A method for calculating cable forces based on 3D scanning of cable shapes

Abstract

This invention discloses a method for calculating the cable force of a cable-stayed bridge based on 3D scanning of cable shape, relating to the field of bridge inspection technology, and includes: 1. Obtaining the original point cloud of the cable based on a 3D scanner, and using the DBSCAN clustering algorithm to segment the scanned cable point cloud, which can quickly and accurately obtain the point cloud of each independent cable; 2. Accurately extracting the cable shape of a single cable; 3. Calculating the cable force using an iterative method based on the cable shape extracted in the above steps using the catenary formula. This invention can quickly and accurately calculate the cable force of a cable-stayed bridge cable, avoiding the shortcomings of traditional cable force testing methods, such as excessive time and unstable accuracy due to the coupling of multiple parameters.

Description

Technical Field

[0001] This invention belongs to the field of bridge inspection technology, specifically a method for calculating the cable force of a stay cable based on three-dimensional scanning cable shape. Background Technology

[0002] In the field of structural engineering, cable-stayed bridges, as a modern bridge structure, are highly complex in design and construction. The stay cables, as crucial components supporting the main girder, directly impact the bridge's safety and operational efficiency due to their stress characteristics. Therefore, accurate testing and analysis of the mechanical properties of stay cables are essential prerequisites for ensuring the structural safety of cable-stayed bridges. Cable force testing is a vital task that is frequently performed on cable-stayed bridges throughout their construction, operation, and maintenance phases. The accuracy of cable force testing directly affects the accuracy of the overall stress analysis of the bridge.

[0003] Traditional methods for measuring cable tension in cable-stayed bridges mainly include: pressure gauge measurement, pressure sensor measurement, magnetic flux method, and frequency method. The pressure gauge method uses the relationship between the hydraulic pressure of a jack cylinder and the cable tension to measure cable tension; it is only used for cable tension measurement during construction or cable replacement and cannot measure tensioned cables. The pressure sensor method uses sensors anchored to the cable ends to test cable tension; it is costly and requires pre-installation during construction, so it is rarely used in existing long-span cable-stayed bridges. The magnetic flux method uses the calibrated relationship between induced electromotive force and cable stress to monitor cable tension changes; however, this method has high calibration requirements and is greatly affected by factors such as temperature, resulting in poor accuracy when testing cable tension during the operational phase. The frequency method, based on string vibration theory, is widely used in structural construction control, condition assessment, and health monitoring; however, traditional string theory ignores the effects of cable bending stiffness, sag, and external dampers, sometimes leading to unacceptable errors in practical applications.

[0004] Currently, 3D laser scanning technology has been widely used in the construction field, but it is rarely used in bridge engineering, especially in the construction monitoring and measurement process of large cable-stayed bridges. Summary of the Invention

[0005] This invention aims to overcome the shortcomings of existing technologies and provide a method for calculating cable force of cable-stayed bridges based on three-dimensional scanning cable shape. It aims to improve the efficiency and accuracy of cable force testing for cable-stayed bridges and solve the problems of excessively long testing time, low efficiency, and unstable cable force calculation accuracy in traditional cable force testing. This will effectively improve the accuracy, reliability, and efficiency of cable force measurement for cable-stayed bridges.

[0006] To achieve the above-mentioned objectives, the present invention adopts the following technical solution:

[0007] The present invention provides a method for calculating the cable force of a stay cable based on a three-dimensional scanning cable shape, characterized by the following steps:

[0008] Step 1: Use a 3D laser scanner to obtain the original point cloud of multiple cables and transform it to a global Cartesian coordinate system to obtain the coordinate set of the 3D point cloud. ,in, Let be the coordinates of the i-th 3D point cloud, and n be the total number of 3D point clouds for all cables. Let represent the coordinates of the i-th 3D point cloud in the x-axis direction. Let represent the coordinates of the i-th point along the y-axis. This represents the coordinates of the i-th point along the z-axis.

