Method, device, equipment and computer storage medium for blade design

Abstract

The present disclosure provides a blade profile design method, apparatus, device, and computer storage medium, relating to the field of blade design. The method comprises: forming a first blade profile of a blade using a first blade profile scheme; optimizing the first blade profile based on aerodynamic performance indicators to obtain an optimized first blade profile; describing the optimized first blade profile using design parameters from a second blade profile scheme to obtain a second blade profile; and optimizing the second blade profile to form an optimal blade profile. The present disclosure improves blade profile design efficiency while enhancing the operating performance of the designed blade profile.

Description

Technical Field

[0001] The present disclosure relates to the field of blade design, and in particular to a method, device, equipment and computer storage medium for blade profile design. Background Art

[0002] Currently, blades are widely used in many technical fields, especially in fluid machinery such as aircraft engines, wind turbines, and pumps. The blade shape directly affects the mechanical performance of the blade and the efficiency of fluid flow.

[0003] In the process of designing the blade profile, a design scheme is needed that can improve the blade profile development efficiency and enhance the blade profile performance. Summary of the Invention

[0004] The present disclosure provides a method, device, equipment and computer storage medium for blade design, which can improve the efficiency of blade design while enhancing the operating performance of the designed blade.

[0005] The technical solution of the present disclosure is achieved as follows:

[0006] In a first aspect, the present disclosure provides a method for blade profile design, the method comprising:

[0007] forming a first blade profile of the blade using a first blade profile scheme;

[0008] Optimizing the first blade profile based on aerodynamic performance indicators to obtain an optimized first blade profile;

[0009] Describing the optimized first blade profile using design parameters in a second blade profile solution to obtain a second blade profile; wherein the complexity of the second blade profile solution is higher than that of the first blade profile solution;

[0010] The second blade profile is optimized to form an optimal blade profile of the blade.

[0011] In a second aspect, the present disclosure provides a device for blade profile design, comprising: a forming part, a first optimization part, a conversion part, and a second optimization part, wherein:

[0012] The forming portion is configured to form a first blade profile of the blade using a first blade profile scheme;

[0013] The first optimization part is configured to optimize the first blade profile based on an aerodynamic performance index to obtain an optimized first blade profile;

[0014] The conversion portion is configured to describe the optimized first blade profile using design parameters in a second blade profile solution to obtain a second blade profile; wherein the complexity of the second blade profile solution is higher than that of the first blade profile solution;

[0015] The second optimization part is configured to optimize the second blade profile to form an optimal blade profile of the blade.

[0016] In a third aspect, the present disclosure provides a computing device comprising a processor and a memory; the processor is configured to execute instructions stored in the memory to implement the blade profile design method as described in the first aspect.

[0017] In a fourth aspect, the present disclosure provides a computer storage medium storing at least one instruction, wherein the at least one instruction is configured to be executed by a processor to implement the airfoil design method according to the first aspect.

[0018] The present disclosure provides a method, apparatus, device, and computer storage medium for blade profile design. First, a first blade profile of a blade is obtained and optimized using a first blade profile scheme with lower complexity, thereby quickly eliminating a large number of non-optimal regions to find a preliminary, more preferred blade profile. A second blade profile scheme with higher complexity is then used to further optimize the optimized first blade profile, rather than optimizing the original blade profile. This improves blade profile design efficiency while enhancing the blade's aerodynamic performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A schematic flow chart of a blade profile design method provided in the present disclosure.

[0020] Figure 2 The present invention provides a schematic diagram of a specific implementation process of the blade profile design method.

[0021] Figure 3 A schematic diagram of a first airfoil provided in the present disclosure.

[0022] Figure 4 A schematic diagram of the optimized first blade profile provided by the present disclosure.

[0023] Figure 5 A schematic diagram of the conversion from a first blade profile to a Bezier curve blade profile provided in the present disclosure.

[0024] Figure 6 A schematic diagram of a process for converting an optimized first blade profile into a second blade profile is provided in the present disclosure.

[0025] Figure 7 This is a schematic diagram of the implementation process of constructing an n-order Bezier curve using the Bezier curve interpolation algorithm provided by the present disclosure.

[0026] Figure 8 An exemplary graph diagram is provided for the present disclosure.

[0027] Figure 9 A schematic diagram of obtaining a root mean square error provided by the present disclosure.

[0028] Figure 10 Another schematic diagram of obtaining the root mean square error provided by the present disclosure.

[0029] Figure 11 A schematic diagram of the device composition of a blade profile design provided in the present disclosure.

