A method, system, device and storage medium for fatigue assessment of offshore wind turbines

Abstract

The present application belongs to the technical field of offshore wind turbine fatigue assessment, and particularly relates to an offshore wind turbine fatigue assessment method, system, device and storage medium. The method comprises: (1) establishing an average wind speed bin; (2) determining a significant wave height and a peak spectrum period; (3) constructing a wind wave consistency coupling environment input; (4) applying the wind wave consistency coupling environment input to an offshore wind turbine finite element model to obtain a time history response of a key part; (5) identifying a fatigue hot spot component; (6) assessing long-term fatigue damage; (7) outputting fatigue hot spot component distribution, hot spot migration results and long-term fatigue assessment results. The system, device and storage medium are all configured to implement the above method and are provided with corresponding modules or software. The present application can more truly reflect the consistency relationship of wind wave environment, and improve the rationality and stability of offshore wind turbine fatigue analysis, hot spot identification and life assessment.

Description

Technical Field

[0001] This invention belongs to the field of offshore wind turbine fatigue assessment technology, specifically relating to an offshore wind turbine fatigue assessment method, system, equipment, and storage medium. Background Technology

[0002] Offshore wind turbines are subjected to both wind and wave loads during their service life, making them prone to fatigue damage accumulation, which affects structural safety and service life. For jacket-type offshore wind turbines, the tower base, main legs, diagonal braces, and their connection areas can all become fatigue-sensitive parts, making reasonable fatigue assessments crucial.

[0003] Existing fatigue analysis methods for offshore wind turbines typically employ fixed wave parameters, meaning that the same or independently set significant wave heights, peak spectral periods, and other wave parameters are used under different wind speed conditions. While this method facilitates modeling and analysis, it fails to fully reflect the correlation between wind speed and wave conditions in the real marine environment, easily leading to biases in fatigue response, hotspot identification, and long-term damage assessment results. Furthermore, existing technologies often focus on global response analysis, such as the tower base, or only perform single-condition assessments on a small number of local components, lacking fatigue hotspot identification methods based on multi-random sample statistics. This makes it difficult to reliably identify fatigue-sensitive components in the jacket support structure and their migration patterns as environmental intensity changes.

[0004] In summary, the existing technology has the following problems: 1. Disconnect between wave input and wind speed conditions: Existing fixed wave parameter methods cannot reflect the synchronous changes in wave state under different wind speed conditions, resulting in insufficient physical consistency of wind and wave environment input.

[0005] 2. Insufficient stability in fatigue hotspot identification: Existing methods often rely on single or limited working condition analysis, making it difficult to stably identify fatigue-sensitive components under random wind and wave conditions.

[0006] 3. Lack of a unified assessment framework for global and local responses: The response characteristics of the tower base, main legs and diagonal bracing components are significantly different, but existing methods usually cannot simultaneously take into account both global and local fatigue risks.

[0007] 4. The long-term fatigue damage assessment is not systematic enough: There is a lack of unified integration between short-term fatigue intensity and the probability of long-term wind speed occurrence, making it difficult to obtain engineering indicators such as annual damage, lifespan and utilization rate.

[0008] Therefore, a technical solution is needed that can reflect the consistency relationship between wind and waves, is applicable to jacket-type offshore wind turbines, and can realize fatigue hot spot identification and long-term fatigue damage assessment. Summary of the Invention

[0009] To overcome the shortcomings of existing technologies, this invention discloses a fatigue assessment method, system, equipment, and storage medium for offshore wind turbines, which can more realistically reflect the consistency of wind and wave environments and improve the rationality and stability of fatigue analysis, hotspot identification, and life assessment of offshore wind turbines.

[0010] To achieve the above objectives, the technical solution of the present invention is as follows: A fatigue assessment method for offshore wind turbines includes the following steps: (1) establishing wind speed sub-boxes corresponding to multiple average wind speed conditions; (2) determining the corresponding significant wave height and peak spectrum period according to each wind speed sub-box; (3) generating irregular wave time histories based on the significant wave height and peak spectrum period, and constructing a wind-wave consistent coupling environment input together with the corresponding turbulent wind field; (4) constructing a finite element model of the offshore wind turbine, applying the wind-wave consistent coupling environment input to the offshore wind turbine finite element model, and obtaining the time history response of key parts; (5) identifying fatigue hotspot components based on the statistical results of multiple random samples; (6) calculating the short-term fatigue strength of the time history response, and assessing long-term fatigue damage in combination with the probability of occurrence of wind speed sub-boxes; (7) outputting the distribution of fatigue hotspot components, hotspot migration results, and long-term fatigue assessment results.

