CN114048643A

CN114048643A - Modeling method of virtual vibration system based on compound control and related equipment

Info

Publication number: CN114048643A
Application number: CN202111053304.0A
Authority: CN
Inventors: 赵艳涛; 李健
Original assignee: CASIC Defense Technology Research and Test Center
Current assignee: CASIC Defense Technology Research and Test Center
Priority date: 2021-09-08
Filing date: 2021-09-08
Publication date: 2022-02-15
Anticipated expiration: 2041-09-08
Also published as: CN114048643B

Abstract

The present disclosure provides a virtual vibration system modeling method and related equipment based on compound control, the method includes: acquiring a control spectrum in the i-th random vibration process of a mechanical model of a shaking table at the current moment; The reference spectrum at the current moment is generated from the spectrum; in response to determining that the control spectrum that is not within the tolerance range of the reference spectrum is the target control spectrum, the following operations are performed: based on the target control spectrum, a corresponding driving PSD spectrum is obtained; driving is obtained from the driving PSD spectrum The amplitude information of the spectrum and random phase information are added, and the inverse Fourier transform is performed on the driving spectrum containing the amplitude and phase information to obtain the pseudo-random signal corresponding to the driving spectrum; the pseudo-random signal is subjected to time-domain randomization to obtain a The time domain driving signal in the next random vibration process is obtained and the mechanical model of the shaking table is controlled.

Description

Virtual vibration system modeling method based on composite control and related equipment

Technical Field

The disclosure relates to the technical field of virtual vibration system modeling, in particular to a virtual vibration system modeling method based on composite control and related equipment.

Background

With the rapid development of virtual test technology, the method is widely applied to the fields of aviation, aerospace, national defense and military. The virtual test technology can reduce huge investment and shorten the development period, thereby making up for the lack of the capability of large-scale test equipment.

At present, the current virtual vibration test is mainly open-loop vibration in finite element software, and random virtual vibration and sinusoidal virtual vibration exist in closed-loop virtual vibration. A closed-loop virtual vibration system constructed by combining broadband random vibration and narrowband random vibration control with a vibration table model does not exist.

Disclosure of Invention

In view of the above, the present disclosure is directed to a method and related apparatus for modeling a virtual vibration system based on compound control, which solve the above problems.

In view of the above, a first aspect of the present disclosure provides a virtual vibration system modeling method based on composite control, including:

acquiring a control spectrum in the ith random vibration process of the mechanical model of the vibration table at the current moment, wherein i is more than or equal to 1;

generating a reference spectrum of the current moment based on the narrow-band random spectrum and the wide-band random spectrum, wherein the reference spectrum of each moment corresponds to the control spectrum in at least one random vibration;

in response to determining that a control spectrum that is not within a tolerance range of the reference spectrum is a target control spectrum, and performing the following:

obtaining a corresponding driving PSD spectrum based on the target control spectrum;

obtaining amplitude information of a corresponding drive spectrum from the drive PSD spectrum, adding random phase information to the amplitude information, and performing inverse Fourier transform on the drive spectrum containing the amplitude information and the phase information to obtain a pseudo-random signal corresponding to the drive spectrum;

and controlling the mechanical model of the vibration table according to the time domain driving signal.

Further, the control spectrum is calculated by the following formula:

wherein R is_cc(τ)^t _iRepresenting the autocorrelation function, G, of the time-domain acceleration signal during the ith random vibration at time t_cc(f)^t _iIndicating control during the ith random vibration at time tSpectrum, f represents frequency, and f ≧ 0.

Further, in the 1 st random vibration process, the driving PSD spectrum is calculated by the following formula:

G_dd(f)^t _i＝|H(f)^-1|²G_ref(f)^t

wherein G is_dd(f)^t _iA driving PSD spectrum of the ith random vibration process corresponding to the reference spectrum at the time t, wherein i is 1, | H (f) | represents the transfer function of the control system, and G_ref(f)^tRepresenting the reference spectrum at time t.

Further, in the (i + 1) th random vibration process, the control spectrum in the last random vibration process is equalized to obtain a driving PSD spectrum in the (i + 1) th random vibration process, where the driving PSD spectrum is obtained by calculation according to the following formula:

wherein G is_dd(f)^t _i+1The driving PSD spectrum of the (i + 1) th random vibration process corresponding to the reference spectrum at the time t, G_cc(f)^t _iShowing the control spectrum in the ith random vibration process within the time t.