[0009] The coordinates in the x-axis direction and coordinates in the z-axis direction Two-dimensional coordinates that make up the i-th 3D point cloud This constitutes two-dimensional point cloud coordinate data. ;

[0010] Step 2: Use the DBSCAN clustering algorithm to... The points are segmented to obtain the complete point cloud for each cable;

[0011] Step 3: The improved RANSAC algorithm is used to denoise the cross-sectional point cloud of each micro-segment on a single cable, so as to obtain the denoised cross-sectional point cloud of each micro-segment on a single cable, and to fit the best circular model of the point cloud on the cross-section of each micro-segment and its fitting center and fitting radius.

[0012] Step 4: Connect the centers of each fitted circle in sequence to obtain the cable shape of a single cable;

[0013] Step 5: Calculate the cable force F of a single cable based on its shape.

[0014] The method for calculating the cable force of a cable-stayed bridge based on a three-dimensional scanning cable shape, as described in this invention, is characterized in that step 2 includes the following steps:

[0015] Step 2.1: Define the minimum cluster radius as The minimum number of point clouds within the fitting radius is p; the number of current clusters is C, and C is initialized to 0; i = 1;

[0016] Step 2.2: with To find cluster centers, use the RegionQuery function to locate them. Cluster radius All point cloud data within and as The neighboring point cloud, to determine If the total number of neighbor point clouds is less than p, then mark the neighbor point clouds in the Cth cluster as noise points and proceed to step 2.4; otherwise, assign C+1 to C and then... The neighbor point clouds are used to form the Cth cluster, and step 2.3 is executed;

[0017] Step 2.3: Use the ExpandCluster function to recursively access all neighbor point clouds in the Cth cluster, and retain all neighbor point clouds whose number of new neighbor point clouds found with each neighbor point cloud as the cluster center is greater than p, and add them to the Cth cluster;

[0018] Step 2.4: After assigning i+1 to i, return to step 1.2 and execute sequentially until i>n, thereby obtaining C clusters, and treating each cluster as a complete point cloud of a single cable;

[0019] Step 2.5: Sort the C cables according to the minimum coordinate value in the x-axis direction of the complete point cloud of each cable, and obtain the sorted C cables.

[0020] Furthermore, step 3 includes the following steps:

[0021] Step 3.1: Fit the complete point cloud of a single cable with a cubic polynomial to obtain the approximate centerline of the single cable, thereby determining the tangent vector of the single cable at any position, and dividing the complete point cloud of the single cable into S micro segments by slicing.

[0022] Step 3.2: Randomly select three points from the denoised point cloud on the cross-section of the s-th micro-segment and perform circle fitting to obtain a fitted circle. Then, count whether the number of points in the fitted circle that meet the fitting requirements is greater than the threshold K. If so, then the corresponding fitted circle is used as the approximate center of the point cloud on the cross-section of the s-th micro-segment. With approximate radius Otherwise, return to step 3.2 and select a new point;

[0023] Step 3.3: Set a radius threshold Calculate the distance from any point in the point cloud on the cross-section of the s-th micro-segment to the approximate center of the circle. The distance d, and will satisfy The points are retained, and the remaining points are treated as noise points and removed, thus obtaining the remaining point cloud on the cross section of the s-th micro-segment;

[0024] Step 3.4: Set a threshold for the number of points If the number of points in the remaining point cloud is greater than the threshold If the fitted circle of the corresponding micro-segment is selected as the candidate circle model, otherwise, return to step 3.2 to reselect points; until the number of candidate circle models reaches the set upper limit.

[0025] Step 3.5: Set the threshold The least squares method is used to calculate the center and radius of the point cloud in any candidate circle model. The fitting is performed, and the distance from any point in any candidate circle model to the center of its own fitted circle is calculated. and will satisfy The points that are selected are retained, and the remaining points are treated as noise points and removed, thus obtaining the remaining point cloud in any candidate circle model;

[0026] Step 3.6: Count the number of remaining point clouds in each candidate circular model. The candidate circular model with the most remaining point clouds is the best circular model of the point cloud on the cross section of the s-th micro segment. The center and radius of the best circular model are the fitted center and fitted radius of the point cloud on the cross section of the s-th micro segment, thus obtaining the fitted center and fitted radius of the point cloud on the cross section of the S micro segments.

