A method and system for dynamic adjustment of advance grouting and improvement of cement soil slag

Abstract

The present invention discloses a method and system for dynamic adjustment of advance grouting and cement soil slag improvement, including: obtaining rock formation conditions based on exploration data; detecting cavities and their distribution in front of the tunnel; performing advance grouting: adjusting the water-cement ratio based on the characteristics of the cavities and rock formation conditions, performing advance grouting reinforcement, establishing an advance grouting database, and constructing a neural network model for the advance grouting database; analyzing the slag state: constructing an improved database neural network model; performing slag improvement: issuing a grouting command to start grouting when the shield machine begins excavation; performing environmental monitoring to obtain monitoring data; and determining the slag improvement effect: judging whether the slag improvement effect meets the requirements based on the monitoring data. The present invention can construct advance grouting parameters that meet excavation requirements during construction, enabling continuous and systematic improvement of "cement soil" during shield excavation, thus achieving automation, intelligence, and refinement of slag improvement.

Description

Technical Field

[0001] The invention belongs to the technical field of tunnel construction, and in particular relates to a method and system for dynamic adjustment of advance grouting and improvement of cement soil slag. Background Art

[0002] With the growing demand for rapid transportation infrastructure and the advancement of construction machinery, balanced shield tunneling has become widely used in urban shield construction due to its advantages such as low environmental impact, safe construction, and rapid construction. Currently, different ground types pose different risks to shield tunneling. Based on practical engineering experience, it has been found that shield machine parameters are difficult to control when tunneling through unevenly hard and soft ground. The shield machine has high thrust, high cutterhead torque, and slow propulsion speed, which can easily cause ground collapse and pose a safety hazard. Pre-reinforcement of the ground due to the influence of old buildings or pipelines is also a challenge. Furthermore, the cutting of cement soil is prone to the risk of "mud cake" formation and severe tool wear. Therefore, to address these risks, pre-grouting reinforcement of the ground and soil modification of the cement soil are necessary. The effectiveness of grouting and soil modification significantly impacts tunneling efficiency and project quality. The effectiveness of pre-grouting is determined by the shield machine's excavation parameters and ground settlement values. For soil debris, the main factor used is its plasticity, which affects the efficiency of the shield machine, such as its discharge efficiency, the likelihood of cutter jamming, and excavation speed. Furthermore, the plasticity of soil debris also affects the control of ground disturbance and ground settlement.

[0003] The existing technology lacks unified scheduling in all links, various parameters cannot be updated in real time, construction technology tends to be controlled by experience, and the monitoring link is mainly based on manual qualitative judgment, which is time-consuming and labor-intensive. It is impossible to establish a database, and the relevant laws are not easy to promote and apply. Summary of the Invention

[0004] In order to solve the above-mentioned deficiencies in the prior art, the present invention provides a method and system for advanced grouting and dynamic adjustment of cement soil slag improvement.

[0005] In order to achieve the above technical objectives, the technical solution adopted by the present invention is:

[0006] A method for advanced grouting and dynamic adjustment of cement soil slag improvement, comprising:

[0007] S1: Obtain rock formation conditions based on exploration data; detect cavities in front of the tunnel and their distribution;

[0008] S2: Perform advance grouting: Adjust the water-cement ratio based on the cavity characteristics and rock formation conditions, perform advance grouting reinforcement, and establish an advance grouting database to record the current geological conditions, advance grouting parameters, and the advancement state parameters after grouting. A neural network model for the advance grouting database is constructed to show the corresponding relationship between the advancement state parameters, geological conditions, and advance grouting parameters.

[0009] S3: Analyze the soil state: inherit the advanced grouting parameters, determine the current soil improvement parameters, perform soil improvement on cement soil, analyze the current soil improvement state, obtain the current soil improvement state parameters, and construct an improved database neural network model that shows the corresponding relationship between the advanced grouting parameters and the current soil improvement state parameters. The improved database neural network model outputs the soil improvement parameters corresponding to the given parameters, including modifier concentration, injection ratio, grouting pressure, and grouting speed.

