A method and system for online mapping of health monitoring data of cable-stayed bridge

Abstract

The present invention discloses an online mapping method and system for health monitoring data of a cable-stayed bridge, and belongs to the technical field of cable-stayed bridge monitoring. A parametric BIM model of a cable-stayed bridge is established, and the BIM model is lightweight processed based on GLTF; the monitoring page is integrated based on Vue and BIMface, and a complex monitoring page is developed in a component-based manner and bound to the BIM model; the API is called to arrange monitoring points; the sensor and the monitoring point are responsively coupled, and the monitoring data is converted from high-dimensional data to low-dimensional data based on PCA, while retaining the characteristics of the monitoring data, realizing dimensionality reduction processing, and displaying it in the form of a chart; the data exceeding the threshold is intuitively displayed in the form of a dynamic line chart and a table, and the components exceeding the threshold are warned and prompted through component color changes and email notification mechanisms. Through the above-mentioned method and system, the present invention opens up the process of data collection, data processing to data visualization management in the health monitoring process of the cable-stayed bridge, and realizes the online mapping of the health monitoring data of the cable-stayed bridge.

Description

Technical Field

[0001] The present invention relates to the technical field of cable-stayed bridge monitoring, and in particular to an online mapping method and system for health monitoring data of a cable-stayed bridge. Background Art

[0002] A cable-stayed bridge, also known as a cable-tensioned bridge, is a bridge in which the main beam is directly pulled onto the bridge tower by many cables. It is a structural system composed of pressure-bearing towers, tensioned cables and bending-bearing beams. Cable-stayed bridges are difficult to operate and manage due to their complex structural forms and the fact that they are built in areas with complex natural environments. Therefore, real-time safety monitoring of cable-stayed bridges is particularly important.

[0003] At present, the safety monitoring of cable-stayed bridges has the following problems:

[0004] (1) Bridge health monitoring system: By installing sensors at the response position of the bridge, data can also be collected with the help of technologies such as cameras and drones. However, the bridge health monitoring system is still not perfect. Due to the limitations of the scale of the health monitoring system and monitoring technology, the bridge health monitoring system cannot provide complete bridge health information;

[0005] (2) Manual regular inspections. The information obtained by conventional manual visual inspections or portable one-time measurements has a long manual inspection cycle, many blind spots, and high subjectivity, which often have great limitations in actual use. In addition, the safety and durability assessment of long-span bridges still relies on experienced engineering and technical personnel. However, the investigation methods and judgment criteria used in this "traditional empirical method" are directly related to the personal knowledge level and experience of the assessor. The expert evaluation results under different background conditions will be highly subjective and may be misjudged. Summary of the invention

[0006] The purpose of the present invention is to provide a method and system for online mapping of health monitoring data of a cable-stayed bridge, which collects and saves health monitoring data, processes the health monitoring data and couples it with a front-end page to achieve visual expression of the monitoring data.

[0007] To achieve the above object, the present invention provides an online mapping method for health monitoring data of a cable-stayed bridge, the steps comprising:

[0008] S1. Establish a parametric BIM model of a cable-stayed bridge and perform lightweight processing on the BIM model;

[0009] S2, integrate the page by calling the BIMface front-end interface through Vue.js, and bind the integrated page with the lightweight BIM model in S1;

[0010] S3, arrange the monitoring points of the cable-stayed bridge by calling the API three-dimensional tags;

[0011] S4, associate the monitoring point with the sensor, and store the relevant information data of the sensor in the monitoring point through Node.js;

[0012] S5, visualize the health monitoring data, and click on the sensor to obtain the health monitoring data according to the association between the monitoring point and the sensor in S4;

[0013] S6. Set a health monitoring warning threshold according to the monitoring target, compare the health monitoring data obtained in S5 with the set health monitoring warning threshold, and output the corresponding result;

[0014] S7, based on the results output by S6, real-time map the health monitoring status of the cable-stayed bridge and roam through the model from a third-person perspective.

