A method and system for generating a fan model

Abstract

The present invention relates to the technical field of computer-aided design, and in particular to a method and system for generating a fan model. The method comprises the following steps: obtaining basic fan design parameters and fan constraint conditions and performing fan model simulation generation and aerodynamic simulation to generate aerodynamic simulation fields corresponding to different fan models; performing blade dynamic curvature and airflow vibration evaluation and analysis on the aerodynamic simulation fields corresponding to different fan models, and performing fan airflow efficiency calculation at the same time to obtain fan air flow efficiency corresponding to different fan models; performing operation acoustic noise evaluation and analysis and performance curve simulation analysis on the corresponding fan three-dimensional model to generate airflow efficiency-noise performance curves corresponding to different fan models; and generating a fan optimization model by obtaining the corresponding fan constraint optimization target and performing sequential energy efficiency ratio optimization design. The present invention can improve the design effect and efficiency of the fan model.

Description

Technical Field

[0001] The present invention relates to the technical field of computer-aided design, and in particular to a method and system for generating a fan model. Background Art

[0002] In recent years, fan model generation methods that combine computational fluid dynamics (CFD), optimization algorithms and artificial intelligence technology have gradually become a research hotspot. These emerging methods can quickly generate fan models with optimal performance under multiple design objectives and constraints through automated modeling, performance simulation and optimization. This method can automatically generate fan models that meet performance requirements by combining computational fluid dynamics (CFD), multi-objective optimization algorithms and automated design tools, and quickly obtain the optimal fan design that meets specific application requirements by comprehensively analyzing and optimizing multiple performances such as the fan's aerodynamic characteristics, structural strength, and noise level. However, the existing fan model generation methods mainly rely on traditional manual design or computer-aided design (CAD) technology. Although manual design has certain flexibility in creativity and appearance design, it cannot effectively perform complex fluid dynamics analysis due to its reliance on experience. Although computer-aided design (CAD) technology can provide more accurate design models through digital means, it is usually only applicable to established design schemes and lacks flexible automated modeling capabilities, thereby reducing the design efficiency of fan models. Summary of the invention

[0003] Based on this, it is necessary for the present invention to provide a method and system for generating a fan model to solve at least one of the above technical problems.

[0004] To achieve the above object, a method for generating a fan model includes the following steps:

[0005] Step S1: Obtaining basic design parameters and fan constraints of the fan, wherein the basic design parameters of the fan include the number of blades, blade length and rotation angle, and the fan constraints include wind speed range, power requirement and noise requirement; performing fan model simulation generation according to the basic design parameters of the fan and the fan constraints, and generating corresponding three-dimensional fan models under different design parameters and constraints;

[0006] Step S2: performing aerodynamic simulation on the corresponding three-dimensional fan models under different design parameters and constraints to generate aerodynamic simulation fields corresponding to different fan models; performing blade dynamic curvature and airflow vibration evaluation and analysis on the aerodynamic simulation fields corresponding to different fan models to obtain blade dynamic curvature and blade airflow vibration frequency corresponding to different fan models; performing fan airflow efficiency calculation on the corresponding aerodynamic simulation fields based on the blade dynamic curvature and blade airflow vibration frequency corresponding to different fan models to obtain fan air flow efficiency corresponding to different fan models;

[0007] Step S3: performing an operation acoustic noise evaluation analysis on the corresponding three-dimensional fan models under different design parameters and constraint conditions to obtain the fan operation acoustic noise levels corresponding to different fan models; performing a performance curve simulation analysis based on the fan air flow efficiency and the fan operation acoustic noise levels corresponding to different fan models to generate airflow efficiency-noise performance curves corresponding to different fan models;

[0008] Step S4: Obtain the corresponding fan constraint optimization target through the corresponding fan three-dimensional model under different design parameters and constraint conditions, and perform timing energy efficiency ratio optimization design on the corresponding fan three-dimensional model based on the fan constraint optimization target corresponding to different fan models and the airflow efficiency-noise performance curve to generate a fan optimization model.

[0009] Further, step S1 includes the following steps:

[0010] Step S11: obtaining basic design parameters and fan constraints of the fan through a graphical interface input, wherein the basic design parameters of the fan include the number of blades, blade length and rotation angle, and the fan constraints include wind speed range, power requirement and noise requirement;

[0011] Step S12: performing fan simulation combination design according to the basic fan design parameters and the fan constraint conditions to generate different fan design parameter and constraint condition simulation combinations;

[0012] Step S13: Perform fan model simulation generation according to different fan design parameters and constraint condition simulation combinations to generate corresponding fan three-dimensional models under different design parameters and constraint conditions.

[0013] Further, step S2 includes the following steps:

[0014] Step S21: performing aerodynamic simulation on the corresponding three-dimensional fan models under different design parameters and constraint conditions to generate aerodynamic simulation fields corresponding to different fan models;

[0015] Step S22: performing airflow field grid division on the aerodynamic simulation fields corresponding to different fan models to obtain air flow field discretization grids corresponding to different fan models;

[0016] Step S23: Based on the air flow field discretization grids corresponding to different fan models, the corresponding three-dimensional fan models are evaluated and analyzed for the dynamic curvature of the fan blades and the airflow vibration frequency of the fan blades, so as to obtain the dynamic curvature of the fan blades and the airflow vibration frequency of the fan blades corresponding to the different fan models;

[0017] Step S24: Calculate the fan airflow efficiency of the corresponding aerodynamic simulation field based on the dynamic curvature of the fan blades and the airflow vibration frequency of the fan blades corresponding to different fan models to obtain the fan air flow efficiency corresponding to different fan models.

[0018] Further, step S23 includes the following steps:

[0019] Step S231: performing fan blade airflow pressure distribution analysis on the air flow field discretization grids corresponding to different fan models to obtain fan blade airflow pressure distribution of the air flow field grids corresponding to different fan models;

[0020] Step S232: analyzing the air flow velocity and wind pressure action of the air flow field grids corresponding to the fan models according to the fan blade air flow pressure distribution of the air flow field grids corresponding to the different fan models, so as to obtain the fan blade air flow velocity and wind pressure action of the air flow field grids corresponding to the different fan models;

[0021] Step S233: performing a blade deformation analysis on the air flow field grids corresponding to the fan models based on the blade air flow velocity and wind pressure force of the air flow field grids corresponding to the different fan models, and obtaining the blade deformation degree of the air flow field grids corresponding to the different fan models under the conditions of air flow velocity and wind pressure;

[0022] Step S234: performing blade dynamic curvature evaluation and calculation on the corresponding three-dimensional fan model according to the degree of blade deformation of the air flow field grids corresponding to different fan models under the conditions of air flow velocity and wind pressure, and obtaining the blade dynamic curvature corresponding to different fan models;

[0023] Step S235: Based on the fan blade airflow pressure distribution of the air flow field grid corresponding to different fan models, the corresponding fan three-dimensional model is evaluated and analyzed to obtain the fan blade airflow vibration frequency corresponding to the different fan models.

[0024] Further, step S234 includes the following steps:

[0025] Perform aerodynamic stress analysis on the fan blade surface in the air flow field discretization grid corresponding to different fan models to obtain the fan blade surface dynamic stress in the air flow field grid corresponding to different fan models;

[0026] Based on the dynamic stress of the fan blade surface of the air flow field grid corresponding to different fan models, the fan blade stress-deformation coupling analysis is performed on the fan blade surface in the air flow field discretization grid corresponding to different fan models to obtain the fan blade surface stress-deformation coupling degree of the air flow field grid corresponding to different fan models;

[0027] The blade deformation degree of the air flow field grids corresponding to different fan models under the conditions of air flow velocity and wind pressure is calculated by grid deformation distribution gradient, and the blade dynamic deformation distribution gradient of the air flow field grids corresponding to different fan models is obtained;

[0028] According to the blade surface stress-deformation coupling degree and blade dynamic deformation distribution gradient of the air flow field grid corresponding to different fan models, the blade dynamic curvature evaluation and calculation are performed on the corresponding fan three-dimensional model to obtain the blade dynamic curvature corresponding to different fan models.

[0029] Further, step S235 includes the following steps:

[0030] Based on the fan blade airflow pressure distribution of the air flow field grid corresponding to different fan models, the fan blade airflow vibration response analysis is performed on the corresponding air flow field discretized grid, and the fan blade airflow vibration response data of the air flow field grid corresponding to different fan models are obtained;

[0031] Performing vibration frequency domain transformation processing on the fan blade airflow vibration response data of the air flow field grids corresponding to different fan models to generate fan blade airflow vibration response spectra of the air flow field grids corresponding to different fan models;

[0032] Based on the blade airflow vibration response spectra of the air flow field grids corresponding to different fan models, the blade airflow vibration evaluation and analysis of the corresponding fan three-dimensional model is performed to obtain the blade airflow vibration frequencies corresponding to different fan models.

[0033] Furthermore, the fan airflow efficiency calculation in step S24 is quantitatively calculated by a fan airflow efficiency calculation formula, wherein the fan airflow efficiency calculation formula is specifically:

[0034] ;

[0035] In the formula, is the fan air flow efficiency, is the length of the fan blades of the fan model, is the spatial position parameter, is the time variable parameter, For the spatial position and time The corresponding air flow velocity is For the spatial position The cross-sectional area of ​​the fan blade at is the air density, For the spatial position The fan blade airflow vibration frequency at For the spatial position The dynamic curvature of the fan blade at For in time The corresponding fan inlet inlet velocity is: For the spatial position The fan inlet inlet cross-sectional area at It is the correction factor of fan air flow efficiency.

[0036] Further, step S3 includes the following steps:

[0037] Step S31: performing an operation acoustic dynamic simulation analysis on the corresponding three-dimensional fan model under different design parameters and constraint conditions to generate a fan operation acoustic simulation field corresponding to different fan models;

[0038] Step S32: dividing the acoustic noise source frequency bands of the fan operation acoustic simulation fields corresponding to different fan models to obtain the fan operation acoustic noise source frequency bands corresponding to different fan models;

[0039] Step S33: performing noise propagation simulation on the fan operation acoustic noise source frequency bands corresponding to different fan models to generate fan operation acoustic noise propagation paths corresponding to the noise source frequency bands of different fan models; performing propagation attenuation characteristic analysis on the fan operation acoustic noise propagation paths corresponding to the noise source frequency bands of different fan models to obtain fan acoustic noise propagation attenuation characteristics of the operation acoustic noise propagation paths corresponding to different fan models;

[0040] Step S34: performing full-band acoustic noise evaluation and analysis on the corresponding three-dimensional fan model based on the fan acoustic noise propagation attenuation characteristics of the operating acoustic noise propagation paths corresponding to different fan models, and obtaining the fan operating acoustic noise levels corresponding to the different fan models;

[0041] Step S35: Perform performance curve simulation analysis according to the fan air flow efficiency and the fan operation acoustic noise level corresponding to different fan models to generate airflow efficiency-noise performance curves corresponding to different fan models.

