CN109992827B - Bridge structure early warning method, bridge structure early warning device, computer equipment and storage medium - Google Patents
Bridge structure early warning method, bridge structure early warning device, computer equipment and storage medium Download PDFInfo
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- 238000004590 computer program Methods 0.000 claims description 18
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
Abstract
The application relates to a bridge structure early warning method, a bridge structure early warning device, computer equipment and a storage medium. The method comprises the following steps: collecting weight information and vehicle identification of a vehicle in a running state; inputting the weight information of the vehicle into a bridge load transverse distribution model to obtain response data of the bridge; when the response data of the bridge exceeds a set threshold value, acquiring the position information of the vehicle on the bridge through the vehicle identifier, and sending out alarm information; the response data comprises at least one of a cable force value, a deflection value, a strain value, an acceleration value, a crack width value and an inclination angle value. By adopting the method, the bridge structure can be early warned in real time.
Description
Technical Field
The present application relates to the field of communications technologies, and in particular, to a bridge structure early warning method, a device, a computer device, and a storage medium.
Background
Bridges are generally structures erected on rivers, lakes and seas to enable vehicles, pedestrians and the like to pass smoothly, and are also buildings erected to span mountain streams, poor geology or meet other traffic needs to enable passing to be more convenient and fast in order to adapt to the traffic industry of modern high-speed development. The bridge is generally composed of an upper structure, a lower structure, a support and an accessory structure, wherein the upper structure is also called a bridge span structure and is a main structure for crossing obstacles; the lower structure comprises a bridge abutment, a bridge pier and a foundation; the support is a force transmission device arranged at the supporting position of the bridge span structure and the bridge pier or the bridge abutment; the auxiliary structure is bridge end butt strap, cone slope protection, bank protection, diversion engineering, etc. Because of the importance of the bridge, the bridge structure is evaluated in real time to ensure the passing safety, and when the traffic tool to be passed through the bridge deck is judged to exceed the bearing range of the bridge, the bridge structure needs to be pre-warned.
At present, the common bridge structure early warning method is based on the theoretical methods such as a deterministic early warning method, a gray system early warning method, a neural network early warning method, a time sequence early warning method and the like. The existing bridge structure early warning method can early warn according to the part of the bridge structure, and the traffic of bridge deck vehicles needs to be limited when relevant parameters are acquired, so that the following problems exist in the prior art: real-time early warning cannot be performed on vehicles passing through the bridge.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a bridge structure early warning method, device, computer device and storage medium capable of early warning a bridge structure in real time.
A bridge construction pre-warning method, the method comprising:
collecting weight information and vehicle identification of a vehicle in a running state;
inputting the weight information of the vehicle into a bridge load transverse distribution model to obtain response data of the bridge;
when the response data of the bridge exceeds a set threshold value, acquiring the position information of the vehicle on the bridge through the vehicle identifier, and sending out alarm information;
the response data comprises at least one of a cable force value, a deflection value, a strain value, an acceleration value, a crack width value and an inclination angle value.
In one embodiment, the method further comprises:
setting a plurality of measuring points on the bridge deck of the bridge;
detecting stress applied to the measuring point and generating bridge structure response according to the stress;
establishing a bridge load transverse distribution model of the bridge structure according to the stress and the bridge structure response;
the bridge structure response is obtained through measurement of sensors arranged at the measuring points, and the response comprises cable force, deflection, strain, acceleration, crack width and inclination angle.
In one embodiment, the measuring point is an area where damage to the bridge structure is likely to occur.
In one embodiment, the detecting the stress applied to the measuring point and the bridge structure response generated according to the stress comprises:
detecting the running track of the vehicle according to the vehicle identification;
judging whether the vehicle reaches the measuring point or not through the running track;
when the vehicle reaches the measuring point, the stress applied to the measuring point and the bridge structure response generated according to the stress are detected.
In one embodiment, the vehicle is an overloaded vehicle.
In one embodiment, the vehicle identification includes at least one of license plate information, vehicle model information, and vehicle appearance characteristics.
