Vehicle body load identification method and system of railway vehicle based on virtual test bench

Abstract

The invention discloses a vehicle body load identification method and system of a railway vehicle based on a virtual test bench. The method comprises the steps that the accelerated speed of the rail vehicle in the testing process is determined by testing the rail vehicle, and the accelerated speed comprises a plurality of vertical accelerated speeds of a sleeper beam of the rail vehicle and a plurality of transverse accelerated speeds of a vehicle body of the rail vehicle; the acceleration is subjected to integral processing, displacement corresponding to the acceleration is obtained, and the displacement comprises multiple vertical displacements of the sleeper beam in the test process and multiple transverse displacements of the vehicle body in the test process; the load of the vehicle body of the railway vehicle is obtained with the displacement as an iteration target through a pre-trained virtual test stand, and the load is used for reflecting the vibration state and the stress state of the vehicle body of the railway vehicle in the actual operation state. According to the invention, the technical problem that the vehicle body load identification precision of the railway vehicle is low in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the field of rail vehicles and load identification, and in particular to a method and system for identifying the body load of a rail vehicle based on a virtual test bench. Background Art

[0002] Rail vehicles are an important part of modern transportation systems. Rail vehicles are subject to a variety of excitations during actual operation, such as the excitation force on rail vehicles, the acceleration of rail vehicles during operation, and the noise of rail vehicles during operation. These excitations will cause vibrations in the track, thus affecting the safe operation and service life of rail vehicles. Therefore, dynamic simulation can be used to identify the body load, so as to understand the actual operation of rail vehicles, improve the vibration of rail vehicles in advance, and increase the service life of rail vehicles.

[0003] In the related art, test drive data is obtained through a physical test bench system, and then the body load of the rail vehicle is predicted through digital simulation technology. However, due to environmental conditions, test difficulty and cost constraints, the amount of test drive data obtained by the physical test bench system is limited, which will lead to reduced simulation accuracy, thereby affecting the accuracy of body load identification.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present invention provide a method and system for identifying the body load of a rail vehicle based on a virtual test bench, so as to at least solve the technical problem of low accuracy in calculating the body load identification of a rail vehicle in the related art.

[0006] According to one aspect of an embodiment of the present invention, a method for calculating the displacement of a rail vehicle is provided, comprising: determining the acceleration of the rail vehicle during the test by testing the rail vehicle, wherein the acceleration comprises: a plurality of vertical accelerations of a bolster of the rail vehicle and a plurality of lateral accelerations of a body of the rail vehicle; integrating the acceleration to obtain a displacement corresponding to the acceleration, wherein the displacement comprises: a plurality of vertical displacements of the bolster during the test and a plurality of lateral displacements of the body during the test; and obtaining the load of the body of the rail vehicle by using a pre-trained virtual test bench with the displacement as an iteration target, wherein the load is used to reflect the vibration state and stress state of the body of the rail vehicle in an actual operating state.

[0007] Furthermore, the above method also includes: obtaining the stress state of the vehicle body based on the load.

[0008] Furthermore, the above method also includes: obtaining the body load of the rail vehicle through a pre-trained virtual test bench with displacement as the iteration target, including: systematically identifying and iterating the initial virtual test bench based on the test displacement to obtain the load of the virtual test bench, wherein the load of the virtual test bench is the displacement obtained by the final drive test, and the driving load corresponding to the relative root mean square error value of the test displacement is less than a preset threshold.

[0009] Furthermore, the initial virtual test bench is systematically identified and iterated based on the test displacement to obtain the load of the virtual test bench, including: in response to the initial virtual test bench being excited, obtaining the product of the initial drive, the frequency response function and the first weighting coefficient to obtain the response drive of the rail vehicle, wherein the initial drive is the initial drive input after the virtual test bench is excited; in response to the relative root mean square error value between the response drive and the initial drive being greater than or equal to a preset threshold, repeatedly executing the steps of obtaining the virtual test bench based on the response drive, the frequency response function and the initial drive until it is determined that the relative root mean square error value between the response drive and the initial drive is less than the preset threshold, and the response drive is determined to be the target drive; and obtaining the load of the virtual test bench based on the target drive.

[0010] Further, the step of obtaining a virtual test bench based on the response drive, the frequency response function and the initial drive is repeatedly performed, including: obtaining the difference between the initial drive and the response drive to obtain the error drive; obtaining the product of the error drive, the frequency response function and the second weighting coefficient to obtain the update variable; obtaining the sum of the update variable and the response drive to obtain the updated response drive; in response to the relative root mean square error value between the updated response drive and the initial drive being greater than or equal to a preset threshold, repeatedly obtaining the updated error drive and the updated update variable, obtaining the updated response drive based on the updated error drive and the updated update variable, and determining whether the relative root mean square error value between the updated response drive and the initial drive is greater than or equal to the preset threshold, until the relative root mean square error value between the updated response drive and the initial drive is less than the preset threshold; in response to the relative root mean square error value between the updated response drive and the initial drive being less than the preset threshold, determining that the updated response drive is the target drive; and obtaining the load of the virtual test bench based on the target drive.

[0011] Furthermore, by testing the rail vehicle, the acceleration of the rail vehicle during the test is determined, including: obtaining the initial acceleration of the rail vehicle based on preset test conditions, wherein the preset test conditions include one of the following: line operation dynamic response test, indoor vehicle vibration test bench, and the test conditions of the line operation dynamic response test need to cover the actual driving environment of the loaded rail vehicle; performing signal preprocessing on the initial acceleration to obtain the initial acceleration after burr removal, wherein the initial acceleration is a plurality of vertical accelerations of the rail vehicle's bolster and a plurality of lateral accelerations of the rail vehicle's body collected by sensors; and compressing the initial acceleration after burr removal based on a preset threshold to obtain the acceleration.

[0012] Furthermore, the acceleration is integrated to obtain the displacement corresponding to the acceleration, including: performing discrete Fourier transform on the acceleration to obtain a simple harmonic signal of the acceleration; performing frequency domain integration processing on the simple harmonic signal according to a preset number of times to obtain harmonics of the displacement; and superimposing the harmonics based on a preset signal processing method to obtain the displacement.

