A fan tower structure optimization method based on finite element analysis

Abstract

The application provides a fan tower structure optimization method based on finite element analysis, and belongs to the technical field of structure optimization; steps include: step 1: obtaining the design requirements of the target fan tower, and establishing a three-dimensional finite element model of the target fan tower; step 2: performing linear stress analysis on the three-dimensional finite element model by using a finite element software, and identifying the area prone to fatigue; step 3: adjusting the prestressed structure parameters of the three-dimensional finite element model, and iteratively optimizing until the area prone to fatigue reaches the fatigue resistance and safety targets, and generating a first model; step 4: using a fatigue analysis method, predicting the performance of the first model during a preset service life to obtain a prediction result; and step 5: according to the prediction result, performing counter-optimization on the first model, adjusting the 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 application relates to the technical field of structure optimization, and particularly relates to a fan tower structure optimization method based on finite element analysis. BACKGROUND

[0002] With the increasing demand for renewable energy worldwide, wind energy as a clean and renewable energy form has attracted widespread attention. However, the existing wind power towers have many challenges in terms of structural safety, maintenance cost and land occupation. Traditional wind power towers mostly use conventional steel structures, which have problems such as insufficient fatigue resistance, high maintenance cost and large land occupation. At the same time, the box-type transformer of the power collection line is independently set on the ground, which requires additional land acquisition and foundation construction, increasing the construction cost.

[0003] Therefore, the present application provides a fan tower structure optimization method based on finite element analysis. SUMMARY

[0004] The present application provides a fan tower structure optimization method based on finite element analysis, which establishes a three-dimensional finite element model of the fan tower, performs linear stress analysis, identifies the fatigue-prone area, adjusts the prestressed structure parameters for iterative optimization, ensures that the fatigue area meets the safety requirements, generates a preliminary model, performs fatigue analysis, predicts the performance of the model during the service life, and adjusts the model parameters according to the prediction results for counter-optimization, and finally obtains the optimal fan tower design, effectively improving the fatigue durability and structural safety of the tower.

[0005] In one aspect, the present application provides a fan tower structure optimization method based on finite element analysis, comprising:

[0006] Step 1: Obtain the design requirements of the target fan tower, and establish a three-dimensional finite element model of the target fan tower;

[0007] Step 2: Perform linear stress analysis on the three-dimensional finite element model by using finite element software, and identify the fatigue-prone area;

[0008] Step 3: Adjust the prestressed structure parameters of the three-dimensional finite element model, and iteratively optimize until the fatigue-prone area meets the fatigue resistance and safety requirements to generate a first model;

[0009] Step 4: Use a fatigue analysis method to predict the performance of the first model during the predetermined service life to obtain a prediction result;

[0010] Step 5: Counter-optimize the first model according to the prediction result, and adjust the model parameters of the first model to generate an optimal model.

[0011] In another aspect, the design requirements of the target fan tower are obtained, comprising:

[0012] Obtaining design requirements of a target wind turbine tower, including structural requirements, material requirements and environmental requirements;

[0013] Generating basic structural information of the target wind turbine tower according to the design requirements combined with international standards.

[0014] On the other hand, a three-dimensional finite element model of the target wind turbine tower is established, including:

[0015] According to the basic structural information of the target wind turbine tower, the overall structure of the tower is built;

[0016] 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, and the connection mode between each tower section and the specific material requirements are described in detail, to obtain the geometric modeling of the target wind turbine tower;

[0017] According to the geometric complexity of the tower and the analysis requirements, the minimum unit accuracy of mesh division is determined, the geometric modeling is placed in the mesh, the boundary conditions and peripheral equipment connection are designed, and the three-dimensional finite element model of the target wind turbine tower is generated.

[0018] On the other hand, linear stress analysis is performed on the three-dimensional finite element model by finite element software, including:

[0019] 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, and the stress vector of any node of any small unit is:

[0020] ; wherein, the stress vector of the node, the Young's modulus of the node material, the Poisson's ratio of the node material, the deformation matrix of the small unit where the node is located, the node displacement vector, the dot product.

