A seabed ground motion inversion method, device, storage medium and program product

Abstract

The present application relates to the technical field of geotechnical engineering, and discloses a seabed ground motion inversion method, device, storage medium and program product, comprising: obtaining detailed geological exploration data of a target offshore wind farm, a wind turbine structure characteristic set and a measured seismic acceleration time history response data set corresponding to the position of the top of the foundation of the offshore wind turbine at the time of earthquake occurrence, and combining pile-soil interaction, offshore wind turbine dynamic water effect and similarity principle to construct a target centrifugal shaking table test scale model; simulating the actual gravity environment of the target offshore wind farm based on a preset centrifugal acceleration, and using the target centrifugal shaking table test scale model to perform simulation test, and constructing an amplitude-related transfer function library based on the nonlinear effect of soil; based on the measured seismic acceleration time history response data set, using the amplitude-related transfer function library based on the nonlinear effect of soil, the actual ground motion state of the seabed of the target offshore wind farm is inverted, and accurate inversion from field data to seabed ground motion is realized.

Description

Technical Field

[0001] This invention relates to the field of geotechnical engineering technology, specifically to a method, apparatus, storage medium, and program product for seabed seismic inversion. Background Technology

[0002] Offshore wind power, as an important development direction of the wind power industry, has significant advantages such as abundant resources, high power generation efficiency, and no occupation of land space. In recent years, the offshore wind power industry has achieved rapid and large-scale development, with completed and under-construction offshore wind farms mainly concentrated in coastal areas, where wind resources are abundant and favorable conditions for offshore wind power development are available.

[0003] However, the coastal region experiences frequent and intense seismic activity, and the potential seismic forces have become one of the core risk factors threatening the safe and stable operation of offshore wind turbines. Offshore wind turbines are highly flexible structures and are sensitive to seismic activity. Once they are damaged by an earthquake, it will not only cause huge economic losses, but may also lead to secondary disasters such as power outages. Therefore, the seismic design and safety assurance of offshore wind power are of paramount importance.

[0004] Current seismic design codes for offshore wind power, such as the "Code for Seismic Design of Wind Farm Engineering" (NB / T 11600-2024), are mainly based on the response spectrum method recommended by the "Code for Seismic Design of Buildings" (GB 50011) (hereinafter referred to as the "Code"). However, it should be clarified that the "Code" is mainly aimed at traditional onshore buildings, and its design concepts and applicable scenarios are fundamentally different from those of offshore wind power support structures. The two differ significantly in terms of building function, structural form, stress characteristics, and service environment. Directly applying the seismic response spectrum from the "Code" to the seismic design of offshore wind power inevitably leads to many unreasonable aspects, the most prominent of which is the mismatch of design ground motion input parameters.

[0005] In the absence of specific seismic safety assessments for particular offshore wind power project sites, the design ground motion input parameters used to determine the seismic response spectrum, as required by the Building Code, are directly taken from the "China Seismic Ground Motion Parameter Zoning Map" (GB18306). However, this zoning map is based on onshore geological conditions and only covers land areas. Its ground motion parameters differ significantly from the geological conditions, hydrological environment, and dynamic response characteristics of nearshore seabed sites, making it unsuitable for offshore wind power sites. Directly applying onshore ground motion zoning parameters to the seismic design of offshore wind power lacks specific on-site measurement data, resulting in insufficient evidence, low accuracy, and an inability to accurately reflect the actual ground motion characteristics of the seabed site. This leads to conservative or even dangerous seismic designs, failing to adequately guarantee the safe and reliable operation of offshore wind turbines under seismic loads. Therefore, it is urgent to obtain actual measured seabed ground motion data for offshore sites to revise current seismic design codes and establish seismic design methods suitable for offshore wind power, bridging the gap between offshore wind power seismic design and onshore building seismic design.

[0006] However, due to the complexity of the nearshore environment, seismic monitoring in the seabed area is extremely difficult. Nearshore waters have large variations in water depth, strong wave action, and complex geological conditions. Directly deploying seismic monitoring equipment on the seabed is not only costly but also susceptible to damage from marine erosion, wind and wave impacts, etc., leading to equipment damage, data distortion, and difficulty in obtaining reliable measured seabed seismic data. This problem has become a core bottleneck restricting the optimization of seismic-resistant design for offshore wind power.

[0007] In recent years, with the continuous development of offshore wind power operation and maintenance technology, structural health monitoring of offshore wind power has gradually gained industry attention. Currently, most existing offshore wind turbines have multiple accelerometers installed on their above-sea structural components (such as the nacelle and towers at different heights) to monitor the vibration response of the turbine structure in real time, conduct real-time health checks on the turbine system, and ensure the normal operation and maintenance of the turbines. In recent near-shore earthquakes, these accelerometers deployed on the turbine structure have successfully recorded relatively complete and reliable measured data on the seismic response of the turbine structure, providing valuable data support for research on offshore seismic motion.

[0008] However, these measured data can only reflect the seismic response characteristics of the wind turbine structure itself, and cannot directly characterize the actual state of seabed ground motion. They cannot be directly used to correct the standard design response spectrum or optimize the seismic design parameters of offshore wind power.

[0009] Therefore, in order to overcome the bottleneck of the difficulty in measuring seabed ground motion and make full use of the existing monitoring resources of offshore wind power foundations, it is urgent to develop a seabed ground motion inversion method based on offshore wind power foundation monitoring data. Summary of the Invention

[0010] This invention provides a method, apparatus, storage medium, and program product for seabed ground motion inversion, in order to solve the problems of high difficulty in actual measurement of seabed ground motion, inability of existing monitoring data to be directly applied to seismic design, insufficient inversion accuracy due to the transfer function not considering soil nonlinearity, and failure to consider wind and water kinetic effects at sea.

[0011] In a first aspect, the present invention provides a method for inverting seabed ground motion, the method comprising: Detailed geological survey data, wind turbine structural characteristic set, and measured seismic acceleration time history response dataset corresponding to the top position of the foundation of the offshore wind turbine at the time of the earthquake were obtained for the target offshore wind field. Based on pile-soil interaction, kinetic-hydrodynamic effects of offshore wind turbines, and similarity principles, a scaled-down model of the target centrifugal shaking table test was constructed using the detailed geological survey data and wind turbine structural characteristic set. The actual gravity environment of the target offshore wind field was simulated based on preset centrifugal acceleration, and simulation tests were conducted using the scaled-down model of the target centrifugal shaking table test, constructing an amplitude correlation transfer function library based on soil nonlinear effects. Based on the measured seismic acceleration time history response dataset, the actual seismic motion state of the seabed of the target offshore wind field was inverted using the amplitude correlation transfer function library based on soil nonlinear effects, resulting in the inverted seabed seismic motion dataset.

[0012] The seabed seismic inversion method provided by this invention ensures the completeness, accuracy, and consistency of the inversion input information with the actual working conditions of the target wind field by acquiring relevant data of the target offshore wind field and measured data corresponding to the top position of the offshore wind turbine foundation at the time of the earthquake. Furthermore, by combining pile-soil interaction, kinetic-hydrodynamic effects of offshore wind turbines, and similarity principles, a scaled-down model of the target centrifugal shaking table test is constructed, accurately reproducing the seabed site, wind turbine structure, and marine dynamic environment. This achieves a realistic simulation of pile-soil interaction and kinetic-hydrodynamic effects, improving the matching degree between the model and the prototype. Further, by simulating the actual gravity environment of the target offshore wind field and conducting simulation experiments using the scaled-down model of the target centrifugal shaking table test, an amplitude-related transfer function library based on soil nonlinear effects is constructed. This accurately reflects the nonlinear dynamic characteristics of soil under different earthquake intensities, eliminating the accuracy defects of traditional single transfer functions and establishing a stable and reliable dynamic transmission relationship. Furthermore, by utilizing an amplitude correlation transfer function library, the actual seismic state of the seabed in the target offshore wind field is inverted, efficiently reconstructing the true seismic state of the seabed without the need for additional seabed monitoring equipment. This provides accurate measured data support for the seismic design of offshore wind power. Therefore, by implementing this invention, accurate inversion from field data to seabed seismic motion is achieved, overcoming the challenge of direct monitoring of seabed seismic motion, making full use of existing wind turbine monitoring resources, and balancing inversion accuracy, economy, and engineering applicability.

[0013] In one alternative implementation, based on pile-soil interaction, offshore wind turbine kinetic-hydrodynamic effects, and similarity principles, a scaled-down model of the target centrifugal shaking table test is constructed using detailed geological survey data and a wind turbine structural characteristic set, including: Based on the principle of similarity, the similarity ratio parameters of the model are determined using the wind turbine structural characteristic set and the preset test equipment dimensions. Based on the principle of similarity and pile-soil interaction, the seabed site is modeled using detailed geological survey data to obtain the target site model, which matches the prototype seabed and reflects the pile-soil interaction. Based on the principle of similarity and the dynamic water effect of offshore wind turbines, a target wind turbine foundation model simulating the dynamic water effect is constructed using the wind turbine structural characteristic set. Based on the principle of similarity, the wind turbine superstructure is simulated using the wind turbine structural characteristic set, and a superstructure model with dynamic characteristics equivalent to the offshore wind turbine prototype is constructed, with the first-order natural frequency of the superstructure model being consistent with that of the offshore wind turbine prototype. The target site model, the target wind turbine foundation model, and the superstructure model are assembled to obtain the initial centrifugal shaking table test scale model. Accelerometers are added to the mud surface position and the top position of the foundation of the initial centrifugal shaking table test scale model to construct the target centrifugal shaking table test scale model.

