Force correction update iteration hybrid test method, system, storage medium and equipment based on multi-task loading

Abstract

A force correction updating iteration hybrid test method, system, storage medium and equipment based on multi-task loading belong to the technical application field of structure hybrid test. By establishing a numerical model of a numerical substructure of a prototype structure and a numerical model of a test substructure, a first round of motion equation is solved to obtain a loading command, the loading command is preprocessed and test data is obtained, an updating iteration equation of two force correction model parameters is established, the force correction model parameters are updated in real time according to the test data of the last round, the last round of correction force is input, the updated motion equation is solved, the iteration loading is executed and the test data is collected, and it is determined whether the convergence index reaches the engineering precision threshold value, if yes, the iteration is terminated; if not, the process of updating the model parameters and the loading command is cycled until the convergence index reaches the engineering precision threshold value, and the parameters of the force correction model are continuously adjusted and improved to approach a better result.

Description

Technical Field

[0001] This invention specifically relates to a force correction update iteration hybrid test method, system, storage medium, and device based on multi-task loading, and relates to the field of structural hybrid test technology. Background Technology

[0002] Real-time hybrid testing methods, as an emerging seismic testing approach combining real physical experiments and computer numerical simulations, have demonstrated unique advantages in the field of structural seismic resistance research. Real-time loading of structurally complex and nonlinearly prominent components yields accurate experimental data; numerical simulations using computer software effectively reduce testing costs and broaden the scope of application. Establishing high-speed data exchange channels enables real-time data interaction, meeting the specific velocity and acceleration characteristics testing requirements of individual specimens. However, this method faces numerous challenges in practical applications. Specifically, within the i-th time step, a series of operations must be completed, including solving the motion equations, transmitting loading commands, dynamic loading, and data feedback, placing extremely high demands on the system's real-time performance. Delays in numerical calculations and dynamic loading systems can easily lead to divergence in experimental results. The complexity of numerical simulations and the stringent boundary conditions make it difficult to guarantee real-time data transmission and loading.

[0003] When a structure contains multiple nonlinear components, there are currently two main experimental strategies: one is the conventional real-time hybrid test, which requires multiple specimens to be loaded synchronously in real time. However, due to differences in the time delays of each loading system, loading asynchrony problems occur frequently, which may lead to test failure in severe cases. The other is the model update method, which selects one nonlinear component as the experimental substructure and the rest as the numerical substructure. The constitutive model of the numerical substructure is updated online using the real-time loading feedback data of the experimental substructure. However, the performance of the simulated experimental substructure still lags behind that of the direct experimental data, and it is difficult to achieve a high degree of real-time synchronization between numerical calculation and physical loading. In addition, the real-time hybrid test method based on multi-task loading proposed in recent years does not undergo rigorous calculation and derivation when determining the force correction model parameters, but directly uses the predetermined parameters of the specimen. This approach greatly limits the application of this method in real-world complex structures.

[0004] To address the issues of low accuracy and slow iterative convergence in existing force correction models, this invention provides a force correction update iterative hybrid test method, system, storage medium, and device based on multi-task loading. By updating model parameters in real time and dynamically adjusting weight coefficients, the test accuracy and convergence efficiency are improved. Summary of the Invention

[0005] To address the issue of divergent experimental results caused by low accuracy of the force correction model, this invention proposes a hybrid experimental method for force correction and iterative updates based on multi-task loading. This method involves establishing numerical models of both the prototype and experimental substructures, solving the initial motion equations to obtain loading commands, preprocessing the loading commands and acquiring experimental data, establishing iterative equations for updating the force correction model parameters, updating the force correction model parameters in real time based on the previous round of experimental data, inputting the previous correction force, solving the updated motion equations, executing iterative loading and collecting experimental data, and determining whether the convergence index reaches the engineering accuracy threshold. If yes, the iteration terminates; otherwise, the process of updating the model parameters and loading commands is repeated until the convergence index reaches the engineering accuracy threshold.

[0006] Preferably, the force correction model parameters include the damping C of the test substructure. E Stiffness K E And the weighting coefficient λ value.

