CN115327952A - Bridge intelligent time-varying twinning system and method based on AI and multi-source information fusion - Google Patents
Bridge intelligent time-varying twinning system and method based on AI and multi-source information fusion Download PDFInfo
- Publication number
- CN115327952A CN115327952A CN202211108610.4A CN202211108610A CN115327952A CN 115327952 A CN115327952 A CN 115327952A CN 202211108610 A CN202211108610 A CN 202211108610A CN 115327952 A CN115327952 A CN 115327952A
- Authority
- CN
- China
- Prior art keywords
- module
- bridge
- design
- analysis
- finite element
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 32
- 230000004927 fusion Effects 0.000 title claims abstract description 30
- 238000004458 analytical method Methods 0.000 claims abstract description 97
- 238000013461 design Methods 0.000 claims abstract description 51
- 238000012800 visualization Methods 0.000 claims abstract description 48
- 238000007689 inspection Methods 0.000 claims abstract description 30
- 230000002787 reinforcement Effects 0.000 claims description 30
- 238000012544 monitoring process Methods 0.000 claims description 27
- 238000012423 maintenance Methods 0.000 claims description 26
- 238000010276 construction Methods 0.000 claims description 24
- 239000000463 material Substances 0.000 claims description 16
- 238000004590 computer program Methods 0.000 claims description 14
- 238000003860 storage Methods 0.000 claims description 11
- 238000012545 processing Methods 0.000 claims description 9
- 201000010099 disease Diseases 0.000 claims description 6
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 6
- 230000008569 process Effects 0.000 claims description 5
- 230000000007 visual effect Effects 0.000 claims description 4
- 239000002699 waste material Substances 0.000 claims description 4
- 230000008439 repair process Effects 0.000 claims description 2
- 238000010835 comparative analysis Methods 0.000 claims 1
- 238000010586 diagram Methods 0.000 description 13
- 230000006870 function Effects 0.000 description 8
- 230000003014 reinforcing effect Effects 0.000 description 7
- 238000001514 detection method Methods 0.000 description 3
- 238000007789 sealing Methods 0.000 description 3
- 229910001294 Reinforcing steel Inorganic materials 0.000 description 2
- 229910000831 Steel Inorganic materials 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 239000010959 steel Substances 0.000 description 2
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000003628 erosive effect Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 230000002441 reversible effect Effects 0.000 description 1
- 238000009991 scouring Methods 0.000 description 1
- 238000005303 weighing Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B17/00—Systems involving the use of models or simulators of said systems
- G05B17/02—Systems involving the use of models or simulators of said systems electric
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
- Bridges Or Land Bridges (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention belongs to the technical field of bridges and provides an AI and multi-source information fusion-based bridge intelligent time-varying twinning system and method. The system comprises an acquisition module, an analysis module, a design module and a visualization module; the acquisition module is used for respectively acquiring the ship flow and the vehicle flow; the analysis module is used for analyzing the time period with the lowest flow according to the flow of the ship, determining the time period as the inspection working time period of the underwater robot, and sending an inspection instruction to the acquisition module so as to enable the underwater robot to perform inspection; the system is used for analyzing a time period with the lowest traffic flow according to the traffic flow of the road surface, and determining the time period as an unmanned aerial vehicle inspection time period so that the unmanned aerial vehicle can inspect cracks and pot holes of the bridge road surface according to set flight logic and display the cracks and pot holes in a visualization module; the design module is provided with a BIM software interface which is used for receiving three-dimensional forward design data, converting the design parameters transmitted by the design module into a finite element model and sending the finite element analysis result to the visualization module.
Description
Technical Field
The invention belongs to the technical field of bridges, and particularly relates to an AI and multi-source information fusion-based bridge intelligent time-varying twinning system and method.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The design of bridge, construction, operation, maintenance reinforcement, demolish each stage be independent each other, lead to the information sharing between each stage, when a stage takes place the problem, can not grasp actual conditions and provide the solution fast high-efficiently.
Disclosure of Invention
The invention provides an AI and multi-source information fusion-based bridge intelligent time-varying twinning system and method, aiming at reducing the manpower consumption of a bridge from design to demolition, solving the problems that the problem condition that the problem cannot be timely obtained when the problem occurs in each stage and the solution cannot be rapidly provided.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides a bridge intelligent time-varying twin system based on AI and multi-source information fusion.