[0011] Preferably, in step (1), the wind speed sub-box covers the low wind speed condition, the condition near the rated wind speed, the high wind speed condition, and the near-cut-out wind speed condition during the operation of the offshore wind turbine; in step (3), the turbulent wind field is generated based on the Kaimal spectrum, and the irregular wave time history is generated based on the JONSWAP wave spectrum; based on the irregular wave time history, the water particle velocity and water particle acceleration are calculated by linear wave theory, and the water particle velocity and water particle acceleration are combined with the corresponding turbulent wind field to construct a wind-wave consistent coupling environment input.

[0012] Preferably, in step (4), the offshore wind turbine finite element model includes a rotor nacelle assembly, a tower, a transition section, a jacket support structure, and a pile foundation. The finite element model considers at least one of material nonlinearity, geometric nonlinearity, and soil-structure interaction. The wave load of the finite element model is calculated based on the Morison equation, and the instantaneous submerged section of the jacket structure component is determined according to the position of the wave free surface to calculate the drag force and inertial force acting on the jacket structure component. The key parts of the finite element model include the tower, the main leg components of the jacket support structure, and the diagonal bracing components of the jacket support structure.

[0013] Preferably, in step (5), the main leg components of the jacket support structure are ranked using a response index based on axial force, and the diagonal bracing components of the jacket support structure are ranked using a combined response index based on axial force and bidirectional bending moment; the combined response index of the diagonal bracing components satisfies: Where P is the axial force of the component, and M y and M z The bidirectional bending moment in the local coordinate system of the component is defined; finite element elements with the same end nodes are merged into the same physical component, and fatigue hotspot components are identified based on the high frequency of occurrence of the physical component in multiple random samples.

[0014] Preferably, in step (6), the short-term fatigue strength is calculated by rainflow counting and equivalent fatigue load, and the long-term fatigue damage is obtained by weighted accumulation of the short-term fatigue results under each wind speed sub-box and the corresponding occurrence probability; the equivalent fatigue load satisfies: , where ΔL i Let n be the response amplitude of the i-th cycle. i The corresponding number of iterations, m is the slope of the SN curve, and N is the number of iterations. eq This is the equivalent reference cycle number.

[0015] Preferably, in step (7), the long-term fatigue assessment results include at least one of annual fatigue damage, equivalent fatigue life, and fatigue utilization rate under a preset service life. By comparing the spatial distribution of fatigue hotspot components under different wind speeds, the migration path of fatigue hotspots in the offshore wind turbine support structure is determined, and the hotspot evolution results corresponding to the migration path are output.

[0016] A fatigue assessment system for offshore wind turbines includes: A. Wind speed sub-binding module, used to establish wind speed sub-bindings corresponding to multiple average wind speed conditions; B. Wave parameter determination module, used to determine the corresponding wave parameters according to each wind speed sub-box, wherein the wave parameters include at least significant wave height and peak spectral period; C. Wind-wave coupling input construction module, used to generate irregular wave time histories based on the wave parameters corresponding to each wind speed sub-box, and to construct wind-wave coupling environment input together with the corresponding turbulent wind field; D. Structural response analysis module, used to apply the wind and wave coupled environment input to the finite element model of the offshore wind turbine to obtain the time history response of key parts; E. Hotspot identification module, used to identify fatigue hotspot components in the support structure of offshore wind turbines based on time history response under multiple random samples; F. Fatigue assessment module, used to calculate short-term fatigue intensity based on the time history response, and assess long-term fatigue damage in combination with the occurrence probability corresponding to each of the wind speed sub-boxes; G. Results Output Module, used to output fatigue hotspot component distribution, hotspot migration results, and long-term fatigue assessment results.

[0017] Preferably, in the system: the wind-wave coupling input construction module includes a wind field generation unit and a wave generation unit; the wind field generation unit is used to generate a turbulent wind field based on the Kaimal spectrum; the wave generation unit is used to generate an irregular wave time history based on the JONSWAP wave spectrum; the structural response analysis module is used to call the finite element model of the offshore wind turbine, the finite element model including at least a portion of the rotor nacelle assembly, tower, transition section, jacket support structure, and pile foundation; the structural response analysis module is also used to analyze based on the Morison... The equations calculate the wave loads acting on the duct structure components and determine the instantaneous submerged section of the duct structure components based on the wave free surface. The hot spot identification module is used to sort the components based on the axial force response index of the main leg components and the combined response index of the diagonal bracing components, and identify fatigue hot spot components based on the statistical results of multiple random samples. The fatigue assessment module is used to perform rainflow counting and equivalent fatigue load calculation on the time history response, and to weight and accumulate the short-term fatigue results under each wind speed sub-box with the corresponding occurrence probability to obtain the long-term fatigue damage results. The long-term fatigue assessment results output by the result output module include at least one of annual fatigue damage, equivalent fatigue life, and fatigue utilization rate under the preset service life.