[0027] Furthermore, step 5 includes the following steps:

[0028] Step 5.1: Establish a two-dimensional local coordinate system for a single cable, with the upper end point of the cable as the origin O(0,0), the direction from the upper end point along the elevation direction to the lower end point as the positive Y-axis, and the direction from the upper end point along the horizontal direction to the lower end point as the positive X-axis. Label the lower end point of the cable as B(l,h); l represents the horizontal span of the cable, and h represents the vertical span. Label the S fitted circle centers in the two-dimensional local coordinate system as follows: ,in, This represents the coordinates of the s-th fitted circle center in the two-dimensional local coordinate system;

[0029] Step 5.2: Set the calculation range for the horizontal component of the cable force. ,in, This represents the lower limit of the calculation range for the horizontal component of the cable force. This represents the upper limit of the calculation range for the horizontal component of the cable force.

[0030] Step 5.3: Initialize q=1, and set the total number of calculations to Q; ;

[0031] Step 5.4: Calculate the qth value of the horizontal component of the cable force using equation (1). :

[0032] (1)

[0033] Step 5.5: Calculate the q-th ordinate value of a single cable using equation (2). :

[0034] (2)

[0035] In equation (2), Let represent the x-coordinate of the s-th fitted circle center in the local coordinate system, c represent the linear unit weight of a single cable, and cosh is the hyperbolic cosine function. and Let be the two coefficients calculated for the qth time, and we have:

[0036] (3)

[0037] (4)

[0038] In equation (4), sinh is a hyperbolic sine function;

[0039] Step 5.6: Use equation (5) to obtain the sum of squared differences in the qth calculation. ;

[0040] (5)

[0041] Step 5.7: After assigning q+1 to q, return to Step 5.4 and recalculate until q>Q. Record the calculated horizontal component of the cable force corresponding to the smallest sum of squared differences as... ;

[0042] Step 5.8: Initialize q=1, update the upper limit of the calculation interval for the horizontal component of the cable force. The lower limit is And update the q-th calculated value using equation (6). Then, following steps 5.5 to 5.7, the updated calculated value of the horizontal component of the cable force is obtained. ;

[0043] (6)

[0044] In equation (6), m represents a multiple;

[0045] Step 5.9: Initialize q=1, update the upper limit of the calculation interval for the horizontal component of the cable force. The lower limit is And update the calculated value of the qth time using equation (7). Then, following steps 5.5 to 5.7, the final calculated value of the horizontal component of the cable force is obtained. And calculate the final horizontal component of the cable force. The two corresponding calculation coefficients are denoted as follows: and ;

[0046] (7)

[0047] Step 5.10: Calculate the cable force F at any position of the cable using equation (8);

[0048] (8)

[0049] In equation (8), The angle between the cable and the horizontal plane is represented by equation (9);

[0050] (9).

[0051] The present invention provides an electronic device, including a memory and a processor, wherein the memory is used to store a program that supports the processor in executing the cable force calculation method based on three-dimensional scanning cable shape, and the processor is configured to execute the program stored in the memory.

[0052] The present invention discloses a computer-readable storage medium on which a computer program is stored, wherein the computer program, when executed by a processor, performs the steps of the cable force calculation method based on a three-dimensional scanned cable shape.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] 1. This invention proposes a method for calculating the cable force of a cable-stayed bridge based on laser scanning, which can quickly and accurately identify the cable force of a cable-stayed bridge. Compared with traditional cable force testing methods, the accuracy of the cable force calculation in this invention is only related to the extraction of the cable's specific weight and cable profile accuracy, and is not affected by the coupling of multiple parameters of the cable itself, thus greatly improving the accuracy of cable force testing. Furthermore, compared with traditional cable force testing, this method has been well validated in actual bridges in terms of data acquisition efficiency, avoidance of potential risks, reduction of traffic interference, and improvement of cable force testing accuracy.