[0010] S4: Perform soil improvement: Set the grouting material, grouting pressure, grouting speed, and grouting time according to the output of step S3, and issue a grouting command to start grouting when the shield machine starts excavating;

[0011] S5: Conduct environmental monitoring to obtain monitoring data on the current parameters of the slag improvement status, including the secant angle of the slag collapse, surface settlement, shield slag output, and shield cutter head torque;

[0012] S6: Determine the effect of slag improvement, and determine whether the slag improvement effect meets the requirements based on the monitoring data of step S5: If not, enter step S3 to calculate the current slag improvement parameters required for the current state; if so, summarize the entire iterative process, calculate the current slag improvement parameters and store them in the improvement database.

[0013] Preferably, in step S1, a high-density electrical method instrument is used to perform advance cavity detection.

[0014] Furthermore, in step S2, the geological conditions include cavity volume, cavity distribution, cavity water content, and rock formation conditions; the advance grouting parameters include: cement type, water-cement ratio, grouting pressure, grouting speed, and slurry setting time; and the post-grouting advancement state parameters include the initial cutterhead thrust value, the initial cutterhead torque value, and the predicted initial surface settlement value.

[0015] Furthermore, in step S3, the main body of the slag improvement is the cement soil cut off by the shield machine, and the improving agent is mainly bentonite slurry and supplemented by foaming agent.

[0016] Preferably, the proportion of the bentonite slurry is 1:7.5-8.5, the proportion of the foaming agent is 3%, and the injection ratio of the foaming agent is 24.3% to 31.5%.

[0017] Furthermore, the grouting pressure adopts the pressure control tiered design principle, and the main control pressure of grouting is set to 1 to 2 times the groundwater pressure. After the pressure is set independently, the grouting pressure increases from small to large, and the grouting volume decreases from large to small, and finally reaches or approaches the designed grouting final pressure; it is adjusted in multiple stages according to the grouting pressure.

[0018] Furthermore, the method of adjusting the grouting pressure in multiple stages is as follows:

[0019] S421: When the grouting pressure is close to 70% of the designed final pressure, the grouting flow rate is adjusted to 80% of the initial grouting flow rate, and the injection is continued, and the pressure gradually increases;

[0020] S422: When the grouting pressure rises to 80% of the designed final pressure, the grouting flow rate is adjusted to 60% of the initial grouting flow rate, and the injection is continued, and the pressure gradually increases;

[0021] S423: When the grouting pressure rises to 90% of the designed final pressure, the grouting flow rate is adjusted to 40% of the initial grouting flow rate, and the injection is continued, and the pressure gradually increases;

[0022] S424: When the grouting pressure rises to the designed final pressure, the grouting pump stops working and the grouting is completed.

[0023] Furthermore, in step S5, the environmental monitoring includes at least propulsion system parameters, cutting system parameters, conveyor system parameters, and soil state parameters. Step S5 includes:

[0024] S51: Extract the shield machine's built-in parameters, including thrust, torque, penetration, and tunneling speed parameters;

[0025] S52: extracting the pressure, speed and slag discharge parameters of the screw conveyor;

[0026] S53: Randomly sample the improved slag discharged from the conveyor, use the laser scanning unit to obtain the contour cloud map of the collapsed soil in real time, automatically calculate the soil state parameters, and obtain the secant angle and slump of the slag collapse body;

[0027] S54: Based on the digital twin of ground settlement, the settlement change law of shield construction is constructed, and a settlement measurement method with prediction as the main method and measurement as the auxiliary method is adopted.

[0028] Preferably, the secant angle index range of the slag slump body is 22° to 30°, and the slump range is 150 to 200 mm. A system using the above-mentioned advanced grouting and dynamic adjustment method for cement soil slag improvement includes an advanced detection module: used to detect the cavities in the front side of the tunnel and their distribution;

[0029] Advance grouting module: performs advance grouting, establishes an advance grouting database, and constructs a neural network model for the advance grouting database;

[0030] Slag soil status analysis module: performs slag soil improvement for cement soil, inherits advanced grouting parameters, determines current slag soil improvement parameters, analyzes the current slag soil improvement status, and constructs an improvement database neural network model;

[0031] Muck improvement execution module: issues grouting instructions when the shield machine starts excavation, and sets grouting materials, grouting pressure, grouting speed, and grouting time according to the instructions of the muck state analysis module;

[0032] Environmental monitoring module: conduct environmental monitoring and obtain monitoring data of current slag improvement status parameters;

[0033] Judgment module: judge the improvement effect based on monitoring data.

