Simulation data processing method and system of pile-soil interaction model

Abstract

The present application relates to the technical field of data processing, and particularly relates to a simulation data processing method and system for a pile-soil interaction model. The method comprises the following steps: obtaining pile contact pressure data sequences of multiple simulation conditions of the pile-soil interaction model, and wind load data sequences corresponding to each simulation condition; determining a preliminary complexity of the pile contact pressure data sequences for each simulation condition; determining a distortion degree of the pile contact pressure data sequences; determining an adaptive mode number; processing the pile contact pressure data sequences by using an adaptive variational mode decomposition algorithm; and achieving simulation data processing for the pile-soil interaction model. The present application analyzes the frequency spectrum of pile pressure data, constructs a spectrum entropy and centroid index to evaluate the complexity, calculates a wind load mutual power spectral density to evaluate the distortion, dynamically adjusts the mode number, and improves the accuracy and applicability of the pile-soil simulation data processing.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a simulation data processing method and system for a pile foundation soil interaction model. Background Technology

[0002] With the increasing demand for energy and communication from modern industry, tall structures such as power transmission towers and communication towers have become key infrastructure in modern society. Their stability and safety are of paramount importance. The foundation of the tower structure lies in the pile foundation, and the bearing capacity of the pile foundation is highly dependent on the interaction between the pile and the surrounding soil.

[0003] In engineering design and safety verification, finite element numerical simulation is a commonly used technique for analyzing the interaction between pile foundations and soil. Through simulation analysis, key data such as stress, displacement, and pile-soil contact pressure of the pile foundation under conditions such as wind load and seismic motion can be obtained. However, the mechanical behavior of the contact interface between the pile foundation and soil is highly nonlinear. During the numerical simulation process, the convergence of the contact algorithm is extremely sensitive to the input soil parameters, such as the friction coefficient and elastic modulus. When the parameters are set improperly or the model has difficulty converging, the output simulated data of pile foundation contact pressure often contains distorted data caused by numerical oscillations, thus interfering with the subsequent accurate evaluation of key indicators such as pile side friction.

[0004] Variational Mode Decomposition (VMD) is an effective technique for processing complex time-series data. This algorithm decomposes complex signals into multiple intrinsic mode components with different center frequencies. However, traditional VMD algorithms require a fixed number of decomposition modes to be preset. In simulation scenarios involving tower and pile foundations, the characteristics of distorted data in the simulation data change with simulation conditions, such as variations in soil parameters. The fixed number of decomposition modes limits the algorithm's applicability. If the preset number of decomposition modes is too small, the algorithm cannot effectively separate the true physical trend from numerical distortion when data distortion is severe, leading to mode aliasing. The processed data may still be distorted. If the preset number of decomposition modes is too large, the algorithm may over-decompose the complete physical trend into multiple redundant modes without actual physical meaning when data distortion is not significant, increasing the complexity of data reconstruction and wasting computational resources. Summary of the Invention

[0005] To address the problem that traditional variational mode decomposition algorithms, which rely on a fixed number of decomposition modes when processing simulation data, can lead to mode aliasing or redundancy, thus affecting the accuracy and applicability of simulation data processing, this invention provides a simulation data processing method and system for a pile foundation soil interaction model.

[0006] In a first aspect, the present invention provides a simulation data processing method for a pile foundation soil interaction model, which adopts the following technical solution: A method for processing simulation data of a pile-soil interaction model includes: acquiring pile contact pressure data sequences for multiple simulation conditions of the pile-soil interaction model, and wind load data sequences corresponding to each simulation condition; for each simulation condition, determining the preliminary complexity of the pile contact pressure data sequence based on the spectral entropy and spectral centroid of the energy spectrum; determining the distortion degree of the pile contact pressure data sequence based on the preliminary complexity and the cross-power spectral density between the pile contact pressure data sequence and the corresponding wind load data sequence; determining the number of adaptive modes for a variational mode decomposition algorithm based on the distortion degree; processing the pile contact pressure data sequence using a variational mode decomposition algorithm based on the number of adaptive modes to obtain multiple modal components; and using the modal component with the highest correlation to the corresponding wind load data sequence as the processed pile contact pressure data to complete the simulation data processing of the pile-soil interaction model.

