A multi-unit cooperation method and device for a shield tunnel construction process

Abstract

The application relates to the technical field of tunnel and underground engineering construction, and discloses a multi-unit cooperation method and device for shield tunnel construction process. The application aims to solve the technical problems that information cannot be circulated between different units and the process circulation is not smooth in the prior art. The application comprises the following steps: S1, constructing a data center; S2, developing a cooperative control platform; S3, establishing a data interaction mechanism; and S4, configuring a prediction identification algorithm. The application realizes information sharing in the shield tunnel construction process: no matter where the tunnel construction site production management personnel are, the personnel can master the current site production condition in real time by using the multi-agent cooperative control platform, and the decision-making efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of tunnel and underground engineering construction technology, and in particular to a multi-unit collaborative method and apparatus for shield tunnel construction. Background Technology

[0002] A tunnel boring machine (TBM) is an advanced tunnel construction equipment integrating mechanical, electrical, hydraulic, control, information technology, and sensor technology. It is widely used in urban rail transit and cross-river / sea tunnel construction and is known as an "underground factory." It comprises multiple subsystems with relatively independent functions, such as the cutterhead drive system, propulsion system, attitude control system, circulating muck removal system, synchronous grouting system, and tail grease sealing system. Traditionally, its use relies on operators in the cab issuing commands from a host computer to the PLCs (Programmable Logic Controllers) of each system, causing each system to execute its predetermined functions to complete the construction task.

[0003] With the continuous integration of new-generation information technologies such as big data and artificial intelligence into shield tunnel construction, some processes or systems have acquired a certain degree of "perception-decision-execution-feedback" capabilities, achieving intelligent operation. Examples include cutterhead systems, propulsion systems, attitude control systems, circulating slag removal systems, material transport systems, and structural component assembly systems, all capable of independently completing tasks and thus considered intelligent agents. However, shield tunnel construction relies on the efficient collaboration of multiple processes / intelligent agents. Although each intelligent agent possesses some automated and intelligent operation capabilities, the lack of interoperability and correlation between their operating states and parameters, coupled with the independent operation of major processes lacking coordination, still prevents information from flowing between different units, creating information silos and hindering overall construction efficiency.

[0004] Therefore, there is an urgent need to propose a multi-unit collaborative method and device for the shield tunnel construction process. Summary of the Invention

[0005] In view of the above technical problems, this disclosure provides a multi-unit collaborative method and device for shield tunnel construction, which solves the technical problems of information not being able to flow between different units and the process cycle not being smooth in the prior art. This improves overall construction efficiency and management capabilities.

[0006] According to one aspect of this disclosure, a multi-unit collaborative method for shield tunnel construction is provided, comprising the following steps: S1 Data Center Construction: Establish a data center at the shield tunnel construction site to store and manage multimodal data from multiple units during the shield tunnel construction process; S2 Development Collaborative Management and Control Platform: Develop a multi-unit collaborative management and control platform for the shield tunnel construction process. The platform is used for managers to interact with each unit and query the operating status and data of each unit in real time. S3 establishes a data interaction mechanism: establishing a data interaction method between units to realize cross-system information sharing for multi-process collaborative operations; S4 Configuration Prediction and Identification Algorithm: Deploy a prediction or identification algorithm trained on historical data on the multi-unit collaborative management and control platform to generate prediction or early warning information to assist decision-making.

[0007] In some embodiments of this disclosure, the data center in S1 is connected to each unit through multiple data transmission terminals. The multiple units include a shield tunneling unit, a slurry pressure control unit, a slurry circulation and muck removal unit, a shield equipment key component status monitoring unit, a structural component assembly unit, a tunnel material transportation unit, and a tunnel environment protection unit. Each unit corresponds to at least one data transmission terminal.