Bridge wisdom time-varying twin system based on AI and multisource information fusion includes: the system comprises an analysis module, an acquisition module, a design module and a visualization module, wherein the acquisition module, the design module and the visualization module are all connected with the analysis module;
the acquisition module is used for respectively acquiring the flow of a ship and the flow of a vehicle;
the analysis module is used for analyzing the time period with the lowest flow according to the flow of the ship, determining the time period as the inspection working time period of the underwater robot, sending an inspection instruction to the acquisition module so that the underwater robot can inspect and display the inspection working time period in the visualization module; the system is used for analyzing a time period with the lowest traffic flow according to the traffic flow of the road surface, and determining the time period as an unmanned aerial vehicle inspection time period so that the unmanned aerial vehicle can inspect cracks and pot holes of the bridge road surface according to set flight logic and display the cracks and pot holes in a visualization module;
and the design module is provided with a BIM software interface and is used for receiving three-dimensional forward design data, converting the design parameters transmitted by the design module into a finite element model and transmitting the finite element analysis result to the visualization module.
The second aspect of the invention provides a bridge intelligent time-varying twinning method based on AI and multi-source information fusion.
The intelligent time-varying twin method for the bridge based on AI and multi-source information fusion adopts the intelligent time-varying twin system for the bridge based on AI and multi-source information fusion in the first aspect, and comprises the following steps:
in the design stage, BIM software is used for forward design, various bridge design parameters are input into a design module through a BIM software interface of the design module, parameter information is sent to a visualization module for three-dimensional model reconstruction and visual display, the visualization module automatically generates a three-dimensional model with coordinates by reading bridge design information, meanwhile, the design information is sent to an analysis module, the analysis module performs finite element analysis on the bridge model, a finite element analysis result is provided, and the finite element analysis result is displayed through the visualization module;
in the construction stage, a local area network is built on site, monitoring instruments and equipment are arranged, the instruments and the equipment are connected with the local area network, monitoring data are provided with coded identifiers and uploaded to a collection module of the twin system in real time through the network, the collection module sends the data to an analysis module, the analysis module processes the data and returns the data to a visualization module, and the visualization module displays the data;
in the operation maintenance stage, monitoring equipment is installed on a bridge, vehicle flow, weight, wind speed, humidity and deflection are monitored in real time, an unmanned aerial vehicle and an underwater robot are introduced to realize daily routing inspection, monitoring data are uploaded to an analysis module and a visualization module through a network, the analysis module compares the received monitoring data with a finite element analysis result in the design stage, and the comparison result is sent to the visualization module; the analysis module provides a solution for the existing disease problem according to the existing bridge monitoring data and the finite element analysis result, and carries out early warning on the disease problem which possibly occurs in the future;
in the maintenance and reinforcement stage, an analysis module selects a plurality of maintenance and reinforcement schemes from a maintenance and reinforcement scheme library aiming at the problems, automatically analyzes a plurality of suitable schemes aiming at the types, spans and materials of the bridge, analyzes the material consumption and the construction period of various schemes, utilizes interface connection finite element analysis software, analyzes the safety performance of the bridge after the reinforcement scheme is implemented, and provides a maintenance and reinforcement scheme report;
in the demolition stage, the analysis module judges whether the bridge enters the demolition stage according to the service life of the bridge, the monitoring data and the early warning system, after demolition is judged, the analysis module intelligently analyzes the quantity and the construction period of the construction waste according to historical data, and the result is uploaded to the visualization module.
A third aspect of the invention provides a computer-readable storage medium.
A computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps in the method for intelligent time-varying twin of a bridge based on AI and multi-source information fusion as described in the second aspect above.
A fourth aspect of the invention provides a computer apparatus.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the steps of the AI and multi-source information fusion-based bridge intelligent time-varying twin method according to the second aspect.
