Spatial cross-correlation multi-point seismic oscillation synthesis method and device for fitting response spectrum

Abstract

The invention discloses a spatial cross-correlation multipoint seismic motion synthesis method and device for fitting a response spectrum, and the method comprises the steps: obtaining a seismic motion acceleration time history of a high-precision fitting target response spectrum through an influence matrix method, and calculating a Fourier amplitude spectrum and a phase spectrum of the seismic motion acceleration time history; a calculation relation between a power spectrum density function and a Fourier amplitude spectrum is considered, the power spectrum density function of the obtained time history is used as an initial value, a random vibration theory and Cholesky decomposition are utilized to obtain a spatial cross-correlation multi-point seismic oscillation time history, a phase spectrum of the seismic oscillation time history of a high-precision fitting target response spectrum is further included, and the spatial cross-correlation multi-point seismic oscillation time history is obtained. And the spatial cross-correlation multi-point seismic oscillation of the fitting response spectrum can be obtained through correction iteration. According to the method, the defects that the fitting effect with the target response spectrum and the non-stability of the synthesized seismic oscillation are difficult to guarantee in the current multipoint seismic oscillation time-history synthesis technology are overcome, and the reliability of a dynamic response analysis result of a large-scale engineering structure under the multipoint seismic oscillation effect is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of structural seismic design and analysis, and in particular to a spatial cross-correlation multi-point seismic motion synthesis method and device for fitting a response spectrum. Background Art

[0002] Earthquake motion is a temporal process with spatial variation, involving both space and time. The factors that cause spatial variation of earthquake motion mainly include site effect, coherence effect, traveling wave effect and attenuation effect. When an earthquake occurs, the energy released from the earthquake source is transmitted to the ground in the form of waves, causing ground vibration. The earthquake waves received at different points on the ground pass through different paths, different site conditions and are refracted and reflected in different media. The vibrations reflected on the surface are bound to be not exactly the same, but there is also a certain correlation. The correlation of earthquake motion is determined by factors such as the earthquake source, propagation path, and site conditions.

[0003] The parameter changes of ground motion from one point to another can be described by the cross-power spectral density of ground motion acceleration, and its standardization is called coherence function. Coherence function is often used to represent the similarity of ground motions at adjacent sites, and can be used to analyze the seismic response of multi-support structures and long structures. When conducting seismic analysis on long structures, it is necessary to input seismic motion data into the model. The first step of seismic analysis is to determine the input method of seismic motion, and considering the coherence of seismic motion is the basis for multi-point seismic motion input. Therefore, considering the synthetic spatial cross-correlation of multi-point seismic motion input is a more reasonable input mode for studying the seismic response of long structures.

[0004] Since earthquake motion is non-repeatable and cannot be accurately predicted, the damage it causes is irreversible and the losses it brings are also very serious. Therefore, the project must be seismically designed in accordance with the requirements of earthquake fortification and earthquake-resistant design specifications. Generally, the earthquake motion time history synthesized according to the requirements needs to consider its coherence effect and frequency domain non-stationarity. The method commonly used in the specifications is to match the synthesized earthquake motion response spectrum with the specification response spectrum or the site-specific response spectrum. However, the earthquake motion time history generated according to the traditional random vibration theory method cannot guarantee that the synthesized cross-correlated earthquake motion frequency is non-stationary, and the existing theories and technologies cannot meet the requirements of high-precision fitting of the synthesized multi-point earthquake motion seismic design response spectrum. Summary of the invention

[0005] Purpose of the invention: In view of the shortcomings of the prior art, the present invention provides a method for synthesizing spatial cross-correlated multi-point seismic motions of a fitting response spectrum, which is based on the influence matrix method of high-precision fitting response spectrum, takes into account the coherence effect of spatial seismic motions, and thus establishes a spatial multi-point non-stationary seismic motion of a fitting response spectrum.

