A real-time hybrid test method based on multi-task loading, an electronic device and a storage medium

Abstract

A real-time hybrid test method based on multi-task loading, an electronic device and a storage medium belong to the technical field of real-time hybrid test. In order to solve the problems that it is difficult to guarantee the real-time performance of numerical calculation and all key components cannot be loaded due to the limitation of test conditions in the real-time hybrid test of complex ductility structure, the numerical substructure and the test substructure of the present application interact with full-time data, and the measured response of all test substructures is reproduced by multi-task full-time loading of one test substructure. First, the time lag compensation is carried out on the given full-time loading displacement of the numerical substructure, then the command selection is carried out, and the full-time loading commands of task 1, task 2,..., task n are sent to the servo loading system one by one, finally, one test substructure is used for multi-task full-time loading, and when the test results of adjacent two iteration rounds meet the convergence condition, the output test result is obtained. The present application is suitable for the case that the test substructure has the repeatable loading characteristic.

Description

Technical Field

[0001] This invention belongs to the field of real-time hybrid testing technology, specifically relating to a real-time hybrid testing method, electronic device, and storage medium based on multi-task loading. Background Technology

[0002] The hybrid testing method is a seismic testing approach that combines physical testing of real specimens with computer numerical simulation. By loading highly nonlinear and critically complex parts of the structure, relatively accurate test results can be obtained. Computer numerical simulation significantly reduces testing costs and improves the applicability of the test. Establishing a high-speed data exchange channel between the two methods enables real-time data transmission, meeting the testing requirements of specimens with velocity and acceleration-related characteristics. However, this requires completing a series of operations within the i-th time step, including solving the motion equations, transmitting loading commands, dynamic loading, and data feedback. The key is to avoid divergence caused by delays in numerical calculations and the dynamic loading system.

[0003] Due to the complexity of numerical simulation calculations and boundary compatibility conditions, it is difficult to guarantee real-time data transmission and loading. Moreover, for large and complex damping structures, the modeling freedom is relatively high. Under strong earthquakes, multiple key components exhibit complex nonlinear stress behaviors, requiring multiple actuators for loading. However, loading all key components is very difficult, necessitating the simulation of some key components, which increases the requirements for the accuracy of numerical simulation.

[0004] Hybrid experimental methods based on model updates can effectively improve the accuracy of numerical simulations, but the performance of simulated experimental substructures differs somewhat from the measured data obtained from direct experiments. Furthermore, this method struggles to achieve high real-time synchronization between numerical calculations and physical loading. Force-corrected iterative hybrid experimental methods can effectively address computational delays, but they do not consider the adverse effects of physical loading delays and multiple nonlinear key components. Summary of the Invention

[0005] To address the challenges of ensuring real-time numerical calculations and the inability to load all critical components under test conditions in real-time hybrid tests of complex tough structures, this invention proposes a real-time hybrid test method, electronic device, and storage medium based on multi-task loading.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A real-time hybrid experiment method based on multi-task loading includes the following steps:

[0008] S1. Divide the overall structure into numerical substructure and experimental substructure, and establish numerical substructure model and experimental substructure model;

[0009] S2. Solve the motion equation using the step-by-step integration method to calculate the time history displacement matrix and the time history restoring force matrix of the numerical substructure model from the first layer to the nth layer. When the integration step number i < k, continue to solve the motion equation using the step-by-step integration method, where k is the total number of steps of the step-by-step integration. When the integration step number i = k, proceed to the next step;

[0010] S4. Compensate for the time delay of the time history displacement matrix of the numerical substructure obtained in step S2 to obtain the time history command displacement matrix of the numerical substructure;

[0011] S7. Extract the time history command displacements of the numerical substructure from the first layer to the nth layer from the time history command displacement matrix of the numerical substructure obtained in step S4, generate n time history loading tasks using the multi-task loading controller, and then transfer them to the servo loading controller;

[0012] S10. According to the time history loading tasks generated in step S7, perform s task loadings on the test substructure with actuators and collect the time history measured displacement matrix and the time history measured reaction force matrix. Judge the number of loadings s and the number of time history loading tasks n. When s < n, continue the loading. When s = n, proceed to the next step;

[0013] S13. Based on the test substructure model established in step S1 and the time history measured displacement matrices of two adjacent iteration rounds obtained in step S10, correct the time history measured reaction force matrix obtained in step S10 to obtain the corrected test substructure time history reaction force matrix;

[0014] S16. Perform convergence judgment on the time history measured displacement matrices of two adjacent iteration rounds obtained in step S10. If it converges, end the test and output the test results. If it does not converge, proceed to the next step;

[0015] S19. Use the iterative convergence control method to transfer the measured displacement matrix in step S10 and the corrected test substructure time history reaction force matrix in step S13 to the next iteration round, and repeat steps S2 - S13.

