Method and device for boundary coordination of real-time hybrid test of maglev train running on bridge

Abstract

The application discloses a kind of magnetic levitation train bridge on the running real-time hybrid test boundary coordination method, equipment, wherein the method comprises: obtaining the displacement response of each numerical control point under the action of current time step magnetic levitation train bridge each degree of freedom;Obtain track irregularity at each numerical control point;Bridge displacement response at each numerical control point and track irregularity at corresponding position are superposed;In two cases of superposition track irregularity and not superposition track irregularity, the displacement response at all numerical control points is respectively linearly fitted, and the displacement response of each physical control point is obtained and vibration test bench control command is generated;Difference value operation is carried out to the displacement response of the track surface of the track surface and the actual displacement response calculated by the numerical substructure, to determine the error peak value;If error peak value does not exceed error limit value, control command is sent to vibration test bench.The application provides a kind of boundary coordination method for evaluating the bridge on the running safety of magnetic levitation train by using vibration test bench real-time hybrid test.

Description

Technical Field

[0001] This invention relates to the field of rail transit technology, and in particular to a method and equipment for real-time mixed test boundary coordination of maglev trains traveling on bridges. Background Technology

[0002] The vibration test bench for the entire vehicle running system (hereinafter referred to as the "vibration test bench") is mainly used for functional and performance tests of maglev vehicles, suspension guidance control, and track systems, reproducing the vehicle-control-track interaction process during actual operation. The vibration test bench can reproduce the seismic process in real time, as well as the track vibration under vehicle load, making it the most direct method for studying structural seismic response and failure mechanisms. Hybrid testing is a commonly used structural testing method in recent years. It divides the overall structure into multiple computational and numerical substructures. The accuracy of the boundary conditions between these substructures significantly affects the structural response of the numerical substructure under train loads. Since bridge deformation is curvature, the vibration test bench, as a rigid component, cannot directly apply the calculated continuous displacement curve of the bridge structure to the train. Therefore, the test bench needs to approximate the bridge structure's response in a certain way. Thus, researching a boundary coordination method for real-time hybrid testing on maglev train bridges to achieve displacement response signal conversion is of great significance. Summary of the Invention

[0003] To address the problems of the prior art, the present invention aims to provide a method and equipment for real-time hybrid test boundary coordination on a maglev train bridge, so as to realize the conversion of displacement response signals and approximately reproduce the response of the bridge structure through a vibration test bench.

[0004] Firstly, a method for boundary coordination in real-time hybrid testing of maglev trains traveling on bridges is provided, including:

[0005] S1: Obtain the displacement response of each degree of freedom of the bridge at each numerical control point under the action of the maglev train at the current time step, and use the interpolation algorithm to ensure consistency with each module in the real-time hybrid test at the time step;

[0006] S2: Use the power spectral density function to obtain and output the track irregularity samples at each numerical control point;

[0007] S3: The displacement response of the bridge at each numerical control point is superimposed with the track irregularity at the corresponding location;

[0008] S4: For two cases of superimposed track irregularity and non-superimposed track irregularity, multi-point linear fitting is performed on the displacement response at all numerical control points, and the displacement response of each physical control point is calculated and corresponding vibration test bench control commands are generated.

[0009] S5: Reproduce the displacement response of the track platform at the corresponding position based on the displacement response of each physical control point, and perform a difference calculation with the actual displacement response at the corresponding position calculated by the numerical substructure to determine the peak error.

[0010] S6: If the peak error does not exceed the error limit, the generated vibration test bench control command will be sent to the vibration test bench.

[0011] Furthermore, the displacement response of each degree of freedom in step S1 includes vertical translational displacement, horizontal translational displacement, pitch angular displacement, roll angular displacement, and yaw angular displacement.

[0012] Furthermore, the acquisition of the displacement response of the bridge at each numerical control point under the action of the current time-step maglev train includes:

[0013] Based on the train length, wheelset position, train speed and integral time step, bridge geometry and node unit information, and response displacement time history, the current time step maglev train position is calculated.

