A tunnel digital twin system

Abstract

The present invention discloses a tunnel digital twin system, which includes five components: a physical entity module, a twin model module, a perception control module, a data management module, and a service application module. The physical entity module is a real tunnel and its surrounding rock mass. The twin model module characterizes and describes the physical entity from multiple dimensions, multiple spatial scales, and multiple time scales. The perception control module is used to collect and transmit operation monitoring data and automatically adjust the operating status of some equipment. The data management module provides accurate, comprehensive, and timely data management support for the tunnel digital twin system. The service application module develops multiple functions for tunnel operation management. The present invention provides solution guidance for the intelligent construction and operation and maintenance of tunnels.

Description

Technical Field

[0001] The present invention relates to the technical field of construction, operation and maintenance of construction projects, in particular to the field of construction, operation and monitoring of tunnel projects, and more particularly to application tools and implementation methods for intelligent construction, operation and monitoring of tunnels, specifically a tunnel digital twin system. Background Art

[0002] During the operation and management phase, tunnels often develop defects such as cracks, bulges, and water leaks. Currently, these defects are primarily detected by visual inspection by inspectors or by testing with instruments (Chongqing Jiaotong University. A 5G-based Intelligent Cloud Control System for Tunnels: 202011400906.4[P]. 2021-04-06.). This approach only allows for remedial measures after a problem has occurred, and often requires determining maintenance plans based on a large number of discrete paper files accumulated during the tunnel construction and operation phase. The increased maintenance records further complicate archival management. Furthermore, monitoring the health of a tunnel often requires closing the road, drilling holes in a small number of lining sections, installing measuring instruments, and connecting cables. This work carries certain risks and produces unreliable monitoring data, making it difficult to truly and effectively understand the tunnel's health. Although some tunnel health monitoring also adopts sensor-based remote monitoring methods, which has reduced manpower loss and achieved automated real-time performance to a certain extent, it still lacks functions in data visualization and interactivity, as well as the participation of management units (Tongji University. A modular building health monitoring system based on a digital twin platform: 202011276245.9[P].2021-02-19).

[0003] Digital twin technology provides a path to fully digital delivery, fully intelligent operation, and full lifecycle management of tunnels. Combining data collection with the Internet of Things (IoT), digital twin technology leverages model and sensor updates, historical operational data, and integrates multidisciplinary, multi-physics, multi-scale, and multi-probabilistic simulation processes to map the tunnel in virtual space. This allows for an understanding of the tunnel's historical conditions, an assessment of its current operational status, simulation and diagnosis of its state and behavior, and prediction of health status trends and potential damage and risks. Summary of the Invention

[0004] The present invention aims to solve the problem that existing tunnels cannot detect and predict the occurrence of diseases in a timely manner during the operation and maintenance stage, improve the credibility of tunnel monitoring data and the participation of tunnel operation and management units, solve the redundancy and discreteness of file management and query work, and improve decision-making efficiency when facing emergencies or formulating maintenance plans.

[0005] The present invention is achieved through at least one of the following technical solutions.

[0006] A tunnel digital twin system for fully intelligent tunnel operations, including a physical entity module, a twin model module, a perception and control module, a data management module, and a service application module;

[0007] The physical entity module is used to represent the tunnel structure, facilities in the tunnel, and the rock mass and geographical environment around the tunnel, including surrounding rock, support, lining, pavement, pipelines, and electromechanical equipment;

[0008] The twin model module is used to characterize the geometry, physics, behavior, and rules of the physical entity module from multiple time scales and multiple spatial scales;

[0009] The perception control module is used to monitor the operating status of the tunnel physical entity in real time and collect and transmit the monitoring data to the data management module. It is also used to transmit instructions issued by the user through the service application module and regulate the operating status of the intelligent electromechanical equipment;

[0010] The data management module is used to store and manage data, and provide a data interface;

[0011] The service application module is a user-oriented functional module used to achieve real-time monitoring of the tunnel operation status, manage project archives, present data or results of modules other than the physical entity module, and guide maintenance and emergency rescue.