Compared with the prior art, the invention has the beneficial effects that:
the invention aims to reduce the manpower consumption of a bridge from design to demolition, solve the problem that the bridge cannot be obtained in time when a problem occurs in each stage and cannot provide a solution rapidly, manage the whole life cycle of the bridge based on AI and multi-source information fusion, react the self state of the bridge and the surrounding environment on a visualization module of a system, automatically acquire data by utilizing unmanned equipment inspection logic built in an acquisition module, evaluate the current state and the future change trend of the bridge by utilizing units built in an analysis module, provide and judge a needed maintenance reinforcement and demolition scheme and evaluate the manufacturing cost. The invention reduces the manpower consumption of the bridge from design to demolition, can find various problems in time for users when the system runs, and provides an analysis report and a solution.
Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
Fig. 1 is a frame diagram of a bridge intelligent time-varying twin system based on AI and multi-source information fusion according to an embodiment of the present invention.
Detailed Description
The invention is further described with reference to the following figures and examples.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
It is noted that the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of methods and systems according to various embodiments of the present disclosure. It should be noted that each block in the flowchart or block diagrams may represent a module, a segment, or a portion of code, which may comprise one or more executable instructions for implementing the logical function specified in the respective embodiment. It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Example one
The embodiment provides a bridge intelligent time-varying twin system based on AI and multi-source information fusion.
As shown in fig. 1, the bridge intelligent time-varying twin system based on AI and multi-source information fusion includes: the device comprises a design module, an acquisition module, an analysis module and a visualization module.
The acquisition module comprises unmanned equipment inspection, sensor real-time acquisition and image acquisition. Wherein, the real-time acquisition of the sensor comprises the real-time acquisition of stress-strain data by the stress-strain sensor.
The analysis module comprises a finite element analysis unit, a maintenance and reinforcement scheme library, a comparison analysis processing unit, a construction cost unit and an AI image recognition unit.
And the design module is provided with a BIM software interface and is used for receiving three-dimensional forward design data, and the data received by the design module is sent to the analysis module and the visualization module through the conversion module.
The acquisition module adopts the multisource data acquisition form, including unmanned aerial vehicle, robot, each type sensor, each type camera for monitor boat flow, stream of people and traffic, wind speed, riverbed scouring condition, pier erosion situation, show bridge self state and all ring edge borders.
The acquisition module carries out operation and maintenance by using a periodic detection method, and an unmanned equipment station is arranged at the bottom of the bridge.
The unmanned equipment station comprises an underwater robot, an unmanned aerial vehicle, charging equipment, a stair and a storage platform, and the unmanned detection equipment performs bridge detection according to set inspection logic.
The unmanned aerial vehicle inspection system comprises an unmanned aerial vehicle inspection logic, an analysis module, an underwater robot inspection working time period, an analysis module, a temporary navigation channel sealing time period and an inspection instruction, wherein the analysis module is used for statistically analyzing the lowest time period of the flow according to ship navigation flow received by a collection module and according to historical monitoring records, the analysis module is used for determining the time period as the inspection working time period of the underwater robot, the analysis module is used for sending the temporary navigation channel sealing time period to a user and a navigation management system, the analysis module is used for sending the inspection instruction to the collection module, the underwater robot is used for inspection, and the real-time working position and the working time of the underwater robot are sent to a visualization module for display.
The unmanned aerial vehicle inspection system comprises an unmanned aerial vehicle inspection logic, an analysis module intelligently analyzes road traffic flow, the lowest time period of traffic flow is analyzed according to historical monitoring data statistics, the analysis module determines the time period as the unmanned aerial vehicle inspection time period, the analysis module sends temporary road sealing information to users and highway managers, the unmanned aerial vehicle inspects cracks and pits on the bridge road surface according to the set flight logic, and acquired images are sent to the analysis module in real time.
After the analysis module receives the image of the unmanned inspection equipment, the AI image recognition unit recognizes the pot hole and the crack, counts the pot hole and the crack, and sends a result report to the visualization module.
And the acquisition module is provided with a network interface and receives sensor data, video pictures and vehicle weighing data through wired and wireless transmission technologies.
And the analysis module is used for converting the design parameters transmitted by the design module into a finite element model and transmitting the finite element analysis result to the visualization module.
And the analysis module automatically compares the finite element analysis result with the real-time bridge monitoring result and displays the finite element analysis result and the real-time bridge monitoring result in the visualization module.
