A pre-test system and method for maglev vehicle-bridge hybrid test

Abstract

The present invention discloses a pre-test system and method for a maglev vehicle-bridge hybrid test. The system includes a numerical vehicle model, a numerical bridge model, a controller model, a boundary coordination module, a vibration table model, a virtual electromagnet, and a hybrid test verification module. The hybrid test verification module verifies the numerical vehicle and bridge models. The numerical vehicle model provides vehicle parameters. The numerical bridge model simulates vehicle speed and preset initial external forces, which are processed into deformation data by the boundary coordination module. The controller model compensates for time lags in this deformation data and inputs it into two vibration table models, a numerical vibration table and a vibration table transfer function, to obtain displacement data. The virtual electromagnet applies the displacement data to the numerical vehicle model. The numerical vehicle model converts the displacement data into force data. The numerical bridge model simulates based on this force data. These steps are repeated to obtain test results. Based on the hybrid test logic, the pre-test system completes a test run under operating conditions, tests the hybrid test algorithm and model, and ensures test accuracy.

Description

Technical Field

[0001] The present invention belongs to the technical field of magnetic levitation vehicle-bridge hybrid testing, and in particular relates to a pre-test system and method for a magnetic levitation vehicle-bridge hybrid testing. Background Art

[0002] The development of rail transit has always been aimed at achieving high-speed operation while maintaining safety and comfort. In conventional wheel-rail railways, support, traction, and braking forces all rely on wheel-rail contact, resulting in a speed limit imposed by the wheel-rail adhesion limit. Maglev trains, on the other hand, utilize electromagnetic forces instead of contact forces for support, traction, and braking, thus overcoming the adhesion limit and making them more suitable for high-speed operation. High-speed maglev trains are a new type of high-speed transportation with promising application prospects, and are becoming a research hotspot.

[0003] Real-time hybrid testing (RTHS) is a novel testing method that combines numerical simulation with physical testing to test the dynamic performance of structures. RTHS has been applied to the study of high-speed railway train-bridge coupled vibration. Using the bridge as the numerical substructure and the train as the experimental substructure, the two substructures interact with each other in real time, enabling on-board testing within limited laboratory space. Under limited funding and space, it can obtain more accurate responses than purely numerical simulation studies, providing a valuable reference for the research and design of high-speed trains and bridges. Real-time hybrid testing accurately reflects the performance and response of the specimen, including its inertia, damping, and restoring forces, making it ideal for in-depth study of complex components. It is currently the most effective and accurate testing method for speed-dependent components. Furthermore, because the experimental substructure is a partial component of the overall structure, real-time hybrid testing requires minimal testing space and equipment, making it economical. Currently, the study of train-bridge coupled vibration is primarily conducted using a hybrid testing approach combining field testing and numerical simulation. However, field tests require the actual establishment of driving routes, which carries a heavy economic burden; numerical simulations are based on multiple assumptions, and their calculation results have large errors, which cannot guarantee the safety of hybrid tests. Summary of the Invention

[0004] In order to remedy the defects of the prior art, the present invention provides a pre-test system and method for a magnetic levitation vehicle-bridge hybrid test.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] In a first aspect, a pre-test system for a maglev vehicle-bridge hybrid test is provided, comprising:

[0007] Numerical vehicle model, numerical bridge model, controller model, boundary coordination module, shaking table model, virtual electromagnet, hybrid test verification module;

[0008] The numerical vehicle model, established by simulation software such as Simpack, is used to provide load excitation to the numerical bridge model and also to simulate the driving speed of the real maglev vehicle;

[0009] The numerical bridge model is used to receive load excitation and vehicle speed, obtain internal excitation of the bridge, and obtain bridge deformation data through an integration algorithm based on the load excitation, vehicle speed and internal excitation of the bridge;

[0010] The boundary coordination module is used to convert bridge deformation data into vibration test bench operation signals and solve them in real time to obtain segmented straight lines, thereby accurately fitting the curved operating conditions of the train line;

[0011] The controller model is used to process the vibration test bench operating signal with a time-delay compensation algorithm, input it into the vibration table model for simulation to obtain displacement data, and apply the displacement data to the numerical vehicle model through a virtual electromagnet;

[0012] The numerical vehicle model is also used to convert displacement data into vertical force data and lateral force data;

[0013] The numerical bridge model is also used to perform cyclic simulations based on vertical force data, lateral force data, and vehicle speed to obtain preliminary experimental results for the maglev vehicle-bridge hybrid test.