[0007] Preferably, the force correction update iterative hybrid test method includes:

[0008] S1. Establish numerical models of the prototype substructure and the experimental substructure, solve the first round of motion equations, and obtain loading commands, including the loading commands for the first round of experiments:

[0009] The equation of motion can be expressed as:

[0010]

[0011] In the above formula, M, C, and K represent the mass matrix, damping matrix, and stiffness matrix of the numerical substructure, respectively. These represent the time-history acceleration matrix, time-history velocity matrix, and time-history displacement matrix of the numerical substructure at the i-th step of the first round, respectively. The numerical model of the experimental substructure represents the time-history reaction force in the first round; the subscript N represents the numerical substructure; i represents the integration time step; a g,i Represents earthquake acceleration excitation;

[0012] S2. Perform time delay compensation on the loading command, and obtain test data based on the time delay compensated loading command;

[0013] S3. Establish update iterative equations for the parameters of the two force correction models, and calculate the damping C of the experimental substructure based on the experimental data. E and stiffness K E :

[0014] The update iterative equation for establishing the force correction model parameters can be:

[0015]

[0016] In the above formula, the superscript j represents the iteration number, and the value of j is not less than 2; λ represents the weight coefficient, and the range of λ is [0,1]; n represents the total number of integration steps; the subscript E represents the experimental substructure; the subscript m represents the measured value; v and d represent the time history velocity matrix and time history displacement matrix of the numerical substructure, respectively; i represents the integration time step; F represents the time history reaction force.

[0017] The update iterative equation for establishing the force correction model parameters can also be:

[0018]

[0019] In the above formula, the value of j is 2;

[0020]

[0021] In the above formula, the value of j is not less than 3, and N represents the total number of iterations;

[0022] S4. Input the experimental data collected in the previous round of experiments into the numerical substructure, solve the motion equations to obtain a new loading command, perform time delay compensation on the loading command, and obtain new experimental data;

[0023] The previous round of corrective force input and solution of the motion equations are as follows:

[0024]

[0025] In the above formula, The correction force representing the experimental substructure can be expressed by the following formula.

[0026]

[0027] S5. Determine the weight coefficient λ in formula (7) using the experimental data and convergence index of two adjacent rounds;

[0028] S6, S3, S4, S5, the number of iterations is determined by the convergence index and the engineering accuracy threshold.

[0029] Preferably, the confirmation process of the convergence index includes:

[0030]

[0031] In the above formula, q represents the qth experimental substructure.

[0032] Preferably, before updating the force correction model parameters in real time based on the previous round of test data, the method further includes using an optimization module to compare the damping C of the substructures in adjacent rounds of tests. E and stiffness K ETo assess iterative convergence, a damping factor C with high iterative convergence efficiency is selected. E and stiffness K E The model parameters are corrected for the current force.

[0033] Preferably, after updating the force correction model parameters in real time based on the previous round of test data, the method further includes correcting the measured data of the previous round of test substructure based on the difference between the measured data of the previous round of test substructure and the instruction data of the current round of test value substructure.

[0034] Preferably, the weight coefficient λ is 0.5 in the first iteration, i.e., the second iteration; in other iterations, the weight coefficient λ is determined by the calculated value of the convergence index.

[0035] Preferably, a force correction update iterative hybrid test system based on multi-task loading is also provided, applied to the above-mentioned force correction update iterative hybrid test method, including:

[0036] The numerical simulation module is used to establish numerical models of the prototype structure's numerical substructures and the experimental substructures.

[0037] The test loading module, including actuators, controllers, and time delay compensation units, is used to execute loading commands and collect test data.

[0038] The parameter update module is used to calculate the force correction model parameters and weight coefficients in real time based on the experimental data.

[0039] The convergence determination module is used to determine the number of iterations based on the convergence index and the engineering accuracy threshold.

[0040] Preferably, a storage medium is also provided, wherein at least one instruction is stored in the storage medium, the at least one instruction being loaded and executed by a processor to implement the above-described force correction update iterative hybrid test method.

[0041] Preferably, a force correction update iteration hybrid test device based on multi-task loading is also provided. The force correction update iteration hybrid test device based on multi-task loading includes a processor, a memory, and a sensor array. The memory stores at least one instruction as described above, the sensor array stores test data, and the processor loads and executes the instruction to implement the force correction update iteration hybrid test method based on multi-task loading as described above.