[0007] This invention analyzes the energy spectrum of pile foundation contact pressure data sequences and constructs evaluation indices of spectral entropy and spectral centroid, enabling a scientific assessment of data complexity. Spectral entropy reflects the complexity of frequency distribution, while spectral centroid reflects the frequency position of the main energy distribution. By calculating the cross-power spectral density of pile foundation contact pressure data sequences and wind load data sequences, and combining this with the initial complexity, a comprehensive evaluation model of distortion degree is constructed, which can effectively identify distortion characteristics that may occur during data processing. Based on the distortion degree, the number of adaptive modes is dynamically determined, realizing intelligent adjustment of variational mode decomposition parameters. When the distortion degree is high, the number of modes is appropriately increased to improve decomposition accuracy; when the distortion degree is low, the number of modes is reduced to avoid redundancy. By selecting the mode component with the highest correlation to the wind load data sequence, the engineering applicability of the processing results is ensured, effectively solving the problems of mode aliasing and mode redundancy caused by the traditional fixed number of modes, and improving the accuracy and applicability of pile foundation soil interaction model simulation data processing.

[0008] Furthermore, the acquisition of pile foundation contact pressure data sequences for multiple simulation conditions of the pile-soil interaction model, and wind load data sequences corresponding to each simulation condition, includes: constructing a pile-soil interaction model using finite element analysis software; inputting different combinations of working condition parameters to perform calculations for multiple simulation conditions; for each simulation condition, extracting the normal contact pressure data of the pile-soil contact interface along the pile depth at all sampling points from the historical database of the pile-soil interaction model as the pile foundation contact pressure data sequence, and extracting the wind load time sequence applied to the top of the tower as the corresponding wind load data sequence.

[0009] Furthermore, after obtaining the pile foundation contact pressure data sequence for multiple simulation conditions of the pile foundation soil interaction model, and the wind load data sequence corresponding to each simulation condition, the method further includes: normalizing the pile foundation contact pressure data sequence for each simulation condition and the wind load data sequence corresponding to each simulation condition to eliminate the influence of dimensions.

[0010] Furthermore, the initial complexity satisfies: In the formula, For the first The initial complexity of the pile foundation contact pressure data sequence for each simulation condition. and The first The spectral entropy and spectral centroid of the energy spectrum of a pile foundation contact pressure data sequence under a simulated working condition. For the first Energy spectrum of pile foundation contact pressure data sequence under simulated working conditions. For the first The energy spectrum of the pile foundation contact pressure data sequence under the simulated working condition is as follows: The energy percentage of each frequency range This represents the total number of frequency intervals. For the index of the frequency range, For the minimum normalization function, It is a logarithmic function with base 2.

[0011] This invention achieves a comprehensive assessment of preliminary complexity by constructing a product term that includes spectral entropy and spectral centroid. Spectral entropy reflects the complexity and uncertainty of frequency distribution, while spectral centroid reflects the distribution characteristics of energy in the frequency domain. The combination of the two can comprehensively assess the frequency domain complexity of pile foundation contact pressure data. The spectral entropy term quantifies the uniformity of frequency distribution. When the energy distribution is uniform, the entropy value is larger, and when the energy is concentrated in a few frequencies, the entropy value is smaller. The spectral centroid term reflects the frequency position of the main energy distribution. Normalization ensures the rationality of the preliminary complexity value range, which is convenient for subsequent distortion calculation.

[0012] Furthermore, the energy spectrum is obtained by performing a fast Fourier transform on the pile foundation contact pressure data sequence.

[0013] Furthermore, the degree of distortion satisfies: In the formula, For the first The degree of distortion in the pile foundation contact pressure data sequence for each simulated working condition. For the first The initial complexity of the pile foundation contact pressure data sequence for each simulation condition. For the first The cross-power spectral density between the pile foundation contact pressure data sequence and the corresponding wind load data sequence for each simulation condition. and The first The power spectral density of the pile foundation contact pressure data sequence and the corresponding wind load data sequence for each simulation condition. For the minimum normalization function, It is a natural exponential function. It is the absolute value symbol.