[0016] Further, the calculation formula of the motion equation in step S2 is:

[0017]

[0018] where, M N 、C N are respectively the mass matrix and the damping matrix of the numerical substructure, are respectively the time history acceleration matrix, the time history velocity matrix, and the time history displacement matrix of the i-th step of the j-th round of the numerical substructure, is the time history restoring force matrix calculated by the numerical substructure in the j-th round, is the time history reaction force matrix corrected by the test substructure in the (j - 1)-th round, These are the time-history displacement matrix and time-history velocity matrix measured at the i-th step of the (j-1)th iteration from the experimental substructure; N and E are the numerical substructure and the experimental substructure, respectively; i is the integration step number; j is the iteration number; a g,i It is a record of earthquake acceleration.

[0019] Furthermore, in step S2, in the first iteration, the time history reaction force matrix of the experimental substructure participating in the solution of the motion equation is obtained by assuming the numerical model of the experimental substructure; in the j (j≥2) iteration, the time history reaction force matrix of the experimental substructure participating in the solution of the motion equation is the time history reaction force matrix of the experimental substructure after performing n full-time loading tasks, measuring its time history reaction force matrix with force sensors, and correcting it through a force correction strategy.

[0020] Furthermore, the successive integration method in step S2 adopts the Zhai method, specifically as follows:

[0021] a N,i =[-M N a g,i -C N v N,i -F N (d N,i )-F E (d E,i ,v E,i )] / M N

[0022] d N,i+1 =d N,i +v N,i Δt+(1 / 2+ψ)a N,i Δt 2 -ψa N,i-1 Δt 2

[0023] v N,i+1 =v N,i +(1+φ)a N,i Δt-φa N,i-1 Δt

[0024] Where ψ and φ are parameters introduced by the Zhai method, and d N,i+1 Let v be the time history displacement matrix at step i+1 of the numerical substructure. N,i+1 Let a be the time-history velocity matrix at the (i+1)th step of the numerical substructure. N,i-1 Let be the time history acceleration matrix of the (i-1)th step of the numerical substructure, and Δt be the integration step size.

[0025] Furthermore, the time delay compensation method in step S3 employs a polynomial extrapolation method, specifically as follows:

[0026]

[0027]

[0028] Where τ is the system time delay, b is the number of data points, and t i It is the time of step i, d N Let d be the numerical substructure displacement matrix. Nc Let d be the time history command displacement matrix of the numerical substructure. Em This is the time-history measured displacement matrix of the experimental substructure.

[0029] Furthermore, steps S3-S5 constitute the inner-loop multi-task loading process, realizing multi-task loading using a single test substructure, reproducing the measured responses of all test substructures, and reducing the requirements of traditional real-time hybrid testing methods on testing equipment. The key technology lies in first selecting the time-history command displacement matrix of the numerical substructure, then feeding back the corresponding full-time dynamic loading task to the loading controller one by one, and finally executing the full-time loading commands of task 1, task 2, ..., task n through a test substructure with actuators, and measuring the time-history displacement matrix and time-history reaction force matrix of the n test substructures.

[0030] Furthermore, the specific method for correcting the time history reaction matrix of the experimental substructure in step S6 is as follows:

[0031]

[0032] In the formula, It is the time-history measured reaction force matrix of the experimental substructure in the j-th iteration. It is an equivalent experimental substructure numerical model. These are the measured time-history displacement matrix and the calculated time-history measured velocity matrix for the j-th round and i-th step of the experimental substructure, respectively. It is the time history reaction force matrix of the substructure in the j-th round of the modified test.

[0033] Furthermore, step S6 corrects the time history reaction force matrix of the test substructure measured by the multi-task loading system one by one based on the difference between the equivalent test substructure numerical model and the time history measured displacement in two adjacent iterations, rather than correcting the restoring force array.

[0034] Furthermore, the convergence judgment in step S7 uses root mean square error and relative area error for judgment:

[0035]

[0036]

[0037] Where RMSE is the root mean square error, RAE is the relative area error, and T is the total time of a time series.