[0014] Obtain the displacement response of each degree of freedom of the bridge at each numerical control point corresponding to the current position of the maglev train.

[0015] Furthermore, in step S2, only samples with irregular wavelengths within the allowable error range are retained for track irregularity samples at each numerical control point.

[0016] Furthermore, the power spectral density function is determined by the statistical characteristics of the measured dynamic detection data of the maglev track.

[0017] Furthermore, in step S4, the method for performing multi-point linear fitting is the least squares algorithm, which converts the displacement response into vibration test bench control commands by replacing the deflection curve with piecewise straight lines.

[0018] Furthermore, step S5 specifically includes:

[0019] In both cases of superimposed and non-superimposed track irregularities, the displacement response at the corresponding position of the track platform is predicted based on the displacement response of each physical control point and the geometric pose relationship between the vibration test bench and the track. The difference between the predicted track platform displacement response and the calculated displacement response of the numerical substructure at the corresponding position is calculated to obtain the platform reproduction error distribution and determine the error peak value.

[0020] Furthermore, the error peak obtained in step S5 is reduced by optimizing the distribution of the error to the remaining physical control points by distance.

[0021] Secondly, an electronic device is provided, comprising:

[0022] A memory that stores computer programs;

[0023] A processor is used to load and execute the computer program to implement the steps of the boundary coordination method for real-time hybrid test on a maglev train bridge as described above.

[0024] Thirdly, a computer-readable storage medium is provided, which stores a computer program that, when executed by a processor, implements the steps of the boundary coordination method for real-time hybrid test on a maglev train bridge as described above.

[0025] This invention proposes a method and equipment for real-time hybrid test boundary coordination of maglev trains traveling on bridges, which has the following advantages:

[0026] (1) It can solve the problem that the vibration test bench cannot directly apply the continuous displacement curve calculated by the bridge structure to the train. It converts the deformation signal of the bridge into the running signal of the vibration test bench. It adopts the secant method of replacing the curve with a segmented straight line and uses the straight line to replace the curve to realize the response of the bridge structure in a certain way on the table, thus completing the conversion of the deformation signal.

[0027] (2) The boundary coordination method improves the algorithm by using multi-point linear fitting, which effectively reduces the size of the reproduction error. At the same time, the interpolation algorithm ensures consistency with other modules in time step and clarifies that the maximum reproduction error can meet the error requirements, minimizing the influence of adverse factors in the experiment and ensuring sufficient accuracy and reliability in the experiment. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 This is a flowchart of the boundary coordination method for real-time mixed test of maglev train running on a bridge provided in an embodiment of the present invention;

[0030] Figure 2 This is a flowchart of the real-time hybrid test system for maglev trains traveling on bridges provided in this embodiment of the invention;

[0031] Figure 3 This is a schematic diagram of the two-point fitting principle between the bridge and the vibration test bench provided in an embodiment of the present invention;

[0032] Figure 4 This is a schematic diagram of the linear interpolation algorithm provided in an embodiment of the present invention;

[0033] Figure 5 This is a schematic diagram illustrating the error distribution optimization based on distance provided in an embodiment of the present invention. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be described in detail below. Obviously, the described embodiments are merely some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other implementation methods obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0035] like Figure 1 , Figure 2 As shown, this embodiment of the invention provides a method for real-time hybrid test boundary coordination of a maglev train traveling on a bridge (corresponding to...). Figure 2 Boundary coordination algorithms (including those in the text) include:

[0036] S1: Obtain the displacement response of each degree of freedom of the bridge at each numerical control point under the action of the maglev train at the current time step, and use the interpolation algorithm to ensure consistency with other modules (loading device, physical substructure, numerical vibration table and control algorithm module, vibration table long stator displacement reproduction calculation module) in the real-time hybrid test at the time step.

[0037] Specifically, the current position of the maglev train needs to be determined first, and then the displacement response of each degree of freedom of the bridge at each numerical control point is obtained based on the position of the maglev train.

