Cable force optical measurement method based on multi-order modal shape fitting and measurement system thereof

Abstract

The application discloses a cable force optical measurement method based on multi-order modal shape fitting and a measurement system thereof. The method first captures a full-field image of a cable through a non-contact optical camera, and obtains dynamic displacement responses of each target point by using an adaptive gray-weighted centroid method; then, the method obtains frequencies of each order of the cable and corresponding modal shape curves by using a CMIF method of modal parameter identification; then, the method performs least square nonlinear fitting (NLSF) on each order of the measured modal shape function curve based on the obtained positions of each measuring point and corresponding amplitude values of the modal shapes, and identifies dimensionless parameters of the modal shapes; finally, the method calculates the cable force size in combination with unit length mass of the cable and the frequencies of each order. The application is dedicated to practical bridge application, and vibration responses of multiple measuring points of the cable can be extracted by using the non-contact full-field measurement advantage of the image.

Description

Technical Field

[0001] This invention belongs to the field of structural health monitoring and measurement, and more specifically, relates to a cable force optical measurement method and measurement system based on multi-mode shape fitting. Background Technology

[0002] As crucial load-bearing components in cable-stayed bridges, suspension bridges, and suspender arch bridges, cables often experience significant displacement due to relatively small changes in stress and strain, leading to relaxation and stress loss. Because of these characteristics, cable stress testing in cable-stayed bridges is of great importance during both the construction and service phases. Currently, commonly used methods for cable stress testing include the jack pressure gauge method, the pressure sensor method, the magnetic flux measurement method, and the vibration frequency method.

[0003] The traditional vibration frequency method for measuring cable force is the most widely used method because its equipment is reusable, the instruments are small and portable, and the results are relatively accurate. The frequency method generally uses classical string vibration theory, treating the cable as a taut string without considering its own weight and bending stiffness. This method is suitable for relatively slender cables. However, for more complex conditions, such as cables with elastic boundary conditions, cables with multiple intermediate supports, and cables where the bending stiffness EI is difficult to determine, the frequency method cannot meet the accuracy requirements of engineering applications.

[0004] The cable force measurement method based on cable mode shapes offers a novel approach, avoiding the challenge of establishing a cable analysis model with complex end boundaries to solve the cable force-frequency relationship. Instead, it analyzes and solves the cable force from the perspective of mode shape functions. There are two main approaches to the mode shape method. The first approach extracts the amplitudes of multiple measurement points from the identified cable mode shapes and establishes a system of equations to solve for the cable force. The second approach calculates the effective vibration length through mode shapes, which can be further divided into local effective length and global effective length. The local effective length method, also known as the half-wave method, uses the distance between the zero-amplitude points of modes of order 3 and above as the cable calculation length and substitutes it into the frequency-based cable force calculation formula to obtain the cable force.

[0005] However, the modal vibration method for measuring cable force is currently limited to the laboratory and has encountered some obstacles in its promotion in actual bridge engineering. This is because installing acceleration sensors at multiple control section locations on a cable is not only extremely costly and difficult to install manually, but also results in huge errors when monitoring only five measuring points. An error at just one measuring point will lead to failure in cable force identification, making it unsuitable for practical engineering applications. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to address the shortcomings of existing bridge cable force measurement technology, and to provide a cable force optical measurement method and system based on multi-mode shape fitting.

[0007] A cable force optical measurement method based on multi-mode shape fitting includes the following steps:

[0008] S1. Image Acquisition: Set up the camera on the bridge deck or at the measuring point under the bridge, adjust the camera lens to focus on the target cable, and then capture and save the sequence of motion images of the cable under environmental vibration or human excitation.

[0009] S2. Multi-point localization and calibration: Based on the line detection algorithm, the image boundary of the cable is extracted. Using the mathematical expression of the two boundary lines of the cable, the number of pixels occupied by the cable width near the measurement point is obtained. According to the formula...

[0010] s=Q / qi(1)

[0011] Calculate the magnification factor for each measuring point, where s is the magnification factor for converting the image pixel displacement to the actual displacement, Q is the actual value of the cable diameter, and qi is the pixel diameter corresponding to the position of the i-th measuring point.