[0013] According to another aspect of an embodiment of the present invention, a body load identification system for a rail vehicle based on a virtual test bench is provided, comprising: a first component, wherein the first component is used to obtain the acceleration of the rail vehicle during a test; a second component, wherein the second component is used to obtain the displacement corresponding to the acceleration; a third component, wherein the third component is used to control the virtual test bench to perform virtual iteration; a fourth component, wherein the fourth component is used to obtain the body load of the rail vehicle; and a display area, wherein the display area is used to display the acceleration, displacement and body load.

[0014] Furthermore, the above system also includes: a fifth component, wherein the fifth component is used to obtain the initial drive of the virtual laboratory bench; a sixth component, wherein the sixth component is used to obtain the response drive of the virtual laboratory bench; a seventh component, wherein the seventh component is used to obtain the frequency response function of the virtual laboratory bench; and the display area is also used to display the initial drive, the response drive and the frequency response function.

[0015] Furthermore, the above system also includes: an eighth component, wherein the eighth component is used to generate a noise signal; a ninth component, wherein the ninth component is used to obtain a sampling frequency; wherein the display area is also used to display the noise signal and the sampling frequency, as well as the starting frequency and the cutoff frequency of the sampling frequency.

[0016] According to another aspect of an embodiment of the present invention, a vehicle is further provided, comprising: a memory storing an executable program; and a processor for running the program, wherein the method in each embodiment of the present invention is executed when the program is running.

[0017] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0018] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0019] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0020] According to another aspect of the embodiments of the present invention, a computer program is further provided. When the computer program is executed by a processor, the methods in the embodiments of the present invention are implemented.

[0021] In an embodiment of the present invention, the acceleration of the rail vehicle during the test is determined by testing the rail vehicle; the acceleration is integrated to obtain the displacement corresponding to the acceleration; the load of the rail vehicle body is obtained by using the pre-trained virtual test bench with the displacement as the iteration target, wherein the load is used to reflect the vibration state and stress state of the rail vehicle body in the actual operation state. It is easy to notice that the displacement is obtained by processing the acceleration that is easy to obtain in the test, that is, firstly obtaining multiple vertical accelerations of the rail vehicle's bolster and multiple lateral accelerations of the rail vehicle's body, and then converting the acceleration into displacement, and then accurately simulating the dynamic response of the rail vehicle during operation through the virtual test bench to obtain the displacement of the rail vehicle in multiple directions in actual operation. Moreover, the virtual test bench is pre-trained, and the computing efficiency can be improved through the virtual test bench, and the consistency between the virtual test data and the actual data can be ensured, so that the virtual test process is more in line with the actual working conditions, and the virtual test data is closer to the actual data. Thus, the body load of the rail vehicle in actual operation can be simulated through the virtual test bench, and the purpose of accurately identifying the body load is achieved, thereby achieving the technical effect of improving the accuracy of identifying the body load of the rail vehicle, and further solving the technical problem of low accuracy in calculating the body load identification of the rail vehicle in the related technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0023] Figure 1 is a flow chart of a vehicle body load identification method for a rail vehicle based on a virtual test bench according to an embodiment of the present invention;

[0024] Figure 2 is a flow chart of load identification of an optional virtual test system according to an embodiment of the present invention;

[0025] Figure 3 is a schematic diagram of an optional acceleration compression according to an embodiment of the present invention;

[0026] Figure 4 is a flow chart of an optional method for identifying a vehicle body load of a rail vehicle based on a virtual test bench according to an embodiment of the present invention;

[0027] Figure 5 is a schematic diagram of a virtual test bench according to an embodiment of the present invention;

[0028] 6(a), 6(b), 6(c) and 6(d) are schematic diagrams of an operation interface of a virtual test bench according to an embodiment of the present invention;

[0029] Figure 7 is a schematic diagram of a vehicle body load identification system for a rail vehicle based on a virtual test bench according to an embodiment of the present invention;

[0030] Figure 8 is a schematic diagram of an optional vehicle body load identification system for a rail vehicle based on a virtual test bench according to an embodiment of the present invention;

[0031] Fig. 9 is a schematic diagram of an optional vehicle body load identification system for a rail vehicle based on a virtual test bench according to an embodiment of the present invention;

[0032] Fig.10 A schematic diagram of a vehicle body load identification device for a rail vehicle based on a virtual test bench according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0034] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0035] According to an embodiment of the present invention, an embodiment of a method for identifying a body load of a rail vehicle based on a virtual test bench is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0036] Figure 1 is a flow chart of a method for identifying a vehicle body load of a rail vehicle based on a virtual test bench according to an embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0037] Step S102, determining the acceleration of the rail vehicle during the test by testing the rail vehicle.

[0038] The acceleration includes: a plurality of vertical accelerations of the bolster of the rail vehicle and a plurality of lateral accelerations of the body of the rail vehicle.

[0039] The above-mentioned rail vehicle can be a vehicle running along the track in railway or urban rail transit. The rail vehicle can be a freight vehicle or a passenger vehicle. The rail vehicle can also be a vehicle running along the track of railway, light rail, subway or cloud rail. The rail vehicle will be subject to various excitations during operation, such as the exciting force on the rail vehicle, the acceleration of the rail vehicle during operation, and the noise of the rail vehicle during operation. These excitations on the rail vehicle during operation will cause the rail vehicle to vibrate, and the vibration will affect the safe operation and service life of the vehicle. Therefore, it is necessary to calculate the displacement of the rail vehicle in order to control the vibration of the rail vehicle.

[0040] The above test may refer to an operation test of a rail vehicle to simulate the line operation, from which the acceleration of the vehicle traveling along the track can be obtained. Optionally, the test can be carried out through a line operation dynamic response test, or it can also be carried out through an indoor vehicle vibration test bench, and the actual response of the vehicle can be reflected through vibration response simulation. In the line operation dynamic response test, the selected test line can reflect the different environments encountered by the rail vehicle in actual operation, such as Class I, Class II and Class III lines in the railway technical regulations, as well as straight line segments, humps, curve segments and siding turnouts. When testing through an indoor vehicle vibration test bench, the vehicle response data at different speed levels can be obtained through the indoor vehicle vibration test bench. Through this test, the test acceleration can be obtained, so as to further obtain the actual acceleration, thereby accurately calculating the displacement of the rail vehicle.

[0041] The above acceleration may include: multiple vertical accelerations of the rail vehicle's bolster, multiple lateral accelerations of the rail vehicle's body. The acceleration is a test acceleration, which can be converted into a displacement to facilitate further simulation to obtain a target displacement.