[0042] Further, step S4 includes the following steps:

[0043] Step S41: obtaining fan constraint optimization targets corresponding to different fan models through corresponding fan three-dimensional models under different design parameters and constraint conditions, wherein the fan constraint optimization targets include maximizing fan power and minimizing fan operation noise;

[0044] Step S42: obtaining fan working energy efficiency performance values ​​corresponding to different fan models at each time point according to airflow efficiency-noise performance curves corresponding to different fan models;

[0045] Step S43: calculating the energy efficiency ratio of the corresponding three-dimensional fan model based on the fan working energy efficiency performance values ​​corresponding to the different fan models at each time point, so as to obtain the fan working timing energy efficiency ratios corresponding to the different fan models; drawing timing curves according to the fan working timing energy efficiency ratios corresponding to the different fan models, so as to generate fan timing energy efficiency ratio curves corresponding to the different fan models;

[0046] Step S44: performing fan energy efficiency optimization calculation on the fan timing energy efficiency ratio curves corresponding to different fan models based on the fan constraint optimization targets corresponding to different fan models, and obtaining fan constraint energy efficiency optimization values ​​corresponding to different fan models;

[0047] Step S45: performing model optimization design on the corresponding fan three-dimensional model based on the fan constraint energy efficiency optimization values ​​corresponding to different fan models to generate a fan optimization model.

[0048] Furthermore, the present invention also provides a fan model generation system, which is used to execute the fan model generation method as described above, and the fan model generation system includes:

[0049] The fan model preliminary simulation generation module is used to obtain the basic design parameters of the fan and the fan constraints, where the basic design parameters of the fan include the number of blades, blade length and rotation angle, and the fan constraints include wind speed range, power demand and noise requirement; the fan model is simulated and generated according to the basic design parameters of the fan and the fan constraints, so as to generate the corresponding three-dimensional fan model under different design parameters and constraints;

[0050] The dynamic simulation airflow efficiency calculation module is used to perform aerodynamic simulation on the corresponding three-dimensional fan model under different design parameters and constraint conditions to generate aerodynamic simulation fields corresponding to different fan models; perform blade dynamic curvature and airflow vibration evaluation and analysis on the aerodynamic simulation fields corresponding to different fan models to obtain the blade dynamic curvature and blade airflow vibration frequency corresponding to different fan models; calculate the fan airflow efficiency of the corresponding aerodynamic simulation field based on the blade dynamic curvature and blade airflow vibration frequency corresponding to different fan models, thereby obtaining the fan air flow efficiency corresponding to different fan models;

[0051] The fan model performance curve simulation module is used to evaluate and analyze the operation acoustic noise of the corresponding three-dimensional fan model under different design parameters and constraints, and obtain the fan operation acoustic noise level corresponding to different fan models; the performance curve simulation analysis is performed according to the fan air flow efficiency and fan operation acoustic noise level corresponding to different fan models to generate the airflow efficiency-noise performance curve corresponding to different fan models;

[0052] The fan model sequential energy efficiency ratio optimization module is used to obtain the corresponding fan constraint optimization target through the corresponding fan three-dimensional model under different design parameters and constraint conditions, and to perform sequential energy efficiency ratio optimization design on the corresponding fan three-dimensional model based on the fan constraint optimization targets corresponding to different fan models and the airflow efficiency-noise performance curve to generate a fan optimization model.

[0053] Beneficial effects of the present invention:

[0054] 1. Compared with the prior art, the method for generating a fan model proposed in the present invention has the beneficial effect of inputting the basic design parameters (such as the number of blades, blade length and rotation angle) and constraints (such as wind speed range, power requirements and noise requirements) of the fan through a graphical interface. The core significance of this process is to provide an intuitive and efficient design interaction method. Through the graphical interface, the basic parameters required for the design can be directly input, which reduces the difficulty of operation and the learning curve. The user can intuitively select or adjust parameters, such as dragging sliders, entering values, selecting preset options, etc., which greatly enhances flexibility and convenience. In addition, the corresponding constraints, such as wind speed range and power requirements, are input during the design process to ensure that the fan achieves the expected effect in actual use. At the same time, by simulating and generating fan models according to the basic design parameters of the fan and the fan constraints, a three-dimensional model under different design schemes is generated. The key to this process is that it converts theoretical design into a visual three-dimensional model, helping designers to more intuitively and accurately evaluate the appearance, structure and functional characteristics of the fan. This simulated three-dimensional model can flexibly reflect the spatial layout of each part of the fan, helping designers to find potential structural problems, such as blade gaps, material stress concentration, poor air flow, etc., thereby providing data support for the subsequent optimization design process. Secondly, by performing aerodynamic simulation on the three-dimensional model of the fan under different design parameters and constraints, the aerodynamic performance of the fan under different operating environments can be effectively evaluated and predicted. This process is achieved through computational fluid dynamics (CFD) technology, simulating the flow field changes, pressure distribution, velocity field, etc. when air flows through the fan blades, so that complex fluid dynamics analysis can be effectively performed. This simulation can help designers deeply understand the impact of different design schemes on fan performance, thereby improving the reliability and feasibility of the design. By evaluating and analyzing the dynamic curvature of fan blades and airflow vibration in the aerodynamic simulation fields corresponding to different fan models, this analysis helps to study the bending deformation and vibration phenomena of fan blades caused by airflow during operation. The analysis of the dynamic curvature of fan blades can reveal the elastic deformation of blades under high-speed rotation, while the airflow vibration frequency analysis can evaluate whether the fan will produce adverse vibration modes during operation, thereby affecting the airflow quality or generating excessive noise, thereby providing basic data support for subsequent processing processes.The fan's airflow efficiency is also calculated based on the dynamic curvature of the fan blades and the airflow vibration frequency corresponding to different fan models. Airflow efficiency is a key indicator for measuring fan performance and determines the fan's ability to convert mechanical energy into airflow energy under specific working conditions. By calculating the airflow efficiency, engineers can quantify the fan's operating performance, identify potential performance bottlenecks or energy efficiency loss points, and more accurately evaluate the fan's aerodynamic efficiency under different design conditions, ensuring that the fan's airflow efficiency is maximized while meeting mechanical and aerodynamic performance, thereby improving the overall performance and design efficiency of the fan model in practical applications. Then, by performing an operation acoustic noise evaluation and analysis on the corresponding three-dimensional fan model under different design parameters and constraints, the fan's noise level in the full frequency band (low frequency to high frequency) can be accurately calculated, helping to determine whether the fan's noise performance under different working conditions meets the standard requirements, and then adjusting the design (for example, by adjusting the blade shape, material, speed, etc.) to reduce noise, ensuring the best balance between the performance and noise level of the fan model. The performance curve simulation analysis is also carried out according to the fan air flow efficiency and the acoustic noise level of the fan operation corresponding to different fan models. The airflow efficiency and noise level of the fan are usually mutually constrained, that is, improving the airflow efficiency of the fan will lead to an increase in the noise level, and vice versa. By comprehensively considering the relationship between the two, designers can generate performance curves of different fan models, which clearly show the trade-off between airflow efficiency and noise level under different design parameters. The curve provides a reference for designers to optimize fan design and can help determine the best design scheme, which can ensure that the airflow efficiency meets the expected requirements and minimize the noise level. Finally, the fan constraint optimization objectives corresponding to different fan models are obtained through the corresponding fan three-dimensional models under different design parameters and constraints. The combination of these design parameters and constraints can directly affect the performance of the fan, including power output and noise level. The goal of maximizing fan power is to improve the working efficiency of the fan so that it can output higher power at lower energy consumption. The goal of minimizing noise is to ensure that the noise level generated by the fan during operation is minimized, so as to evaluate the performance of different design schemes in power and noise, and provide a theoretical basis for subsequent optimization. In addition, the corresponding fan three-dimensional model is optimized for the timing energy efficiency ratio based on the fan constraint optimization objectives and airflow efficiency-noise performance curve corresponding to different fan models, so as to further adjust the fan design according to different optimization objectives and airflow efficiency-noise performance curves. The core of this step is to use the computational model to adjust the working conditions and design parameters of the fan so that it can achieve the best timing energy efficiency performance while meeting the constraints. The obtained fan model can not only maximize its power output, but also has a significant improvement in noise minimization, which can ensure that the fan model can achieve the best performance level under various environmental conditions.

[0055] 2. The fan model generation system proposed in the present invention is generally composed of a fan model preliminary simulation generation module, a power simulation airflow efficiency calculation module, a fan model performance curve simulation module and a fan model timing energy efficiency ratio optimization module. It can realize the generation method of any fan model described in the present invention, and is used to combine the operations between computer programs running on each module to realize the fan model generation method. The internal structures of the system cooperate with each other, which can greatly reduce duplication of work and manpower investment, and can quickly and effectively provide a more accurate and efficient fan model generation process, thereby simplifying the operation flow of the fan model generation system. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments thereof made with reference to the following drawings:

[0057] Figure 1 A schematic flow chart of the steps of the method for generating a fan model of the present invention;

[0058] Figure 2 for Figure 1 Detailed step flow diagram of step S1;

[0059] Figure 3 for Figure 1 Detailed step flow chart of step S2 in FIG. DETAILED DESCRIPTION

[0060] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. 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 technicians in this field without creative work are within the scope of protection of the present invention.

[0061] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0062] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0063] To achieve this, please refer to Figures 1 to 3 The present invention provides a method for generating a fan model, the method comprising the following steps:

[0064] Step S1: Obtaining basic design parameters and fan constraints of the fan, wherein the basic design parameters of the fan include the number of blades, blade length and rotation angle, and the fan constraints include wind speed range, power requirement and noise requirement; performing fan model simulation generation according to the basic design parameters of the fan and the fan constraints, and generating corresponding three-dimensional fan models under different design parameters and constraints;

[0065] Step S2: performing aerodynamic simulation on the corresponding three-dimensional fan models under different design parameters and constraints to generate aerodynamic simulation fields corresponding to different fan models; performing blade dynamic curvature and airflow vibration evaluation and analysis on the aerodynamic simulation fields corresponding to different fan models to obtain blade dynamic curvature and blade airflow vibration frequency corresponding to different fan models; performing fan airflow efficiency calculation on the corresponding aerodynamic simulation fields based on the blade dynamic curvature and blade airflow vibration frequency corresponding to different fan models to obtain fan air flow efficiency corresponding to different fan models;

[0066] Step S3: performing an operation acoustic noise evaluation analysis on the corresponding three-dimensional fan models under different design parameters and constraint conditions to obtain the fan operation acoustic noise levels corresponding to different fan models; performing a performance curve simulation analysis based on the fan air flow efficiency and the fan operation acoustic noise levels corresponding to different fan models to generate airflow efficiency-noise performance curves corresponding to different fan models;

[0067] Step S4: Obtain the corresponding fan constraint optimization target through the corresponding fan three-dimensional model under different design parameters and constraint conditions, and perform timing energy efficiency ratio optimization design on the corresponding fan three-dimensional model based on the fan constraint optimization target corresponding to different fan models and the airflow efficiency-noise performance curve to generate a fan optimization model.