[0014] The seabed seismic inversion method provided by this invention, through the principle of similarity, uses the structural characteristic set of the wind turbine and the preset dimensions of the test equipment to determine the model similarity ratio parameters, ensuring that the scaled model and the prototype wind turbine and seabed site satisfy geometric and dynamic similarity, which helps to ensure that the test results can be equivalently mapped to actual engineering. Furthermore, by modeling the seabed site, the distribution and mechanical properties of the seabed soil layers can be realistically reproduced, accurately reflecting the pile-soil interaction mechanism and ensuring the engineering authenticity of the site model. Furthermore, by constructing a target wind turbine foundation model simulating the dynamic water effect, the dynamic coupling effect between the offshore wind turbine foundation and the seawater can be accurately reproduced, compensating for the deficiency of the onshore model in not considering the dynamic water effect. Furthermore, by constructing a superstructure model with dynamic characteristics equivalent to the prototype offshore wind turbine, the dynamic characteristics of the model and the prototype wind turbine can be ensured to be consistent, ensuring that the structural seismic response transmission law is consistent with the actual engineering. Furthermore, by assembling the target site model, the target wind turbine foundation model, and the superstructure model, and adding accelerometers at the mud surface and the top of the foundation, a scaled-down model of the target centrifugal shaking table test is obtained, forming an integrated, high-fidelity test platform. This provides a stable and reliable test object for subsequent centrifugal shaking table tests. Therefore, by implementing this invention, and constructing a scaled-down test model that closely matches actual offshore wind power projects, the pile-soil interaction and hydrodynamic effects are fully considered, laying a precise model foundation for transfer function acquisition and seismic inversion.

[0015] In one alternative implementation, based on the principle of similarity and the dynamic-hydrodynamic effect of offshore wind turbines, a target wind turbine foundation model simulating the dynamic-hydrodynamic effect is constructed using a set of wind turbine structural characteristics, including: Based on the principle of similarity, an initial wind turbine foundation model equivalent to the offshore wind turbine prototype is constructed using the wind turbine structural characteristic set and model similarity ratio parameters. Based on the principle of similarity and the dynamic water effect of offshore wind turbines, the dynamic water added mass is calculated using the wind turbine structural characteristic set. Based on the model similarity ratio parameters and the dynamic water added mass, the initial wind turbine foundation model is optimized to obtain the target wind turbine foundation model simulating the dynamic water effect.

[0016] The seabed seismic inversion method provided by this invention achieves equivalence between the foundation geometry, stiffness, and mass and the prototype by constructing an initial wind turbine foundation model, thus meeting the foundation similarity requirements of the foundation model. Furthermore, by calculating the added mass of the moving water, the dynamic additional effect between seawater and the foundation is quantified, providing accurate numerical basis for simulating the moving water effect. Moreover, by optimizing the initial wind turbine foundation model using the added water mass, the moving water effect can be accurately integrated into the foundation model, thereby making the foundation dynamic response completely consistent with the actual engineering. Therefore, by implementing this invention, the accuracy of foundation dynamic characteristic simulation is significantly improved, making the model more closely resemble actual offshore working conditions.

[0017] In one optional implementation, the actual gravity environment of the target offshore wind field is simulated based on a preset centrifugal acceleration, and a simulation test is conducted using a scaled model of the target centrifugal shaking table test. An amplitude-related transfer function library based on soil nonlinear effects is constructed, including: The actual gravity environment of the target marine wind field is simulated based on the preset centrifugal acceleration. Under the actual gravity environment, multiple seismic waves are used to excite the scaled model of the target centrifugal shaking table test, and the seismic acceleration time history response datasets at the first mud surface position and the first foundation top position are obtained. The multiple seismic waves adopt different frequency ranges and different peak accelerations. The seismic acceleration time history response datasets at the first mud surface position and the first foundation top position are processed respectively, and an amplitude correlation transfer function library based on the nonlinear effect of soil is established.

[0018] The seabed seismic motion inversion method provided by this invention simulates the actual gravity environment of the target offshore wind field by pre-setting centrifugal acceleration, thus restoring the in-situ stress state of the offshore wind field, ensuring consistency between the soil mechanical properties and reality, and improving the reliability of the experiment. Furthermore, by exciting a scaled-down model of the target centrifugal shaking table test with multiple seismic waves of different frequency ranges and peak accelerations, the system response under earthquakes of different intensities and frequencies can be obtained, covering common engineering earthquake conditions, making the collected data comprehensive and representative. Furthermore, by processing the collected data separately and constructing an amplitude-related transfer function library based on soil nonlinear effects, a stable dynamic mapping relationship between input and output is established, fully reflecting soil nonlinearity and improving the applicability and accuracy of the transfer function. Therefore, by implementing this invention, standardized and comprehensive dynamic transmission laws can be obtained through controlled experiments, providing core calculation basis for seabed seismic motion inversion under actual earthquakes.

[0019] In one optional implementation, the seismic acceleration time history response datasets at the first mud surface location and the first foundation top location are processed respectively, and an amplitude correlation transfer function library based on soil nonlinear effects is established, including: By utilizing the different peak ground acceleration (PGA) magnitudes corresponding to multiple seismic waves, the time-history response datasets of seismic acceleration at the first mud surface location and the top of the first foundation location are grouped by amplitude, resulting in multiple sets of time-history response datasets of seismic acceleration at the second mud surface location and the top of the second foundation location corresponding to different amplitudes. The time-domain acceleration signals in each set of the second mud surface location time-history response datasets are processed to obtain multiple time-domain acceleration signals at the mud surface location. Similarly, the time-domain acceleration signals in each set of the second foundation top location time-history response datasets are processed to obtain multiple time-domain acceleration signals at the foundation top location. Using the Fourier transform method, the multiple time-domain acceleration signals at the mud surface location and the multiple time-domain acceleration signals at the foundation top location are transformed into frequency domain information, resulting in multiple sets of frequency domain information at the mud surface location and the foundation top location. Based on the multiple sets of frequency domain information at the mud surface location and the foundation top location, multiple representative transfer functions are calculated for multiple amplitudes. Based on these multiple representative transfer functions, an amplitude correlation transfer function library based on soil nonlinear effects is constructed.

[0020] The seabed ground motion inversion method provided by this invention groups the amplitudes of multiple seismic waves according to their different peak ground accelerations (PGA) values, enabling the differentiation of soil nonlinearity differences under different earthquake intensities and achieving refined classification of transfer functions. Furthermore, time-domain acceleration signal processing eliminates noise and interference, improving signal purity and data reliability. Further, frequency domain transformation converts the time-domain response into frequency-domain characteristics, facilitating transfer function calculation and dynamic characteristic analysis. Moreover, calculating representative transfer functions smooths out the discretization errors of different seismic waves, yielding stable and universal transfer functions for various amplitudes. Finally, combining multiple representative transfer functions, an amplitude-correlated transfer function library based on soil nonlinearity effects is constructed, forming a complete amplitude-transfer function correspondence system adaptable to the inversion needs of earthquakes of different intensities. Therefore, by implementing this invention and establishing a high-precision, robust amplitude-correlated transfer function library, the inversion error problem caused by soil nonlinearity is effectively solved, significantly improving inversion stability and universality.

[0021] In one optional implementation, based on the measured seismic acceleration time history response dataset, the actual seismic motion state of the seabed in the target offshore wind field is inverted using an amplitude correlation transfer function library based on soil nonlinear effects, resulting in an inverted seabed seismic motion dataset, including: The measured seismic acceleration time history response dataset is preprocessed to obtain the target seismic acceleration time history response dataset. Based on the target seismic acceleration time history response dataset, the measured peak ground acceleration value of the seismic response is determined. Based on the measured peak ground acceleration value of the seismic response, the target transfer function is determined from the amplitude correlation transfer function library based on soil nonlinear effects. Based on the measured seismic acceleration time history response dataset, the actual seismic motion state of the seabed in the target marine wind field is inverted using the target transfer function to obtain the inverted seabed seismic motion dataset.

[0022] The seabed ground motion inversion method provided by this invention, through preprocessing of the measured seismic acceleration time history response dataset, can remove noise and calibrate the baseline, ensuring the purity and reliability of the measured data and improving the quality of the inversion input. Furthermore, by determining the peak ground acceleration (PGA) value of the measured seismic response, the intensity level of the earthquake can be quickly located, providing a crucial basis for matching the target transfer function. Further, by using the PGA value of the measured seismic response, the target transfer function is determined from the amplitude correlation transfer function library based on soil nonlinear effects, achieving precise selection and adaptation of the transfer relationship of the earthquake intensity, ensuring the relevance and accuracy of the inversion calculation. Furthermore, by inverting the actual ground motion state of the seabed in the target offshore wind field using the target transfer function, the true seabed ground motion can be efficiently reconstructed and reliable data that can be directly used for seismic design can be output. Therefore, by implementing this invention, a rapid and accurate inversion from wind turbine structural response to seabed ground motion is achieved, with a simple process and reliable results, directly serving engineering applications.

[0023] In one optional implementation, based on the measured seismic acceleration time history response dataset, the actual seismic motion state of the seabed in the target marine wind field is inverted using the target transfer function to obtain the inverted seabed seismic motion dataset, including: Input the target seismic acceleration time history response dataset into the target transfer function to obtain the frequency domain ground motion dataset corresponding to the mud surface position of the offshore wind turbine at the time of the earthquake; perform a time domain inverse transformation on the frequency domain ground motion dataset to obtain the inverted seabed ground motion dataset.

