Fan tower structure optimization method based on finite element analysis

Abstract

The invention provides a fan tower structure optimization method based on finite element analysis, and belongs to the technical field of structure optimization. The method comprises the steps that 1, the design requirement of a target fan tower is obtained, and a three-dimensional finite element model of the target fan tower is established; 2, linear stress analysis is conducted on the three-dimensional finite element model through finite element software, and areas prone to fatigue are recognized; 3, by adjusting prestress structure parameters of the three-dimensional finite element model, iterative optimization is carried out until an area prone to fatigue reaches the aims of fatigue resistance and safety, and a first model is generated; 4, predicting the performance of the first model in a preset service life period by using a fatigue analysis method to obtain a prediction result; and 5, performing inverse optimization on the first model according to a prediction result, and adjusting model parameters of the first model to generate an optimal model. The tower structure is optimized, the tower strength is improved, and the cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of structural optimization, and in particular to a wind turbine tower structure optimization method based on finite element analysis. Background Art

[0002] As the global demand for renewable energy continues to increase, wind energy has attracted widespread attention as a clean and renewable energy form. However, existing wind power towers face many challenges in terms of structural safety, maintenance costs and land occupation; traditional wind power towers mostly use conventional steel structures, which have problems such as insufficient fatigue resistance, high maintenance costs and large floor space. At the same time, the collector line box transformer is independently set on the ground, which requires additional land acquisition and foundation construction, increasing construction costs.

[0003] Therefore, the present invention proposes a wind turbine tower structure optimization method based on finite element analysis. Summary of the invention

[0004] The present invention provides a wind turbine tower structure optimization method based on finite element analysis, which is used to establish a three-dimensional finite element model of the wind turbine tower and perform linear stress analysis to identify fatigue-prone areas, adjust prestressed structure parameters for iterative optimization, ensure that the fatigue area meets safety requirements, generate a preliminary model, perform fatigue analysis, predict the performance of the model during its service life, reversely optimize according to the prediction results, adjust the model parameters, and finally obtain the optimal wind turbine tower design, thereby effectively improving the fatigue durability and structural safety of the tower.

[0005] In one aspect, the present invention provides a method for optimizing a wind turbine tower structure based on finite element analysis, comprising: Step 1: Obtain the design requirements of the target wind turbine tower and establish a three-dimensional finite element model of the target wind turbine tower; Step 2: Perform linear stress analysis on the 3D finite element model using finite element software to identify areas prone to fatigue; Step 3: Generate the first model by adjusting the prestressed structural parameters of the three-dimensional finite element model and iteratively optimizing until the fatigue-prone area reaches the goals of fatigue resistance and safety; Step 4: Using a fatigue analysis method, predict the performance of the first model during a preset service life to obtain a prediction result; Step 5: De-optimize the first model according to the prediction results, and adjust the model parameters of the first model to generate an optimal model.

[0006] On the other hand, obtain the design requirements of the target wind turbine tower, including: Obtain the design requirements of the target wind turbine tower, including structural requirements, material requirements and environmental requirements; Generate the basic structural information of the target wind turbine tower according to the design requirements and international standards.

[0007] On the other hand, a three-dimensional finite element model of the target wind turbine tower is established, including: Build the overall structure of the tower according to the basic structural information of the target wind turbine tower; According to the design requirements, the tower section design of the tower is determined, and based on the overall structure of the tower, the hierarchical structure is refined, the connection mode and specific material requirements between the tower sections are described in detail, and the geometric modeling of the target wind turbine tower is obtained; According to the geometric complexity of the tower and the analysis requirements, the minimum unit accuracy of the mesh division is determined, the geometric modeling is placed in the mesh, the boundary conditions and peripheral equipment connections are designed, and the three-dimensional finite element model of the target wind turbine tower is generated.

[0008] On the other hand, the linear stress analysis of the three-dimensional finite element model is performed by finite element software, including: Based on the three-dimensional finite element model, the target wind turbine tower is divided into discrete small units, and the specific node information of each structural node in the small unit is obtained. The stress vector of any node of any small unit is obtained as follows: ;in, represents the stress vector at the node, represents the Young's modulus of the node material, represents the Poisson's ratio of the node material, represents the deformation matrix of the cell where the node is located, represents the node displacement vector, Represents the dot product.

