Fatigue life calculation method for floating wind turbine foundation structure under multi-field coupling

Abstract

This invention provides a method for calculating the fatigue life of floating wind turbine foundation structures under multi-field coupling, belonging to the field of wind turbine structure fatigue life calculation technology. This invention establishes a corrosion attenuation model to quantitatively describe the changes in coating corrosion depth with time and environmental parameters, reflecting the corrosion behavior of mooring lines in complex marine environments. Based on historical sea state data decomposition and time-series analysis, accurate environmental load time-series inputs are obtained. Using finite element simulation, combined with rainflow counting and fatigue cumulative damage theory, a first fatigue life without considering corrosion effects is derived. Then, a correction factor is constructed based on the corrosion effect of the mooring line to correct the first fatigue life, resulting in a second fatigue life considering corrosion effects. This effectively reflects the impact of corrosion on the fatigue life of the mooring line, reduces the bias in corrosion effect estimation in traditional methods, and improves the accuracy and reliability of fatigue life prediction for floating wind turbine foundation structures.

Description

Technical Field

[0001] This invention relates to the field of fatigue life calculation technology for wind turbine structures, specifically a method for calculating the fatigue life of floating wind turbine foundation structures under multi-field coupling. Background Technology

[0002] With the rapid development of the offshore wind power industry, the fatigue life of the foundation structure of floating wind turbines, as key technological equipment adapted to deep-sea areas, has become a core issue for ensuring operational safety and economy. Floating wind turbine mooring systems are exposed to complex and variable marine environments for extended periods, subject to the combined effects of various environmental factors such as temperature, salinity, and oxygen content, leading to corrosion and degradation of mooring line materials, which in turn affects their fatigue performance. However, existing fatigue life assessment methods often neglect or simply address corrosion effects and fail to fully incorporate the multi-field coupling effects of environmental parameters, resulting in significant uncertainties and biases in fatigue life prediction.

[0003] In the prior art, CN113283125A discloses a fatigue analysis method for an inner turret mooring system based on measured data, relating to the field of mooring system design and safety assessment. This method includes data acquisition, fatigue analysis, and updating the assessment results of the inner turret mooring system based on fatigue damage calculations. It effectively utilizes detection information collected by location monitoring technology, underwater maintenance technology, and environmental monitoring technology to establish a database for storing monitoring data. Furthermore, it updates the assessment results of the inner turret mooring system using summarized formulas and algorithms, thereby accurately calculating the remaining lifespan of the inner turret mooring system. However, while this method can perform lifespan analysis of the mooring line, it relies on empirical formulas and static load interpolation, failing to consider the impact of corrosion on lifespan, resulting in limited accuracy and applicability of fatigue life prediction.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a method for calculating the fatigue life of floating wind turbine foundation structures under multi-field coupling, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for calculating the fatigue life of floating wind turbine foundation structures under multi-field coupling, the specific steps of which include:

[0008] S1: Collect environmental parameters of the sea area where the floating wind turbine is located, construct several saline environments with different environmental parameters using orthogonal experimental methods, set up mooring lines in each saline environment to conduct accelerated corrosion tests, and generate the acceleration ratio of the test in time at the same time.

[0009] S2: Collect coating parameters of the mooring line as the test time changes, combine the acceleration ratio and test time to obtain the actual service time of the mooring line, generate the influence factors of service time and environmental parameters on coating parameters, and construct a corrosion decay model based on it to calculate the coating parameters under any combination of service time and environmental parameters.

[0010] S3: Collect historical sea state parameters of the sea area, decompose the historical sea state parameters into long-term uniform components and short-term random components, and perform time series analysis on the two using different models before coupling them to obtain the time series sea state parameters of the sea area.

[0011] S4: Establish a three-dimensional model of the floating wind turbine and perform finite element analysis. Use the time-series sea state parameters as the load input of the model. Solve the time-series stress parameters of each mooring line on the floating wind turbine based on the structural dynamics equation. Combine the rainflow counting method and SN fatigue curve to generate the first fatigue life of each mooring line.

[0012] S5: Based on the environmental parameters of the sea area, the first fatigue life, and the corrosion decay model, the coating parameters under the corresponding state of the mooring line are obtained. Then, the first fatigue life is corrected and the second fatigue life is generated to complete the fatigue life calculation of the floating wind turbine foundation structure.

[0013] Preferably, the environmental parameters include ambient temperature, salinity, and oxygen content, and the coating parameter is the maximum corrosion depth;

[0014] When conducting accelerated corrosion tests on mooring lines, an electrochemical acceleration method is used to accelerate the corrosion process. The specific logic of the corrosion test is as follows:

[0015] The environmental parameters related to the corrosion of the mooring line coating were determined, and based on the types of environmental parameters and the preset level values, several sets of brine environments were configured together with the corresponding orthogonal experimental tables. At the same time, a set of brine environments with the same environmental parameters as the sea area was configured as a reference group.