[0015] Preferably, the specific process of step S1 is as follows:

[0016] S11. Convert the BIM model in Revit format into a GLTF file based on the edge folding algorithm. The edge folding algorithm uses a global energy equation to determine the edge folding order and the position of the new vertex, and gradually adds details to generate bridge models of different complexities. The specific contents are as follows:

[0017] S110, input vertex sequence v = [x, y, z] T And the triangle face sequence v l , get v l The sum of the squares of the distances to the faces of all triangles in Planes(v) associated with v is Δv. The specific expression is as follows:

[0018]

[0019] Where p = [a, b, c, d] T In Planes(v), the equation of the plane where each triangle is located is ax+by+cz+d=0, and a 2 +b 2 +c 2 =1;

[0020] S111, after matrix transformation, the error matrix K is obtained p , the specific expression is as follows:

[0021]

[0022]

[0023] S112, error matrix K for the associated plane pSum up and get the error matrix Q of each vertex. The specific expression is as follows:

[0024]

[0025] S12, optimize the GLTF file converted by S11 through Draco;

[0026] S13, loading the optimized GLTF file in S12 to the cloud for rendering to obtain the final lightweight BIM model.

[0027] Preferably, step S2 specifically includes:

[0028] S21. Create a BIMFACE developer account, install Vue.js and set up a Vue.js project;

[0029] S22. Log in to the BIMFACE developer platform, create a new application, and obtain an API key;

[0030] S23. Import the BIMFACE Viewer JavaScript library into the Vue.js project, then initialize the BIMFACEViewer and authenticate using the API key obtained in S22.

[0031] S24. Use the API call provided by BIMFACE Viewer to load BIM model data, including the model's geometric information and attribute data;

[0032] S25. Create one or more components in the Vue.js project to house the BIMFACE Viewer and other user interface related elements;

[0033] S26. Bind the data of the BIM model to the components in Vue.js, and dynamically update the display and attribute information of the model when the user interacts with the application;

[0034] S27. Use the event processing mechanism of Vue.js to add user interaction functions, including the function of displaying relevant information by clicking on model components, the function of zooming in and out, and the function of rotating operations;

[0035] S28. Use Vue.js's style binding and layout management to beautify and customize the appearance of BIMFACE Viewer;

[0036] S29. After testing and debugging, build the Vue.js project into a production version and deploy it to the server.

[0037] Preferably, step S3 specifically includes:

[0038] S31. Use finite element software to build a cable-stayed bridge model and conduct analysis;

[0039] S32. Determine monitoring points based on actual monitoring needs and analysis results;

[0040] S33, obtaining component attributes to obtain the coordinates of the monitoring points;

[0041] S34. Arrange monitoring points through three-dimensional tags and monitoring events.

[0042] Preferably, the specific process of step S4 is as follows:

[0043] S41, classify according to the type of sensor and location, force, identification data, phasing, data and other parameters;

[0044] S42, establishing a corresponding database according to the classification in S41, combined with the sensor data collection interval, the adopted data transmission protocol, and the identification information in the protocol;

[0045] S43, processing the relevant data of the sensor database through Node.js and storing it in the monitoring point, and the monitoring point information is coupled with the sensor information accordingly.

[0046] Preferably, the types of sensors in S41 include vibrating-wire strain sensors, wind sensors, displacement sensors, and cable force sensors.

[0047] Preferably, the relevant data processing of the sensor database in step S43 is specifically to process the collected frequency into stress, and the calculation formula is:

[0048]

[0049] Among them, ε represents stress, K is the calibration coefficient of the sensor, and f i is the initial frequency of the sensor, f0 is the acquisition frequency;

[0050]

[0051] Where E is the elastic modulus of the material and σ is the material strain.

[0052] Preferably, in step S5, the data is processed based on the PCA method to visualize the health data, including:

[0053] S51. Data centering: perform mean centering on each feature. The formula is:

[0054]

[0055] In the formula, X is the original data matrix, X is the mean vector of each column feature, and X centeredrepresents the data center matrix;

[0056] S52. Calculate the covariance matrix Cov(X) of the data matrix. The formula is:

[0057]

[0058] Where m is the number of samples;

[0059] S53, eigenvalue decomposition, perform eigenvalue decomposition on the covariance matrix, the formula is:

[0060] Cov(X)=QΛQ T

[0061] Where Q is the eigenvector matrix, Λ is the diagonal eigenvalue matrix;

[0062] S54, select the principal component, and select the eigenvectors with the largest eigenvalues ​​as the principal component;

[0063] S55. Construct projection matrix Q selected , the formula is

[0064] Q selected =[v1,v2,...,v k ]

[0065] Among them, v k represents the kth eigenvector;

[0066] S56. Project the data onto the selected principal component and visualize the data. The formula is:

[0067] X reduced =X centered ×Q selected

[0068] Where, X reduced is the projection matrix.