[0042] Since both rigid body vibration and elastic body vibration must be considered in actual operation of rail vehicles, the acceleration of the rail vehicle's bolster and the lateral acceleration of the vehicle body can be tested, that is, vertical acceleration test points are arranged at the rail vehicle's bolster, and lateral acceleration test points are arranged on the vehicle body. This can reflect the vehicle body's floating and sinking modes and nodding modes, as well as the elastic body's torsional modes and vertical first-order bending modes. Optionally, an accelerometer or laser vibrometer can be arranged at the corresponding test point to obtain the acceleration of the corresponding test point.

[0043] In an optional embodiment, the acceleration can be obtained by testing the line operation dynamic response test. By controlling the line environment, the dynamic response of the rail vehicle under different road conditions can be tested. Alternatively, the acceleration can be obtained by testing the whole vehicle vibration table. By controlling the frequency, amplitude or waveform of the whole vehicle vibration table, various conditions that the rail vehicle may encounter in actual operation can be simulated.

[0044] Step S104: integrating the acceleration to obtain the displacement corresponding to the acceleration.

[0045] The displacement includes: multiple vertical displacements of the bolster during the test and multiple lateral displacements of the vehicle body during the test.

[0046] The above-mentioned integral processing can be a processing method for converting acceleration into displacement. The integral processing can be frequency domain integral processing or time domain integral processing. By converting the easily obtained acceleration into the corresponding displacement, it is convenient to calculate the target displacement of the rail vehicle in the subsequent process. Through integral processing, the acceleration obtained in the test can be converted into displacement. The displacement test data is helpful to analyze the dynamic characteristics of the rail vehicle and facilitate the understanding of the vibration mode of the rail vehicle.

[0047] The above displacement may include: multiple vertical displacements of the bolster during the test, and multiple lateral displacements of the vehicle body during the test. The displacement is a displacement corresponding to the acceleration. The displacement is a test displacement, and through the test displacement, the target displacement of the rail vehicle can be further obtained through a virtual test bench such as a virtual dynamic test system.

[0048] In an optional embodiment, the acceleration can be integrated in the frequency domain using a frequency domain integration method to determine the displacement corresponding to the acceleration. Specifically, the acceleration can be first subjected to a discrete Fourier transform to obtain a simple harmonic signal of the acceleration, and then the simple harmonic signal can be integrated according to a preset number of integrations to obtain harmonics of the displacement, and the harmonics can be superimposed by a signal processing method to obtain the displacement. In another optional embodiment, the acceleration can also be converted into the displacement by means of time domain integration. In yet another optional embodiment, the displacement corresponding to the acceleration can be calculated by a transfer function.

[0049] Step S106, using the pre-trained virtual test bench, the load of the rail vehicle body is obtained with displacement as the iteration target.

[0050] The load is used to reflect the vibration state and stress state of the rail vehicle body in actual operation.

[0051] The above-mentioned virtual test bench can be a model for virtual simulation of experimental displacement. Through the virtual test bench, the target displacement, that is, the actual displacement, can be obtained. The virtual test bench can be obtained by training with test displacement, and the accuracy of the calculated values ​​obtained by the virtual test bench can be ensured by pre-training. The virtual test bench can be used to simulate the dynamic response of the rail vehicle during actual operation, such as vibration state, stress state, fatigue life, etc. After being stimulated, the virtual test bench will drive the rail vehicle to generate a response and obtain a response drive to determine the load on the body of the rail vehicle.

[0052] The above-mentioned load on the vehicle body can be used to reflect the vibration state and stress state of the vehicle body of the rail vehicle in the actual operating state. The load on the vehicle body can be obtained by simulating the rail vehicle through a virtual test bench. The displacement of the vehicle body can be further calculated through the acceleration obtained by the test, and the load applied to the vehicle body by the test bench can be iteratively obtained with the displacement as the target, so as to determine the vibration state and stress state of the vehicle body of the rail vehicle in the actual operating state, so as to perform fatigue assessment on the rail vehicle.

[0053] In an optional embodiment, the load of the vehicle body can be obtained by using the displacement through the virtual test bench, that is, the vibration state and stress state of the rail vehicle in the actual operation state. Specifically, the flexible body model of the rail vehicle established by the virtual test bench can be used to input the displacement into the pre-trained virtual test bench system, and the load of the vehicle body can be calculated based on the flexible body model.

[0054] In another optional embodiment, after simulating the dynamic response of the rail vehicle using the virtual test bench, the relationship between the simulated dynamic response data and the load can be learned through a machine learning model to obtain the load of the rail vehicle body through the machine learning model to reflect the actual response state. For example, a long short-term memory network can be used to construct a machine learning model, which is only an example here and is not limited to the machine learning model.

[0055] In an embodiment of the present invention, the acceleration of the rail vehicle during the test is determined by testing the rail vehicle; the acceleration is integrated to obtain the displacement corresponding to the acceleration; the load of the rail vehicle body is obtained by using the pre-trained virtual test bench with the displacement as the iteration target, wherein the load is used to reflect the vibration state and stress state of the rail vehicle body in the actual operation state. It is easy to notice that the displacement is obtained by processing the acceleration that is easy to obtain in the test, that is, firstly obtaining multiple vertical accelerations of the rail vehicle's bolster and multiple lateral accelerations of the rail vehicle's body, and then converting the acceleration into displacement, and then accurately simulating the dynamic response of the rail vehicle during operation through the virtual test bench to obtain the displacement of the rail vehicle in multiple directions in actual operation. Moreover, the virtual test bench is pre-trained, and the computing efficiency can be improved through the virtual test bench, and the consistency between the virtual test data and the actual data can be ensured, so that the virtual test process is more in line with the actual working conditions, and the virtual test data is closer to the actual data. Thus, the body load of the rail vehicle in actual operation can be simulated through the virtual test bench, and the purpose of accurately identifying the body load is achieved, thereby achieving the technical effect of improving the accuracy of identifying the body load of the rail vehicle, and further solving the technical problem of low accuracy in calculating the body load identification of the rail vehicle in the related technology.

[0056] Furthermore, the above method also includes: obtaining the stress state of the vehicle body based on the load.