[0014] This invention achieves a scientific assessment of distortion by constructing a composite function that includes a preliminary complexity term and a cross-power spectral density exponent term, comprehensively considering both the complexity of the data itself and its correlation with the excitation source. The cross-power spectral density term reflects the correlation between pile contact pressure data and wind load data. When the correlation is high, the exponent term approaches 0, indicating that the distortion is mainly determined by the complexity. When the correlation is low, the exponent term increases, suggesting possible processing distortion or nonlinear effects. When the pile contact pressure data and wind load are highly correlated and the complexity is moderate, the distortion is low. When the correlation is poor or the complexity is too high, the distortion increases, indicating the need for more refined decomposition processing. The exponential decay form ensures the numerical stability of the distortion and achieves a sensitive response to changes in correlation. The distortion level provides a reliable basis for determining the number of adaptive modes, improving the applicability and accuracy of variational mode decomposition in pile-soil interaction analysis.

[0015] Furthermore, the number of adaptive modes satisfies: In the formula, For the first The number of adaptive modes for each simulation condition. This is the preset lower limit for the number of adaptive modes. This represents the number of decomposition modes in the variational mode decomposition algorithm. For the first The degree of distortion in the pile foundation contact pressure data sequence for each simulated working condition. This is for rounding operations.

[0016] This invention achieves intelligent adjustment of the number of adaptive modes by constructing a linear model that includes lower bound constraints and distortion degree weighting. This ensures a positive correlation between the number of modes and the degree of data distortion, while maintaining the rationality of the values. The introduction of distortion degree allows the number of modes to be dynamically adjusted according to data processing needs. When the distortion degree is high, the number of modes is appropriately increased to improve decomposition accuracy and avoid mode aliasing. When the distortion degree is low, the number of modes is reduced to avoid redundant components. The minimum value constraint ensures that the number of modes is not too small and affects the decomposition effect. The rounding operation ensures that the number of modes is an integer, which meets the implementation requirements of the variational mode decomposition algorithm. The adaptive adjustment mechanism effectively balances the contradiction between decomposition accuracy and computational efficiency, improves the applicability and processing quality of variational mode decomposition in pile foundation soil interaction model analysis, and avoids the limitations of traditional fixed mode number methods.

[0017] Furthermore, the step of processing the pile foundation contact pressure data sequence using the variational mode decomposition algorithm further includes: setting the penalty factor to a value of 1500~2500; setting the time step to a value of 0~0.5; and setting the convergence tolerance to a value of ~ .

[0018] Furthermore, the step of using the modal component with the highest correlation to the corresponding wind load data sequence as the processed pile foundation contact pressure data includes: obtaining the Pearson correlation coefficients of all modal components with the corresponding wind load data sequence; and selecting the modal component with the largest absolute value of the Pearson correlation coefficient as the processed pile foundation contact pressure data.

[0019] This invention achieves quantitative evaluation of each modal component by calculating the Pearson correlation coefficient between all modal components and the wind load data sequence, accurately identifying the modal component most relevant to the external excitation source. The use of the Pearson correlation coefficient ensures accurate measurement of linear correlation, and the principle of maximizing the absolute value guarantees the selection of the modal component most strongly correlated with the wind load. By adhering to the principle of maximizing correlation, the problem of missing physical meaning caused by selecting noise or minor components is effectively avoided, ensuring that the output pile foundation contact pressure data has clear external excitation response characteristics. It fully utilizes the physical mechanism of pile-soil interaction, and through correlation analysis with the excitation source, it achieves accurate extraction of effective information components, improving the accuracy and rationality of simulation data processing.

[0020] Secondly, the present invention provides a simulation data processing system for a pile foundation soil interaction model, which adopts the following technical solution: A simulation data processing system for a pile-soil interaction model includes a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the above-mentioned simulation data processing method for a pile-soil interaction model is implemented.

[0021] By adopting the above technical solution, the simulation data processing method of the above-mentioned pile foundation soil interaction model is used to generate a computer program and store it in the memory so that it can be loaded and executed by the processor. In this way, a terminal device can be made based on the memory and the processor for convenient use.