[0068] In the embodiment of the present invention, please refer to Figure 1FIG. 1 is a schematic diagram of a step flow of a method for generating a fan model of the present invention. In this example, the method for generating a fan model includes the following steps:

[0069] Step S1: Obtaining basic design parameters and fan constraints of the fan, wherein the basic design parameters of the fan include the number of blades, blade length and rotation angle, and the fan constraints include wind speed range, power requirement and noise requirement; performing fan model simulation generation according to the basic design parameters of the fan and the fan constraints, and generating corresponding three-dimensional fan models under different design parameters and constraints;

[0070] In an embodiment of the present invention, basic design parameters and constraints of the fan are input through a graphical interface. The specific operation process is as follows: a graphical design interface is started by using professional fan design software (such as SolidWorks, ANSYS Fluent or similar computational fluid dynamics software). In the interface, the user needs to input the number of blades, blade length and rotation angle of the fan in sequence. For the number of blades, an input box will be displayed in the interface, allowing the user to select or input the number of blades, generally ranging from 3 to 12 blades. Selecting too many or too few will affect the performance of the fan. The input box for blade length requires the user to input the length of the blade, which is generally determined according to the use scenario of the fan, such as an electric fan, a cooling fan, etc., and the setting of the rotation angle generally includes the forward tilt angle, the backward tilt angle and the maximum angle of the blade; and The fan constraints include wind speed range, power requirements and noise requirements. The wind speed range is set through the input interface to limit the minimum and maximum wind speeds that the fan can provide, in meters per second (m / s). For example, the wind speed range is set to 1.5m / s to 4.5m / s. The power requirement is used to specify the minimum and maximum power output of the fan through the input box, in watts (W). For example, the power range is set to 15W to 60W. The noise requirement is usually in decibels (dB). After all these parameters are entered, the graphical interface will perform preliminary parameter verification to obtain the basic design parameters of the fan and the fan constraints. At the same time, according to the basic design parameters and constraints of the fan input by the user, a series of fan design combinations are generated through the simulation analysis tool to simulate the influence of different design parameter combinations on the fan performance. Then, by simulating the combination according to the previously generated different fan design parameters and constraints, a three-dimensional geometric model of the fan is created and further simulation analysis is performed. The specific operations are as follows: in the fan simulation software, each set of design parameters previously generated (such as the number of blades, blade length, rotation angle, wind speed range, power requirement, and noise requirement, etc.) is imported into the three-dimensional modeling module. The software will automatically generate a three-dimensional geometric model of the fan based on these input parameters, simulate the shape, structure and interaction of the fan blades with the air. In the process of model generation, parametric modeling technology is used to adjust the geometric characteristics of the fan model according to the input values ​​and parameters to adapt to different design requirements, and perform detailed aerodynamic performance simulation to simulate the working performance of the fan under different design combinations, and output the final three-dimensional model, and finally generate a corresponding three-dimensional model of the fan under different design parameters and constraints.

[0071] Step S2: performing aerodynamic simulation on the corresponding three-dimensional fan models under different design parameters and constraints to generate aerodynamic simulation fields corresponding to different fan models; performing blade dynamic curvature and airflow vibration evaluation and analysis on the aerodynamic simulation fields corresponding to different fan models to obtain blade dynamic curvature and blade airflow vibration frequency corresponding to different fan models; performing fan airflow efficiency calculation on the corresponding aerodynamic simulation fields based on the blade dynamic curvature and blade airflow vibration frequency corresponding to different fan models to obtain fan air flow efficiency corresponding to different fan models;

[0072] In an embodiment of the present invention, a three-dimensional fan model is created based on different design parameters (such as the number of blades, blade shape, blade angle, etc.) and constraints (such as wind speed range, power requirement, and noise requirement, etc.), and a computational fluid dynamics (CFD) tool, such as ANSYS Fluent or OpenFOAM, is used to perform aerodynamic simulation on each fan model. During the simulation process, the fluid boundary condition is set to steady state or transient flow, depending on the working state of the fan. The simulation result should include the airflow field distribution around the fan, such as velocity field, pressure field, turbulence intensity, etc., and the aerodynamic characteristics of different fan models under given working conditions are provided, thereby generating aerodynamic simulation fields corresponding to different fan models. According to the aerodynamic simulation field corresponding to different fan models, high-quality mesh generation tools such as ANSYSMeshing or ICEM CFD are used to mesh the airflow field. Therefore, finer meshes are set in the blade area, airflow inlet and outlet areas to ensure that subtle changes in the airflow can be captured. The previously divided discretized meshes are used to perform a dynamic analysis of the fan blade based on the mechanical behavior of the fan blade, especially to evaluate the dynamic curvature of the blade and the vibration characteristics caused by the airflow. This analysis usually uses multi-physics field coupling simulation tools, such as the coupling of ANSYS Mechanical and CFD modules, to perform joint calculations of structure and fluid. In the analysis, the vibration frequency of the blade under airflow excitation is obtained by performing modal analysis on the fan blade under fluid load. At the same time, the dynamic curvature of the fan blade is calculated in combination with the material properties, geometric shape and airflow distribution of the blade, so that the dynamic response of the fan blade under different design schemes can be deeply understood, thereby obtaining the dynamic curvature of the fan blade and the airflow vibration frequency of the fan blade corresponding to different fan models. Then, after obtaining the dynamic curvature of the fan blades and the airflow vibration frequency, the airflow efficiency of each fan model is further calculated to use the previously obtained aerodynamic simulation field data and dynamic results to calculate the fan airflow efficiency. The calculation process uses the relationship between the fan power input and the airflow output to evaluate the fan's airflow efficiency, and finally obtains the fan air flow efficiency corresponding to different fan models.

[0073] Step S3: performing an operation acoustic noise evaluation analysis on the corresponding three-dimensional fan models under different design parameters and constraint conditions to obtain the fan operation acoustic noise levels corresponding to different fan models; performing a performance curve simulation analysis based on the fan air flow efficiency and the fan operation acoustic noise levels corresponding to different fan models to generate airflow efficiency-noise performance curves corresponding to different fan models;

[0074] In an embodiment of the present invention, acoustic dynamic simulation analysis is performed on multiple fan design models under different design parameters (such as the number of blades, blade shape, blade angle, etc.) and constraints (such as wind speed range, power demand, and noise requirement, etc.). To this end, computational fluid dynamics (CFD) and acoustic simulation software, such as ANSYS, COMSOL Multiphysics, and other tools, are used to simulate the aerodynamic and acoustic fields of the fan. Three-dimensional geometric models of different fan designs are created in the software, and corresponding working conditions, such as the rotation speed, air density, temperature, and pressure of the fan, are set. The interaction between the fan blades and the airflow is simulated by using a CFD module, and the airflow field distribution is calculated. The acoustic simulation module is further used to analyze the distribution and intensity of the noise sources generated under the airflow field, and the acoustic characteristics of different fan models during operation are obtained to form an acoustic simulation field of the fan. The frequency band of the noise source is divided based on the previously obtained fan operation acoustic simulation field. The specific method is to use acoustic analysis software (such as MATLAB, LMS Virtual Machines, etc.) Lab, etc.), perform Fourier transform on the acoustic data obtained in the simulation field, decompose the noise of different frequency components, first determine the frequency range of the analysis, select a reasonable frequency band according to the fan speed and aerodynamic characteristics, divide the frequency bands of various noise sources, such as low frequency, medium frequency and high frequency, the noise source characteristics corresponding to each frequency band reflect the noise source and its intensity of the fan under different operating conditions, at the same time, through the noise propagation simulation based on the previously divided fan operation acoustic noise source frequency band, analyze the propagation path of noise in different frequency bands in the air and its attenuation characteristics, and simulate the propagation path of noise from the fan sound source to the environment through the acoustic propagation model (for example, based on acoustic ray tracing, boundary element method BEM, finite element method FEM, etc.), and also use the corresponding simulation software, such as ACTRAN or COMSOL In the acoustic module of Multiphysics, the parameters of the propagation medium (air) are set, and the attenuation characteristics of the fan operation acoustic noise propagation paths corresponding to different frequency bands when propagating in the air are considered (including sound absorption, scattering, reflection and other effects). During the simulation process, the sound wave propagation paths of different fan models in different frequency bands are compared to identify the propagation paths of noise in different frequency bands, so as to obtain the propagation attenuation characteristics corresponding to the noise source frequency band. Based on the noise propagation attenuation characteristics obtained based on the previous analysis, the full-band noise level of the fan is further evaluated and analyzed. By using acoustic evaluation tools (such as NoiseMap or Odeon, etc.), the propagation path of the noise source frequency band is combined with the attenuation characteristics to conduct a full-band noise evaluation. By calculating the sound power level, sound pressure level and other parameters of each frequency band, the fan operation acoustic noise level corresponding to different fan models is obtained.Then, based on the previously obtained acoustic noise level of the fan operation and the air flow efficiency of the fan, a simulation analysis of the performance curve is performed. The specific operation is to combine CFD with acoustic noise simulation to model the relationship between airflow efficiency and noise. The fan is simulated under various working conditions in the CFD software, and its airflow efficiency (that is, the ratio of air volume to power consumption) under different working conditions is calculated. The airflow efficiency under each working condition is combined with the obtained noise level to draw a relationship curve between the airflow efficiency and noise, ensuring that the fan can reduce the noise level as much as possible while meeting the air flow efficiency requirements, and finally generate the airflow efficiency-noise performance curves corresponding to different fan models.

[0075] Step S4: Obtain the corresponding fan constraint optimization target through the corresponding fan three-dimensional model under different design parameters and constraint conditions, and perform timing energy efficiency ratio optimization design on the corresponding fan three-dimensional model based on the fan constraint optimization target corresponding to different fan models and the airflow efficiency-noise performance curve to generate a fan optimization model.