The analysis module can automatically read data transmitted back by the bridge in real time through the data of the acquisition module through a built-in analysis logic, and the data is sent to the visualization module after calculation and analysis.
The system comprises an analysis module, a built-in maintenance and reinforcement scheme library, and a plurality of suitable schemes are automatically analyzed according to the type, span and material of a bridge, wherein the maintenance and reinforcement scheme library is divided into a maintenance scheme library and a reinforcement scheme library, for the maintenance scheme library, unmanned acquisition equipment of the acquisition module acquires concrete surface images and scans the surface with a certain thickness of concrete into a three-dimensional entity, a comparison analysis processing unit calculates the volume under the thickness, the volume is different from the partial volume under design parameters to obtain the defect volume of the concrete, a project cost unit gives the using amount of repair materials according to the volume, and a construction period is given according to the daily workload of workers and the number of workers.
For the reinforcing scheme library, a section enlarging reinforcing method, an external prestress reinforcing method, a pasting reinforcing method, an auxiliary component increasing reinforcing method and a structural system changing reinforcing method are arranged in the reinforcing scheme library. The schemes are implemented by calling finite element analysis software, and the main instructions of the reinforcement scheme library comprise the steps of increasing the number of reinforcing steel bars, increasing the cross-sectional area of concrete, adding external prestressed pull rods, sticking steel plates outside the concrete and reinforcing steel bars. And sending an instruction to the finite element analysis software by the reinforcement scheme library, adding reinforcement materials with different materials and sizes according to different schemes, extracting the critical section stress, and judging whether the reinforcement scheme meets the safety performance requirement or not according to a critical safety value set in the finite element software. The construction cost unit gives the amount of the repairing material according to the amount of the repairing material, and gives the construction period according to the daily workload of workers and the number of workers.
The interface is connected with finite element analysis software to analyze the safety performance of the reinforced bridge, a user can properly check and modify the finite element analysis model at any time, the operation steps are recorded into the analysis module at any time, and the analysis module dynamically adjusts the maintenance and reinforcement scheme.
And when the service life of the bridge reaches the standard requirement or the scheme given by the maintenance and reinforcement scheme library cannot be implemented, the analysis module judges that the bridge enters a dismantling stage, calculates the volume and weight of concrete, steel bars and reinforcement materials according to the existing visual model after dismantling, and gives a construction period after adding artificial machines participating in dismantling.
And the visualization module is used for displaying the data returned by the data acquisition module and the result of data analysis in real time through a proper chart and a three-dimensional bridge map.
Example two
The embodiment provides a bridge intelligent time-varying twin method based on AI and multi-source information fusion, and the embodiment is exemplified by applying the method to a server. The server can be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, and can also be a cloud server for providing basic cloud computing services such as cloud service, a cloud database, cloud computing, cloud functions, cloud storage, a network server, cloud communication, middleware service, domain name service, security service CDN (content delivery network), a big data and artificial intelligence platform and the like. The terminal may be, but is not limited to, a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, and the like. The terminal and the server may be directly or indirectly connected through wired or wireless communication, and the application is not limited herein. In this embodiment, the method includes the steps of:
firstly, in a design stage, a designer utilizes BIM software to carry out forward design, various design parameters of a bridge are input into a design module through a BIM software interface of the design module, parameter information is sent to a visualization module to carry out three-dimensional model reconstruction and visual display, the visualization module automatically generates a three-dimensional model with coordinates by reading bridge design information, meanwhile, the design information is sent to an analysis module, the analysis module carries out finite element analysis on the bridge model, an analysis report is issued, and the analysis report is displayed through the visualization module.
And secondly, in a construction stage, from the construction site to the completion delivery, constructing a local area network on the site, arranging monitoring instruments and equipment, connecting the instrument and the equipment with the local area network, uploading monitoring data with a code identifier to an acquisition module of the twin system in real time through the network, sending the data to an analysis module by the acquisition module, processing the data by the analysis module and returning the data to a visualization module, and displaying the data by the visualization module.
And step three, in the operation and maintenance stage, mounting monitoring equipment on the bridge, monitoring the vehicle flow, the weight, the wind speed, the humidity and the deflection in real time, introducing an unmanned aerial vehicle and an underwater robot, realizing daily inspection, uploading monitoring data to an analysis module and a visualization module through a network, comparing the received monitoring data with a finite element analysis result in the step one by the analysis module, and sending a comparison result to the visualization module. The analysis module provides a solution for the existing disease problem according to the existing bridge monitoring data and the finite element analysis result, and carries out early warning on the disease problem which possibly occurs in the future.