[0018] An electronic device includes a processor and a memory, the memory storing a computer program that, when executed by the processor, implements the method as described in any one of claims 1 to 6.

[0019] A computer-readable storage medium having a computer program stored thereon, which, when executed by a computer processor, implements the method as described in any one of claims 1 to 6.

[0020] The beneficial effects of the fatigue assessment method, system, equipment, and storage medium for offshore wind turbines of this invention are as follows: (1) It can construct wind and wave coupling inputs that are more in line with actual sea conditions based on the consistency relationship between wind speed and wave parameters, thereby improving the physical rationality of environmental inputs; (2) It can improve the stability of fatigue hotspot identification and reduce the randomness of single working condition results through multiple random sample statistics; (3) It can simultaneously take into account the global response of the tower base and the local component response of the main leg and diagonal brace, so as to achieve a unified assessment of the fatigue risk of key parts; (4) It can complete the integrated assessment of short-term fatigue strength and long-term fatigue damage, and output engineering indicators such as annual fatigue damage, equivalent life, and utilization rate. (5) It can identify the migration path of fatigue hotspots as wind speed changes, providing a basis for structural optimization design and operation and maintenance decisions of jacket-type offshore wind turbines. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the overall process of the method of the present invention; Figure 2 A schematic diagram showing the correspondence between average wind speed bins and wave parameters; Figure 3 A schematic diagram of the finite element model and key response locations of an offshore wind turbine; Figure 4 A schematic diagram of the fatigue hotspot component identification process; Figure 5 This is a schematic diagram of the long-term fatigue damage assessment process. Detailed Implementation

[0022] The following description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0023] Example 1: A fatigue assessment method for offshore wind turbines includes the following steps.

[0024] Step (1) Establishing average wind speed sub-boxes: The wind speed sub-boxes cover low wind speed conditions, near rated wind speed conditions, high wind speed conditions, and near-cut-off wind speed conditions during the operation of offshore wind turbines. Specifically, multiple average wind speed sub-boxes are constructed based on the operating range of the offshore wind turbine to be analyzed and the wind environment conditions of the target sea area. The average wind speed sub-boxes are used to characterize the wind environment intensity under different operating stages. In this embodiment, six average wind speed levels are selected as analysis conditions, namely 8 m / s, 10 m / s, 11.4 m / s, 16 m / s, 20 m / s, and 24 m / s. Among them, 11.4 m / s corresponds to the near-rated wind speed condition, and 24 m / s corresponds to the near-cut-off wind speed condition.

[0025] Step (2) Construct wind and wave consistent sea state parameters, that is, determine the corresponding significant wave height and peak spectral period according to each wind speed sub-box: For each average wind speed sub-box, determine the corresponding significant wave height H. s and peak spectral period T p This allows the wave state to change synchronously with changes in wind speed and operating conditions. The H... s and T p It can be determined from field observation data, empirical formulas, long-term sea state statistics, or joint wind and wave distribution models. As long as a correspondence between "mean wind speed - significant wave height - peak spectral period" can be established, it is acceptable.

[0026] Step (3) Generating the wind-wave coupled environment input: For each average wind speed sub-box, the Kaimal spectrum is used to generate the corresponding turbulent wind field time history; the JONSWAP wave spectrum is used to generate the irregular wave time history corresponding to the wind speed condition; then the two are combined to form the wind-wave coupled environment input, that is, based on the irregular wave time history, the water particle velocity and water particle acceleration are calculated by linear wave theory, and the wind-wave consistent coupled environment input is constructed based on the water particle velocity and water particle acceleration and the corresponding turbulent wind field. In this embodiment, the wave free surface time history can be obtained by random phase superposition method, and the water particle velocity and water particle acceleration are further calculated based on linear wave theory.