[0012] Furthermore, the twin model module integrates the three-dimensional information model, analytical calculation model, and behavioral evolution model of the tunnel;

[0013] The three-dimensional information model is a three-dimensional information model established for the tunnel structure, geological conditions and surrounding geographical environment;

[0014] The analytical calculation model is a mechanical model based on the surrounding rock pressure of the stratum where the tunnel is located, the physical and mechanical properties of the support structure, and the boundary conditions, and is used to calculate the stress and strain indicators of the verification structure.

[0015] Furthermore, the behavioral evolution model is based on the analytical calculation model, uses a deep learning algorithm to mine the patterns in the physical entity operation data and the analytical calculation model result data, and combines the visualization characteristics of the three-dimensional information model to achieve the reproduction and prediction of the operating health status of the tunnel physical entity.

[0016] Furthermore, the perception control module is used for collecting and transmitting operating status data, transmitting instructions, and regulating intelligent electromechanical equipment. The intelligent electromechanical equipment includes sensors for monitoring stress and strain data, automated monitoring and measurement devices for monitoring tunnel section deformation, atmospheric environment monitoring devices for monitoring air quality and composition, lining crack and water leakage detection devices, inspection vehicles for monitoring pavement structure defects, ventilation machinery and lighting devices that can be automatically and intelligently controlled, video monitoring and pipeline valves, and network transmission equipment for wired networks, wireless networks, or a combination of wired and wireless networks.

[0017] Furthermore, the perception control module uses infrared thermal imaging or laser scanning to monitor lining cracks and water leakage, and the monitoring device is installed on the top of the tunnel lining in a track-type manner, or the monitoring device is mounted on an inspection vehicle to conduct regular safety inspections of the entire tunnel; the monitoring data is uploaded to the data management module in real time through the network transmission equipment in the perception control module.

[0018] Furthermore, the perception control module monitors pavement structure defects by regularly conducting full-line inspections with inspection vehicles, or by pre-embedding monitoring equipment during the pavement structure paving process; monitoring data is uploaded to the data management module in real time via the network transmission equipment in the perception control module.

[0019] Furthermore, the data management module is built using a relational database model, which is used to receive and store the tunnel's operation monitoring data, the calculation analysis and simulation data of the twin model module, and provide a data interface for the twin model module to call and process these data, and provide an interface for the service application module to call data and send instructions to the perception control module.

[0020] Furthermore, the service application module adopts a B / S architecture.

[0021] Furthermore, the service application module calls the three-dimensional information model of the twin model module and its calculation and analysis results, and the operation monitoring data of the perception control module through the data management module, and presents the operation monitoring data in a visual interface, while setting alarm thresholds for different monitoring indicators.

[0022] Furthermore, users monitor the actual operating status of the tunnel's physical entity through the service application module. When adjustment is required, the service application module triggers corresponding instructions, which are transmitted through the network transmission equipment of the perception control module and regulate the operating status of the electromechanical equipment; users use the warning information of the service application module to timely or in advance discover problems in the tunnel operation, make decisions and take treatment plans, and store the decision and treatment results in the data management module.

[0023] The tunnel mentioned in the present invention refers to a transportation infrastructure tunnel and a tunnel in related urban public facilities, including but not limited to roads, railways, urban rail transit, integrated pipeline corridors, urban power supply, water supply and diversion tunnels, etc.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] Improve the level of informatization of tunnel construction, operation and management, improve the accuracy and reliability of tunnel health monitoring, and realize intelligent operation and management of tunnel construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a schematic diagram of the module composition of a tunnel digital twin system of the present invention;

[0027] Figure 2 This is a schematic diagram of the relationship between the three models of the twin model module of a tunnel digital twin system of the present invention;

[0028] Figure 3 This is a schematic diagram of the working process of the perception control module of a tunnel digital twin system of the present invention. DETAILED DESCRIPTION

[0029] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. However, it should be understood that the present invention can be implemented in various forms and should not be limited by the exemplary embodiments described herein. Instead, this embodiment is provided to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art. It should be noted that the embodiments and features of the embodiments of the present invention can be combined with each other unless there is a conflict.

[0030] Example 1

[0031] like Figure 1 The tunnel digital twin system shown is characterized by including five components: a physical entity module, a twin model module, a perception and control module, a data management module, and a service application module.