Further, amplitude information | D of the drive spectrum_dThe computational expression of | is as follows:

wherein, | D_dL represents the modulus of the time domain signal for fourier transformation, N represents the length of the sample sequence, and Δ t represents the time interval of the samples.

Further, the drive spectrum of the added random phase signal is calculated by:

D_d(f)＝|D_d|e^jθ

wherein D is_d(f) Denotes increasing the drive spectrum of the random phase signal, θ denotes uniformly distributed random phases, and j denotes an imaginary unit.

Further, the mechanical model of the vibration table is constructed by:

establishing a moving coil model through finite element analysis software according to the geometric dimension, material and quality of the moving coil of the vibrating table;

and carrying out boundary processing on the moving coil model, and carrying out model calibration on parameters of the moving coil model subjected to the boundary processing according to the moving coil of the vibrating table so as to obtain the mechanical model of the vibrating table.

Further, the boundary processing object comprises a suspension spring and a guide device;

the parameters of the moving coil model comprise: model density, modal simulation frequency, stiffness of the suspension spring, and axial modal frequency of the moving coil.

Based on the same inventive concept, the second aspect of the present disclosure provides a virtual vibration system modeling apparatus based on composite control, including:

a control spectrum acquisition module: the method comprises the steps of obtaining a control spectrum in the ith random vibration process of a mechanical model of the vibration table at the current moment, wherein i is more than or equal to 1;

a reference spectrum generation module: configured to generate a reference spectrum for a current time based on a narrow band and a wide band, wherein the reference spectrum for each time corresponds to the control spectrum in at least one random vibration;

a random vibration iteration module: is configured to, in response to determining that a control spectrum that is not within a tolerance range of the reference spectrum is a target control spectrum, perform the following:

Based on the same inventive concept, a third aspect of the present disclosure provides an electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of the first aspect when executing the program.

From the above, the virtual vibration system modeling method based on composite control and the related device provided by the disclosure fill up the blank of virtual vibration system modeling based on broadband random vibration and narrowband random combined control, and perform pre-test analysis before performing a physical test by using the vibration system based on composite control, so that the test design is optimized, and the physical test is ensured to be performed smoothly.

Drawings

In order to more clearly illustrate the technical solutions in the present disclosure or related technologies, the drawings needed to be used in the description of the embodiments or related technologies are briefly introduced below, and it is obvious that the drawings in the following description are only embodiments of the present disclosure, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.

FIG. 1 is a flow chart of a method for modeling a virtual vibration system based on compound control according to an embodiment of the present disclosure;

FIG. 2 is a schematic structural diagram of a virtual vibration system modeling apparatus based on compound control according to an embodiment of the present disclosure;

fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure.

Detailed Description

For the purpose of promoting a better understanding of the objects, aspects and advantages of the present disclosure, reference is made to the following detailed description taken in conjunction with the accompanying drawings.

It is to be noted that technical terms or scientific terms used in the embodiments of the present disclosure should have a general meaning as understood by those having ordinary skill in the art to which the present disclosure belongs, unless otherwise defined. The use of "first," "second," and similar terms in the embodiments of the disclosure is not intended to indicate any order, quantity, or importance, but rather to distinguish one element from another. The word "comprising" or "comprises", and the like, means that the element or item listed before the word covers the element or item listed after the word and its equivalents, but does not exclude other elements or items.

As described in the background section, the existing modeling method of the virtual vibration system is still difficult to meet the needs, and the applicant finds that random virtual vibration and sinusoidal virtual vibration in a virtual vibration test in the process of implementing the present disclosure, but a closed-loop virtual vibration system constructed by a vibration table model combining broadband random vibration and narrow-band random vibration control is not available yet.

In view of this, the embodiment of the present disclosure provides a virtual vibration system modeling method based on composite control, in which a virtual vibration system is modeled as two parts, one part is modeled as a vibration control system, the other part is modeled as a mechanical part of a vibration table, and finally the two parts of models are interconnected to obtain a whole virtual vibration system, so as to simulate a real object vibration test. In addition, a pre-test analysis is carried out based on the established virtual vibration system, so that the number and the positions of the sensors on the vibration table are determined, the optimization of test design is facilitated, and the smooth performance of a physical test is ensured.