[0042] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0043] 1. The force correction update iterative hybrid experimental method based on multi-task loading proposed in this invention develops a force correction model update technique. It employs finite element software for refined modeling, and a servo loading system sequentially loads both the numerical substructure and the experimental substructure. Experimental data is collected and input into the numerical substructure, and the motion equations are solved to obtain new loading commands. Time delay compensation is performed, and new experimental data is acquired. The motion equations are updated by correcting the force, effectively solving the problem of inconsistent reaction forces during the numerical solution of the motion equations of the numerical substructure, and accelerating the efficiency of iterative convergence. Specific details are as follows.

[0044] If formula (7) is simplified, and the calculation accuracy of the equation is high, then the Kelvin viscoelastic model can characterize the force characteristics of the numerical substructure and the experimental substructure to a certain extent. Therefore, formula (7) can be transformed into:

[0045]

[0046] 2. The force correction update iterative hybrid experimental method based on multi-task loading proposed in this invention uses an update iterative equation to calculate parameters for establishing force correction model parameters, updates the force correction model in real time, and dynamically adjusts the appropriate weight coefficient λ, thereby improving the accuracy of the force correction model and achieving boundary coordination of substructures.

[0047] If the boundaries between substructures are coordinated, then formula (10) can be transformed into Substituting formula (10) into formula (6), formula (6) becomes:

[0048]

[0049] 3. The force correction update iteration hybrid experimental method based on multi-task loading proposed in this invention develops an update iteration technique for the force correction model that avoids the computational time delay problem. The numerical substructure can be modeled in a refined manner, which improves the accuracy of the numerical substructure and reduces the error caused by model simplification.

[0050] 4. The force correction update iterative hybrid test method based on multi-task loading proposed in this invention achieves the goal of verifying the dynamic performance of multiple test substructures through multiple rounds of loading of a single test substructure. It effectively reduces the requirements for the operation technology of real-time hybrid test method and laboratory test conditions, reduces the dependence on real-time synchronous loading equipment, reduces the operation complexity, and saves test costs. Attached Figure Description

[0051] Figure 1 The flowchart is for a hybrid experimental method for force correction update iteration based on multi-task loading.

[0052] Figure 2The flowchart of the principle of the force correction update iteration hybrid test method based on multi-task loading (taking a seven-story frame vibration reduction / seismic structure with six seismic isolation bearings as an example);

[0053] Figure 3 The flowchart of the principle of the force correction update iteration hybrid test method based on multi-task loading (taking a four-span bridge vibration reduction / seismic structure with three viscous dampers installed as an example);

[0054] Figure 4 The flowchart of the principle of the force correction update iterative hybrid test method based on multi-task loading (taking a seven-story frame vibration reduction / seismic structure with seven viscous dampers installed as an example);

[0055] Figure 5 This is a flowchart of a hybrid experimental system for force correction update iteration based on multi-task loading. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of this invention clearer, the invention is described below with reference to specific embodiments shown in the accompanying drawings. However, it should be understood that these descriptions are merely exemplary and not intended to limit the scope of the invention. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concept of the invention.

[0057] It should also be noted that, in order to avoid obscuring the invention with unnecessary details, only the structures and / or processing steps closely related to the solution according to the invention are shown in the accompanying drawings, while other details that are not closely related to the invention are omitted. Specific implementation method one:

[0059] This embodiment provides only a preferred implementation method, which is a force correction update iterative hybrid experimental method based on multi-task loading. It establishes numerical models of the prototype structure's numerical substructure and the experimental substructure, solves the first-round motion equations to obtain loading commands, preprocesses the loading commands, and acquires experimental data (which can be, but is not limited to, displacement, force, acceleration, etc.). It establishes an update iterative equation for the force correction model parameters, updates the force correction model parameters in real time based on the previous round of experimental data, inputs the previous round's correction force, solves the updated motion equations, executes iterative loading, and collects experimental data. It determines whether the convergence index reaches the engineering accuracy threshold. If yes, the iteration terminates; otherwise, it iterates through updating the model parameters and loading commands until the convergence index reaches the engineering accuracy threshold. Specific Implementation Method Two:

[0061] This embodiment provides only a preferred implementation, wherein the force correction model parameters may, but are not limited to, the damping C of the test substructure. E Stiffness K EThe weighting coefficient λ is used to address the inconsistency between the reaction forces of the numerical substructure and the experimental substructure, thereby accelerating the iteration convergence speed. Specific implementation method three:

[0063] This embodiment provides only a preferred implementation method; specifically, as shown below... Figure 2 As shown, taking a high-rise vibration reduction / seismic structure with multiple seismic isolation bearings as an example, the basic principle and usage steps of the method of the present invention are explained. In this embodiment, when the prototype structure is a high-rise vibration reduction structure, the high-rise structure is taken as the numerical substructure, and a finite element software is used for refined modeling. One of the seismic isolation bearings is taken as the test substructure, and a servo loading system is used to load sequentially to carry out a force correction update iterative hybrid test based on multi-task loading. The specific process of the force correction update iterative hybrid test method includes:

[0064] S1. Establish a finite element model of a seven-story frame structure as the numerical model of the prototype structure's numerical substructure and the experimental substructure. Assume that the restoring force of the seismic isolation bearings is zero. Use the central difference method to solve the numerical simulation system to obtain the loading command for the first round of experiments.

[0065] The equation of motion can be expressed as:

[0066]

[0067] In the above formula, M, C, and K represent the mass matrix, damping matrix, and stiffness matrix of the numerical substructure, respectively. These represent the time-history acceleration matrix, time-history velocity matrix, and time-history displacement matrix of the numerical substructure at the i-th step of the first round, respectively. The numerical model of the experimental substructure represents the time-history reaction force in the first round; the subscript N represents the numerical substructure; i represents the integration time step; a g,i Represents earthquake acceleration excitation;

[0068] S2. Time delay compensation is applied to the loading command, and the compensated command is sent to the controller. The actuator executes the command on a single seismic isolation bearing, and finally, test data is collected, i.e., test data is obtained based on the time delay compensated loading command. The time delay compensation method refers to correcting the time delay between numerical calculation and physical loading through algorithms or control strategies to ensure real-time synchronization between the loading command and the structural response. The time delay compensation method adopts existing compensation methods, which can be, but are not limited to, using polynomial extrapolation or simpler first-order hysteresis compensation, such as the forward Euler method. The hybrid test needs to complete the "calculation-loading-feedback" closed loop in each integration step. Using time delay compensation can avoid data desynchronization due to delay.

[0069] S3. Establish update iterative equations for the parameters of the two force correction models, and calculate the damping C of the experimental substructure based on the experimental data.E and stiffness K E Meanwhile, the parameters of the force correction model are updated in real time. This invention provides two iterative equations for updating the parameters of the force correction model. The first one is performed by secant, and the second one is performed by tangent.

[0070] The update iterative equation for establishing the force correction model parameters can be:

[0071]

[0072] In the above formula, the superscript j represents the iteration number, and the value of j is not less than 2; λ represents the weight coefficient, and the range of λ is [0,1]; n represents the total number of integration steps; the subscript E represents the experimental substructure; the subscript m represents the measured value; v and d represent the time history velocity matrix and time history displacement matrix of the numerical substructure, respectively; i represents the integration time step; and F represents the time history reaction force.

[0073] The update iterative equation for establishing the force correction model parameters can also be:

[0074]

[0075] In the above formula, the value of j is 2;

[0076]

[0077] In the above formula, the value of j is not less than 3, and N represents the total number of iterations.

[0078] Specifically, formulas (13), (15), and (16) can be subject to a constraint in their implementation. Preferably, if in the s-th iteration (s≥3), or Therefore, the measured data in the s-th iteration will not be considered. For example, the model parameters in the s-th iteration will be updated to... and

[0079] S4. Input the test data collected in the previous round of testing into the numerical subframe structure, i.e., the (j-1)th round of test data. The data is the collected restoring force. Solve the equation of motion using the central difference method to obtain the displacement loading command for the seismic isolation bearing. Compensate the loading command using the time delay compensation method, and then send the compensated command to the controller. The actuator executes the command on a single seismic isolation bearing. Finally, collect the test data such as displacement and force. Among them, the correction force input and the equation of motion solved in the previous round are:

[0080]

[0081] In the above formula, The correction force representing the experimental substructure can be expressed by the following formula.

[0082]

[0083] Specifically, in the force correction update iterative hybrid test method based on multi-task loading, S2 and S4 above involve loading a small number of test substructures with a limited number of test loading devices. The seismic response of multiple test substructures in the prototype structure is reproduced through multi-task loading technology. For example, time history loading commands for the 1st, 2nd, ..., nth layers are sent to the controller one by one. Then, a set of actuators loads a single test substructure. Finally, the time history measured forces and displacements of the 1st, 2nd, ..., nth layers are collected respectively.

