Intelligent grouting control device and method for subway tunnel

Abstract

The invention discloses an intelligent grouting control device and method for a subway tunnel, and belongs to the technical field of engineering grouting. According to the method, grouting pressure and tunnel deformation and vibration data in a grouting area are monitored in real time in the back grouting process; strain gauges are arranged at the joints of the lining segments to monitor relative deformation between the segments; accelerometers are arranged on the non-grouting side of the duct piece in an array mode, and the grouting fullness is judged by monitoring vibration of the duct piece; a laser displacement sensor is arranged in the tunnel and points to the inner side of the duct piece, and the instability risk is judged by measuring the distance change between the duct piece and the fixed point; a camera device is arranged in the subway tunnel and used for conducting video monitoring on segments in a grouting area, and whether grout seepage, segment dislocation and bottom plate upheaval occur or not is judged through pixel change comparison. According to the method, the problem of excessive grouting or insufficient grouting in traditional grouting can be effectively solved, meanwhile, the problem of instability damage possibly occurring in the grouting process is monitored, and the grouting quality and safety are improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of engineering grouting, and particularly relates to an intelligent grouting control device and method for a subway tunnel. BACKGROUND

[0002] Grouting technology is a key means for ensuring structural stability, controlling ground deformation and achieving water stop and seepage prevention in subway tunnel engineering, and is widely used in scenarios such as filling behind shield tunnel segments and surrounding rock reinforcement. However, the grouting process has a strong concealment, and the internal grout diffusion path, filling density and influence on the surrounding structure cannot be directly observed, which makes the monitoring link the core bottleneck of determining the grouting quality. The deficiencies of the prior art in monitoring mainly lie in the following aspects:

[0003] 1. Single monitoring parameter, difficult to reflect overall state

[0004] The prior art mainly monitors basic parameters such as grouting pressure and grouting volume, and lacks correlation monitoring of grouting effect. For example, when the grouting pressure reaches the preset value, the traditional system defaults that the grouting is qualified, but in fact, it may cause local filling deficiency due to abnormal channeling of grout in the crack, or form a "false pressure" phenomenon (pressure meets the standard but is not truly filled) due to rapid grout setting. This single parameter monitoring cannot capture the complexity of the grouting process, and is prone to misjudgment of "pressure meeting the standard but quality not qualified". According to engineering practice statistics, the rework rate caused by such misjudgment accounts for more than 40% of grouting construction problems.

[0005] 2. Limited monitoring dimension, lack of three-dimensional feedback

[0006] Existing monitoring is mostly focused on the grouting equipment itself, and a three-dimensional monitoring network covering "grout-ground-structure" is not constructed. For example, in segment grouting, the traditional technology only focuses on the pressure change of the grouting pump, but ignores key information such as micro-deformation of segment joints and ground uplift that indirectly reflects the grouting effect. When grout over-diffusion causes segment stress deformation, the existing system often alarms only when the deformation is visible, which has caused structural damage. When the grout is not fully filled, it is also difficult to find hidden dangers in time due to the lack of monitoring means for ground cavities.

[0007] 3. Lack of real-time adjustment, adjustment lags behind construction dynamics

[0008] The existing monitoring is mostly post-data recording, lacking real-time analysis and feedback capability. For example, when grouting in water-rich strata, the grout may be diluted by underground water, resulting in a sharp drop in diffusion efficiency. The traditional system needs to be manually checked regularly to find abnormalities, which has missed the best adjustment opportunity, resulting in waste of materials and possible formation of leakage channels due to long-time low-pressure grouting. In addition, the differences in grout properties (such as setting time and fluidity) between synchronous grouting and secondary grouting are not included in the dynamic monitoring system, resulting in a lack of targeted quality control in different stages.

[0009] 4. Monitoring data is dispersed, making it difficult to achieve global control

[0010] The monitoring data of the prior art is mostly stored in the field equipment, lacking a centralized management platform, and unable to achieve collaborative analysis of multiple working surfaces and multiple parameters. For example, when the pressure of a grouting section drops sharply, it is difficult for the management personnel to quickly associate the stratum data, pipe section state and other information of the adjacent section, to determine whether it is caused by local cracks or systemic risks, resulting in significant decision-making lag and easy triggering of chain quality problems.