[0016] The mooring line was used as the working electrode, and together with the auxiliary and reference electrodes, it was immersed in the corresponding brine environment. A constant potential polarization method was used to accelerate the corrosion process, with the open circuit potential set between 0.2V and 0.5V and the current density set at 1mA / cm². 2 ~5mA / cm 2 between;

[0017] The mooring line is periodically removed for microscopic morphology inspection, and the corrosion depth of all corroded areas is measured. The maximum value is then designated as the maximum corrosion depth.

[0018] Preferably, the actual service time of the mooring line is defined as the product of the test time and the acceleration ratio. The logic for determining the acceleration ratio of the accelerated corrosion test is as follows:

[0019] Mooring lines that have been operating in the sea for a predetermined period of time were collected, and their surface micromorphology was inspected to obtain the total area and average corrosion depth of all corrosion areas. These two were then designated as reference corrosion area and reference corrosion depth, respectively.

[0020] For the reference group in the accelerated corrosion test, the total area and average corrosion depth of all corrosion areas of its mooring line are measured periodically, and the two are compared with the reference corrosion area and reference corrosion depth respectively until the preset similarity conditions are met. The predetermined time is divided by the test time when the reference group meets the similarity conditions to obtain the acceleration ratio.

[0021] The similarity conditions are: the relative error between the total area of ​​all corroded areas of the mooring line in the reference group and the reference corrosion area, and the relative error between the average corrosion depth and the reference corrosion depth are all not higher than 10%.

[0022] Preferably, the corrosion attenuation model is constructed based on the Logistic differential equation and satisfies the nonlinear differential equation form. Specifically, a corrosion factor is added as an exponential term to the right side of the Logistic differential equation, and then multiplied by the influence factors of service time and environmental parameters on coating parameters, wherein:

[0023] The impact factor was obtained by fitting the data using multiple regression or machine learning methods.

[0024] The Logistic differential equation converges to the preset limit corrosion depth.

[0025] Preferably, the sea state parameters are wave loads and wind loads, and the logic for generating time-series sea state parameters in step S3 is as follows:

[0026] S301: Perform a fast Fourier transform on historical sea state data to convert it into a frequency domain signal;

[0027] S302: Construct a low-pass filter based on the sea area cycle, and use it to decompose the frequency domain signal into low-frequency component spectrum and high-frequency component spectrum;

[0028] S303: Perform inverse Fourier transform on the low-frequency component spectrum and the high-frequency component spectrum respectively to obtain the long-term uniform component and the short-term random component, which are used to reflect the long-term trend caused by seasonal changes in the sea area and the short-term trend caused by environmental changes, respectively.

[0029] S304: Seasonal ARIMA and ARMA models are used to fit the long-term uniform component and short-term random component in time series, respectively. The fitting results are then superimposed and output as the time series sea state parameters of the sea area.

[0030] Preferably, step S4 includes:

[0031] S401: Establish a three-dimensional model of the floating wind turbine, and define the material properties, boundary conditions, and connection relationship between the wind turbine body and the mooring line.

[0032] S402: Using the time-series sea state parameters as the load input of the model, the structural dynamics equations are solved using the numerical integration method to obtain the equivalent stress of each mooring line on the floating wind turbine, and then arranged in time order to obtain the time-series stress parameters.

[0033] S403: The time-series stress parameters are divided into cycles using the rainflow counting method to obtain several sets of stress cycles with different stress amplitudes and the corresponding actual number of cycles. The two are then combined with the SN fatigue curve of the mooring line, and the first fatigue life of each mooring line is calculated using the Miners linear cumulative damage method.

[0034] Preferably, the calculation logic for the first fatigue life is as follows:

[0035] Based on the SN fatigue curves of the mooring line and the stress amplitude under each set of stress cycles, the maximum number of cycles corresponding to each set of stress cycles is obtained.

[0036] The cumulative damage caused by all stress cycles is calculated based on the Miners linear cumulative damage method. When the cumulative damage equals 1, the mooring line is considered to have suffered fatigue failure. The first fatigue life is the ratio of the acquisition time corresponding to the time series sea state parameters to the cumulative damage.

[0037] Preferably, the logic for generating the second fatigue life is as follows:

[0038] The first fatigue life is taken as the theoretical maximum service time. The maximum service time and the environmental parameters of the sea area are substituted into the corrosion decay model to obtain the coating parameters of the mooring line under the maximum service time.

[0039] A correction factor is constructed based on the coating parameters. The correction factor is a piecewise function, and the function value decreases monotonically with respect to the coating parameters, satisfying the following:

[0040] When the coating parameters are below the critical value, the piecewise function is in exponential form, with the base term being the natural logarithm and the exponent term including the ratio of the coating parameters to the ultimate corrosion depth.

[0041] When the coating parameters are not lower than the critical value, the piecewise function is in the form of a power function, with the base term including the ratio of the coating parameters to the limit corrosion depth and the exponent term being a control coefficient greater than zero.