[0032] The physical entity module represents the tunnel structure, facilities, rock mass and geographical geological environment around the tunnel. It is the basic component module and the object of attention and operation of a tunnel digital twin system of the present invention. According to the specific functions of the tunnel physical entity during the construction process and operation stage, the tunnel physical entity is divided into surrounding rock, support, lining, pavement, pipelines and electromechanical equipment.

[0033] like Figure 2As shown, the twin model module is used to characterize the geometry, physics, behavior, and rules of the physical entity module from multiple time and spatial scales. It integrates the tunnel's three-dimensional information model, analytical calculation model, and behavioral evolution model. Specifically, the three-dimensional information model is a three-dimensional information model established for the tunnel structure, geological conditions, and surrounding geographical environment. The analytical calculation model is a mechanical model derived from the surrounding rock pressure of the tunnel stratum, the physical and mechanical properties of the support structure, and boundary conditions, guided by tunnel design calculation theory. It is used to calculate and verify indicators such as stress and strain of the structure. The behavioral evolution model is based on the analytical calculation data of the analytical calculation model and the operational monitoring data collected by the perception and control module. It uses deep learning algorithms such as convolutional neural network algorithms and autoencoder neural network algorithms to mine the patterns in the physical entity operation data and the analytical calculation model result data to predict the behavior of the physical entity.

[0034] The perception control module is used to collect operation monitoring data of the tunnel physical entity in real time and transmit the data to the data management module. It is also used to control the operation status of the electromechanical equipment according to the instructions issued by the user with the help of the service application module or the system preset program. For example, the functional relationship between the preset air composition and the ventilation fan speed in the system is set. When the data of the air monitoring equipment changes, the ventilation fan automatically adjusts the speed. Or, for example, in the event of an accident, the user can control the adjustment of the video surveillance shooting angle to timely grasp the on-site situation.

[0035] The data management module is built using a relational database model, and is used to receive and store the operation monitoring data of the perception control module and the computational analysis and simulation data of the twin model module, and provides a data interface for the twin model module to call the operation monitoring data and for the service application module to call the operation monitoring data and computational analysis and simulation data.

[0036] The service application module is a user-oriented functional module in the tunnel digital twin system, which adopts a B / S architecture. It calls the three-dimensional information model and its calculation and analysis results of the twin model module and the operation monitoring data of the perception control module through the data management module, presents the above data in a visual interface, and sets alarm thresholds for different monitoring indicators. Users can monitor the actual operation status of the tunnel physical entity through the service application module. When adjustment is required, the corresponding instructions can be triggered in the service application module. The instructions are transmitted through the network transmission equipment of the perception control module and regulate the operation status of the electromechanical equipment. Users can use the warning information of the service application module to timely or in advance discover problems in the tunnel operation, make decisions and adopt treatment plans, and store the decision results and treatment results in the data management module. The service application module serves as a direct tool for real-time monitoring of the tunnel's operation status, project file management, disease and risk prediction, maintenance guidance and emergency rescue, helping to realize the intelligent construction and operation of the tunnel.

[0037] Example 2

[0038] The construction of the twin model module should be a mapping and expression of physical entity information, which includes but is not limited to planning and design information, geographical environment information of the tunnel site, geological survey information, and tunnel design calculation and analysis theory.

[0039] The twin model module includes a three-dimensional information model, an analytical calculation model, and a behavioral evolution model. For tunnels in operation and construction, the construction of the twin model should highlight the different characteristics of the two life cycle stages.

[0040] For tunnels under construction, the 3D information model should accurately reflect the design intent. At the same time, the geographic and geological information in the 3D information model needs to be continuously supplemented and revised during the construction period. The corresponding analysis and calculation models and behavioral evolution models also need to be promptly revised according to the actual construction conditions, and measurements should be strengthened. The analysis and calculation models and behavioral evolution models should first focus on the verification and prediction of structural safety and tunnel deformation.

[0041] For tunnels in operation, the three-dimensional information model should accurately reflect the structural geometry, geographical geology, and other relevant information of the completed operational status of the tunnel's physical entity. The data on which the restoration model is based is relatively comprehensive, but its accuracy and effectiveness are relatively reduced. Correspondingly, the analytical calculation model and the behavioral evolution model are relatively fixed, and the effectiveness of the behavioral evolution model needs to be gradually improved through a period of measurement and monitoring.