And step four, in the maintenance and reinforcement stage, the analysis module selects a plurality of maintenance and reinforcement schemes from the scheme library aiming at the problems, automatically analyzes a plurality of suitable schemes aiming at the types, spans and materials of the bridge, analyzes the material consumption and the construction period of the schemes, utilizes the interface connection finite element analysis software to analyze the safety performance of the bridge after the reinforcement scheme is implemented, and provides a maintenance and reinforcement scheme report for a user to refer.
And fifthly, in the dismantling stage, judging whether the bridge enters the dismantling stage or not by the analysis module according to the service life of the bridge, the monitoring data and the early warning system, after the dismantling is judged, intelligently analyzing the quantity and the construction period of the construction waste by the analysis module according to historical data, and uploading the result to the visualization module.
EXAMPLE III
The present embodiment provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps in the AI and multi-source information fusion-based bridge intelligent time-varying twin method according to the second embodiment.
Example four
The embodiment provides a computer device, which includes a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the method for intelligently time-varying twinning a bridge based on AI and multi-source information fusion as described in the second embodiment.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. Bridge wisdom time-varying twin system based on AI and multisource information fusion, its characterized in that includes: the system comprises an analysis module, an acquisition module, a design module and a visualization module, wherein the acquisition module, the design module and the visualization module are all connected with the analysis module;
the acquisition module is used for respectively acquiring the flow of a ship and the flow of a vehicle;
the analysis module is used for analyzing the time period with the lowest flow according to the flow of the ship, determining the time period as the inspection working time period of the underwater robot, sending an inspection instruction to the acquisition module so that the underwater robot can inspect and display the inspection working time period in the visualization module; the system is used for analyzing a time period with the lowest traffic flow according to the traffic flow of the road surface, and determining the time period as an unmanned aerial vehicle inspection time period so that the unmanned aerial vehicle can inspect cracks and pot holes of the bridge road surface according to set flight logic and display the cracks and pot holes in a visualization module;
and the design module is provided with a BIM software interface and is used for receiving the three-dimensional forward design data, converting the design parameters transmitted by the design module into a finite element model and transmitting the finite element analysis result to the visualization module.
2. The AI-and multi-source information fusion-based bridge intelligent time-varying twin system of claim 1, wherein the analysis module comprises a finite element analysis unit, a maintenance reinforcement scheme library, a comparative analysis processing unit, a construction cost unit and an AI image recognition unit.
3. The AI-and multi-source information fusion-based bridge intelligent time-varying twinning system of claim 2, wherein the repair and reinforcement scheme library is configured to analyze a plurality of schemes according to bridge type, span and material, analyze material usage and construction period of each scheme, select an optimal scheme, interface with a finite element analysis unit, and analyze the safety performance of the reinforced bridge through a finite element analysis model to obtain a finite element analysis result.
4. The AI-and multi-source information fusion-based bridge intelligent time-varying twin system as claimed in claim 2, wherein the comparison analysis processing unit is configured to compare the finite element analysis result with the data uploaded from the acquisition module to the twin system for display in the visualization module.
5. The AI-and multi-source information fusion-based bridge intelligent time-varying twin system as claimed in claim 2, wherein the engineering cost unit is configured to calculate material usage and construction period according to a scheme provided by the maintenance and reinforcement scheme library;
and the AI image recognition unit is used for recognizing the pot holes and the cracks, counting the pot holes and the cracks, issuing a result report and sending the result report to the visualization module.
6. The AI-and multi-source information fusion-based bridge intelligent time-varying twin system as recited in claim 1, wherein the analysis module is further configured to determine whether the bridge enters a demolition stage according to the service life of the bridge, the monitoring data and the warning information, and after demolition is determined, the analysis module analyzes the amount of construction waste and the construction period according to the historical data.
7. The AI-and multi-source information fusion-based bridge intelligent time-varying twin system according to claim 1, wherein the collection module comprises unmanned aerial vehicle inspection equipment, a sensor and an image collector.