In one embodiment, the method further comprises:
introducing the three-dimensional model of the bridge structure into a finite element model, applying stress to corresponding measuring points in the finite element model, and setting initial parameters of the finite element model to obtain simulation response generated according to the stress;
judging whether the absolute value of the difference between the simulation response and the bridge structure response is smaller than a set error;
if the initial parameter is smaller than the set error, the initial parameter is used as a final parameter of the finite element model;
and if the simulation response is not smaller than the set error, adjusting the initial parameters until the difference between the simulation response and the bridge structure response is smaller than the set error.
A bridge construction warning device, the device comprising:
the acquisition module is used for acquiring weight information and vehicle identification of the vehicle;
the response data calculation module is used for inputting the weight information of the vehicle into a bridge load transverse distribution model to obtain response data of the bridge;
and the alarm module is used for sending alarm information when the response data of the bridge exceeds a set threshold value, wherein the alarm information comprises the vehicle identifier, and the response data comprises at least one of a cable force value, a deflection value, a strain value, an acceleration value, a crack width value and an inclination angle value.
A computer device comprising a memory storing a computer program and a processor which when executing the computer program performs the steps of:
collecting weight information and vehicle identification of a vehicle in a running state;
inputting the weight information of the vehicle into a bridge load transverse distribution model to obtain response data of the bridge;
when the response data of the bridge exceeds a set threshold value, acquiring the position information of the vehicle on the bridge through the vehicle identifier, and sending out alarm information;
the response data comprises at least one of a cable force value, a deflection value, a strain value, an acceleration value, a crack width value and an inclination angle value.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
collecting weight information and vehicle identification of a vehicle in a running state;
inputting the weight information of the vehicle into a bridge load transverse distribution model to obtain response data of the bridge;
when the response data of the bridge exceeds a set threshold value, acquiring the position information of the vehicle on the bridge through the vehicle identifier, and sending out alarm information;
the response data comprises at least one of a cable force value, a deflection value, a strain value, an acceleration value, a crack width value and an inclination angle value.
According to the bridge structure early warning method, the device, the computer equipment and the storage medium, the weight information of the vehicle in the driving state and the vehicle identification are collected, the weight information of the vehicle is input into the bridge load transverse distribution model to judge whether the weight of the vehicle exceeds the bearing range of the bridge structure, when the weight exceeds the bearing range of the bridge structure, the overload vehicle process is tracked and overload warning information is sent out, overload can be early warned in real time, and damage to the bridge structure is prevented or the bridge structure can be maintained in time after the damage is detected.
Drawings
FIG. 1 is a schematic flow chart of a method for early warning a bridge structure in one embodiment;
FIG. 2 is a flow chart illustrating the steps of modeling the lateral distribution of the bridge Liang Hezai in one embodiment;
FIG. 3 is a block diagram of a bridge structure warning device in one embodiment;
fig. 4 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
In one embodiment, as shown in fig. 1, there is provided a bridge structure early warning method, including the following steps:
s110, acquiring weight information and vehicle identification of the vehicle in a driving state.
The vehicle in the running state, in particular, the vehicle does not need to be decelerated, stopped or changed in other running states when the weight information and the vehicle identification are acquired. The vehicle identification includes at least one of license plate information, vehicle model information, and vehicle appearance characteristics. The embodiment focuses on early warning of an overloaded vehicle, and of course, a common vehicle is also suitable for the technical scheme of the embodiment.
Specifically, weight information of the vehicle is obtained through the dynamic weighing equipment, and the vehicle identification is collected through the camera. Weight information and vehicle identification of a vehicle in a driving state are collected before the vehicle enters a bridge structure.
And S120, inputting the weight information of the vehicle into a bridge load transverse distribution model to obtain response data of the bridge.
The bridge load transverse distribution model is used for representing the relationship between stress acting on the bridge structure and response of the bridge structure. The response data comprises at least one of a cable force value, a deflection value, a strain value, an acceleration value, a crack width value and an inclination angle value.
And S130, when the response data of the bridge exceeds a set threshold value, acquiring the position information of the vehicle on the bridge through the vehicle identifier, and sending out alarm information.
The set threshold is determined according to the weight of the bridge structure, and can be calculated according to the bridge design structure parameters or measured by an instrument. The warning information is sent out according to the vehicle, so that the warning information can be sent out to the vehicle to prevent the vehicle from entering the bridge structure, and the warning information is uploaded to a background system, so that the overload vehicle entering the bridge structure can be recorded.