[0011] The above problems of inadequate monitoring directly lead to frequent "over-grouting" and "insufficient grouting" phenomena in the grouting process, affecting the engineering quality and possibly causing safety hazards such as structure leakage and uneven settlement during operation. Therefore, building a multi-parameter, three-dimensional, real-time grouting monitoring and intelligent control system has become the key to solving the quality problems of metro tunnel grouting. SUMMARY

[0012] The present application aims to at least solve one of the above-mentioned technical problems in the related art to some extent.

[0013] To this end, the present application aims to provide a device and method for intelligent grouting control of metro tunnels, which can achieve precise and intelligent control of the grouting process of metro tunnels by building a multi-dimensional real-time monitoring network, effectively solving the problems of over-grouting or insufficient grouting in traditional grouting, and improving the grouting quality and safety.

[0014] To solve the above technical problems, the present application is implemented as follows:

[0015] The present application provides a method for intelligent grouting control of metro tunnels, which comprises:

[0016] In the secondary grouting process, the grouting pressure and the deformation and vibration data of the pipe in the grouting area are monitored in real time to form a full-dimensional three-dimensional monitoring system, the monitoring data are analyzed to identify problems and control the grouting process, and the purpose of rapid response to grouting abnormalities is achieved; the three-dimensional monitoring system comprehensively considers four core dimensions of local deformation of a pipe segment, overall displacement deformation of the pipe segment, filling degree of the grout, and leakage of the grout in the pipe segment, fully covers key monitoring nodes of the grouting operation, ensures the completeness of the monitoring coverage and the scientificity of the evaluation basis, and provides reliable technical support for stable promotion of the secondary grouting operation.

[0017] In addition, the intelligent grouting control method for a subway tunnel according to the present application can further have the following additional technical features:

[0018] In some embodiments, when the grouting pressure is not greater than an initial pressure threshold, a fast grouting strategy is adopted for the grouting operation;

[0019] When the grouting pressure is greater than the initial pressure threshold, a slow grouting speed is adopted for the grouting operation;

[0020] The fast grouting strategy is that the grouting pressure value is increased by 5%.

[0021] The initial pressure threshold is mainly determined according to grouting process tests and the like, and the purpose is to determine the initial grouting pressure, at which the gap between the back of the shield pipe segment and the soil is quickly filled.

[0022] In some embodiments, a plurality of strain gauges are arranged at the joints of the lining pipe segments, and the relative deformation between the pipe segments is judged by the strain values;

[0023] When the deformation of the pipe segment is monitored, the grouting is stopped, and it is judged whether the deformation is caused by the full grouting or by an abnormality in combination with the deformation amount and the current grouting pressure; if the deformation is caused by an abnormality, the secondary grouting is performed after the cause is found and corrected.

[0024] In some embodiments, a plurality of accelerometers are arranged in an array on the non-grouting side (i.e., the inner side of the tunnel) of the pipe segment, and the grouting fullness is judged by monitoring the vibration caused by the grouting of the grout to the pipe segment; specifically including:

[0025] When the monitored vibration signal is within a preset low vibration threshold range, the grouting is stopped, and it is judged whether the grouting of the corresponding area is in a full state in combination with the current grouting pressure.

[0026] In some embodiments, an array-type laser displacement sensor is arranged at a fixed position in the tunnel, the laser of the sensor points to the inner side of the pipe segment in the grouting area, and it is judged whether there is a risk of instability by measuring the distance change between the pipe segment and the fixed point;

[0027] When a rapid increase or sudden change in segment displacement is detected, grouting should be stopped immediately, and the cause of the displacement should be determined based on the grouting pressure.

[0028] In some of these implementations, the strain value at the joint of the pipe segment, the vibration acceleration value / micro-vibration value of the pipe segment, and the displacement value of the pipe segment monitored by the laser displacement sensor are used to comprehensively determine whether the current state is unsaturated grouting, about to be saturated, or whether there is a possibility of instability.

[0029] When it is determined that the grouting is about to reach saturation, the grouting parameters are adjusted; when it is determined that there is a possibility of instability, grouting is stopped and corresponding instability response operations are carried out.