[0034] Furthermore, the slag improvement execution module at least includes:

[0035] Grouting material selection unit: used to select the required improver;

[0036] Grouting pressure regulating unit: adjusts the grouting pressure in real time according to the pressure regulating range;

[0037] Grouting time adjustment unit: adjusts the grouting time according to the grouting adjustment range;

[0038] Grouting speed adjustment unit: According to the shield advancement rate and the preset matching standard, the corresponding grouting speed is matched.

[0039] The beneficial effects of the present invention are:

[0040] The present invention can construct advance grouting parameters that meet the excavation requirements based on machine learning during the construction process, and can realize continuous, uninterrupted and systematic improvement of "cement soil" during shield excavation. Compared with the existing technology, the method of the present invention realizes the automation, intelligence and refinement of slag improvement, and can adjust the slag improvement parameters in real time according to the slag status of the current soil layer, and monitor and verify the improvement effect in real time. The method of the present invention overcomes the problems of traditional slag improvement such as certain empiricism, randomness, redundancy, uncertainty and discontinuity. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0042] Figure 1 is a flow chart of the method of the present invention;

[0043] Figure 2 This is the structure diagram of the neural network model of the advanced grouting database;

[0044] Figure 3 This is the structural diagram of the improved database neural network model. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application for protection, but merely represents the selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0046] A method for advanced grouting and dynamic adjustment of cement soil slag improvement, comprising:

[0047] S1: Use high-density electrical method to conduct advance detection along the line to identify voids and their distribution;

[0048] A high-density electrical method instrument is used for advanced geological surveying. The survey data is processed and transmitted to the shield control center via a temporary network within the tunnel. The survey data includes cavity volume, cavity distribution, cavity water content, and rock formation conditions, which are stored in the shield control center through exploration data.

[0049] S2: Carry out advance grouting, adjust the water-cement ratio according to the characteristics of the cavity and the rock formation conditions, carry out advance grouting reinforcement, and establish an advance grouting database. The advance grouting parameters include: cement type, water-cement ratio, grouting pressure, grouting speed, and slurry setting time; record the current geological conditions and advance grouting parameters. The geological conditions include cavity volume, cavity distribution, cavity moisture content, and rock formation conditions. Record the propulsion state parameters after grouting, including the cutterhead thrust value and cutterhead torque value, and the initial surface settlement prediction value; use machine learning functions to establish an advance grouting database neural network model of cavity volume, cavity distribution, cavity moisture content, rock formation conditions, cement type, water-cement ratio, grouting volume, grouting pressure, slurry setting time and initial cutterhead thrust, initial cutterhead torque, and initial surface settlement prediction value (the values ​​at this time are obtained by digital twin prediction).

[0050] Using the recorded current geological conditions, advanced grouting parameters, and post-grouting advancement parameters, a neural network model for the advanced grouting database was constructed, which correlated the advancement parameters with the geological conditions and advanced grouting parameters. Since grouting requires downtime and solidification before tunneling can resume, the values ​​in the advanced grouting database are used to prepare for the next grouting injection.

[0051] Specifically, during advance grouting, the machine needs to be shut down and the cement soil strength needs to be waited for to meet the standard. The advance distance of each grouting is 10 meters from the cutterhead. Here, one grouting is adopted according to the recognition result of the neural network, and the grouting effect provides a reference for the next advance grouting. All the above information is stored in the advance grouting database and recorded separately for each time. The advance grouting neural network model needs to be updated every time it is recorded. The initial parameters need to be determined through experiments and experience. The construction of the advance grouting neural network will be started after the cumulative number of times reaches 100. The grouting volume, grouting speed, grouting pressure, cutterhead thrust torque value, and surface settlement value are shared with the environmental monitoring module and the slag improvement execution module.

[0052] S3: Analyze the slag state: inherit the advanced grouting parameters, determine the current slag improvement parameters, improve the slag for cement soil, analyze the current slag improvement state, obtain the current slag improvement state parameters, and construct an improved database neural network model of the correspondence between the advanced grouting parameters and the current slag improvement state parameters and the current slag improvement parameters. The improved database neural network model outputs the slag improvement parameters corresponding to the given parameters, including modifier concentration, injection ratio, grouting pressure, and grouting speed.