According to the method and the system, the position information of the vehicle in the bridge is obtained through the vehicle identification, which parts of the bridge are passed by the overloaded vehicle, particularly the damage areas which are easy to occur in the bridge structure can be detected, and if the overloaded vehicle passes the damage areas which are easy to occur, the system needs to record the areas so as to be convenient to maintain in time.
According to the bridge structure early warning method, the weight information of the vehicle in the driving state and the vehicle identification are collected, the weight information of the vehicle is input into the bridge load transverse distribution model to judge whether the weight of the vehicle exceeds the bearing range of the bridge structure, when the weight exceeds the bearing range of the bridge structure, the overload vehicle process is tracked and overload warning information is sent, overload can be early warned in real time, and damage to the bridge structure is prevented or the bridge structure can be maintained in time after the damage is detected.
In one embodiment, as shown in fig. 2, the bridge structure early warning method further includes the steps of:
s111, setting a plurality of measuring points on the bridge deck of the bridge.
The measuring points are used for testing multi-order modal response of the bridge structure so as to obtain a bridge load transverse distribution model. The measuring points are arranged at key sections of the bridge structure, namely areas where the bridge structure is easy to send damage.
S112, detecting stress applied to the measuring point and generating bridge structure response according to the stress.
The stress applied to the measuring point can be applied through vehicles passing through the bridge deck, specifically, weight information of the vehicles is obtained in advance through dynamic weighing equipment, then positions of the vehicles are obtained through a plurality of cameras, and when the vehicles pass through the measuring point, bridge structure response generated according to the stress is detected, wherein the stress is gravity generated by the weight of the vehicles.
And S113, establishing a bridge load transverse distribution model of the bridge structure according to the stress and the bridge structure response.
And obtaining a functional relation between the stress and the response by linear fitting or solving an equation set, and establishing a bridge load transverse distribution model of the bridge structure according to the functional relation.
The bridge structure response is obtained through measurement of sensors arranged at the measuring points, and the response comprises cable force, deflection, strain, acceleration, crack width and inclination angle.
In this embodiment, the bridge Liang Hezai transverse distribution model is built without limiting the traffic of bridge deck vehicles, and the stress applied to the measuring points can be detected by vehicles passing through the bridge deck, so that no additional measuring tool is needed, and the stress and strain of the bridge structure can be measured in real time by installing a camera at the bridge abutment and paving a sensor at the key section, thereby building the bridge load transverse distribution model of the bridge structure.
In one embodiment, the detecting the stress applied to the measuring point and the bridge structure response generated according to the stress comprises:
s1121, detecting the running track of the vehicle according to the vehicle identification.
Wherein the driving track is the track that the vehicle presses across the bridge deck. The vehicle identification can be obtained by collecting images of the vehicle according to the cameras, a plurality of cameras are arranged on the bridge abutment, vehicle information of the bridge deck is photographed in real time, and the driving track of the same vehicle can be formed by combining the vehicle identification according to the relay algorithm.
And S1122, judging whether the vehicle reaches the measuring point or not according to the running track.
The position of the measuring point on the bridge deck is known, and the running track of the vehicle is obtained according to the camera. When the running track passes through the measuring point, the vehicle can be judged to have reached the measuring point.
And S1123, when the vehicle reaches the measuring point, detecting stress applied to the measuring point and bridge structure response generated according to the stress.
The bridge structure response is obtained through sensor measurement arranged at the measuring point.
In one embodiment, the bridge structure early warning method further includes the steps of:
s114, the three-dimensional model of the bridge structure is led into a finite element model, stress is applied to corresponding measuring points in the finite element model, initial parameters of the finite element model are set, and simulation response generated according to the stress is obtained.
The finite element model is a model established by applying a finite element analysis method, is a group of module assemblies which are connected at nodes, transmit force by the nodes and are constrained at the nodes, is a discretization result of a mechanical model, and is a digital model for numerical calculation.
The three-dimensional model of the bridge structure comprises the volume and the density of the bridge structure, and the volume and the density can be measured by the existing instrument. And applying stress to the corresponding measuring points in the finite element model, wherein the stress is applied to the corresponding measuring points of the bridge structure by vehicles passing through the bridge deck.