[0027] Step (4) Establishing a finite element analysis model: Establishing a finite element model of the offshore wind turbine. The finite element model includes the rotor nacelle assembly, tower, transition section, jacket support structure, and pile foundation. As a preferred option: (01) The tower, jacket main legs, diagonal braces, and blades are simulated using beam elements; (02) The mass of the nacelle, hub, and blades is applied using concentrated mass or equivalent mass; (03) Material nonlinearity, geometric nonlinearity, and soil-structure interaction are incorporated into the model; (04) The foundation soil is modeled using the Winkler foundation model, and pile-soil interaction is simulated using py, tz, and qz springs.

[0028] Step (5) Applying wind-wave coupled loads and obtaining time-history responses: The wind-wave coupled environment is input into the finite element model to obtain the time-history responses of key components such as the tower, main legs, and diagonal braces. In this embodiment, wave loads are calculated using the Morison equation. For each moment, the instantaneous submerged section of the duct structure component is determined based on the free surface position, and then the drag force and inertial force are calculated based on the water particle velocity and acceleration, and applied to the corresponding components. Simultaneously, wind loads are applied using a combination of distributed application along the tower body and equivalent thrust application at the rotor position.

[0029] Step (6) Establish key response indicators: Extract key response quantities for offshore wind turbines, including tower base bending moment, axial force of main leg components, and combined internal forces of bracing components. For main leg components, a control response indicator based on axial force is used; for bracing components, a combined response indicator based on axial force and bidirectional bending moment is used. Where P is the axial force of the component, and M y and M z The bending moment is bidirectional in the local coordinate system of the component.

[0030] Step (7) Identify fatigue hotspot components and migration paths: For each average wind speed condition and each random sample, sort the main leg components and diagonal bracing components according to their response indices to select a set of high-response components. To reduce the influence of the finite element discretization method, elements with the same end nodes can be merged into the same physical component, and the frequency of each physical component entering the high-response set is counted under multiple random samples. Components with higher frequencies are identified as fatigue hotspot components; by comparing the spatial distribution of hotspot components under different wind speed conditions, the hotspot migration path can be determined.

[0031] Step (8) Perform short-term fatigue strength assessment: Count rainflows based on the time history response and calculate the equivalent fatigue load DEL: , where ΔL i Let n be the response amplitude of the i-th cycle. i The corresponding number of iterations, m is the slope of the SN curve, and N is the number of iterations. eq This is the equivalent reference cycle number.

[0032] Step (9) Perform long-term fatigue damage assessment: Combine the probability of occurrence of each wind speed condition, weight and accumulate the short-term fatigue results to obtain the long-term fatigue damage results. Preferably, the Weibull distribution is used to describe the probability of occurrence of the average wind speed, and the following are outputs: annual fatigue damage; equivalent fatigue life; fatigue utilization rate under the preset service life; fatigue risk statistical indicators.

[0033] Step (10) Output evaluation results: The final output should include at least the following: wind and wave consistency environment input parameters; key response statistics of tower base, main leg and diagonal bracing components; fatigue hotspot components and their spatial distribution; hotspot migration path; DEL of each key response quantity; annual fatigue damage, equivalent fatigue life and fatigue utilization rate.

[0034] Example 2: A fatigue assessment system for offshore wind turbines includes: A. Wind speed sub-binding module, used to establish wind speed sub-bindings corresponding to multiple average wind speed conditions; B. Wave parameter determination module, used to determine the corresponding wave parameters according to each wind speed sub-box, wherein the wave parameters include at least significant wave height and peak spectral period; C. Wind-wave coupling input construction module, used to generate irregular wave time histories based on the wave parameters corresponding to each wind speed sub-box, and to construct wind-wave coupling environment input together with the corresponding turbulent wind field; D. Structural response analysis module, used to apply the wind and wave coupled environment input to the finite element model of the offshore wind turbine to obtain the time history response of key parts; E. Hotspot identification module, used to identify fatigue hotspot components in the support structure of offshore wind turbines based on time history response under multiple random samples; F. Fatigue assessment module, used to calculate short-term fatigue intensity based on the time history response, and assess long-term fatigue damage in combination with the occurrence probability corresponding to each of the wind speed sub-boxes; G. Results Output Module, used to output fatigue hotspot component distribution, hotspot migration results, and long-term fatigue assessment results.