[0038] The system acquires the train length and wheelset position, train speed and integration time step, bridge geometry, node element information, and response displacement time history. It then integrates the current time step to determine the maglev train's position based on the train speed. Figure 3 Taking the vehicle model shown as an example, the numerical substructure uses a successive integration algorithm to obtain the displacement response of each degree of freedom of the bridge at the corresponding positions of the nine selected numerical control points. The displacement response of each degree of freedom of the bridge includes vertical translational displacement, horizontal translational displacement, pitch angular displacement, roll angular displacement, and yaw angular displacement, such as... Figure 4 As shown, the displacement responses of each degree of freedom of the bridge are obtained and input into the linear interpolation algorithm for linear interpolation. The bridge responses at two adjacent time steps are interpolated to obtain the bridge responses at sixteen equal time steps between the two time steps. The running time steps of other modules (loading device, physical substructure, numerical shaking table and control algorithm module, shaking table stator displacement reproduction calculation module) are consistent with the equal time steps obtained after interpolation, thereby ensuring consistency with other modules in terms of time steps, and the displacement responses in the three directions are extracted into the algorithm workspace.

[0039] S2: Use the power spectral density function to obtain and output the track irregularity samples at each numerical control point.

[0040] The various track irregularities on the line are formed by the superposition of random irregularities with different wavelengths, phases, and amplitudes, and are complex random functions related to the line mileage. Based on the statistical characteristics of the measured dynamic detection data of the maglev track, in this embodiment, the power spectral density function is obtained with reference to the German spectrum. After parameter correction based on the power spectral density function, the wavelengths and amplitudes of track irregularities at nine numerical control points are generated and output.

[0041] The power spectral density function is:

[0042]

[0043] In the formula, Ω is the spatial frequency, and A v Ω is the track roughness constant. r and Ω c These are relevant constants.

[0044] The magnitude and wavelength of track irregularities affect the results of the reproduced displacement signal. According to the application requirements and technical agreements, the error limits for each train test condition are limited, and the wavelength of the reproduced track irregularities has a certain range and must be within the allowable error. Therefore, in this step, only the samples with irregularity wavelengths within the allowable error range are retained at each numerical control point.

[0045] S3: The displacement response of the bridge at each numerical control point is superimposed with the track irregularity at the corresponding location.

[0046] S4: For different operating conditions of the maglev train, two cases are divided: one with superimposed track irregularities and one without. When track irregularities are not considered, the test bench reproduces the dynamic response of the track and bridge under train excitation, highlighting the vehicle-bridge coupled vibration. The test focuses on the impact of the bridge's dynamic response on train safety. When track irregularities are considered, since the magnitude of the irregularities is generally greater than the magnitude of the maglev beam's vibration response, the test focuses on the impact of track smoothness on train safety. Multi-point linear fitting is performed on the displacement response at all numerical control points, and the displacement response of each physical control point is calculated, generating corresponding control commands for the vibration test bench.

[0047] Among them, the method for multi-point linear fitting is the least squares algorithm, which converts the displacement response into control commands for the vibration test bench by replacing the deflection curve with piecewise straight lines.

[0048] Still with Figure 2Taking the illustrated embodiment as an example, the displacements of nine numerical control points with superimposed track irregularities and the displacements of nine numerical control points without superimposed track irregularities are input into eight two-point fitting algorithms. In the eight two-point fitting algorithms, each algorithm fits eight straight lines as the positions of the vibration test bench for the two cases of superimposed track irregularities and non-superimposed track irregularities. The vertical and horizontal translational displacements of the midpoints of the eight fitted straight lines are extracted as the vertical and horizontal translational displacement responses of the eight vibration test bench midpoints. The angle between the eight fitted two-point straight lines and the z-axis is taken as the roll angular displacement of the eight vibration test bench midpoints. The angle between the eight fitted two-point straight lines and the Y-axis is taken as the yaw angular displacement of the eight vibration test bench midpoints. The average rotation angle around the X-axis of adjacent numerical control points in each two-point fitting algorithm is taken as the pitch angular displacement of the vibration test bench midpoint. The resulting displacement responses of the vibration test bench midpoints in five directions are the displacement responses of each physical control point in five directions. At the same time, the displacement responses of each physical control point in five directions are combined to form the vibration test bench control command. The displacement response signal is converted into the vibration test bench control command signal by replacing the deflection curve with a piecewise straight line.