[0008] In some embodiments of this disclosure, the data collected by each unit in S2 includes: Shield tunneling unit: cutterhead drive system: cutterhead speed, rotation direction, cutterhead torque, current, voltage, torque, and power of each drive motor; propulsion system: propulsion speed, hydraulic cylinder pressure in each zone, hydraulic cylinder stroke, propulsion force of each hydraulic cylinder, and total propulsion force; attitude control system: horizontal and vertical deviation of the cutter ring, horizontal and vertical deviation of the shield tail, horizontal and vertical trends, roll angle, and pitch angle; synchronous grouting and grout injection system: pressure and flow rate of each injection pipeline, and cumulative grouting volume per ring; shield tail sealing and grease injection system: pressure of each injection pipeline in each sealing cavity, outlet pressure of the shield tail grease pump, and grease consumption per ring. Slurry tank pressure control unit: air cushion tank pressure, air cushion tank mud level, slurry tank top pressure, current cutting ring top water and soil pressure, valve opening and closing status, air tank pressure; Slurry circulation slag discharge unit: slurry inlet and outlet flow rate, slurry inlet and outlet flow rate difference, slurry inlet and outlet density, slurry inlet and outlet pipeline pressure, slurry inlet and outlet pump speed, drive motor current, inlet and outlet pressure of each slurry inlet and outlet pump, valve opening and closing status; Key component status monitoring unit for tunnel boring machine (TBM) equipment: temperature of each inner and outer sealing cavity of the main bearing, temperature of the inner and outer sealing cooling water, and flow rate of the inner and outer sealing cooling water; temperature, viscosity, water content, dielectric constant, density, ferromagnetic content, and non-ferromagnetic content of the main bearing lubricating oil; temperature, viscosity, density, dielectric constant, saturation, and water content of the hydraulic oil in the TBM propulsion system; wear amount, rotation state, temperature, and load of the TBM cutterhead; and acceleration of the drive motors of each main bearing in the horizontal, vertical, and forward / backward directions. Structural component assembly unit: working status of segment hoist, segment feeder, segment assembler, next ring segment assembly point, and working status of arc component assembler; Material transport unit within the tunnel: location of material transport vehicles within the tunnel, type of transported goods, direction of travel, speed, and obstacle perception results; Tunnel Environmental Protection Unit: Contents of methane, hydrogen sulfide, oxygen, carbon dioxide, and carbon monoxide in the exhaust area of ​​the tunnel boring machine; operating frequency of the fan inverter, fan current, voltage, power, wind speed, and power consumption.

[0009] In some embodiments of this disclosure, the data interaction methods between the units in S3 include at least one of the following collaborative operations: Tunneling-material transportation coordination: Based on the tunneling status, the estimated completion time, the consumption of synchronous grouting slurry and tail sealant grease for each ring, and the current remaining quantity, arrange the material transportation unit in the tunnel to organize the transportation of synchronous grouting slurry and tail sealant grease. Structural component assembly-material transportation coordination: Based on the assembly point information of the next ring segment, determine the transportation demand of segments and curved components, arrange segment transportation and generate a transportation order, and confirm the transportation by the tunnel management personnel after the transportation arrives, thus forming an information loop; Collaborative monitoring of key components of tunneling-shield equipment: Real-time analysis of the changing trends of monitoring parameters is performed using a trend prediction algorithm for the status of key components of the shield, and early warning information is provided to the main shield operator through a multi-unit collaborative management and control platform; Tunneling-Assembly-Tunnel Environment Protection Coordination: Monitoring and early warning information from the tunnel environment protection unit is pushed to structural component assembly workers and tunnel boring machine operators through a multi-unit collaborative management and control platform to determine whether to continue operations or stop the machine to avoid risks.