[0021] On the other hand, the area prone to fatigue is identified, including:

[0022] Based on the node stress vector of the small unit, and according to material mechanics, the fatigue factor of each node is evaluated, and the fatigue life of the small unit is:

[0023] (i); wherein, the fatigue life of the small unit, the maximum amplitude in the stress vector of the i-th node of the small unit, represents the minimum amplitude in the i-th node stress vector of the small element, represents the element material constant, represents the stress adjustment coefficient of the small element, represents the fatigue factor of the i-th node of the small element, represents the reference stress of the i-th node of the small element;

[0024] Traverse all small elements of the three-dimensional finite element model, if the fatigue life of any small element is less than the preset life threshold, determine that the small element is a fatigue-prone area and add a mark to the three-dimensional finite element model.

[0025] On the other hand, by adjusting the prestressed structure parameters of the three-dimensional finite element model, iterative optimization is performed until the fatigue-prone area reaches the target of fatigue resistance and safety, to generate a first model, including:

[0026] According to the fatigue-prone area, a constraint condition is constructed, a fatigue damage coefficient is generated, and a convergence target of optimized fatigue resistance and safety is obtained in combination with the prestressed structure parameters of the fatigue-prone area, and a target function is constructed;

[0027] A population is constructed, 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 as the genes of the individual;

[0028] The fitness of any individual in the population is evaluated as:

[0029] ; wherein, represents the fitness of the j-th individual in the population, represents the fatigue damage fitness weight, represents the stress structure fitness weight, represents the minimum fitness of the population individual, represents the fatigue damage evaluation function of the j-th individual, represents the prestressed structure evaluation function of the j-th individual;

[0030] According to the preset parent proportion of the population, a plurality of individuals are selected as parents, and a parent population is generated, and any two parents of the parent population are crossed to generate new offspring, in which the genes are exchanged with each other;

[0031] The fitness of the new offspring is calculated, and the new parents are selected according to the preset parent proportion;

[0032] When the target function reaches the preset convergence target, the iteration is terminated, and the individual with the highest fitness is selected as the optimal solution;

[0033] Based on the prestress structure parameters and the fatigue damage coefficient under the optimal solution, a three-dimensional finite element model is adjusted to generate a first model.

[0034] On the other hand, using a fatigue analysis method, the performance of the first model during a preset service life is predicted to obtain a prediction result, including:

[0035] According to the fatigue life and stress size of different small units of the first model, an S-N curve of any small unit is constructed;

[0036] Using a mine method combined with the S-N curve, the fatigue damage of all small units in the first model is accumulated to obtain a total fatigue damage of the target fan tower as:

[0037] ; wherein DT represents the total fatigue damage, gk represents the load cycle number under the kth working condition, represents the fatigue life of all small units under the kth working condition;

[0038] If , it is determined that the first model occurs fatigue failure before the predetermined service life.

[0039] On the other hand, according to the prediction result, the first model is counter-optimized, the model parameters of the first model are adjusted to generate an optimal model, including:

[0040] If the load cycle number when the first model occurs fatigue failure is less than a preset number, it is determined that the structure of the first model is unreasonable, the fatigue life of all small units is determined to determine the weak point, the prestress structure parameters and the 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;

[0041] Conversely, it is determined that the first model is reasonable, and the first model is regarded as the optimal model.

[0042] Compared with the prior art, the beneficial effects of the present application are:

[0043] The present application provides a fan tower structure optimization method based on finite element analysis, which establishes a three-dimensional finite element model of a fan tower, performs linear stress analysis, identifies an easy fatigue area, adjusts prestress structure parameters for iterative optimization, ensures that the fatigue area meets safety requirements, generates a preliminary model, performs fatigue analysis, predicts the performance of the model during the service life, counter-optimizes according to the prediction result, adjusts the model parameters, and finally obtains an optimal fan tower design, effectively improving the fatigue durability and structural safety of the tower. BRIEF DESCRIPTION OF DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings described below are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative effort based on these drawings.

[0045] Figure 1 is a flowchart of a fan tower structure optimization method based on finite element analysis provided by an embodiment of the present application. DETAILED DESCRIPTION

[0046] In order to make the objects, technical solutions and advantages of the present application clearer, the following will describe the technical solutions in the present application clearly and completely with reference to the drawings in the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort fall within the protection scope of the present application.