[0014] The vibration table model includes a numerical vibration table modeled by the mechanism and a vibration table transfer function identified by measured data. The numerical vibration table and the vibration table transfer function are circulated separately based on the hybrid test logic.

[0015] The hybrid test verification module includes a vehicle model verification unit, a numerical bridge model verification unit, and a numerical vehicle-numerical bridge driving simulation test unit;

[0016] Vehicle model verification unit, used to verify the accuracy of the numerical vehicle model imported before the test;

[0017] Numerical bridge model verification unit, used to verify the accuracy of the numerical bridge model imported before the test;

[0018] Numerical vehicle-numeric bridge driving simulation test unit, used for real-time verification of driving simulation test;

[0019] The hybrid test verification module is used to analyze the consistency between the vibration table command of the numerical vibration table and the vibration table response of the vibration table transfer function to determine the correctness of the hybrid test.

[0020] Furthermore, the system also includes:

[0021] The numerical bridge model construction module is used to process the ordinary steel bars and prestressed steel strands of the solid unit bridge using the refined modeling method, prestress the beam elements of the solid unit bridge using the equivalent load method, and process the ordinary steel bars using the equivalent section method to construct a numerical bridge model corresponding to the solid unit bridge.

[0022] Furthermore, the system also includes:

[0023] The numerical vehicle model construction module is used to obtain vehicle data of a real maglev vehicle and construct a numerical vehicle model based on the vehicle data.

[0024] Furthermore, the numerical bridge model verification unit is specifically used to compare the vertical frequencies of different beam units and corresponding solid units when establishing solid units of different beam units and corresponding solid units of the bridge during the construction of the numerical bridge model. If the vertical frequency difference is greater than the preset frequency threshold, the accuracy verification of the numerical bridge model fails; if the vertical frequency difference is not greater than the preset frequency threshold, the accuracy verification of the numerical bridge model passes.

[0025] Furthermore, the numerical vehicle-numerical bridge driving simulation test unit is specifically used to import the verified numerical bridge model into the simulation software, jointly simulate the numerical bridge model and the numerical vehicle model through the simulation software, input a constant force of the same magnitude to perform concentrated force bridge crossing analysis, and analyze the relative error of the vertical displacement of the vehicle-bridge connection point calculated at different speeds. If the relative error does not exceed the error threshold, it is determined that the real-time verification of the driving simulation test has passed; if the relative error exceeds the error threshold, it is determined that the real-time verification of the driving simulation test has failed.

[0026] Furthermore, the bridge deformation data is deformation data of three degrees of freedom, and the bridge deformation data includes bridge vertical deformation data, bridge torsional deformation data and bridge bending deformation data.

[0027] Furthermore, the numerical vibration table is a three-degree-of-freedom model.

[0028] Furthermore, the boundary coordination module is specifically used to perform linear fitting of the three-degree-of-freedom deformation data in the bridge deformation data using the boundary coordination algorithm, obtain the three-degree-of-freedom vibration test bench operation signal of the vibration table model, and solve in real time to obtain the segmented straight line, thereby fitting the curved operating conditions of the train line with high precision.

[0029] Furthermore, the controller model is specifically used to process the operating signal of the three-degree-of-freedom vibration test bench using a time-delay compensation algorithm to obtain predicted data. After inputting the predicted data into the vibration table model for simulation, the displacement data of the virtual electromagnet is obtained to realize the time-delay compensation process. The evaluation index time-delay and mean square error test algorithm are used to determine whether the preset compensation and control effects can be achieved.