[0010] In some embodiments of this disclosure, predictive control algorithms are deployed in each unit of S4, including: The shield tunneling unit deploys prediction algorithms for total thrust, cutterhead rotation speed, penetration depth, thrust speed, hydraulic cylinder pressure in each zone of the thrust system, synchronous grouting slurry consumption, and shield tail sealing grease consumption, and recommends suggested values ​​for the above parameters in real time. Among them, the predicted values ​​of cutterhead rotation speed, thrust speed, and hydraulic cylinder pressure in each zone of the thrust system directly participate in the control of the tunneling process. The mud pressure control unit deploys a mud chamber pressure prediction algorithm to predict the pressure at the top of the mud chamber in real time based on the geological survey report and the current mileage location and burial depth, and indirectly controls the pressure at the top of the mud chamber by adjusting the pressure of the air cushion chamber. The slurry circulation and slag discharge unit deploys slurry flow prediction algorithms and decision tree algorithms to control the slurry circulation system to switch between tunneling, segment assembly, and shutdown working modes. The key component status monitoring unit of the tunnel boring machine is equipped with a data trend prediction algorithm to provide real-time information on the sealing status of the main bearing, vibration data of the main bearing drive motor, oil parameters of the main bearing lubricating oil and propulsion system hydraulic oil, cutter wear, rotation status, temperature, and load trends. The structural component assembly unit is equipped with a comprehensive positioning algorithm based on image recognition and laser ranging to achieve high-precision autonomous assembly of segments and curved components; The material transport unit inside the tunnel is equipped with an obstacle detection algorithm based on infrared and visible light to assist the transport vehicle driver.

[0011] A multi-unit collaborative device for shield tunnel construction includes multiple work units, each corresponding to a different process in the shield tunnel construction process, and each work unit has data acquisition, execution, and feedback functions. Each work unit is connected to a data transmission terminal to collect the operating status and data of each work unit; Each data transmission terminal is connected to the data center via a local area network to store and manage multimodal data from each work unit; The data center is connected to the collaborative management and control platform, which is used to query the operating status and data of each work unit in real time, and to realize information interaction between users and each work unit; The data center automatically distributes information from specific work units to other relevant work units according to preset rules, so as to achieve process collaboration.

[0012] The beneficial effects of this invention are as follows: (1) Realize information sharing in the shield tunnel construction process: enable production management personnel at the tunnel construction site to grasp the current on-site production status in real time by using the multi-agent collaborative management and control platform, regardless of their location, thereby improving decision-making efficiency.

[0013] (2) Enhance equipment perception capabilities: Utilize a series of data prediction algorithms to promptly grasp the equipment operating status, achieve "early detection and early handling", and avoid "operating with defects" of tunnel boring equipment.

[0014] (3) Improve the efficiency of process connection and conversion: solve the problem of "idle work" caused by poor information communication in the three core processes of tunnel excavation, assembly and material transportation, such as the untimely supply of synchronous grouting slurry and shield tail grease causing shield tunneling to stop, and the failure to grasp the segment ring position outside the tunnel in time, resulting in the wrong sequence of segment entering the tunnel, and improve the efficiency of tunnel construction. Attached Figure Description

[0015] Figure 1 A flowchart illustrating the multi-unit collaborative method architecture for shield tunnel construction. Detailed Implementation

[0016] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention. Example 1

[0017] This example discloses a multi-unit collaborative method for the shield tunnel construction process. (See also...) Figure 1 This includes the following steps: S1 Data Center Construction: Establish a data center at the shield tunnel construction site to store and manage multimodal data from multiple units during the shield tunnel construction process; S2 Development Collaborative Management and Control Platform: Develop a multi-unit collaborative management and control platform for the shield tunnel construction process. The platform is used for managers to interact with each unit and query the operating status and data of each unit in real time. S3 establishes a data interaction mechanism: establishing a data interaction method between units to realize cross-system information sharing for multi-process collaborative operations; S4 Configuration Prediction and Identification Algorithm: Deploy a prediction or identification algorithm trained on historical data on the multi-unit collaborative management and control platform to generate prediction or early warning information to assist decision-making.