[0009] On the other hand, identify areas that are prone to fatigue, including: Based on the node stress vector of the small unit and evaluating the fatigue factor of each node according to material mechanics, the fatigue life of the small unit is obtained as follows: (i) represents the fatigue life of the small unit, represents the maximum magnitude of the stress vector of the i-th node of the small unit, represents the minimum amplitude of the stress vector of the i-th node of the small unit, represents the unit material constant, represents the stress adjustment coefficient of the small unit, represents the fatigue factor of the i-th node of the small unit, represents the reference stress of the ith node of the small unit; All small units of the three-dimensional finite element model are traversed. If the fatigue life of any small unit is less than a preset life threshold, the small unit is determined to be a fatigue-prone area and a mark is added to the three-dimensional finite element model.

[0010] On the other hand, by adjusting the prestressed structural parameters of the three-dimensional finite element model, iterative optimization is performed until the fatigue-prone area reaches the goal of fatigue resistance and safety, and the first model is generated, including: According to the fatigue-prone areas, constraint conditions are established to generate fatigue damage coefficients. The convergence targets of optimized fatigue resistance and safety are obtained by combining the prestressed structural parameters of the fatigue-prone areas, and the objective function is constructed. Constructing a population, wherein the population size is the sum of the number of parameters of the prestressed structure parameters and the fatigue damage coefficient, and any individual in the population represents a set of prestressed structure parameters and fatigue damage coefficients, which serve as the gene of the individual; The fitness of any individual in the population is evaluated as: ;in, represents the fitness of the jth individual in the population, represents the fatigue damage adaptation weight, represents the stress structure adaptation weight, represents the minimum fitness of individuals in the population, represents the fatigue damage assessment function of the jth individual, represents the prestressed structure evaluation function of the jth individual; Selecting multiple individuals as parents according to a preset parent ratio of the population, generating a parent group, performing crossover on any two parents of the parent group, exchanging genes with each other during the crossover, and generating new offspring; Calculate the fitness of the new offspring and select the new parent according to the preset parent ratio; When the objective function reaches the preset convergence target, the iteration is terminated and the individual with the highest fitness is selected as the optimal solution; The first model is generated by adjusting the three-dimensional finite element model based on the prestressed structural parameters and fatigue damage coefficient under the optimal solution.

[0011] On the other hand, using the fatigue analysis method, the performance of the first model during the preset service life is predicted to obtain prediction results, including: According to the fatigue life and stress magnitude of different small units of the first model, the SN curve of any small unit is constructed; The total fatigue damage of the target wind turbine tower is obtained by accumulating the fatigue damage of all small units in the first model using the mining method combined with the SN curve: ; where DT represents the total fatigue damage, gk represents the number of load cycles under the kth working condition, represents the fatigue life of all small units under the kth working condition; like , it is determined that the first model suffers fatigue failure before the predetermined service life.

[0012] On the other hand, the first model is deoptimized according to the prediction result, and the model parameters of the first model are adjusted to generate an optimal model, including: If the number of load cycles of the first model is less than the preset number when fatigue failure occurs, the structure of the first model is determined to be unreasonable, the weak point is determined according to the fatigue life of all small units, the prestressed structural parameters and fatigue damage coefficient of the small unit are adjusted to obtain a new unit structure, and the optimal model is generated based on the adjusted new unit structure; Otherwise, the first model is determined to be reasonable and is regarded as the optimal model.

[0013] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a wind turbine tower structure optimization method based on finite element analysis, which is used to establish a three-dimensional finite element model of the wind turbine tower and perform linear stress analysis to identify fatigue-prone areas, adjust prestressed structure parameters for iterative optimization, ensure that the fatigue area meets safety requirements, generate a preliminary model, perform fatigue analysis, predict the performance of the model during its service life, reversely optimize according to the prediction results, adjust the model parameters, and finally obtain the optimal wind turbine tower design, thereby effectively improving the fatigue durability and structural safety of the tower. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0015] Figure 1 It is a flow chart of a wind turbine tower structure optimization method based on finite element analysis provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] Embodiment 1: like Figure 1 As shown, an embodiment of the present invention provides a wind turbine tower structure optimization method based on finite element analysis, comprising: Step 1: Obtain the design requirements of the target wind turbine tower and establish a three-dimensional finite element model of the target wind turbine tower; Step 2: Perform linear stress analysis on the 3D finite element model using finite element software to identify areas prone to fatigue; Step 3: Generate the first model by adjusting the prestressed structural parameters of the three-dimensional finite element model and iteratively optimizing until the fatigue-prone area reaches the goals of fatigue resistance and safety; Step 4: Using a fatigue analysis method, predict the performance of the first model during a preset service life to obtain a prediction result; Step 5: De-optimize the first model according to the prediction results, and adjust the model parameters of the first model to generate an optimal model.