[0030] The formula for comprehensive judgment is: F=f(k1×p1+k2×p2+k3×p3+k4×p4);

[0031] Where k1, k2, k3, and k4 are weighting coefficients, and p1, p2, p3, and p4 are the comprehensive strain parameter, comprehensive micro-vibration parameter, comprehensive displacement parameter, and comprehensive image parameter in the grouting area, respectively.

[0032] p1 = k11×p11 + k12×p12 + k13×p13 + ... + k1n×p1n, where k11-k1n are the weighting coefficients corresponding to each strain gauge, which are directly related to the distance; p11-p1n are the monitoring values ​​of each strain gauge (e.g., 0.1%).

[0033] p2 = k21×p21 + k22×p22 + k23×p23 + ... + k2n×p2n, where k21-k2n are the weighting coefficients of each accelerometer, which are directly related to the distance; p21-p2n are the ratios of the monitored values ​​of each accelerometer to the preset acceleration values.

[0034] p3 = k31×p31 + k32×p32 + k33×p33 + ... + k3n×p3n, where k31-k3n are the weighting coefficients of each laser displacement sensor, which are directly related to the distance; p31-p3n are the monitoring values ​​of each laser displacement sensor (e.g., 1%).

[0035] p4 is a comprehensive image parameter, specifically the proportion of change of the inner surface of the segment within a specific grouting area over time.

[0036] In some of these embodiments, the strain gauges are arranged at equal intervals along the segment joints.

[0037] In some of these embodiments, the accelerometers are arranged in an array with equal spacing, and the spacing between any two adjacent accelerometers is 0.5-2m. This spacing is adjusted according to the specifications of the tunnel segments and geological conditions. The basic principle of adjustment is that the spacing is smaller when the segment size is small and the spacing is reduced when encountering adverse geological conditions.

[0038] In some implementations, video surveillance equipment is installed inside the subway tunnel to monitor the grouting area of ​​the tunnel segments. By comparing pixel changes in different frames at specific time intervals, it is determined whether grout leakage, segment misalignment, or floor slab heave has occurred. A judgment model can be trained using historical data through machine learning to identify the type of anomaly based on pixel changes.

[0039] This invention also provides an intelligent grouting control device for subway tunnels, capable of implementing the intelligent grouting control method for subway tunnels as described in any of the preceding embodiments; the device includes:

[0040] Intelligent grouting station: Deployed at the grouting site, it is the core execution equipment, configured to collect, transmit and record various grouting data, as well as perform data analysis and prepare grout and adjust grouting pressure based on the analysis results;

[0041] Sensor module: Deployed inside the grouting tunnel and connected to the intelligent grouting station, it is configured to detect the strain, deformation, vibration and grout seepage of the tunnel segments;

[0042] Intelligent grouting management cloud platform: Deployed in the back-end as a data hub, it is configured to collect construction process data and result reports in real time, summarize, monitor, analyze and store the data, and connect to other smart platforms to provide technical support for management.

[0043] In addition, the intelligent grouting control device for subway tunnels according to the present invention may also have the following additional technical features:

[0044] In some of these implementations, the other smart platform includes a project smart construction cloud platform.

[0045] Compared with the prior art, the present invention has at least the following beneficial effects:

[0046] In this embodiment of the invention, the intelligent grouting control method for subway tunnels provides a three-dimensional comprehensive monitoring system that uses monitoring instruments and equipment to evaluate the grouting effect and judge the safety status of the tunnel segments. The system uses data to judge the grouting effect and decides whether the grouting control parameters need to be adjusted. At the same time, it monitors the safety status of the tunnel segments and predicts whether structural damage or instability will occur.

[0047] In this embodiment of the invention, the intelligent grouting control method for subway tunnels provides a three-dimensional monitoring system that includes key parameters such as grouting pressure and four appearance monitoring methods. Strain gauges monitor the deformation of the tunnel segment joints, laser displacement sensors monitor the risk of tunnel segment instability, micro-vibration monitoring determines the grouting fullness, and image comparison monitors grout leakage and other visible abnormalities. The combination of multi-dimensional data can more accurately reflect the grouting status and provide safety warnings.