[0057] The above stress state can be used to characterize the force applied to the vehicle body after the rail vehicle is vibrated. The stress state may include, but is not limited to, normal stress, shear stress, fatigue stress, etc. The stress state is not limited here and can be determined as needed. With the different working conditions of the rail vehicle, the structural safety and reliability of the rail vehicle in actual operation can be evaluated through the stress state.

[0058] In an optional embodiment, the relationship between the simulated load and the stress state of the vehicle body can be learned through a neural network model to obtain the stress state of the vehicle body through the neural network model, so that the stress state can be used to perform fatigue analysis on the rail vehicle for timely maintenance. For example, a long short-term memory network can be used to construct a machine learning model, which is only an example here and is not limited to the machine learning model.

[0059] In another optional embodiment, a finite element model of the vehicle body can be established based on the load, and then the stress state of the vehicle body can be calculated by simulating the distribution of the load on the vehicle body and the structural response of the vehicle body. This process is crucial to ensure the design safety of the vehicle body structure, predict the life of the material, and avoid potential structural failure.

[0060] Furthermore, the above method also includes: obtaining the body load of the rail vehicle through a pre-trained virtual test bench with displacement as the iteration target, including: systematically identifying and iterating the initial virtual test bench based on the test displacement to obtain the load of the virtual test bench, wherein the load of the virtual test bench is the displacement obtained by the final drive test, and the driving load corresponding to the relative root mean square error value of the test displacement is less than a preset threshold.

[0061] In an optional embodiment, a frequency domain analysis algorithm can be used to identify the difference between the test displacement and the simulated displacement in the virtual test bench model to determine the transfer function of the virtual test bench. The identified transfer function is applied to the virtual test bench, and the driving load is adjusted through an iterative process so that the relative root mean square error between the simulated displacement and the test displacement is gradually reduced until the relative root mean square error value with the test displacement is less than a preset threshold.

[0062] In another optional embodiment, it is also possible to construct a time domain model of the virtual test bench to describe the relationship between displacement and load, and then optimize the time domain model parameters using the least squares method. The initial virtual test bench can be further iteratively optimized using the Kalman filter algorithm to dynamically adjust the load and gradually reduce the time domain error of the test displacement, thereby ensuring the prediction accuracy of the virtual test bench and enabling it to more accurately reflect the actual operating status of the vehicle.

[0063] Furthermore, the initial virtual test bench is systematically identified and iterated based on the test displacement to obtain the load of the virtual test bench, including: in response to the initial virtual test bench being excited, obtaining the product of the initial drive, the frequency response function and the first weighting coefficient to obtain the response drive of the rail vehicle, wherein the initial drive is the initial drive input after the virtual test bench is excited; in response to the relative root mean square error value between the response drive and the initial drive being greater than or equal to a preset threshold, repeatedly executing the steps of obtaining the virtual test bench based on the response drive, the frequency response function and the initial drive until it is determined that the relative root mean square error value between the response drive and the initial drive is less than the preset threshold, and the response drive is determined to be the target drive; and obtaining the load of the virtual test bench based on the target drive.

[0064] The initial drive described above can simulate the target dynamic behavior more accurately, such as more accurately predicting the displacement of the rail vehicle under actual operating conditions in the initial virtual test bench. The initial drive can be adjusted by calculating the frequency response function matrix, the Fourier transform of the error signal, and the weighting coefficients. In the virtual dynamic test, the iteration process of the initial drive is to more realistically reflect the actual dynamic behavior of the rail vehicle.

[0065] The target drive mentioned above can be the input signal used to excite the system during the virtual dynamic test. The input signal can be random noise, white noise, a predefined vibration waveform, or a load calculated based on an empirical model or a physical model. For example, in a virtual dynamic test of a rail vehicle, the target drive can be the acceleration obtained from the line operation dynamic response test, which is converted into displacement through a frequency domain integration algorithm and used as the initial input of the initial virtual test bench. The purpose is to start the simulation process and perform preliminary dynamic excitation on the rail vehicle to calculate the dynamic response of the vehicle body.

[0066] In an optional embodiment, after the initial virtual test bench is stimulated, the response drive of the rail vehicle can be obtained. Optionally, the response drive is calculated by obtaining the product of the initial drive and the frequency response function and the first weighting coefficient. By adjusting the frequency response function and the weighting coefficient, the response of the virtual test bench to signals of different frequencies can be improved, and the adaptability and prediction accuracy of the virtual test bench can be improved. Further, the response drive is iteratively trained to reduce the prediction error until the virtual test bench meets the preset conditions, ensuring that the response drive of each test point is consistent with the predetermined target signal, so as to be suitable for the load of the rail vehicle under different working conditions. Optionally, the virtual test bench can be adjusted by the relative root mean square error.

[0067] In another optional embodiment, the frequency response function matrix and the iterative algorithm can be used to minimize the relative root mean square error, and further obtain the load of the virtual test bench. Specifically, based on the initial virtual test bench, the frequency response function matrix is ​​calculated, and then the input signal is Fourier transformed to obtain its frequency domain representation, the frequency domain representation of the initial virtual test bench response is calculated, and then the frequency domain response is converted back to the time domain to obtain the response drive of the rail vehicle. The relative root mean square error value between the response drive and the initial drive is further calculated. If the error value is greater than or equal to the preset threshold, the frequency domain representation of the initial drive signal is adjusted according to the error signal, and the product operation is performed again with the frequency response function and the first weighting coefficient to obtain the updated response drive. Repeat the above steps until the relative root mean square error value between the response drive and the initial drive is less than the preset threshold. At this time, the response drive is the optimized target drive, and the load of the virtual test bench can be obtained by reverse solving according to the target drive signal.

[0068] Optionally, the response drive can be calculated using the following formula:

[0069] U1(jω)=H -1 (jω)M(jω)α;

[0070] Where U1(jω) is the response drive, H -1 (jw) is the frequency response function, M(jω) is the initial drive, α is the first weighting coefficient, the value of α is [0, 1], and jw represents the imaginary part of the signal.