[0018] In this embodiment, the target wind turbine tower refers to a tower structure specially designed for a wind turbine generator set according to design requirements and engineering needs.

[0019] In this embodiment, the design requirements refer to specific requirements formulated for the functional requirements, performance standards, technical specifications and safety standards of the target wind turbine tower, including: bearing capacity, fatigue durability, material requirements, etc.

[0020] In this embodiment, the three-dimensional finite element model is a three-dimensional digital representation of a target structure numerically simulated by a finite element method.

[0021] In this embodiment, the finite element software is a computer software tool for performing finite element analysis, and is used to simulate and analyze the behavior of physical problems such as complex structures, mechanical components, heat conduction, and electromagnetic fields.

[0022] In this embodiment, linear stress analysis is used to analyze the stress, strain and deformation of a material or structure under the action of an external force.

[0023] In this embodiment, fatigue-prone areas are those areas that are prone to experience local stress concentration and deformation under repeated loading.

[0024] In this embodiment, the prestressed structure parameters refer to the parameters intentionally applied to the structure when designing the structure, including: prestress magnitude, prestress distribution, prestress type, etc.

[0025] In this embodiment, the first model refers to a preliminary optimization model of the wind turbine tower obtained through the following process.

[0026] In this embodiment, the fatigue analysis method is an analysis technique used to evaluate the fatigue damage that may occur to a structure under multiple cyclic loading.

[0027] In this embodiment, the preset service life refers to an expected service life set by the designer based on the actual use environment and requirements of the structure during the design process of the wind turbine tower.

[0028] In this embodiment, the prediction result refers to the expected result obtained by the fatigue analysis method regarding fatigue damage, performance degradation or structural failure that may occur to the target wind turbine tower during a preset service life.

[0029] In this embodiment, model parameters refer to various numerical values ​​and variables used to define and describe tower structural characteristics, load conditions, and material behaviors during wind turbine tower design and optimization, including prestressed structural parameters, material parameters, load parameters, etc.

[0030] In this embodiment, the optimal model is the final wind turbine tower model obtained by completing multiple iterative optimization steps and post-optimization processes.

[0031] The working principle and beneficial effects of the above technical solution are: by establishing a three-dimensional finite element model of the wind turbine tower, performing linear stress and fatigue analysis, optimizing prestressed structural parameters, iterative optimization to improve fatigue resistance, and finally generating the optimal model to ensure the safety and performance of the tower during its service life.

[0032] Embodiment 2: Based on the above embodiment 1, the design requirements of the target wind turbine tower are obtained, including: Obtain the design requirements of the target wind turbine tower, including structural requirements, material requirements and environmental requirements; Generate the basic structural information of the target wind turbine tower according to the design requirements and international standards.

[0033] In this embodiment, the structural requirements include: bearing capacity, stability, fatigue resistance, etc.

[0034] In this embodiment, material requirements include: strength requirements, corrosion resistance, fatigue resistance, etc.

[0035] In this embodiment, the environmental requirements include: temperature conditions, wind speed, humidity, etc.

[0036] In this embodiment, the basic structural information includes: material, tower structure, surface treatment technology, etc.

[0037] The working principle and beneficial effects of the above technical solution are: by analyzing the design requirements of the target wind turbine tower and combining international standards to generate basic structural information, it is ensured that the tower meets the safety, reliability and performance standards on the basis of meeting the structural, material and environmental requirements, thereby optimizing the design process and improving the adaptability of the wind turbine tower.

[0038] Embodiment 3: On the basis of the above-mentioned embodiment 2, a three-dimensional finite element model of the target wind turbine tower is established, including: According to the basic structural information of the target wind turbine tower, build the overall structure of the tower; According to the design requirements, the tower section design of the tower is determined, and based on the overall structure of the tower, the hierarchical structure is refined, the connection method and specific material requirements between the tower sections are described in detail, and the geometric modeling of the target wind turbine tower is obtained; According to the geometric complexity of the tower and the analysis requirements, the minimum unit accuracy of the mesh division is determined, the geometric modeling is placed in the mesh, the boundary conditions and peripheral equipment connections are designed, and the three-dimensional finite element model of the target wind turbine tower is generated.