[0012] S3. Multi-point displacement extraction: The gray-level weighted centroid method based on adaptive threshold is adopted to select the interest calculation area near the measurement point, calculate the displacement response of the area, and finally extract the displacement response data of multiple measurement points; based on the magnification coefficient of each measurement point in S2, the pixel displacement response data of each measurement point is converted into actual displacement.

[0013] S4. Modal parameter identification: Based on actual vibration response data, the frequencies and corresponding mode shape curves of each order of the cable are obtained through the CMIF modal parameter identification method, and the mode shape amplitudes at multiple test points are extracted in an orderly and uniform manner from the mode shape curves.

[0014] S5. Identification of dimensionless parameters of mode shape and calculation of cable force: Based on the obtained positions of each measuring point and the corresponding mode shape amplitude, the least squares nonlinear fitting (NLSF) is performed on the measured mode shape function curves of multiple orders to identify the dimensionless parameters of the mode shape; based on the identified dimensionless parameters of each mode shape, and combined with each order frequency and the mass per unit length m, the cable force is solved simultaneously to eliminate the influence of the bending stiffness value.

[0015] In step S2, image information is used to locate and calibrate each measuring point, achieving true non-contact measurement. This differs from traditional accelerometers and existing image-based methods that require pre-setting special targets and other ranging tools on the structure for measuring point location and calibration, which is impractical for cable-stayed bridge measurements in long spans. Therefore, this invention has stronger engineering applicability.

[0016] The gray-scale weighted centroid method in S3 directly tracks existing features such as landscape light targets on cable surfaces. No additional targets are required; only a single fixed CCD camera is needed to capture digital images of the object before and after deformation. The experimental equipment is portable, easy to operate, and the experimental process is simple.

[0017] In step S5, the mode shape amplitudes at multiple test points are extracted in an orderly and uniform manner from the mode shape curve. At least six test points are selected to fit the true mode shape curve. Obtaining displacement response data from multiple test points using the image method is fast, efficient, and low-cost, avoiding the limitations of difficult accelerometer installation. Furthermore, based on the advantages of the image method, the number of image selection points can far exceed the number of test points ultimately used to extract mode shape amplitudes and calculate cable force. This ensures a closer fit to the true mode shape curve and avoids the problem of inaccurate cable force measurement caused by large deviations at a few test points when fewer test points are selected, leading to large deviations in the mode shape curve.

[0018] The steps for identifying the dimensionless parameters of the vibration modes and calculating the cable forces in S5 and S6 are as follows:

[0019] S51. Assuming the bending stiffness of the cable is EI, the mass per unit length is m, and the tension is T, the equation of free vibration of the bar structure under environmental vibration is:

[0020]

[0021] Where u(x,t) is the lateral displacement response at position x at time t;

[0022] S52. Further derivation yields the mode shape function of the cable structure as follows:

[0023]

[0024] in:

[0025] Four constants, c1 to c4, determine the vibration shape, where a is a constant and g is a parameter related to the cable force. Obviously, a 2 =δ×ε,ε 2 -δ 2 =g 2 ;

[0026] S53. Based on obtaining the mode amplitudes of multiple measuring points through the CMIF method, the least squares nonlinear fitting is performed on the measured mode function curves of each order to identify the dimensionless parameter values ​​δ of each order.

[0027] S54. The magnitude of the cable force at any i-th order is: After identifying the nth mode, the influence of bending stiffness is eliminated by simultaneously solving a system of equations using the dimensionless parameter δ of each mode shape, thereby obtaining the cable force:

[0028]

[0029] Among them, f i f j Let be the i-th and j-th order frequencies of the Lasso.

[0030] A cable force optical measurement system based on multi-mode shape fitting, the system comprising an image acquisition system, a positioning and calibration system, an image-based displacement calculation system, and a cable force solution system;

[0031] The image acquisition system is used to acquire motion image sequences of bridge cables under environmental vibration or human excitation;

[0032] The positioning and calibration system includes two parts: calculating the pixel coordinates of the measurement point based on a straight line detection algorithm and calculating the magnification factor of the measurement point based on the mathematical expression of the two boundary lines of the cable.

[0033] The image-based displacement calculation system is used to import images, select calculation areas, perform displacement response calculations, and finally convert the displacement into actual displacement based on the magnification factor of the measuring points.