[0018] The data center described in S1 is connected to each unit through multiple data transmission terminals. The multiple units include a shield tunneling unit, a slurry pressure control unit, a slurry circulation and muck removal unit, a shield equipment key component status monitoring unit, a structural component assembly unit, a tunnel material transportation unit, and a tunnel environment protection unit. Each unit corresponds to at least one data transmission terminal.

[0019] The data collected by each unit in S2 includes: Shield tunneling unit: cutterhead drive system: cutterhead speed, rotation direction, cutterhead torque, current, voltage, torque, and power of each drive motor; propulsion system: propulsion speed, hydraulic cylinder pressure in each zone, hydraulic cylinder stroke, propulsion force of each hydraulic cylinder, and total propulsion force; attitude control system: horizontal and vertical deviation of the cutter ring, horizontal and vertical deviation of the shield tail, horizontal and vertical trends, roll angle, and pitch angle; synchronous grouting and grout injection system: pressure and flow rate of each injection pipeline, and cumulative grouting volume per ring; shield tail sealing and grease injection system: pressure of each injection pipeline in each sealing cavity, outlet pressure of the shield tail grease pump, and grease consumption per ring. Slurry tank pressure control unit: air cushion tank pressure, air cushion tank mud level, slurry tank top pressure, current cutting ring top water and soil pressure, valve opening and closing status, air tank pressure; Slurry circulation slag discharge unit: slurry inlet and outlet flow rate, slurry inlet and outlet flow rate difference, slurry inlet and outlet density, slurry inlet and outlet pipeline pressure, slurry inlet and outlet pump speed, drive motor current, inlet and outlet pressure of each slurry inlet and outlet pump, valve opening and closing status; Key component status monitoring unit for tunnel boring machine (TBM) equipment: temperature of each inner and outer sealing cavity of the main bearing, temperature of the inner and outer sealing cooling water, and flow rate of the inner and outer sealing cooling water; temperature, viscosity, water content, dielectric constant, density, ferromagnetic content, and non-ferromagnetic content of the main bearing lubricating oil; temperature, viscosity, density, dielectric constant, saturation, and water content of the hydraulic oil in the TBM propulsion system; wear amount, rotation state, temperature, and load of the TBM cutterhead; and acceleration of the drive motors of each main bearing in the horizontal, vertical, and forward / backward directions. Structural component assembly unit: working status of segment hoist, segment feeder, segment assembler, next ring segment assembly point, and working status of arc component assembler; Material transport unit within the tunnel: location of material transport vehicles within the tunnel, type of transported goods, direction of travel, speed, and obstacle perception results; Tunnel Environmental Protection Unit: Contents of methane, hydrogen sulfide, oxygen, carbon dioxide, and carbon monoxide in the exhaust area of ​​the tunnel boring machine; operating frequency of the fan inverter, fan current, voltage, power, wind speed, and power consumption.

[0020] The data interaction methods between units described in S3 include at least one of the following collaborative operations: Tunneling-material transportation coordination: Based on the tunneling status, the estimated completion time, the consumption of synchronous grouting slurry and tail sealant grease for each ring, and the current remaining quantity, arrange the material transportation unit in the tunnel to organize the transportation of synchronous grouting slurry and tail sealant grease. Structural component assembly-material transportation coordination: Based on the assembly point information of the next ring segment, determine the transportation demand of segments and curved components, arrange segment transportation and generate a transportation order, and confirm the transportation by the tunnel management personnel after the transportation arrives, thus forming an information loop; Collaborative monitoring of key components of tunneling-shield equipment: Real-time analysis of the changing trends of monitoring parameters is performed using a trend prediction algorithm for the status of key components of the shield, and early warning information is provided to the main shield operator through a multi-unit collaborative management and control platform; Tunneling-Assembly-Tunnel Environment Protection Coordination: Monitoring and early warning information from the tunnel environment protection unit is pushed to structural component assembly workers and tunnel boring machine operators through a multi-unit collaborative management and control platform to determine whether to continue operations or stop the machine to avoid risks.