[0030] Figure 12 A schematic diagram of the structure of a computing device provided by the present disclosure. DETAILED DESCRIPTION

[0031] The technical solutions in the present disclosure will be described clearly and completely below with reference to the accompanying drawings in the present disclosure.

[0032] In this disclosure, a blade's profile refers to the geometric shape of a blade's cross-section projected onto a plane. Specifically, it can be the two-dimensional shape of a blade at a specific cross-section (the cross-section of the blade at a certain position along the blade's span, from root to tip). This geometry directly influences the flow behavior of fluid over the blade's surface, thereby determining the blade's aerodynamic performance, energy conversion efficiency, and overall equipment reliability.

[0033] During the blade design process, only one blade profile is typically adopted, such as the double-arc blade, multi-arc blade, NACA blade, camber-thickness blade, Pritchard blade, symmetrical blade, and Bezier curve blade. Each of these blade profiles has its own unique blade parameters, geometric construction principles, and corresponding aerodynamic characteristics, resulting in advantages and limitations in terms of performance and applicable operating conditions.

[0034] For example, the pressure and suction curves of a double-arc blade are both composed of simple arcs. This makes design optimization and adjustment relatively intuitive and simple by dragging characteristic points on the arcs to modify the curves, but it also reduces flexibility. However, due to the limitations of its geometric shape, the aerodynamic performance of a double-arc blade is generally limited, especially in complex flow conditions. It is more suitable for high-speed airflow environments.

[0035] In a Bezier blade profile, the shape of the curve can be finely controlled by adjusting the positions of the control points and the order of the curve, providing greater design freedom and flexibility. This also makes the process of implementing the blade profile using the Bezier curve more complex and requires a longer optimization and adjustment cycle, but it can adapt to a variety of complex operating conditions and achieve high aerodynamic performance.

[0036] Comparing the advantages and disadvantages of the double-arc blade profile and the Bezier curve above shows that the double-arc blade profile has a simple design process and can quickly generate a blade profile, but the design process is relatively inflexible, resulting in limited aerodynamic performance. While the Bezier curve is highly flexible and can achieve high aerodynamic performance, its design complexity prolongs the optimization cycle. Consequently, the current traditional blade profile design process struggles to balance design efficiency and aerodynamic performance.

[0037] In order to obtain a more excellent blade profile within the same design cycle, the present disclosure integrates and switches different blade profile schemes during the blade profile design process, hoping to improve the blade profile design efficiency and the aerodynamic performance of the blade by combining the advantages of different blade profile schemes, so that a more excellent blade profile design can be obtained within a limited design cycle. Based on this, the present disclosure provides a blade profile design method, see Figure 1 , the method may include:

[0038] S101: forming a first blade profile of a blade using a first blade profile solution;

[0039] Each blade profile scheme describes the two-dimensional shape of the blade on a specific cross section through corresponding design parameters. In the present disclosure, the design parameters of the first blade profile scheme can be used to describe the two-dimensional shape of the blade on a specific cross section, thereby forming the first blade profile of the blade.

[0040] Furthermore, for each blade profile solution, the blade profile can be adjusted and optimized by adjusting the design parameters. Therefore, the more design parameters a blade profile solution corresponds to, the more complex the blade profile adjustment and optimization becomes. In other words, the number of design parameters is correlated with the complexity of blade profile optimization and adjustment. In the present disclosure, the number of design parameters corresponding to each blade profile solution can represent the complexity of the blade profile solution.

[0041] S102: Optimizing the first blade profile based on the aerodynamic performance index to obtain an optimized first blade profile.

[0042] In the present disclosure, after obtaining a first blade profile, a flow field calculation can be performed on the first blade profile to simulate the behavior of fluid passing through the blade passage, thereby obtaining aerodynamic performance data on the blade surface. In some examples, computational fluid dynamics (CFD) mesh data for the first blade profile can be generated. Subsequently, the behavior of fluid passing through the blade passage can be simulated based on the CFD mesh data of the first blade profile to obtain aerodynamic performance data on the blade surface. In some examples, the aerodynamic performance data can illustratively include, for example, pressure distribution, velocity loads, and aerodynamic loads.

[0043] After obtaining the aerodynamic performance data, the aerodynamic performance indicators of the first blade profile, such as efficiency, losses, and pressure fluctuations, are evaluated based on the aerodynamic performance data. Subsequently, the design parameters of the first blade profile are adjusted based on the aerodynamic performance indicators to optimize the aerodynamic performance indicators. During the aerodynamic performance optimization process, the design parameters are iterated until the aerodynamic performance indicators stabilize, thereby obtaining the optimized first blade profile.