[0076] In an embodiment of the present invention, multiple three-dimensional fan models are established for different design parameters and constraints (such as rotation speed, blade angle, air inlet design, etc.) through computational fluid dynamics (CFD) simulation or similar simulation tools. Each fan model must meet certain design restrictions and operating constraints, such as the allowable power range and noise limit. For each fan model, simulation software is used to predict the performance of wind force and noise, and the power output and operating noise value of each fan model are calculated to obtain the power maximization and noise minimization goals of each fan model. Specifically, the power maximization goal is to increase the power output of the fan as much as possible without exceeding the agreed power upper limit, while the noise minimization goal is to minimize the noise generated by the fan during operation while meeting the power requirements, thereby obtaining the fan constraint optimization goals corresponding to different fan models. At the same time, by simulating each fan model, the airflow efficiency and noise data of the fan under different working conditions are obtained. This process is usually completed using CFD software combined with an acoustic simulation module. Different working conditions (such as fan speed, airflow, etc.) are set, and the simulation is run to record the airflow efficiency and noise level under each working condition. Airflow efficiency refers to the ability of the fan to effectively convert airflow kinetic energy under a certain energy input, while noise is the sound waves generated by the interaction between the blades and the airflow during the rotation of the fan. Through these simulation data, the airflow efficiency-noise performance curve of each fan model under different working conditions is drawn, the working performance at different time points is recorded, and the working energy efficiency performance score at each time point is quantitatively calculated based on the corresponding airflow efficiency and noise level, that is, , and by combining the corresponding working energy efficiency performance score at each time point obtained by quantification, the corresponding fan three-dimensional model is quantitatively calculated at each time point to calculate the energy efficiency ratio, so as to use the energy efficiency performance ratio between the fan working energy efficiency performance value corresponding to the current time point and the fan working energy efficiency performance value corresponding to the previous time point as the energy efficiency ratio value at the current time point, and by performing a time series analysis on the energy efficiency ratio value of each fan model, an energy efficiency change curve of the fan model in the entire working cycle is generated, and then, by combining the corresponding fan constraint optimization target, the energy efficiency optimization calculation of the fan model is performed on the previously drawn time series energy efficiency ratio curve. The specific operation is to optimize the fan time series energy efficiency ratio curve through the defined optimization target and the fan power, noise, airflow efficiency and other performance indicators. This process usually requires the use of mathematical optimization algorithms (such as genetic algorithms, particle swarm optimization or gradient descent method). Under the premise of ensuring that the fan performance indicators meet the design requirements, the optimal combination of working parameters is found to maximize the energy efficiency ratio. The optimization objective function can comprehensively consider factors such as fan power, noise, energy efficiency, etc., and adjust the priority through weights. After optimization calculation, the energy efficiency optimization value corresponding to each fan model is obtained, and the fan three-dimensional model is optimized by using computer-aided design (CAD) tools by combining the fan constraint energy efficiency optimization value obtained by previous quantification. The energy efficiency optimization value of each fan model is compared with its design parameters (such as blade angle, speed, etc.). Then, the three-dimensional geometric model of the fan is modified by CAD software, including the shape, thickness, angle and other design details of the blades, so that the fan can achieve higher energy efficiency under the optimization goal. The fan optimization design is not limited to shape adjustment, but also includes material selection and manufacturing process improvements, which can provide higher energy efficiency and lower noise, and finally optimize the fan optimization model.

[0077] Further, step S1 includes the following steps:

[0078] Step S11: obtaining basic design parameters and fan constraints of the fan through a graphical interface input, wherein the basic design parameters of the fan include the number of blades, blade length and rotation angle, and the fan constraints include wind speed range, power requirement and noise requirement;

[0079] Step S12: performing fan simulation combination design according to the basic fan design parameters and the fan constraint conditions to generate different fan design parameter and constraint condition simulation combinations;

[0080] Step S13: Perform fan model simulation generation according to different fan design parameters and constraint condition simulation combinations to generate corresponding fan three-dimensional models under different design parameters and constraint conditions.

[0081] As an embodiment of the present invention, refer to Figure 2As shown, Figure 1 Detailed step flow diagram of step S1 in FIG. 1 , in this embodiment, step S1 includes the following steps:

[0082] Step S11: obtaining basic design parameters and fan constraints of the fan through a graphical interface input, wherein the basic design parameters of the fan include the number of blades, blade length and rotation angle, and the fan constraints include wind speed range, power requirement and noise requirement;

[0083] In an embodiment of the present invention, basic design parameters and constraints of the fan are input through a graphical interface. The specific operation process is as follows: a graphical design interface is started by using professional fan design software (such as SolidWorks, ANSYS Fluent or similar computational fluid dynamics software). In the interface, the user needs to input the number of blades, blade length and rotation angle of the fan in sequence. For the number of blades, an input box will be displayed in the interface, allowing the user to select or input the number of blades, generally ranging from 3 to 12 blades. Selecting too many or too few will affect the performance of the fan. The input box for blade length requires the user to input the length of the blade, which is generally determined according to the use scenario of the fan, such as electric fans, cooling fans, etc. The setting of the rotation angle generally includes the forward tilt angle, backward tilt angle and maximum angle of the blade; and the constraints of the fan include wind speed range, power requirements and noise requirements. The wind speed range The range setting is used to limit the minimum and maximum wind speeds that the fan can provide through the input interface, in meters per second (m / s), for example, the wind speed range is set to 1.5m / s to 4.5m / s. The power requirement is used to specify the minimum and maximum power output of the fan through the input box, in watts (W), for example, the power range is set to 15W to 60W. The noise requirement is usually in decibels (dB). The user needs to enter the maximum noise value generated when the fan is running to ensure that the fan noise is below a certain noise level. After all these parameters are entered, the graphical interface will perform preliminary parameter verification to ensure that the input values ​​meet the actual usage requirements, and finally obtain the basic design parameters of the fan and the fan constraints.

[0084] Step S12: performing fan simulation combination design according to the basic fan design parameters and the fan constraint conditions to generate different fan design parameter and constraint condition simulation combinations;

[0085] In an embodiment of the present invention, a series of fan design combinations are generated through a simulation analysis tool according to the basic design parameters and constraints of the fan input by the user, so as to simulate the influence of different design parameter combinations on the fan performance by performing multiple simulations using CFD (computational fluid dynamics) software. Through the "design space exploration" module in the software, the basic design parameters of the fan, such as the number of blades, blade length, and rotation angle, are used as design variables. The software quickly calculates different combinations of these variables to simulate the performance of each design combination under constraints such as wind speed, power, and noise. For each group of combinations, the software predicts the air flow, pressure distribution, power demand, and noise generation of the fan under different working conditions by solving complex fluid dynamics equations (such as the Navier-Stokes equations). The simulation results will provide various performance indicators of the fan, such as airflow rate, power consumption, noise level, etc., and finally generate different simulation combinations of fan design parameters and constraints.

[0086] Step S13: Perform fan model simulation generation according to different fan design parameters and constraint condition simulation combinations to generate corresponding fan three-dimensional models under different design parameters and constraint conditions.

[0087] In an embodiment of the present invention, a three-dimensional geometric model of the fan is created and further simulation analysis is performed by simulating combinations based on different fan design parameters and constraints generated previously. The specific operation is as follows: each set of design parameters (such as the number of blades, blade length, rotation angle, etc.) generated previously is imported into the three-dimensional modeling module in the fan simulation software. The software automatically generates a three-dimensional geometric model of the fan based on these input parameters, simulates the shape, structure and interaction of the fan blades with the air. In the process of generating the model, parametric modeling technology is used to adjust the geometric features of the fan model according to the input values ​​and parameters to adapt to different design requirements, and perform detailed aerodynamic performance simulation to simulate the working performance of the fan under different design combinations, such as the flow path, velocity distribution, and vortex generation of air through the fan blades. According to the simulation results, the software can further optimize the design of the fan, such as adjusting the curvature, inclination angle, and front and rear position of the blades to optimize the aerodynamic performance and energy efficiency of the fan, and output the final three-dimensional model, and finally generate a corresponding three-dimensional model of the fan under different design parameters and constraints.

[0088] Further, step S2 includes the following steps:

[0089] Step S21: performing aerodynamic simulation on the corresponding three-dimensional fan models under different design parameters and constraint conditions to generate aerodynamic simulation fields corresponding to different fan models;

[0090] Step S22: performing airflow field grid division on the aerodynamic simulation fields corresponding to different fan models to obtain air flow field discretization grids corresponding to different fan models;

[0091] Step S23: Based on the air flow field discretization grids corresponding to different fan models, the corresponding three-dimensional fan models are evaluated and analyzed for the dynamic curvature of the fan blades and the airflow vibration frequency of the fan blades, so as to obtain the dynamic curvature of the fan blades and the airflow vibration frequency of the fan blades corresponding to the different fan models;

[0092] Step S24: Calculate the fan airflow efficiency of the corresponding aerodynamic simulation field based on the dynamic curvature of the fan blades and the airflow vibration frequency of the fan blades corresponding to different fan models to obtain the fan air flow efficiency corresponding to different fan models.

[0093] As an embodiment of the present invention, refer to Figure 3 As shown, Figure 1 Detailed step flow diagram of step S2 in FIG. 1 , in this embodiment, step S2 includes the following steps:

[0094] Step S21: performing aerodynamic simulation on the corresponding three-dimensional fan models under different design parameters and constraint conditions to generate aerodynamic simulation fields corresponding to different fan models;

[0095] In an embodiment of the present invention, a three-dimensional fan model is created based on different design parameters (such as the number of blades, blade shape, blade angle, etc.) and constraints (such as wind speed range, power requirement, and noise requirement, etc.), and a computational fluid dynamics (CFD) tool, such as ANSYS Fluent or OpenFOAM, is used to perform aerodynamic simulation on each fan model. During the simulation process, the fluid boundary condition is set to steady state or transient flow, depending on the working state of the fan. The simulation result should include the airflow field distribution around the fan, such as velocity field, pressure field, turbulence intensity, etc., and provide aerodynamic characteristics of different fan models under given working conditions, forming an aerodynamic simulation field for each model fan, showing the performance differences under different designs, and finally generating aerodynamic simulation fields corresponding to different fan models.

[0096] Step S22: performing airflow field grid division on the aerodynamic simulation fields corresponding to different fan models to obtain air flow field discretization grids corresponding to different fan models;

[0097] In an embodiment of the present invention, the airflow field is meshed by using high-quality mesh generation tools, such as ANSYS Meshing or ICEM CFD, according to the aerodynamic simulation fields corresponding to different fan models. The fineness of the meshing directly affects the accuracy of the simulation. Therefore, finer meshes are set in the blade area, airflow inlet and outlet areas to ensure that subtle changes in the airflow can be captured. In the division process, unstructured meshes or structured meshes can be selected, depending on the complexity of the airflow. In key areas, such as the surface of the fan blade and the airflow separation area, appropriate refined meshes are used to ensure calculation accuracy. After the meshing is completed, the mesh quality is checked to ensure that the mesh is not deformed, does not overlap, and the calculation area is completely covered, and finally the air flow field discretization meshes corresponding to different fan models are obtained.

[0098] Step S23: Based on the air flow field discretization grids corresponding to different fan models, the corresponding three-dimensional fan models are evaluated and analyzed for the dynamic curvature of the fan blades and the airflow vibration frequency of the fan blades, so as to obtain the dynamic curvature of the fan blades and the airflow vibration frequency of the fan blades corresponding to the different fan models;

[0099] In an embodiment of the present invention, by utilizing the previously divided discretized grid and based on the mechanical behavior of the fan blade, a dynamic analysis of the fan blade is performed, especially evaluating the dynamic curvature of the blade and the vibration characteristics caused by the airflow. The analysis usually uses a multi-physics field coupling simulation tool, such as the coupling of ANSYS Mechanical and the CFD module, to perform joint calculations of the structure and the fluid. In the analysis, the vibration frequency of the blade under the excitation of the airflow is obtained by performing a modal analysis on the fan blade under the action of the fluid load. At the same time, the dynamic curvature of the fan blade is calculated in combination with the material properties, geometric shape and airflow distribution of the blade. The dynamic response of the fan blade under different design schemes can be deeply understood, and finally the dynamic curvature of the fan blade and the airflow vibration frequency of the fan blade corresponding to different fan models are obtained.