Hereinafter, the technical means of the present disclosure will be described in detail by specific examples.

Referring to fig. 1, a method for modeling a virtual vibration system based on compound control according to an embodiment of the present disclosure includes the following steps:

and S101, acquiring a control spectrum in the ith random vibration process of the mechanical model of the vibration table at the current moment.

In this step, the value of i is greater than or equal to 1, and i in all embodiments of the present disclosure is a positive integer, which is not described in detail later. The control spectrum is a time domain acceleration signal acquired by a sensor arranged on a mechanical model of the vibration table, the time domain acceleration signal is a stable random signal, and the corresponding control spectrum is obtained through calculation according to the time domain acceleration signal.

In addition, a control spectrum in the Nth random vibration process at any moment can be calculated by an average periodogram method.

Step S102, generating a reference spectrum of the current moment based on the narrow-band random spectrum and the wide-band random spectrum, wherein the reference spectrum of each moment corresponds to the control spectrum in at least one random vibration.

In this step, a narrow-band stochastic spectrum is superimposed on the wide-band stochastic spectrum, and the narrow-band stochastic spectrum moves at a preset rate, thereby generating a reference spectrum G at the current time t_ref(f)^t。

Step S103, responding to the control spectrum which is determined not to be in the tolerance range of the reference spectrum as the target control spectrum, and executing the steps S104 to S106.

Step S104, based on the target control spectrum, a corresponding Power Spectral Density (PSD) spectrum is obtained.

And step S105, obtaining amplitude information corresponding to the drive spectrum from the drive PSD spectrum, adding random phase information to the amplitude information, and performing inverse Fourier transform on the drive spectrum containing the amplitude information and the phase information to obtain a pseudo-random signal corresponding to the drive spectrum.

In this step, the driving PSD spectrum is a frequency domain signal, which can only obtain amplitude information but lacks phase information, and in order to convert the frequency domain signal into a time domain signal, the driving PSD spectrum needs to be converted to obtain amplitude information and then phase information is added, specifically, random phase information which is uniformly distributed can be added to the amplitude information obtained by converting the driving PSD spectrum, so as to convert the frequency domain signal into the time domain signal.

Specifically, the pseudo-random signal is calculated by the following formula:

D_d(t)＝IFFT(D_d(f))

wherein D is_d(t) represents a pseudo-random signal.

And step S106, performing time domain randomization processing on the pseudo-random signal to obtain a time domain driving signal in the next random vibration process.

In this step, a signal generated after the inverse fourier transform is a pseudorandom signal, a frequency spectrum of the pseudorandom signal is a discrete spectrum, energy is concentrated on a frequency point of an original frequency spectrum, and in order to generate a true random signal, the pseudorandom signal needs to be subjected to random delay, inversion, windowing and superposition in sequence, so as to finally obtain a time domain drive signal.

And S107, controlling the mechanical model of the vibration table according to the time domain driving signal.

It can be seen that the technical scheme provided by this embodiment is different from the single open-loop random vibration simulation performed by using finite element software, and in this technical scheme, a vibration control model is used to perform closed-loop control on a mechanical model of a vibration table, and a physical vibration test also uses closed-loop control, so that the vibration control model is more consistent with the physical vibration test.

In some embodiments, the control spectrum may be calculated by:

wherein R is_cc(τ)^t _iRepresenting the autocorrelation function, G, of the time-domain acceleration signal during the ith random vibration at time t_cc(f)^t _iThe control spectrum in the ith random vibration process in the time t is shown, f represents the frequency, and f is more than or equal to 0.

In some embodiments, during the 1 st random vibration, the drive PSD spectrum is calculated by:

G_dd(f)^t _i＝|H(f)^-1|²G_ref(f)^t

wherein G is_dd(f)^t _iReference indicating time tThe spectrum corresponds to a driving PSD spectrum of the ith random vibration process, i is equal to 1, | H (f) | represents a transfer function of a control system, and G_ref(f)^tRepresenting the reference spectrum at time t.