[0069] Preferably, in step S6, the health monitoring data is compared with the health monitoring warning threshold to determine whether the health monitoring data exceeds the limit. When the health monitoring data exceeds the health monitoring warning threshold, the warning component of the monitoring display web page of the cable-stayed bridge changes color, and an email reminder is sent. The health status of the control section of the monitoring structure is quickly determined based on the warning status, and the dangerous structure parts are quickly located.

[0070] The present invention also provides a mapping system for an online mapping method of health monitoring data of a cable-stayed bridge, comprising a BIM model operation module, a data acquisition module, a real-time monitoring module, a monitoring and early warning module, a data query module, a roaming module and an on-site visualization module, wherein the data query module comprises an early warning report and a historical data query; the real-time monitoring module is electrically connected to the monitoring and early warning module, the monitoring and early warning module is electrically connected to the data query module, the on-site visualization module, the real-time monitoring module, the monitoring and early warning module and the roaming module are all electrically connected to the BIM model operation module, and the data acquisition module provides data for the on-site visualization module and the real-time monitoring module.

[0071] Therefore, the present invention adopts a cable-stayed bridge health monitoring data online mapping method and system of the above structure, and achieves the following beneficial effects:

[0072] (1) Implement a method for directly expanding the operation and maintenance model and integrating data on the Web end, connect the entire process of data collection, data processing, and data visualization management during the health monitoring of cable-stayed bridges, ensure efficient and safe operation and maintenance of cable-stayed bridges, and provide new ideas for the informatization of cable-stayed bridge operation and maintenance;

[0073] (2) It gets rid of the refined modeling of entity monitoring families, uses health monitoring data to drive the color update of monitoring points, realizes efficient visualization of health monitoring data on the Web, and improves the efficiency of health monitoring data management;

[0074] (3) The monitoring points are arranged by three-dimensional labeling, solving the problem that the traditional sensors are placed after the building and structure are completed, and the number of sensors is large, resulting in a large model and complicated construction.

[0075] (4) Based on the PCA algorithm, the monitoring data is converted from high-dimensional data to low-dimensional data, while retaining the characteristics of the monitoring data and achieving dimensionality reduction.

[0076] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 It is a schematic diagram of the system framework of the present invention;

[0078] Figure 2 Design a flow chart for the present invention;

[0079] Figure 3 The BIM model of the cable-stayed bridge of the present invention;

[0080] Figure 4 It is the main interface of the cable-stayed bridge health monitoring of the present invention;

[0081] Figure 5 It is the stress dynamic line graph of the present invention;

[0082] Figure 6 This is a diagram showing the structure changing color and the mailbox prompt when the data exceeds the warning value of the present invention;

[0083] Figure 7 View the model in walkthrough mode for this invention. DETAILED DESCRIPTION

[0084] The technical solution of the present invention is further described below through the accompanying drawings and embodiments.

[0085] Unless otherwise defined, the technical terms or scientific terms used in the present invention shall have the common meanings understood by people with ordinary skills in the field to which the present invention belongs. The words "include" or "comprise" and the like used in the present invention mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, but do not exclude other elements or objects.

[0086] Example

[0087] Reference Figure 1-2 The present invention provides a system for online mapping method of health monitoring data of cable-stayed bridge, referring to Figure 1 The mapping system includes: a BIM model operation module, a data acquisition module, a real-time monitoring module, a monitoring and early warning module, a data query module, a roaming module and a field visualization module. The real-time monitoring module is electrically connected to the monitoring and early warning module, and the monitoring and early warning module is electrically connected to the data query module. The field visualization module, the real-time monitoring module, the monitoring and early warning module, and the roaming module are all electrically connected to the BIM model operation module, which facilitates the operation of the BIM model and the viewing of health monitoring data.