[0042] The first fatigue life is multiplied by a correction factor to obtain the second fatigue life, which reflects the impact of marine corrosion on the theoretical maximum service time of the mooring line.

[0043] Preferably, the critical value of the piecewise function is set between 0.7 and 0.8 times the limit corrosion depth.

[0044] Compared with the prior art, the beneficial effects of the present invention are:

[0045] This invention establishes a corrosion attenuation model reflecting the corrosion behavior of mooring lines in complex marine environments by collecting multi-dimensional environmental parameters and combining electrochemical accelerated corrosion tests and orthogonal experimental design. This model quantitatively describes the changes in coating corrosion depth with time and environmental parameters. Based on historical sea state data decomposition and time-series analysis, accurate environmental load time-series inputs are obtained. The time-series stress of the mooring line is calculated through finite element structural dynamics simulation. Combining the rainflow counting method and fatigue cumulative damage theory, a first fatigue life without considering corrosion is derived. Furthermore, a correction factor is constructed using the ratio of corrosion depth to the ultimate corrosion depth to correct the first fatigue life, resulting in a second fatigue life considering corrosion. This method effectively reflects the impact of environmental corrosion on the fatigue life of mooring lines, improves the accuracy and reliability of fatigue life prediction for floating wind turbine foundation structures, and reduces the bias in corrosion impact estimation in traditional methods. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the overall method flow of the present invention;

[0047] Figure 2 This is a flowchart illustrating step S3 in this invention;

[0048] Figure 3 This is a flowchart illustrating step S4 in this invention. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0050] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0051] Example:

[0052] Please see Figures 1-3 The present invention provides a technical solution:

[0053] A method for calculating the fatigue life of a floating wind turbine foundation structure under multi-field coupling, characterized by the following specific steps:

[0054] S1: Collect environmental parameters of the sea area where the floating wind turbine is located, construct several saline environments with different environmental parameters using orthogonal experimental methods, set up mooring lines in each saline environment to conduct accelerated corrosion tests, and simultaneously generate the acceleration ratio of the test in time.

[0055] Environmental parameters include ambient temperature, salinity, and oxygen content; coating parameters include maximum corrosion depth.

[0056] When conducting accelerated corrosion tests on mooring lines, an electrochemical acceleration method is used to accelerate the corrosion process. The specific logic of the corrosion test is as follows:

[0057] The environmental parameters related to the corrosion of the mooring line coating were determined. Based on the types of environmental parameters and the preset level values, several sets of saline environments were configured together with the corresponding orthogonal experimental tables. At the same time, a set of saline environments with the same environmental parameters as the sea area was configured as a reference group. Since the environmental parameters and coating parameters of the reference group are similar to the actual working conditions of the mooring line, they can also be used as a reference for subsequent model optimization training.

[0058] The mooring line was used as the working electrode, and together with the auxiliary and reference electrodes, it was immersed in the corresponding brine environment. A constant potential polarization method was used to accelerate the corrosion process, with the open circuit potential set between 0.2V and 0.5V and the current density set at 1mA / cm². 2 ~5mA / cm 2 between;

[0059] The mooring line is periodically removed for microscopic morphology inspection, and the corrosion depth of all corroded areas is measured. The maximum value is then designated as the maximum corrosion depth.

[0060] When identifying environmental parameters related to the corrosion of mooring line coatings, in addition to general factors such as ambient temperature, salinity, and oxygen content, more detailed environmental parameters can be selected based on the coating material, such as pH value, chloride ion concentration, and sulfate concentration. Several level values ​​are set for each environmental parameter; for example, ambient temperature can be set to 5℃, 10℃, and 15℃, and salinity to 10%, 15%, and 20%. The number of groups and step sizes for each parameter level can be determined according to specific engineering requirements. More groups and shorter step sizes result in more complex experiments, larger data volumes, and more accurate calculation results. After determining the types and level values ​​of the environmental parameters, a suitable orthogonal array (such as L9 or L16) can be selected to combine the environmental parameters into a limited number of test groups for accelerated corrosion testing.

[0061] Electrochemical acceleration during the experiment is performed to increase the electrochemical reaction rate on the mooring line surface, thereby shortening the experimental cycle. The reference electrode is used to stabilize the circuit and is often a saturated calomel electrode or a silver or silver chloride electrode. The auxiliary electrode is used to close the circuit and is usually made of inert materials (such as platinum sheets).

[0062] Using orthogonal experimental design to create combinations of environmental parameters can significantly reduce the number of experiments and costs. Furthermore, it can capture the influence of multiple environmental parameters on the corrosion of mooring line coatings, greatly improving the representativeness and scientific rigor of the data. Moreover, employing a constant potential polarization method to accelerate the experiment not only ensures stability and controllability but also significantly shortens the experimental time, improving the efficiency of the entire process.

[0063] The logic for determining the acceleration ratio of the accelerated corrosion test is as follows:

[0064] Mooring lines on floating wind turbines that have operated in the sea area were collected, and their surface micromorphology was inspected to obtain the total area and average corrosion depth of all corrosion areas. These two values ​​were then designated as reference corrosion area and reference corrosion depth, respectively.