[0047] Embodiment 1

[0048] As shown in Figure 1 , the fan tower structure optimization method based on finite element analysis provided by an embodiment of the present application comprises:

[0049] Step 1: Obtain the design requirements of a target fan tower, and establish a three-dimensional finite element model of the target fan tower;

[0050] Step 2: Perform linear stress analysis on the three-dimensional finite element model by using a finite element software, and identify the area prone to fatigue;

[0051] Step 3: Adjust the prestressed structure parameters of the three-dimensional finite element model, and iteratively optimize until the area prone to fatigue reaches the fatigue resistance and safety targets, to generate a first model;

[0052] Step 4: Use a fatigue analysis method to predict the performance of the first model during a preset service life, to obtain a prediction result;

[0053] Step 5: Perform counter-optimization on the first model according to the prediction result, and adjust the model parameters of the first model to generate an optimal model.

[0054] In this embodiment, the target fan tower refers to a tower structure specially designed for a wind turbine generator set according to design requirements and engineering needs.

[0055] In this embodiment, design requirements refer to specific requirements established for the functional needs, performance standards, technical specifications, and safety standards of the target wind turbine tower, including: bearing capacity, fatigue durability, material requirements, etc.

[0056] In this embodiment, the three-dimensional finite element model is a three-dimensional digital representation of the target structure obtained through numerical simulation using the finite element method.

[0057] In this embodiment, the finite element software is a computer software tool used for finite element analysis, used to simulate and analyze the behavior of complex structures, mechanical components, heat conduction, electromagnetic fields, and other physical problems.

[0058] In this embodiment, linear stress analysis is used to analyze the stress, strain, and deformation of materials or structures under external forces.

[0059] In this embodiment, areas prone to fatigue are places that are likely to experience local stress concentration and deformation under repeated loads.

[0060] In this embodiment, pre-stress structure parameters refer to parameters intentionally applied to the structure during design, including: pre-stress size, pre-stress distribution, pre-stress type, etc.

[0061] In this embodiment, the first model refers to the preliminary optimized model of the wind turbine tower obtained through the following process.

[0062] In this embodiment, the fatigue analysis method is an analysis technique used to evaluate the possibility of fatigue damage to the structure under multiple cyclic loads.

[0063] In this embodiment, the preset service life refers to a desired 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.

[0064] In this embodiment, the prediction result refers to the expected result of the target wind turbine tower's possible fatigue damage, performance degradation, or structural failure during the preset service life obtained through the fatigue analysis method.

[0065] In this embodiment, model parameters refer to various numerical values and variables used to define and describe the structural characteristics, load conditions, and material behavior of the tower during the design and optimization process of the wind turbine tower, including pre-stress structure parameters, material parameters, load parameters, etc.

[0066] In this embodiment, the optimal model is the final wind turbine tower model obtained through multiple iterations of optimization and post-optimization during the design and optimization process.

[0067] The working principle and beneficial effects of the above technical solution are: by establishing a three-dimensional finite element model of the fan tower, performing linear stress and fatigue analysis, optimizing prestressed structure parameters, iterative optimization to improve fatigue resistance, and finally generating an optimal model to ensure the safety and performance of the tower within its service life.

[0068] Embodiment 2:

[0069] On the basis of the above embodiment 1, the design requirements of the target fan tower are obtained, including:

[0070] The design requirements of the target fan tower include structural requirements, material requirements, and environmental requirements.

[0071] According to the design requirements and international standards, the basic structural information of the target fan tower is generated.

[0072] In this embodiment, the structural requirements include bearing capacity, stability, fatigue resistance, etc.

[0073] In this embodiment, the material requirements include strength requirements, corrosion resistance, fatigue resistance, etc.

[0074] In this embodiment, the environmental requirements include temperature conditions, wind speed, humidity, etc.

[0075] In this embodiment, the basic structural information includes materials, tower structure, surface treatment technology, etc.

[0076] The working principle and beneficial effects of the above technical solution are: by analyzing the design requirements of the target fan tower, combining international standards to generate basic structural information, ensuring that the tower meets the requirements of structure, material and environment, and meets the standards of safety, reliability and performance, optimizing the design process and improving the adaptability of the fan tower.