[0053] The modified material is cut cement soil, and the modifying agent is primarily bentonite slurry, supplemented by a foaming agent. The bentonite slurry ratio is 1:7.5-8.5, and the foaming agent ratio is 3%. The foaming agent injection ratio is 24.3% to 31.5%. Machine learning is used to determine the modifying agent concentration, injection ratio, grouting pressure, and grouting speed that correspond to the given parameters.

[0054] S4: Perform soil improvement. Set the grouting material, grouting pressure, grouting speed, and grouting time according to the instructions output from step S3. Issue the grouting instruction when the shield machine starts excavating. Specifically, soil improvement is performed by the soil improvement execution module. The soil improvement execution module includes at least: a grouting material selection unit, a grouting pressure adjustment unit, a grouting time adjustment unit, and a grouting speed adjustment unit.

[0055] S41: Use the grouting material selection unit to automatically select the required modifier, which is common to the cement selection of the advance grouting module;

[0056] S42: A grouting pressure regulating unit is used. The grouting pressure adopts the principle of pressure control cascade design. The main grouting pressure is set to 1 to 2 times the groundwater pressure. After the pressure is set independently, the grouting pressure increases from small to large, and the grouting volume decreases from large to small, eventually reaching or approaching the designed grouting final pressure. The grouting pressure is adjusted in multiple stages according to the following:

[0057] S421: When the grouting pressure is close to 70% of the designed final pressure, the grouting flow rate is adjusted to 80% of the initial grouting flow rate, and the injection is continued, and the pressure gradually increases;

[0058] S422: When the grouting pressure rises to 80% of the designed final pressure, the grouting flow rate is adjusted to 60% of the initial grouting flow rate, and the injection is continued, and the pressure gradually increases;

[0059] S423: When the grouting pressure rises to 90% of the designed final pressure, the grouting flow rate is adjusted to 40% of the initial grouting flow rate, and the injection is continued, and the pressure gradually increases;

[0060] S424: When the grouting pressure rises to the designed final pressure, the grouting pump stops working and the grouting is completed.

[0061] The grouting sequence design can select the number of sequences according to the actual situation. The PLC control logic relationship is compiled through the above grouting pressure control principle to ensure full grouting filling and grouting quality.

[0062] S43: using a grouting time adjustment unit to adjust the grouting time according to a grouting adjustment range;

[0063] S44: Using the grouting speed adjustment unit, a corresponding grouting speed is matched according to the shield advancement rate and a preset matching standard.

[0064] The concept of grouting flow control is to adopt the principle of grouting speed cascade design. The initial large flow injection is completed through PLC control. After reaching the set pressure, the flow rate is automatically reduced to a certain percentage; then the injection continues, and the pressure decreases. When the pressure reaches the design pressure again, the flow rate is reduced again. After the pressure is reduced three times, the grouting stops.

[0065] Start the grouting of liquid A (such as bentonite mud) system and quickly reach the set flow rate; at the same time, the liquid B (such as foam agent) system adopts follow-up grouting, that is, the liquid A grouting flow rate signal is collected and processed, and grouting is performed according to the set ratio. The value changes with the change of liquid A flow rate, and the set ratio injection is always maintained. The time from startup to the specified ratio is generally 10 to 25 seconds, which can ensure the quality of dual-liquid grouting.

[0066] S5: Conduct environmental monitoring to obtain monitoring data on the current slag improvement state parameters, including the secant angle of the slag collapse, surface settlement, shield slag output, and shield cutter head torque; environmental monitoring parameters include at least propulsion system parameters, cutting system parameters, conveyor system parameters, and soil state parameters, specifically:

[0067] S51: Extracting propulsion system parameters refers to the shield machine's own parameters, including thrust, torque, penetration, and tunneling speed parameters;

[0068] S52: extracting the pressure, speed and slag discharge parameters of the screw conveyor;

[0069] S53: Randomly sample the improved slag discharged from the conveyor, use the laser scanning unit to obtain the contour cloud map of the collapsed soil in real time, and automatically calculate the soil state parameters; among which, the secant angle index range of the slag collapse body is 22°~30°, and the slump range is 150~200mm.

[0070] S54: Based on the digital twin of ground settlement, the settlement change law of shield construction is constructed, and a settlement measurement method with prediction as the main method and measurement as the auxiliary method is adopted.