[0049] S5: Based on the displacement response of each physical control point, reproduce the displacement response of the track platform at the corresponding position, and perform a difference calculation with the actual displacement response at the corresponding position calculated by the numerical substructure to determine the maximum error of the track platform over the entire time history, i.e., the error peak value.

[0050] Specifically, the process of determining the peak error includes:

[0051] Analysis was conducted at each time step throughout the process, under both cases of superimposed and unsuperimposed track irregularities. Based on the displacement response of each physical control point, the vertical and horizontal displacements reproduced at corresponding positions on the track surface were predicted using the geometric pose relationship between the vibration test bench and the track (the geometric pose relationship between the vibration test bench and the track surface is known once the hybrid test model is constructed). Then, the difference between the predicted track surface reproduced displacement response and the calculated displacement response of the numerical substructure at the corresponding position was calculated to obtain the track surface reproduced error distribution, determine the error peak value, and analyze whether the peak value has periodic characteristics to confirm whether the location of the maglev train has a certain influence on the magnitude of the boundary coordination reproduced error.

[0052] like Figure 5As shown, the bridge deformation is mainly vertical, and the vertical absolute error is larger than the horizontal absolute error. Therefore, the main adjustment is to the vertical displacement error. The peak error can be reduced by optimizing the distance distribution formula to the other physical control points, adjusting the displacement response at each numerical control point, changing the geometric position of the platform, thereby changing the displacement response of each physical control point obtained by fitting, and adjusting the control command of the vibration test bench to reduce the peak error.

[0053] The formula for distributing the error by distance is:

[0054]

[0055] In the formula, u i For numerical control point displacement response; α is an adjustable coefficient that determines the distribution ratio; error max is the peak value of the error; distance i is the distance from the numerical control point to the peak value of the error.

[0056] Using multiple points to linearly fit a curve allows the least squares algorithm to calculate the slope of the line with the smallest error. The more numerical control points there are, the smaller the error in linear fitting can be.

[0057] S6: If the peak error does not exceed the error limit, the generated vibration test bench control command will be sent to the vibration test bench.

[0058] Specifically, the peak error determined throughout the entire time period is compared with the error limits required by the application and technical agreements. If the peak error meets the error requirements, the generated vibration test bench control command is sent to the vibration test bench for control, completing the boundary coordination process. Simultaneously, the error magnitude between track irregularities at different wavelengths and their reproduction results is used as a criterion to determine the wavelength range that meets the error limits, clarifying the range of track irregularities that the vibration test bench can reproduce in this real-time hybrid test due to the geometric parameter limitations of the rigid platform.

[0059] The above embodiment provides a boundary coordination method for real-time hybrid testing of maglev trains running on bridges. This method solves the problem that vibration test benches cannot directly apply the continuous displacement curves calculated from the bridge structure to the train. It converts the bridge deformation signal into the vibration test bench's operating signal by using a secant method that substitutes a piecewise straight line for the curve. This allows the test bench to approximate the bridge structure's response in a certain way, thus completing the deformation signal conversion. Furthermore, by using multi-point linear fitting to improve the algorithm, the magnitude of the reproduction error is effectively reduced. Simultaneously, the interpolation algorithm ensures consistency with other modules in terms of time steps, and the maximum reproduction error is clearly defined to meet the error requirements. This minimizes the impact of adverse factors in the experiment, ensuring sufficient accuracy and reliability during the experiment.