[0071] Further, the step of obtaining a virtual test bench based on the response drive, the frequency response function and the initial drive is repeatedly performed, including: obtaining the difference between the initial drive and the response drive to obtain the error drive; obtaining the product of the error drive, the frequency response function and the second weighting coefficient to obtain the update variable; obtaining the sum of the update variable and the response drive to obtain the updated response drive; in response to the relative root mean square error value between the updated response drive and the initial drive being greater than or equal to a preset threshold, repeatedly obtaining the updated error drive and the updated update variable, obtaining the updated response drive based on the updated error drive and the updated update variable, and determining whether the relative root mean square error value between the updated response drive and the initial drive is greater than or equal to the preset threshold, until the relative root mean square error value between the updated response drive and the initial drive is less than the preset threshold; in response to the relative root mean square error value between the updated response drive and the initial drive being less than the preset threshold, determining that the updated response drive is the target drive; and obtaining the load of the virtual test bench based on the target drive.

[0072] The error drive mentioned above may be an error signal between a dynamic response signal and a predetermined target signal. The error drive may reflect the deviation between the predicted displacement of the virtual laboratory bench and the actual displacement, thereby adjusting the virtual laboratory bench.

[0073] In an optional embodiment, the response drive can be updated based on the update variable to obtain an updated response drive. The updated response drive can more accurately reflect the actual operating state of the rail vehicle, thereby facilitating accurate target displacement. Optionally, the update variable can be determined by the product of the error drive obtained by the difference between the initial drive and the response drive, the frequency response function, and the second weighting coefficient. Further, it is still necessary to judge the relative root mean square error value between the updated response drive and the initial drive and the size of the preset threshold. Using the relative root mean square error as an evaluation index can effectively reflect the overall situation and convergence degree of the error during the iteration process. When the relative root mean square error value is greater than the preset threshold, it is still necessary to calculate the update variable so that the relative root mean square error value between the updated response drive and the initial drive is less than the preset threshold, thereby ensuring that the error between the prediction result of the virtual test bench and the actual data meets the preset conditions, so that the virtual test bench can accurately predict the load of the rail vehicle in actual operation.

[0074] In another optional embodiment, the response drive can be adjusted by iterative optimization in the time domain. Specifically, the difference between the initial drive signal and the response drive signal can be calculated in the time domain to obtain an error drive signal. The error drive signal is multiplied by the second weighting coefficient to obtain an update variable. Genetic algorithms and particle swarm optimization algorithms can be used to find update variables that can reduce errors. The updated variable is added to the current response drive signal to obtain an updated response drive signal. The relative root mean square error value between the updated response drive and the initial drive is calculated. If the error is greater than or equal to a preset threshold, the iterative adjustment is repeated until the relative root mean square error value is less than the preset threshold, and the updated drive at this time is determined to be the target drive. The target drive signal is then solved to obtain the load of the virtual test bench.

[0075] Optionally, the update variable can be calculated by the following formula:

[0076] ΔU(jω)=H -1 (jω)E(jω)β;

[0077] Where ΔU(jω) is the update variable of the response drive, H -1 (jw) is the frequency response function, E(jω) is the error drive, β is the second weighting coefficient, the value of β is [0, 1], and jw represents the imaginary part of the signal.

[0078] Optionally, the updated response driver can be calculated by the following formula:

[0079] U new (jω)=U old (jω)+ΔU(jω);

[0080] In the formula, U new(jω) is the updated response drive, ΔU(jω) is the updated variable of the response drive, and U old (jω) is the response drive before updating, and jw represents the imaginary part of the signal.

[0081] Figure 2 is a flow chart of load identification of an optional virtual test system according to an embodiment of the present invention, such as Figure 2 As shown, the method includes:

[0082] A noise signal is generated and a dynamic simulation system of the test bench is excited, and the dynamic simulation system of the test bench includes a flexible vehicle body model. The vibration acceleration response of the flexible vehicle body bolster in the virtual test system is further obtained, and the vehicle body acceleration response result is obtained. The transfer function of the dynamic simulation system is obtained by calculating the excitation signal and the acceleration response result of the vehicle body bolster, and further, the transfer function is inverted to obtain an inverse function.

[0083] Based on the acceleration of the line test, the displacement drive of the dynamic simulation system is first predicted, and further dynamic simulation calculation is performed to obtain the acceleration response of the body bolster. The error between the acceleration response and the test data is obtained, and it is determined whether the error meets the accuracy requirement. When the error meets the accuracy, the acceleration response is determined to be the simulation result. When the error does not meet the accuracy, the drive signal is updated, and the acceleration response of the body bolster is recalculated through dynamic simulation until the error between the acceleration response and the test data meets the accuracy.

[0084] Furthermore, by testing the rail vehicle, the acceleration of the rail vehicle during the test is determined, including: obtaining the initial acceleration of the rail vehicle based on preset test conditions, wherein the preset test conditions include one of the following: line operation dynamic response test, indoor vehicle vibration test bench, and the test conditions of the line operation dynamic response test need to cover the actual driving environment of the loaded rail vehicle; performing signal preprocessing on the initial acceleration to obtain the initial acceleration after burr removal, wherein the initial acceleration is a plurality of vertical accelerations of the rail vehicle's bolster and a plurality of lateral accelerations of the rail vehicle's body collected by sensors; and compressing the initial acceleration after burr removal based on a preset threshold to obtain the acceleration.

[0085] The above-mentioned line operation dynamic response test can reflect the different environments encountered by rail vehicles in actual operation. The test conditions of the line operation dynamic response test can cover the actual driving environment of loaded rail vehicles, such as Class I, Class II and Class III lines in the railway technical regulations, or different line sections, which may involve straight sections, humps, curved sections and siding turnouts.

[0086] The indoor vehicle vibration test bench can be a test device used to simulate the load environment encountered by rail vehicles in actual use. The indoor vehicle vibration test bench generates vibrations by mechanical, hydraulic or electric means to evaluate the strength, rigidity and stability of the internal structure of the rail vehicle, thereby facilitating the acquisition of the acceleration of the rail vehicle under real operating conditions.

[0087] The above-mentioned initial acceleration can be a plurality of vertical accelerations of the bolster of the rail vehicle and a plurality of lateral accelerations of the body of the rail vehicle collected by the sensor. Furthermore, the acceleration obtained by preprocessing and compression can also be a plurality of vertical accelerations of the bolster of the rail vehicle and a plurality of lateral accelerations of the body of the rail vehicle. Due to the influence of environmental noise, such as electromagnetic interference, vibration, etc., the initial acceleration directly collected will fluctuate and deviate. Therefore, it is necessary to process the initial acceleration to obtain an effective acceleration to ensure the accuracy of the subsequent displacement calculation.