[0071] S6: Determine the effect of soil improvement;

[0072] Compare the data monitored in step S5 with the specifications to determine whether the current slag improvement effect meets the requirements: if not, enter step S3 to calculate the slag improvement parameters required for the current state; if so, summarize the entire iterative process, calculate the current slag improvement parameters and store them in the improvement database.

[0073] The present invention also provides a system using the above-mentioned advanced grouting and dynamic adjustment method for improving cement soil residue, comprising:

[0074] Advance detection module: used to detect cavities and their distribution in the front side of the tunnel;

[0075] Advance grouting module: performs advance grouting, establishes an advance grouting database, records the advancement state parameters after grouting, and constructs a neural network model for the advance grouting database;

[0076] Muck state analysis module: inherits the advanced grouting parameters, determines the current muck improvement parameters, performs muck improvement on cement soil, analyzes the current improvement status, obtains the current muck improvement status parameters, and constructs an improvement database neural network model;

[0077] The slag improvement execution module: issues a grouting instruction when the shield machine starts to excavate, and sets the grouting material, grouting pressure, grouting speed, and grouting time according to the instructions of the slag state analysis module; specifically, the slag improvement execution module includes at least: a grouting material selection unit: used to select the required improver; a grouting pressure adjustment unit: adjusts the grouting pressure in real time according to the pressure adjustment range; a grouting time adjustment unit: adjusts the grouting time according to the grouting adjustment range; a grouting speed adjustment unit: matches the corresponding grouting speed according to the shield advancement rate and the preset matching standard.

[0078] Environmental monitoring module: conduct environmental monitoring and obtain monitoring data of current slag improvement status parameters;

[0079] Judgment module: judge the improvement effect of slag soil.

[0080] Of course, the present invention may have many other embodiments. Without departing from the spirit and essence of the present invention, those skilled in the art may make various corresponding changes and modifications based on the present invention, but these corresponding changes and modifications should all fall within the scope of protection of the claims attached to the present invention.

Claims

1. A method for advanced grouting and dynamic adjustment of cement soil slag improvement, characterized by: include: S1: Obtain rock formation conditions based on exploration data; detect cavities in front of the tunnel and their distribution; S2: Perform advance grouting: Adjust the water-cement ratio based on the cavity characteristics and rock formation conditions, perform advance grouting reinforcement, and establish an advance grouting database to record the current geological conditions, advance grouting parameters, and the advancement state parameters after grouting. A neural network model for the advance grouting database is constructed to show the corresponding relationship between the advancement state parameters, geological conditions, and advance grouting parameters. S3: Analyze the soil state: inherit the advanced grouting parameters, determine the current soil improvement parameters, perform soil improvement on cement soil, analyze the current soil improvement state, obtain the current soil improvement state parameters, and construct an improved database neural network model that shows the corresponding relationship between the advanced grouting parameters and the current soil improvement state parameters. The improved database neural network model outputs the soil improvement parameters corresponding to the given parameters, including modifier concentration, injection ratio, grouting pressure, and grouting speed. S4: Perform soil improvement: Set the grouting material, grouting pressure, grouting speed, and grouting time according to the output of step S3, and issue a grouting command to start grouting when the shield machine starts excavating; S5: Conduct environmental monitoring to obtain monitoring data on the current parameters of the slag improvement status, including the secant angle of the slag collapse, real-time surface settlement, shield slag output, and shield cutter head torque; S6: Determine the effect of slag improvement, and determine whether the slag improvement effect meets the requirements based on the monitoring data of step S5: If not, enter step S3 to calculate the slag improvement parameters required for the current state. If so, summarize the entire iterative process, calculate the current slag improvement parameters and store them in the improvement database.

2. The method for advanced grouting and dynamic adjustment of cement soil slag improvement according to claim 1 is characterized in that: In step S1, a high-density electrical method instrument is used to perform advance cavity detection.

3. The method for advanced grouting and dynamic adjustment of cement soil slag improvement according to claim 1 is characterized in that: In step S2, the geological conditions include cavity volume, cavity distribution, cavity water content, and rock formation conditions; the advance grouting parameters include: cement type, water-cement ratio, grouting pressure, grouting speed, and slurry setting time; the post-grouting advancement state parameters include the initial cutterhead thrust value, the initial cutterhead torque value, and the predicted initial surface settlement value.