[0044] S103: Describing the optimized first blade profile using design parameters in the second blade profile solution to obtain a second blade profile.

[0045] In the present disclosure, the complexity of the second blade profile is higher than that of the first blade profile. In other words, the number of design parameters of the second blade profile is greater than that of the first blade profile. The description process of this step can be considered as the process of fitting the optimized first blade profile using the second blade profile.

[0046] It should be noted that as the number of design parameters increases, the second blade profile scheme will have more degrees of freedom to describe the blade shape. Compared with the first blade profile scheme, the second blade profile scheme has enhanced the ability to describe complex curves and can make more subtle and local adjustments to the blade profile, thereby making it possible to describe a wider variety of blade shapes. In addition, since the aerodynamic performance of the blade is very sensitive to the shape of the blade profile, that is, even small changes in the geometric shape may have a significant impact on the flow field, therefore, when the number of design parameters increases and there are more degrees of freedom to describe the blade shape, compared with the first blade profile, the second blade profile can be more finely adjusted to match the more complex flow field, thereby achieving higher aerodynamic performance. In summary, the higher the complexity, the more design parameters can be adjusted during the optimization process, the more finely the blade profile can be optimized, and more refined blade profile optimization can also lead to further improvements in aerodynamic performance indicators.

[0047] S104: Optimize the second blade profile to form an optimal blade profile.

[0048] In the present disclosure, after obtaining the second blade profile, flow field calculations can be performed on the second blade profile to simulate the behavior of fluid passing through the blade passage, thereby obtaining aerodynamic performance data on the blade surface. In some examples, computational fluid dynamics (CFD) mesh data for the second blade profile can be generated. Subsequently, the behavior of fluid passing through the blade passage can be simulated based on the CFD mesh data of the second blade profile to obtain aerodynamic performance data on the blade surface. In some examples, the aerodynamic performance data can illustratively include, for example, pressure distribution, velocity loads, and aerodynamic loads.

[0049] After obtaining the aerodynamic performance data, the aerodynamic performance indicators of the second blade profile, such as efficiency, loss, and pressure fluctuation, are evaluated based on the aerodynamic performance data. Subsequently, the design parameters of the second blade profile are adjusted based on the aerodynamic performance indicators to optimize the aerodynamic performance indicators. During the aerodynamic performance optimization process, the design parameters are iterated until the aerodynamic performance indicators stabilize, thereby obtaining the final optimized second blade profile, i.e., the optimal blade profile described in step S104.

[0050] It should be noted that the optimization process for the second blade profile is similar to that for the first blade profile. However, because the second blade profile has a larger number of design parameters, the optimization process allows for more precise adjustment of the blade profile shape to match a more complex flow field, thereby achieving higher aerodynamic performance. In this disclosure, the optimization process for the first blade profile may be referred to as coarse optimization, and the optimization process for the second blade profile may be referred to as fine optimization.

[0051] In addition, in the fine optimization process, the parameter space that needs to be searched in each iteration is larger than that in the coarse optimization process, which leads to the consumption of computing resources and the optimization cycle required by the fine optimization process being greater than that in the coarse optimization process. Figure 1 The blade profile design method shown in the figure first uses a coarse optimization process to quickly find a preliminary and relatively preferred blade profile (the first blade profile after optimization). Then, based on this relatively preferred blade profile, a more refined fine optimization process is used to find the optimal blade profile with better performance. Compared with using only the coarse optimization process to design the blade profile, Figure 1 The blade design method shown in the figure improves the aerodynamic performance of the blade and avoids the waste of calculation in the early stage of optimization. Compared with the blade design using the fine optimization process alone, Figure 1 The blade profile design method flow shown here achieves the same aerodynamic performance while reducing the consumption of computing resources and optimization cycle.

[0052] for Figure 1The technical solution shown first uses a less complex first blade profile to obtain a first blade profile and then optimizes it. This quickly eliminates a large number of non-optimal regions to find a preliminary, more optimal blade profile. A more complex second blade profile is then used to further optimize the optimized first blade profile, rather than optimizing the original blade. This improves blade profile design efficiency while enhancing the blade's aerodynamic performance.

[0053] based on Figure 1 The technical solution shown takes the double arc blade as the first blade solution and the Bezier curve blade as the second blade solution as an example. The present disclosure provides an implementation process of the blade design method. Figure 2 , the implementation process may include:

[0054] S201: forming a first blade profile of a blade using a double arc blade profile.