[0038] Furthermore, the iterative convergence control method in step S8 adopts the fixed-point iteration method; for the measured displacement matrix of the output time history in the j-th round... The measured displacement matrix of the output time history in the (j+1)th round Represented as:

[0039]

[0040] Set the iteration target F(d) as:

[0041]

[0042]

[0043] For any initial value satisfy The fixed-point iteration method has converged. * Let a and b be the solutions to F(d). a and b are the start and end points of the numerical range.

[0044] An electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the real-time hybrid testing method based on multi-task loading.

[0045] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aforementioned real-time hybrid testing method based on multi-task loading.

[0046] The beneficial effects of this invention are:

[0047] The real-time hybrid experiment method based on multi-task loading described in this invention changes the data interaction method of real-time hybrid experiments, enabling real-time hybrid experiments to be completed under non-real-time numerical calculation conditions, thus making it possible to conduct real-time hybrid experiments using refined models.

[0048] The present invention discloses a real-time hybrid testing method based on multi-task loading, which allows for multi-task loading of a single test substructure to reproduce the measured responses of all test substructures, thus reducing the requirements of traditional real-time hybrid testing methods on testing equipment. The key steps are: first, selecting the displacement matrix of the time-history command for the numerical substructure; second, feeding back the corresponding full-time dynamic loading task to the loading controller one by one; and finally, executing the full-time loading commands for task 1, task 2, ..., task n through a test substructure equipped with actuators.

[0049] The present invention discloses a real-time hybrid testing method based on multi-task loading, which improves the repeatability accuracy of a test substructure when subjected to multi-task loading by combining a time delay compensation method; improves the iterative convergence efficiency and shortens the test time by combining a force correction strategy; and finally converges to the true response of the structure by combining an iterative convergence control algorithm.

[0050] The real-time hybrid test method based on multi-task loading described in this invention is not limited to a specific method, but rather focuses on the fact that the method used can achieve the test objective. Attached Figure Description

[0051] Figure 1 This is a flowchart of a real-time hybrid testing method based on multi-task loading as described in this invention;

[0052] Figure 2 This is a schematic diagram of a real-time hybrid test method based on multi-task loading as described in this invention (taking an n-layer frame damping structure with n viscous dampers installed as an example).

[0053] Figure 3 This is a schematic diagram of a real-time hybrid test method based on multi-task loading as described in this invention (taking a high-speed train carriage equipped with n anti-hunting dampers as an example). Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only for explaining the invention and are not intended to limit the invention; that is, the described specific embodiments are merely some embodiments of the invention, and not all of them. The components of the specific embodiments of the invention described and shown in the accompanying drawings can typically be arranged and designed in various different configurations, and the invention may also have other embodiments.

[0055] Therefore, the following detailed description of specific embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected specific embodiments of the invention. All other specific embodiments obtained by those skilled in the art based on these specific embodiments without inventive effort are within the scope of protection of this invention.

[0056] To further understand the invention's content, features, and effects, the following specific embodiments are provided, along with accompanying drawings. Figure 1-3 Detailed explanation is as follows: Specific implementation method one:

[0058] Taking an n-story frame shock-absorbing structure installed with n viscous dampers as an example, the basic principle and usage steps of the method of the present invention are described.

[0059] As an energy dissipation shock absorption technology, the viscous damper has the advantages of being reusable, having a simple structure, and a clear shock absorption mechanism. In the real-time hybrid test method, due to the non-linear mechanical behavior of the viscous damper, the viscous damper is generally used as the test sub-structure and loaded by an actuator, and the rest of the structure is used as the numerical sub-structure, simulated by a computer, and the real-time transfer of data at the i-th integration step is ensured through a high-speed data exchange channel. Thus, large-scale or even full-scale tests can be realized, and more accurate and effective test results can be obtained. The difficulty of this embodiment lies in that there are n non-linear parts of the structure. Limited by laboratory conditions, it is often unrealistic to take out all the key components for loading. At the same time, the real-time hybrid test method is difficult to ensure the reliability of the numerical structure model, and it will also bring more complex coupled multi-dimensional boundary conditions. Also, because a relatively small sampling step needs to be adopted, it is impossible to ensure real-time data calculation and real-time loading, making it more difficult to implement the real-time hybrid test method. Therefore, this embodiment proposes a real-time hybrid test method based on multi-task loading. The basic principle of the method is as Figure 2 shown, and the specific process of the method is as follows:

[0060] S1. Divide the n-story frame shock-absorbing structure installed with n viscous dampers, take the n viscous dampers as the test sub-structure, and the n-story frame structure as the numerical sub-structure, and establish corresponding numerical models respectively;

[0061] S2. Use the step-by-step integration method to solve the motion equation, calculate the time history displacement matrix and time history restoring force matrix of the numerical sub-structure model from the 1st layer to the nth layer. When the integration step number i < k, continue to use the step-by-step integration method to solve the motion equation, where k is the total number of step-by-step integrations. When the integration step number i = k, proceed to the next step;

[0062] Further, the calculation formula of the motion equation in step S2 is:

[0063]

[0064] where, M N and C N are respectively the mass matrix and damping matrix of the numerical sub-structure, are respectively the time history acceleration matrix, time history velocity matrix, and time history displacement matrix of the i-th step of the j-th round of the numerical sub-structure, is the time history restoring force matrix calculated by the numerical sub-structure in the j-th round, is the time history reaction force matrix corrected by the test sub-structure in the (j - 1)-th round, These are the time-history displacement matrix and time-history velocity matrix measured at the i-th step of the (j-1)th iteration from the experimental substructure; N and E are the numerical substructure and the experimental substructure, respectively; i is the integration step number; j is the iteration number; a g,i It is a record of earthquake acceleration;

[0065] Furthermore, the successive integration method in step S2 adopts the Zhai method, specifically as follows:

[0066] a N,i =[-M N a g,i -C N v N,i -F N (d N,i )-F E (d E,i ,v E,i )] / M N

[0067] d N,i+1 =d N,i +v N,i Δt+(1 / 2+ψ)a N,i Δt 2 -ψa N,i-1 Δt 2

[0068] v N,i+1 =v N,i +(1+φ)a N,i Δt-φa N,i-1 Δt

[0069] Where ψ and φ are parameters introduced by the Zhai method, and d N,i+1 Let v be the time history displacement matrix at step i+1 of the numerical substructure. N,i+1 Let a be the time-history velocity matrix at the (i+1)th step of the numerical substructure. N,i-1 Let be the time history acceleration matrix of the (i-1)th step of the numerical substructure, and Δt be the integration step size;

[0070] S3. Perform time delay compensation on the numerical substructure time history displacement matrix obtained in step S2 to obtain the numerical substructure time history command displacement matrix.

[0071] Furthermore, the time delay compensation method in step S3 employs a polynomial extrapolation method, specifically as follows:

[0072]

[0073]

[0074] Where τ is the system time delay, b is the number of data points, and t iis the time of the i-th step, d N is the displacement matrix of the numerical substructure, d Nc is the displacement matrix of the time history command of the numerical substructure, d Em is the displacement matrix of the time history measured value of the test substructure.

[0075] S4. Extract the displacement of the time history command of the numerical substructure from the 1st layer to the nth layer of the numerical substructure obtained in step S3, generate n time history loading tasks by using a multi-task loading controller, and then transfer them to the servo loading controller;

[0076] S5. According to the time history loading tasks generated in step S4, perform s task loadings on the test substructure with actuators and collect the displacement matrix of the time history measured value and the reaction force matrix of the time history measured value, judge the number of loading times s and the number of time history loading tasks. When s < n, continue the loading. When s = n, proceed to the next step; ]>

[0077] S6. Based on the test substructure model established in step S1 and the displacement matrix of the time history measured value of two adjacent iterative rounds obtained in step S5, correct the reaction force matrix of the time history measured value obtained in step S5 to obtain the corrected reaction force matrix of the time history of the test substructure;

[0078] Further, the specific method for correcting the reaction force matrix of the time history of the test substructure in step S6 is as follows:

[0079]

[0080] In the formula, is the reaction force matrix of the time history measured value of the test substructure in the j-th iterative round, is the equivalent numerical model of the test substructure, [[ID=]30]are respectively the displacement matrix of the time history measured value and the calculated velocity matrix of the time history measured value at the i-th step in the j-th round of the test substructure, is the reaction force matrix of the time history of the corrected test substructure in the j-th round;

[0081] S7. Perform convergence judgment on the displacement matrix of the time history measured value of two adjacent iterative rounds obtained in step S5. If it converges, end the test and output the test results. If it does not converge, proceed to the next step;

[0082] Further, the convergence judgment in step S7 is performed by using the root mean square error and the relative area error:

[0083]

[0084] <000031]1]>

[0085] Among them, RMSE is the root mean square error, RAE is the relative area error, and T is the total time of a time history;

[0086] S8. Using an iterative convergence control method, the measured displacement matrix from step S5 and the modified experimental substructure time history reaction matrix from step S6 are passed to the next iteration round, and steps S2-S6 are repeated.