[0039] In this embodiment, the overall structure of the tower is the basic structure of the tower.

[0040] In this embodiment, the tower section is a segmented unit in the overall structure of the wind turbine tower, and each section represents an independent part of the tower.

[0041] In this embodiment, the hierarchical structure refers to the overall structural function of the tower, the design requirements of each tower segment and the connection method between them.

[0042] In this embodiment, the connection methods include: bolt connection, welding, riveting, etc.

[0043] In this embodiment, geometric modeling refers to the process of creating the geometric shape of an object by computer-aided design (CAD) or other modeling tools.

[0044] In this embodiment, the minimum unit refers to the smallest basic unit used for discretizing the structure during the grid division process.

[0045] In this embodiment, the grid in engineering calculation refers to dividing a complex geometric model into multiple small units or elements, thereby converting a continuous physical problem into a discrete calculation problem.

[0046] In this embodiment, the boundary conditions refer to constraints and loading conditions imposed in the model, such as displacement boundary conditions, mechanical boundary conditions, symmetric boundary conditions, etc.

[0047] The working principle and beneficial effects of the above technical solution are: by building the overall structure of the tower and refining the tower section design, clarifying the connection method and material requirements, and generating a geometric model. Through precise meshing and boundary condition design, a three-dimensional finite element model is constructed, which improves the accuracy and reliability of tower analysis and provides a solid foundation for subsequent optimization.

[0048] Embodiment 4: Based on the above embodiment 1, a linear stress analysis is performed on the three-dimensional finite element model using finite element software, including: Based on the three-dimensional finite element model, the target wind turbine tower is divided into discrete small units, and the specific node information of each structural node in the small unit is obtained. The stress vector of any node of any small unit is obtained as follows: ;in, represents the stress vector at the node, represents the Young's modulus of the node material, represents the Poisson's ratio of the node material, represents the deformation matrix of the cell where the node is located, represents the node displacement vector, Represents the dot product.

[0049] In this embodiment, the small unit refers to each small, independent computing unit obtained after dividing a large structure into multiple discrete areas.

[0050] In this embodiment, the structural node refers to a key point of each small unit in the discretized model, represents a position in the physical space, and is the place where physical quantities such as stress, strain, and displacement are calculated and stored.

[0051] In this embodiment, the specific node information includes: node coordinates, node degrees of freedom, material properties, etc.

[0052] In this embodiment, the stress vector is a physical quantity that describes the internal force state at a certain node inside the material caused by external forces, temperature changes, constraints, and other factors.

[0053] In this embodiment, Young's modulus is used to describe the stiffness of a material under an external force such as tension or compression.

[0054] In this embodiment, Poisson's ratio is a physical quantity that describes the relationship between the transverse strain and the longitudinal strain of a material when it is deformed.

[0055] The working principle and beneficial effects of the above technical solution are: by dividing the target wind turbine tower into discrete small units, obtaining the stress vector of each node, and combining Young's modulus, Poisson's ratio, deformation matrix and displacement vector for stress analysis, the accuracy of the model is improved, which helps to evaluate the mechanical properties and safety of the tower structure.

[0056] Embodiment 5: Based on the above-mentioned embodiment 4, the areas prone to fatigue are identified, including: Based on the node stress vector of the small unit and evaluating the fatigue factor of each node according to material mechanics, the fatigue life of the small unit is obtained as follows: (i) represents the fatigue life of the small unit, represents the maximum magnitude of the stress vector of the i-th node of the small unit, represents the minimum amplitude of the stress vector of the i-th node of the small unit, represents the unit material constant, represents the stress adjustment coefficient of the small unit, represents the fatigue factor of the i-th node of the small unit, represents the reference stress of the ith node of the small unit; All small units of the three-dimensional finite element model are traversed. If the fatigue life of any small unit is less than a preset life threshold, the small unit is determined to be a fatigue-prone area and a mark is added to the three-dimensional finite element model.

[0057] In this embodiment, material mechanics is a discipline that studies the deformation and stress distribution laws of solid materials under the action of external forces.