[0084] S5. Determine the weight coefficient λ in formula (7) using the experimental data and convergence index of two adjacent rounds;

[0085] S6, S3, S4, S5, the number of iterations is determined by the convergence index and the engineering accuracy threshold. Specific implementation method four:

[0087] This embodiment provides only a preferred implementation method. Specifically, the process for confirming the convergence index includes:

[0088]

[0089] In the above formula, q represents the qth experimental substructure. Specific implementation method five:

[0091] This embodiment provides only a preferred implementation. Specifically, before updating the force correction model parameters in real time based on the previous round of test data, it also includes using an optimization module to compare the damping C of the substructures in adjacent rounds of tests. E and stiffness K E To assess iterative convergence, a damping factor C with high iterative convergence efficiency is selected. E and stiffness K E To correct the current force model parameters, specifically, an optimization module is embedded in the numerical system, employing... Iterative convergence of computation and The iterative convergence is compared, and the former is discarded if its convergence efficiency is faster. Benefiting from the advantages of offline iterative hybrid experiments. Specific implementation method six:

[0093] This embodiment provides only a preferred implementation. After updating the force correction model parameters in real time based on the previous round of test data, it also includes correcting the measured data of the previous round of test substructure based on the difference between the measured data of the previous round of test substructure and the command data of the current round numerical substructure. Specifically, the measured force of the (j-1)th round of test substructure is corrected by using the difference between the measured data of displacement and velocity of the (j-1)th round of test substructure and the command data of displacement and velocity of the j-th round numerical substructure. Specific implementation method seven:

[0095] This embodiment provides only a preferred implementation: Specifically, in the first force correction test, i.e., the second round of the experiment, the weighting coefficient λ can be, but is not limited to, 0.5. In other rounds of the experiment, i.e., the j-th round of the experiment, the λ value with the fastest convergence efficiency is determined by calculating the convergence index.

[0096] Preferably, the λ parameter can be solved by numerically simulating the displacement d. N With experimentally measured displacement d Em Convergence analysis enables parameter optimization. Furthermore, in equations (19-1) and (20-1), the parameter λ ranges from [0,1], and its specific value can be dynamically determined based on the convergence characteristics of each iteration. This parameter is introduced to assess the dependence of the force-corrected surrogate model on the damping or stiffness characteristics of the experimental substructure. During the calculation, λ typically adopts an optimization strategy starting from 0 and gradually increasing to 1 in steps of 0.1 to obtain the optimal parameter value. Due to the independent nature of calculations in the offline RTHT numerical system, this module's calculation process consumes almost no additional resources. With a high-performance computer, this part of the calculation can be completed in a very short time, quickly determining the λ value for coordination and adaptation between substructures, improving the overall system matching efficiency, and directly obtaining the optimal λ value through numerical calculation, reducing experimental trial-and-error costs. In addition, this design allows convergence analysis of the weighting coefficient λ to be performed from the second iteration onwards.

[0097]

[0098] Detailed implementation method eight:

[0100] This embodiment provides only a preferred implementation. The invention has similar basic principles when applied to other large and complex vibration reduction structures; specifically, as shown... Figure 3As shown, taking a bridge vibration reduction / seismic structure as an example, the basic principle and usage steps of the method of this invention are explained. This embodiment provides a method for a four-span bridge vibration reduction / seismic structure where the bridge structure is taken as a numerical substructure, and refined modeling is performed using finite element software; one viscous damper is taken as the test substructure, and a servo loading system is used to sequentially load it, conducting a hybrid test based on multi-task loading and force correction update iteration. The specific test procedure is as follows:

[0101] Step 1: Establish a finite element model of the bridge structure. Assuming the restoring forces of the viscous dampers are all zero, use the central difference method to solve the numerical simulation system and obtain the loading commands for the first round of experiments. The equations of motion in Step 1 can be expressed as follows:

[0102]

[0103] In the above formula, M, C, and K are the mass matrix, damping matrix, and stiffness matrix of the bridge structure, respectively. These are the time-history acceleration matrix, time-history velocity matrix, and time-history displacement matrix of the bridge structure in the i-th step of the first round, respectively; the subscript N represents the bridge structure; i is the integration time step; a g,i It is an earthquake acceleration excitation.