[0055] 2. Compared to existing contour line cable segmentation algorithms that require multiple parameters, some of which are difficult to determine precisely, the DBSCAN clustering algorithm used in this invention only requires the cluster radius and minimum number of clusters as input. These two parameters are easily determined, making the cable segmentation method simpler and more convenient, and achieving higher accuracy. For existing cable shape extraction methods, the improved RANSAC algorithm not only improves the efficiency of noise point removal but also dynamically adjusts the number of calculations based on the fitting center effect, simplifying the cable shape extraction steps, reducing workload, and improving computational efficiency. A key advantage of the improved RANSAC algorithm is its strong robustness to outliers in the data. Even with many noise points and outliers in the scanned point cloud data, it can find a reasonable fitting model, thereby improving the accuracy of the fitting, ensuring the precision of cable shape extraction, and making cable force calculation more accurate. Attached Figure Description

[0056] Figure 1 This is a schematic diagram of the specific process of the method of the present invention;

[0057] Figure 2 This is a schematic diagram of the original cable point cloud from a 3D scan.

[0058] Figure 3 This is a schematic diagram of the point cloud of a single cable in three-dimensional coordinates.

[0059] Figure 4a This is a schematic diagram of the DBSCAN clustering algorithm of the present invention segmenting the cable point cloud;

[0060] Figure 4b This is a schematic diagram illustrating the accuracy of segmenting the cable point cloud using the DBSCAN clustering algorithm.

[0061] Figure 5a A schematic diagram of the cross-sectional projection of the point cloud of the cable;

[0062] Figure 5b A schematic diagram illustrating the removal of noise points using the improved RANSAC algorithm;

[0063] Figure 5c This is a comparison chart of the fitted center of the circle before and after noise reduction;

[0064] Figure 5d A schematic diagram for extracting the cable profile of the stay cable;

[0065] Figure 6 This is a diagram showing the comparison between the calculated cable force and the actual cable force. Detailed Implementation

[0066] In this example, a method for calculating the cable force of a stay cable based on a 3D scanned cable shape mainly includes: 1. Obtaining the original point cloud of the stay cable using a 3D scanner, and segmenting the scanned cable point cloud using the DBSCAN clustering algorithm to quickly and accurately obtain the point cloud of each individual cable; 2. Accurately extracting the cable shape; 3. Calculating the cable force of the stay cable using the catenary formula based on the cable shape extracted in the above steps. Specifically, as... Figure 1 As shown, the method is performed according to the following steps:

[0067] Step 1: Obtain the original point cloud of multiple cables using a 3D laser scanner. The original point cloud image of the cables is shown below. Figure 2 As shown. A global Cartesian coordinate system is established, and the original point cloud of multiple cables is transformed into the global coordinate system. A schematic diagram of the point cloud of a single cable in 3D coordinates is shown below. Figure 3 As shown. The coordinates of the point cloud data are... ,in, Let i be the coordinates of the i-th 3D point cloud. , where n is the total number of 3D point clouds of the cable. Let represent the coordinates of the i-th 3D point cloud in the x-axis direction. Let represent the coordinates of the i-th point along the y-axis. This represents the coordinates of the i-th point along the z-axis.

[0068] The coordinates in the x-axis direction and coordinates in the z-axis direction Two-dimensional coordinates that make up the i-th 3D point cloud This constitutes two-dimensional point cloud coordinate data. .

[0069] Step 2: Use the DBSCAN clustering algorithm to... The points are segmented to obtain the complete point cloud for each cable;

[0070] Step 2.1: Define the minimum cluster radius as p = 10, and the minimum number of point clouds within the fitted radius is p = 10; the size of the minimum cluster radius is defined by the shortest horizontal distance between the two cables. The cluster count is C, and C = 0 is initialized; i = 1.