[0030] In a second aspect, a pre-test method for a maglev vehicle-bridge hybrid test is provided, which is applied to the pre-test system for the maglev vehicle-bridge hybrid test in the first aspect, and the method includes:

[0031] S1, the numerical vehicle model provides load excitation to the numerical bridge model and simulates the driving speed of the real maglev vehicle;

[0032] S2, the numerical bridge model receives load excitation and driving speed, obtains the internal excitation of the bridge, and obtains the bridge deformation data through the integration algorithm based on the load excitation, driving speed and internal excitation of the bridge;

[0033] S3, the boundary coordination module converts bridge deformation data into vibration test bench operation signals and solves them in real time to obtain segmented straight lines, thereby accurately fitting the curve conditions of train line operation;

[0034] S4, the controller model processes the vibration test bench operating signal using a time-delay compensation algorithm, inputs the signal into the vibration table model for simulation to obtain displacement data, and applies the displacement data to the numerical vehicle model through a virtual electromagnet;

[0035] S5, the numerical vehicle model converts the displacement data into vertical force data and lateral force data;

[0036] S6, numerical bridge model data is simulated based on vertical force data, lateral force data and driving speed to obtain preliminary experimental results of the maglev vehicle-bridge hybrid test;

[0037] S7, the hybrid test verification module analyzes the consistency between the vibration table command of the numerical vibration table and the vibration table response of the vibration table transfer function to determine the correctness of the hybrid test; verifies the accuracy of the imported numerical vehicle model and numerical bridge model before the test; and verifies the real-time performance of the numerical vehicle-numerical bridge driving simulation test.

[0038] The beneficial effects achieved by the present invention are:

[0039] The numerical vehicle model provides load excitation to the bridge model; the numerical bridge model simulates the load excitation, driving speed and internal excitation of the bridge (different types of excitation such as line irregularities) of the numerical vehicle model to obtain bridge deformation data; the boundary coordination module converts the bridge deformation data into the vibration test bench operation signal, and solves it in real time to obtain a segmented straight line, thereby fitting the curve working condition of the train line with high precision; the controller model processes the vibration test bench operation signal with a time-delay compensation algorithm, and inputs it into the vibration table model for simulation to obtain displacement data, and the displacement data is applied to the numerical vehicle model through a virtual electromagnet; the numerical vehicle model converts the displacement data into the vibration test bench operation signal. The data is converted into vertical and lateral force data. The numerical bridge model is simulated based on the vertical and lateral force data and driving speed to obtain preliminary experimental results for the maglev vehicle-bridge hybrid test. Before the test, the hybrid test verification module verifies the numerical vehicle model and the numerical bridge model to ensure the accuracy of the imported models. A driving simulation test is performed on the numerical vehicle-bridge hybrid model to ensure the real-time performance of the driving simulation calculation. By comparing the numerical vibration table model based on the mechanism model and the vibration table transfer function identified from the measured data through a process cycle test, the consistency of the test vibration table commands and vibration table responses is analyzed to determine the correctness of the hybrid test. Compared with existing hybrid tests, the initial real-time driving simulation test of the numerical vehicle model and the numerical bridge model ensures the accuracy of the imported models and the real-time driving simulation calculation. At the same time, hybrid experiments based on the numerical vibration table and the vibration transfer function are conducted respectively, thus pre-verifying the accuracy of the maglev vehicle-bridge hybrid test. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a structural diagram of a pre-test system for a maglev vehicle-bridge hybrid test according to the present invention;

[0041] Figure 2 The figure is a flow chart of the pre-test method of the magnetic levitation vehicle-bridge hybrid test of the present invention. DETAILED DESCRIPTION

[0042] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention.

[0043] Before conducting an overall closed-loop real-time hybrid test of traffic on an actual bridge, it is necessary to conduct a closed-loop hybrid test simulation based on a numerical vibration table and complete a trial run of all working conditions to ensure stable testing under any working conditions and provide a reference for the actual overall hybrid closed-loop hybrid test of traffic on the bridge.

[0044] like Figure 1 As shown, an embodiment of the present invention provides a pre-test system for a magnetic levitation vehicle-bridge hybrid test, comprising:

[0045] Numerical vehicle model 101, numerical bridge model 102, controller model 103, boundary coordination module 104, shaking table model 105, virtual electromagnet 106, hybrid test verification module 107;

[0046] The numerical vehicle model 101 is established by simulation software such as Simpack and is used to provide load excitation to the numerical bridge model 102 and also to simulate the driving speed of a real maglev vehicle;

[0047] The numerical bridge model 102 is used to receive load excitation and vehicle speed, obtain internal excitation of the bridge, and obtain bridge deformation data through an integration algorithm based on the load excitation, vehicle speed and internal excitation of the bridge;