[0024] The seabed ground motion inversion method provided by this invention, by inputting the target seismic acceleration time history response dataset into the target transfer function, can accurately separate the seabed ground motion input components through frequency domain conversion, eliminating interference from the structure's own response. Furthermore, through inverse time domain transformation, the frequency domain results can be restored to the time domain ground motion time history, yielding ground motion parameters that can be directly used in engineering. Therefore, by implementing this invention, accurate reconstruction of the final ground motion is achieved, and the output standardized time domain data can be directly used for code correction and seismic design parameter optimization.

[0025] In a second aspect, the present invention provides a seabed seismic inversion device, the device comprising: The system comprises four modules: an acquisition module for acquiring detailed geological survey data of the target offshore wind field, a set of wind turbine structural characteristics, and a dataset of measured seismic acceleration time history responses corresponding to the top of the foundation of the offshore wind turbine during an earthquake; a first construction module for constructing a scaled-down model of the target centrifugal shaking table test based on pile-soil interaction, the kinetic-hydrodynamic effect of offshore wind turbines, and similarity principles, using detailed geological survey data and the wind turbine structural characteristics; a second construction module for simulating the actual gravity environment of the target offshore wind field based on preset centrifugal acceleration, conducting simulation tests using the scaled-down model of the target centrifugal shaking table test, and constructing a library of amplitude correlation transfer functions based on soil nonlinear effects; and an inversion module for inverting the actual seismic motion state of the seabed of the target offshore wind field based on the measured seismic acceleration time history response dataset and using the library of amplitude correlation transfer functions based on soil nonlinear effects, to obtain the inverted seabed seismic motion dataset.

[0026] Thirdly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the seabed seismic inversion method of the first aspect or any corresponding embodiment described above.

[0027] Fourthly, the present invention provides a computer program product, including computer instructions for causing a computer to execute the seabed seismic inversion method of the first aspect or any corresponding embodiment described above. Attached Figure Description

[0028] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0029] Figure 1 This is a schematic diagram of an application scenario according to an embodiment of the present invention; Figure 2 This is a schematic flowchart of the seabed seismic inversion method according to an embodiment of the present invention; Figure 3 This is a flowchart illustrating the seabed seismic inversion method based on on-site monitoring data of offshore wind power foundations according to an embodiment of the present invention. Figure 4 This is a schematic diagram of the transfer function curve under the condition of 0.15g base excitation according to an embodiment of the present invention; Figure 5 This is a structural block diagram of a seabed seismic inversion device according to an embodiment of the present invention; Figure 6This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0032] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0033] As an optional application scenario of this invention, the specific application environment architecture or specific hardware architecture on which the seabed seismic inversion method depends is described here. For example... Figure 1 As shown, the architecture system may include at least one terminal device and at least one server. Figure 1 The system is illustrated in the example, which includes a computer 101, a mobile terminal 102, and a server 103, and the terminal devices such as the computer 101 and the mobile terminal 102 are connected to the server 103 through a network 110.

[0034] Specifically, the terminal device can be a smartphone, tablet, laptop, PDA, desktop computer, game console, smart TV, smart wearable device, in-vehicle terminal, VR (Virtual Reality) device, AR (Augmented Reality) device, etc. Server 103 can be a standalone physical server, a server cluster, a distributed system, or a cloud server providing cloud services. Network 110 can be a wired or wireless network, examples of which include, but are not limited to, the Internet, corporate intranet, local area network, wide area network, mobile communication network, and combinations thereof.

[0035] This invention provides a method for inverting seabed ground motion. By combining pile-soil interaction, wind-driven hydrodynamic effects, and similarity principles, a scaled-down model of the target centrifugal shaking table test is constructed and simulated under a simulated actual gravity environment. Then, an amplitude correlation transfer function library based on the nonlinear effect of soil is constructed to invert the actual ground motion state of the seabed in the target offshore wind field, thereby achieving accurate inversion from field data to seabed ground motion. This method overcomes the challenge of direct monitoring of seabed ground motion, makes full use of existing wind turbine monitoring resources, and balances the effects of inversion accuracy, economy, and engineering applicability.

[0036] According to an embodiment of the present invention, a method for inverting seabed ground motion is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0037] This embodiment provides a seabed seismic inversion method, which can be used on the aforementioned mobile terminals, such as mobile phones and tablets. Figure 2 This is a flowchart of the seabed seismic inversion method according to an embodiment of the present invention, as follows: Figure 2 As shown, the process includes the following steps: Step S201: Obtain detailed geological survey data of the target offshore wind field, a set of wind turbine structural characteristics, and a dataset of measured seismic acceleration time history response corresponding to the top position of the foundation of the offshore wind turbine at the time of the earthquake.

[0038] In one optional embodiment, the target offshore wind farm refers to a specific near-shore offshore wind farm for which seabed seismic inversion needs to be carried out for seismic design and safety assessment of offshore wind power. It can be an operational wind farm or a planned wind farm, and is the only engineering object of this inversion.

[0039] Furthermore, detailed geological survey data represents the basic geological data of the seabed site obtained through exploration within the site area of ​​the target offshore wind field. This data is used to accurately reconstruct the engineering characteristics of the seabed site and may include information such as the distribution of seabed soil layers, layer information, physical and mechanical parameters of each soil layer (unit weight, internal friction angle, density, saturation, etc.), geological structural features, thickness of overburden layer, and distribution of weak layers.

[0040] Furthermore, the wind turbine structural characteristic set represents all structural parameters of the support system of a single wind turbine in the target offshore wind farm. It is used to construct an experimental model that is equivalent to the prototype dynamics. It can include information such as wind turbine model, tower height, total weight of nacelle and impeller, foundation type (such as large-diameter monopile), pile diameter, pile length, top elevation, structural stiffness distribution, and the first-order natural frequency of the system.

[0041] In one alternative embodiment, the offshore wind turbine refers to a highly flexible wind power structure already installed and operating within the target offshore wind farm, which may include a tower, nacelle, rotor, and foundation (monopile / jacket, etc.). Furthermore, its foundation is submerged in seawater, is sensitive to ground vibration, and has its own structural health monitoring system.

[0042] Furthermore, the "top position of the foundation" refers to the position of the top section of the foundation above the seabed mud surface and below the bottom of the tower.

[0043] Furthermore, the measured seismic acceleration time history response dataset represents the complete acceleration time history data collected and recorded in real time by the acceleration sensor on top of the wind turbine foundation during an offshore earthquake, which can reflect the dynamic response of the structure under a real earthquake.

[0044] Step S202: Based on pile-soil interaction, offshore wind turbine hydrodynamic effect and similarity principle, a scaled-down model of the target centrifugal shaking table test is constructed using detailed geological survey data and wind turbine structural characteristic set.

[0045] In an optional embodiment, pile-soil interaction represents the mutual contact, stress, deformation and stiffness coupling effect between the offshore wind turbine foundation pile and the surrounding seabed soil under the action of seismic motion. It can reflect the load transfer between the pile and the soil, the soil constraint effect and the influence of soil stiffness degradation on the dynamic response of the structure.

[0046] Furthermore, the kinetic-hydrodynamic effect of offshore wind turbines refers to the additional inertial and hydrodynamic effects generated by the dynamic interaction between the submerged section above the mud surface of the wind turbine foundation and the surrounding seawater during seismic vibrations. This interaction can alter the overall mass, stiffness, and vibration characteristics of the structure. Moreover, this kinetic-hydrodynamic effect is a unique dynamic effect that is not present in onshore structures but must be considered for offshore wind turbines.

[0047] Furthermore, the similarity principle represents a theoretical guideline for reducing an actual engineering prototype to an experimental model according to strict proportional relationships in geometry, physics, dynamics, and boundary conditions. Moreover, this similarity principle ensures that the model and the prototype maintain consistency in their dynamic response patterns, stress mechanisms, and deformation characteristics under seismic loading, thereby enabling the experimental results to be equivalently mapped to actual engineering projects.

[0048] Furthermore, the scaled-down model of the target centrifugal shaking table test represents a reduced-scale integrated wind turbine-seabed model fabricated based on the principle of similarity and capable of being tested on a centrifugal shaking table. It can recreate the seabed site, wind turbine foundation, superstructure, and hydrodynamic effects. Moreover, this scaled-down model of the target centrifugal shaking table test can obtain the power transmission characteristics of the wind turbine system by simulating in-situ stress states in a centrifugal acceleration field.

[0049] In one alternative embodiment, offshore wind turbines are subjected to the combined effects of seabed soil constraint and seawater dynamic coupling during earthquakes, making direct in-situ testing difficult. In this embodiment, based on the actual geological and structural parameters of the target wind field, and by comprehensively considering pile-soil interaction, hydrodynamic effects, and similarity principles, the actual offshore wind turbine and seabed site can be scaled down proportionally into an integrated model suitable for centrifugal shaking table testing.

[0050] Step S203: Simulate the actual gravity environment of the target offshore wind field based on the preset centrifugal acceleration, and conduct simulation tests using a scaled model of the target centrifugal shaking table test to construct an amplitude-related transfer function library based on the nonlinear effect of soil.

