[0003] In recent years, to improve the precision and controllability of the grouting process, various micro-disturbance grouting technologies and equipment have been proposed in the industry. For example, patent document CN120844918A discloses a "micro-disturbance grouting vertical drilling and injection integrated machine and process method in subway tunnels." This solution achieves continuous operation of drilling and grouting processes by integrating drill rods and grouting channels into a single device, and uses sealing components and pressure gauges to perform preliminary monitoring of the grouting process, thus improving construction efficiency and sealing performance to a certain extent. However, this existing technology still has the following limitations: The control logic is still passive feedback: its grouting process control mainly relies on construction experience and empirical adjustments to grouting pressure and flow rate, lacking quantitative modeling and positive prediction capabilities for the dynamic coupling relationship between grouting parameters (pressure, flow rate, pulse frequency) and tunnel structure response (displacement, stress).

[0004] Lack of prediction and forward-looking control: Although the process mentions "adjusting the drill pipe movement speed according to real-time monitoring data", it is essentially a passive adjustment after the displacement or pressure changes. It cannot make predictive interventions before deformation occurs or in the early stages of trend formation, making it difficult to achieve true "preventive" micro-disturbance control.

[0005] Parameter optimization relies on experience: The selection of grouting parameters is mostly based on manual experience or simple trial and error. No intelligent algorithm is introduced to systematically optimize the combination of multiple parameters, making it difficult to quickly determine the global optimal or near-optimal solution under complex multi-constraint conditions (such as strict deformation threshold and grouting efficiency).

[0006] The system lacks intelligence and adaptability: It has not built a digital twin or response model that integrates multi-source data such as geology, structure, and monitoring, and does not have the closed-loop adaptive control capability to update the model online and optimize parameters in a rolling manner based on real-time monitoring feedback during the grouting process.

[0007] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0008] The main objective of this invention is to provide a micro-disturbance grouting method and system suitable for subway tunnels in operation, aiming to solve the technical problems caused by traditional methods, such as feedback lag, lack of predictability, coarse parameter optimization, and insufficient system adaptability.

[0009] To achieve the above objectives, the present invention provides a micro-disturbance grouting method suitable for subway tunnels in operation, the micro-disturbance grouting method for subway tunnels in operation comprising the following steps: Acquire multi-source feature data of the target grouting area, wherein the multi-source feature data includes at least geometric deformation data of the segment surface, distribution data of geological cavities behind the wall, and allowable deformation threshold during operation; Based on the multi-source feature data, a formation-segment coupled response model is constructed. The formation-segment coupled response model is used to characterize the nonlinear mapping relationship between grouting parameters and segment displacement. Multiple sets of candidate grouting parameter combinations are generated, and each set of candidate grouting parameter combinations is input into the formation-segment coupling response model to perform virtual grouting simulation in order to obtain the corresponding predicted segment displacement curves. Using the allowable deformation threshold during the operation period as a constraint, the optimal grouting parameter combination is selected from the multiple candidate grouting parameter combinations; The grouting equipment is controlled to perform grouting operations according to the optimal grouting parameter combination. The actual segment displacement during the operation is collected in real time. When the deviation between the actual segment displacement and the corresponding predicted segment displacement curve exceeds the preset tolerance, the current grouting parameters are dynamically corrected in real time based on the rolling time domain control strategy.

[0010] In one embodiment, acquiring multi-source feature data of the target grouting area includes: The initial geometric deformation data of the pipe segment surface in the target grouting area is obtained by a wireless laser displacement sensor array. The initial geometric deformation data includes settlement, uplift and misalignment. The back wall of the tunnel lining is scanned by high-frequency ground-penetrating radar to obtain data on the distribution of geological cavities behind the wall. The data on the distribution of geological cavities behind the wall includes the volume of the cavities, dielectric constant, and data on the distribution of stratigraphic heterogeneity. Obtain the maximum allowable deformation threshold set by the operating unit.