[0006] Another object of the present invention is to provide a spatially cross-correlated multi-point earthquake motion synthesis device, a computer device and a computer storage medium for a corresponding fitting response spectrum.

[0007] Technical solution: In the first aspect, a spatial cross-correlation multi-point seismic synthesis method for fitting response spectra comprises the following steps:

[0008] (1) Based on the properties of the target response spectrum, the natural earthquake time history A(t) is selected, and the influence matrix method is used to adjust the selected natural earthquake response spectrum to a earthquake time history A(t) that fits the target response spectrum with high accuracy. C (t), and use Fourier transform to calculate the single-sided Fourier amplitude spectrum F(ω) and phase spectrum of the time course

[0009] (2) Based on the obtained one-sided Fourier amplitude spectrum F(ω), the earthquake time history A that fits the target response spectrum with high precision is calculated. C (t) energy spectral density function P(ω), and use P(ω) as the initial power spectral density function S(ω);

[0010] (3) Based on the power spectrum density function S(ω), the coordinates of each seismic wave input point on the site and the selected coherence function model, the auto-power spectrum S of each point is calculated respectively. jj (ω) and the cross power spectrum S between each point jk (iω), thus forming a power spectrum matrix S(iω), where i is an imaginary unit, j and k are the serial numbers of the seismic wave input points;

[0011] (4) Based on the power spectrum matrix S(iω), the cross-correlation Fourier amplitude and cross-correlation phase angle of different frequency components of different seismic wave input points are obtained by Cholesky decomposition. The uniformly distributed random phase is used to synthesize a stable multi-point ground motion time history, which is taken into account in the phase spectrum of the ground motion time history of the high-precision fitting target response spectrum obtained in step (1). Synthesize non-stationary multi-point ground motion time history;

[0012] (5) Calculate the relative error between the acceleration response spectrum of the earthquake time history at each input point and the target response spectrum. If the fitting accuracy does not meet the requirements, correct the input power spectrum density function and repeat steps (3) to (5) until the fitting accuracy meets the requirements.

[0013] Furthermore, the natural ground motion time history is selected based on the properties of the target response spectrum, including:

[0014] Select natural ground motion time histories whose site type, source characteristics, and response spectrum shapes are similar to the target response spectrum.

[0015] Furthermore, based on the obtained one-sided Fourier amplitude spectrum F(ω), the earthquake time history A that fits the target response spectrum with high precision is calculated. C The energy spectral density function P(ω) of (t) is calculated as follows:

[0016]

[0017] Among them, t m =t 5-75 It is the duration of a strong earthquake required to increase from 5% to 75% of the Arias intensity.

[0018] Furthermore, the power spectrum S of each point jj (ω) and the cross power spectrum S between each point jk (iω) is calculated as follows:

[0019]

[0020] In the formula, γ nm (iω k ) is the coherence function, |γ nm (iω k )| is the hysteresis coherence function, which is used to describe the coherence effect of ground motion between two points; Represents the phase angle between the ground motions at two points, used to describe the traveling wave effect; d nm Represents the distance between two points along the propagation direction, V app is the apparent wave velocity.

[0021] Furthermore, the corrected input power spectral density function uses the following formula:

[0022]

[0023] Among them, TRS is the target response spectrum, and ARS is the earthquake acceleration response spectrum in the iterative calculation process.

[0024] In a second aspect, a spatial cross-correlation multi-point earthquake motion synthesis device for fitting a response spectrum is provided, comprising:

[0025] The target response spectrum fitting module is used to select the natural earthquake time history A(t) based on the properties of the target response spectrum, and adjust the selected natural earthquake response spectrum to the earthquake time history A(t) that fits the target response spectrum with high precision using the influence matrix method. C (t), and use Fourier transform to calculate the single-sided Fourier amplitude spectrum F(ω) and phase spectrum of the time course