S115, judging whether the absolute value of the difference between the simulation response and the bridge structure response is smaller than a set error.
The simulation response is calculated through a finite element model, and the bridge structure response is obtained through detection of a sensor arranged at a bridge deck measuring point.
And S116, if the initial parameter is smaller than the setting error, taking the initial parameter as a final parameter of the finite element model.
And S117, if the simulation response is not smaller than the set error, adjusting the initial parameters until the difference between the simulation response and the bridge structure response is smaller than the set error.
By the method, the finite element model of the bridge structure can be built in a background system, so that the bridge structure can be analyzed for stress and strain later.
It should be understood that, although the steps in the flowcharts of fig. 1-2 are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 1-2 may include multiple sub-steps or phases that are not necessarily performed at the same time, but may be performed at different times, nor does the order in which the sub-steps or phases are performed necessarily occur sequentially, but may be performed alternately or alternately with at least a portion of the sub-steps or phases of other steps or other steps.
In one embodiment, as shown in fig. 3, there is provided a bridge structure early warning device, including: the system comprises an acquisition module 210, a response data calculation module 220 and an alarm module 230, wherein:
the acquisition module 210 is configured to acquire weight information and a vehicle identifier of a vehicle in a driving state.
The vehicle identification comprises at least one of license plate information, vehicle model information and vehicle appearance characteristics.
And the response data calculation module 220 is configured to input the weight information of the vehicle into a bridge load transverse distribution model to obtain response data of the bridge.
The response data comprises at least one of a cable force value, a deflection value, a strain value, an acceleration value, a crack width value and an inclination angle value.
And the alarm module 230 is configured to obtain, when the response data of the bridge exceeds a set threshold, the position information of the vehicle on the bridge through the vehicle identifier, and send out alarm information.
The warning information is sent out according to the vehicle, so that the warning information can be sent out to the vehicle to prevent the vehicle from entering the bridge structure, and the warning information is uploaded to a background system, so that the overload vehicle entering the bridge structure can be recorded.
In one embodiment, a bridge structure early warning device further includes: and the bridge load transverse distribution model building module is used for building a bridge load transverse distribution model.
The bridge load transverse distribution model building module comprises: the measuring point setting unit is used for setting a plurality of measuring points on the bridge deck of the bridge; a stress and response detection unit for detecting stress applied to the measuring point and bridge structure response generated according to the stress; and the model building unit is used for building a bridge load transverse distribution model of the bridge structure according to the stress and the bridge structure response.
In one embodiment, the stress and response detection unit comprises: a driving track detection subunit, configured to detect a driving track of the vehicle according to a vehicle identifier; the judging subunit is used for judging whether the vehicle reaches the measuring point or not through the running track; and the stress and response detection subunit is used for detecting the stress applied to the measuring point and the bridge structure response generated according to the stress when the vehicle reaches the measuring point.
In one embodiment, a bridge structure early warning device further includes: the simulation response module is used for importing the three-dimensional model of the bridge structure into a finite element model, applying stress to corresponding measuring points in the finite element model and setting initial parameters of the finite element model, and obtaining simulation response generated according to the stress; the judging module is used for judging whether the absolute value of the difference between the simulation response and the bridge structure response is smaller than a set error; the final parameter determining module is used for taking the initial parameter as the final parameter of the finite element model if the initial parameter is smaller than the set error; and the adjusting module is used for adjusting the initial parameters until the difference between the simulation response and the bridge structure response is smaller than the set error if the simulation response and the bridge structure response are not smaller than the set error.
The specific limitation of the bridge structure early warning device can be referred to the limitation of the bridge structure early warning method, and the description thereof is omitted here. All or part of the modules in the bridge structure early warning device can be realized by software, hardware and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 4. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing stress strain data of the bridge structure. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program when executed by the processor is used for realizing a bridge structure early warning method.