In some embodiments, in the (i + 1) th random vibration process, the control spectrum in the last random vibration process is equalized to obtain a driving PSD spectrum in the (i + 1) th random vibration process, where the driving PSD spectrum is calculated by the following formula:

In some embodiments, the magnitude information | D of the drive spectrum_dThe computational expression of | is as follows:

In some embodiments, the drive spectrum for adding a random phase signal is calculated by:

D_d(f)＝|D_d|e^jθ

In some embodiments, the mechanical model of the vibration table is constructed by:

In some embodiments, the boundary-processed object includes a suspension spring and a guide;

In this embodiment, the radial direction of the suspension spring can be connected to the periphery of the table top by using a stiffness damping spring, and the stiffness damping spring is connected to the central guide part of the suspension spring, and only the axial degree of freedom is reserved, wherein the axial direction of the stiffness damping spring is determined by the axial stiffness of the suspension spring and the air spring (part of the vibration table).

Correspondingly, the guiding effect of the guiding device on the moving coil is simulated by a Multi-point constraint unit (MPC), a lower end node of the MPC unit is fixedly connected with the spring unit, and all MPC units retain axial translation freedom.

In addition, in order to ensure that the constructed moving coil model is consistent with a real object, firstly, the density of the model needs to be adjusted to be consistent with the density of the actual moving coil, and then, the elastic modulus is adjusted to ensure that the modal simulation frequency of the moving coil model is consistent with the real object modal simulation test result, so that the modal error frequency is ensured to be within 5%. Specifically, a constant-voltage characteristic curve and a constant-current characteristic curve of the empty vibrating table can be measured actually to calibrate the moving coil model, the low-order resonance frequency of the constant-current characteristic curve corresponds to the rigidity of the suspension spring, and the high-order resonance frequency of the constant-current characteristic curve and the high-order resonance frequency of the constant-voltage characteristic curve correspond to the axial modal frequency of the moving coil model.

When the virtual test is actually carried out, the tested product model can be connected with the moving coil model, and then the moving coil model is calibrated, so that the mechanical model of the vibration table is obtained.

After the mechanical model of the vibration table is calibrated, the mechanical model and the vibration control model are combined to form a whole virtual vibration system, a plurality of positions on the tested product model can be provided with sensors, and the vibration response conditions of the plurality of positions can be obtained after the virtual vibration test is carried out, so that the advantages and the disadvantages of product design can be conveniently known, the design iteration update is accelerated at the model stage, and the design process is accelerated.

It should be noted that the method of the embodiments of the present disclosure may be executed by a single device, such as a computer or a server. The method of the embodiment can also be applied to a distributed scene and completed by the mutual cooperation of a plurality of devices. In such a distributed scenario, one of the devices may only perform one or more steps of the method of the embodiments of the present disclosure, and the devices may interact with each other to complete the method.

It should be noted that the above describes some embodiments of the disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments described above and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

Based on the same inventive concept, corresponding to the method of any embodiment, the disclosure also provides a virtual vibration system modeling device based on composite control.

Referring to fig. 2, the virtual vibration system modeling apparatus based on composite control includes:

the control spectrum acquisition module 201: the method is configured to obtain a control spectrum in the ith random vibration process of the mechanical model of the vibration table at the current moment, wherein i is larger than or equal to 1.

The reference spectrum generation module 202: configured to generate a reference spectrum for a current time instant based on a narrow band and a wide band, wherein the reference spectrum for each time instant corresponds to the control spectrum in at least one random vibration.

Random vibration iteration module 203: is configured to, in response to determining that a control spectrum that is not within a tolerance range of the reference spectrum is a target control spectrum, perform the following:

performing time domain randomization on the pseudo-random signal to obtain a time domain driving signal in the next random vibration process;

As an alternative embodiment, the control spectrum is calculated by the following formula:

As an alternative embodiment, in the 1 st random vibration process, the driving PSD spectrum is calculated by the following formula:

G_dd(f)^t _i＝|H(f)^-1|²G_ref(f)^t

As an optional embodiment, in the i +1 th random vibration process, the control spectrum in the last random vibration process is equalized to obtain a driving PSD spectrum in the i +1 th random vibration process, where the driving PSD spectrum is calculated by the following formula:

As an alternative embodiment, the amplitude information | D of the drive spectrum_dThe computational expression of | is as follows:

As an alternative embodiment, the drive spectrum for adding a random phase signal is calculated by:

D_d(f)＝|D_d|e^jθ

As an alternative embodiment, referring to fig. 2, the apparatus further comprises a mechanical model building module 204 configured to build a moving coil model by finite element analysis software according to the geometry, material and mass of the vibrating table moving coil; and carrying out boundary processing on the moving coil model, and carrying out model calibration on parameters of the moving coil model subjected to the boundary processing according to the moving coil of the vibrating table so as to obtain the mechanical model of the vibrating table.