[0042] The 3D information model is a fusion of a 3D information model of the tunnel structure and a 3D information model of the geography and geology. The 3D information model of the tunnel structure can be created based on design and design change information using commonly used BIM modeling software such as Revit and Bently-ABD. The 3D information model of geography and geology is created in a 3D environment using 3D geological modeling technology, combining tools such as spatial information management, geological interpretation, spatial analysis and prediction, geostatistics, entity content analysis, and graphic visualization. For example, a 3D point cloud model of topography can be created using drone-mounted LiDAR scanning, and a geological model can be created using geological modeling software such as EVS. The 3D information model of the tunnel structure and the 3D information model of the geography and geology are converted and then fused to generate the 3D information model.

[0043] The analysis and calculation model is based on the tunnel design calculation and analysis theory, and abstracts the surrounding rock pressure of the tunnel stratum, the physical and mechanical properties of the support structure, the boundary conditions, etc. into a finite element analysis and calculation model. The model can be established using general finite element software, or with the help of secondary development of the modeling BIM software, the part of the three-dimensional information model that mainly affects the structural analysis and calculation can be converted into a preliminary finite element model, and then the model can be corrected using general finite element software.

[0044] The behavioral evolution is based on an analytical calculation model, using deep learning technologies such as convolutional neural networks and autoencoder neural networks to mine and analyze the patterns in the calculation result data and the physical entity operation monitoring data. Combined with the visualization characteristics of the three-dimensional information model, it can achieve the reproduction and prediction of the operational health status of the tunnel physical entity.

[0045] Example 3

[0046] like Figure 3 The sensory control module, shown here, is used to monitor and adjust the operating status of tunnel facilities in real time. It includes sensory devices, transmission devices, and control devices. The sensory control module collects real-time operating data from the tunnel's physical entities through the sensory devices and uploads this data to the data management module via the transmission devices. Users access and view this data through the service application module, providing real-time visibility into the operating status of the tunnel's physical entities. To ensure the healthy and safe operation of the tunnel, when adjustments to tunnel facilities are necessary, users trigger corresponding instructions in the service application module. The sensory control module's transmission devices transmit these instructions to the control devices, adjusting the operating status of the physical entities.

[0047] The sensing equipment includes sensors for monitoring stress and strain data, automated monitoring and measurement devices for monitoring tunnel section deformation, atmospheric environment monitoring devices for monitoring air quality and composition, lining crack and water leakage monitoring devices, pavement structure disease monitoring devices, lighting brightness monitoring devices, video monitoring, etc.

[0048] The transmission equipment includes a wired network, a wireless network, or a network transmission equipment combining a wired network and a wireless network.

[0049] The control equipment includes equipment for controlling ventilation machinery speed, lighting brightness, pipeline valve opening and closing, video monitoring angle adjustment, etc.

[0050] When constructing a digital twin system for a tunnel under construction, in the perception and control module, sensors that monitor the stress and strain data of anchor rods and linings can be pre-buried in the support structure during the construction process. Sensors that monitor water leakage can be pre-buried between the initial support and the secondary lining. Devices that monitor pavement structure defects can be pre-buried in layers during pavement paving.

[0051] When building a digital twin system for an operating tunnel, in the perception and control module, sensors or measuring devices that monitor the stress and strain data of anchor rods and linings are laid on the inner surface of the lining; infrared thermal imaging or laser scanning are used to monitor lining cracks and water leakage. The monitoring device can be installed on the top of the tunnel lining in a track-type manner for all-weather monitoring, or the monitoring device can be mounted on an inspection vehicle to regularly inspect the entire tunnel; for monitoring pavement structure defects, a road inspection vehicle is used to regularly inspect the entire tunnel.

[0052] Example 4

[0053] The service application module may also adopt a C / S architecture mode (client and server architecture mode), where the server side carries the data management module and the client side is installed on the user's computer.

[0054] When the service application module adopts the C / S architecture model, the visual interface design of the service application module is completed during client development, and the data management module only provides a data interface, so that the client of the service application module can access the operation monitoring data of the perception control module, the analysis and calculation results of the twin model module, and the simulation prediction data; the user uses the client of the service application module to trigger the control instructions of the equipment in the perception control module, and transmits them through the transmission equipment of the perception control module.