[0048] In this embodiment of the invention, the intelligent grouting control method for subway tunnels explores typical geological parameters, proposes targeted control standards for different grout types, and adjusts the grouting speed according to the amount of grout to be injected, so that the grouting process can adapt to different geological conditions and construction needs, reducing the problems caused by blindly setting parameters.

[0049] The intelligent grouting control device for subway tunnels of the present invention can realize the intelligent grouting control method for subway tunnels described above, and therefore has at least all the features and advantages of the intelligent grouting control method for subway tunnels described above, which will not be repeated here. Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0050] Figure 1 This is a block diagram of an intelligent grouting control method for subway tunnels disclosed in one embodiment of the present invention;

[0051] Figure 2 This is a schematic diagram of the overall structure and a partial structural diagram of an intelligent grouting control device for subway tunnels, disclosed in an embodiment of the present invention.

[0052] Explanation of reference numerals in the attached figures:

[0053] 1-Segment; 2-Strain gauge; 3-Accelerometer; 4-Laser displacement sensor; 5-Camera equipment; 6-Track; 7-Grouting area behind. Detailed Implementation

[0054] The technical solutions of 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, not all, of the embodiments of the present invention. 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.

[0055] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and specific examples and application scenarios.

[0056] Please see Figure 1As shown, in some embodiments of the present invention, a method for intelligent grouting control in subway tunnels (intelligent grouting monitoring behind subway tunnels constructed using the shield tunneling method) is provided. This method employs an intelligent grouting system, primarily composed of an intelligent grouting station and an intelligent grouting management cloud platform. The intelligent grouting station, deployed on-site, is the core execution device of the intelligent grouting system, responsible for all data acquisition, transmission, recording, grout mixing, pressure adjustment, intelligent control of water pressure and grouting process construction, and one-click grouting. The intelligent grouting management cloud platform, deployed in the rear, is the data hub of the intelligent grouting system. It collects grouting construction process data and construction reports in real time, summarizes, monitors, analyzes, and stores the grouting data, providing technical support for intelligent grouting construction management, and can be connected to other intelligent platforms such as the project intelligent construction cloud platform.

[0057] Real-time monitoring and feedback evaluation are crucial for ensuring the effectiveness of grouting. This invention employs advanced sensors and data acquisition systems to monitor key parameters during the grouting process in real time. These key parameters include grouting pressure, the appearance of tunnel segments, and vibration data. This monitoring data allows for timely understanding of the dynamic changes in the grouting process, providing a basis for subsequent adjustments and optimizations. The monitoring system collects data from multiple measuring points, forming a three-dimensional monitoring network. Centralized management and analysis of this information allows for the identification of problems during grouting and rapid response. Specifically, if a significant deviation between the actual grouting pressure and the preset pressure is detected during grouting, the system will issue an alarm. Engineers can then immediately adjust the grouting parameters based on this feedback to ensure the effectiveness and safety of the grouting. Pressure sensors and various appearance inspection sensors are connected to the intelligent grouting station, transmitting real-time measurements to the station's data acquisition unit for subsequent processing, analysis, and intelligent control.

[0058] In some embodiments of the present invention, the appearance and vibration data of the tunnel segments are monitored during grouting to monitor and determine whether the grouting is complete and whether there is a possibility of instability. The monitoring methods include four types. For example... Figure 2As shown, one method involves adding strain gauges 2 in the potential area, specifically at the joints of the lining segments 1. Since the segments themselves are relatively rigid, their deformation needs to be monitored at the joints. Another method is to add laser displacement sensors 4 inside the tunnel for real-time observation. Changes in the distance between the segments and the fixed points are used to determine if there is a risk of instability, avoiding over-grouting. Over-grouting can cause the segments to bulge, resulting in changes in the distance between them and the fixed points. The third method involves monitoring the micro-vibrations generated by grouting. Specifically, accelerometers 3 are installed on some segments. Since the grout injection is a dynamic process, it causes vibrations in the segments. The vibrations caused by grout in a saturated or incomplete state are different. Therefore, micro-vibration monitoring can determine the saturation state of the grouting. Based on experience, thresholds are set: when the micro-vibrations are within the high threshold range, it is considered an incomplete state; when the micro-vibrations are within the low threshold range, it is considered a saturated state. Fourthly, a camera device 5 is installed inside the subway tunnel to monitor the grouting area of ​​the tunnel segments via video. By comparing pixel changes in different frames at specific time intervals, it determines whether grout seepage, segment misalignment, or floor slab heave has occurred. A judgment model can be trained using historical data through machine learning to identify the type of anomaly based on pixel changes. The laser displacement sensor 4 and camera device 5 are mounted on a flatbed trolley, which is connected to a track 6 via two wheel hubs. This allows the trolley to move along the track 6, enabling grouting monitoring of different tunnel sections. The connection between the laser displacement sensor 4 and camera device 5 and the flatbed trolley is retractable and rotatable, allowing for adjustments to the height and tilt angle of the laser displacement sensor 4 and camera device 5, increasing flexibility to adapt to the grouting monitoring requirements of different areas of the tunnel segments.