[0021] Predictive control algorithms are deployed in each unit of S4, including: The shield tunneling unit deploys prediction algorithms for total thrust, cutterhead rotation speed, penetration depth, thrust speed, hydraulic cylinder pressure in each zone of the thrust system, synchronous grouting slurry consumption, and shield tail sealing grease consumption, and recommends suggested values ​​for the above parameters in real time. Among them, the predicted values ​​of cutterhead rotation speed, thrust speed, and hydraulic cylinder pressure in each zone of the thrust system directly participate in the control of the tunneling process. The mud pressure control unit deploys a mud chamber pressure prediction algorithm to predict the pressure at the top of the mud chamber in real time based on the geological survey report and the current mileage location and burial depth, and indirectly controls the pressure at the top of the mud chamber by adjusting the pressure of the air cushion chamber. The slurry circulation and slag discharge unit deploys slurry flow prediction algorithms and decision tree algorithms to control the slurry circulation system to switch between tunneling, segment assembly, and shutdown working modes. The key component status monitoring unit of the tunnel boring machine is equipped with a data trend prediction algorithm to provide real-time information on the sealing status of the main bearing, vibration data of the main bearing drive motor, oil parameters of the main bearing lubricating oil and propulsion system hydraulic oil, cutter wear, rotation status, temperature, and load trends. The structural component assembly unit is equipped with a comprehensive positioning algorithm based on image recognition and laser ranging to achieve high-precision autonomous assembly of segments and curved components; The material transport unit inside the tunnel is equipped with an obstacle detection algorithm based on infrared and visible light to assist the transport vehicle driver.

[0022] A multi-unit collaborative device for shield tunnel construction includes multiple work units, each corresponding to a different process in the shield tunnel construction process, and each work unit has data acquisition, execution, and feedback functions. Each work unit is connected to a data transmission terminal to collect the operating status and data of each work unit; Each data transmission terminal is connected to the data center via a local area network to store and manage multimodal data from each work unit; The data center is connected to the collaborative management and control platform, which is used to query the operating status and data of each work unit in real time, and to realize information interaction between users and each work unit; The data center automatically distributes information from specific work units to other relevant work units according to preset rules, so as to achieve process collaboration.

[0023] Overall Approach First, a data center is established at the shield tunnel construction site to store and manage data from the perception, operation, decision-making, and feedback processes of various intelligent agents during the shield tunnel construction. This data is multimodal, including time-series data, image data, and text data. The data center includes data acquisition terminals deployed on each intelligent agent, connected to each intelligent agent via a local area network, and supports 5G communication.

[0024] Secondly, a multi-agent collaborative management and control platform for the shield tunnel construction process was developed. This platform serves as an interaction channel between construction site managers and various agents, allowing real-time monitoring of the operational status and data of agents involved in shield tunneling, attitude control, slurry circulation and muck removal, tunnel structure assembly, material transportation, and tunnel environmental monitoring. The platform supports multi-terminal access (personal computers, industrial control computers, mobile phones, etc.), enabling managers to monitor the on-site operation status and system operation in real time from different work locations such as the various agent operation monitoring areas, the construction site dispatch center, offices, and inside the tunnel.

[0025] Secondly, an intelligent agent data interaction mechanism is established to achieve cross-system information sharing for multi-process collaboration. For example, when the tunnel boring machine (TBM) begins excavation, information such as the start of excavation, the current synchronous grouting volume, remaining grout volume, and remaining tail sealant grease is automatically distributed through the data center to the tunnel material transportation system, the external tunnel segment hoisting system, the synchronous grouting grout production system, and the material warehouse, facilitating production organization and material preparation by each system. The information distributed by each intelligent agent is displayed, updated, and alerted in real time on the multi-agent collaborative management and control platform.

[0026] Finally, various prediction and identification algorithms trained on historical data are deployed on the multi-agent collaborative management and control platform to generate prediction and early warning information in real time to assist operators in decision-making. The overall architecture diagram is shown in Figure 1.