[0011] In one embodiment, constructing the formation-segment coupling response model based on the multi-source feature data includes: A three-dimensional geological physical model was established based on the data on the distribution of geological cavities behind the wall. The acquired initial geometric deformation data is used as boundary conditions to initialize and calibrate the three-dimensional formation physical model in order to construct the formation-segment coupled response model. The formation-segment coupled response model is used to predict the dynamic effects of grouting pressure, grouting flow rate and pulse frequency on segment displacement and stress.

[0012] In one embodiment, generating multiple sets of candidate grouting parameter combinations and inputting each set of candidate grouting parameter combinations into the formation-segment coupling response model for virtual grouting simulation to obtain the corresponding predicted segment displacement curves includes: Set a grouting parameter search space that includes initial grouting pressure, grouting flow rate, and frequency range of variable frequency pulses; The multiple sets of candidate grouting parameter combinations are generated within the search space using a particle swarm optimization algorithm or a genetic algorithm. The candidate grouting parameter combinations of each group are input into the formation-segment coupling response model for simulation, and the corresponding predicted segment displacement curves are output. In one embodiment, the real-time dynamic correction of the current grouting parameters based on the rolling time-domain control strategy includes: Calculate the deviation and rate of change between the actual segment displacement and the predicted segment displacement curve; When the absolute value of the deviation or the rate of change exceeds the preset micro-disturbance safety tolerance, the rolling time domain control strategy is activated, the parameter optimization and simulation steps are re-executed, and a new optimal grouting parameter combination is generated. The control commands for the grouting equipment are updated according to the new optimal combination of grouting parameters until the grouting filling rate reaches the set value and the segment displacement is stable.

[0013] In one embodiment, the controlled grouting equipment performs grouting operations according to the optimal grouting parameter combination, and collects the actual segment displacement during the operation in real time, including: Send a control signal to the grouting actuator to control the electro-hydraulic servo frequency conversion pulse pump to start the grouting operation; The actual segment displacement data output by the laser displacement sensor is collected in real time, with a sampling frequency of not less than 100 Hz.

[0014] In one embodiment, the wireless laser displacement sensor array is smaller than 0.1 mm and has a sampling frequency of not less than 10 Hz.

[0015] Furthermore, to achieve the above objectives, the present invention also proposes a micro-disturbance grouting system suitable for subway tunnels in operation. This micro-disturbance grouting system is applied to the micro-disturbance grouting method for subway tunnels in operation as described above. The apparatus includes: The acquisition module is used to acquire multi-source feature data of the target grouting area. The multi-source feature data includes at least geometric deformation data of the segment surface, geological cavity distribution data behind the wall, and allowable deformation threshold during operation. The construction module is used to construct a formation-segment coupled response model based on the multi-source feature data. The formation-segment coupled response model is used to characterize the nonlinear mapping relationship between grouting parameters and segment displacement. The simulation module is used to generate multiple sets of candidate grouting parameter combinations and input each set of candidate grouting parameter combinations into the formation-segment coupling response model to perform virtual grouting simulation in order to obtain the corresponding predicted segment displacement curves. The filtering module is used to filter out the optimal grouting parameter combination from the multiple candidate grouting parameter combinations, using the allowable deformation threshold during the operation period as a constraint. The correction module is used to control the grouting equipment to perform grouting operations according to the optimal grouting parameter combination, collect the actual segment displacement in real time during the operation, and when the deviation between the actual segment displacement and the corresponding predicted segment displacement curve exceeds the preset tolerance, the current grouting parameters are dynamically corrected in real time based on the rolling time domain control strategy.

[0016] Furthermore, to achieve the above objectives, the present invention also proposes a micro-disturbance grouting device suitable for subway tunnels in operation. The micro-disturbance grouting device suitable for subway tunnels in operation includes: a memory, a processor, and a micro-disturbance grouting program suitable for subway tunnels in operation stored in the memory and executable on the processor. The micro-disturbance grouting program suitable for subway tunnels in operation is configured to implement the steps of the micro-disturbance grouting method suitable for subway tunnels in operation as described above.