[0077] Embodiment 3:

[0078] On the basis of the above embodiment 2, a three-dimensional finite element model of the target fan tower is established, including:

[0079] According to the basic structural information of the target fan tower, the overall structure of the tower is built.

[0080] According to the design requirements, the tower section design is determined, and based on the overall structure of the tower, the hierarchical structure is refined, the connection method between each tower section and the specific material requirements are described in detail, and the geometric modeling of the target fan tower is obtained.

[0081] According to the geometric complexity of the tower and the analysis requirements, the minimum unit accuracy of mesh division is determined, the geometric modeling is placed in the mesh, the boundary conditions and peripheral equipment connection are designed, and the three-dimensional finite element model of the target fan tower is generated.

[0082] In this embodiment, the tower overall structure is the basic structure of the tower.

[0083] In this embodiment, the tower segment is a segmented unit in the tower overall structure, and each segment represents an independent part of the tower.

[0084] In this embodiment, the hierarchical structure refers to the overall structure function of the tower, the design requirements of each tower segment, and the connection method between them.

[0085] In this embodiment, the connection method includes bolt connection, welding, riveting, etc.

[0086] In this embodiment, geometric modeling refers to the process of creating the geometry of an object through computer-aided design (CAD) or other modeling tools.

[0087] In this embodiment, the minimum unit refers to the smallest basic unit used for discretization of the structure in the meshing process.

[0088] In this embodiment, the mesh in engineering calculation refers to dividing a complex geometric model into a plurality of small units or elements, thereby converting a continuous physical problem into a discrete calculation problem.

[0089] In this embodiment, the boundary condition refers to the constraints and loading conditions applied in the model, such as displacement boundary conditions, mechanical boundary conditions, symmetric boundary conditions, etc.

[0090] The working principle and beneficial effects of the above technical solution are: by building the tower overall structure and refining the tower segment design, the connection method and material requirements are clear, and the geometric model is generated. Through accurate meshing and boundary condition design, a three-dimensional finite element model is constructed, which improves the accuracy and reliability of the tower analysis and provides a solid foundation for subsequent optimization.

[0091] Embodiment 4:

[0092] Based on the above embodiment 1, linear stress analysis is performed on the three-dimensional finite element model by using finite element software, including:

[0093] 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 structure node in the small unit is obtained. The stress vector of any node of any small unit is:

[0094] ; wherein, represents the stress vector of 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 small unit where the node is located, a node displacement vector, a dot product.

[0095] In this embodiment, a small unit refers to each small, independent calculation unit obtained after a large structure is divided into multiple discrete regions.

[0096] In this embodiment, a structure node refers to a key point of each small unit in a discretized model, representing a certain position in the physical space, and is a place for calculating and storing physical quantities such as stress, strain, displacement, etc.

[0097] In this embodiment, the specific node information includes node coordinates, node degrees of freedom, material properties, etc.

[0098] In this embodiment, the stress vector is a physical quantity describing the internal force state at a node in the material caused by external forces, temperature changes, constraints, etc.

[0099] In this embodiment, Young's modulus is used to describe the stiffness of the material under the action of external forces such as tension or compression.

[0100] In this embodiment, the Poisson's ratio is a physical quantity describing the relationship between the transverse strain and the longitudinal strain of the material when deformed.

[0101] 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, and the mechanical properties and safety of the tower structure are evaluated.

[0102] Embodiment 5:

[0103] On the basis of the above-mentioned embodiment 4, the area prone to fatigue is identified, including:

[0104] Based on the node stress vector of the small unit, and according to the material mechanics, the fatigue factor of each node is evaluated, and the fatigue life of the small unit is obtained as:

[0105] (i); wherein, the fatigue life of the small unit, the maximum amplitude in the stress vector of the i-th node of the small unit, the minimum amplitude in the stress vector of the i-th node of the small unit, the material constant of the unit, the stress adjustment coefficient of the small unit, the fatigue factor of the i-th node of the small unit, the reference stress of the i-th node of the small unit;

[0106] Traverse all small elements of the three-dimensional finite element model, if the fatigue life of any small element is less than the preset life threshold, determine that the small element is a fatigue-prone area and add a marker to the three-dimensional finite element model.

