The application thinking of digital twin technology in the long bridge pipe care

Jiangsu has established 12 highways across the river bridge. Among them, the daily traffic volume of over a thousand -meter cross -river bridge such as Sutong Bridge and Jiangyin Bridge has reached 100,000 vehicles, far exceeding the design expectations, and the proportion of heavy vehicles is high. The tidal characteristics challenged the safety of the bridge structure, smooth traffic, and quality pipe care. With the maturity and gradual application of 5G, cloud computing, artificial intelligence, especially digital twin technology (DT), it is possible to promote the digital transformation of the long bridge to deep water to deep water. Digital twin technology has conducted preliminary exploration and application in projects such as Taihu Tunnel and Wufengshan Bridge, a new Southern High -speed Southern High -speed Southern High -speed Southern High -speed Southern High -speed Southern High -speed Southern High -speed Southern High -speed Southern High -Speed. However, the application of the long -term bridge -long bridge pipeline of the stock is still in its infancy, and the systemic research framework has not yet been formed. Technical expansion and application scenarios are still insufficient. It is necessary to target the specific construction time, structural type, service environment, and bridge vehicle structure of the long bridge. It is guided by problems and needs to clarify the models, data, connection and service applications in the management process to achieve the health of the bridge health Safety twin deductions, in terms of key management and control scenarios, preventive maintenance and all -weather intelligent operations, promote the further improvement of bridge perception, service capabilities, and safety performance, and provide reference for digital twins on the application of long bridge pipe care.

With the increasing increase of the service life and traffic of the bridge, the disease problems of the early bridge construction in the early days have become increasingly prominent, and the operation and maintenance of the bridge has become the key task of bridge operation management at this stage. Traditional long bridge operation and maintenance management has shortcomings such as low information efficiency, poor real -time, and inadequate feedback. Digital twin technology can establish accurate mapping correlation between the physical world and the virtual world, which can effectively solve problems such as low standardization of standardization in the nourishment of the long bridge, not intuitive integration expression, and less simulation prediction interaction.

This article will take the digital twin technology of the long bridge pipe as the research object, sort out the origin of the technology, explore the definition of digital twin technology in the field of long bridge pipe care, and clarify the meaning of models, data, connection and services in the process of pipe support process. Composition, focusing on service, explain the application scope of the technology in the field of bridge pipe care, and then look forward to its development trend in large span bridge operation and maintenance.

Digital twin technology development and principle

Digital twin origin and development

The development of digital twins (DT) can be roughly divided into three stages.

The first stage: concept formed development period. In 2003, Professor Michael Grieves University of Michigan in the United States first proposed the virtual digital expression of physical products, and then continued to deepen expansion. It successively proposed a mirror spatial model and information mirror model, and finally formed the prototype of the digital twin concept.

The second stage: the application exploration period, concentrated in the aerospace industry. In 2010, the National Aeronautical Aviation Administration (NASA) introduced digital twin concepts into "NASA Space Technical Road Map" for the first time. In 2012, the US Air Force Research Office applied digital twins to fighter maintenance.

The third stage: booming period to expand applications to multiple industries. In recent years, digital twin applications have been fully expanded from the field of aerospace to various fields of industries. Siemens and GE industrial giants have created digital twin solutions to empower the digital transformation of manufacturing.

In the field of transportation, the United States focuses on building models and model embedding and automation for AI; EU focuses on security and modeling; Germany pays attention to the design and development of digital intelligent ecosystems; Japan focuses on the construction of technological construction in open data and disaster prevention. Essence The in -depth integration of digital twin technology and transportation industry can greatly promote the informatization and intelligent development of the transportation industry.

Fundamental

First of all, based on modeling tools to build accurate physical objects virtual models in digital space, and then use data -driven model operations, and then integrate and integrate data and models to build comprehensive decision -making capabilities to promote closed -loop optimization of the entire business process. The basic principle of digital twin is shown in Figure 1.

Figure 1 The basic principle of digital twin

How to participate in the bridge operation and maintenance

Facing the application of the long bridge pipe care engineering, the author will use the definition of digital twins as follows: create a virtual mapping of bridge physical entities in a digital manner, and obtain multi -source differences with the help of artificial examination, health monitoring, finite element analysis, traffic control and other means to obtain multi -source differences Construct twin data to control feedback to control the nutritional care process of the physical entity of the bridge, and realize the interactive communication, self -iterative optimization and update of the physical entity objects of the bridge and the relationship with the virtual bridge.

Model definition

The concept model of digital twins in the long -bridge operation period includes five parts: physical bridge, virtual bridge, twin data, information interaction and various services, as shown in Figure 2.