[0026] The power spectrum density function calculation module is used to calculate the earthquake time history A of the target response spectrum with high precision based on the obtained single-sided Fourier amplitude spectrum F(ω). C(t) energy spectral density function P(ω), and use P(ω) as the initial power spectral density function S(ω);

[0027] The power spectrum matrix calculation module is used to calculate the auto-power spectrum S of each point based on the power spectrum density function S(ω), the coordinates of each seismic wave input point in the site and the selected coherence function model. jj (ω) and the cross power spectrum S between each point jk (iω), thus forming a power spectrum matrix S(iω), where i is an imaginary unit, j and k are the serial numbers of the seismic wave input points;

[0028] The multi-point seismic motion synthesis module is used to obtain the cross-correlation Fourier amplitude and cross-correlation phase angle of different frequency components of different seismic wave input points based on the power spectrum matrix S(iω) through Cholesky decomposition, and synthesize the stable multi-point seismic motion time history using uniformly distributed random phases, and take into account the phase spectrum of the seismic motion time history that fits the target response spectrum with high precision obtained by the target response spectrum fitting module Synthesize non-stationary multi-point ground motion time history;

[0029] The iterative control module is used to calculate the relative error between the acceleration response spectrum of the earthquake time history of each input point and the target response spectrum. If the fitting accuracy does not meet the requirements, the input power spectrum density function is corrected, and the operations of the power spectrum matrix calculation module and the multi-point earthquake synthesis module are repeated until the fitting accuracy meets the requirements.

[0030] Furthermore, in the power spectrum density function calculation module, based on the obtained single-sided Fourier amplitude spectrum F(ω), the earthquake time history A of the target response spectrum with high precision is calculated. C The energy spectral density function P(ω) of (t) is calculated as follows:

[0031]

[0032] Among them, t m =t 5-75 It is the duration of a strong earthquake required to increase from 5% to 75% of the Arias intensity.

[0033] Furthermore, in the power spectrum matrix calculation module, the power spectrum S of each point jj (ω) and the cross power spectrum S between each point jk (iω) is calculated as follows:

[0034]

[0035] In the formula, γ nm (iω k ) is the coherence function, |γ nm (iω k)| is the hysteresis coherence function, which is used to describe the coherence effect of ground motion between two points; Represents the phase angle between the ground motions at two points, used to describe the traveling wave effect; d nm Represents the distance between two points along the propagation direction, V app is the apparent wave velocity.

[0036] According to a third aspect, a computer device is provided, comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and when the programs are executed by the processors, the steps of the spatial cross-correlation multi-point seismic synthesis method of fitting response spectra as described in the first aspect of the present invention are implemented.

[0037] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the spatial cross-correlation multi-point seismic synthesis method of fitting response spectra as described in the first aspect of the present invention are implemented.

[0038] Beneficial effects: The present invention provides a method and device for synthesizing spatially cross-correlated multi-point seismic motions based on a fitting response spectrum. The influence matrix method is used to adjust the selected natural seismic motion time history so that its response spectrum can fit the target response spectrum with high precision within the full frequency range. The energy spectrum density function corresponding to the obtained time history is calculated and used as the initial power spectrum density function for synthesizing multi-point seismic motions. Combined with the phase spectrum of the aforementioned time history, the spatially cross-correlated non-stationary seismic motion time history that fits the target response spectrum is synthesized. The present invention overcomes the difficulties in ensuring the fitting effect with the target response spectrum and the non-stationarity of the synthesized seismic motion in the current multi-point seismic motion time history synthesis technology, and helps to improve the reliability of the dynamic response analysis results of large-scale engineering structures under the action of multi-point seismic motions. The iterative process of the present invention is monotonic and convergent, meets the requirements of the specification, and has strong practicality. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is an overall flow chart of a spatial cross-correlation multi-point seismic synthesis method for fitting response spectra according to an embodiment of the present invention.