As an alternative embodiment, the boundary processing object includes a suspension spring and a guide device;

For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, the functionality of the various modules may be implemented in the same one or more software and/or hardware implementations of the present disclosure.

The device of the above embodiment is used to implement the virtual vibration system modeling method based on composite control in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiment, which are not described herein again.

Based on the same inventive concept, corresponding to any of the above embodiments, the present disclosure further provides an electronic device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, the virtual vibration system modeling method based on composite control according to any of the above embodiments is implemented.

Fig. 3 is a schematic diagram illustrating a more specific hardware structure of an electronic device according to this embodiment, where the electronic device may include: a processor 1010, a memory 1020, an input/output interface 1030, a communication interface 1040, and a bus 1050. Wherein the processor 1010, memory 1020, input/output interface 1030, and communication interface 1040 are communicatively coupled to each other within the device via bus 1050.

The processor 1010 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits, and is configured to execute related programs to implement the technical solutions provided in the embodiments of the present disclosure.

The Memory 1020 may be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, or the like. The memory 1020 may store an operating system and other application programs, and when the technical solution provided by the embodiments of the present specification is implemented by software or firmware, the relevant program codes are stored in the memory 1020 and called to be executed by the processor 1010.

The input/output interface 1030 is used for connecting an input/output module to input and output information. The i/o module may be configured as a component in a device (not shown) or may be external to the device to provide a corresponding function. The input devices may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output devices may include a display, a speaker, a vibrator, an indicator light, etc.

The communication interface 1040 is used for connecting a communication module (not shown in the drawings) to implement communication interaction between the present apparatus and other apparatuses. The communication module can realize communication in a wired mode (such as USB, network cable and the like) and also can realize communication in a wireless mode (such as mobile network, WIFI, Bluetooth and the like).

Bus 1050 includes a path that transfers information between various components of the device, such as processor 1010, memory 1020, input/output interface 1030, and communication interface 1040.

It should be noted that although the above-mentioned device only shows the processor 1010, the memory 1020, the input/output interface 1030, the communication interface 1040 and the bus 1050, in a specific implementation, the device may also include other components necessary for normal operation. In addition, those skilled in the art will appreciate that the above-described apparatus may also include only those components necessary to implement the embodiments of the present description, and not necessarily all of the components shown in the figures.

The electronic device of the above embodiment is used to implement the virtual vibration system modeling method based on composite control in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiment, which are not described herein again.

Based on the same inventive concept, corresponding to any of the above-described embodiment methods, the present disclosure also provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the virtual vibration system modeling method based on composite control according to any of the above embodiments.

Computer-readable media of the present embodiments, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.

The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the virtual vibration system modeling method based on composite control according to any of the above embodiments, and have the beneficial effects of corresponding method embodiments, which are not described herein again.

Those of ordinary skill in the art will understand that: the discussion of any embodiment above is meant to be exemplary only, and is not intended to intimate that the scope of the disclosure, including the claims, is limited to these examples; within the idea of the present disclosure, also technical features in the above embodiments or in different embodiments may be combined, steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present disclosure as described above, which are not provided in detail for the sake of brevity.

In addition, well-known power/ground connections to Integrated Circuit (IC) chips and other components may or may not be shown in the provided figures for simplicity of illustration and discussion, and so as not to obscure the embodiments of the disclosure. Furthermore, devices may be shown in block diagram form in order to avoid obscuring embodiments of the present disclosure, and this also takes into account the fact that specifics with respect to implementation of such block diagram devices are highly dependent upon the platform within which the embodiments of the present disclosure are to be implemented (i.e., specifics should be well within purview of one skilled in the art). Where specific details (e.g., circuits) are set forth in order to describe example embodiments of the disclosure, it should be apparent to one skilled in the art that the embodiments of the disclosure can be practiced without, or with variation of, these specific details. Accordingly, the description is to be regarded as illustrative instead of restrictive.

While the present disclosure has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art in light of the foregoing description. For example, other memory architectures (e.g., dynamic ram (dram)) may use the discussed embodiments.