[0027] Overall data transmission route: Data transmission terminal 1 connects to the shield tunneling intelligent body, the slurry pressure control intelligent body, and the slurry circulation and muck discharge intelligent body; Data transmission terminal 2 connects to the intelligent agent for monitoring the status of key components of the tunnel boring machine; Data transmission terminal 3 connects to the intelligent body assembled from structural components; Data transmission terminal 4 connects to the intelligent material transport agent in the tunnel; Data transmission terminal 5 connects to the intelligent entity that protects the environment inside the tunnel.

[0028] The data center and data transmission terminals 1, 2, 3, 4, and 5 at the shield tunnel construction site are connected via a local area network. The multi-agent collaborative management platform serves as the interaction interface, responsible for information exchange between the user and each agent.

[0029] Typical collaborative work methods ①Tunneling-Material Transportation Coordination: Production management personnel outside the tunnel use a multi-agent collaborative control platform to monitor the current tunneling status of the shield tunneling, the estimated completion time, the consumption of synchronous grouting slurry and shield tail sealing grease for each ring, the current remaining amount of synchronous grouting slurry and shield tail sealing grease, and arrange the transportation system inside the tunnel to organize the transportation of synchronous grouting slurry and shield tail sealing grease into the tunnel.

[0030] ② Structural component assembly and material transportation coordination: Production management personnel inside the tunnel use a multi-agent collaborative control platform to update the assembly point information for the next ring of tunnel segments, determining the transportation requirements for segments and curved components. Production management personnel outside the tunnel then arrange segment transportation based on this information and generate transportation orders. Upon arrival at the destination, production management personnel inside the tunnel confirm the transportation information, forming an information loop.

[0031] ③ Collaborative monitoring of key components of tunneling and shield equipment: By using the status trend prediction algorithm of key components of shield equipment, the changing trend of relevant monitored parameter data is analyzed in real time and early warning information is provided to the shield operator through the multi-agent collaborative management and control platform. This allows the shield operator to simultaneously grasp the current tunneling status of the shield and the operating status of key components of the equipment, so as to determine whether to intervene.

[0032] ④ Collaborative Excavation-Assembly-Tunnel Environment Protection: The intelligent monitoring and early warning information of the tunnel environment protection is pushed to the personnel assembling structural components in the shield machine area and the shield machine operator through the multi-agent collaborative management and control platform, so that they can grasp the current environmental conditions of the working area as soon as possible and determine whether to continue the work or stop the machine to avoid danger.

[0033] Predictive control algorithms for each agent: The tunnel boring machine (TBM) intelligent agent is equipped with algorithms to predict total propulsion force, cutterhead rotation speed, penetration depth, propulsion speed, hydraulic cylinder pressure in each zone of the propulsion system, synchronous grouting slurry consumption, and tail seal grease consumption. These algorithms can recommend suggested values ​​for these parameters in real time. Among these, the predicted values ​​for cutterhead rotation speed, propulsion speed, and hydraulic cylinder pressure in each zone of the propulsion system directly participate in the control of the tunneling process. The slurry pressure control intelligent agent is equipped with an algorithm to predict slurry chamber pressure. Based on the geological survey report and the current burial depth, it predicts the pressure at the top of the slurry chamber in real time and indirectly controls the pressure at the top of the slurry chamber by adjusting the pressure of the air cushion chamber. The slurry circulation and muck discharge intelligent agent is equipped with algorithms to predict slurry inlet and outlet flow rates and decision tree algorithms. This controls the slurry circulation system to switch between tunneling, segment assembly, and shutdown working modes, enabling the TBM to have "one-click start and autonomous operation," reducing the workload of the TBM operator.

[0034] The intelligent agent for monitoring the status of key components of the tunnel boring machine (TBM) has deployed a data trend prediction algorithm to provide real-time information on key components such as the sealing status of the main bearing, vibration data of the main bearing drive motor, parameters of the main bearing lubricating oil and propulsion system hydraulic oil, and trends in cutter wear, rotation status, temperature, and load.