[0100] Step S24: Calculate the fan airflow efficiency of the corresponding aerodynamic simulation field based on the dynamic curvature of the fan blades and the airflow vibration frequency of the fan blades corresponding to different fan models to obtain the fan air flow efficiency corresponding to different fan models.

[0101] In an embodiment of the present invention, after obtaining the dynamic curvature of the fan blades and the airflow vibration frequency, the airflow efficiency of each fan model is further calculated, so as to use the previously obtained aerodynamic simulation field data and dynamic results to calculate the fan airflow efficiency. The calculation process adopts the relationship between the fan power input and the airflow output, and evaluates the fan's airflow efficiency by comparing the fan's aerodynamic performance (such as flow rate, wind pressure, power consumption, etc.) with the actual wind force generated. The influence of factors such as noise and vibration during fan operation on the airflow efficiency can also be considered to comprehensively obtain the comprehensive air flow performance of each fan model in actual application, and finally obtain the fan air flow efficiency corresponding to different fan models.

[0102] Further, step S23 includes the following steps:

[0103] Step S231: performing fan blade airflow pressure distribution analysis on the air flow field discretization grids corresponding to different fan models to obtain fan blade airflow pressure distribution of the air flow field grids corresponding to different fan models;

[0104] In an embodiment of the present invention, computational fluid dynamics (CFD) software, such as ANSYS Fluent or OpenFOAM, is used to discretize the airflow of different fan models into grids, so that the air flow field in the area around the fan is gridded according to the geometric shape of the fan blades and the airflow characteristics, ensuring that the grid fineness is fine enough on the blade surface and the key airflow area. Then, boundary conditions, such as intake velocity, fan speed, and external environmental pressure, are applied to perform numerical simulation, and the airflow pressure distribution diagram on the fan blade is obtained by calculation. The airflow pressure data of the fan blade in different areas are recorded, including the pressure values ​​of the leading edge, the trailing edge, and the blade surface, and finally the airflow pressure distribution of the fan blade corresponding to the air flow field grid of different fan models is obtained.

[0105] Step S232: analyzing the air flow velocity and wind pressure action of the air flow field grids corresponding to the fan models according to the fan blade air flow pressure distribution of the air flow field grids corresponding to the different fan models, so as to obtain the fan blade air flow velocity and wind pressure action of the air flow field grids corresponding to the different fan models;

[0106] In an embodiment of the present invention, a CFD tool is used to analyze the airflow velocity and wind pressure force based on the airflow pressure distribution obtained by the previous analysis. In this process, the airflow velocity on the surface of the fan blade is calculated to obtain the airflow velocity distribution of the fan blade, and the flow field is solved by using the same grid as the pressure distribution. During the solution, the fan speed, wind pressure and momentum exchange effect of the airflow are considered to calculate the velocity field of the airflow on the blade surface and its surrounding area, and then the wind pressure force is obtained. The calculation basis of these forces includes the interaction force model between the blade surface and the fluid, and finally the wind pressure force is calculated, and finally the fan blade airflow velocity and wind pressure force of the air flow field grid corresponding to different fan models are obtained.

[0107] Step S233: performing a blade deformation analysis on the air flow field grids corresponding to the fan models based on the blade air flow velocity and wind pressure force of the air flow field grids corresponding to the different fan models, and obtaining the blade deformation degree of the air flow field grids corresponding to the different fan models under the conditions of air flow velocity and wind pressure;

[0108] In an embodiment of the present invention, the deformation of the fan blade is analyzed by using a finite element analysis (FEA) tool, such as ANSYS or ABAQUS, based on the previously obtained airflow velocity and wind pressure force. During the analysis process, a three-dimensional geometric model of the fan blade is first established, and the corresponding airflow velocity and wind pressure force are applied according to the fluid mechanics analysis results, and the deformation degree of the blade under the action of the airflow is calculated using the theory of elastic mechanics, taking into account the elastic modulus and yield strength of the material and the dynamic response of the airflow. Through this process, the deformation amount of the blade under different airflow and wind pressure conditions under different fan models is obtained, such as deformation forms such as twisting and bending, and the deformation value of each blade area is recorded, and finally the degree of fan blade deformation of the air flow field grid corresponding to the different fan models under the conditions of airflow velocity and wind pressure is obtained.

[0109] Step S234: performing blade dynamic curvature evaluation and calculation on the corresponding three-dimensional fan model according to the degree of blade deformation of the air flow field grids corresponding to different fan models under the conditions of air flow velocity and wind pressure, and obtaining the blade dynamic curvature corresponding to different fan models;

[0110] In an embodiment of the present invention, the dynamic curvature of the fan blade is evaluated by further using a method combining CFD software with finite element analysis based on the degree of blade deformation under the conditions of air flow velocity and wind pressure corresponding to the air flow field grid of different fan models previously obtained. In this step, the dynamic response of the blade is first calculated by applying boundary conditions of wind pressure and air flow velocity, and then the bending deformation of the blade during rotational motion is analyzed. The curvature of the fan blade is evaluated using a material mechanics model, especially the dynamic bending characteristics of the blade under different fan models, with emphasis on the bending of the blade under the maximum air flow velocity and wind pressure, thereby obtaining the dynamic curvature index of the fan model, and finally obtaining the dynamic curvature of the blade corresponding to different fan models.

[0111] Step S235: Based on the fan blade airflow pressure distribution of the air flow field grid corresponding to different fan models, the corresponding fan three-dimensional model is evaluated and analyzed to obtain the fan blade airflow vibration frequency corresponding to the different fan models.

[0112] In an embodiment of the present invention, an airflow vibration evaluation is performed on the corresponding three-dimensional fan model according to the airflow pressure distribution of the fan blades in the air flow field grid corresponding to different fan models, so as to simulate the vibration response of the fan blades under the action of airflow velocity and wind pressure by combining CFD tools and vibration analysis software (such as ANSYS Mechanical or COMSOL Multiphysics), and calculate the vibration mode of the blades by applying vibration boundary conditions of different frequencies, especially the resonant frequency coupled with the airflow frequency, and evaluate the vibration frequency based on the periodic changes of the wind flow and the dynamic response of the blades in the air flow field, so as to obtain the airflow vibration frequencies of different fan models under actual operating conditions, and finally obtain the airflow vibration frequencies of the fan blades corresponding to the different fan models.

[0113] Further, step S234 includes the following steps:

[0114] Perform aerodynamic stress analysis on the fan blade surface in the air flow field discretization grid corresponding to different fan models to obtain the fan blade surface dynamic stress in the air flow field grid corresponding to different fan models;

[0115] In an embodiment of the present invention, the fan blade surface within the air flow field discretization grid corresponding to different fan models is meshed discretized, so as to simulate the air flow field near the fan blade surface by using high-precision computational fluid dynamics (CFD) software, such as ANSYS Fluent or OpenFOAM. Through these software, the fan model is divided into multiple small units (grids), and the flow field is numerically solved in each grid. When performing numerical analysis, various influencing factors of aerodynamics (such as air flow velocity, wind pressure distribution, turbulence model, etc.) are taken into account to calculate the aerodynamic stress on the fan blade surface. Specifically, the software will obtain the stress distribution on the fan blade surface under different airflow conditions by solving the Navier-Stokes equations and applying appropriate boundary conditions. This process ensures that the calculated stress field can accurately reflect the blade force conditions under different fan models, and finally obtains the dynamic stress on the fan blade surface of the air flow field grid corresponding to different fan models.

[0116] Preferably, based on the dynamic stress of the fan blade surface of the air flow field grid corresponding to different fan models, the fan blade surface in the air flow field discretization grid corresponding to different fan models is subjected to the fan blade stress-deformation coupling analysis to obtain the fan blade surface stress-deformation coupling degree of the air flow field grid corresponding to different fan models;

[0117] In an embodiment of the present invention, the previously obtained fan blade surface stress data is coupled with the deformation characteristics of the blade for analysis. This process is mainly achieved through finite element analysis (FEA) using tools such as ABAQUS or ANSYS Mechanical. The specific operation is to input the previously obtained fan blade surface stress as an external force boundary condition into the finite element model, and perform structural deformation analysis in combination with the material properties, structural characteristics and geometric shape of the blade. The dynamic response of the blade is simulated to calculate the stress-deformation coupling degree of the blade, that is, the relationship between the deformation and stress distribution of the blade under the action of wind pressure and airflow. The core of this step is to determine the comprehensive performance of the blade under different fan models by numerically decoupling the aerodynamic stress and the deformation response of the blade, and finally obtain the fan blade surface stress-deformation coupling degree of the air flow field grid corresponding to different fan models.

[0118] Preferably, the degree of blade deformation of the air flow field grids corresponding to different fan models under the conditions of air flow velocity and wind pressure is calculated by grid deformation distribution gradient, so as to obtain the blade dynamic deformation distribution gradient of the air flow field grids corresponding to different fan models;

[0119] In an embodiment of the present invention, the dynamic deformation distribution gradient of the fan blades in the air flow field grid corresponding to different fan models is calculated under the action of airflow. To this end, the airflow velocity distribution and wind pressure conditions are first obtained using CFD software, and then these data are input into the deformation analysis module, and numerical methods such as finite difference method or finite element method are used to calculate the deformation degree and deformation gradient of the fan blades under different airflow velocities and wind pressure conditions. The gradient calculation is based on the dynamic response of the blades, and the deformation distribution of the entire fan blade surface is calculated taking into account the stress changes at different positions and at different times. The obtained dynamic deformation distribution gradient can accurately reflect the blade deformation characteristics of different fan models under the action of airflow, and finally the dynamic deformation distribution gradient of the fan blades corresponding to the air flow field grid of different fan models is obtained.

[0120] Preferably, the blade dynamic curvature evaluation calculation is performed on the corresponding fan three-dimensional model according to the blade surface stress-deformation coupling degree and the blade dynamic deformation distribution gradient of the air flow field grid corresponding to different fan models to obtain the blade dynamic curvature corresponding to different fan models.

[0121] In an embodiment of the present invention, a comprehensive mechanical model is used to evaluate the dynamic curvature of the blades of the three-dimensional fan model by combining the previously obtained stress-deformation coupling degree and the dynamic deformation distribution gradient. Specifically, ABAQUS or other advanced finite element software is used to establish a three-dimensional structural model of the fan blades, and the above-mentioned analysis results are used as input data. By establishing dynamic equations, the bending response of the fan blades under different working conditions is calculated. In this process, the curvature of the blades is evaluated by comparing the maximum deformation of the blades under the action of airflow with the initial shape, considering the influence of aerodynamic loads on the blades, evaluating the bending characteristics under different fan models, and finally obtaining the dynamic curvature of the fan blades corresponding to different fan models.