It will be appreciated by persons skilled in the art that the architecture shown in fig. 4 is merely a block diagram of some of the architecture relevant to the present inventive arrangements and is not limiting as to the computer device to which the present inventive arrangements are applicable, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:
collecting weight information and vehicle identification of a vehicle in a running state;
inputting the weight information of the vehicle into a bridge load transverse distribution model to obtain response data of the bridge;
when the response data of the bridge exceeds a set threshold value, acquiring the position information of the vehicle on the bridge through the vehicle identifier, and sending out alarm information;
the response data comprises at least one of a cable force value, a deflection value, a strain value, an acceleration value, a crack width value and an inclination angle value.
In one embodiment, the processor when executing the computer program further performs the steps of: setting a plurality of measuring points on the bridge deck of the bridge; detecting stress applied to the measuring point and generating bridge structure response according to the stress; establishing a bridge load transverse distribution model of the bridge structure according to the stress and the bridge structure response; the bridge structure response is obtained through measurement of sensors arranged at the measuring points, and the response comprises cable force, deflection, strain, acceleration, crack width and inclination angle.
In one embodiment, the processor when executing the computer program further performs the steps of: introducing the three-dimensional model of the bridge structure into a finite element model, applying stress to corresponding measuring points in the finite element model, and setting initial parameters of the finite element model to obtain simulation response generated according to the stress; judging whether the absolute value of the difference between the simulation response and the bridge structure response is smaller than a set error; if the initial parameter is smaller than the set error, the initial parameter is used as a final parameter of the finite element model; and if the simulation response is not smaller than the set error, adjusting the initial parameters until the difference between the simulation response and the bridge structure response is smaller than the set error.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
collecting weight information and vehicle identification of a vehicle in a running state;
inputting the weight information of the vehicle into a bridge load transverse distribution model to obtain response data of the bridge;
when the response data of the bridge exceeds a set threshold value, acquiring the position information of the vehicle on the bridge through the vehicle identifier, and sending out alarm information;
the response data comprises at least one of a cable force value, a deflection value, a strain value, an acceleration value, a crack width value and an inclination angle value.
In one embodiment, the computer program when executed by the processor further performs the steps of: setting a plurality of measuring points on the bridge deck of the bridge; detecting stress applied to the measuring point and generating bridge structure response according to the stress; establishing a bridge load transverse distribution model of the bridge structure according to the stress and the bridge structure response; the bridge structure response is obtained through measurement of sensors arranged at the measuring points, and the response comprises cable force, deflection, strain, acceleration, crack width and inclination angle.
In one embodiment, the computer program when executed by the processor further performs the steps of: introducing the three-dimensional model of the bridge structure into a finite element model, applying stress to corresponding measuring points in the finite element model, and setting initial parameters of the finite element model to obtain simulation response generated according to the stress; judging whether the absolute value of the difference between the simulation response and the bridge structure response is smaller than a set error; if the initial parameter is smaller than the set error, the initial parameter is used as a final parameter of the finite element model; and if the simulation response is not smaller than the set error, adjusting the initial parameters until the difference between the simulation response and the bridge structure response is smaller than the set error.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (10)
1. A bridge construction pre-warning method, the method comprising:
setting a plurality of measuring points on the bridge deck of the bridge;
detecting stress applied to the measuring point and generating bridge structure response according to the stress;
according to the stress and the bridge structure response, a functional relation between the stress and the bridge structure response is obtained by linear fitting or equation solving, and a bridge load transverse distribution model of the bridge structure is established according to the functional relation;
before a vehicle enters a bridge structure, acquiring weight information and a vehicle identifier of the vehicle in a running state;
inputting the weight information of the vehicle into a bridge load transverse distribution model to obtain response data of the bridge;
when the response data of the bridge exceeds a set threshold value, alarm information is sent to the vehicle to prevent the vehicle from entering a bridge structure, meanwhile, the position information of the vehicle in the bridge is obtained through the vehicle identification, whether the vehicle passes through the area where the bridge structure is easy to damage or not is detected, and if the vehicle passes through the area where the bridge structure is easy to damage, the areas are recorded so as to facilitate timely maintenance;
the bridge structure response is obtained by measuring a sensor arranged at the measuring point, wherein the response comprises cable force, deflection, strain, acceleration, crack width and inclination angle; the response data comprises at least one of a cable force value, a deflection value, a strain value, an acceleration value, a crack width value and an inclination angle value.