[0058] In this embodiment, the fatigue factor is a parameter measured based on the fatigue strength, stress level and stress cycle of the material.

[0059] In this embodiment, fatigue life refers to the number of load cycles that a material or structure can withstand before fatigue failure occurs under certain loading conditions.

[0060] In this embodiment, the preset life threshold refers to a specific value set in fatigue life assessment to determine whether a small unit has fatigue risk.

[0061] The working principle and beneficial effect of the above technical solution are: by evaluating the fatigue factor of each node and calculating the fatigue life of small units based on the stress amplitude, the model is traversed to identify fatigue-prone areas. By marking the fatigue areas, it helps to optimize the design and improve the durability and safety of the tower. Embodiment 6: On the basis of the above-mentioned embodiment 5, by adjusting the prestressed structural parameters of the three-dimensional finite element model, iterative optimization is performed until the fatigue-prone area reaches the goals of fatigue resistance and safety, and a first model is generated, including: According to the fatigue-prone areas, constraint conditions are established to generate fatigue damage coefficients. The convergence targets of optimized fatigue resistance and safety are obtained by combining the prestressed structural parameters of the fatigue-prone areas, and the objective function is constructed. Constructing a population, wherein the population size is the sum of the number of parameters of the prestressed structure parameters and the fatigue damage coefficient, and any individual in the population represents a set of prestressed structure parameters and fatigue damage coefficients, which serve as the gene of the individual; The fitness of any individual in the population is evaluated as: ;in, represents the fitness of the jth individual in the population, represents the fatigue damage adaptation weight, represents the stress structure adaptation weight, represents the minimum fitness of individuals in the population, represents the fatigue damage assessment function of the jth individual, represents the prestressed structure evaluation function of the jth individual; Selecting multiple individuals as parents according to a preset parent ratio of the population, generating a parent group, performing crossover on any two parents of the parent group, exchanging genes with each other during the crossover, and generating new offspring; Calculate the fitness of the new offspring and select the new parent according to the preset parent ratio; When the objective function reaches the preset convergence target, the iteration is terminated and the individual with the highest fitness is selected as the optimal solution; The first model is generated by adjusting the three-dimensional finite element model based on the prestressed structural parameters and fatigue damage coefficient under the optimal solution.

[0062] In this embodiment, the fatigue damage coefficient is a quantitative indicator for measuring the damage degree of a structure or material under cyclic load.

[0063] In this embodiment, the convergence target refers to the objective function reaching a preset optimal state through the iterative optimization process.

[0064] In this embodiment, the objective function is a function that comprehensively considers fatigue damage and structural stress, and aims to minimize fatigue damage and optimize fatigue resistance and safety of the structure.

[0065] In this embodiment, the population refers to a group of individuals (solutions) used to simulate the evolution process, and each individual represents a specific set of prestressed structural parameters and fatigue damage coefficients.

[0066] In this example, genes refer to the components of each individual in the population.

[0067] In this embodiment, fitness is an indicator used in a genetic algorithm to measure the performance of an individual in a certain problem.

[0068] In this embodiment, the preset parent ratio refers to the ratio used to select parent individuals from the current population in a genetic algorithm or an evolutionary algorithm.

[0069] In this embodiment, the parent generation refers to the individuals selected from the population for breeding the next generation.

[0070] In this embodiment, crossover is an operation that simulates the natural biological reproduction process, generating new individuals (offspring) by exchanging genetic information between two parent individuals.

[0071] In this embodiment, the new offspring refers to the next generation of individuals generated by the crossover operation.

[0072] In this embodiment, the optimal solution refers to a set of parameters that are ultimately found through iteration and selection during the optimization process, so that the value of the constructed objective function reaches a preset convergence target.

[0073] The working principle and beneficial effects of the above technical solution are: by optimizing the fatigue damage coefficient and prestressed structural parameters, combined with genetic algorithm to iteratively select the optimal solution, improve fatigue resistance and safety. By constructing the objective function and fitness evaluation, the efficiency and accuracy of design optimization are improved, which helps to extend the life of the structure.

[0074] Embodiment 7: Based on the above embodiment 1, a fatigue analysis method is used to predict the performance of the first model during a preset service life to obtain a prediction result, including: According to the fatigue life and stress magnitude of different small units of the first model, the SN curve of any small unit is constructed; The total fatigue damage of the target wind turbine tower is obtained by accumulating the fatigue damage of all small units in the first model using the mining method combined with the SN curve: ; where DT represents the total fatigue damage, gk represents the number of load cycles under the kth working condition, represents the fatigue life of all small units under the kth working condition; like , it is determined that fatigue failure occurs to the first model before the predetermined service life.