[0087] Furthermore, the iterative convergence control method in step S8 adopts the fixed-point iteration method; for the measured displacement matrix of the output time history in the j-th round... The measured displacement matrix of the output time history in the (j+1)th round Represented as:

[0088]

[0089] Set the iteration target F(d) as:

[0090]

[0091]

[0092] For any initial value satisfy The fixed-point iteration method has converged. * Let a and b be the solutions to F(d), where a and b are the start and end points of the numerical range.

[0093] The real-time hybrid experiment method based on multi-task loading described in this embodiment changes the real-time hybrid experiment data interaction method, enabling real-time hybrid experiments to be completed under non-real-time numerical calculation conditions, thus making real-time hybrid experiments using refined models possible.

[0094] This embodiment describes a real-time hybrid testing method based on multi-task loading, which allows for multi-task loading of a single test substructure to reproduce the measured responses of all test substructures, reducing the requirements of traditional real-time hybrid testing methods on testing equipment. The key steps are: first, selecting the displacement matrix of the time-history command for the numerical substructure; second, feeding back the corresponding full-time dynamic loading task to the loading controller one by one; and finally, executing the full-time loading commands for task 1, task 2, ..., task n through a test substructure equipped with an actuator.

[0095] The real-time hybrid testing method based on multi-task loading described in this embodiment improves the repeatability accuracy of a test substructure when performing multi-task loading by combining a time delay compensation method; improves the iterative convergence efficiency and shortens the test time by combining a force correction strategy; and finally converges to the true response of the structure by combining an iterative convergence control algorithm.

[0096] A real-time hybrid test method based on multi-task loading described in this embodiment, the step-by-step integration algorithm, time-delay compensation method, force correction method, and iterative convergence control algorithm used are not limited to a specific method, and the key lies in that the methods used can achieve the test purpose. [[ID=X]]Specific Embodiment 2:

[0098] The present invention has similar basic principles when applied to other large and complex vibration damping structures; taking a high-speed train as an example, the basic principles and usage steps of the method of the present invention are described.

[0099] During the operation of a high-speed train, lateral vehicle hunting vibration will occur. Severe hunting vibration will affect the safety and stability of train operation and reduce the instability critical speed of the high-speed train. By installing anti-hunting dampers, the hunting movement of the train can be effectively suppressed, and the critical speed and driving stability of the high-speed train can be improved. Therefore, conducting tests on anti-hunting dampers and studying the effect of anti-hunting dampers during train operation is of great significance for improving the smooth running of trains and further increasing the running speed of trains. However, due to the dynamic response of high-speed trains being a high-frequency dynamics problem, and because the train itself has a complex structure, a large number of degrees of freedom, and because there are often many dampers and they exhibit non-linear force behaviors, multiple actuators are required for loading. However, limited by laboratory conditions, it is often unrealistic to take out all the key components for loading. However, the current real-time hybrid test method based on model updating is limited by the requirements of test real-time and the method of simulating the performance of test specimens, which will lead to distortion of test results. Therefore, the present invention proposes a real-time hybrid test method based on multi-task loading, and the basic principle of the method is as Figure 3 shown, and the specific process of the method is as follows:

[0100] S1. Divide the high-speed train car body structure equipped with n anti-hunting dampers, take the n anti-hunting dampers as test sub-structures, and the high-speed train car body as a numerical sub-structure, and establish corresponding numerical models respectively;

[0101] S2. Use the step-by-step integration method to solve the motion equation, calculate the time-history displacement matrix and time-history restoring force matrix of the numerical sub-structure model from the 1st layer to the nth layer. When the integration step i < k, continue to use the step-by-step integration method to solve the motion equation, where k is the total number of integration steps. When the integration step i = k, proceed to the next step;

[0102] Further, the calculation formula of the motion equation in step S2 is:

[0103]