[0035] In the system described above: the wind-wave coupling input construction module includes a wind field generation unit and a wave generation unit; the wind field generation unit is used to generate turbulent wind fields based on the Kaimal spectrum; the wave generation unit is used to generate irregular wave time histories based on the JONSWAP wave spectrum; the structural response analysis module is used to call the finite element model of the offshore wind turbine, the finite element model including at least a portion of the rotor nacelle assembly, tower, transition section, jacket support structure, and pile foundation; the structural response analysis module is also used to analyze based on the Morison... The equations calculate the wave loads acting on the duct structure components and determine the instantaneous submerged section of the duct structure components based on the wave free surface. The hot spot identification module is used to sort the components based on the axial force response index of the main leg components and the combined response index of the diagonal bracing components, and identify fatigue hot spot components based on the statistical results of multiple random samples. The fatigue assessment module is used to perform rainflow counting and equivalent fatigue load calculation on the time history response, and to weight and accumulate the short-term fatigue results under each wind speed sub-box with the corresponding occurrence probability to obtain the long-term fatigue damage results. The long-term fatigue assessment results output by the result output module include at least one of annual fatigue damage, equivalent fatigue life, and fatigue utilization rate under the preset service life.

[0036] Each module can be deployed in software on a server, engineering computing platform, or offshore wind turbine evaluation terminal. It can also interact with a finite element solver to achieve environmental input construction, time history response analysis, hotspot identification, and long-term fatigue assessment.

[0037] Example 3: This embodiment provides an electronic device, including a processor and a memory. The memory stores a computer program, which, when executed by the processor, implements a fatigue assessment method for offshore wind turbines as described in the preceding embodiment.

[0038] Example 4: This embodiment also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements a method for fatigue assessment of offshore wind turbines as described in the foregoing embodiment.

[0039] Working principle of the invention: 1. This invention determines wave parameters synchronously based on average wind speed conditions, so that the wave state changes with wind speed, overcoming the problem of insufficient environmental input consistency in the traditional fixed-wave method.

[0040] 2. This invention identifies fatigue hotspot components based on the high frequency of response under multiple random samples, and can reduce the randomness of single working condition results.

[0041] 3. A differentiated response discrimination mechanism for main legs and diagonal braces is proposed: different response indices are constructed for main legs and diagonal braces respectively to improve the pertinence of fatigue hot spot identification under different component types.

[0042] 4. Propose a hotspot migration identification mechanism: This invention can identify the hotspot migration path by the change in the spatial distribution of hotspots under different wind speed conditions, thereby reflecting the impact of environmental intensity changes on fatigue-sensitive areas of the supporting structure.

[0043] 5. Establish an integrated assessment framework for short-term fatigue intensity and long-term fatigue damage: This invention organically combines DEL, wind speed probability weighting, annual damage, equivalent life and utilization rate to improve the systematic nature of long-term fatigue assessment.

Claims

1. A fatigue assessment method for offshore wind turbines, characterized in that, Includes the following steps: (1) Establish wind speed sub-boxes corresponding to multiple average wind speed conditions; (2) Determine the corresponding significant wave height and peak spectrum period according to each wind speed sub-box; (3) Generate irregular wave time histories based on the significant wave height and peak spectrum period, and construct a wind-wave consistent coupling environment input together with the corresponding turbulent wind field; (4) Construct a finite element model of offshore wind turbine, apply the wind-wave consistent coupling environment input to the offshore wind turbine finite element model, and obtain the time history response of key parts; the key parts of the finite element model include the main leg components of the tower and jacket support structure, and the diagonal bracing components of the jacket support structure; (5) Identify fatigue hotspot components based on the statistical results of multiple random samples; (6) Perform short-term fatigue strength calculation on the time history response, and assess long-term fatigue damage in combination with the probability of occurrence of wind speed sub-boxes; (7) Output the distribution of fatigue hotspot components, hotspot migration results and long-term fatigue assessment results.

2. The fatigue assessment method for offshore wind turbines as described in claim 1, characterized in that, In step (1), the wind speed sub-box covers the low wind speed condition, the condition near the rated wind speed, the high wind speed condition, and the near-cut-out wind speed condition during the operation of the offshore wind turbine; in step (3), the turbulent wind field is generated based on the Kaimal spectrum, and the irregular wave time history is generated based on the JONSWAP wave spectrum; based on the irregular wave time history, the water particle velocity and water particle acceleration are calculated by linear wave theory, and the water particle velocity and water particle acceleration are combined with the corresponding turbulent wind field to construct a wind-wave consistent coupling environment input.

3. The fatigue assessment method for offshore wind turbines as described in claim 2, characterized in that, In step (4), the offshore wind turbine finite element model includes a rotor nacelle assembly, a tower, a transition section, a jacket support structure, and a pile foundation. The finite element model considers at least one of material nonlinearity, geometric nonlinearity, and soil-structure interaction. The wave load of the finite element model is calculated based on the Morison equation, and the instantaneous submerged section of the jacket structure component is determined according to the position of the wave free surface, so as to calculate the drag force and inertial force acting on the jacket structure component.