[0051] In an optional embodiment, the preset centrifugal acceleration is expressed as the centrifugal loading acceleration pre-set to restore the in-situ effective stress state of the seabed soil in the centrifugal vibration table test, which is used to make the soil stress inside the scaled model consistent with the actual seabed stress of the offshore wind field.

[0052] Furthermore, the actual gravity environment represents the actual stress state and stress environment of the seabed soil in the target offshore wind field under the action of in-situ real self-weight stress and gravity field. It can truly reflect the density, stiffness, constraint conditions and mechanical properties of the seabed soil under the action of natural gravity and overlying load.

[0053] Furthermore, the amplitude-dependent transfer function library based on soil nonlinear effects represents a set of transfer functions that can reflect the nonlinear laws of soil stiffness degradation and dynamic characteristic changes as earthquake intensity increases. This library is used to establish a precise correspondence between the top response of the wind turbine foundation and the seabed seismic input.

[0054] Among them, the nonlinear effect of soil means that the dynamic characteristics of seabed soil, such as stiffness and damping, will change significantly with the increase of vibration amplitude under different intensity of seismic excitation (stiffness degradation, modulus reduction), which in turn leads to the mechanical behavior of the overall dynamic transmission characteristics of the wind turbine-seabed system changing significantly with different earthquake intensities.

[0055] In one optional embodiment, seabed soil exhibits significant nonlinear characteristics of stiffness degradation under earthquakes of varying intensities, making it impossible for a single transfer function to accurately describe the dynamic transmission law. This embodiment utilizes a preset centrifugal acceleration in a centrifugal field to recreate the actual gravity stress conditions of the offshore wind field. Then, multi-amplitude seismic excitation tests are conducted on a scaled-down model of the centrifugal shaking table test, thereby collecting input and output dynamic response data. Ultimately, this allows for the establishment of a transfer function library that considers soil nonlinearity and is related to earthquake amplitude.

[0056] Furthermore, the established amplitude correlation transfer function library based on soil nonlinearity can accurately reflect the influence of soil nonlinearity on structural dynamic transmission, which helps to ensure the reliability of the inversion results.

[0057] Step S204: Based on the measured earthquake acceleration time history response dataset, the actual seismic motion state of the seabed of the target offshore wind field is inverted using the amplitude correlation transfer function library based on soil nonlinear effects, and the inverted seabed seismic motion dataset is obtained.

[0058] In one optional embodiment, the seabed ground motion dataset represents the time history set of time-domain ground motion accelerations on the seabed surface under actual seismic action, which is obtained by inversion calculation and can truly reflect the target offshore wind field. It can be directly used for seismic design, code correction and parameter optimization of offshore wind power, and can include complete dynamic characteristics such as real ground motion amplitude, frequency and duration.

[0059] In one optional embodiment, the seismic response at the top of the wind turbine foundation is jointly determined by the seabed ground motion input and the dynamic transmission characteristics of the system. Soil nonlinearity under different earthquake intensities alters the system's transmission patterns. This embodiment uses measured seismic acceleration time-history response data at the top of the offshore wind turbine foundation as input, and employs an amplitude-correlation transfer function library that considers soil nonlinearity effects for dynamic conversion. This allows for the reverse derivation of the actual seabed ground motion input from the structural response, ultimately yielding a high-precision seabed ground motion dataset suitable for engineering applications.

[0060] The seabed ground motion inversion method provided in this embodiment achieves accurate inversion from field data to seabed ground motion, overcomes the problem of direct monitoring of seabed ground motion, makes full use of existing wind turbine monitoring resources, and takes into account inversion accuracy, economy and engineering applicability.

[0061] In some optional implementations, step S202 above includes: Step S2021: Based on the principle of similarity, the model similarity ratio parameters are determined using the wind turbine structural characteristic set and the preset test equipment dimensions.

[0062] In one optional embodiment, the preset test equipment size represents the hardware physical boundary parameters of the centrifugal vibration table test system, such as the pre-determined table size, model box volume, loading range, and installation space, and is a constraint condition for the model scaling design.

[0063] Furthermore, the model similarity ratio parameter represents the geometric, physical, and dynamic scaling ratio between the model and the prototype determined according to the similarity principle. It is generally taken as 1:50 to 1:100, with 1:50 being preferred, to ensure that the dynamic response laws of the model and the prototype are consistent.

[0064] In one optional embodiment, the experimental equipment has limited space and load-bearing capacity, making prototype testing impossible. Therefore, it is necessary to scale down the model to a uniform ratio to ensure that the stress, vibration, and deformation patterns of the model are consistent with the engineering prototype. In this embodiment, based on the principle of similarity and combined with the scale of the wind turbine prototype and the preset experimental equipment dimensions, the geometric, mass, stiffness, and dynamic scaling ratios of the model and prototype can be determined.

[0065] For example, based on the hardware conditions such as the effective platform size of the test equipment, the internal space of the model box, and the centrifugal loading capacity, and combined with the structural scale, foundation size, and seabed site range of the target offshore wind farm turbine prototype, a scaling ratio between 1:50 and 1:100 can be selected according to the unified requirements of geometric similarity, dynamic similarity, and mass similarity, with priority given to the 1:50 scaling ratio. This allows for the determination of a complete set of model similarity ratio parameters, including geometric similarity ratio, mass similarity ratio, stiffness similarity ratio, and frequency similarity ratio, between the model and the prototype.

[0066] Step S2022: Based on the principle of similarity and pile-soil interaction, the seabed site is modeled using detailed geological survey data to obtain the target site model.

[0067] In one alternative embodiment, the target site model is matched to the prototype seabed and reflects the pile-soil interaction.

[0068] In one alternative embodiment, the distribution, density, and saturation of the seabed soil layers directly determine the pile-soil interaction and soil nonlinearity. Only by restoring the real geological conditions can the accuracy of subsequent power transmission characteristics be guaranteed.

[0069] For example, the distribution of seabed soil layers, physical and mechanical parameters of each soil layer, soil layer thickness, density and saturation index can be scaled proportionally according to a determined model similarity ratio based on the detailed geological survey data of the target offshore wind field.

[0070] Furthermore, by using the sand rain method or compaction method to fill and prepare samples in layers on the model site, and controlling the soil density, moisture content and saturation layer by layer, the mechanical state of the model seabed soil can be kept consistent with that of the prototype seabed. This allows for the accurate reproduction of the seabed soil structure and pile-soil contact conditions, and ultimately, a target site model that can truly reflect the pile-soil interaction can be obtained.

[0071] Step S2023: Based on the principle of similarity and the dynamic water effect of offshore wind, construct a target wind turbine foundation model to simulate the dynamic water effect using the wind turbine structural characteristic set.

[0072] Specifically, step S2023 above includes: Step a1: Based on the principle of similarity, an initial wind turbine basic model equivalent to the offshore wind turbine prototype is constructed using the wind turbine structural characteristic set and model similarity ratio parameters.

[0073] Step a2: Based on the similarity principle and the dynamic water effect of offshore wind turbines, the added mass of dynamic water is calculated using the structural characteristic set of the wind turbine.

[0074] Step a3: Based on the model similarity ratio parameter and the added mass of the dynamic water, the initial wind turbine foundation model is optimized to obtain the target wind turbine foundation model that simulates the dynamic water effect.

[0075] In one optional embodiment, the dynamic water added mass represents the equivalent added inertial mass generated by the interaction between the submerged section of the wind turbine foundation and seawater under seismic action, and is used to simulate the dynamic water effect.

[0076] In one optional embodiment, firstly, the wind turbine foundation can be scaled up proportionally according to the foundation type, pile diameter, pile length, wall thickness, cross-sectional properties, stiffness and mass parameters included in the wind turbine structural characteristic set, and combined with the determined model similarity ratio parameters, so that the geometric dimensions, mass distribution, cross-sectional properties and overall stiffness of the initial wind turbine foundation model are equivalent to those of the offshore wind turbine prototype foundation, and finally an initial wind turbine foundation model without considering the dynamic water effect is obtained.

[0077] Secondly, the water depth, foundation immersion height, external and internal radii of the single pile, and the height of the calculation point from the mud surface can be considered based on the structural characteristics of the wind turbine. Furthermore, by incorporating seawater density, the additional mass of the external dynamic water around each single pile can be calculated. Additional mass of internal dynamic water in a single pile The following relationships (1) and (2) are shown: (1) (2) In the formula: Indicates the density of water; and These represent the outer radius and inner radius of a single pile, respectively. Indicates water depth; This represents a modified Bessel function of the second kind; ; This represents a modified Bessel function of the first kind; Indicates the order; This indicates the height of the calculation point from the mud surface.

[0078] Finally, the calculated additional mass of the dynamic water is converted into an equivalent mass usable in the model test according to the model similarity ratio parameters. Furthermore, by selecting iron material to make a circular weight of corresponding mass and fixing the iron ring at the corresponding height position of the submerged section of the initial wind turbine foundation model, the additional inertial effect brought about by the dynamic water effect can be accurately reflected in the foundation model during vibration, and finally a target wind turbine foundation model that can simulate the dynamic water effect is obtained.

[0079] Step S2024: Based on the principle of similarity, the superstructure of the wind turbine is simulated using the wind turbine structural characteristic set, and a superstructure model equivalent to the dynamic characteristics of the offshore wind turbine prototype is constructed.

[0080] In one optional embodiment, the upper structure of the wind turbine refers to the overall structure above the turbine's mud surface, including the tower, nacelle, and impeller, and is a highly flexible system. Furthermore, its dynamic characteristics are dominated by the first-order natural frequency.