[0034] The cable force calculation system, based on actual displacement response data, obtains the frequencies and corresponding mode shape curves of each order of the cable through modal analysis, and performs least-squares nonlinear fitting on the measured mode shape function curves of each order to identify the dimensionless parameters of the mode shape, thereby solving the cable force by combining the mass per unit length and the frequencies of each order.

[0035] According to another aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the cable force optical measurement method based on multi-mode shape fitting of the present invention.

[0036] According to another aspect of the present invention, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the cable force optical measurement method based on multi-mode shape fitting of the present invention.

[0037] Compared with the prior art, the present invention has at least the following beneficial effects:

[0038] (1) This invention successfully avoids the problem of establishing a complex boundary analysis model of a cable with intermediate elastic support (such as a shock absorber or damper for a cable, a tie rod support frame for a tied arch bridge, a shock absorber frame for a suspender cable, etc.) to solve the relationship between cable force and frequency. It only requires the use of modal testing method to measure the cable force with complex unknown boundaries by using the amplitude at multiple measuring points of a certain vibration frequency and the corresponding mode shape.

[0039] (2) Previous modal-based cable force testing methods were limited to the laboratory. In actual bridge applications, a large number of sensors need to be installed in the cables, which is too cumbersome and impractical. This invention uses a non-contact image measurement method to measure cable force through modal analysis, which can effectively solve this problem. This technology has advantages such as non-contact, no equipment loss, full-field measurement, high economy, and low equipment threshold.

[0040] (3) Based on the advantages of the image method, the number of image points selected in this invention can be far greater than the number of points used to extract the mode amplitude and calculate the cable force. This can fit the real mode curve as much as possible and avoid the problem that when a single or a few sensors fail or when fewer measurement points are selected, the deviation of a few measurement points is large, resulting in a large deviation of the mode curve and thus inaccurate cable force measurement.

[0041] (4) This invention uses multi-mode vibration to treat bending stiffness as an implicit calculation parameter, which not only accurately considers its influence, but also avoids the problem that it is difficult to identify in actual engineering. Attached Figure Description

[0042] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments will be briefly described below. Obviously, the drawings described below only relate to some embodiments of the present invention and are not intended to limit the present invention.

[0043] Figure 1 This is a schematic flowchart of the method of the present invention;

[0044] Figure 2 Schematic diagram of cable measuring point calibration;

[0045] Figure 3 This is a diagram showing the calculation of the cable diameter based on straight line detection.

[0046] Figure 4 Flowchart for calculating dynamic displacement using the center-of-mass method;

[0047] Figure 5 This is a field test diagram from an embodiment;

[0048] Figure 6 The above are the mode shapes obtained from modal analysis in the examples.

[0049] Figure 7 The cable force diagram calculated in the example;

[0050] Figure 8 This is a comparison chart of acceleration results and optical measurement results in the example. Detailed Implementation

[0051] like Figure 1-8 As shown:

[0052] This invention proposes a cable force optical measurement method based on multi-mode shape fitting, comprising the following steps:

[0053] (1) Image acquisition: The camera is set up on the bridge deck or at the measuring point under the bridge. The camera lens is adjusted to focus on the target cable position to capture the motion image sequence of the cable under environmental vibration or human excitation. The data acquisition system acquires the motion images of the cable and saves the acquired image sequence file.

[0054] (2) Multi-point positioning and calibration: Based on the line detection algorithm, the image boundary of the cable is extracted. Using a concept similar to crack width calculation, the number of pixels occupied by the cable diameter is calculated, and combined with the actual diameter value, the measurement points are calibrated. For example... Figure 2 As shown, taking point S1 as an example, the actual cable diameter Q (mm) is first extracted by binarization or straight line detection methods to obtain the cable profile. Then, the pixel diameter q (pixel) corresponding to the S1 node position is calculated. Therefore, the magnification factor of point S1 is s1 = Q / q (mm / pixel). This invention defines the cable width as the distance between two points where the perpendicular line from the cable axis intersects the cable edge line. In orthogonal photography, the two edge lines of a cable are parallel, so the cable pixel width can be directly solved by the distance from the detected straight line equation. In oblique photography, after obtaining the cable's central axis and edges, three consecutive points on the central axis are used to determine the local perpendicular line of the central axis. Figure 3 The diagram illustrates how to determine the crack width at pixel A on the central axis. First, find the two connected pixels Q and P above and below pixel A. Approximately, the line connecting Q and P is considered the tangent to the axis at pixel A; therefore, the perpendicular line from QP represents the crack width. After obtaining the perpendicular line from QP, calculate the distance between its two intersection points with the edge; this distance represents the crack width at pixel A.