[0065] For the reference group in the accelerated corrosion test, the total area and average corrosion depth of all corrosion areas of its mooring line are measured periodically, and the two are compared with the reference corrosion area and reference corrosion depth, respectively.

[0066] If the relative error between the total area, average corrosion depth and reference corrosion area and reference corrosion depth of all corroded areas of the mooring line in the reference group is not higher than 10%, it is considered that the corrosion state of the mooring line in the reference group is similar to that of the mooring line that has been used in the sea. The acceleration ratio is the ratio of the service time of the latter in the sea to the test time of the former in the accelerated corrosion test.

[0067] As can be seen from the above logic, the acceleration ratio refers to the timescale magnification of the accelerated corrosion test relative to the actual service corrosion process in the sea area. It is used to map the accelerated test results to the actual service duration, thereby ensuring temporal consistency in subsequent data analysis. By comparing the mooring lines in the reference group with those that have actually been in service in the sea area, the corrosion states of the two can be compared intuitively and comprehensively, avoiding misjudgments of the acceleration effect of the test. Furthermore, it is understandable that after verifying the acceleration effect of the test and completing the data analysis, even if it is later necessary to set up the floating wind turbine in other sea areas, it is not necessary to conduct the test again; the results of this test can be reused.

[0068] S2: Collect coating parameters of the mooring line as the test time changes, combine the acceleration ratio and test time to obtain the actual service time of the mooring line, generate the influence factors of service time and environmental parameters on coating parameters, and construct a corrosion attenuation model based on it to calculate the coating parameters under any combination of service time and environmental parameters.

[0069] The corrosion attenuation model is constructed based on the Logistic differential equation and satisfies the nonlinear differential equation form. Specifically, a corrosion factor is added as an exponential term to the right-hand side of the Logistic differential equation, and then multiplied by the influence factors of service time and environmental parameters on coating parameters, where:

[0070] The impact factor was obtained by fitting the data using multiple regression or machine learning methods.

[0071] The Logistic differential equation converges to the preset limit corrosion depth.

[0072] Understandably, during the corrosion process, a dense oxide film or corrosion product layer (i.e., passivation film) is formed on the mooring line. This film can partially prevent further erosion by the corrosive medium, and the corrosion reaction rate gradually slows down, causing the corrosion depth to approach saturation. The ultimate corrosion depth represents the saturation value of the mooring line during the corrosion process. This value can be measured in accelerated corrosion tests. For example, if the rate of change of the maximum corrosion depth is less than 5% in two consecutive tests (the specific value can be adjusted according to expert experience), the corrosion process can be considered to be approaching saturation, and the maximum corrosion depth at this point is defined as the ultimate corrosion depth.

[0073] Specifically, the functional expression of the corrosion attenuation model is:

[0074]

[0075] In the formula Indicates the service life as Maximum corrosion depth at that time Indicates service time. The corrosion factor is used to adjust the steepness of the Logistic differential equation. When it is 1, it is the standard Logistic differential equation. When it is greater than 1, the corrosion rate is considered to decrease faster in the corrosion process, and it is close to linear in the early stage, but it slows down rapidly when it approaches saturation, showing a stronger "passivation" or "passivation layer" effect. When it is less than 1, the corrosion rate is considered to decrease more slowly, the corrosion process is longer, the corrosion persistence is stronger, and the passivation effect is weaker. Its value is usually set between 0.5 and 3, and the specific value is determined by expert experience. Indicates the service life as The vector representation of the environmental parameters at that time, i.e.:

[0076]

[0077] in These represent the service life as follows: The ambient temperature, salinity, and oxygen content at that time The base corrosion rate is obtained by fitting experimental data. The functional expression representing the impact factor. This indicates the limiting corrosion rate.

[0078] As can be seen from the model, its variation curve is similar to the Logistic growth curve, that is, the maximum corrosion depth in the early stage increases almost linearly with the service time, while in the middle and late stages, due to factors such as passivation layer, coating damage limit, and physical space limitation, the corrosion rate gradually decreases and eventually approaches the limit value.

[0079] Understandably, since data acquisition in practical engineering applications is generally done in a discrete manner, discretizing the functional expression of the corrosion attenuation model is more applicable. The discretized corrosion attenuation model is expressed as follows:

[0080]

[0081] In the formula The time interval for data acquisition is used to collect the maximum corrosion depth obtained in the accelerated corrosion test, along with the corresponding service time and environmental parameter combination, as data samples. Then, multiple regression or machine learning methods are used to fit the data. If the number of data samples is small (e.g., less than 100 sets), multiple regression can be used. If the number of data samples is large (e.g., more than 100 sets), machine learning algorithms such as support vector regression, random forest, and neural networks can be used. The specific method used can be adjusted based on expert experience or engineering needs. After fitting, methods such as the coefficient of determination and residual analysis can be used to test the goodness of fit and generalization ability of the model. Specifically, if using the coefficient of determination method, a coefficient of determination greater than 0.8 indicates a good model fit. If using residual analysis, the Shapiro-Wilk test needs to be performed on the residuals to determine whether they are approximately normally distributed. If they are randomly distributed near zero with no obvious trend or periodicity, the model is considered to have a good fit.