[0122] Further, step S235 includes the following steps:

[0123] Based on the fan blade airflow pressure distribution of the air flow field grid corresponding to different fan models, the fan blade airflow vibration response analysis is performed on the corresponding air flow field discretized grid, and the fan blade airflow vibration response data of the air flow field grid corresponding to different fan models are obtained;

[0124] In an embodiment of the present invention, the fan blade airflow pressure distribution of the air flow field grid corresponding to different fan models is obtained by combining the previous analysis, and the corresponding air flow field discretized grid is analyzed for the response of the fan blade airflow vibration condition. On this basis, the air flow is solved by CFD simulation. The force of the airflow is closely related to the vibration response of the fan blade. The pressure change of the airflow on the fan blade is the main factor causing the fan blade to vibrate. The finite element method (FEM) is used to solve the airflow vibration response of the blade by utilizing the airflow simulation results and based on the physical characteristics of the fan blade. The vibration response analysis obtains a time domain data containing multiple frequency components, and finally the fan blade airflow vibration response data of the air flow field grid corresponding to different fan models is obtained.

[0125] Preferably, the fan blade airflow vibration response data of the air flow field grids corresponding to different fan models are subjected to vibration frequency domain transformation processing to generate fan blade airflow vibration response spectra of the air flow field grids corresponding to different fan models;

[0126] In an embodiment of the present invention, frequency domain transformation processing is performed on the fan blade airflow vibration response data obtained from the previous analysis. First, the fast Fourier transform (FFT) algorithm is used to convert the vibration response data in the time domain into frequency domain data. FFT is a commonly used frequency domain analysis tool, which can effectively extract vibration information of multiple frequencies. In specific implementation, the vibration data is subjected to FFT processing using a signal processing tool in MATLAB or Python. After transformation processing, a vibration response spectrum containing different frequency components can be obtained. The vibration response spectrum reflects the vibration intensity at different frequencies. By analyzing the spectrum, the resonant frequency of the fan blade can be identified. For each grid of a different fan model, a corresponding airflow vibration response spectrum is generated. The amplitude of each frequency on the spectrum represents the vibration intensity at that frequency. Finally, fan blade airflow vibration response spectra corresponding to the air flow field grids of different fan models are generated.

[0127] Preferably, based on the blade airflow vibration response spectra of the air flow field grids corresponding to different fan models, the blade airflow vibration evaluation and analysis is performed on the corresponding fan three-dimensional model to obtain the blade airflow vibration frequencies corresponding to the different fan models.

[0128] In an embodiment of the present invention, a vibration evaluation analysis is performed on the fan blade airflow vibration response spectra of the air flow field grids corresponding to different fan models. In a specific implementation, the three-dimensional model of the fan is first imported into a finite element analysis (FEA) software, such as ANSYS or Abaqus, in combination with the vibration response spectrum to perform a vibration characteristic evaluation. The previous airflow vibration response spectrum is used as a boundary condition, and the natural modal frequency of the fan blade is matched with the airflow frequency to identify potential resonance phenomena. When evaluating the vibration, the structural characteristics of the fan blade, such as material properties, blade geometry, blade thickness, stiffness, etc., should be considered to calculate the vibration frequency of the fan blade under the action of the airflow, and finally the fan blade airflow vibration frequency corresponding to different fan models is obtained.

[0129] Furthermore, the fan airflow efficiency calculation in step S24 is quantitatively calculated by a fan airflow efficiency calculation formula, wherein the fan airflow efficiency calculation formula is specifically:

[0130] ;

[0131] In the formula, is the fan air flow efficiency, is the length of the fan blades of the fan model, is the spatial position parameter, is the time variable parameter, For the spatial position and time The corresponding air flow velocity is For the spatial position The cross-sectional area of ​​the fan blade at is the air density, For the spatial position The fan blade airflow vibration frequency at For the spatial position The dynamic curvature of the fan blade at For in time The corresponding fan inlet inlet velocity is: For the spatial position The fan inlet inlet cross-sectional area at It is the correction factor of fan air flow efficiency.

[0132] The present invention obtains a fan airflow efficiency calculation formula by using a specific mathematical model and verifying it, which is used to calculate the fan airflow efficiency for the corresponding aerodynamic simulation field. The fan airflow efficiency calculation formula calculates the fan's air flow efficiency through multiple variables (such as the dynamic curvature of the fan blades, the airflow vibration frequency, the airflow speed, etc.). This can not only reflect the speed and direction of the airflow, but also take into account the dynamic characteristics of the fan blades and the impact of airflow vibration on performance, and comprehensively evaluate the working effect of the fan. By introducing the dynamic characteristics of spatial and temporal changes, this means that the airflow speed and airflow vibration frequency of the fan may change with position and time during operation. This dynamic simulation can more accurately reflect the efficiency of the fan under real working conditions and avoid factors that cannot be considered in static calculations. Through the formula (cross-sectional area of ​​fan blades), Factors such as (dynamic curvature) can quantify the changes in blade shape, deformation, and impact on airflow. The curvature of the fan blade directly affects its aerodynamic performance at different speeds, reflects the deformation of the fan blade during operation, and provides a more accurate assessment of airflow efficiency. and The above terms take into account the airflow characteristics of the fan inlet. The air inlet is the key part where the airflow enters the fan. The speed and cross-sectional area of ​​the airflow will directly affect the airflow distribution and efficiency of the fan. The introduction of this factor can make the efficiency calculation of the fan more realistic and in line with the performance in actual use. In addition, the correction coefficient in the formula is an adjustment item for the air flow efficiency of the fan. It can be adjusted according to experimental data or specific conditions to ensure the accuracy of the calculation results in practical applications. For example, the efficiency can be fine-tuned according to the material, working environment, external airflow interference and other conditions of the fan to ensure that the formula is applicable to a wider range of situations. Through the above formula, the airflow efficiency of different fan models (for example, different designs such as size, blade shape, and speed) can be quantified and compared. Designers can obtain the efficiency of each fan model through simulation, thereby selecting the optimal design, reducing the workload of actual testing, and optimizing performance in the design stage. Since the formula provides an efficiency calculation method based on the dynamic behavior of airflow and fan blades, it can assist designers in optimizing the aerodynamic performance of the fan in the initial design stage. For example, by optimizing parameters such as the curvature of the fan blades, material selection, and fan blade angle, the airflow efficiency can be improved, thereby improving the overall performance of the fan. The fan airflow efficiency calculation formula essentially provides a mathematical framework for aerodynamic calculations in fluid mechanics, which can be well combined with CFD simulation. Through CFD software to simulate the airflow field and divide the grid, we can obtain data such as flow velocity and pressure at different positions and time points, and further use the formula to calculate the efficiency to achieve efficient fan performance evaluation. In summary, this formula fully considers the fan air flow efficiency. , fan model blade length , spatial position parameters , time variable parameter , in spatial position and time The corresponding air flow velocity , in spatial position The cross-sectional area of ​​the fan blade , air density , in spatial position The fan blade airflow vibration frequency at , in spatial position Dynamic bending of the fan blade at , at time The corresponding fan inlet inlet velocity , in spatial position The fan inlet inlet cross-sectional area at , correction factor for fan air flow efficiency , based on the fan air flow efficiency The correlation between the above parameters constitutes a functional relationship This formula can realize the calculation process of fan airflow efficiency for the corresponding aerodynamic simulation field. At the same time, the correction coefficient of fan air flow efficiency is The introduction of can be adjusted according to the error conditions that occur during the calculation process, thereby improving the accuracy and applicability of the fan airflow efficiency calculation formula.

[0133] Further, step S3 includes the following steps:

[0134] Step S31: performing an operation acoustic dynamic simulation analysis on the corresponding three-dimensional fan model under different design parameters and constraint conditions to generate a fan operation acoustic simulation field corresponding to different fan models;

[0135] In an embodiment of the present invention, acoustic dynamic simulation analysis is performed on multiple fan design models under different design parameters (such as the number of blades, blade shape, blade angle, etc.) and constraints (such as wind speed range, power requirement, and noise requirement, etc.). To this end, computational fluid dynamics (CFD) and acoustic simulation software, such as ANSYS, COMSOL Multiphysics and other tools, are used to simulate the aerodynamic and acoustic fields of the fan. Three-dimensional geometric models of different fan designs are created in the software, and then corresponding working conditions, such as the rotation speed, air density, temperature, pressure, etc. of the fan are set. The CFD module is used to simulate the interaction between the fan blades and the airflow, and the airflow field distribution is calculated. The acoustic simulation module is further used to analyze the distribution and intensity of the noise sources generated under the airflow field, and the acoustic characteristics of different fan models during operation are obtained, and the acoustic simulation field data of the fan is formed, and finally the fan operation acoustic simulation field corresponding to the different fan models is generated.

[0136] Step S32: dividing the acoustic noise source frequency bands of the fan operation acoustic simulation fields corresponding to different fan models to obtain the fan operation acoustic noise source frequency bands corresponding to different fan models;

[0137] In an embodiment of the present invention, the frequency bands of noise sources are divided based on the previously obtained fan operation acoustic simulation field. The specific method is to use acoustic analysis software (such as MATLAB, LMS Virtual Lab, etc.) to perform Fourier transform on the acoustic data obtained in the simulation field to decompose the noise of different frequency components. First, the frequency range of the analysis is determined, and a reasonable frequency band is selected according to the rotation speed and aerodynamic characteristics of the fan. The obtained sound pressure data is processed by using a spectrum analysis tool to divide the frequency bands of various noise sources, such as low frequency, medium frequency and high frequency. The noise source characteristics corresponding to each frequency band reflect the noise source and its intensity of the fan under different operating conditions, and finally the fan operation acoustic noise source frequency bands corresponding to different fan models are obtained.

[0138] Step S33: performing noise propagation simulation on the fan operation acoustic noise source frequency bands corresponding to different fan models to generate fan operation acoustic noise propagation paths corresponding to the noise source frequency bands of different fan models; performing propagation attenuation characteristic analysis on the fan operation acoustic noise propagation paths corresponding to the noise source frequency bands of different fan models to obtain fan acoustic noise propagation attenuation characteristics of the operation acoustic noise propagation paths corresponding to different fan models;

[0139] In an embodiment of the present invention, noise propagation simulation is performed based on the previously divided frequency band of the fan operation acoustic noise source, the propagation path and attenuation characteristics of noise in different frequency bands in the air are analyzed, and the propagation process of noise from the fan sound source to the environment is simulated by an acoustic propagation model (for example, based on acoustic ray tracing, boundary element method BEM, finite element method FEM, etc.), thereby generating fan operation acoustic noise propagation paths corresponding to the noise source frequency bands of different fan models. At the same time, by using corresponding simulation software, such as the acoustic module in ACTRAN or COMSOL Multiphysics, the parameters of the propagation medium (air) are set, and the attenuation characteristics (including sound absorption, scattering, reflection and other effects) of the fan operation acoustic noise propagation paths corresponding to different frequency bands when propagating in the air are considered. During the simulation process, the sound wave propagation paths of different fan models in different frequency bands are compared to identify the propagation paths of noise in different frequency bands, thereby obtaining the propagation attenuation characteristics corresponding to the noise source frequency band, and finally obtaining the fan acoustic noise propagation attenuation characteristics corresponding to the operation acoustic noise propagation paths of different fan models.