[0104] where, M N 、C NThese are the mass matrix and damping matrix of the numerical substructure, respectively. These are the time-history acceleration matrix, time-history velocity matrix, and time-history displacement matrix of the j-th round and i-th step of the numerical substructure, respectively. It is the time-history restoring force matrix calculated for the j-th round-number substructure. It is the time history reaction matrix after the substructure of the (j-1)th round of experiment is corrected. These are the time-history displacement matrix and time-history velocity matrix measured at the i-th step of the (j-1)th iteration from the experimental substructure; N and E are the numerical substructure and the experimental substructure, respectively; i is the integration step number; j is the iteration number; a g,i It is a record of earthquake acceleration;

[0105] Furthermore, the successive integration method in step S2 adopts the Zhai method, specifically as follows:

[0106] a N,i =[-M N a g,i -C N v N,i -F N (d N,i )-F E (d E,i ,v E,i )] / M N

[0107] d N,i+1 =d N,i +v N,i Δt+(1 / 2+ψ)a N,i Δt 2 -ψa N,i-1 Δt 2

[0108] v N,i+1 =v N,i +(1+φ)a N,i Δt-φa N,i-1 Δt

[0109] Where ψ and φ are parameters introduced by the Zhai method, and d N,i+1 Let v be the time history displacement matrix at step i+1 of the numerical substructure. N,i+1 Let a be the time-history velocity matrix at the (i+1)th step of the numerical substructure. N,i-1 Let be the time history acceleration matrix of the (i-1)th step of the numerical substructure, and Δt be the integration step size;

[0110] S3. Perform time delay compensation on the numerical substructure time history displacement matrix obtained in step S2 to obtain the numerical substructure time history command displacement matrix.

[0111] Further, the time-delay compensation method in step S3 adopts the polynomial extrapolation method, and the specific method is as follows:

[0112]

[0113]

[0114] where τ is the system time delay, b is the number of data points, t i is the time of the i-th step, d N is the displacement matrix of the numerical substructure, d Nc is the time-history command displacement matrix of the numerical substructure, d Em is the time-history measured displacement matrix of the experimental substructure.

[0115] S4. Extract the time-history command displacements of the 1st to nth layers of the numerical substructure from the time-history command displacement matrix of the numerical substructure obtained in step S3, generate n time-history loading tasks by using a multi-task loading controller, and then transfer them to the servo loading controller;

[0116] S5. According to the time-history loading tasks generated in step S4, perform s task loadings on the experimental substructure with actuators and collect the time-history measured displacement matrix and the time-history measured reaction force matrix, and judge the number of loadings s and the number of time-history loading tasks n. When s < n, continue the loading. When s = n, proceed to the next step;

[0117] S6. Based on the experimental substructure model established in step S1 and the time-history measured displacement matrices of two adjacent iterative rounds obtained in step S5, correct the time-history measured reaction force matrix obtained in step S5 to obtain the corrected time-history reaction force matrix of the experimental substructure;

[0118] Further, the specific method for correcting the time-history reaction force matrix of the experimental substructure in step S6 is as follows:

[0119]

[0120] In the formula, is the time-history measured reaction force matrix of the experimental substructure in the j-th iteration round, is the equivalent numerical model of the experimental substructure, are respectively the measured time-history measured displacement matrix and the calculated time-history measured velocity matrix at the i-th step in the j-th round of the experimental substructure, is the corrected time-history reaction force matrix of the experimental substructure in the j-th round;

[0121] S7. Perform convergence judgment on the time-history measured displacement matrices of two adjacent iterative rounds obtained in step S5. If it converges, end the experiment and output the experimental results. If it does not converge, proceed to the next step;

[0122] Furthermore, the convergence judgment in step S7 uses root mean square error and relative area error for judgment:

[0123]

[0124]

[0125] Where RMSE is the root mean square error, RAE is the relative area error, and T is the total time of a time series;

[0126] S8. Using an iterative convergence control method, the measured displacement matrix from step S5 and the modified experimental substructure time history reaction matrix from step S6 are passed to the next iteration round, and steps S2-S6 are repeated.

[0127] Furthermore, the iterative convergence control method in step S8 adopts the fixed-point iteration method; for the measured displacement matrix of the output time history in the j-th round... The measured displacement matrix of the output time history in the (j+1)th round Represented as:

[0128]

[0129] Set the iteration target F(d) as:

[0130]

[0131]

[0132] For any initial value satisfy The fixed-point iteration method has converged. * Let a and b be the solutions to F(d), where a and b are the start and end points of the numerical range.

