Stay cable force identification method based on frequency multiplication relation global optimization

Abstract

The invention provides a stay cable force recognition method based on frequency multiplication relation global optimization, and the method comprises the steps: recognizing a plurality of candidate frequencies through spectrum analysis based on stay cable vibration acceleration data collected in real time; the candidate frequency set is input into a fundamental frequency solving model, the sum of squares of frequency multiplication rounding deviation of each frequency and an approximate fundamental frequency is minimized through an optimization algorithm, and the approximate fundamental frequency is an optimization parameter for global search of the optimization algorithm; and determining a final fundamental frequency according to the solved approximate fundamental frequency, and outputting the cable force.

Description

Technical Field

[0001] The present invention belongs to the technical field of bridge structure health monitoring, and in particular relates to a method for identifying cable forces based on global optimization of frequency doubling relationships. Background Art

[0002] As the core load-bearing component of a cable-stayed bridge, the cable tension state is directly related to the safety and durability of the bridge's overall structure. Therefore, efficient and accurate monitoring of cable tension is a key research area in bridge health monitoring. Currently, cable tension identification methods based on vibration signals have become the most widely used technology in engineering practice due to their ease of use and cost-effectiveness.

[0003] The core logic of this method is to collect cable vibration signals through sensors, extract the vibration frequency through spectral analysis, and then calculate the cable force based on theoretical relationships between frequency and cable force (such as string vibration theory or axially loaded beam theory). Accurately identifying the vibration frequency and determining the vibration modal order of the identified frequency are two key steps that affect the accuracy of cable force calculation.

[0004] Traditional methods for vibration frequency identification rely on simple peak detection algorithms such as threshold and differential methods. However, the spectrum of cable vibrations in real-world projects often exhibits periodic or quasi-periodic characteristics (i.e., multiple frequencies are distributed as integer multiples). Traditional peak detection algorithms fail to exploit this characteristic, leading to missed detection of valid peaks and insufficient reliability of the identified candidate frequency set.

[0005] When determining the fundamental frequency, accelerometers are typically placed at the ends of cables for ease of installation and maintenance. The displacement of the first-order vibration mode of the cable approaches zero at the ends, resulting in a weak first-order frequency signal amplitude that is difficult to directly obtain through spectrum analysis. Existing methods often manually determine the fundamental frequency of the cable by screening for frequencies with higher amplitudes in the spectrum. However, manually determining the fundamental frequency of the cable is time-consuming and labor-intensive for online cable tension monitoring, and can easily lead to misjudgment of the fundamental frequency. It also fails to meet the demand for real-time cable tension monitoring and affects the accuracy of cable tension calculations.

[0006] In summary, the existing vibration-based cable force identification technology still has limitations in the accuracy of cable vibration frequency identification and the automation level of determining the modal order of the identified frequency, making it difficult to meet the "real-time" and "unmanned intervention" requirements of long-term online monitoring of bridges. Summary of the Invention

[0007] In view of the defects in the existing technology that the peak recognition of cable vibration spectrum is insufficiently adaptable to periodic / quasi-periodic characteristics, the fundamental frequency determination relies on manual intervention and is prone to misjudgment, the present invention provides a cable force identification method based on global optimization of the frequency doubling relationship.

[0008] This method achieves a technological breakthrough through the following core innovative designs: First, online data segmentation technology (such as sliding window technology) is used to dynamically segment the real-time collected cable vibration acceleration data to ensure real-time data processing; second, spectrum analysis (such as power spectrum density analysis) is performed on the segmented data, and the automatic multi-scale peak detection (AMPD) algorithm is combined to identify the effective peak points in the spectrum, solving the problem that the traditional peak detection algorithm has poor adaptability to periodic / quasi-periodic spectra; third, by setting quantiles based on the amplitude of the identified peak point, low-amplitude interference frequencies are eliminated, and high-amplitude candidate frequencies that are well excited are retained; then, based on the "frequency doubling" law of the cable vibration frequency, an objective function is set and a particle swarm optimization (PSO) algorithm is used to automatically solve the approximate fundamental frequency. Finally, the final fundamental frequency of the cable is determined based on the approximate fundamental frequency, avoiding the risk of misjudgment caused by manual determination of the cable fundamental frequency;

[0009] The core advantage of this invention is that no human intervention is required throughout the entire process, and fully automatic online operation is achieved from data acquisition, spectrum analysis, peak identification to fundamental frequency solution. This not only improves the real-time performance of cable force identification, but also significantly improves the reliability of frequency identification and the accuracy of fundamental frequency determination through the coordinated application of AMPD and PSO algorithms, providing efficient and stable technical support for the long-term health monitoring of cable-stayed bridges.