[0022] The present invention has the following technical effects: (1) Breaking through the limitation of the fixed number of decomposition modes in traditional variational mode decomposition, the data characteristics are evaluated by two dimensions of preliminary complexity and distortion, and the adaptive matching of the number of modes is achieved. The preliminary complexity is obtained by the spectral entropy of the pile foundation contact pressure data sequence reflecting the uniformity of the spectral distribution and the spectral centroid reflecting the energy concentration band. The more complex the data, such as high-frequency fluctuation data under strong wind load, the higher the preliminary complexity, and the more modes are allocated accordingly. The distortion is corrected by combining the cross power spectral density. If the data is severely distorted due to wind load interference, the number of modes is appropriately adjusted to separate the interference components. The dynamic adjustment mechanism avoids the problem of insufficient mode number for complex data leading to aliasing and excessive mode number for simple data leading to redundancy, ensuring that the decomposition accuracy matches the actual characteristics of the data and improving the accuracy of simulation data processing.

[0023] (2) Traditional variational mode decomposition only completes the data decomposition without targeted screening of mode components, which easily retains irrelevant interference components. This invention locks the core mode through correlation screening and takes the mode component with the highest correlation to the corresponding wind load data sequence as the final processing result. It accurately retains the correlation response components between wind load and pile foundation contact pressure, and eliminates irrelevant modes such as random soil disturbance and measurement noise. This makes the processed result more reflective of the real mechanical properties of pile foundation soil interaction and avoids interference components affecting subsequent model analysis.

[0024] (3) Adaptable to multiple simulation conditions. Under different simulation conditions of the pile-soil interaction model, such as different wind speeds, soil types, and pile structure parameters, the complexity and distortion of pile contact pressure data are significantly different. Under high wind speed conditions, the data fluctuates frequently and is highly complex, so the number of adaptive modes will increase. Under low wind speed or stable soil properties conditions, the data is relatively stable and less complex, so the number of modes will decrease. Compared with the limitation of traditional fixed mode number which is difficult to adapt to all conditions, the adaptive mechanism of this invention can flexibly cope with the data differences of different conditions without adjusting parameters one by one, improving the practicality and generalization ability of the technology in multiple scenarios and reducing the threshold for engineering applications. Attached Figure Description

[0025] Figure 1 This is a flowchart of a simulation data processing method for a pile foundation soil interaction model according to an embodiment of the present invention.

[0026] Figure 2 This is a comparison chart of the processing effects of pile foundation contact pressure data sequence in a simulation data processing method for a pile foundation soil interaction model according to an embodiment of the present invention. Detailed Implementation

[0027] 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, not all, of the embodiments of the present invention. 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.

[0028] This invention discloses a simulation data processing method for a pile foundation soil interaction model, referring to... Figure 1 This includes steps S001-S006: S001: Obtain the pile contact pressure data sequence for multiple simulation conditions of the pile-soil interaction model, as well as the wind load data sequence corresponding to each simulation condition.

[0029] Specifically, firstly, a numerical model of the pile-soil interaction of the tower pile foundation is constructed using finite element analysis software, such as ABAQUS. Based on design requirements, different combinations of working condition parameters are input, such as different soil friction coefficients, soil elastic moduli, and pile foundation geometric dimensions, to perform multiple sets of simulation calculations. After the simulation calculations are completed, the following two types of core data are extracted from the model's historical database using big data technology: Pile foundation contact pressure data: Extracting the normal contact pressure data at the pile-soil interface distributed along the pile depth. For the first... Each simulation condition is organized into a one-dimensional data sequence. ,in, Indexing of sampling points along the pile depth, Wind load data: Extracted from the above-mentioned data. The time series of wind loads applied to the top of the tower corresponding to each simulation condition are organized into a one-dimensional data sequence. and ensure its consistency with sampling points Correspondingly, it is used to assist in analysis; subsequently, for the acquired and Normalization is performed to eliminate the influence of dimensions and facilitate subsequent calculations.

[0030] S002: For each simulation condition, determine the preliminary complexity of the pile foundation contact pressure data sequence.