[0017] Furthermore, to achieve the above objectives, the present invention also proposes a storage medium storing a micro-disturbance grouting program suitable for subway tunnels in operation. When the micro-disturbance grouting program suitable for subway tunnels in operation is executed by a processor, it implements the steps of the micro-disturbance grouting method suitable for subway tunnels in operation as described above.

[0018] This invention constructs a stratum-segment coupled response model based on multi-source data to characterize the nonlinear relationship between grouting parameters and segment displacement. Multiple candidate grouting parameter combinations are generated through an optimization algorithm and input into the model for virtual grouting simulation to obtain predicted displacement curves. The optimal grouting parameter combination is selected based on the operational allowable deformation threshold. The grouting equipment is controlled to operate according to the optimal parameters, and segment displacement is monitored in real time. When the model predicts that the threshold is about to be reached, a load reduction or breathing mode is initiated, and corrections are made as soon as the rate of change begins to increase. This allows the actual segment lifting or settlement to be controlled within a very small range, far below the safety threshold required by the operator, truly achieving the goal of micro-disturbance or even zero-disturbance during operation and ensuring the absolute safety of rail transit operation. Attached Figure Description

[0019] Figure 1 This is a schematic flowchart of the first embodiment of the micro-disturbance grouting method of the present invention applicable to subway tunnels in operation; Figure 2 This is a structural block diagram of the first embodiment of the micro-disturbance grouting system for subway tunnels in operation according to the present invention.

[0020] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0021] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0022] This invention provides a micro-disturbance grouting method suitable for subway tunnels in operation, referring to... Figure 1 , Figure 1 This is a schematic flowchart of the first embodiment of a micro-disturbance grouting method for subway tunnels in operation according to the present invention.

[0023] In this embodiment, the micro-disturbance grouting method applicable to subway tunnels in operation includes the following steps: Step S10: Obtain multi-source feature data of the target grouting area.

[0024] In this embodiment, the execution subject is a micro-disturbance grouting device suitable for subway tunnels in operation. This micro-disturbance grouting device suitable for subway tunnels in operation has functions such as data processing, data communication, and program execution. The micro-disturbance grouting device suitable for subway tunnels in operation can be a computer terminal device or other network device. Of course, it can also be other devices with similar functions. This embodiment does not limit it.

[0025] It's important to note that for operational subway tunnels, traditional automated grouting is based on "feedback" (adjusting pressure upon detecting displacement). However, in operational tunnels, once displacement is detected, it may have already caused irreversible, minute changes to the track geometry. The tunnel itself is a black box; the relationship between grouting pressure and uplift is not a simple linear one, but is significantly affected by moisture content and porosity. Traditional methods suffer from "feedback lag," leading to uncontrollable deformation of the operational subway tunnel structure due to grouting disturbances.

[0026] To address the aforementioned technical challenges, this embodiment constructs a ground-segment coupled response model based on multi-source data to characterize the nonlinear relationship between grouting parameters and segment displacement. Multiple candidate grouting parameter combinations are generated using an optimization algorithm and input into the model for virtual grouting simulation to obtain predicted displacement curves. The optimal grouting parameter combination is selected based on the operational allowable deformation threshold. The grouting equipment is controlled to operate according to the optimal parameters, and segment displacement is monitored in real time. When the model predicts that the threshold is about to be reached, a load reduction or breathing mode is initiated, and corrections are made as soon as the rate of change begins to increase. This allows the actual segment lifting or settlement to be controlled within a very small range, far below the safety threshold required by the operator, truly achieving the goal of micro-disturbance or even zero-disturbance during operation and ensuring the absolute safety of rail transit operation.

[0027] It should be noted that the multi-source feature data in this embodiment includes at least the geometric deformation data of the segment surface, the distribution data of geological cavities behind the wall, and the allowable deformation threshold during operation.