[0059] In the above embodiments, the specific judgment value ranges for these four monitoring methods need to be set differently in different projects. These ranges can be provided by staff based on experience or through other targeted methods. The strain value at the segment joint can be determined based on relevant data from existing projects where problems have already occurred.

[0060] In the above embodiment, the lining pipe is composed of several pipe segments 1 spliced ​​together, for example, six pipe segments, each occupying approximately 60 degrees, spliced ​​together to form a 360-degree tubular shape. Accelerometers for measuring micro-vibrations are installed on the pipe segments to measure the vibration caused by the grout flow during grouting. The number of accelerometers is determined according to the pipe segment size; preferably, the distance between two adjacent accelerometers is 0.5-2m. All accelerometers are arranged in an array on the pipe segments, preferably on the inner side of the pipe segments, i.e., the non-grouting side. Each accelerometer is correspondingly numbered and its location is marked so that the grout flow position and the grouting full area can be determined during data processing. Strain gauges are installed on the joints of adjacent pipe segments around the grouting area. Since the pipe segments themselves are rigid and not easily deformed, when grouting causes micro-deformation, it is more likely to be reflected at the joints. Therefore, placing strain gauges at the pipe segment joints is the most effective strain monitoring location. Strain gauges are evenly spaced along the joints, and each gauge is numbered and labeled to identify the specific strain gauge and location of strain during data processing. Laser displacement sensors inside the tunnel monitor for sudden instability. These sensors are positioned at fixed locations within the tunnel, pointing towards the inside of the grouting segment, and measure the distance from their location to the inner surface of the segment. A group of laser displacement sensors can be used, arranged in an array pointing towards the inside of the segment; that is, laser points form an array on the segment to monitor the distance from each location on the segment to the corresponding laser displacement sensor. A change in distance indicates a risk of instability at the corresponding location.

[0061] In the above embodiment, the accelerometer is set perpendicular to the tube segment, and the tube segment is tapped by excitation to monitor data.

[0062] In the above embodiments, in addition to visual monitoring, the amount of grout to be injected is also determined. When the amount of grout to be injected is relatively large, a fast grouting speed is used; when the amount of grout to be injected is relatively small, a slow grouting speed is used. The amount of grout to be injected is determined and reflected by the grouting pressure.

[0063] In some embodiments of the present invention, the importance of the four appearance monitoring methods is ranked as follows: micro-vibration, micro-strain, laser displacement, and image monitoring. Grouting is stopped if any of the four methods show abnormalities. Since vibration is caused by the movement of grout, micro-vibration mainly determines the position of the grout and generally does not show abnormalities. However, if an abnormality occurs, grouting must be stopped to find the cause. Micro-strain and laser displacement are used to judge the grouting effect. When micro-strain is detected at the joint, grouting is stopped, and the cause of the micro-strain is determined by combining the grouting volume and micro-vibration (when grouting reaches a certain level, the grout stops moving and the vibration disappears). This determines whether the micro-strain is caused by grouting completion or by deficiencies in the segment itself or in the segment's fixation. If grouting is determined to be complete, the grouting is ended; otherwise, the cause is found, repaired, and a second grouting is performed. When laser displacement detects an abnormality, it indicates a possibility of instability, grouting is stopped, and the cause of the abnormality is determined by combining the grouting volume and micro-vibration. After repair, a second grouting is performed. If grout leakage, segment misalignment, and / or base plate heave are detected by video monitoring, grouting should be stopped, and the cause of the abnormality should be determined based on the grouting volume (or grouting pressure), and corresponding countermeasures should be taken.