[0088] BIM model operation module: Build a BIM cable-stayed bridge model, and perform operations such as "different perspectives", "main perspective", "frame selection", "annotation", "measurement", "sectioning", "component details", "settings", and "full screen" on the model. The specific functions are as follows:

[0089] (1) Different viewing angles: The cable-stayed bridge can be rotated by dragging the small cube in the upper right corner or clicking on different faces of the cube. The model can be zoomed and translated using the mouse wheel, allowing monitoring personnel to observe the details of the cable-stayed bridge model from different angles.

[0090] (2) Main perspective: View the cable-stayed bridge model and quickly switch the cable-stayed bridge to the set main perspective.

[0091] (3) Box selection: helps select and operate specific areas of the cable-stayed bridge. With the box selection function, hold down the mouse and drag to create a box selection area, and then perform various operations within the area to change the perspective, making it easier to quickly view a local area of ​​the model.

[0092] (4) Annotation: The annotation function allows you to add text or symbols to the cable-stayed bridge model to illustrate specific components, areas, or issues. You can select the appropriate annotation type, such as text annotation, arrow annotation, circle annotation, etc., and select the appropriate location on the cable-stayed bridge model to add it.

[0093] (5) Measurement: The interface supports dimensional measurement in the model, including parameters such as distance, area, and volume. Users only need to select the starting and ending points, boundary points, or volume range on the model, and the system will automatically calculate and display the relevant dimensional data. In addition to basic dimensional measurement, the system also provides advanced measurement functions, including angle and slope measurement. Users can select the appropriate measurement tool and specify the measurement point or direction in the model, and the system will give accurate measurement results.

[0094] (6) Slicing and Sectioning: The interface allows you to slice and section the cable-stayed bridge model to observe the internal structure of the cable-stayed bridge in more detail. You can select a slice plane and view the internal details of the sliced ​​surface, or create a section view to view the internal structure of a specific part.

[0095] (7) Component details: In the cable-stayed bridge model, you can select any component using the mouse or other interactive tools. Once selected, the system automatically displays the detailed information of the component. Component properties: The details page displays property information including name, material, size, weight, and manufacturer, which can clearly understand the basic characteristics of the component.

[0096] (8) Settings: Simple settings for the interactive effects of the cable-stayed bridge.

[0097] (9) Full Screen: Displays the cable-stayed bridge in full screen.

[0098] Data acquisition module: provides data for the on-site visualization module and real-time monitoring module. The data acquisition module includes cameras and sensors.

[0099] On-site visualization module: Through the camera to collect data, it can be used to monitor the cable-stayed bridge site in real time and understand the on-site conditions in real time. In the main interface of the cable-stayed bridge health monitoring system, the monitoring personnel can jump to the on-site visualization module and environmental monitoring module by clicking the on-site video and environmental monitoring function buttons. This function allows the monitoring personnel to observe the on-site conditions of the bridge and its surrounding environment in real time.

[0100] Real-time monitoring module: Through the BIM model, the health monitoring data is visualized (in the form of bar charts, pie charts, node diagrams, on-site videos, etc.) to form an overview of the monitoring information of each line of the project for easy viewing.

[0101] Monitoring and early warning module: Set a threshold value. When the threshold is exceeded, the color of the BIM model will change to achieve monitoring and early warning.

[0102] Data query module: The data query module includes early warning reports and historical data queries to facilitate online analysis.

[0103] Reference Figure 2 , a method for online mapping of health monitoring data of a cable-stayed bridge, comprising the steps of:

[0104] S1. Use Revit to build a parametric BIM model of a cable-stayed bridge and perform lightweight processing on the BIM model. GLTF is a file format for cloud transmission and loading of 3D models and scenes. The file is stored in JSON format, including the node hierarchy, material, and camera logical structure of the bridge 3D model. The specific process is as follows:

[0105] S11. Convert the BIM model in Revit format into a GLTF file based on the edge folding algorithm. The edge folding algorithm uses a global energy equation to determine the edge folding order and the position of the new vertex, and gradually adds details to generate bridge models of different complexities. The specific contents are as follows:

[0106] S110, input vertex sequence v = [x, y, z] T And the triangle face sequence v l , get v l The sum of the squares of the distances to the faces of all triangles in Planes(v) associated with v is Δv. The specific expression is as follows:

[0107]

[0108] Where p = [a, b, c, d] T In Planes(v), the equation of the plane where each triangle is located is ax+by+cz+d=0, and a 2 +b 2 +c 2 =1;

[0109] S111, after matrix transformation, the error matrix K is obtained p , the specific expression is as follows:

[0110]

[0111]

[0112] S112, error matrix K for the associated plane p Sum up and get the error matrix Q of each vertex. The specific expression is as follows:

[0113]

[0114] S12. Use Draco to optimize the GLTF file converted from S11. The specific process is as follows:

[0115] S121, counting the frequency of occurrence of characters;

[0116] S122, traverse the Huffman tree, and assign a unique code value to each character, for example, the node of the left subtree is assigned a value of 0, and the node of the right subtree is assigned a value of 1;

[0117] S123, encode the original data, and replace each character with the corresponding Huffman code;

[0118] S124. Write the encoded data into a file.

[0119] S13. Load the optimized GLTF file in S12 to the cloud for rendering to obtain the final lightweight BIM model. The specific process is as follows:

[0120] S131, the basic framework of cloud display is built, and the entire data parsing, extraction and conversion process is completed by compiling in HbuilderX and using the GLTFLoader of the Three.js engine;

[0121] S132, parsing and extracting material information, creating scenes, cameras and renderers, loading successfully, obtaining the loaded model object GLTF.scene in the callback function, and finding all Mesh objects by traversing the sub-objects of the model object to obtain its material attribute material;

[0122] S133. After the cloud obtains the attribute information of the bridge model, it will obtain a model containing thousands of "family" instance objects. The Draco algorithm has merged all the mergeable meshes. At this point, the external 3D model loaded in the entire scene exists as an object in the 3D scene. Based on this, the octree is called, and the octree divides the cloud scene into spatial scenes for model rendering. The octree is traversed from front to back and the occluded octree nodes encountered are removed, and triangles are rendered only in the visible frame to improve the cloud page interaction speed. Each component has its own identifier ID to associate the data information of the two regions, and then the cloud matches the identifier to realize the display of attribute information and model interaction.

[0123] S2, integrate the page by calling the BIMface front-end interface through Vue.js, and bind the integrated page with the lightweight BIM model in S1; specifically, it includes:

[0124] S21. Create a BIMFACE developer account, install Vue.js and set up a Vue.js project;

[0125] S22. Log in to the BIMFACE developer platform, create a new application, and obtain an API key;

[0126] S23. Import the BIMFACE Viewer JavaScript library into the Vue.js project, then initialize the BIMFACEViewer and authenticate using the API key obtained in S22.

[0127] S24. Use the API call provided by BIMFACE Viewer to load BIM model data, including the model's geometric information and attribute data;

[0128] S25. Create one or more components in the Vue.js project to house the BIMFACE Viewer and other user interface related elements;

[0129] S26. Bind the data of the BIM model to the components in Vue.js, and dynamically update the display and attribute information of the model when the user interacts with the application;

[0130] S27. Use the event processing mechanism of Vue.js to add user interaction functions, including the function of displaying relevant information by clicking on model components, the function of zooming in and out, and the function of rotating operations;

[0131] S28. Use Vue.js's style binding and layout management to beautify and customize the appearance of BIMFACE Viewer;

[0132] S29. After testing and debugging, build the Vue.js project into a production version and deploy it to the server.

[0133] S3. Arrange the monitoring points of the cable-stayed bridge by calling the API three-dimensional tags; the monitoring points are the data carriers for the integration of monitoring data of the cable-stayed bridge. They are built according to the actual project needs, taking into account the structural form, stress conditions, safety and maintenance convenience of the cable-stayed bridge, including:

[0134] S31. Use finite element software to build a cable-stayed bridge model and conduct analysis;

[0135] S32. Determine monitoring points based on actual monitoring needs and analysis results;

[0136] S33, obtaining component attributes to obtain the coordinates of the monitoring points;

[0137] S34. Arrange monitoring points through three-dimensional tags and monitoring events.