[0081] Furthermore, the first-order natural frequency of the superstructure model is consistent with that of the offshore wind turbine prototype.

[0082] In one alternative embodiment, the wind turbine is a highly flexible structure, and its first-order natural frequency dominates the seismic response. Therefore, only with frequency equivalence can the dynamic characteristics of the model and the prototype be guaranteed to be consistent.

[0083] For example, the tower height, total weight of nacelle and impeller, structural stiffness distribution, and first-order natural frequency parameters of the system can be scaled proportionally according to the similarity ratio based on the wind turbine's structural characteristic set.

[0084] Then, the overall dynamic characteristics of the wind turbine nacelle, impeller and tower are simulated by combining lumped mass and equivalent stiffness. By adjusting the lumped mass and equivalent stiffness parameters, the first natural frequency of the superstructure of the model can be made to be completely consistent with the prototype of the offshore wind turbine, and thus the superstructure model with equivalent dynamic characteristics can be finally obtained.

[0085] Step S2025: Assemble the target site model, the target wind turbine foundation model, and the superstructure model to obtain the initial scaled-down model of the centrifugal vibration table test.

[0086] In one optional embodiment, the constructed target site model, target wind turbine foundation model, and superstructure model are assembled in an integrated manner according to the actual relative positions and connection methods of the prototype. Then, the site model is positioned, the foundation model is installed and fixed, and the superstructure model is rigidly connected to the foundation model in sequence. By ensuring that the connection stiffness of each component and the boundary constraints are consistent with the actual project, a complete initial scaled model of the centrifugal vibration table test is finally formed.

[0087] Step S2026: Add accelerometers to the mud surface position and the top position of the foundation of the initial centrifugal shaking table test scale model and construct the target centrifugal shaking table test scale model.

[0088] In one alternative embodiment, firstly, an acceleration sensor is placed at the mud surface position of the scaled-down model of the initial centrifugal shaking table test to collect the seismic input signal of the seabed surface during the test.

[0089] Then, an acceleration sensor was installed at the top of the model wind turbine foundation to collect the structural output response signal during the test.

[0090] Finally, by wiring, fixing, debugging and calibrating the range of all acceleration sensors, it can be ensured that the sensor acquisition frequency and measurement accuracy meet the test requirements. Thus, after the sensor layout is completed, a scaled-down model of the target centrifugal vibration table test can be obtained for use in centrifugal vibration table dynamic tests.

[0091] In some optional implementations, step S203 above includes: Step S2031: Simulate the actual gravity environment of the target sea wind field based on the preset centrifugal acceleration.

[0092] In one alternative embodiment, the soil thickness of the scaled-down model is much smaller than that of the prototype, and its own weight alone cannot achieve the in-situ effective stress level. Furthermore, by applying centrifugal acceleration, the stress in the model soil can be made consistent with that in actual engineering, ensuring the authenticity of the soil's mechanical properties.

[0093] For example, the assembled scaled-down model of the target centrifugal vibration table test can be placed in the center of the centrifugal vibration table equipment and fixed firmly, and the centrifugal acceleration can be set to 50g~100g, with 50g preferred.

[0094] Then, the centrifuge equipment is activated to place the model in a stable centrifugal acceleration field. Through site consolidation and in-situ stress simulation, the density, stiffness, and constraint conditions of the seabed soil in the model can be made completely consistent with the actual gravity environment of the target offshore wind field.

[0095] Step S2032: Under actual gravity conditions, multiple seismic waves are used to excite the scaled model of the target centrifugal shaking table test, and the seismic acceleration time history response datasets at the first mud surface position and the first foundation top position are obtained. The multiple seismic waves adopt different frequency ranges and different peak accelerations.

[0096] In one alternative embodiment, different seismic intensities and frequencies will excite varying degrees of nonlinear characteristics in the soil. Therefore, multi-wave, multi-amplitude excitation can be used to obtain the dynamic response under all working conditions, ensuring that the transfer function library covers actual seismic scenarios in engineering projects.

[0097] For example, the centrifugal acceleration is first kept stable, and various seismic waves such as Kobe waves, Chichi waves, and artificial nearshore seismic waves are selected as excitation inputs. At the same time, the excitation frequency range can be set to 0.1Hz~10Hz and the peak acceleration to 0.05g~0.4g.

[0098] Furthermore, different seismic waves and different peak accelerations were applied to the model sequentially, and the seismic acceleration time history at the mud surface location of the model was collected synchronously during the experiment, thereby obtaining the corresponding seismic acceleration time history response dataset at the first mud surface location.

[0099] Simultaneously, the seismic acceleration time history at the top of the model foundation was collected, thereby obtaining the corresponding seismic acceleration time history response dataset at the top of the first foundation, ensuring that all data are continuous, complete, undistorted, and untrunculated.

[0100] Step S2033: Process the earthquake acceleration time history response datasets at the first mud surface location and the first foundation top location, respectively, and establish an amplitude correlation transfer function library based on the nonlinear effects of soil.

[0101] Specifically, step S2033 includes: Step b1: Using the different peak ground acceleration values ​​corresponding to multiple seismic waves, the earthquake acceleration time history response datasets at the first mud surface location and the first foundation top location are grouped by amplitude to obtain multiple sets of earthquake acceleration time history response datasets at the second mud surface location and multiple sets of earthquake acceleration time history response datasets at the second foundation top location corresponding to different amplitudes.

[0102] Step b2 involves processing the time-domain acceleration signals in each group of seismic acceleration time history response datasets at the second mud surface location to obtain multiple mud surface location time-domain acceleration signals.

[0103] Step b3: Process the time-domain acceleration signals in the seismic acceleration time history response dataset at the top of each second foundation to obtain multiple time-domain acceleration signals at the top of the foundation.

[0104] Step b4: Using the Fourier transform method, the time-domain acceleration signals of multiple mud surface positions and the time-domain acceleration signals of multiple foundation top positions are converted into the frequency domain to obtain multiple sets of mud surface position frequency domain information and multiple sets of foundation top position frequency domain information.

[0105] Step b5: Based on multiple sets of frequency domain information of mud surface location and multiple sets of frequency domain information of foundation top location, calculate multiple representative transfer functions at multiple amplitudes.

[0106] Step b6: Construct an amplitude-dependent transfer function library based on soil nonlinear effects, using multiple representative transfer functions.

[0107] In one optional embodiment, the time-domain acceleration signal at the mud surface position represents the original seismic acceleration time history signal that is continuously varied over time and is directly collected at the mud surface position of the model during the centrifugal shaking table test; the time-domain acceleration signal at the top of the foundation position represents the time-domain acceleration signal corresponding to the top of the foundation in each group after grouping according to the peak excitation acceleration, which is the test response data after grouping.

[0108] Furthermore, multiple sets of frequency domain information on mud surface location are used to reflect the amplitude and phase characteristics of seismic input at different frequencies; multiple sets of frequency domain information on foundation top location are used to reflect the seismic response characteristics of the structure at different frequencies.

[0109] Furthermore, the transfer functions represented by multiple mud surface locations / multiple foundation top locations represent representative transfer functions obtained by averaging the transfer functions corresponding to different seismic waves under the same excitation amplitude. This is used to eliminate wave pattern discrepancy errors and stably reflect the dynamic transmission characteristics of the system under that amplitude.

[0110] In an alternative embodiment, firstly, peak acceleration is excited. Based on the grouping criteria, the datasets of the first mud surface position and the first foundation top position are divided into several amplitude groups according to the intervals of 0.05g, 0.1g, 0.15g, 0.2g, 0.3g, and 0.4g.

[0111] Furthermore, each group contains multiple test data of different seismic waves under the same amplitude, and finally obtains multiple sets of seismic acceleration time history response datasets at the second mud surface location and multiple sets of seismic acceleration time history response datasets at the top of the second foundation corresponding to different amplitudes.

[0112] Secondly, the time-domain acceleration signals in each group of second mud surface position data are sequentially processed by detrending, baseline correction, and 0.05Hz~10Hz bandpass filtering to remove low-frequency drift and high-frequency noise, and finally obtain a clean and stable mud surface position time-domain acceleration signal.

[0113] Meanwhile, the time-domain acceleration signals in each group of second base top position data are also processed sequentially, including detrending, baseline correction, and 0.05Hz~10Hz bandpass filtering, and finally a clean and stable base top position time-domain acceleration signal is obtained.

[0114] Then, the time-domain acceleration signals of each set of mud surface positions were converted using Fast Fourier Transform (FFT) to obtain multiple sets of frequency-domain information of mud surface positions. The following relation (3) is shown: (3) In the formula: Indicates frequency; Represents the time-domain signal of the mud surface; Simultaneously, the same transformation was performed on the time-domain acceleration signals of each group of foundation top positions to obtain multiple groups of foundation top position frequency-domain information. The following relation (4) is shown: (4) In the formula: This represents the time-domain signal at the top of the base.

[0115] Furthermore, combining multiple sets of frequency domain information on mud surface locations and multiple sets of basic top position frequency domain information The transfer function under a single waveform is calculated using the following relation (5). : (5) Furthermore, the arithmetic mean of the transfer functions of seismic waves with the same amplitude but different amplitudes is calculated to obtain the representative transfer function for that amplitude. The following relation (6) is shown: (6) In the formula: This represents the total number of seismic waves with the same amplitude.