[0104] Step 2: Perform time delay compensation on the displacement loading command, send the compensated command to the controller, and have the actuator execute the command on a single viscous damper. Finally, collect test data such as displacement and force.

[0105] Step 3: Calculate the damping C of the viscous damper using formula (22) or formulas (23) to (25). E and stiffness K E Simultaneously, the parameters of the force correction model are updated in real time; the formula for step three is expressed as follows:

[0106] The first method of updating model parameters, namely

[0107] In the j-th iteration (j≥2),

[0108]

[0109] In the above formula, λ is the weighting coefficient, and the range of λ is [0,1]; n is the total number of integration steps; the subscript E represents the viscous damper; the subscript m represents the measured value; and the superscript j represents the iteration round.

[0110] The second method for updating model parameters is as follows:

[0111] In the second iteration,

[0112]

[0113] In the j-th iteration (j≥3),

[0114]

[0115] In the above formula, N is the total number of iterations.

[0116] Specifically, formulas (22), (24), and (25) will also have a limitation in their implementation. If, in the s-th iteration, where s is not less than 3, or Therefore, the measured data in the s-th iteration will not be considered. For example, the model parameters in the s-th iteration will be updated to... and

[0117] Step 4: First, input the restoring force collected in the previous round, i.e., the j-1th round of the test, into the bridge structure. Solve the motion equation by the central difference method, i.e., formula (26), to obtain the displacement loading command of the viscous damper. Use the time delay compensation method to compensate the loading command. Then send the compensated command to the controller, and the actuator executes the command on a single viscous damper. Finally, collect the test data such as displacement and force.

[0118]

[0119] In the above formula, It is the correction force of the viscous damper (3), and the specific correction formula can be expressed as follows:

[0120]

[0121] Step 5: Determine the appropriate weight coefficient λ in formula (27) using the experimental data and convergence index of two adjacent rounds; specifically, λ in the second round can be set to 0.5.

[0122] Step Six: Repeat Steps Three, Four, and Five, determining the number of iterations based on the convergence metric and engineering accuracy requirements. The convergence metric can be expressed as follows:

[0123]

[0124] In the above formula, q refers to the q-th viscous damper, where the value of q is between 1 and 3. Specific implementation method nine:

[0126] This embodiment provides only a preferred implementation. The invention has similar basic principles when applied to other large and complex vibration reduction structures; specifically, as shown... Figure 4As shown, taking a frame vibration reduction / damping structure with seven viscous dampers as an example, the basic principle and usage steps of the method of the present invention are explained. In this embodiment, when the prototype structure is a frame vibration reduction / damping structure with seven viscous dampers, the frame structure is taken as the numerical substructure, and refined modeling is performed using finite element software; one of the viscous dampers is taken as the test substructure, and a servo loading system is used to load it sequentially, carrying out a force correction update iteration hybrid test based on multi-task loading. The specific test procedure is as follows:

[0127] Step 1: Establish the finite element model of the frame structure. Assuming the restoring forces of the viscous dampers are all zero, use the central difference method to solve the numerical simulation system and obtain the loading commands for the first round of experiments. The equations of motion in Step 1 can be expressed as follows:

[0128]

[0129] In the above formula, M, C, and K are the mass matrix, damping matrix, and stiffness matrix of the frame structure, respectively. These are the time-history acceleration matrix, time-history velocity matrix, and time-history displacement matrix of the frame structure at the i-th step of the first round, respectively; the subscript N represents the frame structure; i is the integration time step; a g,i It is an earthquake acceleration excitation.

[0130] Step 2: Perform time delay compensation on the displacement loading command, send the compensated command to the controller, and have the actuator execute the command on a single viscous damper. Finally, collect test data such as displacement and force.

[0131] Step 3: Calculate the damping C of the viscous damper using formula (32) or formulas (33) to (35). E and stiffness K E Simultaneously, the parameters of the force correction model are updated in real time; the formula for step three is expressed as follows:

[0132] The first method of updating model parameters, namely

[0133] In the j-th iteration (j≥2),

[0134]

[0135] In the above formula, λ is the weighting coefficient, and the range of λ is [0,1]; n is the total number of integration steps; the subscript E represents the viscous damper; the subscript m represents the measured value; and the superscript j represents the iteration round.