4. The fatigue assessment method for offshore wind turbines as described in claim 3, characterized in that, In step (5), the main leg components of the jacket support structure are ranked using a response index based on axial force, and the diagonal bracing components of the jacket support structure are ranked using a combined response index based on axial force and bidirectional bending moment; the combined response index of the diagonal bracing components satisfies: Where P is the axial force of the component, and M y and M z The bidirectional bending moment in the local coordinate system of the component is defined; finite element elements with the same end nodes are merged into the same physical component, and fatigue hotspot components are identified based on the high frequency of occurrence of the physical component in multiple random samples.

5. The fatigue assessment method for offshore wind turbines as described in claim 4, characterized in that, In step (6), the short-term fatigue strength is calculated using rainflow counting and equivalent fatigue load, and the long-term fatigue damage is obtained by weighted accumulation of the short-term fatigue results under each wind speed sub-box and the corresponding occurrence probability; the equivalent fatigue load satisfies: , where ΔL i Let n be the response amplitude of the i-th cycle. i The corresponding number of iterations, m is the slope of the SN curve, and N is the number of iterations. eq This is the equivalent reference cycle number.

6. The fatigue assessment method for offshore wind turbines as described in claim 5, characterized in that, In step (7), the long-term fatigue assessment results include at least one of annual fatigue damage, equivalent fatigue life, and fatigue utilization rate under the preset service life. By comparing the spatial distribution of fatigue hotspot components under different wind speeds, the migration path of fatigue hotspots in the offshore wind turbine support structure is determined, and the hotspot evolution results corresponding to the migration path are output.

7. A fatigue assessment system for offshore wind turbines, characterized in that, The system is used to implement the method of any one of claims 1-6, comprising: A. Wind speed sub-binding module, used to establish wind speed sub-bindings corresponding to multiple average wind speed conditions; B. Wave parameter determination module, used to determine the corresponding wave parameters according to each wind speed sub-box, wherein the wave parameters include at least significant wave height and peak spectral period; C. Wind-wave coupling input construction module, used to generate irregular wave time histories based on the wave parameters corresponding to each wind speed sub-box, and to construct wind-wave coupling environment input together with the corresponding turbulent wind field; D. Structural response analysis module, used to apply the wind and wave coupled environment input to the finite element model of the offshore wind turbine to obtain the time history response of key parts; E. Hotspot identification module, used to identify fatigue hotspot components in the support structure of offshore wind turbines based on time history response under multiple random samples; F. Fatigue assessment module, used to calculate short-term fatigue intensity based on the time history response, and assess long-term fatigue damage in combination with the occurrence probability corresponding to each of the wind speed sub-boxes; G. Results Output Module, used to output fatigue hotspot component distribution, hotspot migration results, and long-term fatigue assessment results.

8. The offshore wind turbine fatigue assessment system as described in claim 7, characterized in that, In the system described above: the wind-wave coupling input construction module includes a wind field generation unit and a wave generation unit; the wind field generation unit is used to generate a turbulent wind field based on the Kaimal spectrum; the wave generation unit is used to generate an irregular wave time history based on the JONSWAP wave spectrum; the structural response analysis module is used to call the finite element model of the offshore wind turbine, the finite element model including at least a part of the rotor nacelle assembly, tower, transition section, jacket support structure, and pile foundation; the structural response analysis module is also used to calculate the wave load acting on the jacket structure components based on the Morison equation, and to determine the instantaneous submerged section of the jacket structure components based on the wave free surface; the hot spot identification module is used to sort the components based on the axial force response index of the main leg components and the combined response index of the diagonal bracing components, and to identify fatigue hot spot components based on the statistical results of multiple random samples; The fatigue assessment module is used to count rainflows and calculate equivalent fatigue loads on the time history response, and to weight and accumulate the short-term fatigue results under each wind speed sub-box with the corresponding occurrence probability to obtain the long-term fatigue damage results. The long-term fatigue assessment results output by the result output module include at least one of annual fatigue damage, equivalent fatigue life, and fatigue utilization rate under a preset service life.

9. An electronic device, characterized in that, It includes a processor and a memory, wherein the memory stores a computer program that, when executed by the processor, implements the method as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a computer's processor, implements the method as described in any one of claims 1 to 6.

Images