[0040] Figure 2 The target response spectrum of the embodiment of the present invention, the response spectrum of the natural earthquake time history, and the response spectrum of the earthquake time history obtained by using the influence matrix method to fit the target response spectrum with high precision;

[0041] Figure 3 is the response spectrum of the spatially cross-correlated multi-point earthquake acceleration time history calculated by the embodiment of the present invention;

[0042] Figure 4 It is the spatially cross-correlated multi-point earthquake acceleration time history calculated by the embodiment of the present invention. DETAILED DESCRIPTION

[0043] The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

[0044] In one embodiment, the RG1.60 design spectrum is selected as the target design response spectrum, and the method of the present invention is used to generate a non-stationary multi-point earthquake input time history with spatial cross-correlation fitting the target response spectrum. Figure 1 As shown in FIG. 1 , a spatial cross-correlation multi-point ground motion synthesis method for fitting a response spectrum includes the following steps:

[0045] Step (1), selecting the RG1.60 design spectrum as the target design response spectrum, the number of frequency points of the target response spectrum RG1.60 design spectrum is M=301, and each frequency point in the frequency range [0.1, 100] Hz is evenly distributed in the logarithmic coordinate;

[0046] Step (2), select a natural earthquake time history with a site type, source characteristics and response spectrum shape similar to the target response spectrum. Use the influence matrix method to obtain the acceleration time history, velocity time history and displacement time history of the target response spectrum TRS with high precision, and use Fourier transform to calculate the Fourier amplitude spectrum and phase spectrum corresponding to the obtained acceleration time history;

[0047] The specific implementation steps are as follows:

[0048] (2.1) In this embodiment, the acceleration time history of the Mammoth Lake earthquake recorded by the Long Valley station is selected as the original natural ground motion time history. The duration of the time history is T = 30s, and the time interval is dt = 0.005s.

[0049] (2.2) Using the influence matrix method, the selected natural earthquake records are adjusted to earthquake time histories that fit the target response spectrum with high precision. The specific steps of the influence matrix method can be referred to invention patents ZL201910011113.4 "An influence matrix method for adjusting earthquake waves to accurately match target response spectra" or ZL201910268756.7 "An improved influence matrix method for alternating high and low frequency bands with target spectra", which can obtain natural earthquake time histories that fit the target response spectrum with high precision; Figure 2 Shown are examples of natural ground motion time history response spectra and target response spectra;

[0050] (2.3) Based on the high-precision fitting of the seismic acceleration time history of the target response spectrum, the Fourier transform is used to calculate the corresponding Fourier amplitude spectrum and phase spectrum of the time history.

[0051] Step (3): Calculate the energy spectrum density function P(ω) of the time course using the following formula:

[0052]

[0053] Among them, |F(ω)| calculates the one-sided Fourier amplitude spectrum, t m =t 5-75 It is the duration of a strong earthquake required to increase from 5% to 75% of the Arias intensity.

[0054] The obtained P(ω) is used as the initial power spectral density function S(ω).

[0055] Step (4): Based on the coordinates of each seismic wave input point in the site and the selected coherence function model, the autopower spectrum S of each point is calculated. jj (ω) and the cross power spectrum S between each point jk (iω), thus forming a power spectrum matrix S(iω), where i is an imaginary unit, and j and k are the serial numbers of the seismic wave input points.

[0056] The specific implementation steps are as follows:

[0057] (4.1) Four points evenly distributed on the horizontal surface of the site are selected, namely P1, P2, P3 and P4, and the x-direction coordinates of the seismic wave input points are 0m, 80m, 160m and 180m respectively. Only horizontal seismic motion is considered at each point.