[0140] Step S34: performing full-band acoustic noise evaluation and analysis on the corresponding three-dimensional fan model based on the fan acoustic noise propagation attenuation characteristics of the operating acoustic noise propagation paths corresponding to different fan models, and obtaining the fan operating acoustic noise levels corresponding to the different fan models;

[0141] In an embodiment of the present invention, based on the noise propagation attenuation characteristics obtained from the previous analysis, the full-band noise level of the fan is further evaluated and analyzed, so as to combine the propagation path and attenuation characteristics of the noise source frequency band by using an acoustic evaluation tool (such as NoiseMap or Odeon, etc.) to perform a full-band noise evaluation. By calculating the sound power level, sound pressure level and other parameters of each frequency band, the noise source data of each frequency band is integrated to obtain the acoustic noise level of the fan in the full frequency band, and finally obtain the fan operation acoustic noise level corresponding to different fan models.

[0142] Step S35: Perform performance curve simulation analysis according to the fan air flow efficiency and the fan operation acoustic noise level corresponding to different fan models to generate airflow efficiency-noise performance curves corresponding to different fan models.

[0143] In an embodiment of the present invention, a simulation analysis of a performance curve is performed based on the previously obtained acoustic noise level of the fan operation and the air flow efficiency of the fan. The specific operation is to combine CFD with acoustic noise simulation to model the relationship between airflow efficiency and noise, simulate various working conditions of the fan in CFD software, calculate its airflow efficiency (i.e., the ratio of air volume to power consumption) under different working conditions, and draw a relationship curve between airflow efficiency and noise by combining the airflow efficiency under each working condition with the obtained noise level. Through simulation analysis under different design parameters and operating conditions, an airflow efficiency-noise performance curve is generated to help optimize the fan design and balance performance and noise output. The curve can provide designers with important decision-making basis to ensure that the fan reduces the noise level as much as possible while meeting the air flow efficiency requirements, and finally generate airflow efficiency-noise performance curves corresponding to different fan models.

[0144] Further, step S4 includes the following steps:

[0145] Step S41: obtaining fan constraint optimization targets corresponding to different fan models through corresponding fan three-dimensional models under different design parameters and constraint conditions, wherein the fan constraint optimization targets include maximizing fan power and minimizing fan operation noise;

[0146] In an embodiment of the present invention, multiple three-dimensional fan models are established for different design parameters and constraints (such as rotation speed, blade angle, air inlet design, etc.) through computational fluid dynamics (CFD) simulation or similar simulation tools. Each fan model must meet certain design restrictions and operating constraints, such as the allowable power range and noise limit. For each fan model, simulation software is used to predict the performance of wind force and noise, and the power output and operating noise value of each fan model are calculated. Through multiple simulations, the power maximization and noise minimization goals of each fan model are obtained. These goals are used for further optimization calculations. Specifically, the power maximization goal is to maximize the power output of the fan without exceeding the agreed power upper limit, while the noise minimization goal is to minimize the noise generated by the fan during operation while meeting the power requirements. Finally, the fan constraint optimization goals corresponding to different fan models are obtained.

[0147] Step S42: obtaining fan working energy efficiency performance values ​​corresponding to different fan models at each time point according to airflow efficiency-noise performance curves corresponding to different fan models;

[0148] In an embodiment of the present invention, the airflow efficiency and noise data of the fan under different working conditions are simulated for each fan model. This process is usually completed using CFD software in combination with an acoustic simulation module. Different working conditions (such as fan speed, airflow, etc.) are set, and the simulation is run to record the airflow efficiency and noise level under each working condition. Airflow efficiency refers to the ability of the fan to effectively convert airflow kinetic energy under a certain energy input, while noise is the sound waves generated by the interaction between the blades and the airflow during the rotation of the fan. Through these simulation data, the airflow efficiency-noise performance curve of each fan model under different working conditions is drawn, the working performance at different time points is recorded, and the working energy efficiency performance score at each time point is quantitatively calculated based on the corresponding airflow efficiency and noise level, that is, , and finally obtain the fan working energy efficiency performance values ​​corresponding to different fan models at each time point.

[0149] Step S43: calculating the energy efficiency ratio of the corresponding three-dimensional fan model based on the fan working energy efficiency performance values ​​corresponding to the different fan models at each time point, so as to obtain the fan working timing energy efficiency ratios corresponding to the different fan models; drawing timing curves according to the fan working timing energy efficiency ratios corresponding to the different fan models, so as to generate fan timing energy efficiency ratio curves corresponding to the different fan models;

[0150] In an embodiment of the present invention, the energy efficiency ratio of the corresponding fan three-dimensional model is quantitatively calculated at each time point by combining the previously quantified corresponding fan working energy efficiency performance value at each time point, so as to use the energy efficiency performance ratio between the fan working energy efficiency performance value corresponding to the current time point and the fan working energy efficiency performance value corresponding to the previous time point as the energy efficiency ratio value at the current time point, thereby obtaining the fan working time series energy efficiency ratio corresponding to different fan models. At the same time, by performing time series analysis on the energy efficiency ratio value of each fan model, an energy efficiency change curve of the fan model in the entire working cycle is generated. Specifically, the energy efficiency ratio of each time point previously obtained is used as a data point, which is connected in sequence to form a complete time series energy efficiency ratio curve. This curve reflects the change trend of the fan energy efficiency during the entire working process. For example, as time goes by, whether the efficiency of the fan remains stable, whether there is fluctuation, or whether there is energy efficiency attenuation. The drawing of the time series curve is usually completed by professional data analysis tools. These tools can process and visualize a large amount of time series data, and finally generate fan time series energy efficiency ratio curves corresponding to different fan models.

[0151] Step S44: performing fan energy efficiency optimization calculation on the fan timing energy efficiency ratio curves corresponding to different fan models based on the fan constraint optimization targets corresponding to different fan models, and obtaining fan constraint energy efficiency optimization values ​​corresponding to different fan models;

[0152] In an embodiment of the present invention, the energy efficiency optimization calculation of the fan model is performed on the previously drawn and generated sequential energy efficiency ratio curve by combining the corresponding fan constraint optimization target. The specific operation is to optimize the fan sequential energy efficiency ratio curve through the defined optimization target in combination with the fan's power, noise, airflow efficiency and other performance indicators. This process usually requires the use of a mathematical optimization algorithm (such as a genetic algorithm, a particle swarm optimization or a gradient descent method) to find the optimal combination of working parameters and maximize the energy efficiency ratio while ensuring that the fan performance indicators meet the design requirements. The optimization objective function can comprehensively consider the fan's power, noise, energy efficiency and other factors, and adjust the priority through weights. After optimization calculation, the energy efficiency optimization value corresponding to each fan model is obtained, and finally the fan constraint energy efficiency optimization values ​​corresponding to different fan models are obtained.

[0153] Step S45: performing model optimization design on the corresponding fan three-dimensional model based on the fan constraint energy efficiency optimization values ​​corresponding to different fan models to generate a fan optimization model.

[0154] In an embodiment of the present invention, a computer-aided design (CAD) tool is used to optimize the design of a three-dimensional fan model by combining the previously quantified fan constraint energy efficiency optimization value, so as to compare the energy efficiency optimization value of each fan model with its design parameters (such as blade angle, rotation speed, etc.), confirm which design parameters need to be adjusted, and then modify the three-dimensional geometric model of the fan through CAD software, including the shape, thickness, angle and other design details of the blades, so that the fan can achieve higher energy efficiency under the optimization goal. The fan optimization design is not limited to shape adjustment, but also includes material selection and manufacturing process improvement. The performance of the new design model is verified through simulation analysis to ensure that the optimized fan model can provide higher energy efficiency and lower noise while meeting the constraint conditions, and finally optimize and generate a fan optimization model.

[0155] Furthermore, the present invention also provides a fan model generation system, which is used to execute the fan model generation method as described above, and the fan model generation system includes:

[0156] The fan model preliminary simulation generation module is used to obtain the basic design parameters of the fan and the fan constraints, where the basic design parameters of the fan include the number of blades, blade length and rotation angle, and the fan constraints include wind speed range, power demand and noise requirement; the fan model is simulated and generated according to the basic design parameters of the fan and the fan constraints, so as to generate the corresponding three-dimensional fan model under different design parameters and constraints;

[0157] The dynamic simulation airflow efficiency calculation module is used to perform aerodynamic simulation on the corresponding three-dimensional fan model under different design parameters and constraint conditions to generate aerodynamic simulation fields corresponding to different fan models; perform blade dynamic curvature and airflow vibration evaluation and analysis on the aerodynamic simulation fields corresponding to different fan models to obtain the blade dynamic curvature and blade airflow vibration frequency corresponding to different fan models; calculate the fan airflow efficiency of the corresponding aerodynamic simulation field based on the blade dynamic curvature and blade airflow vibration frequency corresponding to different fan models, thereby obtaining the fan air flow efficiency corresponding to different fan models;

[0158] The fan model performance curve simulation module is used to evaluate and analyze the operation acoustic noise of the corresponding three-dimensional fan model under different design parameters and constraints, and obtain the fan operation acoustic noise level corresponding to different fan models; the performance curve simulation analysis is performed according to the fan air flow efficiency and fan operation acoustic noise level corresponding to different fan models to generate the airflow efficiency-noise performance curve corresponding to different fan models;

[0159] The fan model sequential energy efficiency ratio optimization module is used to obtain the corresponding fan constraint optimization target through the corresponding fan three-dimensional model under different design parameters and constraint conditions, and to perform sequential energy efficiency ratio optimization design on the corresponding fan three-dimensional model based on the fan constraint optimization targets corresponding to different fan models and the airflow efficiency-noise performance curve to generate a fan optimization model.