[0048] Boundary coordination module 104, used to convert bridge deformation data into vibration test bench operation signals and solve in real time to obtain piecewise straight lines, thereby fitting the curve conditions of train line operation with high precision;

[0049] The controller model 103 is used to process the vibration test bench operation signal with a time-delay compensation algorithm, input the signal into the vibration table model 105 for simulation to obtain displacement data, and apply the displacement data to the numerical vehicle model 101 through the virtual electromagnet 106;

[0050] The numerical vehicle model 101 is also used to convert the displacement data into vertical force data and lateral force data;

[0051] The numerical bridge model 102 is also used to perform cyclic simulation based on vertical force data, lateral force data and driving speed to obtain preliminary experimental results of the maglev vehicle-bridge hybrid test;

[0052] The vibration table model 105 includes a numerical vibration table modeled by the mechanism and a vibration table transfer function identified by measured data, and the numerical vibration table and the vibration table transfer function are respectively cycled based on the hybrid test logic;

[0053] The hybrid test verification module 107 includes a vehicle model verification unit, a numerical bridge model verification unit, and a numerical vehicle-numerical bridge driving simulation test unit;

[0054] A vehicle model verification unit, used to verify the accuracy of the numerical vehicle model 101 imported before the test;

[0055] a numerical bridge model verification unit, for verifying the accuracy of the numerical bridge model 102 imported before the test;

[0056] Numerical vehicle-numeric bridge driving simulation test unit, used for real-time verification of driving simulation test;

[0057] The hybrid test verification module 107 is used to analyze the consistency between the vibration table command of the numerical vibration table and the vibration table response of the vibration table transfer function to determine the correctness of the hybrid test.

[0058] The implementation principle of the embodiment of the present invention is:

[0059] The numerical vehicle model provides load excitation to the bridge model; the numerical bridge model simulates the load excitation, driving speed and internal excitation of the bridge (different types of excitation such as line irregularities) of the numerical vehicle model to obtain bridge deformation data; the boundary coordination module converts the bridge deformation data into the vibration test bench operation signal, and solves it in real time to obtain a segmented straight line, thereby fitting the curve working condition of the train line with high precision; the controller model processes the vibration test bench operation signal with a time-delay compensation algorithm, and inputs it into the vibration table model for simulation to obtain displacement data, and the displacement data is applied to the numerical vehicle model through a virtual electromagnet; the numerical vehicle model converts the displacement data into the vibration test bench operation signal. The data is converted into vertical and lateral force data. The numerical bridge model is simulated based on the vertical and lateral force data and driving speed to obtain preliminary experimental results for the maglev vehicle-bridge hybrid test. Before the test, the hybrid test verification module verifies the numerical vehicle model and the numerical bridge model to ensure the accuracy of the imported models. A driving simulation test is performed on the numerical vehicle-bridge hybrid model to ensure the real-time performance of the driving simulation calculation. By comparing the numerical vibration table model based on the mechanism model and the vibration table transfer function identified from the measured data through a process cycle test, the consistency of the test vibration table commands and vibration table responses is analyzed to determine the correctness of the hybrid test. Compared with existing hybrid tests, the initial real-time driving simulation test of the numerical vehicle model and the numerical bridge model ensures the accuracy of the imported models and the real-time driving simulation calculation. At the same time, hybrid experiments based on the numerical vibration table and the vibration transfer function are conducted respectively, thus pre-verifying the accuracy of the maglev vehicle-bridge hybrid test.

[0060] Preferably, in some embodiments of the present invention, the pre-test system for the maglev vehicle-bridge hybrid test further includes:

[0061] The numerical bridge model construction module is used to process the ordinary steel bars and prestressed steel strands of the solid unit bridge using the refined modeling method, prestress the beam elements of the solid unit bridge using the equivalent load method, and process the ordinary steel bars using the equivalent section method to construct a numerical bridge model corresponding to the solid unit bridge.

[0062] Since ordinary steel bars and prestressed steel strands can withstand different forces in solid unit bridges, it is necessary to use a refined modeling method to process ordinary steel bars and prestressed steel strands, and use the equivalent load method to prestress the beam elements of the solid unit bridge, and use the equivalent section method to process ordinary steel bars, so as to construct a numerical bridge model corresponding to the solid unit bridge.