[0035] The intelligent assembly agent for structural components is equipped with a comprehensive positioning algorithm based on image recognition and laser ranging to achieve high-precision autonomous assembly of pipe segments and curved components.

[0036] The intelligent material transport system inside the tunnel is equipped with a comprehensive obstacle detection algorithm based on infrared and visible light to assist the transport vehicle driver.

[0037] Although some preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the invention.

[0038] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this application and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A multi-unit collaborative method for shield tunnel construction, characterized in that, Includes the following steps: S1 Data Center Construction: Establish a data center at the shield tunnel construction site to store and manage multimodal data from multiple units during the shield tunnel construction process; S2 Development Collaborative Management and Control Platform: Develop a multi-unit collaborative management and control platform for the shield tunnel construction process. The platform is used for managers to interact with each unit and query the operating status and data of each unit in real time. S3 establishes a data interaction mechanism: establishing a data interaction method between units to realize cross-system information sharing for multi-process collaborative operations; S4 Configuration Prediction and Identification Algorithm: Deploy a prediction or identification algorithm trained on historical data on the multi-unit collaborative management and control platform to generate prediction or early warning information to assist decision-making.

2. The multi-unit collaborative method for shield tunnel construction as described in claim 1, characterized in that: The data center described in S1 is connected to each unit through multiple data transmission terminals. The multiple units include a shield tunneling unit, a slurry pressure control unit, a slurry circulation and muck removal unit, a shield equipment key component status monitoring unit, a structural component assembly unit, a tunnel material transportation unit, and a tunnel environment protection unit. Each unit corresponds to at least one data transmission terminal.

3. The multi-unit collaborative method for shield tunnel construction as described in claim 1, characterized in that: The data collected by each unit in S2 includes: Shield tunneling unit: cutterhead drive system: cutterhead speed, rotation direction, cutterhead torque, current, voltage, torque, and power of each drive motor; propulsion system: propulsion speed, hydraulic cylinder pressure in each zone, hydraulic cylinder stroke, propulsion force of each hydraulic cylinder, and total propulsion force; attitude control system: horizontal and vertical deviation of the cutter ring, horizontal and vertical deviation of the shield tail, horizontal and vertical trends, roll angle, and pitch angle; synchronous grouting and grout injection system: pressure and flow rate of each injection pipeline, and cumulative grouting volume per ring; shield tail sealing and grease injection system: pressure of each injection pipeline in each sealing cavity, outlet pressure of the shield tail grease pump, and grease consumption per ring. Slurry tank pressure control unit: air cushion tank pressure, air cushion tank mud level, slurry tank top pressure, current cutting ring top water and soil pressure, valve opening and closing status, air tank pressure; Slurry circulation slag discharge unit: slurry inlet and outlet flow rate, slurry inlet and outlet flow rate difference, slurry inlet and outlet density, slurry inlet and outlet pipeline pressure, slurry inlet and outlet pump speed, drive motor current, inlet and outlet pressure of each slurry inlet and outlet pump, valve opening and closing status; Key component status monitoring unit for tunnel boring machine (TBM) equipment: temperature of each inner and outer sealing cavity of the main bearing, temperature of the inner and outer sealing cooling water, and flow rate of the inner and outer sealing cooling water; temperature, viscosity, water content, dielectric constant, density, ferromagnetic content, and non-ferromagnetic content of the main bearing lubricating oil; temperature, viscosity, density, dielectric constant, saturation, and water content of the hydraulic oil in the TBM propulsion system; wear amount, rotation state, temperature, and load of the TBM cutterhead; and acceleration of the drive motors of each main bearing in the horizontal, vertical, and forward / backward directions. Structural component assembly unit: working status of segment hoist, segment feeder, segment assembler, next ring segment assembly point, and working status of arc component assembler; Material transport unit within the tunnel: location of material transport vehicles within the tunnel, type of transported goods, direction of travel, speed, and obstacle perception results; Tunnel Environmental Protection Unit: Contents of methane, hydrogen sulfide, oxygen, carbon dioxide, and carbon monoxide in the exhaust area of ​​the tunnel boring machine; operating frequency of the fan inverter, fan current, voltage, power, wind speed, and power consumption.