[0071] Step 2.2: with To find cluster centers, use the RegionQuery function to locate them. Cluster radius All point cloud data within and as The neighboring point cloud, to determine If the total number of neighbor point clouds is less than p, then mark the neighbor point clouds in the Cth cluster as noise points and proceed to step 1.4; otherwise, assign C+1 to C and then... The neighbor point clouds are used to form the Cth cluster, and step 1.3 is executed.

[0072] Step 2.3: Use the ExpandCluster function to recursively access all neighbor point clouds in the Cth cluster, and retain all neighbor point clouds whose number of new neighbor point clouds found with each neighbor point cloud as the cluster center is greater than p, and add them to the Cth cluster;

[0073] Step 2.4: After assigning i+1 to i, return to step 1.2 and execute sequentially until i>n, thus obtaining C clusters, and treating each cluster as a complete point cloud of a single cable; the cable segmentation image is as follows. Figure 4a As shown, each color represents a single cable point cloud; the segmentation accuracy image is as follows. Figure 4b As shown, it can be observed that the number of points in the cable point cloud automatically segmented is exactly the same as that manually segmented.

[0074] Step 2.5: Sort the C cables according to the minimum coordinate value in the x-axis direction of the complete point cloud of each cable, and obtain the sorted C cables.

[0075] Step 3: The improved RANSAC algorithm is used to denoise the cross-sectional point cloud of the cable to obtain the denoised cross-sectional point cloud of the cable.

[0076] Step 3.1: Fit the complete point cloud of a single cable using a cubic polynomial to obtain an approximate centerline of the cable, thereby determining the tangent vector of the cable at any position; then divide the complete point cloud of the single cable into S micro-segments using a slicing method. The number of micro-segments S is related to the length of the cable, and is generally taken as 0.5m to 1m as the length of one micro-segment;

[0077] Step 3.2: Randomly select three points from the point cloud on the cross-section of the s-th micro-segment and perform circle fitting to obtain a fitted circle, where, The cross-sectional projection of the cable is shown below. Figure 5a As shown. Calculate the center and radius of the fitted circle formed by the three sample points. For each remaining sample point, calculate the distance from that point to the center of the fitted circle and compare it with a preset threshold to determine if the point is an interior point. If the distance is less than the set radius threshold, the point is marked as an interior point and retained; otherwise, it is marked as an exterior point and removed. Count whether the number of points in the fitted circle that meet the fitting requirements is greater than a threshold K. The threshold K is generally three-quarters of the total number of fitted points. If so, the corresponding fitted circle is used as the approximate center of the point cloud on the cross-section of the s-th micro-segment. With approximate radius Otherwise, return to step 3.2 to select a new point.

[0078] Step 3.3: Set a radius threshold =0.01m, calculate the distance from any point in the point cloud on the cross-section of the s-th micro-segment to the approximate center of the circle. The distance d, and will satisfy The points are retained, and the remaining points are treated as noise points and removed, thus obtaining the remaining point cloud on the cross section of the s-th micro-segment;

[0079] Step 3.4: Set a point cloud quantity threshold , The value is set to two-thirds of the total number of fitted sample points. If the number of points in the remaining point cloud is greater than the threshold... The fitted circle of the corresponding micro-segment is selected as the candidate circle model; otherwise, return to step 3.2 to reselect points; this continues until the number of candidate circle models reaches the set upper limit. The improved RANSAC algorithm separates noisy points in the image as follows: Figure 5b As shown, the red points are the removed outer points, i.e., noise points; the blue points are the retained inner points, used to fit the center and radius of the circle.