8. The method for intelligently time-varying twinning of a bridge based on AI and multi-source information fusion is characterized in that the system for intelligently time-varying twinning of a bridge based on AI and multi-source information fusion of any one of claims 1 to 7 is adopted, and comprises the following steps:
in the design stage, BIM software is used for forward design, various bridge design parameters are input into the design module through a BIM software interface of the design module, parameter information is sent to a visualization module for three-dimensional model reconstruction and visual display, the visualization module automatically generates a three-dimensional model with coordinates by reading bridge design information, meanwhile, the design information is sent to an analysis module, the analysis module performs finite element analysis on the bridge model, provides a finite element analysis result and displays the finite element analysis result through the visualization module;
in the construction stage, a local area network is built on site, monitoring instruments and equipment are arranged, the instruments and the equipment are connected with the local area network, monitoring data are provided with coded identifiers and uploaded to an acquisition module of the twin system in real time through the network, the acquisition module sends the data to an analysis module, the analysis module processes the data and returns the data to a visualization module, and the visualization module displays the data;
in the operation and maintenance stage, monitoring equipment is installed on a bridge to monitor the vehicle flow, weight, wind speed, humidity and deflection in real time, an unmanned aerial vehicle and an underwater robot are introduced to realize daily inspection, monitoring data are uploaded to an analysis module and a visualization module through a network, the analysis module compares the received monitoring data with a finite element analysis result in the design stage, and the comparison result is sent to the visualization module; the analysis module provides a solution for the existing disease problem according to the existing bridge monitoring data and the finite element analysis result, and carries out early warning on the disease problem which possibly occurs in the future;
in the maintenance and reinforcement stage, an analysis module selects a plurality of maintenance and reinforcement schemes from a maintenance and reinforcement scheme library aiming at the problems, automatically analyzes a plurality of suitable schemes aiming at the types, spans and materials of the bridge, analyzes the material consumption and the construction period of various schemes, utilizes interface connection finite element analysis software, analyzes the safety performance of the bridge after the reinforcement scheme is implemented, and provides a maintenance and reinforcement scheme report;
in the demolition stage, the analysis module judges whether the bridge enters the demolition stage according to the service life of the bridge, the monitoring data and the early warning system, after demolition is judged, the analysis module intelligently analyzes the quantity and the construction period of the construction waste according to historical data, and the result is uploaded to the visualization module.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the AI-and multi-source information fusion-based bridge intelligent time-varying twin method as claimed in claim 8.
10. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps in the AI and multi-source information fusion based bridge intelligent time-varying twin method as claimed in claim 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211108610.4A CN115327952A (en) | 2022-09-13 | 2022-09-13 | Bridge intelligent time-varying twinning system and method based on AI and multi-source information fusion |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211108610.4A CN115327952A (en) | 2022-09-13 | 2022-09-13 | Bridge intelligent time-varying twinning system and method based on AI and multi-source information fusion |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115327952A true CN115327952A (en) | 2022-11-11 |
Family
ID=83929449
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211108610.4A Pending CN115327952A (en) | 2022-09-13 | 2022-09-13 | Bridge intelligent time-varying twinning system and method based on AI and multi-source information fusion |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115327952A (en) |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109612427A (en) * | 2019-01-16 | 2019-04-12 | 兰州交通大学 | A kind of the unmanned plane highway bridge deformation detecting method and system of multi-sensor cooperation |
| CN110516820A (en) * | 2019-07-16 | 2019-11-29 | 西南交通大学 | A kind of steel structure bridge informationization operational system and processing method based on BIM |