[0031] It should be noted that this step first performs time-frequency conversion on the pile foundation contact pressure data sequence to analyze its energy distribution characteristics in the frequency domain. The logic behind this is as follows: the more concentrated the spectral energy distribution of a data sequence, that is, the energy is concentrated in a few frequency bands, the simpler the internal structure of the data sequence and the lower its complexity. Conversely, the more dispersed the energy, the higher the complexity of the data sequence. If the spectral entropy of a pile foundation contact pressure sequence under a simulation condition is larger, it indicates that the energy is more dispersed and the corresponding initial complexity is higher. If the spectral centroid of a pile foundation contact pressure sequence under a simulation condition is larger, it indicates that the energy is more distributed in the high-frequency region, which also indicates that the initial complexity of the pile foundation contact pressure sequence under the simulation condition is higher.

[0032] The preliminary complexity of the pile foundation contact pressure data sequence is determined based on the spectral entropy and spectral centroid of the energy spectrum.

[0033] Specifically, the energy spectrum is obtained by performing a fast Fourier transform on the pile foundation contact pressure data sequence.

[0034] Specifically, the initial complexity satisfies: ; In the formula, For the first The initial complexity of the pile foundation contact pressure data sequence for each simulation condition. and The first The spectral entropy and spectral centroid of the energy spectrum of a pile foundation contact pressure data sequence under a simulated working condition. For the first Energy spectrum of pile foundation contact pressure data sequence under simulated working conditions. For the first The energy spectrum of the pile foundation contact pressure data sequence under the simulated working condition is as follows: The energy percentage of each frequency range Through the After normalization, This represents the total number of frequency intervals. For the index of the frequency range, For the minimum normalization function, It is a logarithmic function with base 2.

[0035] in, Calculated the first The spectral entropy of the pile foundation contact pressure sequence under simulated working conditions indicates the signal's spectral energy is more dispersed, thus indicating a higher degree of initial complexity. The larger it is; Calculated the first The centroid value of the spectral distribution of the pile foundation contact pressure sequence under each simulated working condition indicates the extent and frequency of energy distribution in the high-frequency region. A larger value suggests a greater likelihood of being affected by distorted data, corresponding to a higher degree of initial complexity. The larger it is.

[0036] S003: Determine the degree of distortion in the pile foundation contact pressure data sequence.

[0037] It should be noted that the initial complexity cannot distinguish between energy dispersion caused by the actual physical response and energy dispersion caused by distorted data. The purpose of this invention is to denoise the distorted data. Therefore, this step requires distinguishing between real and distorted data. In the scenario of pile-soil interaction, the actual response of the pile contact pressure data is usually caused by changes in wind load data. Therefore, wind load data and pile contact pressure data will have a high correlation in the frequency domain. Distorted contact pressure data, however, does not have this correlation with wind load data and will not have a high correlation in the frequency domain. Therefore, this step will analyze the correlation between wind load data and pile contact pressure data. Combining the initial complexity of the pile contact pressure data sequence for each simulation condition, the degree of distortion of the pile contact pressure data sequence for each simulation condition will be obtained. The smaller the correlation between wind load data and pile contact pressure data, the greater the likelihood that the pile contact pressure data is distorted rather than real data. Therefore, the higher the initial complexity, the greater the credibility, and the greater the corresponding degree of distortion.

[0038] The degree of distortion of the pile foundation contact pressure data sequence is determined based on the initial complexity and the cross power spectral density between the pile foundation contact pressure data sequence and the corresponding wind load data sequence.

[0039] Specifically, the degree of distortion satisfies: ; In the formula, For the first The degree of distortion in the pile foundation contact pressure data sequence for each simulated working condition. For the first The initial complexity of the pile foundation contact pressure data sequence for each simulation condition. For the first The cross-power spectral density between the pile foundation contact pressure data sequence and the corresponding wind load data sequence for each simulation condition. and The first The power spectral density of the pile foundation contact pressure data sequence and the corresponding wind load data sequence for each simulation condition. For the minimum normalization function, It is a natural exponential function. It is the absolute value symbol.

[0040] in, The larger the value, the higher the spectral energy distribution analysis based on pile foundation contact pressure data. The greater the initial complexity of the pile foundation contact pressure sequence for a simulation condition, the greater the corresponding distortion will be. Reflects the first The correlation between the contact pressure sequence and its corresponding wind load sequence for each simulated working condition is such that the larger the value, the stronger the correlation. The greater the likelihood that the contact pressure sequence of the simulated working condition belongs to distorted data rather than real data, then the more likely the 1st... The greater the initial complexity of the contact pressure sequence for a simulated working condition, the greater its reliability, but also the greater the degree of distortion.