[0064] In some embodiments of the present invention, four dimensions—strain, micro-vibration, laser displacement, and image—are comprehensively judged, and the formula for comprehensive judgment is: F=f(k1×p1+k2×p2+k3×p3+k4×p4);

[0065] Where k1, k2, k3, and k4 are weighting coefficients, and p1, p2, p3, and p4 are the comprehensive strain parameter, comprehensive micro-vibration parameter, comprehensive displacement parameter, and comprehensive image parameter in the grouting area, respectively.

[0066] p1 = k11×p11 + k12×p12 + k13×p13 + ... + k1n×p1n, where k11-k1n are the weighting coefficients corresponding to each strain gauge, which are directly related to the distance; p11-p1n are the monitoring values ​​of each strain gauge (e.g., 0.1%).

[0067] p2 = k21×p21 + k22×p22 + k23×p23 + ... + k2n×p2n, where k21-k2n are the weighting coefficients of each accelerometer, which are directly related to the distance; p21-p2n are the ratios of the monitored values ​​of each accelerometer to the preset acceleration values.

[0068] p3 = k31×p31 + k32×p32 + k33×p33 + ... + k3n×p3n, where k31-k3n are the weighting coefficients of each laser displacement sensor, which are directly related to the distance; p31-p3n are the monitoring values ​​of each laser displacement sensor (e.g., 1%).

[0069] p4 is a comprehensive image parameter, specifically the proportion of change of the inner surface of the segment within a specific grouting area over time.

[0070] The formula for comprehensive judgment is: F=f(k1×p1+k2×p2+k3×p3+k4×p4);

[0071] Where k1, k2, k3, and k4 are weighting coefficients, and p1, p2, p3, and p4 are the comprehensive strain parameter, comprehensive micro-vibration parameter, comprehensive displacement parameter, and comprehensive image parameter in the grouting area, respectively.

[0072] p1 = k11×p11 + k12×p12 + k13×p13 + ... + k1n×p1n, where k11-k1n are the weighting coefficients corresponding to each strain gauge, which are directly related to the distance; p11-p1n are the monitoring values ​​of each strain gauge (e.g., 0.1%).

[0073] p2 = k21×p21 + k22×p22 + k23×p23 + ... + k2n×p2n, where k21-k2n are the weighting coefficients of each accelerometer, which are directly related to the distance; p21-p2n are the ratios of the monitored values ​​of each accelerometer to the preset acceleration values.

[0074] p3 = k31×p31 + k32×p32 + k33×p33 + ... + k3n×p3n, where k31-k3n are the weighting coefficients of each laser displacement sensor, which are directly related to the distance; p31-p3n are the monitoring values ​​of each laser displacement sensor (e.g., 1%).

[0075] p4 is a comprehensive image parameter, specifically the proportion of change of the inner surface of the segment within a specific grouting area over time.

[0076] In some embodiments of the present invention, during the entire tunnel grouting process, two or more of the four dimensions—strain, micro-vibration, laser displacement, and imaging—are selectively used for monitoring different grouting sections to achieve rapid and precise monitoring of the current grouting section. A rapid monitoring system can be composed of laser displacement and imaging, while a precise monitoring system can be composed of strain, micro-vibration, laser displacement, and imaging. The choice between rapid and precise monitoring for a given grouting section is determined based on its geological conditions and segment support conditions, minimizing the impact of strain and micro-vibration monitoring device installation workload on the overall grouting project while ensuring monitoring effectiveness. When using a rapid monitoring system, the strain and micro-vibration components are removed from the comprehensive judgment formula.

[0077] In some embodiments of the present invention, the judgment thresholds for strain, acceleration and micro-vibration at each level are determined by model test and numerical simulation. The judgment thresholds will vary greatly depending on the geological conditions of various working conditions, and the present invention does not impose a uniform limitation.

[0078] Any part of this invention not described in detail can be referred to in the prior art or in the art known to those skilled in the art. This embodiment does not limit such part and will not describe it in detail here.