[0080] Step 3.5: Set the threshold =0.008m, using the least squares method to determine the center and radius of any candidate circle model. Perform a fitting operation and calculate the distance from any point cloud in any candidate circle model to its own center. and will satisfy The points that are selected are retained, and the remaining points are treated as noise points and removed, thus obtaining the remaining point cloud in any candidate circle model;

[0081] Step 3.6: Count the number of remaining point clouds in each candidate circular model. The candidate circular model with the largest number of remaining point clouds is the optimal circular model for the point cloud on the cross-section of the s-th micro-segment. The center and radius of the optimal circular model are the fitted center and radius of the point cloud on the cross-section of the s-th micro-segment, thus obtaining the fitted center and radius of the point cloud on the cross-sections of the S micro-segments. A comparison of the fitted center of the circle before and after noise reduction is shown in the figure. Figure 5c As shown, the red circle represents the fitted circle after the first noise reduction, and the blue circle represents the final fitted circle.

[0082] Step 4: Connect the centers of the S fitted circles in sequence to obtain the cable shape of a single cable. The cable shape image of a single cable is shown below. Figure 5d As shown;

[0083] Step 5.1: Establish a two-dimensional local coordinate system for a single cable, with the upper end point of the cable as the origin O(0,0), the direction from the upper end point along the elevation direction to the lower end point as the positive Y-axis, and the direction from the upper end point along the horizontal direction to the lower end point as the positive X-axis. Label the lower end point of the cable as B(l,h); l represents the horizontal span of the cable, and h represents the vertical span. Label the S fitted circle centers in the two-dimensional local coordinate system as follows: ,in, This represents the coordinates of the s-th fitted circle center in the two-dimensional local coordinate system;

[0084] Step 5.2: Set the calculation range for the horizontal component of the cable force. ,in, This represents the lower limit of the calculation range for the horizontal component of the cable force. This is the upper limit of the calculation range for the horizontal component of the cable force; the calculation range for the horizontal component of the cable force is based on empirical values ​​of the cable forces on actual bridges.

[0085] Step 5.3: Initialize q=1, and set the total number of calculations to Q; The value of Q is related to the upper and lower limits of the calculation range of the horizontal component of the cable force.

[0086] Step 5.4: Calculate the qth value of the horizontal component of the cable force using equation (1). :

[0087] (1)

[0088] Step 5.5: Calculate the q-th ordinate value of a single cable using equation (2). :

[0089] (2)

[0090] In equation (2), Let represent the x-coordinate of the s-th fitted circle center in the local coordinate system, c represent the linear unit weight of a single cable, and cosh is the hyperbolic cosine function. and Let be the two coefficients calculated for the qth time, and we have:

[0091] (3)

[0092] (4)

[0093] In equation (4), sinh is a hyperbolic sine function.

[0094] Step 5.6: Use equation (5) to obtain the sum of squared differences in the qth calculation. ;

[0095] (5)

[0096] Step 5.7: After assigning q+1 to q, return to Step 5.4 and recalculate until q>Q. Record the calculated horizontal component of the cable force corresponding to the smallest sum of squared differences as... ;

[0097] Step 5.8: Initialize q=1, update the upper limit of the calculation interval for the horizontal component of the cable force. The lower limit is And update the q-th calculated value using equation (6). Then, following steps 5.5 to 5.7, the updated calculated value of the horizontal component of the cable force is obtained. ;

[0098] (6)

[0099] In equation (6), m represents a multiple;

[0100] Step 5.9: Initialize q=1, update the upper limit of the calculation interval for the horizontal component of the cable force. The lower limit is The value of m is taken as 1 / 1000 of the length of the calculation interval. The q-th calculated value is then updated using equation (7). Then, following steps 5.5 to 5.7, the final calculated value of the horizontal component of the cable force is obtained. And calculate the final horizontal component of the cable force. The two corresponding calculation coefficients are denoted as follows: and ;

[0101] (7)

[0102] Step 5.10: Calculate the cable force F at any position of the cable using equation (8), and compare the calculated cable force with the actual cable force. Figure 6 As shown, the error between the calculated cable force and the designed cable force is basically kept within 5%;

[0103] (8)

[0104] In equation (8), The angle between the cable and the horizontal plane is represented by equation (9);

[0105] (9).