[0010] The technical solution specifically adopted by the present invention to solve the technical problem is:

[0011] A method for identifying cable forces based on global optimization of the frequency-doubling relationship:

[0012] Based on the real-time collected vibration acceleration data of the inclined cable, multiple candidate frequencies are identified through spectrum analysis;

[0013] The candidate frequency set is input into the fundamental frequency solution model, and the sum of squared deviations between each frequency and the approximate fundamental frequency is minimized by an optimization algorithm, where the approximate fundamental frequency is the optimization parameter of the global search of the optimization algorithm;

[0014] Based on the solved approximate fundamental frequency, the final fundamental frequency is determined and the cable force is output.

[0015] Furthermore, the formula for calculating the sum of squares of the frequency doubling and rounding deviations is:

[0016]

[0017] in is the candidate frequency, corresponding to the identified The vibration frequency of the cable, is the approximate fundamental frequency, which is used as the optimization parameter in the optimization algorithm. m is the number of candidate frequencies, corresponding to the total number of cables identified. This is a rounding operation.

[0018] Furthermore, the optimization algorithm is a particle swarm optimization algorithm.

[0019] Furthermore, the spectrum analysis includes:

[0020] Split the time domain signal by sliding the window, and the window step size is smaller than the window length;

[0021] The power spectral density algorithm is used to generate the vibration spectrum, and quantile filtering is used to retain candidate frequencies with peak amplitudes higher than a set threshold.

[0022] Furthermore, the candidate frequency identification method includes:

[0023] Construct a local maximum scale map matrix, the matrix element values ​​satisfy:

[0024] When the amplitude of a certain position is greater than the amplitudes of its k adjacent positions on the left and right, it is marked as 0;

[0025] Otherwise, it is marked with a random number between 1 and 2;

[0026] Candidate frequencies are determined based on the columns of the matrix with zero standard deviation.

[0027] Furthermore, the final fundamental frequency is calculated by dividing each candidate frequency by an integer multiple of the approximate fundamental frequency corresponding to the candidate frequency, and calculating the arithmetic average of all quotients:

[0028]

[0029] The calculation of the cable force satisfies the following relationship:

[0030] Cable force = 4 × unit mass × cable length 2 × Final fundamental frequency 2 -π 2 × elastic modulus × section moment of inertia / cable length 2 .

[0031] Among them, unit mass, cable length, elastic modulus, and section moment of inertia are all inherent properties of the inclined cable.

[0032] Furthermore, the method for reducing the number of rows of the scalogram matrix includes: calculating the sum of elements in each row, and taking the number of rows corresponding to the minimum sum as the effective analysis scale.

[0033] And, a cable force identification system based on global optimization of the frequency doubling relationship, comprising:

[0034] A data acquisition module configured to acquire vibration acceleration data of the inclined cable in real time;

[0035] a spectrum analysis module configured to perform spectrum analysis and output a set of candidate frequencies;

[0036] An approximate fundamental frequency optimization solution module is configured to minimize the sum of squared deviations of the rounded-off frequencies through an optimization algorithm and use the approximate fundamental frequency as a global search parameter; the final fundamental frequency of the cable is determined based on the approximate fundamental frequency;

[0037] a cable force calculation module configured to calculate a cable force value according to a final fundamental frequency;

[0038] The output interface is configured to transmit the cable force value to the monitoring platform.

[0039] And, a computer device includes a memory, a processor and a computer program stored in the memory, and the processor implements the above method when executing the computer program.

[0040] A non-transitory computer-readable storage medium stores a computer program, which implements the method described above when executed by a processor.

[0041] Compared with the prior art, the present invention and its preferred embodiments have at least the following beneficial effects:

[0042] 1. Breakthrough solution to the bottleneck of fundamental frequency identification

[0043] Through the global optimization mechanism of the frequency doubling relationship, we completely get rid of the traditional method's reliance on manual determination of the fundamental frequency, overcome the industry's difficult problem that the acceleration sensor cannot effectively measure the fundamental frequency of the cable due to its arrangement at the end of the cable, and significantly improve the reliability of cable fundamental frequency identification under complex working conditions.

[0044] 2. Anti-interference ability is significantly enhanced

[0045] The AMPD algorithm is suitable for peak identification of periodic / quasi-periodic vibration spectra of cables, significantly reducing the misidentification rate of cable vibration frequencies and providing a high-confidence data basis for subsequent cable force calculations.