[0063] Preferably, in some embodiments of the present invention, the pre-test system for the maglev vehicle-bridge hybrid test further includes:

[0064] The numerical vehicle model construction module is used to obtain vehicle data of a real maglev vehicle and construct a numerical vehicle model based on the vehicle data.

[0065] When a real maglev vehicle passes through a solid unit bridge, the electromagnetic force generated by the real maglev vehicle is continuous. The electromagnetic force is simplified into a certain number of concentrated forces, such as establishing four vertical force elements and four horizontal force elements between the suspension frame and the connecting frame and the track of the solid unit bridge, thereby constructing a numerical vehicle model.

[0066] It should be noted that when a real maglev vehicle passes over a solid unit bridge, the gravity of the suspension system, including the maglev vehicle, suspension frame, and electromagnets, serves as the preset initial external force. As the maglev vehicle gradually increases in speed, the electromagnetic force between the electromagnets and the wheel rails excites the bridge, causing vertical, torsional, and bending deformations. This means that the current bridge deformation data, given the current vehicle speed, represents three degrees of freedom (DOF) deformation: vertical, torsional, and bending. The numerical shaking table is a three-DOF model.

[0067] Preferably, in some embodiments of the present invention,

[0068] The numerical bridge model verification unit is specifically used to compare the vertical frequencies of different beam units and corresponding solid units when establishing the solid units of different solid units in the process of constructing the numerical bridge model. If the vertical frequency difference is greater than the preset frequency threshold, the accuracy verification of the numerical bridge model fails; if the vertical frequency difference is not greater than the preset frequency threshold, the accuracy verification of the numerical bridge model passes.

[0069] Preferably, in some embodiments of the present invention,

[0070] The numerical vehicle-numerical bridge driving simulation test unit is specifically used to import the verified numerical bridge model into the simulation software, jointly simulate the numerical bridge model and the numerical vehicle model through the simulation software, input a constant force of the same magnitude to perform concentrated force bridge crossing analysis, and analyze the relative error of the vertical displacement of the vehicle-bridge connection point calculated at different speeds. If the relative error does not exceed the error threshold, it is determined that the real-time verification of the driving simulation test has passed; if the relative error exceeds the error threshold, it is determined that the real-time verification of the driving simulation test has failed.

[0071] Preferably, in some embodiments of the present invention,

[0072] The boundary coordination module is specifically used to perform linear fitting of the three-degree-of-freedom deformation data in the bridge deformation data using the boundary coordination algorithm, obtain the three-degree-of-freedom vibration test bench operation signal of the vibration table model, and solve it in real time to obtain the segmented straight line, thereby fitting the curved operating conditions of the train line with high precision.

[0073] Preferably, in some embodiments of the present invention,

[0074] The controller model is specifically used to process the operating signal of the three-degree-of-freedom vibration test bench using a time-delay compensation algorithm to obtain predicted data. After inputting the predicted data into the vibration table model for simulation, the displacement data of the virtual electromagnet is obtained to realize the time-delay compensation process. The evaluation index time-delay and mean square error test algorithm are used to determine whether the preset compensation and control effects can be achieved.

[0075] The numerical vibration table is a mechanical modeling of the main components of the actual vibration table, such as the electro-hydraulic servo valve, piston, hydraulic cylinder (motor), and other hardware. Pulsar software is used to comprehensively consider frequency response, transient response, linearity, rated speed, resolution, hysteresis, zero drift displacement, maximum output force, and stroke. First, system identification is performed and white noise testing is conducted. Based on a sampling rate of 1024Hz, a high-order state space three-input and three-output simulation model is established. The degree of fit is evaluated using the formula to obtain the Z-axis fit, Pitch fit, and Roll fit. By comparing the output data of the simulation model with the output data of the actual vibration table, the accuracy of the numerical vibration table can be evaluated.

[0076] The controller model is designed based on a numerical vibration table. Pure numerical simulation is performed on the Matlab platform. White noise of specified time, frequency, and amplitude is loaded onto the numerical vibration table. The appropriate number of poles and zeros is selected to ensure accuracy. The time-history signal of the response is measured, and the transfer function of the vibration table is identified based on the time-history signal. The control model can be built through a simulation platform (for example, the Matlab / Simulink platform). The input three-degree-of-freedom table midpoint data is passed through a time-delay compensator to perform a time-delay compensation algorithm to obtain predicted data. After the data is sent to the numerical vibration table for simulation through the controller model, the long stator displacement data is fed back to the controller model to achieve a closed loop of the time-delay compensation process. The evaluation indicators time-delay and mean square error test algorithm can be used to determine whether the ideal compensation and control effect is achieved. Assuming that the time-delay compensation algorithm uses a model-predictive control system MPC, then the time-delay compensation algorithm, the numerical vibration table, and the controller model are all Simulink models.