[0106] In this embodiment, an electronic device includes a memory and a processor. The memory stores a program that supports the processor in executing the above-described method, and the processor is configured to execute the program stored in the memory.

[0107] In this embodiment, a computer-readable storage medium stores a computer program, which is executed by a processor to perform the steps of the above method.

Claims

1. A method for calculating the cable force of a stay cable based on a three-dimensional scanning cable shape, characterized in that, Includes the following steps: Step 1: Use a 3D laser scanner to obtain the original point cloud of multiple cables and transform it to a global Cartesian coordinate system to obtain the coordinate set of the 3D point cloud. ,in, Let be the coordinates of the i-th 3D point cloud, and n be the total number of 3D point clouds for all cables. Let represent the coordinates of the i-th 3D point cloud in the x-axis direction. Let represent the coordinates of the i-th point along the y-axis. This represents the coordinates of the i-th point along the z-axis. The coordinates in the x-axis direction and coordinates in the z-axis direction Two-dimensional coordinates that make up the i-th 3D point cloud This constitutes two-dimensional point cloud coordinate data. ; Step 2: Use the DBSCAN clustering algorithm to... The points are segmented to obtain the complete point cloud for each cable; Step 3: The improved RANSAC algorithm is used to denoise the cross-sectional point cloud of each micro-segment on a single cable, so as to obtain the denoised cross-sectional point cloud of each micro-segment on a single cable, and to fit the best circular model of the point cloud on the cross-section of each micro-segment and its fitting center and fitting radius. Step 3.1: Fit the complete point cloud of a single cable with a cubic polynomial to obtain the approximate centerline of the single cable, thereby determining the tangent vector of the single cable at any position, and dividing the complete point cloud of the single cable into S micro segments by slicing. Step 3.2: Randomly select three points from the denoised point cloud on the cross-section of the s-th micro-segment and perform circle fitting to obtain a fitted circle. Then, count whether the number of points in the fitted circle that meet the fitting requirements is greater than the threshold K. If so, then the corresponding fitted circle is used as the approximate center of the point cloud on the cross-section of the s-th micro-segment. With approximate radius Otherwise, return to step 3.2 and select a new point; Step 3.3: Set a radius threshold Calculate the distance from any point in the point cloud on the cross-section of the s-th micro-segment to the approximate center of the circle. The distance d, and will satisfy The points are retained, and the remaining points are treated as noise points and removed, thus obtaining the remaining point cloud on the cross section of the s-th micro-segment; Step 3.4: Set a threshold for the number of points If the number of points in the remaining point cloud is greater than the threshold If the fitted circle of the corresponding micro-segment is selected as the candidate circle model, otherwise, return to step 3.2 to reselect points; until the number of candidate circle models reaches the set upper limit. Step 3.5: Set the threshold The least squares method is used to calculate the center and radius of the point cloud in any candidate circle model. The fitting is performed, and the distance from any point in any candidate circle model to the center of its own fitted circle is calculated. and will satisfy The points that are selected are retained, and the remaining points are treated as noise points and removed, thus obtaining the remaining point cloud in any candidate circle model; Step 3.6: Count the number of remaining point clouds in each candidate circular model. The candidate circular model with the most remaining point clouds is the best circular model of the point cloud on the cross section of the s-th micro segment. The center and radius of the best circular model are the fitted center and fitted radius of the point cloud on the cross section of the s-th micro segment, thus obtaining the fitted center and fitted radius of the point cloud on the cross section of the S micro segments. Step 4: Connect the centers of each fitted circle in sequence to obtain the cable shape of a single cable; Step 5: Calculate the cable force F of a single cable based on its shape.

2. The method for calculating the cable force of a stay cable based on a three-dimensional scanning cable shape according to claim 1, characterized in that, Step 2 includes the following steps: Step 2.1: Define the minimum cluster radius as The minimum number of point clouds within the fitting radius is p; the number of current clusters is C, and C is initialized to 0; i = 1; Step 2.2: with To find cluster centers, use the RegionQuery function to locate them. Cluster radius All point cloud data within and as The neighboring point cloud, to determine If the total number of neighbor point clouds is less than p, then mark the neighbor point clouds in the Cth cluster as noise points and execute step 2.