[0046] 3. Full process automation

[0047] A closed-loop processing chain is formed from real-time collection of vibration signals, spectrum analysis to cable force output, without any human intervention, meeting the real-time requirements of long-term online monitoring of cable-stayed bridges and significantly reducing operation and maintenance costs.

[0048] 4. Edge computing friendliness

[0049] The low computational complexity design of the optimization algorithm and signal processing module supports efficient operation in resource-constrained embedded devices, providing technical feasibility for on-site deployment on bridges. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments:

[0051] Figure 1 This is a flowchart for implementing an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to make the features and advantages of the present invention more clearly understood, the following embodiments are given for detailed description:

[0053] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in this specification have the same meanings as those commonly understood by those skilled in the art to which this application belongs.

[0054] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0055] The process of the embodiment of the present invention is as follows Figure 1 As shown in the figure, a sliding window technique is used to segment the cable's vibration acceleration online. Then, a power spectral density (PSD) analysis is performed on each sliding window data to obtain the cable's vibration spectrum. The automatic multiscale peak detection (AMPD) algorithm is used to identify candidate frequencies. The particle swarm optimization (PSO) algorithm is then used to solve the objective function to determine the approximate fundamental frequency of the cable. The final fundamental frequency of the cable is then calculated based on the approximate fundamental frequency. Finally, the final fundamental frequency of the cable is imported into the cable vibration formula to obtain the cable force. The specific implementation process is as follows:

[0056] S1: Online collection of vibration acceleration data of the cable-stayed cable, and online segmentation of the collected data using sliding. Specifically, when the amount of newly collected acceleration data reaches the length of a sliding window, the sliding window slides forward one step. The sliding step can be the length of a sliding window or smaller. Subsequently, the data in each sliding window will be used for the next step of analysis.

[0057] S2: Perform power spectral density (PSD) analysis on the data in the sliding window to obtain the vibration spectrum of the cable, and use the automatic multi-scale peak detection (AMPD) algorithm to identify it. The main principles involved in this process are as follows:

[0058] Assume that the PSD analysis result is a one-dimensional array , For the array length, AMPD first creates a ( , represents the rounding-up operation) of the local maximum scale map matrix:

[0059] (1)

[0060] in:

[0061] (2)

[0062] Where, is the signal analysis scale, , For A uniformly distributed random number.

[0063] Pair Matrix Sum each row of , and return the row number corresponding to the smallest sum , delete the number of rows after entering, Matrix of size Reduced size to Matrix .calculate The standard deviation of each column in the matrix is ​​returned. The index of all columns with zero standard deviation is returned. These column indices are the locations of the peaks.

[0064] S3: The peak point of the PSD analysis result is the possible vibration modal frequency of the cable. In order to select the well-excited modal frequency, the cable vibration frequency with the largest peak value is selected by the quantile of the peak amplitude. .

[0065] S4: According to the law that the vibration frequency of the cable is "multiple frequency", determine the approximate vibration fundamental frequency of the cable , the process is achieved by setting the objective function and using the particle swarm optimization (PSO) algorithm to solve the minimum value of the objective function. When the PSO algorithm solves the objective function, As the optimization parameter. Specifically, the objective function is set as:

[0066] (3)

[0067] Where, To identify the The vibration frequency of the cable, is the total number of identified cables, This is a rounding operation.

[0068] S5: The final fundamental frequency of the cable is determined as follows:

[0069] (4)

[0070] S6: Finally, the fundamental frequency of the cable Substituting this into the beam theory formula for the axial load of the cable, we can obtain the cable force:

[0071] (5)

[0072] Where, is the axial length of the cable, , , are the mass per unit length, elastic modulus and section moment of inertia of the cable respectively.

[0073] The solution provided in the above embodiment can be implemented through MATALB or other programming languages ​​such as PYTHON: first, the programming of the AMPD, PSO and PSD algorithms designed in the present invention should be implemented, and then the vibration monitoring data of the cable should be connected, and the sliding window length, quantile and optimization boundary of the PSO algorithm in the present invention should be set. Finally, the program can be run to realize online fully automatic cable force identification.

[0074] The above solution can realize online cable force identification and fully automatic cable force identification without any human intervention.

[0075] Based on the same inventive concept, the present invention also provides a computer device, which includes: one or more processors and a memory for storing one or more computer programs; the program includes program instructions, and the processor is used to execute the program instructions stored in the memory. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is used to implement one or more instructions, specifically for loading and executing one or more instructions in a computer storage medium to implement the above method.