[0058] (4.2) Select the Feng&Hu coherence function model as follows:

[0059]

[0060] Among them: ρ1, ρ2 are regression parameters, take ρ1=1.5*10 -5 s / m,ρ2=4*10 -3 l / m,d jk is the distance between the jth point and the kth point;

[0061] (4.3) Use the following formula to calculate the autopower spectrum S of the four points respectively: jj (ω) and the cross power spectrum S between the four points jk (iω), thus forming a power spectrum matrix S(iω), where j = 1…4, k = 1…4;

[0062] For the convenience of description, the subscript mn represents jj or jk, and the power spectrum calculation formula is as follows:

[0063]

[0064] Where: γ nm (iω k ) is the coherence function, |γ nm (iω k)| is the hysteresis coherence function, which is used to describe the coherence effect of ground motion between two points; Represents the phase angle between the ground motions at two points, used to describe the traveling wave effect; d nm Represents the distance between two points along the propagation direction, V app is the apparent wave velocity.

[0065] Step (5), based on the power spectrum matrix S(iω), using Cholesky decomposition, solve the cross-correlation Fourier amplitude and cross-correlation phase angle of different frequency components of different seismic wave input points, and use uniformly distributed random phases to synthesize the stable multi-point earthquake motion time history. Taking into account the acceleration time history phase spectrum of the high-precision fitting target response spectrum obtained in step (2), a non-stationary multi-point earthquake motion time history is obtained. Figure 3 The response spectrum of the spatially cross-correlated multi-point earthquake acceleration time history calculated by the embodiment of the present invention, with a total of four points; Figure 4 It is the spatially cross-correlated multi-point earthquake acceleration time history calculated by the embodiment of the present invention.

[0066] Step (6), calculate the relative error between the response spectrum ARS of the ground motion acceleration of each input point obtained in step (5) and the target response spectrum TRS. If the fitting accuracy does not meet the requirements, the input power spectrum density function S(ω) is corrected using the following formula:

[0067]

[0068] In the embodiment of the present invention, ARS takes the average value of four horizontal earthquake response spectra; and repeats steps (4) to (6) until the fitting accuracy meets the requirements.

[0069] Based on the same technical concept as the above method embodiment, in another embodiment, a spatial cross-correlation multi-point ground motion synthesis device for fitting response spectrum is provided, comprising:

[0070] The target response spectrum fitting module is used to select the natural earthquake time history A(t) based on the properties of the target response spectrum, and adjust the selected natural earthquake response spectrum to the earthquake time history A(t) that fits the target response spectrum with high precision using the influence matrix method. C (t), and use Fourier transform to calculate the single-sided Fourier amplitude spectrum F(ω) and phase spectrum of the time course

[0071] The power spectrum density function calculation module is used to calculate the earthquake time history A of the target response spectrum with high precision based on the obtained single-sided Fourier amplitude spectrum F(ω). C (t) energy spectral density function P(ω), and use P(ω) as the initial power spectral density function S(ω);

[0072] The power spectrum matrix calculation module is used to calculate the auto-power spectrum S of each point based on the power spectrum density function S(ω), the coordinates of each seismic wave input point in the site and the selected coherence function model. jj (ω) and the cross power spectrum S between each point jk (iω), thus forming a power spectrum matrix S(iω), where i is an imaginary unit, j and k are the serial numbers of the seismic wave input points;

[0073] The multi-point seismic motion synthesis module is used to obtain the cross-correlation Fourier amplitude and cross-correlation phase angle of different frequency components of different seismic wave input points based on the power spectrum matrix S(iω) through Cholesky decomposition, and synthesize the stable multi-point seismic motion time history using uniformly distributed random phases, and take into account the phase spectrum of the seismic motion time history that fits the target response spectrum with high precision obtained by the target response spectrum fitting module Synthesize non-stationary multi-point ground motion time history;

[0074] The iterative control module is used to calculate the relative error between the acceleration response spectrum of the earthquake time history of each input point and the target response spectrum. If the fitting accuracy does not meet the requirements, the input power spectrum density function is corrected, and the operations of the power spectrum matrix calculation module and the multi-point earthquake synthesis module are repeated until the fitting accuracy meets the requirements.