[0077] The time-delay compensation algorithm and the numerical vibration table can also be simulated and tested. The input is directly replayed without forming a closed loop, and the time-delay and root mean square error are analyzed to ensure that the same Simulink model can be correctly calculated on the Concurrent platform. Then, a time-delay compensation closed-loop simulation test is performed. The numerical bridge model, virtual electromagnet, and numerical vibration table are input. Two time-delay compensation algorithms, adaptive time series (ATS) and model predictive control system (MPC), are used respectively. The appropriate step size and quantitative indicators (such as time-delay, root mean square error, and peak error) are selected. The output simulation results of the three degrees of freedom of the numerical vibration table are analyzed to obtain the simulation effect of the Concurrent platform to ensure that the Concurrent platform can correctly and real-timely implement the algorithm simulation on the Simulink platform.

[0078] The virtual electromagnet's inputs and outputs are two displacement signal inputs and two magnetic levitation force outputs. At the beginning of the simulation, the train's gravity is applied to the bridge. After solving the bridge's numerical model, the bridge's response at each point under a single electromagnet is obtained. The bridge responses are linearly interpolated and input into the boundary coordination algorithm. The displacement of the vibration table's midpoint is then processed by the time-delay compensation algorithm and then sent to the numerical vibration table. The numerical vibration table then outputs the long stator displacement data and feeds it back to the virtual electromagnet. The virtual electromagnet then outputs an electromagnetic force, which, along with the current vehicle speed data, is input into the numerical bridge model, completing a preliminary test of the maglev vehicle-bridge hybrid test. After the current moment, preliminary tests of the maglev vehicle-bridge hybrid test are conducted at predetermined intervals to provide complete preliminary results for the entire hybrid test.

[0079] In the above embodiments, a pre-test system for a maglev vehicle-bridge hybrid test is described. The following describes a pre-test method for a maglev vehicle-bridge hybrid test applied to the pre-test system for a maglev vehicle-bridge hybrid test through an embodiment.

[0080] like Figure 2 As shown, an embodiment of the present invention provides a pre-test method for a magnetic levitation vehicle-bridge hybrid test, comprising:

[0081] S1, the numerical vehicle model provides load excitation to the numerical bridge model and simulates the driving speed of the real maglev vehicle;

[0082] S2, the numerical bridge model receives load excitation and driving speed, obtains the internal excitation of the bridge, and obtains the bridge deformation data through the integration algorithm based on the load excitation, driving speed and internal excitation of the bridge;

[0083] S3, the boundary coordination module converts bridge deformation data into vibration test bench operation signals and solves them in real time to obtain segmented straight lines, thereby accurately fitting the curve conditions of train line operation;

[0084] S4, the controller model processes the vibration test bench operating signal using a time-delay compensation algorithm, inputs the signal into the vibration table model for simulation to obtain displacement data, and applies the displacement data to the numerical vehicle model through a virtual electromagnet;

[0085] S5, the numerical vehicle model converts the displacement data into vertical force data and lateral force data;

[0086] S6, numerical bridge model data is simulated based on vertical force data, lateral force data and driving speed to obtain preliminary experimental results of the maglev vehicle-bridge hybrid test;

[0087] S7, the hybrid test verification module analyzes the consistency between the vibration table command of the numerical vibration table and the vibration table response of the vibration table transfer function to determine the correctness of the hybrid test; verifies the accuracy of the imported numerical vehicle model and numerical bridge model before the test; and verifies the real-time performance of the numerical vehicle-numerical bridge driving simulation test.