[0088] The above-mentioned signal preprocessing can be a process of processing the initial acceleration to obtain an effective acceleration. When testing rail vehicles, the equipment for obtaining test data, such as accelerometers, sensors, etc., will be subject to external interference, so the test data obtained will be unstable and inaccurate. Therefore, the initial acceleration is processed through signal preprocessing to ensure the validity of the test data and the consistency of subsequent data simulation. Optionally, the initial acceleration can be preprocessed by filtering, signal smoothing, signal correction and other processing methods to obtain acceleration.

[0089] The above compression can be a process of screening acceleration. By compression, the amount of data is reduced while retaining the required acceleration, thereby saving test resources and improving test efficiency. Optionally, by setting an amplitude threshold, the acceleration whose amplitude of the vibration waveform during the test meets the preset threshold can be selected. The preset threshold can be determined as needed and is not limited here.

[0090] like Figure 3 As shown in the figure, the micro-strain values ​​of the corresponding test points changing with time are shown, among which SZ121 is the strain test point of the front eight-shaped cover of the vehicle body, SH1 is the test point of the large cross beam of the vehicle body, and SZ02 is the test point of the middle beam of the vehicle body. Figure 3 In the a, b, and c regions, the amplitudes of these three regions are smaller than the preset thresholds, and the accelerations corresponding to these regions are deleted to obtain the compressed accelerations.

[0091] In an optional embodiment, the initial acceleration can be first obtained through a line operation dynamic response test or an indoor vehicle vibration test bench test to obtain the dynamic response data of the rail vehicle during transportation, thereby reflecting the actual situation and improving the reliability and practicality of the subsequent displacement calculation. Then, the initial acceleration is preprocessed to remove the burrs in the signal to obtain the initial acceleration with the burrs removed. Optionally, the signal higher than the preset frequency can be cut off by filtering, or the abnormal frequency can be identified by spectrum analysis. Furthermore, the initial acceleration is compressed to delete the acceleration below the preset threshold, thereby improving the test efficiency.

[0092] Furthermore, the acceleration is integrated to obtain the displacement corresponding to the acceleration, including: performing discrete Fourier transform on the acceleration to obtain a simple harmonic signal of the acceleration; performing frequency domain integration processing on the simple harmonic signal according to a preset number of times to obtain harmonics of the displacement; and superimposing the harmonics based on a preset signal processing method to obtain the displacement.

[0093] The simple harmonic signal may be a periodic signal, a sine signal or a cosine signal. The acceleration may be converted into displacement by the simple harmonic signal.

[0094] In an optional embodiment, the acceleration can be integrated in the frequency domain using a frequency domain integration method to determine the displacement corresponding to the acceleration. Specifically, the acceleration can be first subjected to a discrete Fourier transform to obtain a simple harmonic signal of the acceleration, and then the simple harmonic signal can be integrated according to a preset number of integrations to obtain harmonics of the displacement, and the harmonics can be superimposed by a signal processing method to obtain the displacement. Through discrete Fourier transform and signal processing, the displacement can be extracted from the acceleration for dynamic response analysis of the rail vehicle, especially using the test displacement to obtain the actual displacement of the rail vehicle.

[0095] Figure 4 is a flow chart of an optional method for identifying a vehicle body load of a rail vehicle based on a virtual test bench according to an embodiment of the present invention, such as Figure 4 As shown, the method includes:

[0096] Through the line operation dynamic response test or the railway freight car vibration test, the vertical and lateral accelerations of the vibration position of the bolster of the railway freight car body are obtained, as well as the strain time domain data of the car body. Furthermore, the acceleration and strain time domain data are combined into multi-channel synchronous data for time domain data compression processing.

[0097] The minimum value of the root mean square value of the integrated displacement curve at different low-frequency cutoff frequencies is determined. Further, the frequency domain integration of the bolster acceleration is performed based on the minimum value to obtain the displacement curve. Taking the integrated displacement as the target, the initial drive of the virtual test system is identified through the transfer function. Then, the initial drive excitation test is performed, and the comparison error between the initial drive response and the target displacement of the bolster is calculated to correct the initial drive response. Finally, the displacement of the bolster is simulated to obtain the load of the virtual test system.

[0098] Figure 5 is a structural diagram of a virtual container test bench according to an embodiment of the present invention, such as Figure 5 As shown, the container dynamic simulation test bench includes longitudinal actuator 1, longitudinal actuator 2, longitudinal actuator 3, longitudinal actuator 4, flexible corner piece support platform 5, flexible corner piece support platform 6, transverse actuator 7, transverse actuator 8, vertical actuator 9, vertical actuator 10, vertical actuator 11, vertical actuator 12, longitudinal actuator 13, longitudinal actuator 14, longitudinal actuator 15, longitudinal actuator 16, container beam 17, container beam 18, flexible corner piece support platform 19, flexible corner piece support platform 20, support seat 21, support seat 22.

[0099] Longitudinal actuator 1, longitudinal actuator 2, longitudinal actuator 3 and longitudinal actuator 4 are respectively connected to container beam 17 through ball joints (not marked in the figure), and longitudinal actuator 13, longitudinal actuator 14, longitudinal actuator 15 and longitudinal actuator 16 are respectively connected to container beam 18 through ball joints (not marked in the figure).

[0100] The transverse actuator 7 is connected to the container beam 17 via a ball joint (not shown in the figure), and the transverse actuator 8 is connected to the container beam 18 via a ball joint (not shown in the figure).

[0101] The vertical actuator 9 and the vertical actuator 10 are respectively connected to the container beam 17 through a ball joint (not marked in the figure), and the vertical actuator 11 and the vertical actuator 12 are respectively connected to the container beam 18 through a ball joint (not marked in the figure); the vertical actuator 9 and the vertical actuator 10 are respectively connected to the support seat 21 through a ball joint (not marked in the figure), and the vertical actuator 11 and the vertical actuator 12 are respectively connected to the support seat 22 through a ball joint (not marked in the figure).

[0102] In addition, the flexible corner piece support platform 5 and the flexible corner piece support platform 6 are respectively located above the container beam 17, and the flexible corner piece support platform 19 and the flexible corner piece support platform 20 are respectively located above the container beam 18. The flexible corner piece support platform 20 includes a flexible spring 201 and a flexible container connection point 202, and the flexible container connection point can be used to connect the main node of the rigid area of ​​the flexible container.