[0133] Through the above experimental process, the force-displacement response of the high-speed train anti-hunting damper under actual driving conditions can be obtained, providing a research basis for the high-speed and stable operation of high-speed trains. Furthermore, this experimental method can not only be applied to anti-hunting dampers, but also, through different substructure division methods, to conduct multi-task loading tests on complex, highly nonlinear components with multiple repeatability characteristics.

[0134] The real-time hybrid experiment method based on multi-task loading described in this embodiment changes the real-time hybrid experiment data interaction method, enabling real-time hybrid experiments to be completed under non-real-time numerical calculation conditions, thus making real-time hybrid experiments using refined models possible.

[0135] This embodiment describes a real-time hybrid testing method based on multi-task loading, which allows for multi-task loading of a single test substructure to reproduce the measured responses of all test substructures, reducing the requirements of traditional real-time hybrid testing methods on testing equipment. The key steps are: first, selecting the displacement matrix of the time-history command for the numerical substructure; second, feeding back the corresponding full-time dynamic loading task to the loading controller one by one; and finally, executing the full-time loading commands for task 1, task 2, ..., task n through a test substructure equipped with an actuator.

[0136] The real-time hybrid testing method based on multi-task loading described in this embodiment improves the repeatability accuracy of a test substructure when performing multi-task loading by combining a time delay compensation method; improves the iterative convergence efficiency and shortens the test time by combining a force correction strategy; and finally converges to the true response of the structure by combining an iterative convergence control algorithm.

[0137] The real-time hybrid test method based on multi-task loading described in this embodiment is not limited to a specific method, but the key is that the method used can achieve the test objective. Specific implementation method three:

[0139] An electronic device includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of a real-time hybrid testing method based on multi-task loading as described in Specific Embodiment 1 or 2.

[0140] The computer device of the present invention may include a processor and a memory, such as a microcontroller containing a central processing unit. Furthermore, when the processor executes the computer program stored in the memory, it implements the steps of the aforementioned recommendation method for modifyable relationship-driven recommendation data based on CREO software.

[0141] The processor referred to can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0142] The memory may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a given function (such as sound playback or image playback). The data storage area may store data created based on the use of the mobile phone (such as audio data or phonebook entries). Furthermore, the memory may include high-speed random access memory (RAM) and non-volatile memory, such as hard disks, RAM, plug-in hard disks, smart media cards (SMC), secure digital cards (SD), flash cards (FC), at least one disk storage device, flash memory device, or other volatile solid-state storage devices. Specific implementation method four:

[0144] A computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements a real-time hybrid testing method based on multi-task loading as described in Specific Embodiment 1 or 2.

[0145] The computer-readable storage medium of the present invention can be any form of storage medium that can be read by the processor of a computer device, including but not limited to non-volatile memory, volatile memory, ferroelectric memory, etc. The computer-readable storage medium stores a computer program. When the processor of the computer device reads and executes the computer program stored in the memory, the steps of the above-described modeling method for modifyable relation-driven modeling data based on CREO software can be implemented.

[0146] The computer program includes computer program code, which may be in the form of source code, object code, executable file, or certain intermediate forms. The computer-readable medium may include any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium may be appropriately added to or subtracted according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media may not include electrical carrier signals and telecommunication signals.