[0160] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0161] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for generating a fan model, characterized in that: The following steps are involved: Step S1: Obtaining basic design parameters and fan constraints of the fan, wherein the basic design parameters of the fan include the number of blades, blade length and rotation angle, and the fan constraints include wind speed range, power requirement and noise requirement; performing fan model simulation generation according to the basic design parameters of the fan and the fan constraints, and generating corresponding three-dimensional fan models under different design parameters and constraints; Step S2: performing aerodynamic simulation on the corresponding three-dimensional fan models under different design parameters and constraints to generate aerodynamic simulation fields corresponding to different fan models; performing blade dynamic curvature and airflow vibration evaluation and analysis on the aerodynamic simulation fields corresponding to different fan models to obtain blade dynamic curvature and blade airflow vibration frequency corresponding to different fan models; performing fan airflow efficiency calculation on the corresponding aerodynamic simulation fields based on the blade dynamic curvature and blade airflow vibration frequency corresponding to different fan models to obtain fan airflow efficiency corresponding to different fan models; Step S3: performing an operation acoustic noise evaluation analysis on the corresponding three-dimensional fan models under different design parameters and constraints to obtain the fan operation acoustic noise levels corresponding to different fan models; performing a performance curve simulation analysis based on the fan airflow efficiency and the fan operation acoustic noise levels corresponding to different fan models to generate airflow efficiency-noise performance curves corresponding to different fan models; Step S4: Obtain corresponding fan constraint optimization targets through corresponding fan three-dimensional models under different design parameters and constraint conditions, and perform sequential energy efficiency ratio optimization design on the corresponding fan three-dimensional models based on the fan constraint optimization targets corresponding to different fan models and the airflow efficiency-noise performance curves to generate a fan optimization model. Step S4 includes the following steps: Step S41: obtaining fan constraint optimization targets corresponding to different fan models through corresponding fan three-dimensional models under different design parameters and constraint conditions, wherein the fan constraint optimization targets include maximizing fan power and minimizing fan operation noise; Step S42: obtaining fan working energy efficiency performance values ​​corresponding to different fan models at each time point according to airflow efficiency-noise performance curves corresponding to different fan models; Step S43: calculating the energy efficiency ratio of the corresponding three-dimensional fan model based on the fan working energy efficiency performance values ​​corresponding to the different fan models at each time point, so as to obtain the fan working timing energy efficiency ratios corresponding to the different fan models; drawing timing curves according to the fan working timing energy efficiency ratios corresponding to the different fan models, so as to generate fan timing energy efficiency ratio curves corresponding to the different fan models; Step S44: performing fan energy efficiency optimization calculation on the fan timing energy efficiency ratio curves corresponding to different fan models based on the fan constraint optimization targets corresponding to different fan models, and obtaining fan constraint energy efficiency optimization values ​​corresponding to different fan models; Step S45: performing model optimization design on the corresponding fan three-dimensional model based on the fan constraint energy efficiency optimization values ​​corresponding to different fan models to generate a fan optimization model.

2. The method for generating a fan model according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: obtaining basic design parameters and fan constraints of the fan through a graphical interface input, wherein the basic design parameters of the fan include the number of blades, blade length and rotation angle, and the fan constraints include wind speed range, power requirement and noise requirement; Step S12: performing fan simulation combination design according to the basic fan design parameters and the fan constraint conditions to generate different fan design parameter and constraint condition simulation combinations; Step S13: Perform fan model simulation generation according to different fan design parameters and constraint condition simulation combinations to generate corresponding fan three-dimensional models under different design parameters and constraint conditions.

3. The method for generating a fan model according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: performing aerodynamic simulation on the corresponding three-dimensional fan models under different design parameters and constraint conditions to generate aerodynamic simulation fields corresponding to different fan models; Step S22: performing airflow field grid division on the aerodynamic simulation fields corresponding to different fan models to obtain air flow field discretization grids corresponding to different fan models; Step S23: Based on the air flow field discretization grids corresponding to different fan models, the corresponding three-dimensional fan models are evaluated and analyzed for the dynamic curvature of the fan blades and the airflow vibration frequency of the fan blades, so as to obtain the dynamic curvature of the fan blades and the airflow vibration frequency of the fan blades corresponding to the different fan models; Step S24: Calculate the fan airflow efficiency of the corresponding aerodynamic simulation field based on the dynamic curvature of the fan blades and the airflow vibration frequency of the fan blades corresponding to different fan models to obtain the fan airflow efficiency corresponding to different fan models.

4. The method for generating a fan model according to claim 3, characterized in that: Step S23 includes the following steps: Step S231: performing fan blade airflow pressure distribution analysis on the air flow field discretization grids corresponding to different fan models to obtain fan blade airflow pressure distribution of the air flow field grids corresponding to different fan models; Step S232: analyzing the air flow velocity and wind pressure action of the air flow field grids corresponding to the fan models according to the fan blade air flow pressure distribution of the air flow field grids corresponding to the different fan models, so as to obtain the fan blade air flow velocity and wind pressure action of the air flow field grids corresponding to the different fan models; Step S233: performing a blade deformation analysis on the air flow field grids corresponding to the fan models based on the blade air flow velocity and wind pressure force of the air flow field grids corresponding to the different fan models, and obtaining the blade deformation degree of the air flow field grids corresponding to the different fan models under the conditions of air flow velocity and wind pressure; Step S234: performing blade dynamic curvature evaluation and calculation on the corresponding three-dimensional fan model according to the degree of blade deformation of the air flow field grids corresponding to different fan models under the conditions of air flow velocity and wind pressure, and obtaining the blade dynamic curvature corresponding to different fan models; Step S235: Based on the fan blade airflow pressure distribution of the air flow field grid corresponding to different fan models, the corresponding fan three-dimensional model is evaluated and analyzed to obtain the fan blade airflow vibration frequency corresponding to the different fan models.

5. The method for generating a fan model according to claim 4, characterized in that: Step S234 includes the following steps: Perform aerodynamic stress analysis on the fan blade surface in the air flow field discretization grid corresponding to different fan models to obtain the fan blade surface dynamic stress in the air flow field grid corresponding to different fan models; Based on the dynamic stress of the fan blade surface of the air flow field grid corresponding to different fan models, the fan blade stress-deformation coupling analysis is performed on the fan blade surface in the air flow field discretization grid corresponding to different fan models to obtain the fan blade surface stress-deformation coupling degree of the air flow field grid corresponding to different fan models; The blade deformation degree of the air flow field grids corresponding to different fan models under the conditions of air flow velocity and wind pressure is calculated by grid deformation distribution gradient, and the blade dynamic deformation distribution gradient of the air flow field grids corresponding to different fan models is obtained; According to the blade surface stress-deformation coupling degree and blade dynamic deformation distribution gradient of the air flow field grid corresponding to different fan models, the blade dynamic curvature evaluation and calculation are performed on the corresponding fan three-dimensional model to obtain the blade dynamic curvature corresponding to different fan models.

6. The method for generating a fan model according to claim 4, characterized in that: Step S235 includes the following steps: Based on the fan blade airflow pressure distribution of the air flow field grid corresponding to different fan models, the fan blade airflow vibration response analysis is performed on the corresponding air flow field discretization grid, and the fan blade airflow vibration response data of the air flow field grid corresponding to different fan models are obtained; Performing vibration frequency domain transformation processing on the fan blade airflow vibration response data of the air flow field grids corresponding to different fan models to generate fan blade airflow vibration response spectra of the air flow field grids corresponding to different fan models; Based on the blade airflow vibration response spectra of the air flow field grids corresponding to different fan models, the blade airflow vibration evaluation and analysis of the corresponding fan three-dimensional model is performed to obtain the blade airflow vibration frequencies corresponding to different fan models.

7. The method for generating a fan model according to claim 3, characterized in that: The fan airflow efficiency calculation in step S24 is quantitatively calculated by a fan airflow efficiency calculation formula, wherein the fan airflow efficiency calculation formula is specifically: ； In the formula, is the fan airflow efficiency, is the length of the fan blade of the fan model, is the spatial position parameter, is the time variable parameter, For the spatial position and time The corresponding air flow velocity is For the spatial position The cross-sectional area of ​​the fan blade at is the air density, For the spatial position The fan blade airflow vibration frequency at For the spatial position The dynamic curvature of the fan blade at For in time The corresponding fan inlet inlet velocity is: For the spatial position The fan inlet cross-sectional area at is the correction factor for the fan airflow efficiency.

8. The method for generating a fan model according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: performing an operation acoustic dynamic simulation analysis on the corresponding three-dimensional fan model under different design parameters and constraint conditions to generate a fan operation acoustic simulation field corresponding to different fan models; Step S32: dividing the acoustic noise source frequency bands of the fan operation acoustic simulation fields corresponding to different fan models to obtain the fan operation acoustic noise source frequency bands corresponding to different fan models; Step S33: performing noise propagation simulation on the fan operation acoustic noise source frequency bands corresponding to different fan models to generate fan operation acoustic noise propagation paths corresponding to the noise source frequency bands of different fan models; performing propagation attenuation characteristic analysis on the fan operation acoustic noise propagation paths corresponding to the noise source frequency bands of different fan models to obtain fan acoustic noise propagation attenuation characteristics of the operation acoustic noise propagation paths corresponding to different fan models; Step S34: performing full-band acoustic noise evaluation and analysis on the corresponding three-dimensional fan model based on the fan acoustic noise propagation attenuation characteristics of the operating acoustic noise propagation paths corresponding to different fan models, and obtaining the fan operating acoustic noise levels corresponding to the different fan models; Step S35: performing performance curve simulation analysis according to the fan airflow efficiency and the fan operation acoustic noise level corresponding to different fan models, so as to generate airflow efficiency-noise performance curves corresponding to different fan models.

9. A system for generating a fan model, characterized in that: For executing the method for generating a fan model as claimed in claim 1, the system for generating a fan model comprises: The fan model preliminary simulation generation module is used to obtain the basic design parameters of the fan and the fan constraints, where the basic design parameters of the fan include the number of blades, blade length and rotation angle, and the fan constraints include wind speed range, power demand and noise requirement; the fan model is simulated and generated according to the basic design parameters of the fan and the fan constraints, so as to generate the corresponding three-dimensional fan model under different design parameters and constraints; The dynamic simulation airflow efficiency calculation module is used to perform aerodynamic simulation on the corresponding three-dimensional fan model under different design parameters and constraint conditions to generate aerodynamic simulation fields corresponding to different fan models; perform blade dynamic curvature and airflow vibration evaluation and analysis on the aerodynamic simulation fields corresponding to different fan models to obtain the blade dynamic curvature and blade airflow vibration frequency corresponding to different fan models; calculate the fan airflow efficiency of the corresponding aerodynamic simulation field based on the blade dynamic curvature and blade airflow vibration frequency corresponding to different fan models, thereby obtaining the fan airflow efficiency corresponding to different fan models; The fan model performance curve simulation module is used to evaluate and analyze the operation acoustic noise of the corresponding three-dimensional fan model under different design parameters and constraints, and obtain the fan operation acoustic noise level corresponding to different fan models; the performance curve simulation analysis is performed according to the fan airflow efficiency and fan operation acoustic noise level corresponding to different fan models to generate the airflow efficiency-noise performance curve corresponding to different fan models; The fan model sequential energy efficiency ratio optimization module is used to obtain the corresponding fan constraint optimization target through the corresponding fan three-dimensional model under different design parameters and constraint conditions, and to perform sequential energy efficiency ratio optimization design on the corresponding fan three-dimensional model based on the fan constraint optimization targets corresponding to different fan models and the airflow efficiency-noise performance curve to generate a fan optimization model.

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