[0107] In this embodiment, material mechanics is a discipline that studies the deformation and stress distribution of solid materials under external forces.

[0108] In this embodiment, the fatigue factor is a parameter that measures the fatigue strength of the material, the stress level, and the way stress cycles are based.

[0109] In this embodiment, fatigue life refers to the number of load cycles a material or structure can withstand before it fails due to fatigue under certain loading conditions.

[0110] In this embodiment, the preset life threshold refers to a specific value set to determine whether a small element is at risk of fatigue in fatigue life assessment.

[0111] The working principle and beneficial effects of the above technical solution are: by evaluating the fatigue factor of each node and calculating the fatigue life of the small element based on the stress amplitude, the fatigue-prone area is identified by traversing the model. By marking the fatigue area, it helps to optimize the design and improve the durability and safety of the tower

[0112] Embodiment 6:

[0113] Based on the above embodiment 5, by adjusting the prestressed structure parameters of the three-dimensional finite element model, iteratively optimize until the fatigue-prone area reaches the fatigue resistance and safety target, generate the first model, including:

[0114] According to the fatigue-prone area, construct the constraint condition, generate the fatigue damage coefficient, combine the prestressed structure parameters of the fatigue-prone area to get the optimized fatigue resistance and safety convergence target, and construct the objective function;

[0115] Construct a population, the population size is the sum of the number of prestressed structure parameters and fatigue damage coefficients, and any individual in the population represents a set of prestressed structure parameters and fatigue damage coefficients as the individual's genes;

[0116] The fitness of any individual in the population is evaluated as:

[0117] ; wherein, indicates the fitness of the jth individual in the population, indicates the stress structure fitness weight, indicates the stress structure fitness weight, indicates the minimum fitness of the population individual, represents the fatigue damage evaluation function of the jth individual, represents the prestressed structure evaluation function of the jth individual;

[0118] select a plurality of individuals as parents according to a preset parent proportion of the population, and generate a parent population, and perform crossover on any two parents in the parent population, and exchange genes with each other in the crossover to generate new offspring;

[0119] calculate the fitness of the new offspring, and select new parents according to the preset parent proportion;

[0120] When the objective function reaches a preset convergence target, terminate the iteration, and select the individual with the highest fitness as the optimal solution;

[0121] Based on the prestressed structure parameters and the fatigue damage coefficient under the optimal solution, a first model is generated.

[0122] In this embodiment, the fatigue damage coefficient is a quantitative indicator that measures the degree of damage of a structure or material under the action of cyclic loading.

[0123] In this embodiment, the convergence target refers to the objective function reaching a preset optimal state through the iterative optimization process.

[0124] In this embodiment, the objective function is a function that comprehensively considers fatigue damage and structural stress, aiming to minimize fatigue damage and optimize the fatigue resistance and safety of the structure.

[0125] In this embodiment, the population refers to a group of individuals (solutions) used to simulate the evolutionary process, and each individual represents a specific set of prestressed structure parameters and fatigue damage coefficients.

[0126] In this embodiment, the gene refers to the component of each individual in the population.

[0127] In this embodiment, the fitness is an indicator used in genetic algorithms to measure the performance of individuals in a certain problem.

[0128] In this embodiment, the preset parent proportion refers to the proportion used to select parent individuals from the current population in genetic algorithms or evolutionary algorithms.

[0129] In this embodiment, the parent refers to an individual selected from the population for breeding the next generation.

[0130] In this embodiment, crossover is an operation that simulates the natural biological reproduction process, and generates new individuals (offspring) by exchanging gene information of two parent individuals.

[0131] In this embodiment, the new offspring refers to the next generation of individuals generated by the crossover operation.

[0132] In this embodiment, the optimal solution refers to a set of parameters ultimately found through iteration and selection in the optimization process, so that the value of the constructed objective function reaches the preset convergence target.

[0133] The working principle and beneficial effects of the above technical solution are: by optimizing the fatigue damage coefficient and the prestressed structure parameters, and combining the genetic algorithm to iteratively select the optimal solution, the fatigue resistance and safety are improved. By constructing the objective function and fitness evaluation, the efficiency and accuracy of design optimization are improved, which helps to prolong the service life of the structure.