[0075] It should be understood that the spatial cross-correlation multi-point seismic synthesis device for fitting response spectra in the embodiments of the present invention can implement all the technical solutions in the above-mentioned method embodiments, and the functions of its various functional modules can be specifically implemented according to the methods in the above-mentioned method embodiments. The specific implementation process can refer to the relevant description in the above-mentioned embodiments, which will not be repeated here.

[0076] The present invention also provides a computer device, comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and when the programs are executed by the processors, the steps of the spatial cross-correlation multi-point seismic synthesis method of fitting the response spectrum as described above are implemented.

[0077] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the spatial cross-correlation multi-point seismic synthesis method of fitting response spectra as described above.

[0078] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, devices (systems), computer equipment or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0079] The present invention is described with reference to a flowchart of a method according to an embodiment of the present invention. It should be understood that each process in the flowchart and a combination of processes in the flowchart can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the process in the flowchart. Figure 1 A device that specifies functions in a process or multiple processes.

[0080] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A function specified in a process or multiple processes.

[0081] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 The steps of a specified function in a process or multiple processes.

Claims

1. A spatial cross-correlation multi-point ground motion synthesis method for fitting response spectra, characterized in that: The steps include: (1) Based on the properties of the target response spectrum, the natural earthquake time history A(t) is selected, and the selected natural earthquake response spectrum is adjusted to a earthquake time history A(t) that fits the target response spectrum with high accuracy using the influence matrix method. C (t), and use Fourier transform to calculate the single-sided Fourier amplitude spectrum F(ω) and phase spectrum of the time course (2) Based on the obtained one-sided Fourier amplitude spectrum F(ω), the earthquake time history A that fits the target response spectrum with high precision is calculated. C (t) energy spectral density function P(ω), and use P(ω) as the initial power spectral density function S(ω); (3) Based on the power spectrum density function S(ω), the coordinates of each seismic wave input point on the site and the selected coherence function model, the auto-power spectrum S of each point is calculated respectively. jj (ω) and the cross power spectrum S between each point jk (iω), thus forming a power spectrum matrix S(iω), where i is an imaginary unit, j and k are the serial numbers of the seismic wave input points; (4) Based on the power spectrum matrix S(iω), the cross-correlation Fourier amplitude and cross-correlation phase angle of different frequency components of different seismic wave input points are obtained by Cholesky decomposition. The uniformly distributed random phase is used to synthesize a stable multi-point ground motion time history, which is taken into account in the phase spectrum of the ground motion time history of the high-precision fitting target response spectrum obtained in step (1). Synthesize non-stationary multi-point ground motion time history; (5) Calculate the relative error between the acceleration response spectrum of the earthquake time history at each input point and the target response spectrum. If the fitting accuracy does not meet the requirements, correct the input power spectrum density function and repeat steps (3) to (5) until the fitting accuracy meets the requirements.

2. The spatial cross-correlation multi-point earthquake motion synthesis method of the fitting response spectrum according to claim 1 is characterized in that: The natural ground motion time history is selected based on the properties of the target response spectrum, including: Select natural ground motion time histories whose site type, source characteristics, and response spectrum shapes are similar to the target response spectrum.

3. The spatial cross-correlation multi-point earthquake motion synthesis method of fitting response spectrum according to claim 1 is characterized in that: Based on the obtained one-sided Fourier amplitude spectrum F(ω), the earthquake time history A that fits the target response spectrum with high precision is calculated. C The energy spectral density function P(ω) of (t) is calculated as follows: Among them, t m =t 5-75 It is the duration of a strong earthquake required to increase from 5% to 75% of the Arias intensity.

4. The spatial cross-correlation multi-point earthquake motion synthesis method of fitting response spectrum according to claim 1 is characterized in that: The power spectrum S of each point jj (ω) and the cross power spectrum S between each point jk (iω) is calculated as follows: In the formula, γ nm (iω k ) is the coherence function, |γ nm (iω k )| is the hysteresis coherence function, which is used to describe the coherence effect of ground motion between two points; Represents the phase angle between the ground motions at two points, used to describe the traveling wave effect; d nm Represents the distance between two points along the propagation direction, V app is the apparent wave velocity.