4. Otherwise, after assigning C+1 to C, The neighbor point clouds are used to form the Cth cluster, and step 2.3 is executed; Step 2.3: Use the ExpandCluster function to recursively access all neighbor point clouds in the Cth cluster, and retain all neighbor point clouds whose number of new neighbor point clouds found with each neighbor point cloud as the cluster center is greater than p, and add them to the Cth cluster; Step 2.4: After assigning i+1 to i, return to step 1.2 and execute sequentially until i>n, thereby obtaining C clusters, and treating each cluster as a complete point cloud of a single cable; Step 2.5: Sort the C cables according to the minimum coordinate value in the x-axis direction of the complete point cloud of each cable, and obtain the sorted C cables.

3. The method for calculating the cable force of a stay cable based on a three-dimensional scanning cable shape according to claim 2, characterized in that, Step 5 includes the following steps: Step 5.1: Establish a two-dimensional local coordinate system for a single cable, with the upper end point of the cable as the origin O(0,0), the direction from the upper end point along the elevation direction to the lower end point as the positive Y-axis, and the direction from the upper end point along the horizontal direction to the lower end point as the positive X-axis. Label the lower end point of the cable as B(l,h); l represents the horizontal span of the cable, and h represents the vertical span. Label the S fitted circle centers in the two-dimensional local coordinate system as follows: ,in, This represents the coordinates of the s-th fitted circle center in the two-dimensional local coordinate system; Step 5.2: Set the calculation range for the horizontal component of the cable force. ,in, This represents the lower limit of the calculation range for the horizontal component of the cable force. This represents the upper limit of the calculation range for the horizontal component of the cable force. Step 5.3: Initialize q=1, and set the total number of calculations to Q; ; Step 5.4: Calculate the qth value of the horizontal component of the cable force using equation (1). : (1) Step 5.5: Calculate the q-th ordinate value of a single cable using equation (2). : (2) In equation (2), Let represent the x-coordinate of the s-th fitted circle center in the local coordinate system, c represent the linear unit weight of a single cable, and cosh is the hyperbolic cosine function. and Let be the two coefficients calculated for the qth time, and we have: (3) (4) In equation (4), sinh is a hyperbolic sine function; Step 5.6: Use equation (5) to obtain the sum of squared differences in the qth calculation. ; (5) Step 5.7: After assigning q+1 to q, return to Step 5.4 and recalculate until q>Q. Record the calculated horizontal component of the cable force corresponding to the smallest sum of squared differences as... ; Step 5.8: Initialize q=1, update the upper limit of the calculation interval for the horizontal component of the cable force. The lower limit is And update the q-th calculated value using equation (6). Then, following steps 5.5 to 5.7, the updated calculated value of the horizontal component of the cable force is obtained. ; (6) In equation (6), m represents a multiple; Step 5.9: Initialize q=1, update the upper limit of the calculation interval for the horizontal component of the cable force. The lower limit is And update the calculated value of the qth time using equation (7). Then, following steps 5.5 to 5.7, the final calculated value of the horizontal component of the cable force is obtained. And calculate the final horizontal component of the cable force. The two corresponding calculation coefficients are denoted as follows: and ; (7) Step 5.10: Calculate the cable force F at any position of the cable using equation (8); (8) In equation (8), The angle between the cable and the horizontal plane is represented by equation (9); (9)。 4. An electronic device, comprising a memory and a processor, characterized in that, The memory is used to store programs that support the processor in executing the cable force calculation method based on three-dimensional scanning cable shape as described in any of claims 1-3, and the processor is configured to execute the programs stored in the memory.

5. A computer-readable storage medium storing a computer program thereon, characterized in that, When the computer program is run by the processor, it executes the steps of the cable force calculation method based on three-dimensional scanning cable shape as described in any of claims 1-3.

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