Figure 2 Digital Twin Model in the Operating Period of the Long Bridge

Physical bridge

Physical bridges are objective entities. Various sensors are deployed on physical entities to monitor their environmental data, operating status and response in real time. Physical bridges include bridge time and space location, elements and ecological environments. Among them, the location of time and space is the geographical space information of the bridge, including the time, coordinate information, and high program information of the entities of the bridge; the bridge element is the general name of the various physical entities that constitute the bridge , Information facilities, etc.; The bridge ecological environment is the element of the natural environment of the bridge, including geology, meteorology, hydrology, riverbed river potential, channel, etc. Digital twin physical bridge is an important support for the overall operation of the bridge. Virtual bridge

As a carrier of a bridge digital twin, the virtual bridge is a description and portrayal of the entire element of the physical bridge, the scale and space scale, and the multi -field. In essence, it is a collection of multi -dimensional virtual models, which can be subdivided into four layers: geometric, physical, behavior and rules. Among them, the geometric model is a three -dimensional model that describes the size and shape of the physical bridge size, shape and other space; the physical model adds information such as the physical attributes, constraints and characteristics of the physical bridge on the basis of the geometric model; the behavior model is the physical bridge Responsibility and behaviors made by self -weight, vehicle load, wind load, explosion, boat collision, earthquake role, etc.; the rules models have a model of modular and operating rules of bridge physical physical physical physical mechanics, and the virtual bridges have evaluation and prediction.

The virtual bridge should meet the requirements of precise, standard, lightweight, visible, visible, interaction and reconstruction in the construction to achieve the purpose of available, universal, fast, easy -to -use, joint use, and activation. As shown in Figure 3.

Figure 3 Principles of Virtual Bridge Construction

Twin data

The twin data is the sum of the various types of data of the bridge. It is the core driver of building a bridge digital twin system. It mainly includes: physical bridge, virtual bridge, service, knowledge, and fusion derivative. The physical bridge data includes the attribute data and dynamic process data of the physical factor; the virtual bridge data includes the relevant data in the four -layer model and the simulation data developed by the model; the service data consists of algorithm, model, data processing method, management data, etc. Including expert knowledge, industry standards, rules constraints, reasoning inferences, commonly used algorithm libraries and model libraries, etc.; Fusion derivative data is the data transformed by data conversion, pre -processing, classification, association, integration, integration, etc. on the above 4 data. Twin data involves multiple formats, multiple types, and multiple sources. It requires corresponding data standards to facilitate later sharing. It mainly includes the representation, classification, storage, pre -processing, use and maintenance, and testing of twin data.

Connection and service

The connection will connect the above physical bridges, virtual bridges, twin data, and service parts to make it effective and real -time data transmission, thereby achieving real -time interaction to ensure consistency between each part.

Services are the main purpose of digital twin applications. The services in the maintenance of bridge pipelines mainly include inspection management, emergency management, maintenance and maintenance, health monitoring, auxiliary decision -making, traffic control, etc.

Inspection management

The initial inspection results of the long bridge will be used as the benchmark for operational inspection and assessment. Since then, the routine daily inspections, regular inspections, regular inspections and special inspections will run through the entire process of nourishing the nourishment of the long bridge to provide it with the most direct and comprehensive basic twin data. In recent years, with the advancement of the bridge, new technologies such as drones and robots have been widely used in bridges, high pier, larva, main cables, and underwater structure inspections, which has greatly enriched the types of inspection data. The accuracy has expanded the dimension and accuracy of the twin data of the long bridge. Using digital twin technology, the bridge inspection results can be mapped on the virtual bridge to achieve its visual display. At the same time, the geometric features that can be automatically matched and automatic comparison of the geometric characteristics of cracks and rust damage can be achieved based on AI algorithms. As shown in Figure 4.

Figure 4 Digital twin long bridge inspection management service architecture

Emergency management

During the process of growing the bridge, emergency incidents such as natural disasters and accident disasters may be responded. The use of digital twin technology can be managed by emergency plans, emergency rescue, and disaster evaluation in virtual bridges. After the establishment of emergency resource surveys, hazard sources and risk assessment, the emergency management plan can be completed, emergency resource allocation can be performed in the virtual bridge, and emergency plans can be simulated and optimized. With the help of tilting photography technology and bridge video surveillance system, it will achieve display and evaluation predictions of facilities caused by human destruction of bridges and natural disasters. In the virtual bridge, display the type of accident type, location, and area facilities and equipment monitoring data and operating status information, and the distribution of emergency resources, and analyze the danger. According to the relevant plan, the emergency treatment plan is quickly formed to assist preferred personnel evacuation paths and traffic guidance paths. Provide a basis for emergency decision -making, command scheduling and disposal. As shown in Figure 5.