2. The method of claim 1, wherein the stress is gravity caused by the weight of the vehicle.
3. The method of claim 1, wherein the site is an area of the bridge structure susceptible to damage.
4. The method of claim 1, wherein the detecting the stress applied to the station and the bridge structure response based on the stress comprises:
detecting the running track of the vehicle according to the vehicle identification;
judging whether the vehicle reaches the measuring point or not through the running track;
when the vehicle reaches the measuring point, the stress applied to the measuring point and the bridge structure response generated according to the stress are detected.
5. The method of claim 1, wherein the vehicle is an overloaded vehicle.
6. The method of claim 1, wherein the vehicle identification includes at least one of license plate information, vehicle model information, and vehicle appearance characteristics.
7. The method as recited in claim 1, further comprising:
introducing the three-dimensional model of the bridge structure into a finite element model, applying stress to corresponding measuring points in the finite element model, and setting initial parameters of the finite element model to obtain simulation response generated according to the stress;
judging whether the absolute value of the difference between the simulation response and the bridge structure response is smaller than a set error;
if the initial parameter is smaller than the set error, the initial parameter is used as a final parameter of the finite element model;
and if the simulation response is not smaller than the set error, adjusting the initial parameters until the difference between the simulation response and the bridge structure response is smaller than the set error.
8. A bridge construction warning device, the device comprising:
the bridge load transverse distribution model building module is used for building a bridge load transverse distribution model;
the acquisition module is used for acquiring weight information and vehicle identification of the vehicle in a running state before the vehicle enters the bridge structure;
the response data calculation module is used for inputting the weight information of the vehicle into a bridge load transverse distribution model to obtain response data of the bridge;
the warning module is used for sending warning information to the vehicle when the response data of the bridge exceeds a set threshold value so as to prevent the vehicle from entering a bridge structure, acquiring the position information of the vehicle in the bridge through the vehicle identifier, detecting whether the vehicle passes through the area easy to be damaged by the bridge structure, and recording the areas if the vehicle passes through the area easy to be damaged so as to facilitate timely maintenance;
the bridge load transverse distribution model building module comprises:
the measuring point setting unit is used for setting a plurality of measuring points on the bridge deck of the bridge;
a stress and response detection unit for detecting stress applied to the measuring point and bridge structure response generated according to the stress;
the model building unit is used for obtaining a functional relation between the stress and the bridge structure response in a linear fitting or equation solving mode according to the stress and the bridge structure response, and building a bridge load transverse distribution model of the bridge structure according to the functional relation;
the bridge structure response is obtained by measuring a sensor arranged at the measuring point, wherein the response comprises cable force, deflection, strain, acceleration, crack width and inclination angle; the response data comprises at least one of a cable force value, a deflection value, a strain value, an acceleration value, a crack width value and an inclination angle value.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910126094.XA CN109992827B (en) | 2019-02-20 | 2019-02-20 | Bridge structure early warning method, bridge structure early warning device, computer equipment and storage medium |
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| CN201910126094.XA CN109992827B (en) | 2019-02-20 | 2019-02-20 | Bridge structure early warning method, bridge structure early warning device, computer equipment and storage medium |
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| WO2021119947A1 (en) * | 2019-12-16 | 2021-06-24 | 哈尔滨工业大学（深圳） | Method for quick detection of damage to bridge, and related device |
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| CN111710165B (en) * | 2020-08-17 | 2020-11-20 | 湖南大学 | Bridge supervision and early warning method and system based on multi-source monitoring data fusion and sharing |
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| CN113077632A (en) * | 2021-06-07 | 2021-07-06 | 四川紫荆花开智能网联汽车科技有限公司 | V2X intelligent network connection side system and realizing method |
| CN114001887B (en) * | 2021-10-26 | 2024-02-27 | 浙江工业大学 | Bridge damage assessment method based on deflection monitoring |
| CN115311246A (en) * | 2022-08-23 | 2022-11-08 | 保利长大工程有限公司 | Bridge safety management method and system based on big data |
| CN117093842B (en) * | 2023-08-31 | 2024-03-19 | 四川省公路规划勘察设计研究院有限公司 | Geological deformation upper risk bridge monitoring demand assessment method and system |
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