CN111881495A - Prestress steel structure safety assessment method based on digital twinning - Google Patents
Prestress steel structure safety assessment method based on digital twinning Download PDFInfo
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Abstract
The method comprises the steps of utilizing BIM and three-dimensional scanning technology to build a digital twinning model of a structure, building a structure prediction model based on experiment and historical big data through the digital twinning model, and predicting the safety risk level of the structure according to real-time data. The example results show that the novel method can effectively monitor and predict the safety level of the prestressed steel structure during service, and provides effective data for the maintenance of the subsequent structure. Researches show that the digital twin technology can improve the intelligent degree in the safety assessment process of the prestressed steel structure, and provides a new idea for monitoring the prestressed steel structure.
Description
Technical Field
The invention relates to the technical field of building construction, in particular to a prestress steel structure safety assessment method based on digital twinning.
Background
Generally, in the process of safety assessment of an in-service prestressed steel structure, the failure mechanism of the prestressed steel structure is analyzed, the structural change rule under different damage conditions is determined, the sensitivity of each parameter is calculated, and the limit values and the influence degrees of errors, damages and defects of the stay cable and other key components are given; finally, the sensitivity value and the change trend of the input variables such as the material properties of the input variables and the applied prestress to the mechanical index output by the structure are judged. Although the traditional method can realize safety evaluation to a certain extent, large finite element software such as ABAQUS, ANSYS and COMSOL is generally adopted for analysis and calculation, the boundary conditions and the initial conditions are sometimes difficult to accurately determine; and the operation is more complicated, the number of sample points is less, and the predictability is lacked, so the method cannot be well used for the safety evaluation of the in-service prestressed steel structure.
The digital twin technology can realize interactive fusion of an in-service prestressed steel structure physical space and an information space, a user can acquire real-time information of the physical structure through a virtual structure, extract correlation characteristics among data by using a neural network and carry out safety assessment on the basis of the correlation characteristics, and the physical structure can take corresponding maintenance measures according to the assessment result of the virtual structure, so that the safe service of a building is ensured, and the basic idea of analyzing, assessing and applying the data in the in-service prestressed steel structure safety assessment process is met. Therefore, the digital twin technology provides a new method for safety evaluation of the prestressed steel structure.
Disclosure of Invention
Aiming at the traditional problem of safety risk assessment of an in-service prestressed steel structure, a safety risk assessment method based on digital twinning is provided. Constructing two-dimensional and three-dimensional models of a virtual structure according to the arrangement of the prestressed steel structure entities by using a digital twin technology; and arranging a sensor, acquiring a cable force displacement signal during the service period of the structure, acquiring and interacting relevant data in the service process of the prestressed steel structure, and establishing a complete digital twin model of the prestressed steel structure on the basis. The cable force change in the structure using process can be synchronously reflected in the three-dimensional point cloud correction model, and the cable force change value can be stored in the real-time database through the physical sensor. Ninety percent of the network is selected from experimental and historical data to be trained; and (4) taking the evaluation indexes and the safety risk levels of the residual data as inspection samples to establish a prestress steel structure safety evaluation model. And obtaining the safety risk level of the structure through the prediction model, comparing the safety risk level with the actual risk level, and calculating the classification accuracy, wherein the higher the accuracy is, the stronger the prediction capability of the model is. The safety evaluation process of the method is as follows: firstly, constructing a three-dimensional digital model of a prestressed steel structure; secondly, acquiring real-time data of the structure by using a sensor; training and checking the model through historical and experimental data, and establishing a safety evaluation model; and fourthly, taking the structure real-time data as an input value and the structure safety level as an output value, and predicting the structure safety level by using the trained safety evaluation model.
The technical scheme adopted by the invention is a digital twinning-based prestressed steel structure safety assessment method, and a digital twinning technology is utilized to construct two-dimensional and three-dimensional models of a virtual prestressed steel structure according to the arrangement of prestressed steel structure entities; and arranging a sensor, acquiring a cable force displacement signal during the service period of the prestressed steel structure, communicating and transmitting the cable force displacement signal to an upper computer through a serial port, so as to realize acquisition and interaction of relevant data in the service process of the prestressed steel structure, and establishing a complete multi-dimensional multi-scale digital twin model for safety risk assessment of the prestressed steel structure on the basis. After the prestressed steel structure is put into use, the sensors arranged in advance carry out acquisition and storage of prestressed steel structure information; after the solid prestressed steel structure is changed, the virtual prestressed steel structure model can also generate corresponding changes of cable force and displacement. The method comprises the steps of training a network by using structural data, establishing a safety risk assessment support model, and carrying out state monitoring, functional diagnosis and reliability judgment on an entity structure in a physical layer by using the trained model so as to realize risk prediction and assessment during the service period of the structure and provide guarantee for the safety service of the structure entity in the physical layer.