[0079] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of the present invention.

Claims

1. A method for intelligent grouting control in subway tunnels, characterized in that, The method includes: During the secondary grouting process, the grouting pressure and the deformation and vibration data of the pipeline in the grouting area are monitored in real time to form a three-dimensional monitoring system. The monitoring data is analyzed to identify problems and control the grouting process, so as to achieve the purpose of rapid response.

2. The intelligent grouting control method for subway tunnels according to claim 1, characterized in that, When the grouting pressure is not greater than the initial pressure threshold, a rapid grouting strategy is adopted for grouting operation; When the grouting pressure is greater than the initial pressure threshold, a slow grouting speed is used for grouting operation; The rapid grouting strategy is as follows: the grouting pressure value is increased by 5% increments.

3. The intelligent grouting control method for subway tunnels according to claim 1, characterized in that, Several strain gauges are installed at the joints of the lining segments, and the relative deformation between the segments is determined by the strain values. When deformation of the tunnel segment is detected, grouting is stopped, and the deformation amount and current grouting pressure are used to determine whether the deformation is caused by full grouting or by an abnormality. If the cause is abnormal, find the cause and correct it before performing secondary grouting.

4. The intelligent grouting control method for subway tunnels according to claim 1, characterized in that, Several accelerometers are arrayed on the non-grouting side of the tunnel segment to determine the grouting fullness by monitoring the vibration caused to the tunnel segment during grout injection; specifically including: When the monitored vibration signal is within the preset low vibration threshold range, grouting is stopped, and the grouting in the corresponding area is judged to be full based on the current grouting pressure.

5. The intelligent grouting control method for subway tunnels according to claim 1, characterized in that, An array of laser displacement sensors is installed at a fixed location inside the tunnel. The laser of the sensor is pointed to the inside of the grouting area segment. By measuring the change in distance between the segment and the fixed point, it is determined whether there is a risk of instability. When a rapid increase or sudden change in segment displacement is detected, grouting should be stopped immediately, and the cause of the displacement should be determined based on the grouting pressure.

6. The intelligent grouting control method for subway tunnels according to claim 1, characterized in that, Based on the strain value at the joint of the pipe segment, the vibration acceleration value / micro-vibration value of the pipe segment, and the displacement value of the pipe segment monitored by the laser displacement sensor, it is comprehensively judged whether the current state is unsaturated grouting, about to be saturated, or whether there is a possibility of instability. When it is determined that the grouting is about to reach saturation, the grouting parameters are adjusted; when it is determined that there is a possibility of instability, grouting is stopped and corresponding instability response operations are carried out.

7. The intelligent grouting control method for subway tunnels according to claim 4, characterized in that, The accelerometers are arranged in an array with equal spacing. The spacing between any two adjacent accelerometers is 0.5-2m. This spacing is adjusted according to the specifications of the tunnel segments and geological conditions. The basic principle of adjustment is that the spacing is smaller when the segment size is small and the spacing is reduced when encountering adverse geological conditions.

8. The intelligent grouting control method for subway tunnels according to claim 1, characterized in that, Cameras are installed inside the subway tunnel to monitor the grouting area of ​​the tunnel segments. By comparing the pixel changes of two frames of images at specific time intervals, it is determined whether grout seepage, segment misalignment, or bottom slab heave has occurred.

9. A smart grouting control device for subway tunnels, characterized in that, The device is capable of implementing the intelligent grouting control method for subway tunnels as described in any one of claims 1-8; the device comprises: Intelligent grouting station: Deployed at the grouting site, it is the core execution equipment, configured to collect, transmit and record various grouting data, as well as perform data analysis and prepare grout and adjust grouting pressure based on the analysis results; Sensor module: Deployed inside the grouting tunnel and connected to the intelligent grouting station, it is configured to detect the strain, deformation, vibration and grout seepage of the tunnel segments; Intelligent grouting management cloud platform: Deployed in the back-end as a data hub, it is configured to collect construction process data and result reports in real time, summarize, monitor, analyze and store the data, and connect to other smart platforms to provide technical support for management.

10. The intelligent grouting control device for subway tunnels according to claim 9, characterized in that, The other intelligent platforms include the project's intelligent construction cloud platform.

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