[0028] In specific implementation, the process of acquiring multi-source feature data of the target grouting area involves: acquiring initial geometric deformation data of the segment surface of the target grouting area using a wireless laser displacement sensor array, including settlement, uplift, and misalignment; scanning the back wall of the segment using high-frequency ground-penetrating radar to acquire data on the distribution of geological cavities behind the wall, including cavity volume, dielectric constant, and stratigraphic heterogeneity; and acquiring the maximum allowable deformation threshold set by the operating unit. The dielectric constant is used to invert the water content, the wireless laser displacement sensor array is less than 0.1 mm, and the sampling frequency is not less than 10 Hz.

[0029] Step S20: Construct a formation-segment coupling response model based on the multi-source feature data.

[0030] It should be noted that the formation-segment coupled response model in this embodiment is used to characterize the nonlinear mapping relationship between grouting parameters and segment displacement. The process of constructing the formation-segment coupled response model specifically involves establishing a three-dimensional formation physical model based on the backfill geological cavity distribution data; using the acquired initial geometric deformation data as boundary conditions to initialize and calibrate the three-dimensional formation physical model to construct the formation-segment coupled response model. Specifically, the formation-segment coupled response model is used to predict the dynamic effects of grouting pressure, grouting flow rate, and pulse frequency on segment displacement and stress.

[0031] Step S30: Generate multiple sets of candidate grouting parameter combinations, and input each set of candidate grouting parameter combinations into the formation-segment coupling response model to perform virtual grouting simulation in order to obtain the corresponding predicted segment displacement curves.

[0032] In the specific implementation, multiple sets of candidate grouting parameter combinations are generated, and each set of candidate grouting parameter combinations is input into the formation-segment coupling response model for virtual grouting simulation to obtain the corresponding predicted segment displacement curve. This includes setting a grouting parameter search space that includes the initial grouting pressure, grouting flow rate, and frequency range of the variable frequency pulse; using a particle swarm optimization algorithm or a genetic algorithm to generate the multiple sets of candidate grouting parameter combinations within the search space; inputting each set of candidate grouting parameter combinations into the formation-segment coupling response model for simulation, and outputting the corresponding predicted segment displacement curve.

[0033] Step S40: Using the allowable deformation threshold during the operation period as a constraint, select the optimal grouting parameter combination from the multiple candidate grouting parameter combinations.

[0034] It should be noted that the optimal grouting parameter combination is selected from the group with the maximum predicted displacement as the primary constraint and maximizing grouting efficiency (fill rate / time) as the optimization objective. The optimal grouting parameter combination is selected from the candidate grouting parameter combinations with the allowable deformation threshold during the operation period as the constraint. This optimal grouting parameter combination includes at least the grouting pressure baseline value, grouting flow rate, and pulse frequency.

[0035] Step S50: Control the grouting equipment to perform grouting operations according to the optimal grouting parameter combination, collect the actual segment displacement during the operation in real time, and when the deviation between the actual segment displacement and the corresponding predicted segment displacement curve exceeds the preset tolerance, perform real-time dynamic correction of the current grouting parameters based on the rolling time domain control strategy.

[0036] In specific implementation, the grouting equipment is controlled to perform grouting operations according to the optimal grouting parameter combination, and the actual segment displacement during the operation is collected in real time. This includes: sending control signals to the grouting actuator to control the electro-hydraulic servo frequency conversion pulse pump to start the grouting operation; and collecting the actual segment displacement data output by the laser displacement sensor in real time. The sampling frequency is not less than 100Hz.

[0037] Furthermore, this embodiment can also dynamically correct the current grouting parameters in real time based on a rolling time-domain control strategy. Specifically, this includes calculating the deviation and rate of change between the actual segment displacement and the predicted segment displacement curve; when the absolute value of the deviation or the rate of change exceeds a preset micro-disturbance safety tolerance, the rolling time-domain control strategy is activated, the parameter optimization and simulation steps are re-executed, and a new optimal grouting parameter combination is generated; the control commands for the grouting equipment are updated according to the new optimal grouting parameter combination until the grouting filling rate reaches the set value and the segment displacement stabilizes.