In the three-dimensional model construction of the virtual prestressed steel structure, the constructed three-dimensional digital model comprises a finite element model and a correction model. The physical model was numerically simulated using finite element software ANSYS. After the construction of the prestressed steel structure is completed, a solid prestressed steel structure model is obtained by using a three-dimensional laser scanning technology, and then a point cloud model is established. And importing the processed and spliced point cloud data into BIM software, extracting key points of the prestressed steel structure, and establishing a BIM model. And establishing a correction BIM model according to the point cloud model, and extracting new key node coordinates in the correction BIM model. And establishing a corrected finite element model according to the node coordinates of the point cloud model, wherein the corrected finite element model considers construction errors and eliminates the influence of the construction errors on the sensitivity of the length errors of the components.
In the acquisition of the information of the prestressed steel structure, the acquired data is stored by using an intelligent safety assessment information system of the prestressed steel structure, and then the reliability of the prestressed steel structure is analyzed in the virtual structure, so that corresponding maintenance remedial measures are taken, and the method is an important way for performing safety risk assessment on the in-service prestressed steel by using a digital twin model. In the process of realizing the safety risk assessment way, the data acquisition in the physical prestressed steel structure, namely the prestressed steel structure entity, is important prerequisite work. The different rods of the prestressed steel structure bear different functions, and the data acquisition conditions of the rods of the prestressed steel structure are not completely the same.
The method comprises the steps of establishing a complete multi-dimensional multi-scale digital twin model for safety risk assessment of the prestressed steel structure, providing a multi-dimensional model for safety risk assessment by combining a safety risk assessment process and a digital twin five-dimensional model, and forming the multi-dimensional multi-scale digital twin assessment model of the structure by combining an entity structure, a virtual structure, real-time data, assessment services and connection among all parts of the prestressed steel structure.
The safety risk assessment support model is used for training an artificial network by using historical data and experimental data to obtain a safety risk assessment support model, and then predicting the safety level of the structure by using in-service prestressed steel structure real-time data obtained by a sensor, so that risk assessment of the prestressed steel structure is realized.
Compared with the prior art, the invention provides a prestressed steel structure safety risk assessment method based on a digital twin technology and explains the implementation process of the novel method. The method solves the problems of complex operation, few sample points, lack of predictability and the like in the evaluation process of the traditional method, and predicts and evaluates the data acquired in real time by using a network model. A digital twin model of the structure is built by utilizing BIM (building Information modeling) and three-dimensional scanning technology, and self-perception, self-prediction and self-evaluation of the structure are realized through a digital twin body, so that the intelligent degree and the safety level of the structure are higher in the using process. The example results show that the novel method can effectively monitor and predict the safety level of the prestressed steel structure during service, and provides effective data for the maintenance of the subsequent structure. Researches show that the digital twin technology can improve the intelligent degree in the safety assessment process of the prestressed steel structure, and provides a new idea for monitoring the structure.
Drawings
FIG. 1A Multi-dimensional model of security risk assessment.
FIG. 2 is a technical route flow diagram.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and examples.
A prestress steel structure safety assessment method based on digital twinning comprises the following specific implementation steps:
the method comprises the following steps: and constructing a three-dimensional digital model of the prestressed steel structure according to the physical entity structure. The method adopts finite element software ANSYS to carry out numerical simulation on a physical model, simultaneously utilizes a three-dimensional laser scanning technology to obtain point cloud data of the structure, and establishes a corrected BIM model and a corrected finite element model of the structure.
Step two: the sensors are arranged on the physical structure, and for the prestressed steel structure, the functions borne by different rods are different, so that the position and the type of the sensors are not completely the same. And the cable force displacement signals acquired by the sensor during the service period of the structure are transmitted to an upper computer through serial port communication, so that acquisition and interaction of relevant data in the service process of the prestressed steel structure are realized.