4. The method for advanced grouting and dynamic adjustment of cement soil slag improvement according to claim 1 is characterized in that: In step S3, the main body of the slag improvement is the cement soil cut by the shield machine, and the improving agent is mainly bentonite slurry and supplemented by foaming agent.

5. The method for advanced grouting and dynamic adjustment of cement soil slag improvement according to claim 4 is characterized in that: The proportion of the bentonite slurry is 1:7.5-8.5, the proportion of the foaming agent is 3%, and the injection ratio of the foaming agent is 24.3%-31.5%.

6. The method for advanced grouting and dynamic adjustment of cement soil slag improvement according to claim 1, characterized in that: The grouting pressure adopts the pressure control cascade design principle. The main control pressure of grouting is set to 1 to 2 times the groundwater pressure. After the pressure is set independently, the grouting pressure increases from small to large, and the grouting volume decreases from large to small, and finally reaches or approaches the designed grouting final pressure; it is adjusted in multiple stages according to the grouting pressure.

7. The method for advanced grouting and dynamic adjustment of cement soil slag improvement according to claim 6, characterized in that: The method of adjusting the grouting pressure in multiple stages is as follows: S421: When the grouting pressure is close to 70% of the designed final pressure, the grouting flow rate is adjusted to 80% of the initial grouting flow rate, and the injection is continued, and the pressure gradually increases; S422: When the grouting pressure rises to 80% of the designed final pressure, the grouting flow rate is adjusted to 60% of the initial grouting flow rate, and the injection is continued, and the pressure gradually increases; S423: When the grouting pressure rises to 90% of the designed final pressure, the grouting flow rate is adjusted to 40% of the initial grouting flow rate, and the injection is continued, and the pressure gradually increases; S424: When the grouting pressure rises to the designed final pressure, the grouting pump stops working and the grouting is completed.

8. The method for advanced grouting and dynamic adjustment of cement soil slag improvement according to claim 1, characterized in that: In step S5, the environmental monitoring includes at least propulsion system parameters, cutting system parameters, conveyor system parameters, and soil state parameters. Step S5 includes: S51: Extract the shield machine's built-in parameters, including thrust, torque, penetration, and tunneling speed parameters; S52: extracting the pressure, speed and slag discharge parameters of the screw conveyor; S53: Randomly sample the improved slag discharged from the conveyor, use the laser scanning unit to obtain the contour cloud map of the collapsed soil in real time, automatically calculate the soil state parameters, and obtain the secant angle and slump of the slag collapse body; S54: Based on the digital twin of ground settlement, the settlement change law of shield construction is constructed, and a settlement measurement method with prediction as the main method and measurement as the auxiliary method is adopted.

9. The method for advanced grouting and dynamic adjustment of cement soil slag improvement according to claim 8, characterized in that: The secant angle index range of the slag slump body is 22°~30°, and the slump range is 150~200mm.

10. A system using the advanced grouting and dynamic adjustment method for improving cement soil residue according to any one of claims 1 to 9, characterized in that: include Advance detection module: used to detect cavities and their distribution in the front side of the tunnel; Advance grouting module: performs advance grouting, establishes an advance grouting database, and constructs a neural network model for the advance grouting database; Slag soil status analysis module: performs slag soil improvement for cement soil, inherits advanced grouting parameters, determines current slag soil improvement parameters, analyzes the current slag soil improvement status, and constructs an improvement database neural network model; Muck improvement execution module: issues grouting instructions when the shield machine starts excavation, and sets grouting materials, grouting pressure, grouting speed, and grouting time according to the instructions of the muck state analysis module; Environmental monitoring module: conduct environmental monitoring and obtain monitoring data of current slag improvement status parameters; Judgment module: judge the improvement effect based on monitoring data.

11. The system according to claim 10, characterized in that: The slag improvement execution module at least includes: Grouting material selection unit: used to select the required improver; Grouting pressure regulating unit: adjusts the grouting pressure in real time according to the pressure regulating range; Grouting time adjustment unit: adjusts the grouting time according to the grouting adjustment range; Grouting speed adjustment unit: According to the shield advancement rate and the preset matching standard, the corresponding grouting speed is matched.

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