[0075] In this embodiment, the SN curve is a graphical representation used to describe the fatigue life of a material at different stress levels, and describes the number of cycles (N) that a material can withstand under different stress amplitudes (S) until fatigue failure occurs.

[0076] In this embodiment, the mining method is a method for evaluating the accumulation of fatigue damage of materials or structures under multiple load conditions. Under multiple conditions, the different load cycles borne by the structure will cause different degrees of fatigue damage. The core idea of ​​the mining method is to accumulate the damage under each load condition in proportion and finally determine the overall fatigue life of the structure or material.

[0077] In this embodiment, fatigue damage refers to gradual damage caused by repeated loading of a material or structure after multiple cycles of loading.

[0078] In this embodiment, fatigue failure refers to the phenomenon that after a period of time, when a material or structure is subjected to periodic or repeated loads, microcracks are generated, expanded and finally fractured, resulting in performance degradation or failure of the structure.

[0079] The working principle and beneficial effects of the above technical solution are: by constructing the SN curve and applying the mining method, the fatigue damage of small units under different working conditions is comprehensively considered to accurately evaluate the overall fatigue life of the wind turbine tower. It is effective to determine whether the tower will fail due to fatigue within the predetermined service life, thereby improving the structural reliability and safety.

[0080] Embodiment 8: Based on the above-mentioned embodiment 7, the first model is deoptimized according to the prediction result, and the model parameters of the first model are adjusted to generate an optimal model, including: If the number of load cycles of the first model is less than the preset number when fatigue failure occurs, the structure of the first model is determined to be unreasonable, the weak point is determined according to the fatigue life of all small units, the prestressed structural parameters and fatigue damage coefficient of the small unit are adjusted to obtain a new unit structure, and the optimal model is generated based on the adjusted new unit structure; Otherwise, the first model is determined to be reasonable and is regarded as the optimal model.

[0081] In this embodiment, the preset number refers to an upper limit of the number of periodic load cycles set during the design process.

[0082] In this embodiment, the number of load cycles refers to the number of times a material or structure is subjected to repeated loads (ie, cyclic loads) during fatigue testing or actual use.

[0083] The working principle and beneficial effects of the above technical solution are: by judging whether the number of load cycles at fatigue failure is less than the preset value, identifying the structural weak points and adjusting the prestressed structural parameters and fatigue damage coefficient, optimizing the unit structure, and finally generating the optimal model to improve the reliability and service life of the structure.

[0084] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A wind turbine tower structure optimization method based on finite element analysis, characterized in that: include: Step 1: Obtain the design requirements of the target wind turbine tower and establish a three-dimensional finite element model of the target wind turbine tower; Step 2: Perform linear stress analysis on the 3D finite element model using finite element software to identify areas prone to fatigue; Step 3: Generate the first model by adjusting the prestressed structural parameters of the three-dimensional finite element model and iteratively optimizing until the fatigue-prone area reaches the goals of fatigue resistance and safety; Step 4: Using a fatigue analysis method, predict the performance of the first model during a preset service life to obtain a prediction result; Step 5: De-optimize the first model according to the prediction results, and adjust the model parameters of the first model to generate an optimal model.

2. A wind turbine tower structure optimization method based on finite element analysis according to claim 1, characterized in that: Obtain the design requirements of the target wind turbine tower, including: Obtain the design requirements of the target wind turbine tower, including structural requirements, material requirements and environmental requirements; Generate the basic structural information of the target wind turbine tower according to the design requirements and international standards.

3. The wind turbine tower structure optimization method based on finite element analysis according to claim 2, characterized in that: Establish a 3D finite element model of the target wind turbine tower, including: Build the overall structure of the tower according to the basic structural information of the target wind turbine tower; According to the design requirements, the tower section design of the tower is determined, and based on the overall structure of the tower, the hierarchical structure is refined, the connection method and specific material requirements between the tower sections are described in detail, and the geometric modeling of the target wind turbine tower is obtained; According to the geometric complexity of the tower and the analysis requirements, the minimum unit accuracy of the mesh division is determined, the geometric modeling is placed in the mesh, the boundary conditions and peripheral equipment connections are designed, and the three-dimensional finite element model of the target wind turbine tower is generated.