[0055] (3) Multi-point displacement extraction: The gray-scale weighted centroid method based on adaptive threshold is adopted to select the interest calculation area near the measurement point, calculate the displacement response of the area, and finally extract the displacement response data of multiple measurement points.

[0056] like Figure 4 As shown, the Otsu method, an adaptive threshold determination method, is first used to obtain the image threshold, and the image is binarized. Then, the gray-scale weighted centroid method is used for centroid localization. If the industrial camera sensor size is m×n pixels, the centroid calculation formula is (1), where I ij It is the grayscale value of the pixel in the i-th row (i corresponds to y) and j-th column (j corresponds to x) of the image.

[0057]

[0058] Although the camera field of view in actual bridge applications contains a series of point light sources, these point light sources exhibit significant vibration and translation almost exclusively in a single direction (perpendicular to the cable length), with a relatively small range of movement. Furthermore, the light spots are evenly spaced, with intervals much larger than their own size. Therefore, considering the specific circumstances of actual cable engineering applications, this problem is addressed by delineating multiple regions of interest (ROIs) containing complete light spots in the initial frame image and defining the search range. For the X and Y directions of the image, two search range parameters, a and b, are set for the ROIs. a and b can be set to 10 times the pixel size occupied by the target itself.

[0059] Considering the interference caused by stray light spots such as car lights and landscape lights suddenly entering the ROI, this study adopts a dual interference spot elimination method. First, new light spots exceeding ±5% of the area of ​​point light source A in the previous frame are deleted, along with point light sources C and D. If point light source B with a similar area still exists in the ROI, it is considered to eliminate it by minimizing the object distance. Generally, the vibration amplitude of point light sources on the cable is small. By calculating the Euclidean distance between the centroids of point light sources A' and B in the ROI and the centroid of point light source A in the previous frame, the point light source with the smallest distance is selected as the tracking object for this frame, and the remaining light spots are deleted.

[0060] Calibration is performed using the actual diameter Q (mm) of the tracking target. Taking point S1 as an example, the target contour is first extracted using the Hough transform detection method, and then the pixel diameter q (pixel) corresponding to the S1 node position is calculated. This yields the magnification factor for point S1.

[0061] (4) Modal parameter identification: Based on actual vibration response data, the frequency and corresponding mode shape curve of each order of the cable are obtained by using the CMIF method of modal parameter identification, and the mode shape amplitudes φ1, φ2, φ3, etc. at multiple test points are extracted in an orderly and uniform manner from the mode shape curve.

[0062] This invention employs the CMIF method, short for Complex Mode Indication Function, a modal parameter identification algorithm in the frequency domain. The CMIF method was initially used to perform singular value decomposition on the acquired frequency response function matrix. Singular value curves were plotted to determine the modal order of the system, and the peak values ​​of the singular value curves were used to determine the system's natural frequencies. Through repeated practice, this method has proven to have excellent identification performance for dense modes, and has gradually developed into a mature modal parameter identification algorithm. This invention first performs cross-correlation calculations and Fourier transforms on the measured multi-point displacements of the optical camera to obtain the scale-free frequency response function. Then, singular value decomposition is performed, and the modal order and peak frequency are determined using the singular value curves. Finally, the displacement mode shape is extracted from the left singular vector.

[0063] (5) Identification of dimensionless parameters of mode shapes and calculation of cable forces: Based on the obtained positions of each measuring point and the corresponding mode shape amplitudes, least squares nonlinear fitting (NLSF) is performed on the measured mode shape function curves of multiple orders to identify the dimensionless parameters of the mode shapes. Based on the identified dimensionless parameters of each mode shape, and combined with each order frequency and the mass per unit length m, the cable force is solved simultaneously to eliminate the influence of the bending stiffness value.

[0064] The specific calculation steps are as follows:

[0065] Assuming the bending stiffness of the member is EI and the mass per unit length is m, the equation of free vibration of the member structure under environmental vibration is:

[0066]

[0067] Where u(x,t) is the lateral displacement response at position x at time t.