Step three: training samples are selected from historical and experimental data as input quantity, the structure safety level is used as output, the network is trained, and the rest samples are used for inspection, so that a prestress steel structure safety risk assessment model is established.
Step four: and selecting the collected real-time structure data as a test sample, taking the test sample as an input value and the structure safety level as an output, and predicting the safety risk level of the structure, thereby realizing the structure safety risk assessment service.
The multi-dimensional model for safety risk assessment is shown as formula (1):
MSDT＝(BPE,LPE,BVE,LVE,SS,DD,OA,CN) (1)
in formula (1):
MSDTmultidimensional model representing a security risk assessment, BPERepresenting architectural structural entities, LPERepresents a bearer entity, BVERepresenting building structure virtual entities, LVERepresenting a payload virtual entity, SSRepresents a security risk assessment service to the structure, DD represents data related to the security risk assessment, OA represents a risk assessment algorithm that processes the data, and CN represents connections between the various components.
In the above evaluation model, BVENot only needs to depict BPEThe geometric characteristics of (A) and (B) are required to be describedPEThe overall dimension, the installation position relationship, the material type, the node connection and other information of each rod piece. For in-service prestressed steel structure, the structural states of internal force, stress, deformation, strain, crack, damage and the like are closely related to the performance and reliability of the structure, so that the method needs to be applied to the in-service prestressed steel structureAs embodied in DD.
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 (5)
1. The safety assessment method for the prestressed steel structure based on the digital twin is characterized by comprising the following steps of: constructing two-dimensional and three-dimensional models of the virtual prestressed steel structure according to the arrangement of the prestressed steel structure entity by using a digital twin technology; arranging a sensor, acquiring a cable force displacement signal during the service period of the prestressed steel structure, and transmitting the cable force displacement signal to an upper computer through serial port communication, so that acquisition and interaction of relevant data in the service process of the prestressed steel structure are realized, and a complete multi-dimensional multi-scale digital twin model for safety risk assessment of the prestressed steel structure is established; after the prestressed steel structure is put into use, arranging a sensor in advance to acquire and store prestressed steel structure information; after the solid prestressed steel structure is changed, the virtual prestressed steel structure model can generate corresponding cable force and displacement change; the method comprises the steps of training a network by using structural data, establishing a safety risk assessment support model, and carrying out state monitoring, functional diagnosis and reliability judgment on an entity structure in a physical layer by using the trained model so as to realize risk prediction and assessment during the service period of the structure and provide guarantee for the safety service of the structure entity in the physical layer.
2. The digital twin-based prestressed steel structure safety assessment method according to claim 1, characterized in that: in the three-dimensional model construction of the virtual prestressed steel structure, the constructed three-dimensional digital model comprises a finite element model and a correction model; carrying out numerical simulation on the physical model by using finite element software ANSYS; after the construction of the prestressed steel structure is completed, a solid prestressed steel structure model is obtained by using a three-dimensional laser scanning technology, and then a point cloud model is established; importing the processed and spliced point cloud data into BIM software, extracting key points of a prestressed steel structure, and further establishing a BIM model; establishing a correction BIM (building information modeling) according to the point cloud model, and extracting new key node coordinates from the correction BIM; and establishing a corrected finite element model according to the node coordinates of the point cloud model, wherein the corrected finite element model considers construction errors and eliminates the influence of the construction errors on the sensitivity of the length errors of the components.
3. The digital twin-based prestressed steel structure safety assessment method according to claim 1, characterized in that: in the acquisition of the information of the prestressed steel structure, the acquired data is stored by using an intelligent safety assessment information system of the prestressed steel structure, and then the reliability of the prestressed steel structure is analyzed in a virtual structure, so that maintenance remedial measures are taken, and the method is an important way for performing safety risk assessment on in-service prestressed steel by using a digital twin model; in the implementation process of the safety risk assessment method, the data acquisition in the physical prestressed steel structure, namely the prestressed steel structure entity is important prerequisite work; the different rods of the prestressed steel structure bear different functions, and the data acquisition conditions of the rods of the prestressed steel structure are not completely the same.