[0055] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to the specific embodiments described. Obviously, many modifications and variations are possible based on the content of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A tunnel digital twin system for intelligent tunnel construction and operation, characterized by: Including physical entity module, twin model module, perception control module, data management module, and service application module; The physical entity module is used to represent the tunnel structure, facilities in the tunnel, and the rock mass and geographical environment around the tunnel, including surrounding rock, support, lining, pavement, pipelines, and electromechanical equipment; The twin model module is used to characterize the geometric, physical, behavioral, and regular features of the physical entity module from multiple time scales and multiple spatial scales; the twin model module integrates the three-dimensional information model, analytical calculation model, and behavioral evolution model of the tunnel; the three-dimensional information model is a three-dimensional information model established for the tunnel structure, geological conditions, and surrounding geographical environment; the analytical calculation model is a mechanical model based on the surrounding rock pressure of the stratum in which the tunnel is located, the physical and mechanical properties of the support structure, and the boundary conditions, and is used to calculate and verify the stress and strain indicators of the structure; the behavioral evolution model is based on the analytical calculation model, uses a deep learning algorithm to mine the laws in the physical entity operation data and the analytical calculation model result data, and combines the visualization characteristics of the three-dimensional information model to achieve the reproduction and prediction of the operating health status of the tunnel physical entity; The perception control module is used to monitor the operating status of the tunnel physical entity in real time and collect and transmit the monitoring data to the data management module. It is also used to transmit instructions issued by the user through the service application module and regulate the operating status of the intelligent electromechanical equipment; The data management module is used to store and manage data and provide a data interface. The data management module is built using a relational database model and is used to receive and store tunnel operation monitoring data and calculation, analysis, and simulation data from the twin model module. It also provides a data interface for the twin model module to call and process this data, and an interface for the service application module to call data and send instructions to the perception control module. The service application module is a user-oriented functional module used to achieve real-time monitoring of the tunnel operation status, manage project files, present data or results of modules other than the physical entity module, and guide maintenance and emergency rescue; The service application module calls the three-dimensional information model of the twin model module and its calculation and analysis results, and the operation monitoring data of the perception control module through the data management module, and presents the operation monitoring data in a visual interface, while setting alarm thresholds for different monitoring indicators; Users monitor the actual operating status of the tunnel's physical entities through the service application module. When adjustments are needed, the service application module triggers corresponding instructions, which are transmitted through the network transmission equipment of the perception control module and regulate the operating status of the electromechanical equipment; Users can use the warning information from the service application module to timely or preemptively discover problems in tunnel operation, make decisions and adopt treatment plans, and store the decision and treatment results in the data management module.

2. The tunnel digital twin system according to claim 1, characterized in that: The perception control module is used for collecting and transmitting operating status data, transmitting instructions, and regulating intelligent electromechanical equipment. The intelligent electromechanical equipment includes sensors for monitoring stress and strain data, automated monitoring and measurement devices for monitoring tunnel section deformation, atmospheric environment monitoring devices for monitoring air quality and composition, lining crack and water leakage detection devices, inspection vehicles for monitoring pavement structure defects, ventilation machinery and lighting devices that can be automatically and intelligently regulated, video monitoring and pipeline valves, and network transmission equipment for wired networks, wireless networks, or a combination of wired and wireless networks.

3. The tunnel digital twin system according to claim 1, characterized in that: The perception control module uses infrared thermal imaging or laser scanning to monitor lining cracks and water leakage. The monitoring device is mounted on the top of the tunnel lining using a track, or the monitoring device is mounted on an inspection vehicle to conduct regular safety inspections of the entire tunnel. The monitoring data is uploaded to the data management module in real time through the network transmission equipment in the perception control module.

4. The tunnel digital twin system according to claim 1, characterized in that: The perception control module monitors pavement structure defects by using regular full-line inspections by inspection vehicles or by pre-embedding monitoring equipment during the pavement structure construction process; monitoring data is uploaded to the data management module in real time via the network transmission equipment in the perception control module.

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