[0076] It should be further explained that, based on the same inventive concept, the present invention also provides a computer storage medium having a computer program stored thereon, which, when executed by a processor, performs the above-described method. The storage medium may be any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0077] It should be noted that, unless otherwise defined, the technical or scientific terms used in the present invention should have the usual meanings understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0078] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any other manner. Any person skilled in the art may utilize the above-disclosed technical content to modify or modify the present invention into equivalent embodiments. However, any simple modifications, equivalent variations, and modifications to the above embodiments that do not depart from the technical content of the present invention and are based on the technical essence of the present invention remain within the scope of protection of the present invention.

[0079] The present invention is not limited to the above-mentioned optimal implementation mode. Anyone can derive various other forms of cable force identification methods based on global optimization of the frequency doubling relationship under the inspiration of the present invention. All equal changes and modifications made according to the scope of the patent application of the present invention should fall within the scope of the present invention.

Claims

1. A method for identifying cable forces based on global optimization of frequency doubling relationships, characterized by: Based on the real-time collected vibration acceleration data of the inclined cable, multiple candidate frequencies are identified through spectrum analysis; The candidate frequency set is input into the fundamental frequency solution model, and the sum of squared deviations between each frequency and the approximate fundamental frequency is minimized by an optimization algorithm, where the approximate fundamental frequency is the optimization parameter of the global search of the optimization algorithm; Based on the solved approximate fundamental frequency, the final fundamental frequency is determined and the cable force is output.

2. The method for identifying cable forces based on global optimization of frequency doubling relationships according to claim 1 is characterized in that: The calculation formula of the sum of squares of the frequency doubling rounding deviation is: in is the candidate frequency, corresponding to the identified The vibration frequency of the cable, is the approximate fundamental frequency, which is used as the optimization parameter in the optimization algorithm. m is the number of candidate frequencies, corresponding to the total number of cables identified. This is a rounding operation.

3. The method for identifying cable forces based on global optimization of frequency doubling relationships according to claim 1 is characterized in that: The optimization algorithm is a particle swarm optimization algorithm.

4. The method for identifying cable forces based on global optimization of frequency doubling relationships according to claim 1 is characterized in that: The spectrum analysis includes: Split the time domain signal by sliding the window, and the window step size is smaller than the window length; The power spectral density algorithm is used to generate the vibration spectrum, and the quantile is used to set the amplitude threshold. The candidate frequencies with amplitudes higher than the set threshold are filtered and retained.

5. The method for identifying cable forces based on global optimization of frequency doubling relationships according to claim 1 is characterized in that: The candidate frequency identification method includes: Construct a local maximum scale map matrix, the matrix element values ​​satisfy: When the amplitude of a certain position is greater than the amplitudes of its k adjacent positions on the left and right, it is marked as 0; Otherwise, it is marked with a random number between 1 and 2; Candidate frequencies are determined based on the columns of the matrix with zero standard deviation.

6. The method for identifying cable forces based on global optimization of frequency doubling relationships according to claim 2 is characterized in that: The final fundamental frequency is calculated by dividing each candidate frequency by the integer multiple of the approximate fundamental frequency corresponding to that frequency, and taking the arithmetic average of all quotients: The calculation of the cable force satisfies the following relationship: Cable force = 4 × unit mass × cable length 2 × Final fundamental frequency 2 -π 2 × elastic modulus × section moment of inertia / cable length 2 .

7. The method for identifying cable forces based on global optimization of frequency doubling relationships according to claim 5 is characterized in that: The method for reducing the number of rows of the scalogram matrix includes: calculating the sum of elements in each row, and taking the number of rows corresponding to the minimum sum as the effective analysis scale.

8. A cable force identification system based on global optimization of frequency doubling relationship, characterized in that: include: A data acquisition module configured to acquire vibration acceleration data of the inclined cable in real time; a spectrum analysis module configured to perform spectrum analysis and output a set of candidate frequencies; An approximate fundamental frequency optimization solution module is configured to minimize the sum of squared deviations of the rounded-off frequencies through an optimization algorithm and use the approximate fundamental frequency as a global search parameter; the final fundamental frequency of the cable is determined based on the approximate fundamental frequency; a cable force calculation module configured to calculate a cable force value according to a final fundamental frequency; The output interface is configured to transmit the cable force value to the monitoring platform.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory, wherein the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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