4. The multi-unit collaborative method for shield tunnel construction as described in claim 1, characterized in that: The data interaction methods between units described in S3 include at least one of the following collaborative operations: Tunneling-material transportation coordination: Based on the tunneling status, the estimated completion time, the consumption of synchronous grouting slurry and tail sealant grease for each ring, and the current remaining quantity, arrange the material transportation unit in the tunnel to organize the transportation of synchronous grouting slurry and tail sealant grease. Structural component assembly-material transportation coordination: Based on the assembly point information of the next ring segment, determine the transportation demand of segments and curved components, arrange segment transportation and generate a transportation order, and confirm the transportation by the tunnel management personnel after the transportation arrives, thus forming an information loop; Collaborative monitoring of key components of tunneling-shield equipment: Real-time analysis of the changing trends of monitoring parameters is performed using a trend prediction algorithm for the status of key components of the shield, and early warning information is provided to the main shield operator through a multi-unit collaborative management and control platform; Tunneling-Assembly-Tunnel Environment Protection Coordination: Monitoring and early warning information from the tunnel environment protection unit is pushed to structural component assembly workers and tunnel boring machine operators through a multi-unit collaborative management and control platform to determine whether to continue operations or stop the machine to avoid risks.

5. The multi-unit collaborative method for shield tunnel construction as described in claim 1, characterized in that: Predictive control algorithms are deployed in each unit of S4, including: The shield tunneling unit deploys prediction algorithms for total thrust, cutterhead rotation speed, penetration depth, thrust speed, hydraulic cylinder pressure in each zone of the thrust system, synchronous grouting slurry consumption, and shield tail sealing grease consumption, and recommends suggested values ​​for the above parameters in real time. Among them, the predicted values ​​of cutterhead rotation speed, thrust speed, and hydraulic cylinder pressure in each zone of the thrust system directly participate in the control of the tunneling process. The mud pressure control unit deploys a mud chamber pressure prediction algorithm to predict the pressure at the top of the mud chamber in real time based on the geological survey report and the current mileage location and burial depth, and indirectly controls the pressure at the top of the mud chamber by adjusting the pressure of the air cushion chamber. The slurry circulation and slag discharge unit deploys slurry flow prediction algorithms and decision tree algorithms to control the slurry circulation system to switch between tunneling, segment assembly, and shutdown working modes. The key component status monitoring unit of the tunnel boring machine is equipped with a data trend prediction algorithm to provide real-time information on the sealing status of the main bearing, vibration data of the main bearing drive motor, oil parameters of the main bearing lubricating oil and propulsion system hydraulic oil, cutter wear, rotation status, temperature, and load trends. The structural component assembly unit is equipped with a comprehensive positioning algorithm based on image recognition and laser ranging to achieve high-precision autonomous assembly of segments and curved components; The material transport unit inside the tunnel is equipped with an obstacle detection algorithm based on infrared and visible light to assist the transport vehicle driver.

6. A multi-unit collaborative device for shield tunnel construction, characterized in that, It includes multiple work units, each corresponding to a different process in the shield tunnel construction process. Each work unit has data acquisition, execution, and feedback functions. Each work unit is connected to a data transmission terminal to collect the operating status and data of each work unit; Each data transmission terminal is connected to the data center via a local area network to store and manage multimodal data from each work unit; The data center is connected to the collaborative management and control platform, which is used to query the operating status and data of each work unit in real time, and to realize information interaction between users and each work unit; The data center automatically distributes information from specific work units to other relevant work units according to preset rules, so as to achieve process collaboration.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 5.

9. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the steps of the method as described in any one of claims 1 to 5.

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