[0088] The implementation principle of the embodiment of the present invention is:

[0089] The numerical vehicle model provides load excitation to the bridge model; the numerical bridge model simulates the load excitation, driving speed and internal excitation of the bridge (different types of excitation such as line irregularities) of the numerical vehicle model to obtain bridge deformation data; the boundary coordination module converts the bridge deformation data into the vibration test bench operation signal, and solves it in real time to obtain a segmented straight line, thereby fitting the curve working condition of the train line with high precision; the controller model processes the vibration test bench operation signal with a time-delay compensation algorithm, and inputs it into the vibration table model for simulation to obtain displacement data, and the displacement data is applied to the numerical vehicle model through a virtual electromagnet; the numerical vehicle model converts the displacement data into the vibration test bench operation signal. The data is converted into vertical and lateral force data. The numerical bridge model is simulated based on the vertical and lateral force data and driving speed to obtain preliminary experimental results for the maglev vehicle-bridge hybrid test. Before the test, the hybrid test verification module verifies the numerical vehicle model and the numerical bridge model to ensure the accuracy of the imported models. A driving simulation test is performed on the numerical vehicle-bridge hybrid model to ensure the real-time performance of the driving simulation calculation. By comparing the numerical vibration table model based on the mechanism model and the vibration table transfer function identified from the measured data through a process cycle test, the consistency of the test vibration table commands and vibration table responses is analyzed to determine the correctness of the hybrid test. Compared with existing hybrid tests, the initial real-time driving simulation test of the numerical vehicle model and the numerical bridge model ensures the accuracy of the imported models and the real-time driving simulation calculation. At the same time, hybrid experiments based on the numerical vibration table and the vibration transfer function are conducted respectively, thus pre-verifying the accuracy of the maglev vehicle-bridge hybrid test.

[0090] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0091] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1A device that provides the functions specified in a block or multiple blocks.

[0092] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0093] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0094] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are included in the scope of the claims of the present invention to be approved.

Claims

1. A pre-test system for a maglev vehicle-bridge hybrid test, characterized in that: include: Numerical vehicle model, numerical bridge model, controller model, boundary coordination module, shaking table model, virtual electromagnet, hybrid test verification module; The numerical vehicle model is established by Simpack simulation software and is used to provide load excitation to the numerical bridge model and to simulate the driving speed of a real maglev vehicle; The numerical bridge model is used to receive the load excitation and the driving speed, obtain the internal excitation of the bridge, and obtain bridge deformation data through an integration algorithm based on the load excitation, the driving speed and the internal excitation of the bridge; The boundary coordination module is used to convert the bridge deformation data into a vibration test bench operation signal and solve it in real time to obtain a piecewise straight line, thereby fitting the curve operating conditions of the train line with high precision; The controller model is used to process the operating signal of the vibration test bench using a time-delay compensation algorithm, input the processed signal into the vibration table model for simulation to obtain displacement data, and apply the displacement data to the numerical vehicle model via the virtual electromagnet; The numerical vehicle model is further used to convert the displacement data into vertical force data and lateral force data; The numerical bridge model is further used to perform cyclic simulation based on the vertical force data, the lateral force data and the driving speed to obtain preliminary experimental results of the magnetic levitation vehicle-bridge hybrid test; The vibration table model includes a numerical vibration table modeled by a mechanism and a vibration table transfer function identified by measured data, and the numerical vibration table and the vibration table transfer function are respectively cycled based on a hybrid test logic; The hybrid test verification module includes a vehicle model verification unit, a numerical bridge model verification unit, and a numerical vehicle-numerical bridge driving simulation test unit; The vehicle model verification unit is used to verify the accuracy of the numerical vehicle model imported before the test; The numerical bridge model verification unit is used to verify the accuracy of the numerical bridge model imported before the test; The numerical vehicle-numerical bridge driving simulation test unit is used to perform real-time verification of the driving simulation test; The hybrid test verification module is used to analyze the consistency between the vibration table command of the numerical vibration table and the vibration table response of the vibration table transfer function to determine the correctness of the hybrid test.

2. The pre-test system for the maglev vehicle-bridge hybrid test according to claim 1 is characterized in that: The system further comprises: The numerical bridge model construction module is used to process the ordinary steel bars and prestressed steel strands of the solid unit bridge using a refined modeling method, prestress the beam elements of the solid unit bridge using an equivalent load method, and process the ordinary steel bars using an equivalent section method to construct a numerical bridge model corresponding to the solid unit bridge.