5. The spatial cross-correlation multi-point earthquake motion synthesis method of fitting response spectrum according to claim 1 is characterized in that: The modified input power spectral density function uses the following formula: Among them, TRS is the target response spectrum, and ARS is the earthquake acceleration response spectrum in the iterative calculation process.

6. A spatial cross-correlation multi-point earthquake motion synthesis device for fitting response spectrum, characterized in that: include: The target response spectrum fitting module is used to select the natural earthquake time history A(t) based on the properties of the target response spectrum, and adjust the selected natural earthquake response spectrum to the earthquake time history A(t) that fits the target response spectrum with high precision using the influence matrix method. C (t), and use Fourier transform to calculate the single-sided Fourier amplitude spectrum F(ω) and phase spectrum of the time course The power spectrum density function calculation module is used to calculate the earthquake time history A of the target response spectrum with high precision based on the obtained single-sided Fourier amplitude spectrum F(ω). C (t) energy spectral density function P(ω), and use P(ω) as the initial power spectral density function S(ω); The power spectrum matrix calculation module is used to calculate the auto-power spectrum S of each point based on the power spectrum density function S(ω), the coordinates of each seismic wave input point in the site and the selected coherence function model. jj (ω) and the cross power spectrum S between each point jk (iω), thus forming a power spectrum matrix S(iω), where i is an imaginary unit, j and k are the serial numbers of the seismic wave input points; The multi-point seismic motion synthesis module is used to obtain the cross-correlation Fourier amplitude and cross-correlation phase angle of different frequency components of different seismic wave input points based on the power spectrum matrix S(iω) through Cholesky decomposition, and synthesize the stable multi-point seismic motion time history using uniformly distributed random phases, and take into account the phase spectrum of the seismic motion time history that fits the target response spectrum with high precision obtained by the target response spectrum fitting module Synthesize non-stationary multi-point ground motion time history; The iterative control module is used to calculate the relative error between the acceleration response spectrum of the earthquake time history of each input point and the target response spectrum. If the fitting accuracy does not meet the requirements, the input power spectrum density function is corrected, and the operations of the power spectrum matrix calculation module and the multi-point earthquake synthesis module are repeated until the fitting accuracy meets the requirements.

7. The spatial cross-correlation multi-point earthquake motion synthesis device for fitting response spectrum according to claim 6 is characterized in that: In the power spectrum density function calculation module, based on the obtained single-sided Fourier amplitude spectrum F(ω), the earthquake time history A of the target response spectrum with high precision is calculated. C The energy spectral density function P(ω) of (t) is calculated as follows: Among them, t m =t 5-75 It is the duration of a strong earthquake required to increase from 5% to 75% of the Arias intensity.

8. The spatial cross-correlation multi-point earthquake motion synthesis device for fitting response spectrum according to claim 6 is characterized in that: In the power spectrum matrix calculation module, the power spectrum S of each point jj (ω) and the cross power spectrum S between each point jk (iω) is calculated as follows: In the formula, γ nm (iω k ) is the coherence function, |γ nm (iω k )| is the hysteresis coherence function, which is used to describe the coherence effect of ground motion between two points; Represents the phase angle between two points of ground motion, used to describe the traveling wave effect; d nm Represents the distance between two points along the propagation direction, V app is the apparent wave velocity.

9. A computer device, characterized in that: include: one or more processors; Memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and when the programs are executed by the processors, the steps of the spatial cross-correlation multi-point seismic synthesis method for fitting response spectra as described in any one of claims 1 to 5 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the spatial cross-correlation multi-point ground motion synthesis method for fitting response spectra according to any one of claims 1 to 5 are implemented.

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