[0138] S4. Associate the monitoring point with the sensor, and store the sensor's related information data in the monitoring point through Node.js; the specific process is as follows:

[0139] S41, classifying according to the type of sensor and position, force, identification data, phasing, data and other parameters; wherein the type of sensor includes vibrating wire strain sensor, wind force sensor, displacement sensor, cable force sensor;

[0140] S42, establishing a corresponding database according to the classification in S41, combined with the sensor data collection interval, the adopted data transmission protocol, and the identification information in the protocol;

[0141] S43, after processing the relevant data of the sensor database through Node.js, the data is stored in the monitoring point, and the monitoring point information is coupled with the sensor information. The relevant data processing of the sensor database is specifically to process the collected frequency into stress, and the calculation formula is:

[0142]

[0143] Among them, ε represents stress, K is the calibration coefficient of the sensor, and f i is the initial frequency of the sensor, f0 is the acquisition frequency;

[0144]

[0145] Where E is the elastic modulus of the material and σ is the material strain.

[0146] S5, visualizing the health monitoring data, according to the association between the monitoring point and the sensor in S4, clicking the sensor to obtain the health monitoring data; wherein the data is processed based on the PCA method to visualize the health data, including the following steps:

[0147] S51. Data centering: perform mean centering on each feature (each attribute or variable in the data set, as well as the data itself), that is, subtract the mean of the feature column from each feature value to ensure that the mean of the data set is zero. The formula is:

[0148]

[0149] Where X is the original data matrix, is the mean vector of each column feature, X centered represents the data center matrix;

[0150] S52. Calculate the covariance matrix Cov(X) of the data matrix. The covariance measures the correlation between two variables. The formula is:

[0151]

[0152] Where m is the number of samples;

[0153] S53, eigenvalue decomposition, the covariance matrix is ​​decomposed into eigenvectors and corresponding eigenvalues. The eigenvector is a vector with a specific relationship with the covariance matrix, and the eigenvalue indicates the importance of the eigenvector. The eigenvector is usually normalized to a unit vector. The formula is:

[0154] Cov(X)=QΛQ T

[0155] Where Q is the eigenvector matrix, Λ is the diagonal eigenvalue matrix;

[0156] S54, selecting the principal component, according to the size of the eigenvalue, selecting the eigenvectors with the largest eigenvalues ​​as the principal component;

[0157] S55. Construct projection matrix Q selected , the formula is

[0158] Q selected =[v1,v2,...,v k ]

[0159] Among them, v k represents the kth eigenvector;

[0160] S56. Project the data onto the selected principal components to visualize the data. The original high-dimensional data set is mapped to a low-dimensional space while retaining the variance of the data set as much as possible. This projection is achieved through matrix multiplication, that is, the original data matrix is ​​multiplied by the projection matrix composed of the selected principal components. The specific formula is:

[0161] X reduced =X centered Q selected

[0162] Where, X reduced is the projection matrix.

[0163] S6. Set a health monitoring warning threshold according to the monitoring target, compare the health monitoring data obtained in S5 with the set health monitoring warning threshold, and determine whether the health monitoring data exceeds the limit. When the health monitoring data exceeds the health monitoring warning threshold, the warning component of the monitoring display webpage of the cable-stayed bridge changes color, and sends an email reminder. According to the warning status, the health status of the control section of the monitoring structure is quickly determined, the dangerous structure part is quickly located, and the corresponding result is output;

[0164] S7, based on the results output by S6, maps the health monitoring status of the cable-stayed bridge in real time and roams through the model from a third-person perspective. Roaming specifically includes: setting the roaming mode, breaking the traditional manual inspection to perform tasks in dangerous or difficult-to-reach places, reducing the risk of personnel. Setting the third-person perspective of the roaming mode, the third-person perspective observes the model from the perspective behind the model, setting the roaming rate, and the speed multiplier is set to 8 to speed up the roaming speed, which can browse large models faster and improve inspection efficiency.

[0165] Project Examples

[0166] Establish a BIM cable-stayed bridge model. A bridge is a prestressed concrete low-tower cable-stayed bridge consolidation system. The calculated span is (124+248+124)m, the total length is 497.5 (including 0.75m from the beam end to the support center on both sides), the small mileage beam gap is 0.3m, and the large mileage beam gap is 0.25m. The lateral center distance of the side support is 9.3m, the net width of the inner side of the protective wall is 9.0m, the board panel width is 14.30m, and the tower beam pier consolidation is partially widened to 18.3m. The model is as follows Figure 3 shown.