[0041] S004: Determine the number of adaptive modes.

[0042] It should be noted that after obtaining the distortion level of the pile foundation contact pressure data sequence for each simulation condition, this step will adaptively calculate the number of adaptive modes for each simulation condition based on the distortion level. The logic is as follows: the greater the distortion level of the pile foundation contact pressure data sequence for each simulation condition, the more thorough the noise reduction is required, and the more adaptive modes are correspondingly required; and vice versa.

[0043] Based on the degree of distortion, the number of adaptive modes used in the variational mode decomposition algorithm is determined.

[0044] Specifically, the number of adaptive modes satisfies: ; In the formula, For the first The number of adaptive modes for each simulation condition. This is the preset lower limit for the number of adaptive modes. This represents the number of decomposition modes in the variational mode decomposition algorithm. For the first The degree of distortion in the pile foundation contact pressure data sequence for each simulated working condition. This is for rounding operations.

[0045] Implementers can set the lower limit for the number of adaptive modes and the number of decomposed modes according to the specific implementation situation, for example, , .

[0046] S005: The pile foundation contact pressure data sequence is processed using an adaptive variational mode decomposition algorithm.

[0047] Based on the number of adaptive modes, the pile foundation contact pressure data sequence is processed using a variational mode decomposition algorithm to obtain multiple modal components.

[0048] Specifically, the step of processing the pile foundation contact pressure data sequence using a variational mode decomposition algorithm further includes: The penalty factor is set to a value between 1500 and 2500; The time step value is set to 0~0.5; Set the convergence tolerance value to be... ~ .

[0049] S006: Implement simulation data processing for the pile foundation soil interaction model.

[0050] The modal component with the highest correlation to the corresponding wind load data sequence is used as the processed pile foundation contact pressure data to complete the simulation data processing of the pile foundation soil interaction model.

[0051] Specifically, the step of using the modal component with the highest correlation to the corresponding wind load data sequence as the processed pile foundation contact pressure data includes: Obtain the Pearson correlation coefficients between all modal components and the corresponding wind load data sequences; The modal component with the largest absolute value of the Pearson correlation coefficient was selected as the processed pile foundation contact pressure data.

[0052] like Figure 2 As shown in the figure, this graph compares the original pile foundation pressure signal with the results processed by two VMD algorithms. The horizontal axis represents the time step, and the vertical axis represents the signal amplitude. The red curve represents the original pile foundation pressure signal, exhibiting obvious high-frequency fluctuation characteristics. The blue curve is the decomposition result of adaptive VMD, and the green curve is the decomposition result of traditional VMD. The comparison shows that different mode number settings result in different decomposition effects on the original pile foundation pressure signal. Adaptive VMD can extract the signal feature components more meticulously under multi-modal decomposition, providing richer and more reliable feature support for subsequent analysis of pile foundation pressure signals, such as fault diagnosis and condition monitoring.

[0053] This invention also discloses a simulation data processing system for a pile-soil interaction model, including a processor and a memory. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, a simulation data processing method for a pile-soil interaction model according to the present invention is implemented.

[0054] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and will not be described in detail here.

[0055] The above are all preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Therefore, all equivalent changes made in accordance with the structure, shape and principle of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for processing simulation data of a pile foundation soil interaction model, characterized in that, include: Obtain the pile foundation contact pressure data sequence for multiple simulation conditions of the pile foundation soil interaction model, as well as the wind load data sequence corresponding to each simulation condition; For each simulation condition, based on the spectral entropy and spectral centroid of the energy spectrum of the pile foundation contact pressure data sequence, the preliminary complexity of the pile foundation contact pressure data sequence is determined. The preliminary complexity satisfies the following: ； In the formula, For the first The initial complexity of the pile foundation contact pressure data sequence for each simulation condition. and The first The spectral entropy and spectral centroid of the energy spectrum of a pile foundation contact pressure data sequence under a simulated working condition. For the first Energy spectrum of pile foundation contact pressure data sequence under simulated working conditions. For the first The energy spectrum of the pile foundation contact pressure data sequence under the simulated working condition is as follows: The energy percentage of each frequency range This represents the total number of frequency intervals. For the index of the frequency range, For the minimum normalization function, It is a logarithmic function with base 2; Based on the initial complexity and the cross-power spectral density between the pile foundation contact pressure data sequence and the corresponding wind load data sequence, the degree of distortion of the pile foundation contact pressure data sequence is determined. Based on the degree of distortion, determine the number of adaptive modes used in the variational mode decomposition algorithm; Based on the number of adaptive modes, the pile foundation contact pressure data sequence is processed using a variational mode decomposition algorithm to obtain multiple modal components; The modal component with the highest correlation to the corresponding wind load data sequence is used as the processed pile foundation contact pressure data to complete the simulation data processing of the pile foundation soil interaction model.