[0068] Assume the solution to this equation has the form:

[0069]

[0070] Substituting (3) into (2) and separating the variables, we get:

[0071]

[0072] The left side of the above equation is only a function of x, and the right side is only a function of t. Therefore, the equation holds only for any x and t when both sides are constants. Let the constant be a. 4 This leads to two independent ordinary differential equations:

[0073]

[0074] in,

[0075] Let the solution to (5) be... Substituting (5) into the equation, we get:

[0076] (k 4 -g 2 k 2 -a 4 Ce kx =0 (7)

[0077] Solving for k 1,2 =±iδ,k 3,4 =±ε

[0078] in:

[0079] The general solution of (5) is derived as follows:

[0080]

[0081] Obviously, a 2 =δ×ε,ε 2 -δ 2 =g 2 .

[0082] Modal analysis yielded the mode amplitudes φ1 to φ5 at five test points, and the modal displacements of any two points (e.g., points i and j) in a certain mode were obtained as follows:

[0083]

[0084] Further conversion yields:

[0085] (sin(δx i )-λ ij sin(δx j ))c1+(cos(δx i )-λ ij cos(δx j ))c2+(sinh(εx i )-λ ij sinh(εx j ))c3+(cosh(εx i )-λ ij cosh(εx j c4 = 0

[0086] The sensors located at positions i and j are called the ordinary point and the reference point, respectively. Having determined the reference point, four independent ratios can be obtained from the five measurement points, allowing the construction of a system of characteristic equations:

[0087] S 4×4 [c1 c2 c3 c4] T =0 (10)

[0088] In this formula, c1 to c4 must have non-zero solutions, therefore the determinant of the characteristic matrix S is equal to 0, that is:

[0089] |S|=0 (11)

[0090] The equation has two unknowns, δ and ε. It is easy to see that ε can be expressed by δ, making δ the only variable. Substituting this into the equation |S|=0, we can solve for δ. Therefore, we can further derive the expression for the cable force containing the unknown δ:

[0091]

[0092] However, solving for δ using only five points of response data has significant drawbacks. An error at even one measurement point can cause the entire mode shape identification to fail. Furthermore, the actual bending stiffness EI is difficult to determine, with a huge range of values. Therefore, the method proposed in this invention, after identifying the CMIF mode shape, performs least-squares nonlinear fitting on the multi-order measured mode shape function curves based on the obtained locations of multiple measurement points and corresponding mode shape amplitudes to identify the parameter value δ. Then, it uses the multi-order mode shape identification δ results to solve a system of equations to eliminate the influence of bending stiffness, thereby obtaining the cable force value.

[0093] After identifying n orders, the force at any i-th order can be obtained:

[0094]

[0095] get:

[0096]

[0097] Among them, f i f j Let be the i-th and j-th order frequencies of the Lasso.

[0098] Meanwhile, this invention also discloses a cable force optical measurement system based on multi-mode shape fitting. The system comprises an image acquisition system, a positioning and calibration system, an image-based displacement calculation system, and a cable force solution system. The image acquisition system is used to acquire motion image sequences of bridge cables under environmental vibration or human excitation. The positioning and calibration system includes two parts: calculating the pixel coordinates of the measuring points based on a straight line detection algorithm and calculating the magnification factor of the measuring points based on the mathematical expression of the two boundary straight lines of the cable. The displacement calculation system is used to import images, select the calculation area, perform displacement response calculation, and finally convert the actual displacement based on the magnification factor of the measuring points. The cable force solution system, based on the actual displacement response data, obtains the frequencies and corresponding mode shape curves of each order of the cable through modal analysis, and performs least-squares nonlinear fitting (NLSF) on the measured mode shape function curves of each order to identify the dimensionless parameters of the mode shape, thereby solving the cable force by combining the mass per unit length and the frequencies of each order.

[0099] Example 1:

[0100] The following case study uses actual bridge cable images to measure cable force to illustrate the implementation steps of the proposed optical measurement method for cable force based on multi-mode shape fitting. The Zhongshan Bridge in Wuhu City uses an arch-beam composite steel structure with secondary chords, with a span arrangement of (28+90+28)m. Each arch rib has 13 factory-made hangers, spaced 6m apart. The hanger cables consist of 12 strands of 15.2mm epoxy-coated unbonded steel strands (1860MPa) wrapped with PE extrusion, and the nominal breaking strength is 3125kN. The hangers are connected to the tie beam at both ends using fork lugs and arch ribs (effectively solving the fatigue problem of short hangers). Other original experimental data are as follows: Eighteen test points S1 to S18 are calculated along the length of the rod being tested, with each test point spaced 0.66 meters apart.