[0134] Embodiment 7:

[0135] On the basis of the above-mentioned embodiment 1, the fatigue analysis method is used to predict the performance of the first model during the preset service life, and the prediction result includes:

[0136] According to the fatigue life and stress size of different small units of the first model, the S-N curve of any small unit is constructed;

[0137] The total fatigue damage of the target wind turbine tower is obtained by using the mine method to accumulate the fatigue damage of all small units in the first model according to the S-N curve:

[0138] ; wherein 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;

[0139] If , it is determined that the first model has fatigue failure before the predetermined service life.

[0140] In this embodiment, the S-N curve is a graphical representation used to describe the fatigue life of materials under different stress levels, which describes the number of cycles (N) that materials can withstand under different stress amplitudes (S) until fatigue failure occurs.

[0141] In this embodiment, the mine method is a method used to evaluate the fatigue damage accumulation of materials or structures under multiple load conditions. Under multiple working conditions, different load cycles borne by the structure will cause different degrees of fatigue damage, and the core idea of the mine method is to accumulate the damage under each load condition in proportion, and finally judge the overall fatigue life of the structure or material.

[0142] In this embodiment, fatigue damage refers to the gradual damage of materials or structures after experiencing multiple cyclic loading under repeated loading.

[0143] In this embodiment, fatigue failure refers to a phenomenon that a material or structure is subjected to periodic load or repeated load, and after a period of time, micro-cracks are generated, expanded and finally broken, resulting in performance degradation or failure of the structure.

[0144] The working principle and beneficial effects of the above technical solution are: by constructing the S-N curve and applying the mine method, the fatigue damage of small units under different working conditions is comprehensively considered, and the overall fatigue life of the fan tower is accurately evaluated. Effectively determine whether the tower will fail due to fatigue within the predetermined service life, improve the reliability and safety of the structure.

[0145] Embodiment 8:

[0146] On the basis of the above-mentioned embodiment 7, the first model is counter-optimized according to the prediction result, the model parameters of the first model are adjusted to generate an optimal model, comprising:

[0147] If the number of load cycles when the first model fails due to fatigue is less than the preset number, it is determined that the structure of the first model is unreasonable, the weak point is determined according to the fatigue life of all small units, and the prestress structure parameters and the fatigue damage coefficient of the small unit are adjusted to obtain a new unit structure. The optimal model is generated based on the adjusted new unit structure;

[0148] On the contrary, it is determined that the first model is reasonable, and the first model is regarded as the optimal model.

[0149] In this embodiment, the preset number refers to an upper limit of the number of periodic load cycles set during the design process.

[0150] In this embodiment, the number of load cycles refers to the number of times a material or structure is subjected to repeated load (i.e. periodic load) during fatigue testing or actual use.

[0151] The working principle and beneficial effects of the above technical solution are: by judging whether the number of load cycles when the fatigue failure occurs is less than the preset value, identifying the weak point of the structure and adjusting the prestress structure parameters and the fatigue damage coefficient, optimizing the unit structure, and finally generating the optimal model, the reliability and service life of the structure are improved.

[0152] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solution deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for optimizing a fan tower structure based on finite element analysis, characterized in that, The method comprises the following steps: 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 three-dimensional finite element model by using a finite element software, and identify the area prone to fatigue; Step 3: Adjust the prestressed structure parameters of the three-dimensional finite element model, and iteratively optimize until the area prone to fatigue meets the fatigue resistance and safety requirements to generate a first model; Step 4: Use a fatigue analysis method to predict the performance of the first model during a preset service life to obtain a prediction result; Step 5: According to the prediction result, perform counter-optimization on the first model, adjust the model parameters of the first model, and generate an optimal model; Wherein, using the fatigue analysis method to predict the performance of the first model during the preset service life to obtain the prediction result comprises: According to the fatigue life and stress size of different small units of the first model, an S-N curve of any small unit is constructed; Using the mine method combined with the S-N curve, the fatigue damage of all small units in the first model is accumulated to obtain the total fatigue damage of the target wind turbine tower as: ; where DT represents total fatigue damage, gk represents the number of load cycles at the kth operating condition, represents the fatigue life of all the small elements at the kth operating condition; If , it is determined that the first model has experienced fatigue failure before the predetermined service life. According to the prediction result, the counter-optimization is performed on the first model, the model parameters of the first model are adjusted, and the optimal model is generated, which comprises: If the load cycle number of the first model when fatigue failure occurs is less than the preset number, it is determined that the first model structure is unreasonable, the weak point is determined according to the fatigue life of all small units, the prestressed structure parameters and the 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; On the contrary, it is determined that the first model is reasonable, and the first model is regarded as the optimal model.