[0103] The operation interface of the container dynamic simulation test bench is shown in Figure 6(a), Figure 6(b), Figure 6(c) and Figure 6(d). The system dynamics automatic analysis software includes test bench, container, virtual test, results, files, edit, view, create, simulate, evaluate, set, tool and help, with a total of 13 interactive items for users to choose. Among them, as shown in Figure 6(a), the interactive item "test bench" includes existing virtual experiments, existing test benches, new container tests, and adjusting test benches. As shown in Figure 6(b), the interactive item "container" includes flexible bodies, connecting containers to test benches, sensor installation, setting container modes and damping. As shown in Figure 6(c), the interactive item "virtual test" includes typical loads, random loads, and starting tests. As shown in Figure 6(d), the interactive item "results" includes support platform acceleration analysis, container acceleration analysis, container strain analysis, and modal coordinate results.

[0104] According to an embodiment of the present invention, an embodiment of a vehicle body load identification system for a rail vehicle based on a virtual test bench is provided. It should be noted that the system can be used to execute the above-mentioned vehicle body load identification method for a rail vehicle based on a virtual test bench.

[0105] Figure 7 is a schematic diagram of a vehicle body load identification system for a rail vehicle based on a virtual test bench according to an embodiment of the present invention. Figure 7 As shown, the system includes: a first component, wherein the first component is used to obtain the acceleration of the rail vehicle during the test; a second component, wherein the second component is used to obtain the displacement corresponding to the acceleration; a third component, wherein the third component is used to control the virtual test bench to perform virtual iteration; a fourth component, wherein the fourth component is used to obtain the body load of the rail vehicle; and a display area, wherein the display area is used to display the acceleration, displacement and body load.

[0106] Furthermore, if Figure 8 As shown, the above system also includes: a fifth component, wherein the fifth component is used to obtain the initial drive of the virtual laboratory bench; a sixth component, wherein the sixth component is used to obtain the response drive of the virtual laboratory bench; a seventh component, wherein the seventh component is used to obtain the frequency response function of the virtual laboratory bench; and the display area is also used to display the initial drive, the response drive and the frequency response function.

[0107] Furthermore, if Fig. 9 As shown, the above system also includes: an eighth component, wherein the eighth component is used to generate a noise signal; a ninth component, wherein the ninth component is used to obtain a sampling frequency; wherein the display area is also used to display the noise signal and the sampling frequency, as well as the starting frequency and the cutoff frequency of the sampling frequency.

[0108] According to an embodiment of the present invention, an embodiment of a vehicle body load identification device for a rail vehicle based on a virtual test bench is provided. It should be noted that the device can be used to execute the above-mentioned vehicle body load identification method for a rail vehicle based on a virtual test bench.

[0109] Fig.10 A schematic diagram of a vehicle body load identification device for a rail vehicle based on a virtual test bench according to an embodiment of the present invention is shown in FIG. Fig.10 As shown, the device includes: a determination module 1002, which is used to determine the acceleration of the rail vehicle during the test by testing the rail vehicle, wherein the acceleration includes: multiple vertical accelerations of the bolster of the rail vehicle and multiple lateral accelerations of the body of the rail vehicle; an acquisition module 1004, which is used to integrate the acceleration to obtain the displacement corresponding to the acceleration, wherein the displacement includes: multiple vertical displacements of the bolster during the test and multiple lateral displacements of the body during the test; an input module 1006, which is used to obtain the load of the body of the rail vehicle by using a pre-trained virtual test bench with the displacement as an iteration target, wherein the load is used to reflect the vibration state and stress state of the body of the rail vehicle in the actual operating state.

[0110] Furthermore, the above device also includes an obtaining module.

[0111] The module is used to obtain the stress state of the vehicle body based on the load.

[0112] Furthermore, the above device also includes a generating module.

[0113] A generation module is used to systematically identify and iterate the initial virtual test bench based on the test displacement to obtain the load of the virtual test bench, wherein the load of the virtual test bench is the driving load corresponding to the displacement obtained by the final drive test and the relative root mean square error value of the test displacement is less than a preset threshold.

[0114] The generation module is also used to obtain the product of the initial drive, the frequency response function and the first weighting coefficient in response to the initial virtual test bench being excited, so as to obtain the response drive of the rail vehicle, wherein the initial drive is the initial drive input after the virtual test bench is excited; in response to the relative root mean square error value between the response drive and the initial drive being greater than or equal to a preset threshold, repeatedly execute the steps of obtaining the virtual test bench based on the response drive, the frequency response function and the initial drive until it is determined that the relative root mean square error value between the response drive and the initial drive is less than the preset threshold, and the response drive is determined to be the target drive; and obtain the load of the virtual test bench based on the target drive.

[0115] The generation module is also used to obtain the difference between the initial drive and the response drive to obtain the error drive; obtain the product of the error drive, the frequency response function and the second weighting coefficient to obtain the update variable; obtain the sum of the update variable and the response drive to obtain the updated response drive; in response to the relative root mean square error value between the updated response drive and the initial drive being greater than or equal to a preset threshold, repeatedly obtain the updated error drive and the updated update variable, obtain the updated response drive based on the updated error drive and the updated update variable, and determine whether the relative root mean square error value between the updated response drive and the initial drive is greater than or equal to the preset threshold, until the relative root mean square error value between the updated response drive and the initial drive is less than the preset threshold; in response to the relative root mean square error value between the updated response drive and the initial drive being less than the preset threshold, determine that the updated response drive is the target drive; and obtain the load of the virtual test bench based on the target drive.

[0116] A determination module is used to obtain the initial acceleration of the rail vehicle based on preset test conditions, wherein the preset test conditions include one of the following: line operation dynamic response test, indoor vehicle vibration test bench, and the test conditions of the line operation dynamic response test need to cover the actual driving environment of the loaded rail vehicle; perform signal preprocessing on the initial acceleration to obtain the initial acceleration after burr removal, wherein the initial acceleration is a plurality of vertical accelerations of the rail vehicle's bolster and a plurality of lateral accelerations of the rail vehicle's body collected by the sensor; and compress the initial acceleration after burr removal based on a preset threshold to obtain the acceleration.

[0117] The acquisition module is also used to perform discrete Fourier transform on the acceleration to obtain a simple harmonic signal of the acceleration; perform frequency domain integration processing on the simple harmonic signal according to a preset number of times to obtain harmonics of the displacement; and superimpose the harmonics based on a preset signal processing method to obtain the displacement.