[0038] In this embodiment, a stratum-segment coupled response model is constructed based on multi-source data to characterize the nonlinear relationship between grouting parameters and segment displacement. Multiple candidate grouting parameter combinations are generated through optimization algorithms and input into the model for virtual grouting simulation to obtain predicted displacement curves. The optimal grouting parameter combination is selected based on the operational allowable deformation threshold. The grouting equipment is controlled to perform operations according to the optimal parameters, and the segment displacement is monitored in real time. When the model predicts that the threshold is about to be reached, the load reduction or breathing mode is activated, and corrections are made as soon as the rate of change begins to increase. This allows the actual segment lifting or settlement to be controlled within a very small range, far below the safety threshold required by the operator, truly achieving the goal of micro-disturbance or even zero disturbance during the operation period, and ensuring the absolute safety of rail transit operation.

[0039] Furthermore, this embodiment of the invention also proposes a storage medium storing a micro-disturbance grouting program suitable for subway tunnels in operation. When the micro-disturbance grouting program suitable for subway tunnels in operation is executed by a processor, it implements the steps of the micro-disturbance grouting method suitable for subway tunnels in operation as described above.

[0040] Reference Figure 2 , Figure 2 This is a structural block diagram of the first embodiment of the micro-disturbance grouting system for subway tunnels in operation according to the present invention.

[0041] like Figure 2 As shown in the figure, the micro-disturbance grouting system for subway tunnels in operation proposed in this embodiment of the invention includes: The acquisition module 10 is used to acquire multi-source feature data of the target grouting area. The multi-source feature data includes at least geometric deformation data of the segment surface, distribution data of geological cavities behind the wall, and allowable deformation threshold during operation. Module 20 is used to construct a formation-segment coupled response model based on the multi-source feature data. The formation-segment coupled response model is used to characterize the nonlinear mapping relationship between grouting parameters and segment displacement. Simulation module 30 is used to generate multiple sets of candidate grouting parameter combinations and input each set of candidate grouting parameter combinations into the formation-segment coupling response model to perform virtual grouting simulation in order to obtain the corresponding predicted segment displacement curves. The screening module 40 is used to select the optimal grouting parameter combination from the multiple candidate grouting parameter combinations, using the allowable deformation threshold during the operation period as a constraint. The correction module 50 is used to control the grouting equipment to perform grouting operations according to the optimal grouting parameter combination, collect the actual segment displacement in real time during the operation, and when the deviation between the actual segment displacement and the corresponding predicted segment displacement curve exceeds the preset tolerance, perform real-time dynamic correction of the current grouting parameters based on the rolling time domain control strategy.

[0042] In this embodiment, a stratum-segment coupled response model is constructed based on multi-source data to characterize the nonlinear relationship between grouting parameters and segment displacement. Multiple candidate grouting parameter combinations are generated through optimization algorithms and input into the model for virtual grouting simulation to obtain predicted displacement curves. The optimal grouting parameter combination is selected based on the operational allowable deformation threshold. The grouting equipment is controlled to perform operations according to the optimal parameters, and the segment displacement is monitored in real time. When the model predicts that the threshold is about to be reached, the load reduction or breathing mode is activated, and corrections are made as soon as the rate of change begins to increase. This allows the actual segment lifting or settlement to be controlled within a very small range, far below the safety threshold required by the operator, truly achieving the goal of micro-disturbance or even zero disturbance during the operation period, and ensuring the absolute safety of rail transit operation.

[0043] This application embodiment also provides a micro-disturbance grouting device suitable for subway tunnels in operation, including a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other through the communication bus. The memory is used to store micro-disturbance grouting programs suitable for subway tunnels in operation. When the processor executes the program stored in the memory, it implements the above-mentioned micro-disturbance grouting method suitable for subway tunnels in operation.