4. The wind turbine tower structure optimization method based on finite element analysis according to claim 1, characterized in that: Linear stress analysis of 3D finite element models using finite element software, including: Based on the three-dimensional finite element model, the target wind turbine tower is divided into discrete small units, and the specific node information of each structural node in the small unit is obtained. The stress vector of any node of any small unit is obtained as follows: ;in, represents the stress vector at the node, represents the Young's modulus of the node material, represents the Poisson's ratio of the node material, represents the deformation matrix of the cell where the node is located, represents the node displacement vector, Represents the dot product.

5. The wind turbine tower structure optimization method based on finite element analysis according to claim 4, characterized in that: Identify areas that are prone to fatigue, including: Based on the node stress vector of the small unit and evaluating the fatigue factor of each node according to material mechanics, the fatigue life of the small unit is obtained as follows: (i) represents the fatigue life of the small unit, represents the maximum magnitude of the stress vector of the i-th node of the small unit, represents the minimum amplitude of the stress vector of the i-th node of the small unit, represents the unit material constant, represents the stress adjustment coefficient of the small unit, represents the fatigue factor of the i-th node of the small unit, represents the reference stress of the ith node of the small unit; All small units of the three-dimensional finite element model are traversed. If the fatigue life of any small unit is less than a preset life threshold, the small unit is determined to be a fatigue-prone area and a mark is added to the three-dimensional finite element model.

6. The wind turbine tower structure optimization method based on finite element analysis according to claim 5, characterized in that: The first model is generated by adjusting the prestressed structural parameters of the 3D finite element model and iteratively optimizing until the fatigue-prone area reaches the goal of fatigue resistance and safety, including: According to the fatigue-prone areas, constraint conditions are established to generate fatigue damage coefficients. The convergence targets of optimized fatigue resistance and safety are obtained by combining the prestressed structural parameters of the fatigue-prone areas, and the objective function is constructed. Constructing a population, wherein the population size is the sum of the number of parameters of the prestressed structure parameters and the fatigue damage coefficient, and any individual in the population represents a set of prestressed structure parameters and fatigue damage coefficients, which serve as the gene of the individual; The fitness of any individual in the population is evaluated as: ;in, represents the fitness of the jth individual in the population, represents the fatigue damage adaptation weight, represents the stress structure adaptation weight, represents the minimum fitness of individuals in the population, represents the fatigue damage assessment function of the jth individual, represents the prestressed structure evaluation function of the jth individual; Selecting multiple individuals as parents according to a preset parent ratio of the population, generating a parent group, performing crossover on any two parents of the parent group, exchanging genes with each other during the crossover, and generating new offspring; Calculate the fitness of the new offspring and select the new parent according to the preset parent ratio; When the objective function reaches the preset convergence target, the iteration is terminated and the individual with the highest fitness is selected as the optimal solution; The first model is generated by adjusting the three-dimensional finite element model based on the prestressed structural parameters and fatigue damage coefficient under the optimal solution.

7. The wind turbine tower structure optimization method based on finite element analysis according to claim 1, characterized in that: Using fatigue analysis methods, the performance of the first model during the preset service life is predicted to obtain prediction results, including: According to the fatigue life and stress magnitude of different small units of the first model, the SN curve of any small unit is constructed; The total fatigue damage of the target wind turbine tower is obtained by accumulating the fatigue damage of all small units in the first model using the mining method combined with the SN curve: ; where DT represents the total fatigue damage, gk represents the number of load cycles under the kth working condition, represents the fatigue life of all small units under the kth working condition; like , it is determined that the first model suffers fatigue failure before the predetermined service life.

8. The wind turbine tower structure optimization method based on finite element analysis according to claim 7, characterized in that: De-optimizing the first model according to the prediction result, adjusting the model parameters of the first model to generate an optimal model, including: If the number of load cycles of the first model is less than the preset number when fatigue failure occurs, the structure of the first model is determined to be unreasonable, the weak point is determined according to the fatigue life of all small units, the prestressed structural parameters and fatigue damage coefficient of the small unit are adjusted to obtain a new unit structure, and the optimal model is generated based on the adjusted new unit structure; Otherwise, the first model is determined to be reasonable and is regarded as the optimal model.

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