[0136] The second method for updating model parameters is as follows:

[0137] In the second iteration,

[0138]

[0139] In the j-th iteration (j≥3),

[0140]

[0141] In the above formula, N is the total number of iterations.

[0142] Specifically, formulas (32), (34), and (35) will also have a constraint in their implementation. If in the s-th iteration, where s is not less than 3, or Therefore, the measured data in the s-th iteration will not be considered. For example, the model parameters in the s-th iteration will be updated to... and

[0143] Step 4: First, input the restoring force collected in the previous round, i.e., the (j-1)th round of the test, into the frame structure. Solve the motion equation using the central difference method, i.e., formula (36), to obtain the displacement loading command of the viscous damper. Compensate the loading command using the time delay compensation method, and then send the compensated command to the controller. The actuator executes the command on a single viscous damper, and finally collects test data such as displacement and force.

[0144]

[0145] In the formula, It is the correction force of the viscous damper (3), and the specific correction formula can be expressed as follows:

[0146]

[0147] Step 5: Determine the appropriate weight coefficient λ in formula (37) using the experimental data and convergence index of two adjacent rounds; specifically, λ in the second round can be set to 0.5.

[0148] Step Six: Repeat steps Three, Four, and Five of this embodiment, determining the number of iterations based on the convergence metric and engineering accuracy requirements. The convergence metric can be expressed as follows:

[0149]

[0150] In the above formula, q refers to the q-th viscous damper, where the value of q is between 1 and 7. Specific Implementation Method Ten:

[0152] This embodiment provides only a preferred implementation. The present invention provides a force correction update iteration hybrid experimental system based on multi-task loading, such as... Figure 5 As shown, the method applied to the force correction update iterative hybrid test includes:

[0153] The numerical simulation module is used to establish numerical models of the prototype structure's numerical substructures and the experimental substructures.

[0154] The test loading module, including actuators, controllers, and time delay compensation units, is used to execute loading commands and collect test data.

[0155] The parameter update module is used to calculate the force correction model parameters and weight coefficients in real time based on the experimental data.

[0156] The convergence determination module is used to determine the number of iterations based on the convergence index and the engineering accuracy threshold. Detailed implementation method eleven:

[0158] This embodiment provides only a preferred implementation method. This implementation method is a storage medium that stores at least one instruction. The at least one instruction is loaded and executed by a processor to implement the above-mentioned time-varying parameter identification method. The storage medium described in this embodiment includes, but is not limited to, hard disks, USB flash drives, embedded system storage instruction sets, etc., which support real-time data processing and parameter updates. Detailed Implementation Method Twelve:

[0160] This embodiment provides only a preferred implementation. This embodiment is a force correction update iteration hybrid test device based on multi-task loading. The force correction update iteration hybrid test device based on multi-task loading includes a processor, a memory, and a sensor array. The memory stores at least one of the above-mentioned instructions. The sensor array collects response data in real time. The processor loads and executes the instructions to implement the above-mentioned force correction update iteration hybrid test method based on multi-task loading and outputs an early warning signal. The force correction update iteration hybrid test device may, but is not limited to, integrate a multi-channel data acquisition module, an edge computing unit, and a 4G communication module to realize "end-cloud" collaborative early warning. The device mentioned in this embodiment includes, but is not limited to, mobile devices, workstations, etc.