[0116] Finally, the representative transfer functions corresponding to each amplitude are sorted in ascending order of peak acceleration to form an amplitude-transfer function mapping library. .

[0117] Furthermore, this function library can reflect the dynamic characteristics of the system as the excitation amplitude increases, the nonlinearity of the soil deepens, the equivalent stiffness of the soil around the pile decreases, the first-order peak frequency of the system shifts to lower frequencies, and the peak amplitude changes.

[0118] In some optional implementations, step S204 above includes: Step S2041: Preprocess the measured earthquake acceleration time history response dataset to obtain the target earthquake acceleration time history response dataset.

[0119] In one optional embodiment, the raw measured data may be affected by marine environmental noise, sensor drift, electromagnetic interference, baseline shift, etc., and direct use will lead to distortion of the inversion results. Furthermore, by performing noise reduction, calibration and normalization processing on the raw measured seismic acceleration time history data collected from the top of the wind turbine foundation, interference factors can be eliminated, and a clean, reliable target dataset that can be used for inversion calculation can be obtained.

[0120] For example, by sequentially performing detrending processing, baseline correction, denoising processing, 0.05Hz~10Hz bandpass filtering, and data amplitude calibration on the measured seismic acceleration time history response dataset, environmental interference, equipment system errors and signal drift can be eliminated, and the time-domain acceleration signal can be made smooth, continuous and without abnormal abrupt changes, so as to finally obtain the target seismic acceleration time history response dataset that meets the requirements of inversion calculation.

[0121] Step S2042: Determine the peak ground acceleration value of the measured earthquake response based on the target earthquake acceleration time history response dataset.

[0122] In one optional embodiment, the measured peak ground acceleration value represents the maximum absolute acceleration value in the measured seismic acceleration time history data at the top of the offshore wind turbine foundation when an offshore earthquake occurs, and is used to characterize the intensity level of the actual earthquake action.

[0123] In one alternative embodiment, the nonlinear effect of the soil is directly related to the earthquake intensity. Different intensities correspond to different soil stiffness and dynamic transmission characteristics. Peak acceleration must be used to match the transfer function of the corresponding amplitude in order to ensure accurate inversion.

[0124] For example, the acceleration values ​​at all times in the target earthquake acceleration time history response dataset are traversed, the acceleration value with the largest absolute value is calculated and selected, and this value is determined as the peak ground acceleration value of the measured seismic response of this earthquake. .

[0125] Step S2043: Based on the measured peak ground acceleration value of the earthquake response, determine the target transfer function from the amplitude correlation transfer function library based on the nonlinear effect of soil.

[0126] In one optional embodiment, the amplitude-related transfer function library is constructed according to different earthquake intensity levels. Only by selecting a transfer function consistent with the intensity of the current earthquake can the influence of soil nonlinearity on dynamic transmission be accurately reflected, thus avoiding inversion bias.

[0127] For example, the measured peak ground acceleration value of the earthquake response The amplitude nodes in the amplitude-related transfer function library are compared. Furthermore, if... A peak acceleration in the amplitude-dependent transfer function library If they are completely identical, the representative transfer function corresponding to that amplitude is directly selected as the target transfer function.

[0128] Furthermore, if If the target transfer function is located between two amplitude nodes in the amplitude correlation transfer function library, then a linear interpolation method can be used to calculate the target transfer function adapted to this earthquake. .

[0129] Step S2044: Based on the measured seismic acceleration time history response dataset, the actual seismic motion state of the seabed in the target offshore wind field is inverted using the target transfer function to obtain the inverted seabed seismic motion dataset.

[0130] Specifically, step S2044 includes: Step c1: Input the target seismic acceleration time history response dataset into the target transfer function to obtain the frequency domain ground motion dataset corresponding to the mud surface position of the offshore wind turbine at the time of the earthquake.

[0131] Step c2 involves performing a time-domain inverse transformation on the frequency-domain ground motion dataset to obtain the inverted seabed ground motion dataset.

[0132] In an optional embodiment, the target seismic acceleration time history response dataset is subjected to a Fast Fourier Transform (FFT) to convert it into frequency domain structural response data. .

[0133] Furthermore, based on and target transfer function The frequency domain ground motion dataset of the mud surface location is calculated as shown in the following relation (7): (7) In the formula: This represents the frequency domain ground motion data of the seabed mud surface obtained through inversion.

[0134] Furthermore, the calculated frequency domain ground motion dataset... Performing an inverse fast Fourier transform (IFFT) can convert frequency domain data into time domain data, ultimately yielding an inverted seabed ground motion dataset that can be directly used for seismic design of offshore wind power, code correction, and parameter optimization. .

[0135] Furthermore, this seabed seismic dataset can accurately reflect the actual seismic state of the target wind field seabed and can be directly used for the revision of offshore wind power seismic design codes and the optimization of design parameters.

[0136] In one instance, such as Figure 3 As shown, this paper presents a method for inverting seabed ground motion based on on-site monitoring data of offshore wind turbine foundations. This method aims to overcome the technical bottlenecks of existing technologies, such as the difficulty in conducting actual seabed ground motion measurements and the inability to directly apply existing monitoring data to seismic design. It also addresses the shortcomings of existing technologies, such as insufficient inversion accuracy due to the transfer function not considering soil nonlinearity and the failure to account for the kinetic and hydrodynamic effects of offshore wind turbines. By combining the target wind turbine site survey results, wind turbine structural physical parameters, and centrifugal dynamic tests, the method accurately obtains the wind turbine system's transfer function in the frequency domain. Then, during actual earthquakes, this transfer function is used to convert the wind turbine structural monitoring data, efficiently inverting and obtaining accurate and reliable seabed ground motion data.

[0137] Furthermore, this method is highly versatile, applicable not only to planned offshore wind farms but also to existing operational wind farms. It requires no modifications to existing wind turbine structures or monitoring systems, enabling seabed seismic inversion using existing monitoring systems. The method is simple, easy to operate, and produces scientifically accurate results. It eliminates the need for additional seabed monitoring equipment, fully utilizing existing offshore wind power monitoring resources, reducing monitoring and inversion costs, facilitating engineering application, and providing reliable data support for revising seismic design criteria and optimizing seismic design parameters for offshore wind power.

[0138] Furthermore, the method includes the following steps: S1. Model Construction: Based on detailed geological survey data of the target offshore wind farm (including seabed soil layer distribution, soil physical and mechanical parameters, geological structural characteristics, etc.) and the specific characteristics of the wind turbine structural system (including wind turbine model, tower height, foundation type and size, structural stiffness distribution, etc.), following the principle of similarity and fully considering the pile-soil interaction and the unique hydrodynamic effect of offshore wind turbines, a scaled-down model of the centrifugal shaking table test is constructed according to the following specific steps: (1) Determine the similarity ratio: Based on the size of the test equipment and the scale of the prototype, a scaling ratio of 1:50 to 1:100 is generally selected, with 1:50 being preferred; (2) Seabed site modeling: The soil layers are filled in layers according to the geological survey, and the sand rain method / compaction method is used to prepare the soil, and the density and saturation are controlled to be consistent with the prototype. (3) Basic modeling: The basic model is fabricated according to the scale ratio to ensure that the stiffness, mass and cross-sectional properties are equivalent to the prototype; (4) Calculation of dynamic water added mass: Unlike onshore wind turbines, offshore wind turbines are submerged in seawater above the foundation mud surface. When a single pile vibrates under seismic excitation, its interaction with the surrounding water will generate additional dynamic effects on the structure, which will change the dynamic characteristics of the structure. This dynamic water effect between the single pile and the water body can usually be simulated by the dynamic water added mass method. The dynamic water added mass can be calculated according to the above relationships (1) and (2).

[0139] Furthermore, after calculating the additional mass of the dynamic water in the submerged section, an iron ring of corresponding mass is made according to the similarity ratio and fixed at the corresponding height of the submerged section of the foundation to simulate the dynamic water effect under earthquake action.

[0140] (5) Modeling of the superstructure: The simulation is carried out by lumped mass + equivalent stiffness to ensure that the first natural frequency is consistent with the prototype; (6) Model assembly: Complete the assembly of the site, foundation and superstructure.

[0141] S2. Sensor Deployment: Accelerometers are deployed at key locations on the scaled-down model of the centrifugal shaking table test. Specifically, accelerometers are deployed on the mud surface of the model (corresponding to the actual seabed surface) to collect seismic motion data of the seabed surface during the test; accelerometers are deployed at the top of the wind turbine foundation of the model to collect seismic response data of the top of the foundation, laying the foundation for subsequent transfer function construction and inversion calculation.

[0142] S3. Centrifugal shaking table test: The completed scaled-down model is placed on a centrifugal shaking table, and the centrifugal acceleration is set to 50g~100g (50g preferred) to simulate the gravity environment of the actual offshore wind field. Then, seismic waves (such as Kobe waves, Chichi waves, and artificial nearshore seismic waves) with a frequency range of 0.1Hz~10Hz and a peak acceleration of 0.05g~0.4g are used to excite the model. Seismic acceleration time history response data at the mud surface and the top of the foundation are collected simultaneously to ensure that the collected data is complete, continuous, and undistorted, so as to provide sufficient data support for the calculation of the transfer function.

[0143] S4. Amplitude-related transfer function acquisition: The seismic motion at the mud surface (input) and the seismic response at the top of the foundation (output) collected under different excitation amplitude conditions in step S3 are processed separately to establish an amplitude-related transfer function library that considers the nonlinear effects of soil. This library can accurately reflect the influence of soil stiffness degradation on the dynamic transmission characteristics of the structure under different earthquake intensities. The specific steps are as follows: (1) Working condition grouping.