[0082] As for the impact factor, its functional expression can be set as:

[0083]

[0084] In the formula ~ The parameters of the model to be fitted are... , , This indicates the various environmental parameters under the reference state, and the corresponding data can be obtained from the reference group in the experiment.

[0085] As can be seen from the functional expression of the influencing factors, they are constructed based on the principle of electrochemical corrosion. Specifically, increased temperature accelerates the corrosion reaction, and the reaction rate often increases exponentially with temperature, which conforms to the Arrhenius relationship in electrochemical reactions. Moreover, higher salinity and higher electrolyte concentration enhance corrosivity, and increased oxygen concentration leads to a stronger cathodic reaction, which in turn increases the corrosion rate. Therefore, these environmental parameters are all approximated by power functions.

[0086] In this step, by constructing a corrosion attenuation model, the physical process of rapid initial growth and eventual saturation of mooring lines under seawater corrosion can be well represented. This model can accurately reflect the nonlinear characteristics of the maximum corrosion depth as environmental parameters and service time change, thereby greatly improving the overall realism and interpretability of the scheme.

[0087] S3: Collect historical sea state parameters of the sea area, decompose the historical sea state parameters into long-term uniform components and short-term random components, and perform time series analysis on the two using different models before coupling them to obtain the time series sea state parameters of the sea area.

[0088] The sea state parameters are wave loads and wind loads. The logic for generating time-series sea state parameters in step S3 is as follows:

[0089] S301: Perform a Fast Fourier Transform (FFT) on the historical sea state data to convert it into a frequency domain signal. The expression is as follows:

[0090]

[0091] In the formula Represents frequency domain signals, Indicates signal frequency. Represents historical sea state parameters. Indicates Fast Fourier Transform;

[0092] S302: Construct a low-pass filter based on the sea area cycle, and use it to decompose the frequency domain signal into low-frequency component spectrum and high-frequency component spectrum. The low-pass filter is represented as follows:

[0093]

[0094] In the formula Indicates a low-pass filter. This indicates the cutoff frequency, which can be set according to the sea area cycle. Assuming the historical sea state parameters are sampled once a day for a total duration of 2 years, to separate the long-term uniform component of each month from the short-term random component of each day, the cutoff frequency can be set to 1 / 30.

[0095] The spectrum of the low-frequency components after decomposition and high-frequency component spectrum They are represented as follows:

[0096]

[0097]

[0098] S303: Perform inverse Fourier transforms on the low-frequency and high-frequency component spectra respectively to obtain the long-term uniform component. and short-term random components These are used to reflect the long-term trend caused by seasonal changes in the sea area and the short-term trend caused by environmental changes, respectively. Their expressions are as follows:

[0099]

[0100]

[0101] S304: Seasonal ARIMA and ARMA models are used to fit the long-term uniform component and short-term random component in time series, respectively. The fitting results are then superimposed and output as the time series sea state parameters of the sea area.

[0102] The reason for using these two models for time series fitting is that long-term uniform components often exhibit obvious periodicity (such as annual and monthly variations) and seasonality. Such signals are best modeled using seasonal ARIMA (i.e., SARIMA), which can effectively capture their periodicity and seasonality. On the other hand, short-term random components are mostly high-frequency disturbances without obvious periodicity, so they are more suitable for fitting using the traditional ARMA model.

[0103] Understandably, sea state parameters exhibit both relatively gentle periodic variations such as seasonal changes and climate trends, as well as rapid and irregular changes such as daily fluctuations, extreme weather, and random disturbances. Direct time-series analysis would struggle to capture the dynamic characteristics of all time scales, leading to reduced model accuracy. By using FFT and low-pass filtering to divide the original historical sea state parameters into components at two different time scales (long and short), the physical mechanisms can be better explained, and the actual marine environment can be more accurately reconstructed, thereby improving the accuracy of subsequent calculations of mooring line fatigue life.

[0104] S4: A three-dimensional model of the floating wind turbine is established and finite element analysis is performed. The time-series sea state parameters are used as the load input of the model. The time-series stress parameters of each mooring line on the floating wind turbine are obtained by solving the structural dynamics equation. The first fatigue life of each mooring line is generated by combining the rainflow counting method and SN fatigue curve.

[0105] Step S4 includes:

[0106] S401: Establish a three-dimensional model of the floating wind turbine, and define the material properties, boundary conditions, and connection relationship between the wind turbine body and the mooring line.

[0107] S402: Using the time-series sea state parameters as the load input of the model, the structural dynamics equations are solved using the numerical integration method to obtain the equivalent stress of each mooring line on the floating wind turbine, and then arranged in time order to obtain the time-series stress parameters.