[0147] It should be noted that relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0148] Although this application has been described above with reference to specific embodiments, various modifications can be made and components can be replaced with equivalents without departing from the scope of this application. In particular, as long as there is no structural conflict, the features in the specific embodiments disclosed in this application can be combined with each other in any way. The lack of an exhaustive description of these combinations in this specification is merely for the sake of brevity and resource conservation. Therefore, this application is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A real-time hybrid experimental method based on multi-task loading, characterized in that: It includes the following steps: S1. Divide the overall structure into numerical sub-structures and experimental sub-structures, and establish numerical sub-structure models and experimental sub-structure models; S2. Use the step-by-step integration method to solve the motion equation, calculate the time-history displacement matrix and time-history restoring force matrix of the numerical sub-structure model from the 1st layer to the nth layer. When the integration step number i < k, continue to use the step-by-step integration method to solve the motion equation, where k is the total number of step-by-step integrations. When the integration step number i = k, proceed to the next step; S3. Perform time-delay compensation on the time-history displacement matrix of the numerical sub-structure obtained in step S2 to obtain the time-history command displacement matrix of the numerical sub-structure; S4. Extract the time-history command displacements of the numerical sub-structure from the 1st layer to the nth layer from the time-history command displacement matrix of the numerical sub-structure obtained in step S3, generate n time-history loading tasks using a multi-task loading controller, and then transfer them to the servo loading controller; S5. According to the time-history loading tasks generated in step S4, perform s times of task loading on the experimental sub-structure with actuators and collect the time-history measured displacement matrix and time-history measured reaction force matrix. Compare the number of loading times s with the number of time-history loading tasks n. When s < n, continue loading. When s = n, proceed to the next step; S6. Based on the experimental sub-structure model established in step S1 and the time-history measured displacement matrices of two adjacent iteration rounds obtained in step S5, correct the time-history measured reaction force matrix obtained in step S5 to obtain the corrected experimental sub-structure time-history reaction force matrix; The corrected experimental sub-structure time-history reaction force matrix in step S6 is: In the formula, It is the time-history measured reaction force matrix of the experimental substructure in the j-th iteration. It is an equivalent experimental substructure numerical model. These are the measured time-history displacement matrix and the calculated time-history measured velocity matrix for the j-th round and i-th step of the experimental substructure, respectively. It is the time history reaction matrix of the substructure in the j-th round of the modified test; These are the time-history displacement matrix and time-history velocity matrix of the j-th round and i-th step of the experimental substructure, respectively. S7. Perform convergence judgment on the time-history measured displacement matrices of two adjacent iteration rounds obtained in step S5. If it converges, end the experiment and output the experimental results. If it does not converge, proceed to the next step; S8. Use the iterative convergence control method to transfer the measured displacement matrix in step S5 and the corrected experimental sub-structure time-history reaction force matrix in step S6 to the next iteration round, and repeat steps S2 - S6; The iterative convergence control method in step S8 adopts the fixed-point iteration method; for the output time history measured displacement matrix of the j-th round... The measured displacement matrix of the output time history in the (j+1)th round , is represented as: Set iteration target for: For any initial value ∈[a, b], satisfy The fixed-point iteration method has converged. for The solution is given by a and b, where a and b are the start and end points of the numerical range.

2. The real-time hybrid experimental method based on multi-task loading according to claim 1, characterized in that: The calculation formula of the motion equation in step S2 is: in, These are the mass matrix and damping matrix of the numerical substructure, respectively. These are the time-history acceleration matrix, time-history velocity matrix, and time-history displacement matrix of the j-th round and i-th step of the numerical substructure, respectively. It is the time-history restoring force matrix calculated for the j-th round-number substructure. It is the time history reaction matrix after the substructure of the (j-1)th round of experiment is corrected. These are the time-history displacement matrix and time-history velocity matrix of the (j-1)th round and the i-th step of the experimental substructure, respectively; N and E are the numerical substructure and the experimental substructure, respectively; i is the integration step number; j is the iteration round; It is a record of earthquake acceleration.

3. The real-time hybrid experimental method based on multi-task loading according to claim 2, characterized in that: The step-by-step integration method in step S2 adopts the Zhai method, and the specific method is: in, The parameters introduced for the Zhai method, Let be the time-history displacement matrix of the (i+1)th step of the numerical substructure. Let be the time-history velocity matrix at the (i+1)th step of the numerical substructure. Let be the time-history acceleration matrix of the (i-1)th step of the numerical substructure. This is the integration step size.

4. The real-time hybrid experimental method based on multi-task loading according to claim 3, characterized in that: The time-delay compensation method in step S3 adopts the polynomial extrapolation method, and the specific method is: in, Let b be the system time delay and b be the number of data points. It is the time of step i. This is the numerical substructure displacement matrix. The time history command displacement matrix of the numerical substructure. This is the time-history measured displacement matrix of the experimental substructure.

5. The real-time hybrid experimental method based on multi-task loading according to claim 4, characterized in that: The convergence judgment in step S7 adopts the root mean square error and relative area error for judgment: in, The root mean square error, The relative area error is T, and the total time of one time series is T.

6. An electronic device, characterized in that, It includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the steps of a real-time hybrid test method based on multi-task loading according to any one of claims 1 - 5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements a real-time hybrid test method based on multi-task loading according to any one of claims 1 - 5.

Images