[0144] According to peak acceleration The magnitude of the amplitude determines the magnitude of the amplitude. The experimental data is divided into several amplitude groups, such as 0.05g, 0.1g, 0.15g, 0.2g, 0.3g, 0.4g, etc. Each group contains multiple experimental data of different seismic waves (Kobe wave, Chichi wave, artificial nearshore seismic wave) at the same amplitude.

[0145] (2) Group frequency domain conversion.

[0146] The time-domain acceleration signals within each amplitude group were preprocessed: detrending, baseline correction, and bandpass filtering from 0.05Hz to 10Hz; then, they were transformed to the frequency domain using Fourier transform to obtain the mud surface input for that amplitude group. and the base top output frequency domain information As shown in equations (3) and (4) above.

[0147] (3) Calculation of group transfer function: as shown in the above relation (5).

[0148] Furthermore, the transfer functions of different seismic wave conditions with the same amplitude are averaged to obtain the representative transfer function under that amplitude, as shown in the above relation (6).

[0149] (4) Establishment of amplitude-related transfer function library.

[0150] Summarize representative transfer functions for each amplitude and establish an amplitude-transfer function mapping library: .

[0151] Furthermore, this function library can reflect the dynamic characteristics of the system as the excitation amplitude increases, the nonlinearity of the soil deepens, the equivalent stiffness of the soil around the pile decreases, the first-order peak frequency of the system shifts to lower frequencies, and the peak amplitude changes.

[0152] S5. Seabed Seismic Motion Inversion: Obtain the measured time history of the top acceleration of the actual offshore wind turbine foundation during the earthquake. Preprocess the measured data (including noise reduction, filtering, data calibration, etc.) and extract the peak ground acceleration of the measured response to the earthquake. ;according to The magnitude is determined by selecting the corresponding or interpolated transfer function from the amplitude-related transfer function library established in step S4. Substitute the measured response data in the frequency domain into the transfer function, and obtain the frequency domain ground motion data at the mud surface through inversion calculation, as shown in the above relation (7).

[0153] Furthermore, by inversely transforming the frequency domain ground motion data to the time domain, the inverted seabed ground motion data can be obtained. This data can accurately reflect the actual seismic motion state of the seabed in the target wind field and can be directly used for the revision of offshore wind power seismic design specifications and the optimization of design parameters.

[0154] The seabed seismic inversion method based on on-site monitoring data of offshore wind power foundations provided in this example has the following advantages: 1. Significantly improved inversion accuracy: By establishing an amplitude correlation transfer function library, the nonlinear dynamic characteristics of soil under different earthquake intensities are fully considered, solving the problem of large inversion error of traditional single transfer function under strong earthquake action; 2. Highly targeted: For the first time, the unique hydrodynamic effect of offshore wind turbines was systematically considered in centrifugal model tests, making the model more closely resemble actual engineering conditions; 3. Good economic efficiency: It makes full use of the existing structural health monitoring system of offshore wind turbines, eliminating the need for additional seabed monitoring equipment and significantly reducing the cost of seabed seismic data acquisition; 4. Wide range of applications: It can be applied to both planned and in-service offshore wind farms, providing data support for seismic design of offshore wind power at different stages.

[0155] Furthermore, a specific embodiment is provided based on the above method: A certain offshore wind turbine uses a large-diameter monopile as its support system. The monopile has a diameter of 4m, a total pile length of 40m, a top elevation of 8m, and an elevation of 80m at the nacelle. The total weight of the nacelle and impeller is 150t, and the first-order natural frequency of the wind turbine system is 0.31Hz. Geological survey results of the wind farm site indicate that the site is mainly composed of medium-dense to dense sandy soil with a unit weight of 19kN / m³. 3 The internal friction angle is 32°, the soil layers are evenly distributed, there are no obvious weak interlayers, and the site geological conditions are stable.

[0156] (1) Model Construction: Based on the detailed geological survey data and wind turbine structural system parameters of the offshore wind farm, a centrifugal shaking table test model including the seabed site, large-diameter monopile foundation, and wind turbine superstructure was constructed at a scale of 1:50. The model monopile diameter is 0.08m, the total length of the pile foundation is 0.8m, and the equivalent weight of the nacelle impeller is 1.2kg. The superstructure is established as a single-degree-of-freedom system to achieve the equivalent first-order natural frequency of the structural system. The site model is filled with homogeneous dense sand consistent with the actual site. The filling thickness is determined according to the actual seabed cover layer thickness and the scale ratio. The site sample is prepared by the sand rain method, and the site is saturated by a vacuum saturation device. The additional mass of the submerged section of the monopile is calculated, and an iron ring is made according to the similarity ratio and fixed at the corresponding height to simulate the dynamic water effect under seismic action.

[0157] (2) Sensor Deployment: High-precision accelerometers were deployed at key locations on the scaled-down model, with a maximum range of 20g. The specific deployment scheme is as follows: One accelerometer was deployed at the mud surface of the model to collect seismic input data of the seabed surface during the test; one accelerometer was deployed at the top of the single pile foundation of the model wind turbine to collect the seismic response output data of the top of the foundation; at the same time, referring to the monitoring point layout of the actual wind turbine, an additional accelerometer was deployed at the nacelle of the model to verify the consistency of the frequency characteristics of the model and the prototype. The test acceleration response was recorded using a dynamic acquisition system, with the acquisition frequency set at 5000Hz.

[0158] (3) Centrifugal shaking table test: The scaled-down model was placed on the centrifugal shaking table, and the centrifugal acceleration was set to 50g for site consolidation. Then, seismic waves with different frequency components (including Kobe waves, Chichi waves and synthetic nearshore seismic waves) were selected as seismic motion excitations. Three different excitation conditions with different amplitudes (peak accelerations of 0.1g, 0.2g and 0.3g, respectively) were set to excite the model. During the test, the seismic acceleration response at the mud surface and the top of the foundation was collected. The collection process continued until the seismic wave excitation ended to ensure that the collected data was complete, continuous and undistorted, providing sufficient and reliable data support for the calculation of the transfer function.

[0159] (4) Establishment of amplitude-related transfer function library: The test data collected in step (3) under the three working conditions are preprocessed. The bandpass filtering method is used to eliminate environmental noise and equipment interference. The filtering frequency band is selected from 0.05Hz to 10Hz. Then, the acceleration response in the time domain is converted to the frequency domain by Fourier transform. The transfer functions of different waveforms with the same amplitude are averaged according to the peak acceleration of the excitation to obtain the representative transfer function under each amplitude and establish the amplitude-transfer function correspondence library.

[0160] Furthermore, such as Figure 4 As shown, the transfer function curve obtained under the condition of 0.15g base excitation is displayed.

[0161] (5) Seabed ground motion inversion: Collect measured ground motion response data of the offshore wind turbine during a near-shore earthquake. This data is recorded by the acceleration sensor at the top of the foundation. Preprocess the measured data, including noise reduction, filtering, baseline calibration, etc., to eliminate equipment errors and environmental interference during the monitoring process. Extract the peak acceleration of the measured response and select the transfer function with the corresponding amplitude from the transfer function library established in step (4). Substitute the measured response data in the frequency domain into the transfer function and obtain the frequency domain ground motion data at the mud surface through inverse calculation. Then, convert the frequency domain ground motion data to the time domain through Fourier inverse transformation to obtain the inverted seabed ground motion data. .

[0162] This embodiment also provides a seabed seismic inversion device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0163] This embodiment provides a seabed seismic inversion device, such as... Figure 5 As shown, the device includes: The acquisition module 501 is used to acquire detailed geological survey data of the target offshore wind field, the wind turbine structural characteristic set, and the measured seismic acceleration time history response dataset corresponding to the top position of the foundation of the offshore wind turbine at the time of the earthquake.

[0164] The first construction module 502 is used to construct a scaled-down model of the target centrifugal shaking table test based on pile-soil interaction, offshore wind turbine hydrodynamic effect and similarity principle, using the detailed geological survey data and the wind turbine structural characteristic set.

[0165] The second construction module 503 is used to simulate the actual gravity environment of the target offshore wind field based on a preset centrifugal acceleration, and to conduct simulation tests using a scaled-down model of the target centrifugal shaking table test, thereby constructing an amplitude-related transfer function library based on the nonlinear effects of soil.

[0166] The inversion module 504 is used to invert the actual seismic motion state of the seabed of the target marine wind field based on the measured seismic acceleration time history response dataset and the amplitude correlation transfer function library based on soil nonlinear effects, so as to obtain the inverted seabed seismic motion dataset.

[0167] The seabed seismic inversion device provided in this embodiment of the invention can execute the seabed seismic inversion method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the above modules are the same as in the corresponding embodiments described above, and will not be repeated here.

[0168] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0169] The following is a detailed reference. Figure 6 This diagram illustrates a suitable structural design for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 601, which can perform various appropriate actions and processes based on a program stored in read-only memory (ROM) 602 or a program loaded from memory 608 into random access memory (RAM) 603. RAM 603 also stores various programs and data required for the operation of the electronic device. The processor 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0170] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 608 including, for example, magnetic tapes, hard disks, etc.; and communication devices 609. Communication device 609 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 6 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0171] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 609, or installed from a memory 608, or installed from a ROM 602. When the computer program is executed by the processor 601, it performs the functions defined in the seabed seismic inversion method of the embodiments of the present invention.