[0044] The communication bus mentioned in the micro-disturbance grouting equipment applicable to subway tunnels during operation can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc.

[0045] The communication interface is used for communication between the aforementioned micro-disturbance grouting equipment, which is applicable to subway tunnels in operation, and other equipment.

[0046] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0047] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0048] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (SSD)).

[0049] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0050] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0051] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

[0052] It should be understood that the above are merely illustrative examples and do not constitute any limitation on the technical solutions of the present invention. In specific applications, those skilled in the art can make settings as needed, and the present invention does not impose any restrictions on this.

[0053] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of this invention. In practical applications, those skilled in the art can select some or all of the workflow to achieve the purpose of this embodiment according to actual needs, and no restrictions are imposed here.

[0054] In addition, for technical details not described in detail in this embodiment, please refer to the micro-disturbance grouting method for subway tunnels in operation provided in any embodiment of the present invention, which will not be repeated here.

[0055] Furthermore, it should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0056] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0057] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory (ROM) / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0058] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

[0059] It is understood that the system provided in the embodiments of the present invention corresponds to the method provided in the embodiments of the present invention, and the explanation, examples and beneficial effects of the relevant content can be referred to the corresponding parts of the above methods.

Claims

1. A micro-disturbance grouting method suitable for subway tunnels in operation, characterized in that, The micro-disturbance grouting method applicable to subway tunnels in operation includes: Acquire multi-source feature data of the target grouting area, wherein the multi-source feature data includes at least geometric deformation data of the segment surface, distribution data of geological cavities behind the wall, and allowable deformation threshold during operation; Based on the multi-source feature data, a formation-segment coupled response model is constructed. The formation-segment coupled response model is used to characterize the nonlinear mapping relationship between grouting parameters and segment displacement. Multiple sets of candidate grouting parameter combinations are generated, and each set of candidate grouting parameter combinations is input into the formation-segment coupling response model to perform virtual grouting simulation in order to obtain the corresponding predicted segment displacement curves. Using the allowable deformation threshold during the operation period as a constraint, the optimal grouting parameter combination is selected from the multiple candidate grouting parameter combinations; The grouting equipment is controlled to perform grouting operations according to the optimal grouting parameter combination. The actual segment displacement during the operation is collected in real time. When the deviation between the actual segment displacement and the corresponding predicted segment displacement curve exceeds the preset tolerance, the current grouting parameters are dynamically corrected in real time based on the rolling time domain control strategy.

2. The micro-disturbance grouting method for subway tunnels in operation as described in claim 1, characterized in that, The acquisition of multi-source feature data of the target grouting area includes: The initial geometric deformation data of the pipe segment surface in the target grouting area is obtained by a wireless laser displacement sensor array. The initial geometric deformation data includes settlement, uplift and misalignment. The back wall of the tunnel lining is scanned by high-frequency ground-penetrating radar to obtain data on the distribution of geological cavities behind the wall. The data on the distribution of geological cavities behind the wall includes the volume of the cavities, dielectric constant, and data on the distribution of stratigraphic heterogeneity. Obtain the maximum allowable deformation threshold set by the operating unit.

3. The micro-disturbance grouting method for subway tunnels in operation as described in claim 2, characterized in that, The construction of the formation-segment coupling response model based on the multi-source feature data includes: A three-dimensional geological physical model was established based on the data on the distribution of geological cavities behind the wall. The acquired initial geometric deformation data is used as boundary conditions to initialize and calibrate the three-dimensional formation physical model in order to construct the formation-segment coupled response model. The formation-segment coupled response model is used to predict the dynamic effects of grouting pressure, grouting flow rate and pulse frequency on segment displacement and stress.