4. The digital twin-based prestressed steel structure safety assessment method according to claim 1, characterized in that: the method comprises the steps of establishing a complete multi-dimensional multi-scale digital twin model for safety risk assessment of the prestressed steel structure, providing a multi-dimensional model for safety risk assessment by combining a safety risk assessment process and a digital twin five-dimensional model, and forming the multi-dimensional multi-scale digital twin assessment model of the structure by combining an entity structure, a virtual structure, real-time data, assessment services and connection among all parts of the prestressed steel structure.
5. The digital twin-based prestressed steel structure safety assessment method according to claim 1, characterized in that: the safety risk assessment support model is used for training an artificial network by using historical data and experimental data to obtain a safety risk assessment support model, and then predicting the safety level of the structure by using in-service prestressed steel structure real-time data obtained by a sensor, so that risk assessment of the prestressed steel structure is realized.
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| CN112394667A (en) * | 2020-11-24 | 2021-02-23 | 长江勘测规划设计研究有限责任公司 | Construction process safety monitoring method based on digital twinning |
| CN113051838A (en) * | 2021-05-12 | 2021-06-29 | 南京航空航天大学 | Reliable life prediction method for space on-orbit manufacturing structure based on digital twinning technology |
| CN113051649A (en) * | 2021-03-31 | 2021-06-29 | 中煤科工集团重庆研究院有限公司 | Risk assessment model based on concrete stress strain |
| CN113219048A (en) * | 2021-07-09 | 2021-08-06 | 西南交通大学 | Steel bridge damage detection system and method based on eddy current and digital twinning technology |
| CN113408927A (en) * | 2021-06-30 | 2021-09-17 | 四川交达预应力工程检测科技有限公司 | Big data-based prestressed construction quality evaluation method and system |
| CN113434948A (en) * | 2021-07-26 | 2021-09-24 | 哈尔滨工业大学（深圳） | High-rise steel structure construction model updating method |
| CN113569445A (en) * | 2021-07-01 | 2021-10-29 | 洛阳星派数值仿真研究院有限公司 | Steel structure health monitoring system and method based on digital twinning technology |
| CN114065589A (en) * | 2021-11-19 | 2022-02-18 | 华东理工大学 | Pressure container safety evaluation and risk early warning method based on digital twinning |
| CN116678368A (en) * | 2023-07-28 | 2023-09-01 | 山东德丰重工有限公司 | BIM technology-based intelligent acquisition method for assembled steel structure data |
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| CN112394667B (en) * | 2020-11-24 | 2022-05-31 | 长江勘测规划设计研究有限责任公司 | Construction process safety monitoring method based on digital twinning |
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| CN113408927B (en) * | 2021-06-30 | 2023-01-10 | 四川交达预应力工程检测科技有限公司 | Big data-based prestressed construction quality evaluation method and system |
| CN113408927A (en) * | 2021-06-30 | 2021-09-17 | 四川交达预应力工程检测科技有限公司 | Big data-based prestressed construction quality evaluation method and system |
| CN113569445A (en) * | 2021-07-01 | 2021-10-29 | 洛阳星派数值仿真研究院有限公司 | Steel structure health monitoring system and method based on digital twinning technology |
| CN113219048A (en) * | 2021-07-09 | 2021-08-06 | 西南交通大学 | Steel bridge damage detection system and method based on eddy current and digital twinning technology |
| CN113434948A (en) * | 2021-07-26 | 2021-09-24 | 哈尔滨工业大学（深圳） | High-rise steel structure construction model updating method |
| CN113434948B (en) * | 2021-07-26 | 2023-01-20 | 哈尔滨工业大学（深圳） | High-rise steel structure construction model updating method |
| CN114065589A (en) * | 2021-11-19 | 2022-02-18 | 华东理工大学 | Pressure container safety evaluation and risk early warning method based on digital twinning |
| CN114065589B (en) * | 2021-11-19 | 2024-03-08 | 华东理工大学 | Digital twinning-based pressure vessel safety evaluation and risk early warning method |
| CN116678368A (en) * | 2023-07-28 | 2023-09-01 | 山东德丰重工有限公司 | BIM technology-based intelligent acquisition method for assembled steel structure data |
| CN116678368B (en) * | 2023-07-28 | 2023-10-17 | 山东德丰重工有限公司 | BIM technology-based intelligent acquisition method for assembled steel structure data |
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