| CN110852001A (en) * | 2018-07-25 | 2020-02-28 | 浙江大学 | Bridge structure safety assessment method based on image processing |
| CN111143932A (en) * | 2019-12-26 | 2020-05-12 | 杭州鲁尔物联科技有限公司 | Bridge health state assessment method, device, system and equipment |
| CN112598319A (en) * | 2020-12-30 | 2021-04-02 | 重庆源道建筑规划设计有限公司 | Intelligent bridge operation and maintenance management method and system based on BIM, computer equipment and storage medium |
| CN113269128A (en) * | 2021-06-10 | 2021-08-17 | 成都软易达信息技术有限公司 | Automatic disease identification method and system based on AI intelligence |
| CN113806978A (en) * | 2021-08-31 | 2021-12-17 | 华南理工大学 | Bridge structure digital twin body and method based on BIM-FEM |
| CN113971300A (en) * | 2020-07-22 | 2022-01-25 | 上海禅净数字技术有限公司 | Bridge maintenance and reconstruction information visualization method |
-
2022
- 2022-09-13 CN CN202211108610.4A patent/CN115327952A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110852001A (en) * | 2018-07-25 | 2020-02-28 | 浙江大学 | Bridge structure safety assessment method based on image processing |
| CN109612427A (en) * | 2019-01-16 | 2019-04-12 | 兰州交通大学 | A kind of the unmanned plane highway bridge deformation detecting method and system of multi-sensor cooperation |
| CN110516820A (en) * | 2019-07-16 | 2019-11-29 | 西南交通大学 | A kind of steel structure bridge informationization operational system and processing method based on BIM |
| CN111143932A (en) * | 2019-12-26 | 2020-05-12 | 杭州鲁尔物联科技有限公司 | Bridge health state assessment method, device, system and equipment |
| CN113971300A (en) * | 2020-07-22 | 2022-01-25 | 上海禅净数字技术有限公司 | Bridge maintenance and reconstruction information visualization method |
| CN112598319A (en) * | 2020-12-30 | 2021-04-02 | 重庆源道建筑规划设计有限公司 | Intelligent bridge operation and maintenance management method and system based on BIM, computer equipment and storage medium |
| CN113269128A (en) * | 2021-06-10 | 2021-08-17 | 成都软易达信息技术有限公司 | Automatic disease identification method and system based on AI intelligence |
| CN113806978A (en) * | 2021-08-31 | 2021-12-17 | 华南理工大学 | Bridge structure digital twin body and method based on BIM-FEM |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109472091B (en) | Assembly type building construction and service stage monitoring system and method | |
| CN107194861B (en) | Road network operation comprehensive monitoring management platform and method based on 3DGIS + BIM | |
| CN111021265B (en) | BIM technology-based railway large-span continuous beam swivel construction control method | |
| CN110516820B (en) | BIM-based steel structure bridge informatization operation and maintenance system and processing method | |
| CN110008591B (en) | Continuous rigid frame bridge construction management control method based on BIM | |
| CN112016908A (en) | BIM-based construction progress monitoring method and system, electronic equipment and storage medium | |
| CN112785458A (en) | Intelligent management and maintenance system for bridge health big data | |
| CN111582188B (en) | Concrete pouring side station supervision method based on artificial intelligence | |
| CN107146041A (en) | A kind of road network based on 3DGIS+BIM runs long-range disease screening interactive system and method | |
| CN110717736A (en) | Construction progress intelligent tracking method and system for building | |
| CN114912641A (en) | Road network bridge and tunnel maintenance decision and intelligent inspection system based on BIM | |
| CN115494802A (en) | Flow operation multi-level safety digital intelligent monitoring system | |
| CN111445160A (en) | Self-accompanying concrete quality management method based on artificial intelligence video analysis | |
| CN115327952A (en) | Bridge intelligent time-varying twinning system and method based on AI and multi-source information fusion | |
| CN111582191A (en) | Pouring amount estimation method in concrete pouring based on artificial intelligence video analysis | |
| CN110348145B (en) | Construction method for building tunnel based on BIM technology | |
| CN117114412A (en) | Safety pre-control method and device for dangerous chemical production enterprises | |
| CN116993665A (en) | Intelligent detection method for construction progress of construction engineering working face based on computer vision | |
| CN111062827A (en) | Engineering supervision method based on artificial intelligence mode | |
| CN115440044A (en) | Road multi-source event data fusion method and device, storage medium and terminal | |
| CN112487925B (en) | Bridge load damage identification method and system | |
| CN113128837A (en) | Big data analysis system of rail transit power supply system | |
| CN104023205A (en) | Intelligent security monitoring system | |
| CN113888043A (en) | Full-period visual management and analysis system for girder diseases of beam bridge | |
| CN112115876A (en) | Water-soluble method experimental process identification method based on 3D convolutional neural network |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |