A monitoring and repair method, device and medium for tunnel deformation

Abstract

The present application discloses a method, device and medium for monitoring and repairing tunnel deformation, relating to the technical field of tunnel treatment. The method includes: arranging optical fiber sensors on the lining surface of the tunnel in a diamond grid, integrating temperature sensors for the optical fiber sensors, and generating digital passports for the optical fiber sensors and the temperature sensors; obtaining strain field data on the lining surface through the optical fiber sensors, performing temperature compensation on the strain field data, and establishing a distribution model; obtaining the stress distribution characteristics of tunnel damage and the historical data of corresponding repair cases, and generating a first repair instruction, wherein the stress distribution characteristics of tunnel damage include three-dimensional stress distribution and failure evolution path; performing tensor slicing processing on the distribution model, matching it with the historical data, and generating a second repair instruction by using an optimization algorithm. Through the above method, the present application realizes the full-section high-density monitoring of the three-dimensional stress field, ensures the integrity and traceability of monitoring data, and improves the accuracy rate.

Description

Technical Field

[0001] This application relates to the technical field of tunnel treatment, and particularly to a method, device and medium for monitoring and repairing tunnel deformation. Background Art

[0002] With the development of urban underground space towards deeper and larger cross-sections, the deformation monitoring of tunnel structures faces severe challenges under complex geological conditions and external loads.

[0003] Traditional monitoring methods mainly rely on manual inspections and discrete sensor networks, suffering from technical bottlenecks such as large monitoring blind spots, significant temperature interference, and lag in identifying damage evolution paths. Most of the fiber optic sensor networks used in existing technologies adopt a rectangular layout, having inherent defects in characterizing the shear strain field and lacking dynamic coupling analysis with the thermal expansion characteristics of materials. Existing repair technologies mostly rely on static repair schemes based on empirical judgments, with insufficient matching between the grouting pressure parameters and the on-site working conditions. Although BIM technology has been applied to tunnel engineering, there is a lack of deep integration with real-time monitoring data. The existing systems have insufficient prediction accuracy for damage evolution, and the repair process lacks reliable digital records, resulting in the inability to trace and attribute quality disputes.

[0004] Through the above analysis, the problems and defects existing in the prior art are as follows:

[0005] In the tunnel deformation monitoring of the prior art, there are problems such as low spatial resolution, insufficient temperature interference compensation, poor dynamic adaptability of repair schemes, and insufficient data security and traceability. Summary of the Invention

[0006] The embodiments of this application provide a method, device and medium for monitoring and repairing tunnel deformation, which can solve the problems of low spatial resolution, insufficient temperature interference compensation, poor dynamic adaptability of repair schemes, and insufficient data security and traceability in the tunnel deformation monitoring of the prior art.

[0007] In a first aspect, the embodiments of this application provide a method for monitoring and repairing tunnel deformation, the method including: arranging fiber optic sensors on the lining surface of the tunnel in a diamond grid, integrating temperature sensors for the fiber optic sensors, and generating digital passports for the fiber optic sensors and temperature sensors; obtaining strain field data on the lining surface through the fiber optic sensors, performing temperature compensation on the strain field data, and establishing a distribution model; obtaining the stress distribution characteristics of tunnel damage and the historical data of corresponding repair cases, and generating a first repair instruction, where the stress distribution characteristics of tunnel damage include three-dimensional stress distribution and failure evolution path; performing tensor slicing processing on the distribution model, matching it with the historical data, and generating a second repair instruction using an optimization algorithm.

[0008] In an implementation of the present application, strain field data on the lining surface is obtained through a fiber optic sensor, temperature compensation is performed on the strain field data, and a distribution model is established, specifically including: collecting real-time temperature data at the location of the fiber optic sensor through a temperature sensor; obtaining the concrete mix ratio, and calculating the coefficient of thermal expansion at the location of the fiber optic sensor based on the real-time temperature data, and calculating the coupling relationship with the strain field data; separating the temperature drift component of the strain field data according to the coupling relationship to obtain a three-dimensional stress distribution model of the net mechanical strain value.

[0009] In an implementation of the present application, stress distribution characteristics of tunnel damage and historical data of corresponding repair cases are obtained to generate a first repair instruction, specifically including: matching repair cases based on the BIM component library, and the repair cases include material usage, construction machinery path, and grouting pressure parameters; using the time reversal algorithm to generate a timestamped failure path sequence.

[0010] In an implementation of the present application, the method further includes: performing reverse modeling on the repair area through a drone equipped with a laser scanner, and comparing the Mahalanobis distance of the strain field data before and after repair; dynamically adjusting the material usage, construction machinery path, and grouting pressure parameters based on the Mahalanobis distance and the failure path sequence to obtain a first repair instruction, and generating a blockchain evidence log containing the holographic image of the repair process.

[0011] In an implementation of the present application, tensor slicing processing is performed on the distribution model and matched with historical data, and an optimization algorithm is used to generate a second repair instruction, specifically including: generating circumferential stress slices along the tunnel axis at a preset interval and matching them with the stress distribution characteristics; after obtaining the corresponding first repair instruction by matching, using an intelligent optimization algorithm to plan the material usage, construction machinery path, and grouting pressure parameters to generate a second repair instruction including three-dimensional coordinate positioning.

[0012] In an implementation of the present application, digital passports are generated for the fiber optic sensor and the temperature sensor, specifically including: generating unique digital identifiers for the fiber optic sensor and the temperature sensor based on the blockchain, and writing the factory calibration parameters and installation positioning coordinates; when uploading the strain field data and real-time temperature data, verifying the logical consistency between the current data and the reference curve through zero-knowledge proof; if the verification fails continuously for a preset number of times, marking the current fiber optic sensor as an abnormal state and starting the redundant node data reconstruction process.

[0013] In an implementation of the present application, the time reversal algorithm is used to generate a timestamped failure path sequence, specifically including: extracting the time series characteristics of stress redistribution in historical data, and constructing a prediction model based on the path transition probability of LSTM; introducing an environmental corrosion factor into the prediction model to correct the crack propagation rate, and generating a multi-dimensional failure scenario tree with a confidence interval.

[0014] In one implementation of the present application, after performing tensor slicing on the distribution model, matching it with historical data, and generating a second repair instruction using an optimization algorithm, the method further includes: when executing the second repair instruction, synchronously monitoring the grouting density using distributed fiber optic acoustic sensing; if the frequency-domain energy of the acoustic signal in the grouting area is lower than a preset value, automatically updating the grouting pressure parameter.

[0015] In a second aspect, an embodiment of the present application further provides a monitoring and repair device for tunnel deformation. The device includes at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and when the instructions are executed by the at least one processor, the at least one processor is enabled to: arrange fiber optic sensors on the lining surface of the tunnel in a diamond grid, integrate temperature sensors for the fiber optic sensors, and generate digital passports for the fiber optic sensors and the temperature sensors; obtain strain field data on the lining surface through the fiber optic sensors, perform temperature compensation on the strain field data, and establish a distribution model; obtain the stress distribution characteristics of the tunnel damage and the historical data of the corresponding repair cases, and generate a first repair instruction, wherein the stress distribution characteristics of the tunnel damage include three-dimensional stress distribution and failure evolution path; perform tensor slicing on the distribution model, match it with the historical data, and generate a second repair instruction using an optimization algorithm.

[0016] In a third aspect, an embodiment of the present application further provides a non-volatile computer storage medium for monitoring and repairing tunnel deformation, storing computer-executable instructions, and the computer-executable instructions are set to: arrange fiber optic sensors on the lining surface of the tunnel in a diamond grid, integrate temperature sensors for the fiber optic sensors, and generate digital passports for the fiber optic sensors and the temperature sensors; obtain strain field data on the lining surface through the fiber optic sensors, perform temperature compensation on the strain field data, and establish a distribution model; obtain the stress distribution characteristics of the tunnel damage and the historical data of the corresponding repair cases, and generate a first repair instruction, wherein the stress distribution characteristics of the tunnel damage include three-dimensional stress distribution and failure evolution path; perform tensor slicing on the distribution model, match it with the historical data, and generate a second repair instruction using an optimization algorithm.

[0017] A method, device and medium for monitoring and repairing tunnel deformation provided by an embodiment of the present application integrate fiber optic sensors and temperature sensors through a rhombic grid layout, realizing full-section high-density monitoring of a three-dimensional stress field; adopting digital passport and blockchain evidence storage technology to ensure the integrity and traceability of monitoring data, and cross-verification of device status and data can be achieved during the entire life cycle of the tunnel; by combining a BIM component library with a time reversal algorithm, a failure evolution model with spatio-temporal correlation is constructed, improving the matching accuracy of the repair plan, and the dynamic adjustment mechanism improves the qualification rate of grouting density; adopting closed-loop control of distributed fiber optic acoustic sensing and intelligent optimization algorithms to realize real-time feedback adjustment of the repair process. Description of the Drawings

[0018] The drawings described herein are used to provide a further understanding of the present application, and constitute a part of the present application. The illustrative embodiments and descriptions thereof of the present application are used to explain the present application, and do not constitute an improper limitation of the present application. In the drawings:

[0019] Figure 1 It is a flowchart of a method for monitoring and repairing tunnel deformation provided by an embodiment of the present application;

[0020] Figure 2 It is a schematic diagram of the internal structure of a device for monitoring and repairing tunnel deformation provided by an embodiment of the present application. Detailed Embodiments

[0021] To make the objectives, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be clearly and completely described below in conjunction with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0022] An embodiment of the present application provides a method, device and medium for monitoring and repairing tunnel deformation, which solves the problems of low spatial resolution, insufficient temperature interference compensation, poor dynamic adaptability of the repair plan, and insufficient data security and traceability in tunnel deformation monitoring in the prior art.

[0023] The technical solutions proposed by the embodiments of the present application will be described in detail below with reference to the drawings.

[0024] Figure 1 It is a flowchart of a method for monitoring and repairing tunnel deformation provided by an embodiment of the present application. As Figure 1 shown, a method for monitoring and repairing tunnel deformation provided by an embodiment of the present application specifically includes the following steps:

[0025] Step 10: Fiber optic sensors are arranged on the lining surface of the tunnel in a diamond grid. Integrate temperature sensors for the fiber optic sensors and generate digital passports for the fiber optic sensors and temperature sensors.

[0026] In this step, for example, the side length of the grid can be 0.5 - 1.2 meters, adjusted according to the formation stability. Epoxy resin encapsulation and fixation are used at the node intersections. The spacing between adjacent optical fibers needs to cover the curvature change of the lining surface to ensure that the spatial sampling density of the strain field ≥ 20 points / ㎡. Alternatively, a digital temperature sensor can be integrated every three diamond nodes, with a spacing of about 3 meters, and share the data transmission channel with the fiber optic sensors through a multiplexer.

[0027] As an alternative embodiment, generating digital passports for the fiber optic sensors and temperature sensors can specifically include: Step 101: Generate unique digital identifiers for the fiber optic sensors and temperature sensors based on the blockchain, and write in the factory calibration parameters and installation positioning coordinates; Step 102: When uploading strain field data and real-time temperature data, verify the logical consistency between the current data and the reference curve through zero-knowledge proof; Step 103: If the verification fails continuously for a preset number of times, mark the current fiber optic sensor as an abnormal state and initiate the redundant node data reconstruction process.

[0028] In this step, the factory calibration parameters can be the zero strain value and the temperature sensitivity coefficient; the installation positioning coordinates can be the local coordinate system based on the tunnel BIM model; as well as the sensor activation time and the first data upload time, and the data generates an immutable hash value. Each time data is uploaded, the zk-SNARK protocol is used to verify the consistency between the current data and the factory reference curve. For example, if the verification fails continuously 3 times, such as when the data mutation exceeds the threshold of ±200με, the system automatically marks the sensor as abnormal and activates the adjacent redundant nodes, that is, the preset backup sensors for data interpolation and reconstruction.

[0029] Step 20: Obtain the strain field data on the lining surface through the fiber optic sensors, perform temperature compensation on the strain field data, and establish a distribution model.

[0030] As an alternative embodiment, obtaining the strain field data on the lining surface through the fiber optic sensors, performing temperature compensation on the strain field data, and establishing a distribution model can specifically include: Step 201: Collect the real-time temperature data at the location of the fiber optic sensors through the temperature sensors; Step 202: Obtain the concrete mix ratio, calculate the thermal expansion coefficient at the location of the fiber optic sensors based on the real-time temperature data, and calculate the coupling relationship with the strain field data; Step 203: Separate the temperature drift component of the strain field data according to the coupling relationship to obtain a three-dimensional stress distribution model of the net mechanical strain value.

[0031] In this step, the temperature sensor collects the temperature on the lining surface, and then eliminates environmental noise through Kalman filtering to generate a thermal map of the temperature field. Then, the concrete mix parameters are input: cement type, aggregate size, water-cement ratio. Combining with the real-time temperature data, the thermal expansion coefficient α(T)=α0 + kΔT is calculated. According to the real-time temperature ΔT and the concrete mix, α(T) is dynamically calculated, where α0 is the thermal expansion coefficient of the concrete at the reference temperature, which is determined by the concrete mix in the laboratory and is directly related to the concrete mix parameters, k is the material temperature sensitivity factor, and ΔT is the difference between the real-time temperature and the reference temperature. The temperature component Δε in the fiber optic strain data is separated T from the mechanical strain component Δε M , and the temperature strain ΔεT = α(T) ΔT, Δε M = Δε 总 - α(T)ΔT. That is to say, the total strain Δεtotal is composed of the superposition of the temperature strain ΔεT and the mechanical strain ΔεM. After removing the strain caused by temperature through temperature compensation, the strain data reflecting the true deformation of the structure. Based on the compensated net mechanical strain value, in tunnel monitoring, it is very difficult to directly measure the three-dimensional stress distribution, but the strain data can be obtained in real time through fiber optic sensors. Therefore, the finite element inverse analysis method is used to reconstruct the three-dimensional stress field, convert the strain data after temperature compensation into a three-dimensional stress tensor, and output it in tensor form.

[0032] Step 30: Obtain the stress distribution characteristics of tunnel damage and the historical data of corresponding repair cases, and generate a first repair instruction, where the stress distribution characteristics of tunnel damage include three-dimensional stress distribution and failure evolution path.

[0033] As an alternative embodiment, obtaining the stress distribution characteristics of tunnel damage and the historical data of corresponding repair cases, and generating a first repair instruction may specifically include: Step 301: Match repair cases based on the BIM component library, and the repair cases include material usage, construction machinery path, and grouting pressure parameters; Step 302: Use the time reversal algorithm to generate a timestamped failure path sequence.

[0034] In this step, for example, historical repair cases are retrieved from the BIM (Building Information Modeling) component library, and the following features are extracted: damage type: shear crack, circumferential fracture, etc.; stress distribution similarity: Euclidean distance ≤ 0.15; environmental parameters: groundwater pH value, surrounding rock grade; after successful matching, the material usage in the case is automatically associated, such as the epoxy resin grouting volume Q = πr²L·filling coefficient, construction machinery path: six-axis robotic arm movement trajectory; grouting pressure: P = 0.5 - 1.2 MPa (the grouting pressure can be adjusted between 0.5 MPa and 1.2 MPa).

[0035] As an alternative embodiment, the method may further include: Step 303: Use a drone to carry a laser scanner to perform reverse modeling on the repair area and compare the Mahalanobis distance of the strain field data before and after repair; Step 304: Dynamically adjust the material dosage, the path of the construction machinery, and the grouting pressure parameters based on the Mahalanobis distance and the failure path sequence to obtain a first repair instruction, and generate a blockchain evidence log containing the holographic image of the repair process.

[0036] In this step, the Mahalanobis distance can reflect the relative position change of data points in a multi-dimensional space and is an effective indicator for evaluating the repair effect. If the Mahalanobis distance is small, it indicates that the repair effect is good and the strain field difference between the repaired area and the unrepaired area is small; if the Mahalanobis distance is large, it indicates that there is still a large strain difference in the repaired area and the repair process may need to be further optimized. Package the repair instruction, sensor data, and image file to generate an IPFS hash and write it into the blockchain evidence log to support subsequent quality traceability.

[0037] As an alternative embodiment, use the time reversal algorithm to generate a failure path sequence with timestamps, which may specifically include: Step 3021: Extract the time series characteristics of stress redistribution in historical data and construct a prediction model for the path transition probability based on LSTM; Step 3022: Introduce an environmental corrosion factor into the prediction model to correct the crack growth rate and generate a multi-dimensional failure scenario tree with a confidence interval.

[0038] In this step, input the time series of historical stress data and train the long short-term memory network to predict the crack growth rate v: v = v 0 e kt (Introduce the corrosion factor k = 0.02Cl- concentration, the corrosion factor k is used to quantify the corrosion rate of the material in the environment, Cl- represents the chloride ion concentration, and chloride ions are common corrosive ions), output the failure path sequence with timestamps. For example, when t = 72h, the circumferential crack extends to 2m, and generate a multi-dimensional scenario tree. For example, the paths with a probability weight ≥ 80% can be preferentially displayed.

[0039] Step 40: Perform tensor slicing processing on the distribution model, match it with historical data, and use an optimization algorithm to generate a second repair instruction.

[0040] As an alternative embodiment, tensor slicing is performed on the distribution model and matched with historical data, and an optimization algorithm is used to generate a second repair instruction, which may specifically include: Step 401: Generate circumferential stress slices along the tunnel axis at a preset interval and match them with the stress distribution characteristics; Step 402: After obtaining the corresponding first repair instruction through matching, use an intelligent optimization algorithm to plan the material usage, construction machinery path, and grouting pressure parameters to generate a second repair instruction including three-dimensional coordinate positioning.

[0041] In this step, for example, circumferential stress slices are generated every 0.5 meters along the tunnel axis, the maximum principal stress and shear stress within the slices are extracted, and matched with the damage modes in the BIM case library. Then, based on the first repair instruction, an intelligent optimization algorithm, such as a genetic algorithm, particle swarm algorithm, simulated annealing algorithm, etc., is used to plan the material usage, construction machinery path, and grouting pressure parameters, and the optimized repair parameters are combined with the three-dimensional coordinate positioning information of the tunnel to generate a second repair instruction including three-dimensional coordinate positioning.

[0042] As an alternative embodiment, after performing tensor slicing on the distribution model, matching it with historical data, and using an optimization algorithm to generate a second repair instruction, the method may further include: When executing the second repair instruction, synchronously use distributed fiber optic acoustic sensing to monitor the grouting density; if the frequency domain energy of the acoustic signal in the grouting area is lower than a preset value, automatically update the grouting pressure parameters.

[0043] In this step, distributed fiber optic acoustic sensors are arranged around or inside the grouting area. The sensors transmit acoustic signals through optical fibers and can monitor the acoustic wave changes generated during the grouting process in real time. Through methods such as Fourier transform, the time-domain acoustic wave signals are converted into frequency-domain signals, and the energy distribution at different frequencies is analyzed. According to the frequency domain energy distribution, the density of the grouting area is evaluated, and a threshold of the frequency domain energy of the acoustic signal is preset as the judgment standard for the grouting density; if the frequency domain energy of the acoustic signal in the grouting area is lower than the preset value, it indicates that the grouting material may not be fully filled or the density is insufficient. At this time, the system automatically updates the grouting pressure parameters, increases the grouting pressure or adjusts the grouting method to improve the grouting effect.

[0044] The above is the method embodiment proposed in this application. Based on the same inventive concept, the embodiments of this application also provide a monitoring and repair device for tunnel deformation, and its structure is as Figure 2 shown.

[0045] Figure 2 This is a schematic diagram of the internal structure of a monitoring and repair device for tunnel deformation provided by an embodiment of this application. As shown in Figure 2 shown, the device includes:

[0046] At least one processor 201;

[0047] and a memory 202 communicatively connected to at least one processor;

[0048] Wherein, the memory 202 stores instructions executable by at least one processor, and the instructions are executed by at least one processor 201 to enable at least one processor 201 to: arrange fiber optic sensors on the lining surface of the tunnel in a diamond grid, integrate temperature sensors for the fiber optic sensors, and generate digital passports for the fiber optic sensors and the temperature sensors; obtain strain field data on the lining surface through the fiber optic sensors, perform temperature compensation on the strain field data, and establish a distribution model; obtain the stress distribution characteristics of tunnel damage and historical data of corresponding repair cases, and generate a first repair instruction, wherein the stress distribution characteristics of tunnel damage include three-dimensional stress distribution and failure evolution path; perform tensor slicing processing on the distribution model, match it with the historical data, and generate a second repair instruction using an optimization algorithm.

[0049] Some embodiments of the present application provide a non-volatile computer storage medium corresponding to Figure 1 for monitoring and repairing tunnel deformation, storing computer-executable instructions, and the computer-executable instructions are set to: arrange fiber optic sensors on the lining surface of the tunnel in a diamond grid, integrate temperature sensors for the fiber optic sensors, and generate digital passports for the fiber optic sensors and the temperature sensors; obtain strain field data on the lining surface through the fiber optic sensors, perform temperature compensation on the strain field data, and establish a distribution model; obtain the stress distribution characteristics of tunnel damage and historical data of corresponding repair cases, and generate a first repair instruction, wherein the stress distribution characteristics of tunnel damage include three-dimensional stress distribution and failure evolution path; perform tensor slicing processing on the distribution model, match it with the historical data, and generate a second repair instruction using an optimization algorithm.

[0050] Each embodiment in the present application is described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and the key points of each embodiment are the differences from other embodiments. In particular, for the embodiments of the Internet of Things devices and media, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0051] The systems and media provided by the embodiments of the present application correspond one-to-one with the methods. Therefore, the systems and media also have beneficial technical effects similar to the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the systems and media will not be elaborated here.

[0052] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0053] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0054] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0055] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0056] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0057] The memory may include non-permanent memory in the computer-readable medium, random access memory (RAM), and / or non-volatile memory in the form of, for example, read-only memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.

[0058] A computer-readable medium includes permanent and non-permanent, removable and non-removable media that can implement information storage by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transitory medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer-readable medium does not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0059] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the element.

[0060] The above description is only for the embodiments of the present application and is not intended to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A method for monitoring and repairing tunnel deformation, characterized in that: The method comprises: Arranging optical fiber sensors in a diamond grid on the lining surface of the tunnel, integrating temperature sensors with the optical fiber sensors, and generating a digital passport for the optical fiber sensors and the temperature sensors; Acquiring strain field data of the lining surface through the optical fiber sensor, performing temperature compensation on the strain field data, and establishing a distribution model; The stress distribution characteristics of the tunnel damage and the historical data of the corresponding repair cases are obtained to generate a first repair instruction, wherein the stress distribution characteristics of the tunnel damage include three-dimensional stress distribution and failure evolution path, specifically including: Matching the repair case based on the BIM component library, wherein the repair case includes material usage, construction machinery path and grouting pressure parameters; A time reversal algorithm is used to generate a failure path sequence with timestamps; Using a laser scanner mounted on a drone, reverse modeling of the repaired area was performed to compare the Mahalanobis distance of the strain field data before and after the repair. Dynamically adjust the material usage, construction machinery path and grouting pressure parameters based on the Mahalanobis distance and failure path sequence to obtain a first repair instruction, and generate a blockchain evidence log containing a holographic image of the repair process; The distribution model is subjected to tensor slicing processing and matched with the historical data, and a second repair instruction is generated by using an optimization algorithm, specifically including: Generate circumferential stress slices along the tunnel axis at preset intervals to match the stress distribution characteristics; After the corresponding first repair instruction is matched, an intelligent optimization algorithm is used to plan the material usage, construction machinery path and grouting pressure parameters to generate a second repair instruction including three-dimensional coordinate positioning.

2. A method for monitoring and repairing tunnel deformation according to claim 1, characterized in that: The step of obtaining the strain field data of the lining surface by the optical fiber sensor, performing temperature compensation on the strain field data, and establishing a distribution model specifically includes: Collecting real-time temperature data of the location of the optical fiber sensor through the temperature sensor; Obtaining the concrete mix ratio, and calculating the thermal expansion coefficient of the location of the optical fiber sensor according to the real-time temperature data, and calculating the coupling relationship with the strain field data; The temperature drift component of the strain field data is separated according to the coupling relationship to obtain a three-dimensional stress distribution model of the net mechanical strain value.

3. A method for monitoring and repairing tunnel deformation according to claim 1, characterized in that: The generating of a digital passport for the optical fiber sensor and the temperature sensor specifically includes: Generate a unique digital identifier for the optical fiber sensor and temperature sensor based on blockchain, and write factory calibration parameters and installation positioning coordinates; When the strain field data and real-time temperature data are uploaded, the logical consistency between the current data and the reference curve is verified by zero-knowledge proof; If the verification fails for a preset number of consecutive times, the current optical fiber sensor is marked as abnormal and the redundant node data reconstruction process is started.

4. A method for monitoring and repairing tunnel deformation according to claim 1, characterized in that: The time reversal algorithm is used to generate a failure path sequence with a timestamp, specifically including: Extracting the time series characteristics of stress redistribution in the historical data, and constructing a prediction model of path transition probability based on LSTM; The environmental corrosion factor is introduced into the prediction model to correct the crack growth rate and generate a multi-dimensional failure scenario tree with confidence intervals.

5. The method for monitoring and repairing tunnel deformation according to claim 1, characterized in that: After performing tensor slicing processing on the distribution model and matching it with the historical data, and using an optimization algorithm to generate a second repair instruction, the method further includes: When executing the second repair instruction, the grouting density is monitored synchronously using distributed optical fiber acoustic wave sensing; If the frequency domain energy of the acoustic wave signal in the grouting area is lower than a preset value, the grouting pressure parameter is automatically updated.

6. A monitoring and repair device for tunnel deformation, characterized in that: The device comprises: at least one processor; and, a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to: Execute the steps of a method for monitoring and repairing tunnel deformation as described in any one of claims 1-5.

7. A non-volatile computer storage medium for monitoring and repairing tunnel deformation, storing computer executable instructions, characterized in that: The computer executable instructions are configured to: Execute the steps of a method for monitoring and repairing tunnel deformation as described in any one of claims 1-5.

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