[0101] The cable-mounted image was captured using a Hikvision MV-CA050-20UM industrial camera with a resolution of 2592 pixels × 2048 pixels, a pixel size of 4.8 micrometers, a maximum frame rate of 71.8 fps, and an industrial lens with a focal length of 25mm. The on-site test setup is as follows: Figure 5 As shown, the first three vibration modes obtained are as follows: Figure 6 As shown, the calculated cable force is as follows Figure 7 As shown, the acceleration results are compared with the optical measurement results. Figure 8 As shown.

[0102] In summary, this invention is dedicated to the application of long-span bridges, relying entirely on image information for the positioning and calibration of cable targets. Unlike traditional accelerometers and existing image methods, it eliminates the need for manually setting special targets on the structure before testing to locate and calibrate measurement points, achieving truly non-contact measurement. Furthermore, this invention successfully avoids the challenge of establishing an analytical model for cables with complex end boundaries to solve the relationship between cable force and frequency. Starting from the perspective of mode shape functions, it uses known response data from multiple measurement points to identify mode shapes, enabling the measurement of cable forces with complex unknown boundaries. Further, this invention is committed to the widespread application in real bridges. Utilizing the advantages of non-contact full-field optical measurement, it can easily extract the vibration response of multiple points across the entire cable field. Installation is also extremely convenient, resulting in stronger engineering applicability, and the results meet engineering accuracy requirements. Based on the superiority of optical image measurement methods, this invention can perform displacement tracking measurements on far more than five measurement points. This allows for a closer fit to the true mode shape curve, avoiding the problem of inaccurate cable force measurement caused by large deviations in mode shape curves due to sensor malfunctions or a limited number of measurement points in traditional methods. This invention can more effectively assess and maintain bridges, improve bridge inspection efficiency, and is a promising new method for cable force measurement.

[0103] Example 2:

[0104] The computer-readable storage medium of this embodiment stores a computer program that, when executed by a processor, implements the steps in the cable force optical measurement method based on multi-mode shape fitting of Embodiment 1.

[0105] The computer-readable storage medium in this embodiment can be an internal storage unit of the terminal, such as the terminal's hard disk or memory; the computer-readable storage medium in this embodiment can also be an external storage device of the terminal, such as a plug-in hard disk, smart memory card, secure digital card, flash memory card, etc. equipped on the terminal; furthermore, the computer-readable storage medium can include both the terminal's internal storage unit and external storage devices.

[0106] The computer-readable storage medium of this embodiment is used to store computer programs and other programs and data required by the terminal. The computer-readable storage medium can also be used to temporarily store data that has been output or will be output.

[0107] Example 3:

[0108] The computer device of this embodiment includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the cable force optical measurement method based on multi-mode shape fitting of Embodiment 1.

[0109] In this embodiment, the processor can be a central processing unit, or other general-purpose processors, digital signal processors, application-specific integrated circuits, off-the-shelf programmable gate arrays or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc. The memory can include read-only memory and random access memory, and provides instructions and data to the processor. A portion of the memory can also include non-volatile random access memory. For example, the memory can also store device type information.

[0110] Those skilled in the art will understand that the content disclosed in the embodiments can be provided as a method, system, or computer program product. Therefore, this solution can take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this solution can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage) containing computer-usable program code.

[0111] This solution is described with reference to flowchart illustrations and / or block diagrams of methods and computer program products according to embodiments of this solution. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing device, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0112] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0113] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0114] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0115] The examples described herein are merely preferred embodiments of the invention and are not intended to limit the concept and scope of the invention. Any modifications and improvements made by those skilled in the art to the technical solutions of the invention without departing from the design concept of the invention should fall within the protection scope of the invention.