[0167] After completing the modeling of the BIM cable-stayed bridge model, the monitoring page is integrated and improved. The main interface of the system is mainly divided into three modules, such as Figure 4 As shown. The left interface is the sensor area, which shows the arrangement of sensors; the right interface is the cable force and stress changes of the key monitoring parts of the bridge structure and the wind control threshold of the corresponding physical quantity; the top of the middle corresponds to the total number of sensors and the number of operations. The middle of the system page is the model area, where various operations of the model can be realized. The upper side of the model area corresponds to the sensor monitoring module, the field visualization module, the equipment management module, the environmental monitoring management module, the file management and data analysis module, the threshold management module, the health monitoring early warning module, and the roaming module. The upper left part is the "Home" button and the "Page Operation" button, which correspond to jumping back to the home page and performing page operations (including refreshing the page, closing other pages, and closing all pages). The middle part of the main interface is the display interface of each function of the system, which is initially the home page; according to the different monitoring instruments and monitoring requirements, the monitoring information of each line of the project is summarized in the form of BIM model and monitoring data visualization (bar chart, pie chart, node diagram, field video, etc.).

[0168] Online mapping of health monitoring data automatically connects monitoring points to the database, and visualizes the monitoring and operation data in one picture, such as Figure 5 As shown. The round caps on the cable-stayed bridge represent the locations of different types of monitoring instruments. Click the round cap corresponding to the monitoring instrument, and the system will automatically locate and pop up a frame to display the measured data curve of the monitoring instrument. The system provides a variety of data presentation methods according to the types of different monitoring instruments. When the monitoring instrument is a thermometer, the measurement information interface will generate a temperature change curve over a specified time interval. When the monitoring instrument is a stress meter, the chart should include a stress change curve over time. Based on the monitoring data, on-site managers can directly view the overall situation of the project and the monitoring model in the 3D model environment, and timely understand the health information of the monitoring points.

[0169] Compare the stress monitoring data with the prescribed warning value to determine whether the monitoring data exceeds the limit. When the stress exceeds the limit, the warning component of the cable-stayed bridge monitoring display web page will be displayed in red, and an email reminder will be sent. According to the warning status, the health status of the monitoring structure control section can be quickly determined, and the dangerous structure parts can be quickly located, such as Figure 6 shown.

[0170] The cable-stayed bridge health monitoring interface can use the third-person perspective to roam and view the model, replacing the traditional manual inspection. Figure 7 shown.