[0108] S403: The time-series stress parameters are divided into cycles using the rainflow counting method to obtain several sets of stress cycles with different stress amplitudes and the corresponding actual number of cycles. The two are then combined with the SN fatigue curve of the mooring line, and the first fatigue life of each mooring line is calculated using the Miners linear cumulative damage method.

[0109] The calculation logic for the first fatigue life is as follows:

[0110] Based on the SN fatigue curves of the mooring line and the stress amplitude under each set of stress cycles, the maximum number of cycles corresponding to each set of stress cycles is obtained.

[0111] The cumulative damage caused by all stress cycles is calculated based on the Miners linear cumulative damage method. When the cumulative damage equals 1, the mooring line is considered to have suffered fatigue failure. The first fatigue life is the ratio of the acquisition time corresponding to the time series sea state parameters to the cumulative damage.

[0112] Since rainflow counting is a classic stress cycle extraction method, its specific extraction process will not be elaborated further. Each extracted stress cycle corresponds to a stress amplitude. By consulting the SN fatigue curve of the mooring line (usually available in the product manual), the maximum number of cycles at that stress amplitude can be obtained. When using the Miners linear cumulative damage method to calculate the cumulative damage caused by all stress cycles, the calculation formula is as follows:

[0113]

[0114] In the formula Indicates cumulative damage. , They represent the first time. The actual number of cycles (obtained by rainflow counting method) and the maximum number of cycles (obtained by SN fatigue curve) under the group stress amplitude, with subscripts. The index representing the stress amplitude group is also equivalent to the index representing the stress cycle group. This indicates the total number of stress cycle groups.

[0115] Since the first fatigue life is the ratio of the acquisition time corresponding to the time series sea state parameters to the cumulative damage, its actual physical meaning is the theoretical life of the mooring line of the floating wind turbine when it is in service in the sea, without considering the effect of corrosion.

[0116] In this step, by using historical sea state parameters as load inputs in the simulation analysis, the complex dynamic characteristics of marine loads and their impact on structural stress can be captured, thereby better reflecting changes in environmental loads in the sea area and enabling more accurate fatigue life assessment.

[0117] S5: Based on the environmental parameters of the sea area, the first fatigue life, and the corrosion decay model, the coating parameters under the corresponding state of the mooring line are obtained. Then, the first fatigue life is corrected and the second fatigue life is generated to complete the fatigue life calculation of the floating wind turbine foundation structure.

[0118] The logic for generating the second fatigue life is as follows:

[0119] The first fatigue life is taken as the theoretical maximum service time. The maximum service time and the environmental parameters of the sea area are substituted into the corrosion decay model to obtain the coating parameters of the mooring line under the maximum service time.

[0120] A correction factor is constructed based on coating parameters. The correction factor is a piecewise function, and the function value decreases monotonically with respect to the coating parameters. The critical value of the piecewise function is set between 0.7 and 0.8 times the limit corrosion depth, and satisfies the following:

[0121] When the coating parameters are below the critical value, the piecewise function is in exponential form, with the base term being the natural logarithm and the exponent term including the ratio of the coating parameters to the ultimate corrosion depth.

[0122] When the coating parameters are not lower than the critical value, the piecewise function is in the form of a power function, with the base term including the ratio of the coating parameters to the limit corrosion depth and the exponent term being a control coefficient greater than zero.

[0123] The first fatigue life is multiplied by a correction factor to obtain the second fatigue life, which reflects the impact of marine corrosion on the theoretical maximum service time of the mooring line.

[0124] The piecewise function expression for the correction factor is:

[0125]

[0126] In the formula Indicates the correction factor. , Both represent empirical parameters greater than 0, generally taken between 0.5 and 2 and 0.8 and 3 respectively. The piecewise function needs to be smoothly connected at the critical value, meaning the function value and first derivative are continuous at that point. This requires satisfying the following equation:

[0127]

[0128] This indicates the maximum corrosion depth when the line reaches its first fatigue life. Indicates the first fatigue life. This represents the ratio of the coating parameter (i.e., the maximum corrosion depth) to the limiting corrosion depth, and its value ranges from 0 to 1. Take a value between 0.7 and 0.8.

[0129] As can be seen from the piecewise function expression, when the maximum corrosion depth is below the critical value, although the maximum corrosion depth increases approximately linearly with service time, it can still provide good protection for the mooring line. Therefore, its impact on fatigue life is small, which is consistent with the characteristic of the exponential function in the piecewise function changing slowly in the early stage. However, when the maximum corrosion depth exceeds the critical value, the coating of the mooring line is considered to have failed significantly, and its protective effect on the mooring line is greatly limited. Therefore, its impact on fatigue life also increases sharply, that is, accelerated deterioration occurs.