Claims

1. A cable force optical measurement method based on multi-mode shape fitting, characterized in that, The steps are as follows: S1. Image Acquisition: Set up the camera on the bridge deck or at the measuring point under the bridge, adjust the camera lens to focus on the target cable, and then capture and save the sequence of motion images of the cable under environmental vibration or human excitation. S2. Multi-point localization and calibration: Based on the line detection algorithm, the image boundary of the cable is extracted. Using the mathematical expression of the two boundary lines of the cable, the number of pixels occupied by the cable width near the measurement point is obtained. According to the formula... s=Q / qi(1) Calculate the magnification factor for each measuring point, where s is the magnification factor for converting the image pixel displacement to the actual displacement, Q is the actual value of the cable diameter, and qi is the pixel diameter corresponding to the position of the i-th measuring point. S3. Multi-point displacement extraction: The gray-scale weighted centroid method based on adaptive threshold is adopted to select the region of interest near the measuring point, calculate the displacement response of the region, and finally extract the displacement response data of multiple measuring points. Based on the amplification coefficient of each measuring point in S2, the pixel displacement response data of each measuring point is converted into actual displacement. S4. Modal parameter identification: Based on actual vibration response data, the frequencies and corresponding mode shape curves of each order of the cable are obtained through the CMIF modal parameter identification method, and the mode shape amplitudes at multiple test points are extracted in an orderly and uniform manner from the mode shape curves. S5. Identification of dimensionless parameters of mode shape and calculation of cable force: Based on the obtained positions of each measuring point and the corresponding mode shape amplitude, the least squares nonlinear fitting (NLSF) is performed on the measured mode shape function curves of multiple orders to identify the dimensionless parameters of the mode shape; based on the identified dimensionless parameters of each mode shape, and combined with each order frequency and the mass per unit length m, the cable force is solved simultaneously to eliminate the influence of the bending stiffness value.

2. The method according to claim 1, characterized in that, In step S2, image information is used to locate and calibrate each measuring point.

3. The method according to claim 1, characterized in that, The gray-scale weighted centroid method in S3 directly tracks the existing features of the cable-stayed surface landscape light target.

4. The method according to claim 1, characterized in that, In step S5, the mode amplitude values ​​at multiple test points are extracted in an orderly and uniform manner from the mode curve, and at least six test points are selected to fit the real mode curve.

5. The method according to claim 1, characterized in that, The steps for identifying the dimensionless parameters of the vibration modes and calculating the cable forces in S5 and S6 are as follows: S51. Assuming the bending stiffness of the cable is EI, the mass per unit length is m, and the tension is T, the equation of free vibration of the bar structure under environmental vibration is: （2） in, The lateral displacement response at position x at time t; S52. Further derivation yields the mode shape function of the cable structure as follows: （3） in: ; Four constants c1 to c4 determine the vibration shape, where a is a constant. For cable tension related parameters, Obviously, , ; S53. Based on obtaining the mode shape amplitudes at multiple measurement points using the CMIF method, the least squares nonlinear fitting method is performed on the measured mode shape function curves of each order to identify the dimensionless parameter values ​​of each order. ; S54, any number The magnitude of the cable force can be obtained as follows: After identifying the nth mode, the dimensionless parameters of each mode shape are used. The simultaneous equations eliminated the influence of bending stiffness, thus yielding the cable force: （4） in, , For Lasso and the First frequency.

6. A cable force optical measurement system based on multi-mode shape fitting, characterized in that, The system includes an image acquisition system, a positioning and calibration system, an image-based displacement calculation system, and a cable force solution system; The image acquisition system is used to acquire motion image sequences of bridge cables under environmental vibration or human excitation; The positioning and calibration system includes two parts: calculating the pixel coordinates of the measurement point based on a straight line detection algorithm and calculating the magnification factor of the measurement point based on the mathematical expression of the two boundary lines of the cable. The image-based displacement calculation system is used to import images, select calculation areas, perform displacement response calculations, and finally convert the displacement into actual displacement based on the magnification factor of the measuring points. The cable force calculation system, based on actual displacement response data, obtains the frequencies and corresponding mode shape curves of each order of the cable through modal analysis, and performs least-squares nonlinear fitting on the measured mode shape function curves of each order to identify the dimensionless parameters of the mode shape, thereby solving the cable force by combining the mass per unit length and the frequencies of each order.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by the processor, it implements the steps in the cable force optical measurement method based on multi-mode shape fitting as described in any one of claims 1 to 5.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the cable force optical measurement method based on multi-mode shape fitting as described in any one of claims 1 to 5.

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