[0171] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for online mapping of health monitoring data of a cable-stayed bridge, characterized in that , the steps are as follows: S1. Establish a parametric BIM model of a cable-stayed bridge and perform lightweight processing on the BIM model based on GLTF; S2, integrate the page by calling the BIMface front-end interface through Vue.js, and bind the integrated page with the lightweight BIM model in S1; S21. Create a BIMFACE developer account, install Vue.js and set up a Vue.js project; S22. Log in to the BIMFACE developer platform, create a new application, and obtain an API key; S23. Import the BIMFACE Viewer JavaScript library into the Vue.js project, then initialize the BIMFACEViewer and authenticate using the API key obtained in S22. S24. Use the API call provided by BIMFACE Viewer to load BIM model data, including the model's geometric information and attribute data; S25. Create one or more components in the Vue.js project to house the BIMFACE Viewer and user interface related elements; S26. Bind the data of the BIM model to the components in Vue.js, and dynamically update the display and attribute information of the model when the user interacts with the application; S27. Use the event processing mechanism of Vue.js to add user interaction functions, including the function of displaying relevant information by clicking on model components, the function of zooming in and out, and the function of rotating operations; S28. Use Vue.js's style binding and layout management to beautify and customize the appearance of BIMFACE Viewer; S29. After testing and debugging, build the Vue.js project into a production version and deploy it to the server; S3. Arrange the monitoring points of the cable-stayed bridge by calling the API three-dimensional tags; S31. Use finite element software to build a cable-stayed bridge model and conduct analysis; S32. Determine monitoring points based on actual monitoring needs and analysis results; S33, obtaining component attributes to obtain the coordinates of the monitoring points; S34, arranging monitoring points through three-dimensional tags and monitoring events; S4, associate the monitoring point with the sensor, and store the relevant information data of the sensor in the monitoring point through Node.js; S41, classify according to the type of sensor and the position, force, identification data, phasing, data; S42, establishing a corresponding database according to the classification in S41, combined with the sensor data collection interval, the adopted data transmission protocol, and the identification information in the protocol; S43, after processing the relevant data of the sensor database through Node.js, the data is stored in the monitoring point, and the monitoring point information is coupled with the sensor information; the relevant data processing of the sensor database is specifically to process the collected frequency into stress, and the calculation formula is: in, represents stress, K is the calibration coefficient of the sensor, is the initial frequency of the sensor, is the acquisition frequency; Where E is the elastic modulus of the material, is the material strain; S5, visualize the health monitoring data, and click on the sensor to obtain the health monitoring data according to the association between the monitoring point and the sensor in S4; S51. Data centering: perform mean centering on each feature. The formula is: Where X is the original data matrix, is the mean vector of each column feature, represents the data center matrix; S52. Calculate the covariance matrix of the data matrix , the formula is: Where m is the number of samples; S53, eigenvalue decomposition, perform eigenvalue decomposition on the covariance matrix, the formula is: Where Q is the eigenvector matrix, Λ is the diagonal eigenvalue matrix; S54, select the principal component, and select the eigenvectors with the largest eigenvalues ​​as the principal component; S55. Constructing the projection matrix , the formula is = in, represents the kth eigenvector; S56. Project the data onto the selected principal component and visualize the data. The formula is: In the formula, is the matrix after projection; S6. Set a health monitoring warning threshold according to the monitoring target, compare the health monitoring data obtained in S5 with the set health monitoring warning threshold, and determine whether the health monitoring data exceeds the limit. When the health monitoring data exceeds the health monitoring warning threshold, the warning component of the monitoring display webpage of the cable-stayed bridge changes color, and sends an email reminder. According to the warning status, the health status of the monitoring structure control section can be quickly determined, and the dangerous structure parts can be quickly located; S7, based on the results output by S6, real-time map the health monitoring status of the cable-stayed bridge and roam through the model from a third-person perspective.

2. The online mapping method for health monitoring data of a cable-stayed bridge according to claim 1 is characterized in that: The specific process of step S1 is as follows: S11. Convert the BIM model in Revit format into a GLTF file based on the edge folding algorithm. The edge folding algorithm uses a global energy equation to determine the edge folding order and the position of the new vertex, and gradually adds details to generate bridge models of different complexities. The specific contents are as follows: S110, input vertex sequence v=[x,y,z]T and triangle face sequence ,get The sum of the squared distances to the face of each triangle in Planes(v) associated with v , the specific expression is as follows: Where p=[a,b,c,d]T represents the plane equation ax+by+cz+d=0 for each triangle in Planes(v), and a2+b2+c2=1; S111, after matrix transformation, obtain the error matrix , the specific expression is as follows: S112, Error matrix for associated plane Sum up and get the error matrix Q of each vertex. The specific expression is as follows: ； S12, optimize the GLTF file converted by S11 through Draco; S13, loading the optimized GLTF file in S12 to the cloud for rendering to obtain the final lightweight BIM model.

3. The online mapping method for health monitoring data of a cable-stayed bridge according to claim 2 is characterized in that: The types of sensors in S41 include vibrating wire strain sensors, wind sensors, displacement sensors, and cable force sensors.

4. A mapping system for the online mapping method for health monitoring data of a cable-stayed bridge according to any one of claims 1 to 3, characterized in that: It includes a BIM model operation module, a data acquisition module, a real-time monitoring module, a monitoring and early warning module, a data query module, a roaming module and a field visualization module. The data query module includes an early warning report and a historical data query; the real-time monitoring module is electrically connected to the monitoring and early warning module, the monitoring and early warning module is electrically connected to the data query module, the field visualization module, the real-time monitoring module, the monitoring and early warning module, and the roaming module are all electrically connected to the BIM model operation module, and the data acquisition module provides data for the field visualization module and the real-time monitoring module.

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