[0130] Second fatigue life The calculation formula is:

[0131]

[0132] Understandably, floating wind turbines are connected to the seabed anchoring system via mooring lines. The mooring lines bear the loads of the marine environment (waves, wind, hydrodynamics, etc.), maintaining the floating stability and positional constraint of the turbine. Their integrity directly determines the overall stability and safety of the turbine foundation. For floating wind turbines, although the foundation structure of the turbine itself (floating pontoons, pile foundations, etc.) bears the overall mechanical response, fatigue accumulation is usually slower than that of the mooring lines. The mooring lines are most affected by dynamic loads, especially the alternating stresses caused by waves and wind, resulting in rapid fatigue damage accumulation. Once the mooring lines experience fatigue fracture, the turbine will lose its constraint, causing positional drift or excessive movement, leading to overload or even damage to the foundation structure. Therefore, the fatigue life of the mooring lines can be approximated as the safe lower limit of the fatigue life of the floating wind turbine foundation structure.

[0133] The primary function of the mooring line coating is to prevent or mitigate direct contact between the mooring line's substrate and seawater. The maximum corrosion depth reflects the severity of coating damage. The more severe the coating damage, the larger the exposed area of ​​the metal substrate, making fatigue crack initiation and propagation more likely, thus leading to a shortened fatigue life. The calculation of the first fatigue life ignores corrosion factors and represents the maximum fatigue life under ideal conditions. However, corrosion is unavoidable in real-world environments, and corrosion damage effectively reduces the material's fatigue performance. Therefore, a correction factor is introduced to reflect this life-shortening effect. In other words, by introducing a correction factor caused by corrosion, the calculated second fatigue life is equivalent to the actual effective fatigue life of the mooring line after considering the impact of marine corrosion. This second fatigue life is closer to actual service conditions than the first fatigue life, thus significantly improving the accuracy of fatigue life calculations for floating wind turbines.

[0134] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0135] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0136] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0137] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for calculating the fatigue life of a floating wind turbine foundation structure under multi-field coupling, characterized in that, The specific steps include: S1: Collect environmental parameters of the sea area where the floating wind turbine is located, construct several saline environments with different environmental parameters using orthogonal experimental methods, set up mooring lines in each saline environment to conduct accelerated corrosion tests, and generate the acceleration ratio of the test in time at the same time. S2: Collect coating parameters of the mooring line as the test time changes, combine the acceleration ratio and test time to obtain the actual service time of the mooring line, generate the influence factors of service time and environmental parameters on coating parameters, and construct a corrosion decay model based on it to calculate the coating parameters under any combination of service time and environmental parameters. The functional expression of the corrosion attenuation model is: In the formula Indicates the service life as Maximum corrosion depth at that time Indicates service time. Indicates corrosion factor, Indicates the service life as Vector representation of environmental parameters at time, Indicates the basic corrosion rate. The functional expression representing the impact factor. Indicates the limiting corrosion rate; S3: Collect historical sea state parameters of the sea area, decompose the historical sea state parameters into long-term uniform components and short-term random components, and perform time series analysis on the two using different models before coupling them to obtain the time series sea state parameters of the sea area. S4: Establish a three-dimensional model of the floating wind turbine and perform finite element analysis. Use the time-series sea state parameters as the load input of the model. Solve the time-series stress parameters of each mooring line on the floating wind turbine based on the structural dynamics equation. Combine the rainflow counting method and SN fatigue curve to generate the first fatigue life of each mooring line. S5: Based on the environmental parameters of the sea area, the first fatigue life, and the corrosion decay model, the coating parameters under the corresponding state of the mooring line are obtained. Then, the first fatigue life is corrected and the second fatigue life is generated to complete the fatigue life calculation of the floating wind turbine foundation structure.

2. The method for calculating the fatigue life of a floating wind turbine foundation structure under multi-field coupling as described in claim 1, characterized in that: The environmental parameters include ambient temperature, salinity, and oxygen content, and the coating parameter is the maximum corrosion depth; When conducting accelerated corrosion tests on mooring lines, an electrochemical acceleration method is used to accelerate the corrosion process. The specific logic of the corrosion test is as follows: The environmental parameters related to the corrosion of the mooring line coating were determined, and based on the types of environmental parameters and the preset level values, several sets of brine environments were configured together with the corresponding orthogonal experimental tables. At the same time, a set of brine environments with the same environmental parameters as the sea area was configured as a reference group. The mooring line was used as the working electrode and immersed in the corresponding brine environment along with the auxiliary and reference electrodes. A constant potential polarization method was used to accelerate the corrosion process, with the open circuit potential set between 0.2V and 0.5V and the current density set at 1mA / cm². 2 ~5mA / cm 2 between; Periodically remove the mooring line and perform microscopic morphology inspection on its surface. Measure the corrosion depth of all corroded areas on the mooring line and mark the maximum value as the maximum corrosion depth.