2. The simulation data processing method for a pile foundation soil interaction model according to claim 1, characterized in that, The acquisition of pile foundation contact pressure data sequences for multiple simulation conditions of the pile foundation-soil interaction model, and wind load data sequences corresponding to each simulation condition, includes: A pile-soil interaction model was constructed using finite element analysis software. Calculate multiple simulation conditions by inputting different combinations of operating parameters; For each simulation case, the normal contact pressure data of the pile-soil contact interface along the pile depth of all sampling points are extracted from the historical database of the pile-soil interaction model as the pile contact pressure data sequence, and the wind load time series applied to the top of the tower is extracted as the corresponding wind load data sequence.

3. The simulation data processing method for a pile foundation soil interaction model according to claim 1, characterized in that, After obtaining the pile foundation contact pressure data sequence for multiple simulation conditions of the pile foundation-soil interaction model, and the wind load data sequence corresponding to each simulation condition, the method further includes: The pile foundation contact pressure data sequence and the corresponding wind load data sequence for each simulation condition were normalized to eliminate the influence of dimensions.

4. The simulation data processing method for a pile foundation soil interaction model according to claim 1, characterized in that, The energy spectrum is obtained by performing a fast Fourier transform on the pile foundation contact pressure data sequence.

5. The simulation data processing method for a pile foundation soil interaction model according to claim 1, characterized in that, The degree of distortion satisfies: ； In the formula, For the first The degree of distortion in the pile foundation contact pressure data sequence for each simulated working condition. For the first The initial complexity of the pile foundation contact pressure data sequence for each simulation condition. For the first The cross-power spectral density between the pile foundation contact pressure data sequence and the corresponding wind load data sequence for each simulation condition. and The first The power spectral density of the pile foundation contact pressure data sequence and the corresponding wind load data sequence for each simulation condition. For the minimum normalization function, It is a natural exponential function. It is the absolute value symbol.

6. The simulation data processing method for a pile foundation soil interaction model according to claim 1, characterized in that, The number of adaptive modes satisfies: ； In the formula, For the first The number of adaptive modes for each simulation condition. This is the preset lower limit for the number of adaptive modes. This represents the number of decomposition modes in the variational mode decomposition algorithm. For the first The degree of distortion in the pile foundation contact pressure data sequence for each simulated working condition. For rounding operations, the lower limit of the number of adaptive modes. With the number of decomposition modes These are all fixed preset values ​​set according to the specific implementation situation.

7. The simulation data processing method for a pile foundation soil interaction model according to claim 1, characterized in that, The process of processing the pile foundation contact pressure data sequence using the variational mode decomposition algorithm further includes: The penalty factor is set to a value between 1500 and 2500; The time step value is set to 0~0.5; Set the convergence tolerance value to be... ~ .

8. The simulation data processing method for a pile foundation soil interaction model according to claim 1, characterized in that, The modal component with the highest correlation to the corresponding wind load data sequence is used as the processed pile foundation contact pressure data, including: Obtain the Pearson correlation coefficients between all modal components and the corresponding wind load data sequences; The modal component with the largest absolute value of the Pearson correlation coefficient was selected as the processed pile foundation contact pressure data.

9. A simulation data processing system for a pile foundation soil interaction model, characterized in that, include: A processor and a memory, the memory storing computer program instructions that, when executed by the processor, implement a simulation data processing method for a pile foundation soil interaction model according to any one of claims 1-8.

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