3. The pre-test system for the maglev vehicle-bridge hybrid test according to claim 1 is characterized in that: The system further comprises: The numerical vehicle model construction module is used to obtain vehicle data of a real maglev vehicle and construct a numerical vehicle model based on the vehicle data.

4. The pre-test system for the maglev vehicle-bridge hybrid test according to claim 1 is characterized in that: The numerical bridge model verification unit is specifically used to compare the vertical frequencies of different beam units and corresponding solid units when establishing solid units of different solid units of the bridge during the construction of the numerical bridge model. If the vertical frequency difference is greater than a preset frequency threshold, the accuracy verification of the numerical bridge model fails; if the vertical frequency difference is not greater than the preset frequency threshold, the accuracy verification of the numerical bridge model passes.

5. The pre-test system for the maglev vehicle-bridge hybrid test according to claim 1 is characterized in that: The numerical vehicle-numerical bridge driving simulation test unit is specifically used to import the verified numerical bridge model into the simulation software, jointly simulate the numerical bridge model and the numerical vehicle model through the simulation software, input a constant force of the same magnitude to perform concentrated force bridge crossing analysis, and analyze the relative error of the vertical displacement of the bridge connection point calculated at different speeds. If the relative error does not exceed the error threshold, it is determined that the real-time verification of the driving simulation test has passed; if the relative error exceeds the error threshold, it is determined that the real-time verification of the driving simulation test has failed.

6. The pre-test system for the maglev vehicle-bridge hybrid test according to any one of claims 1 to 5, characterized in that: The bridge deformation data is deformation data of three degrees of freedom, and the bridge deformation data includes bridge vertical deformation data, bridge torsional deformation data, and bridge bending deformation data.

7. The pre-test system for the maglev vehicle-bridge hybrid test according to claim 1, characterized in that: The numerical vibration table is a three-degree-of-freedom model.

8. The pre-test system for the maglev vehicle-bridge hybrid test according to claim 1, characterized in that: The boundary coordination module is specifically used to perform linear fitting of the three-degree-of-freedom deformation data in the bridge deformation data using a boundary coordination algorithm, obtain the three-degree-of-freedom vibration test bench operation signal of the vibration table model, and solve in real time to obtain a piecewise straight line, thereby fitting the curved operating conditions of the train line with high precision.

9. The pre-test system for the maglev vehicle-bridge hybrid test according to claim 8, characterized in that: The controller model is specifically used to process the operating signal of the three-degree-of-freedom vibration test platform with a time-delay compensation algorithm to obtain prediction data. After inputting the prediction data into the vibration platform model for simulation, the displacement data of the virtual electromagnet is obtained to implement the time-delay compensation process. The evaluation index time-delay and mean square error test algorithm are used to determine whether the preset compensation and control effects can be achieved.

10. A pre-test method for a maglev vehicle-bridge hybrid test, characterized in that: A pre-test system for a maglev vehicle-bridge hybrid test according to any one of claims 1 to 9, the method comprising: S1, the numerical vehicle model provides load excitation to the numerical bridge model and simulates the driving speed of the real maglev vehicle; S2, the numerical bridge model receives the load excitation and the driving speed, obtains the internal excitation of the bridge, and obtains bridge deformation data through an integration algorithm according to the load excitation, the driving speed and the internal excitation of the bridge; S3, the boundary coordination module converts the bridge deformation data into a vibration test bench operation signal, and solves it in real time to obtain a piecewise straight line, thereby fitting the curve operating condition of the train line with high precision; S4, the controller model processes the vibration test bench operation signal using a time-delay compensation algorithm, inputs the processed signal into the vibration table model for simulation to obtain displacement data, and applies the displacement data to the numerical vehicle model via a virtual electromagnet; S5, the numerical vehicle model converts the displacement data into vertical force data and lateral force data; S5, performing simulation on the numerical bridge model according to the vertical force data, the lateral force data, and the driving speed to obtain preliminary experimental results of the maglev vehicle-bridge hybrid test; S6, the hybrid test verification module analyzes the consistency between the vibration table command of the numerical vibration table and the vibration table response of the vibration table transfer function to determine the correctness of the hybrid test; verifies the accuracy of the imported numerical vehicle model and the numerical bridge model before the test; and performs real-time verification of the numerical vehicle-numerical bridge driving simulation test.

Images