[0172] Figure 6The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0173] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the seabed seismic inversion method shown in the above embodiments is implemented.

[0174] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0175] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for inverting seabed ground motion, characterized in that, The method includes: Obtain detailed geological survey data of the target offshore wind field, wind turbine structural characteristic set, and measured seismic acceleration time history response dataset corresponding to the top position of the foundation of the offshore wind turbine at the time of the earthquake; Based on pile-soil interaction, offshore wind turbine hydrodynamic effect and similarity principle, a scaled model of the target centrifugal shaking table test is constructed using the detailed geological survey data and the wind turbine structural characteristic set. The actual gravity environment of the target offshore wind field is simulated based on the preset centrifugal acceleration, and the simulation test is carried out using the scaled model of the target centrifugal shaking table test. An amplitude correlation transfer function library based on the nonlinear effect of soil is constructed. Based on the measured seismic acceleration time history response dataset, the actual seismic motion state of the seabed of the target offshore wind field is inverted using the amplitude correlation transfer function library based on soil nonlinear effects, and the inverted seabed seismic motion dataset is obtained. The simulation method involves using a preset centrifugal acceleration to model the actual gravity environment of the target offshore wind field, and conducting simulation tests using a scaled-down model of the target centrifugal shaking table test. It also includes constructing a library of amplitude-related transfer functions based on soil nonlinear effects, comprising: The actual gravity environment of the target offshore wind field is simulated based on the preset centrifugal acceleration. Under the actual gravity environment, multiple seismic waves were used to excite the scaled model of the target centrifugal shaking table test, and the seismic acceleration time history response datasets at the first mud surface location and the first foundation top location were obtained. The multiple seismic waves used different frequency ranges and different peak accelerations. Using the magnitudes of different peak accelerations corresponding to the multiple seismic waves, the earthquake acceleration time history response datasets at the first mud surface location and the first foundation top location are grouped by amplitude to obtain multiple sets of earthquake acceleration time history response datasets at the second mud surface location and multiple sets of earthquake acceleration time history response datasets at the second foundation top location corresponding to different amplitudes. The time-domain acceleration signals in each group of seismic acceleration time history response datasets at the second mud surface location were processed to obtain multiple mud surface location time-domain acceleration signals. The time-domain acceleration signals in the seismic acceleration time history response dataset at the top of each second foundation were processed to obtain multiple time-domain acceleration signals at the top of the foundation. Using the Fourier transform method, the time-domain acceleration signals of the multiple mud surface positions and the time-domain acceleration signals of the multiple foundation top positions are converted into the frequency domain to obtain multiple sets of mud surface position frequency domain information and multiple sets of foundation top position frequency domain information. Based on the multiple sets of mud surface location frequency domain information and the multiple sets of foundation top location frequency domain information, calculate multiple representative transfer functions at multiple amplitudes; Based on the multiple representative transfer functions, the amplitude correlation transfer function library based on soil nonlinear effects is constructed.

2. The method according to claim 1, characterized in that, Based on pile-soil interaction, offshore wind turbine kinetic-hydrodynamic effects, and similarity principles, a scaled-down model of the target centrifugal shaking table test is constructed using the detailed geological survey data and the wind turbine structural characteristic set, including: Based on the aforementioned similarity principle, the model similarity ratio parameters are determined using the wind turbine structural characteristic set and the preset test equipment dimensions. Based on the aforementioned similarity principle and the pile-soil interaction, the seabed site is modeled using the aforementioned detailed geological survey data to obtain a target site model. The target site model matches the prototype seabed and reflects the pile-soil interaction. Based on the aforementioned similarity principle and the aforementioned dynamic water effect of offshore wind turbines, a target wind turbine foundation model simulating the dynamic water effect is constructed using the aforementioned wind turbine structural characteristic set. Based on the aforementioned similarity principle, the superstructure of the wind turbine is simulated using the aforementioned wind turbine structural characteristic set, and a superstructure model with dynamic characteristics equivalent to the offshore wind turbine prototype is constructed. The first-order natural frequency of the superstructure model is consistent with that of the offshore wind turbine prototype. The target site model, the target wind turbine foundation model, and the superstructure model are assembled to obtain an initial scaled model of the centrifugal vibration table test. Accelerometers were added to the mud surface and the top of the foundation of the initial scaled-down centrifugal shaking table test model, respectively, and the target scaled-down centrifugal shaking table test model was constructed.

3. The method according to claim 2, characterized in that, Based on the aforementioned similarity principle and the aforementioned dynamic water effect of offshore wind turbines, a target wind turbine foundation model simulating the dynamic water effect is constructed using the aforementioned wind turbine structural characteristic set, including: Based on the aforementioned similarity principle, an initial wind turbine basic model equivalent to the offshore wind turbine prototype is constructed using the aforementioned wind turbine structural characteristic set and the aforementioned model similarity ratio parameter. Based on the aforementioned similarity principle and the aforementioned dynamic water effect of offshore wind turbines, the dynamic water added mass is calculated using the aforementioned wind turbine structural characteristic set. Based on the model similarity ratio parameter and the added mass of the dynamic water, the initial wind turbine foundation model is optimized to obtain the target wind turbine foundation model that simulates the dynamic water effect.

4. The method according to claim 1, characterized in that, Based on the measured seismic acceleration time history response dataset, and using the amplitude correlation transfer function library based on soil nonlinear effects, the actual seismic motion state of the seabed in the target offshore wind field is inverted to obtain the inverted seabed seismic motion dataset, including: The measured earthquake acceleration time history response dataset is preprocessed to obtain the target earthquake acceleration time history response dataset; Based on the target earthquake acceleration time history response dataset, determine the measured peak ground acceleration value of the earthquake response; Based on the measured peak ground acceleration value of the earthquake response, the target transfer function is determined from the amplitude correlation transfer function library based on the nonlinear effect of soil. Based on the measured seismic acceleration time history response dataset, the actual seismic motion state of the seabed in the target marine wind field is inverted using the target transfer function to obtain the inverted seabed seismic motion dataset.

5. The method according to claim 4, characterized in that, Based on the measured seismic acceleration time history response dataset, the actual seismic motion state of the seabed in the target marine wind field is inverted using the target transfer function to obtain the inverted seabed seismic motion dataset, including: Input the target seismic acceleration time history response dataset into the target transfer function to obtain the frequency domain ground motion dataset corresponding to the mud surface position of the offshore wind turbine at the time of the earthquake. The frequency domain ground motion dataset is inversely transformed in the time domain to obtain the inverted seabed ground motion dataset.

6. A seabed seismic inversion device, characterized in that, The device includes: The acquisition module is used to acquire detailed geological survey data of the target offshore wind field, the set of wind turbine structural characteristics, and the measured seismic acceleration time history response dataset corresponding to the top position of the foundation of the offshore wind turbine at the time of the earthquake. The first construction module is used to construct a scaled model of the target centrifugal shaking table test based on pile-soil interaction, offshore wind turbine kinetic water effect and similarity principle, using the detailed geological survey data and the wind turbine structural characteristic set. The second construction module is used to simulate the actual gravity environment of the target offshore wind field based on a preset centrifugal acceleration, and to conduct simulation tests using a scaled model of the target centrifugal shaking table test, and to construct an amplitude correlation transfer function library based on the nonlinear effect of soil. The inversion module is used to invert the actual seismic motion state of the seabed of the target marine wind field based on the measured seismic acceleration time history response dataset and the amplitude correlation transfer function library based on soil nonlinear effects, so as to obtain the inverted seabed seismic motion dataset. The second building module is specifically used for: The actual gravity environment of the target offshore wind field is simulated based on the preset centrifugal acceleration. Under the actual gravity environment, multiple seismic waves were used to excite the scaled model of the target centrifugal shaking table test, and the seismic acceleration time history response datasets at the first mud surface location and the first foundation top location were obtained. The multiple seismic waves used different frequency ranges and different peak accelerations. Using the magnitudes of different peak accelerations corresponding to the multiple seismic waves, the earthquake acceleration time history response datasets at the first mud surface location and the first foundation top location are grouped by amplitude to obtain multiple sets of earthquake acceleration time history response datasets at the second mud surface location and multiple sets of earthquake acceleration time history response datasets at the second foundation top location corresponding to different amplitudes. The time-domain acceleration signals in each group of seismic acceleration time history response datasets at the second mud surface location were processed to obtain multiple mud surface location time-domain acceleration signals. The time-domain acceleration signals in the seismic acceleration time history response dataset at the top of each second foundation were processed to obtain multiple time-domain acceleration signals at the top of the foundation. Using the Fourier transform method, the time-domain acceleration signals of the multiple mud surface positions and the time-domain acceleration signals of the multiple foundation top positions are converted into the frequency domain to obtain multiple sets of mud surface position frequency domain information and multiple sets of foundation top position frequency domain information. Based on the multiple sets of mud surface location frequency domain information and the multiple sets of foundation top location frequency domain information, calculate multiple representative transfer functions at multiple amplitudes; Based on the multiple representative transfer functions, the amplitude correlation transfer function library based on soil nonlinear effects is constructed.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the seabed seismic inversion method according to any one of claims 1 to 5.

8. A computer program product, characterized in that, Includes computer instructions for causing a computer to execute the seabed seismic inversion method according to any one of claims 1 to 5.

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