Figure 5 Digital twin long bridge emergency management service architecture

Maintenance

The structure of the long bridge is complicated, and the process of information understanding and coordination involves a lot of information understanding and coordination in the maintenance and maintenance process. Digital twin technology can provide users with high degree of visualized medium and can interact with virtual bridges. Complete maintenance and maintenance tasks efficiently and accurately. Before maintenance, you can conduct three -dimensional roaming, collision inspection, construction simulation, etc. in the virtual bridge based on the maintenance and maintenance plan, and find out unreasonable places in the plan. In the bridge. During the maintenance and maintenance process, the maintenance site can be projected into the virtual bridge, and whether the school check -in construction is consistent with the plan, and then make timely modification or remedial measures. Costs, security and other information are reflected in the virtual bridge in real time for visual display analysis. As shown in Figure 6. Figure 6 Digital twin long bridge maintenance and maintenance service architecture

Health monitoring

Bridge structure Health monitoring uses modern sensing technology, data collection transmission technology, signal analysis technology, etc., to measure, collect, process and analyze the environmental performance parameters of the bridge's environmental effects, load response, and the structural performance parameters of the bridge. The long bridge health monitoring system obtains a large amount of sensor monitoring data and other status related information. These polygonal heterogeneous, space -time discrete data constitute the main data sources in the process of long bridge digital twin pipe care. Health monitoring needs to be based on the analysis of the finite element model, but during the analysis of the limited element analysis, due to the assumptions of units, boundary conditions, parameter values, etc., the calculation analysis results are deviated with the actual response of the bridge. Digital twin uses twin data as a driving model, which can improve the damage recognition efficiency of monitoring data and evaluate the quality and use the monitoring data as a supplement to correct the finite element analysis to improve the accuracy of finite element analysis. As shown in Figure 7.

Figure 7 Digital twin long bridge health monitoring service architecture

Decision support

At present, the maintenance management of the bridge is mostly afterwards. When the damage reaches a certain degree, the necessary maintenance is easy to cause waste or inadequate maintenance of maintenance resources. The use of digital twin technology can effectively obtain various historical data in the long bridge pipe, combined with technical conditions, reliability, durability, and applicability, etc. to comprehensively evaluate the bridge. Use the principles of Bayes, Marcoov and other principles to establish the performance degradation probability distribution of bridges or components, and then aim at the minimum cost and maximum performance of the surplus life cycle to establish a multi -target optimization model, so as to transform traditional post -primary maintenance into pre -maintenance beforehand. , Realize the reasonable maintenance strategy design of bridge preventive maintenance, and achieve the purpose of early maintenance. Digital twin -driving long bridge maintenance strategy is based on the twin data, a new model of long bridge decision management formed by synchronous mapping and real -time interaction of physical bridges and virtual bridges. As shown in Figure 8.

Figure 8 Digital twin bridge auxiliary decision -making service architecture

Traffic control

Pay data monitoring, operating vehicle satellite positioning, multiplier personnel mobile signaling, Internet maps and other data to the long bridge twin data system, based on the management system of integrated transportation monitoring equipment, environmental monitoring equipment, and urban road electromechanical equipment , Analyze the traffic flow, traffic time, average speed speed, etc. of the bridge, use AI image recognition, simulation algorithm and other data processing technologies to predict the traffic data and potential congestion risks of the future period, to realize the real -time nature of lane -level traffic information The extensiveness of services, effectively solve the pain points of the industry with difficulty in traffic traffic and difficulties in decision -making, reduce the occupation rate and traffic traffic rate, and improve the efficiency of traffic. As shown in Figure 9.

Figure 9 Digital twin long bridge traffic control service architecture

Future

At present, the research and application of digital twins in the nourishment of the long bridge is in the initial stage. The following aspects still need to be further studied:

Deep integration of digital twin and computer technology

Digital twin technology should be applied in the long -bridge pipes, which is inseparable from the support of various computer technologies, especially relying on the development of information technologies such as artificial intelligence and big data. For example, the interconnection integration between twin data and physical bridges, virtual bridges, and services requires the support of the Internet of Things. The storage sharing of large amounts of data requires relying on cloud services, and the driver of analyzing decision -making depends on the support of big data and artificial intelligence algorithms. In addition, 3R (VR/AR/MR) is indispensable for visual interaction. Only the deep fusion of the two can effectively ensure the ideal effect of digital twins in the nourishment of the long bridge.

Digital twin standard specifications

There are fewer digital twin standards at home and abroad, and most of them are overview of conceptual terms and overall universal frameworks. The lack of specific descriptions of modeling language, data connection, and integrated platform services. The application of digital twins in the field of long bridge pipe care involves multi -disciplinary cross -interdisciplinary cross -disciplinary cross -disciplinary cross -disciplinary guidelines and theoretical applications. It can play a leading role in the further deepening development of digital twins in the pipeline of the long bridge.

Deepen Digital twin digital technology research

Bridge tube nourishing digital twin models lack the theoretical system guidance.Digital twin virtual models involve a wide range of fields, high integration, and high digital design levels such as bridges and other traditional industries. The level of basic design capabilities is still not high.It is a lack of digital simulation capabilities for key core components or processes.Carrying out digital design research can break through the bottleneck of digital twin technology development and promote the application of technology in bridge pipe care.In the future, the digital twin and the digital economy of the bridge will continue to integrate and innovate, forming a new situation that affects the influence of physical bridge and virtual bridges in parallel., Help a century -old bridge management and regional economic development.

This article is published / "Bridge Conservation and Operation" magazine

2022, Issue 3, Issue 19

Author /Guo Donghao

Author Unit /Jiangsu Sutong Bridge Co., Ltd.

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