[0060] This invention also provides an electronic device, comprising:

[0061] A memory that stores computer programs;

[0062] A processor is used to load and execute the computer program to implement the steps of the boundary coordination method for real-time hybrid test of maglev train bridge as described in the above embodiments.

[0063] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the boundary coordination method for real-time hybrid test of maglev train bridge described in the above embodiments.

[0064] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0065] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will 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 apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0066] 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.

[0067] 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.

[0068] It is understood that the same or similar parts in the above embodiments can be referred to each other, and the contents not described in detail in some embodiments can be referred to the same or similar contents in other embodiments.

[0069] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of the invention pertain.

[0070] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for boundary coordination in real-time hybrid testing of maglev trains running on bridges, characterized in that, include: S1: Obtain the displacement response of each degree of freedom of the bridge at each numerical control point under the action of the maglev train at the current time step, and use the interpolation algorithm to ensure consistency with each module in the real-time hybrid test at the time step; S2: Use the power spectral density function to obtain and output the track irregularity samples at each numerical control point; S3: The displacement response of the bridge at each numerical control point is superimposed with the track irregularity at the corresponding location; S4: For two cases of superimposed track irregularity and non-superimposed track irregularity, multi-point linear fitting is performed on the displacement response at all numerical control points to calculate the displacement response of each physical control point and generate corresponding vibration test bench control commands; the method of multi-point linear fitting is the least squares algorithm, and the displacement response is converted into vibration test bench control commands by replacing the deflection curve with piecewise straight lines. S5: Reproduce the displacement response of the track platform at the corresponding position based on the displacement response of each physical control point, and perform a difference calculation with the actual displacement response at the corresponding position calculated by the numerical substructure to determine the peak error. S6: If the peak error does not exceed the error limit, the generated vibration test bench control command will be sent to the vibration test bench.

2. The method for real-time hybrid test boundary coordination of maglev train running on a bridge according to claim 1, characterized in that, The displacement response of each degree of freedom in step S1 includes vertical translational displacement, horizontal translational displacement, pitch angular displacement, roll angular displacement, and yaw angular displacement.

3. The method for real-time hybrid test boundary coordination of maglev train running on a bridge according to claim 1, characterized in that, The process of obtaining the displacement response of the bridge at each degree of freedom at each numerical control point under the action of the maglev train at the current time step includes: Based on train length, wheelset position, train speed and integral time step, bridge geometry and node unit information, and response displacement time history, the current time step maglev train position is calculated. Obtain the displacement response of each degree of freedom of the bridge at each numerical control point corresponding to the current position of the maglev train.

4. The method for real-time hybrid test boundary coordination of maglev train running on a bridge according to claim 1, characterized in that, In step S2, only samples with irregular wavelengths within the allowable error range are retained for track irregularity samples at each numerical control point.

5. The method for real-time hybrid test boundary coordination of maglev train running on a bridge according to claim 1, characterized in that, The power spectral density function is determined by the statistical characteristics of the measured dynamic detection data of the maglev track.

6. The method for real-time hybrid test boundary coordination of maglev train running on a bridge according to claim 2, characterized in that, Step S5 specifically includes: In both cases of superimposed and non-superimposed track irregularities, the displacement response at the corresponding position of the track platform is predicted based on the displacement response of each physical control point and the geometric pose relationship between the vibration test bench and the track. The difference between the predicted track platform displacement response and the calculated displacement response of the numerical substructure at the corresponding position is calculated to obtain the platform reproduction error distribution and determine the error peak value.

7. The method for real-time hybrid test boundary coordination of maglev train running on a bridge according to claim 1, characterized in that, The error peak obtained in step S5 is then optimized and distributed to the remaining physical control points by distance.

8. An electronic device, characterized in that, include: A memory that stores computer programs; A processor is configured to load and execute the computer program to implement the steps of the boundary coordination method for real-time hybrid test of maglev train bridge as described in any one of claims 1 to 7.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the boundary coordination method for real-time hybrid test of maglev train bridge as described in any one of claims 1 to 7.

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