4. The micro-disturbance grouting method for subway tunnels in operation as described in claim 1, characterized in that, The process involves generating multiple sets of candidate grouting parameter combinations and inputting each set of candidate grouting parameter combinations into the formation-segment coupling response model for virtual grouting simulation to obtain the corresponding predicted segment displacement curves, including: Set a grouting parameter search space that includes initial grouting pressure, grouting flow rate, and frequency range of variable frequency pulses; The multiple sets of candidate grouting parameter combinations are generated within the search space using a particle swarm optimization algorithm or a genetic algorithm. The candidate grouting parameter combinations of each group are input into the formation-segment coupling response model for simulation, and the corresponding predicted segment displacement curves are output.

5. The micro-disturbance grouting method for subway tunnels in operation as described in claim 1, characterized in that, The real-time dynamic correction of the current grouting parameters based on the rolling time-domain control strategy includes: Calculate the deviation and rate of change between the actual segment displacement and the predicted segment displacement curve; When the absolute value of the deviation or the rate of change exceeds the preset micro-disturbance safety tolerance, the rolling time domain control strategy is activated, the parameter optimization and simulation steps are re-executed, and a new optimal grouting parameter combination is generated. The control commands for the grouting equipment are updated according to the new optimal combination of grouting parameters until the grouting filling rate reaches the set value and the segment displacement is stable.

6. The micro-disturbance grouting method for subway tunnels in operation as described in claim 1, characterized in that, The controlled grouting equipment executes grouting operations according to the optimal grouting parameter combination, and collects the actual segment displacement during the operation in real time, including: Send a control signal to the grouting actuator to control the electro-hydraulic servo frequency conversion pulse pump to start the grouting operation; The actual segment displacement data output by the laser displacement sensor is collected in real time, with a sampling frequency of not less than 100 Hz.

7. The micro-disturbance grouting method for subway tunnels in operation as described in claim 2, characterized in that, The wireless laser displacement sensor array is smaller than 0.1 mm and has a sampling frequency of not less than 10 Hz.

8. A micro-disturbance grouting system suitable for subway tunnels in operation, characterized in that, The micro-disturbance grouting system for subway tunnels in operation is applied to the micro-disturbance grouting method for subway tunnels in operation as described in any one of claims 1 to 7, wherein the apparatus comprises: The acquisition module is used to acquire multi-source feature data of the target grouting area. The multi-source feature data includes at least geometric deformation data of the segment surface, geological cavity distribution data behind the wall, and allowable deformation threshold during operation. The construction module is used to construct a formation-segment coupled response model based on the multi-source feature data. The formation-segment coupled response model is used to characterize the nonlinear mapping relationship between grouting parameters and segment displacement. The simulation module is used to generate multiple sets of candidate grouting parameter combinations and input each set of candidate grouting parameter combinations into the formation-segment coupling response model to perform virtual grouting simulation in order to obtain the corresponding predicted segment displacement curves. The filtering module is used to filter out the optimal grouting parameter combination from the multiple candidate grouting parameter combinations, using the allowable deformation threshold during the operation period as a constraint. The correction module is used to control the grouting equipment to perform grouting operations according to the optimal grouting parameter combination, collect the actual segment displacement in real time during the operation, and when the deviation between the actual segment displacement and the corresponding predicted segment displacement curve exceeds the preset tolerance, the current grouting parameters are dynamically corrected in real time based on the rolling time domain control strategy.

9. A micro-disturbance grouting device suitable for subway tunnels in operation, characterized in that, The micro-disturbance grouting device for metro tunnels in operation includes: a memory, a processor, and a micro-disturbance grouting program for metro tunnels in operation stored in the memory and executable on the processor, wherein the micro-disturbance grouting program for metro tunnels in operation is configured to implement the steps of the micro-disturbance grouting method for metro tunnels in operation as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium stores a micro-disturbance grouting program suitable for subway tunnels in operation. When the micro-disturbance grouting program suitable for subway tunnels in operation is executed by the processor, it implements the steps of the micro-disturbance grouting method suitable for subway tunnels in operation as described in any one of claims 1 to 7.

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