2. The wind turbine tower structure optimization method based on finite element analysis according to claim 1, wherein, Obtaining the design requirements of the target wind turbine tower comprises: Obtaining the design requirements of the target wind turbine tower includes structural requirements, material requirements and environmental requirements; According to the design requirements and international standards, the basic structure information of the target wind turbine tower is generated.

3. The wind turbine tower structure optimization method based on finite element analysis according to claim 2, characterized in that, Establishing a three-dimensional finite element model of the target wind turbine tower comprises: According to the basic structure information of the target wind turbine tower, the overall structure of the tower is built; According to the design requirements, the tower section design is determined, and based on the overall structure of the tower, the hierarchical structure is refined, the connection mode between each tower section and the specific material requirements are described in detail, and the geometric modeling of the target wind turbine tower is obtained; According to the geometric complexity and analysis requirements of the tower, the minimum unit accuracy of mesh division is determined, the geometric modeling is placed in the mesh, the boundary conditions and peripheral equipment connection 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, wherein, Performing linear stress analysis on the three-dimensional finite element model by using a finite element software comprises: 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 structure node in the small unit is obtained, the stress vector of any node of any small unit is obtained as: ; wherein, denotes the stress vector of the node, denotes the Young's modulus of the node material, denotes the Poisson's ratio of the node material, denotes the deformation matrix of the small element in which the node is located, denotes the node displacement vector, denotes the dot product.

5. The wind turbine tower structure optimization method based on finite element analysis according to claim 4, characterized in that, Identifying the area prone to fatigue comprises: Based on the node stress vector of the small unit, and according to the material mechanics, the fatigue factor of each node is evaluated, and the fatigue life of the small unit is obtained as: ; wherein, represents the fatigue life of the small element, represents the maximum amplitude in the stress vector of the i-th node of the small element, represents the minimum amplitude in the stress vector of the i-th node of the small element, represents the material constant of the small element, represents the stress adjustment coefficient of the small element, represents the fatigue factor of the i-th node of the small element, represents the reference stress of the i-th node of the small element; Traverse all small units of the three-dimensional finite element model, if the fatigue life of any small unit is less than a preset life threshold, it is determined that the small unit is an area prone to fatigue 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, wherein, The prestress structure parameters of the three-dimensional finite element model are adjusted, and iteration optimization is performed until the fatigue-prone area reaches the fatigue resistance and safety target to generate a first model, including: A constraint condition is constructed according to the fatigue-prone area, a fatigue damage coefficient is generated, and a convergence target of optimized fatigue resistance and safety is obtained in combination with the prestress structure parameters of the fatigue-prone area, and a target function is constructed; A population is constructed, the population size is the sum of the number of parameters of the prestress structure parameters and the fatigue damage coefficient, and any individual in the population represents a set of prestress structure parameters and fatigue damage coefficients as the genes of the individual; The fitness of any individual in the population is evaluated as: ; wherein, represents the fitness of the jth individual in the population, represents the fatigue damage fitness weight, represents the stress structure fitness weight, represents the minimum fitness of the population individual, represents the fatigue damage evaluation function of the jth individual, represents the prestress structure evaluation function of the jth individual; A plurality of individuals are selected as parents according to a preset parent proportion of the population, and a parent population is generated, any two parents of the parent population are crossed, and genes are exchanged in the crossing to generate new offspring; The fitness of the new offspring is calculated, and new parents are selected according to the preset parent proportion; When the target function reaches the preset convergence target, the iteration is terminated, and the individual with the highest fitness is selected as the optimal solution; The prestress structure parameters and the fatigue damage coefficient under the optimal solution are used to adjust the three-dimensional finite element model to generate the first model.

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