3. The method for calculating the fatigue life of a floating wind turbine foundation structure under multi-field coupling as described in claim 2, characterized in that: The actual service time of the mooring line is defined as the product of the test time and the acceleration ratio. The logic for determining the acceleration ratio of the accelerated corrosion test is as follows: Mooring lines that have been operating in the sea for a predetermined period of time were collected, and their surface micromorphology was inspected to obtain the total area and average corrosion depth of all corrosion areas. These two were then designated as reference corrosion area and reference corrosion depth, respectively. For the reference group in the accelerated corrosion test, the total area and average corrosion depth of all corrosion areas of its mooring line are measured periodically, and the two are compared with the reference corrosion area and reference corrosion depth respectively until the preset similarity conditions are met. The predetermined time is divided by the test time when the reference group meets the similarity conditions to obtain the acceleration ratio. The similarity conditions are: the relative error between the total area of ​​all corroded areas of the mooring line in the reference group and the reference corrosion area, and the relative error between the average corrosion depth and the reference corrosion depth are all not higher than 10%.

4. The method for calculating the fatigue life of a floating wind turbine foundation structure under multi-field coupling as described in claim 2, characterized in that: The corrosion attenuation model is constructed based on the Logistic differential equation and satisfies the nonlinear differential equation form. Specifically, a corrosion factor is added as an exponential term to the right side of the Logistic differential equation, and then multiplied by the influence factors of service time and environmental parameters on coating parameters, where: The impact factor was obtained by fitting the data using multiple regression or machine learning methods. The Logistic differential equation converges to the preset limit corrosion depth.

5. The method for calculating the fatigue life of a floating wind turbine foundation structure under multi-field coupling as described in claim 1, characterized in that: The sea state parameters are wave loads and wind loads. The logic for generating time-series sea state parameters in step S3 is as follows: S301: Perform a fast Fourier transform on historical sea state data to convert it into a frequency domain signal; S302: Construct a low-pass filter based on the sea area cycle, and use it to decompose the frequency domain signal into low-frequency component spectrum and high-frequency component spectrum; S303: Perform inverse Fourier transform on the low-frequency component spectrum and the high-frequency component spectrum respectively to obtain the long-term uniform component and the short-term random component, which are used to reflect the long-term trend caused by seasonal changes in the sea area and the short-term trend caused by environmental changes, respectively. S304: Seasonal ARIMA and ARMA models are used to fit the long-term uniform component and short-term random component in time series, respectively. The fitting results are then superimposed and output as the time series sea state parameters of the sea area.

6. The method for calculating the fatigue life of a floating wind turbine foundation structure under multi-field coupling as described in claim 1, characterized in that: Step S4 includes: S401: Establish a three-dimensional model of the floating wind turbine, and define the material properties, boundary conditions, and connection relationship between the wind turbine body and the mooring line. S402: Using the time-series sea state parameters as the load input of the three-dimensional model, the structural dynamics equations are solved using the numerical integration method to obtain the equivalent stress of each mooring line on the floating wind turbine, and these stresses are arranged in chronological order to obtain the time-series stress parameters. S403: The time-series stress parameters are divided into cycles using the rainflow counting method to obtain several sets of stress cycles with different stress amplitudes and the corresponding actual number of cycles. The two are then combined with the SN fatigue curve of the mooring line, and the first fatigue life of each mooring line is calculated using the Miners linear cumulative damage method.

7. The method for calculating the fatigue life of a floating wind turbine foundation structure under multi-field coupling as described in claim 6, characterized in that: The calculation logic for the first fatigue life is as follows: Based on the SN fatigue curves of the mooring line and the stress amplitude under each set of stress cycles, the maximum number of cycles corresponding to each set of stress cycles is obtained. The cumulative damage caused by all stress cycles is calculated based on the Miners linear cumulative damage method. When the cumulative damage equals 1, the mooring line is considered to have suffered fatigue failure. The first fatigue life is the ratio of the acquisition time corresponding to the time series sea state parameters to the cumulative damage.

8. The method for calculating the fatigue life of a floating wind turbine foundation structure under multi-field coupling as described in claim 4, characterized in that: The logic for generating the second fatigue life is as follows: The first fatigue life is taken as the theoretical maximum service time. The maximum service time and the environmental parameters of the sea area are substituted into the corrosion decay model to obtain the coating parameters of the mooring line under the maximum service time. A correction factor is constructed based on the coating parameters. The correction factor is a piecewise function, and the function value decreases monotonically with respect to the coating parameters, satisfying the following: When the coating parameters are below the critical value, the piecewise function is in exponential form, with the base term being the natural logarithm and the exponent term including the ratio of the coating parameters to the ultimate corrosion depth. When the coating parameters are not lower than the critical value, the piecewise function is in the form of a power function, with the base term including the ratio of the coating parameters to the limit corrosion depth and the exponent term being a control coefficient greater than zero. The first fatigue life is multiplied by a correction factor to obtain the second fatigue life, which reflects the impact of marine corrosion on the theoretical maximum service time of the mooring line.

9. The method for calculating the fatigue life of a floating wind turbine foundation structure under multi-field coupling as described in claim 8, characterized in that: The critical value of the piecewise function is set between 0.7 and 0.8 times the limit corrosion depth.

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