[0118] An embodiment of the present application further provides a vehicle, comprising: a memory storing an executable program; and a processor for running the program, wherein the method in each embodiment of the present invention is executed when the program is running.

[0119] An embodiment of the present application further provides a computer-readable storage medium, which includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0120] An embodiment of the present application further provides a computer program product, including a computer program, which implements the methods in various embodiments of the present invention when executed by a processor.

[0121] An embodiment of the present application further provides a computer program product, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0122] The embodiments of the present application further provide a computer program, which implements the methods in the above-mentioned embodiments of the present invention when executed by a processor.

[0123] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0124] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0125] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0126] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0127] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0128] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for identifying vehicle body loads based on the displacement of a rail vehicle using a virtual test bench, characterized in that: include: By testing the rail vehicle, the acceleration of the rail vehicle during the test is determined, wherein the acceleration includes: a plurality of vertical accelerations of a bolster of the rail vehicle and a plurality of lateral accelerations of a body of the rail vehicle; Integrating the acceleration to obtain a displacement corresponding to the acceleration, wherein the displacement includes: a plurality of vertical displacements of the bolster during the test and a plurality of lateral displacements of the vehicle body during the test; The load of the body of the rail vehicle is obtained by using the pre-trained virtual test bench with the displacement as an iteration target, wherein the load is used to reflect the vibration state and stress state of the body of the rail vehicle in the actual operating state.

2. The method according to claim 1, characterized in that The method further comprises: Based on the load, a stress state of the vehicle body is obtained.

3. The method according to claim 1, characterized in that The vehicle body load of the rail vehicle is obtained by using a pre-trained virtual test bench with the displacement as an iteration target, including: Based on the test displacement, the initial virtual test bench is systematically identified and iterated to obtain the load of the virtual test bench, wherein the load of the virtual test bench is the displacement obtained by the final drive test, and the driving load corresponding to the relative root mean square error value of the test displacement is less than a preset threshold.

4. The method according to claim 3, characterized in that Based on the test displacement, the initial virtual test bench is systematically identified and iterated to obtain the load of the virtual test bench, including: In response to the initial virtual test bench being excited, obtaining the product of the initial drive and the frequency response function and the first weighting coefficient, thereby obtaining the response drive of the rail vehicle, wherein the initial drive is the initial drive input after the virtual test bench is excited; In response to a relative root mean square error value between the response drive and the initial drive being greater than or equal to a preset threshold, repeatedly performing the step of obtaining the virtual test bench based on the response drive, the frequency response function, and the initial drive until it is determined that the relative root mean square error value between the response drive and the initial drive is less than a preset threshold, and determining that the response drive is a target drive; The load of the virtual test bench is obtained based on the target drive.

5. The method according to claim 4, characterized in that Repeating the step of obtaining the virtual test bench based on the response drive, the frequency response function and the initial drive includes: Obtaining a difference between the initial drive and the response drive to obtain an error drive; Obtaining the product of the error drive, the frequency response function and a second weighting coefficient to obtain an updated variable; Obtaining a sum of the update variable and the response driver to obtain an updated response driver; In response to the relative root mean square error value between the updated response drive and the initial drive being greater than or equal to the preset threshold, repeatedly obtaining the updated error drive and the updated update variable, obtaining the updated response drive based on the updated error drive and the updated update variable, and determining whether the relative root mean square error value between the updated response drive and the initial drive is greater than or equal to the preset threshold, until the relative root mean square error value between the updated response drive and the initial drive is less than the preset threshold; In response to a relative root mean square error value between the updated response drive and the initial drive being less than the preset threshold, determining the updated response drive as the target drive; The load of the virtual test bench is obtained based on the target drive.

6. The method according to claim 1, characterized in that The method includes testing a rail vehicle and determining an acceleration of the rail vehicle during the test, including: The initial acceleration of the rail vehicle is obtained based on preset test conditions, wherein the preset test conditions include one of the following: a line operation dynamic response test, an indoor vehicle vibration test bench, and the test conditions of the line operation dynamic response test need to cover the actual driving environment of the rail vehicle; Performing signal preprocessing on the initial acceleration to obtain the initial acceleration after burrs are removed, wherein the initial acceleration is a plurality of vertical accelerations of the bolster of the rail vehicle and a plurality of lateral accelerations of the body of the rail vehicle collected by sensors; The initial acceleration after the burrs are removed is compressed based on a preset threshold to obtain the acceleration.

7. The method according to claim 1, characterized in that Integrating the acceleration to obtain the displacement corresponding to the acceleration includes: Performing discrete Fourier transform on the acceleration to obtain a simple harmonic signal of the acceleration; Performing frequency domain integration on the simple harmonic signal according to a preset number of times to obtain harmonics of the displacement; The harmonics are superimposed based on a preset signal processing method to obtain the displacement.

8. A vehicle body load identification system for a rail vehicle based on a virtual test bench, characterized in that: include: A first component, wherein the first component is used to obtain the acceleration of the rail vehicle during the test; A second component, wherein the second component is used to obtain a displacement corresponding to the acceleration; A third component, wherein the third component is used to control the virtual experiment table to perform virtual iteration; A fourth component, wherein the fourth component is used to obtain a body load of the rail vehicle; A display area, wherein the display area is used to display the acceleration, the displacement and the vehicle body load.

9. The system according to claim 8, characterized in that The system further comprises: A fifth component, wherein the fifth component is used to obtain an initial drive of the virtual experimental platform; A sixth component, wherein the sixth component is used to obtain a response drive of the virtual experimental platform; A seventh component, wherein the seventh component is used to obtain a frequency response function of the virtual experimental platform; The display area is also used to display the initial drive, the response drive and the frequency response function.

10. The system according to claim 8, characterized in that The system further comprises: an eighth component, wherein the eighth component is used to generate a noise signal; A ninth component, wherein the ninth component is used to obtain a sampling frequency; The display area is also used to display the noise signal and the sampling frequency, as well as the starting frequency and the cutoff frequency of the sampling frequency.

11. A vehicle, characterized in that: include: A memory storing an executable program; A processor, configured to run the program, wherein the program executes the method according to any one of claims 1 to 7 when running.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored executable program, wherein when the executable program is run, the device where the storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

13. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 7.

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