The disclosed embodiments are intended to embrace all such alternatives, modifications and variances which fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalents, improvements, and the like that may be made within the spirit and principles of the embodiments of the disclosure are intended to be included within the scope of the disclosure.

Claims

1. A virtual vibration system modeling method based on composite control, comprising:

Obtain the control spectrum during the i-th random vibration process of the mechanical model of the shaking table at the current moment, where i≥1;

Generate a reference spectrum at the current moment based on the narrowband random spectrum and the broadband random spectrum, wherein the reference spectrum at each moment corresponds to the control spectrum in at least one random vibration;

In response to determining that a control spectrum that is not within the tolerance of the reference spectrum is the target control spectrum, perform the following actions:

Based on the target control spectrum, a corresponding drive PSD spectrum is obtained;

Obtaining the amplitude information of the corresponding driving spectrum from the driving PSD spectrum, adding random phase information to the amplitude information, and performing inverse Fourier transform on the driving spectrum including the amplitude information and the phase information to obtain obtaining a pseudo-random signal corresponding to the driving spectrum;

performing time-domain randomization processing on the pseudo-random signal to obtain a time-domain driving signal in the next random vibration process;

The shaker mechanical model is controlled based on the time domain drive signal.

2. The modeling method according to claim 1, wherein the control spectrum is calculated by the following formula:

Among them, R _cc (τ) ^t _i represents the autocorrelation function of the time-domain acceleration signal during the i-th random vibration process at time t, and G _cc (f) ^t _i represents the control spectrum during the i-th random vibration process at time t , f represents the frequency, and f≥0.

3. The modeling method according to claim 1, wherein, in the 1st random vibration process, the drive PSD spectrum is calculated by the following formula:

G _dd (f) ^t _i =|H(f) ^-1 | ² G _ref (f) ^t

Among them, G _dd (f) ^t _i represents the driving PSD spectrum of the i-th random vibration process corresponding to the reference spectrum at time t, and i=1, |H(f)| represents the transfer function of the control system, G _ref ( f) ^t represents the reference spectrum at time t.

4. The modeling method according to claim 3, wherein, in the i+1st random vibration process, the control spectrum in the last random vibration process is equalized to obtain the i+1st random vibration process The driving PSD spectrum in , which is calculated by the following formula:

Among them, G _dd (f) ^t _i+1 represents the driving PSD spectrum of the i+1th random vibration process corresponding to the reference spectrum at time t, and G _cc (f) ^t _i represents the i-th random vibration process at time t in the control spectrum.

5. The modeling method according to claim 3, wherein the calculation expression of the amplitude information |D _d | of the driving spectrum is as follows:

Among them, |D _d | represents the modulus of the Fourier transform of the time domain signal, N represents the length of the sampling sequence, and Δt represents the sampling time interval.

6. The modeling method according to claim 5, wherein, the driving spectrum of adding random phase signal is calculated by the following formula:

D _d (f)=|D _d |e ^jθ

Among them, D _d (f) represents the driving spectrum for increasing the random phase signal, θ represents the uniformly distributed random phase, and j represents the imaginary unit.

7. The modeling method of claim 1, wherein the shaker mechanical model is constructed by:

According to the geometric size, material and mass of the moving coil of the shaking table, the moving coil model is established by the finite element analysis software;

Boundary processing is performed on the moving coil model, and model calibration is performed on the parameters of the moving coil model after boundary processing according to the moving coil of the shaking table, so as to obtain the mechanical model of the shaking table.

8. The modeling method according to claim 7, wherein the objects of the boundary processing include suspension springs and guides;

The parameters of the moving coil model include: model density, modal simulation frequency, stiffness of the suspension spring, and axial modal frequency of the moving coil.

9. A virtual vibration system modeling device based on compound control, comprising:

Control spectrum acquisition module: configured to acquire the control spectrum in the i-th random vibration process of the mechanical model of the shaking table at the current moment, where i≥1;

Reference spectrum generation module: configured to generate a reference spectrum at the current moment based on narrowband and broadband, wherein the reference spectrum at each moment corresponds to the control spectrum in at least one random vibration;

A random vibration iteration module: configured to, in response to determining a control spectrum not within the tolerance range of the reference spectrum, be the target control spectrum, and to perform the following operations:

10. An electronic device comprising a memory, a processor and a computer program stored on the memory and running on the processor, the processor implementing the program according to any one of claims 1 to 9 when the processor executes the program method.