[0161] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A hybrid experimental method for force correction update iteration based on multi-task loading, characterized in that: The force correction update iterative hybrid test method involves establishing numerical models of the prototype structure's numerical substructure and the test substructure, solving the first round of motion equations to obtain loading commands, preprocessing the loading commands and acquiring test data, establishing update iterative equations for the force correction model parameters, updating the force correction model parameters in real time based on the previous round of test data, inputting the previous round of correction force, solving the updated motion equations, executing iterative loading and collecting test data, and determining whether the convergence index reaches the engineering accuracy threshold. If so, the iteration is terminated. If not, the process of updating model parameters and loading commands in a loop continues until the convergence index reaches the engineering accuracy threshold. The force correction model parameters include the damping C of the experimental substructure. E Stiffness K E and the weighting coefficient λ value; The force correction update iterative hybrid experimental method includes: S1. Establish numerical models of the prototype substructure and the experimental substructure, solve the first round of motion equations, and obtain loading commands, including the loading commands for the first round of experiments: The equation of motion can be expressed as: （1） In the above formula, These represent the mass matrix, damping matrix, and stiffness matrix of the numerical substructure, respectively. These represent the time-history acceleration matrix, time-history velocity matrix, and time-history displacement matrix of the numerical substructure in the first round and the i-th step, respectively. The numerical model of the experimental substructure represents the time-history reaction force in the first round; the subscript N represents the numerical substructure; i represents the integration time step; Represents earthquake acceleration excitation; S2. Perform time delay compensation on the loading command, and obtain test data based on the time delay compensated loading command; S3. Establish update iterative equations for the parameters of the two force correction models, and calculate the damping C of the experimental substructure based on the experimental data. E and stiffness K E : The update iterative equation for the force correction model parameters is as follows: （2） In the above formula, the superscript Represents the iteration round, The value of is not less than 2. Represents the weighting coefficient. The range is [0,1]; n represents the total number of integration steps; subscript E represents the experimental substructure; subscript m represents the measured value; v and d represent the time history velocity matrix and time history displacement matrix of the numerical substructure, respectively; i represents the integration time step; F represents the time history reaction force; The update iterative equation for the parameters of the established force correction model is also: （3） In the above formula, The value of is 2; （4） （5） In the above formula, The value of is not less than 3, and N represents the total number of iterations; S4. Input the experimental data collected in the previous round of experiments into the numerical substructure, solve the motion equations to obtain a new loading command, perform time delay compensation on the loading command, and obtain new experimental data; The previous round of corrective force input and solution of the motion equations are as follows: （6） In the above formula, The correction force representing the experimental substructure can be expressed by the following formula. （7） S5. Determine the weight coefficient λ in formula (7) using the experimental data and convergence index of two adjacent rounds; S6, S3, S4, S5, the number of iterations is determined by the convergence index and the engineering accuracy threshold.

2. The force correction update iterative hybrid experimental method based on multi-task loading according to claim 1, characterized in that: The process for confirming the convergence metric includes: （8） （9） In the above formula, q represents the qth experimental substructure.

3. The force correction update iterative hybrid experimental method based on multi-task loading according to claim 2, characterized in that: Before updating the force correction model parameters in real time based on the previous round of test data, the process also includes using an optimization module to compare the damping C of the substructures in adjacent rounds of tests. E and stiffness K E To assess iterative convergence, a damping factor C with high iterative convergence efficiency is selected. E and stiffness K E The model parameters are corrected for the current force.

4. The force correction update iterative hybrid experimental method based on multi-task loading according to claim 3, characterized in that: The process of updating the force correction model parameters in real time based on the previous round of test data also includes correcting the measured data of the previous round of test substructure based on the difference between the measured data of the previous round of test substructure and the instruction data of the current round of test value substructure.

5. A hybrid experimental method for force correction update iteration based on multi-task loading according to any one of claims 1 to 4, characterized in that: In the first iteration, i.e. the second round of correction, the weight coefficient λ is 0.5; in other rounds, the weight coefficient λ is determined by calculating the value of the convergence index.

6. A force correction update iterative hybrid test system based on multi-task loading, applied to the force correction update iterative hybrid test method according to any one of claims 1 to 5, characterized in that, include: The numerical simulation module is used to establish numerical models of the prototype structure's numerical substructures and the experimental substructures. The test loading module, including actuators, controllers, and time delay compensation units, is used to execute loading commands and collect test data. The parameter update module is used to calculate the force correction model parameters and weight coefficients in real time based on the experimental data. The convergence determination module is used to determine the number of iterations based on the convergence index and the engineering accuracy threshold.

7. A storage medium, characterized in that, The storage medium stores at least one instruction, which is loaded and executed by a processor to implement the force correction update iterative hybrid test method as described in any one of claims 1 to 5.

8. A force correction update iteration hybrid test device based on multi-task loading, characterized in that, The force correction update iterative hybrid test device based on multi-task loading includes a processor, a memory, and a sensor array. The memory stores at least one instruction as described in claim 7, the sensor array stores test data, and the processor loads and executes the instruction to implement the force correction update iterative hybrid test method based on multi-task loading as described in any one of claims 1 to 5.

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