[0055] In this embodiment, if Figure 3 As shown, in the first airfoil 30 formed by a double-arc airfoil, the pressure side curve 31 and the suction side curve 32 are each formed by a separate arc, and the leading edge 33 and the trailing edge 34 are also formed by separate arcs. Adjustment of the pressure side curve 31 is achieved by moving a point 35 on the arc of the pressure side curve 31. It can be seen that the design parameters of the double-arc airfoil are the positions of the points on the arc. In other words, for a single curve, the double-arc airfoil has only one design parameter.

[0056] S202: performing flow field calculation optimization on the first blade profile to evaluate aerodynamic performance indicators, and iteratively adjusting design parameters of the double-arc blade profile according to the aerodynamic performance indicators to obtain an optimized first blade profile.

[0057] During the implementation process, CFD mesh data for the first blade profile is first generated. Next, the behavior of fluid flowing through the blade passage is simulated based on this CFD mesh data to obtain aerodynamic performance data on the blade surface, such as pressure distribution, velocity load, and aerodynamic load. Based on this aerodynamic performance data, an objective function for the first blade profile's aerodynamic performance indicators, including efficiency, loss, and pressure fluctuation, is generated. Subsequently, design parameters for the first blade profile are adjusted based on the objective function for the aerodynamic performance indicators.

[0058] New CFD mesh data is generated based on the adjusted design parameters, and the behavior of the fluid passing through the blade channel is simulated based on the new CFD mesh data to obtain the optimized aerodynamic performance data of the blade surface. Then, the objective function of the optimized aerodynamic performance index of the first blade profile is generated based on the optimized aerodynamic performance data. In this way, the design parameters are iteratively adjusted until the objective function value of the aerodynamic performance index meets the set conditions, such as the highest efficiency, the lowest loss, the smallest pressure fluctuation, etc., thereby obtaining the optimized first blade profile. Figure 3 As an example of the first blade profile shown in the figure, the optimized first blade profile is as follows Figure 4 As shown, it includes an optimized first blade profile pressure surface curve 41 , an optimized first blade profile suction surface curve 42 , an optimized first blade profile leading edge 43 and an optimized first blade profile trailing edge 44 .

[0059] It's important to note that since the design parameters for the double-arc blade are solely the positions of the points on the arc, the optimization process for the first blade can be considered a search in a one-dimensional parameter space. Due to the small parameter space, the search process can quickly bring the objective function value to the set conditions, eliminating most non-optimal regions and ultimately obtaining a preliminary optimal solution.

[0060] Furthermore, due to geometric constraints, the first blade profile formed by the double-arc blade has limited adjustment flexibility, making it difficult to achieve complex geometric changes to adapt to changing aerodynamic requirements. This generally provides limited improvement in aerodynamic performance and is more suitable for applications under high-speed airflow conditions. Therefore, after obtaining the initial optimal solution for the optimized first blade profile, this disclosure will further optimize aerodynamic performance using a more flexible blade profile solution based on this initial optimal solution.

[0061] S203: Converting the optimized first blade profile into a second blade profile described by a Bezier curve parameter blade profile solution.

[0062] In this embodiment, Figure 5 As an example of the blade profile shown in FIG. 1 , the solid line curve is the first blade profile optimized by steps S201 and S202. In the first blade profile optimized, the pressure surface curve and the suction surface curve are both Figure 5 The multi-order Bezier curves shown in the dotted line are used to form the second blade profile. In the present disclosure, the order of each Bezier curve is at least 3, that is, the control points of each Bezier curve (such as Figure 5 The number of control points (shown as black dots in the figure) is at least 3 + 1 = 4. After forming the second blade profile using the Bezier curve, the shapes of the pressure and suction side curves of the second blade profile can be controlled by adjusting the positions of the control points. Therefore, the number of design parameters for the Bezier curve parameter blade profile is consistent with the number of control points, which is at least 4.

[0063] Since the number of control points (i.e., the number of design parameters) used by the Bezier curve parametric blade to control the curve shape is significantly greater than the number of points on the arc used by the double arc blade to control the curve shape, the second blade profile can adjust the curve more flexibly and accurately than the first blade profile, and can achieve more complex geometric changes to the curve.

[0064] The above process of converting the optimized first blade profile into the second blade profile can be considered as a process of fitting the optimized first blade profile using the Bezier curve. In the implementation process, each curve to be converted in the optimized first blade profile can be fitted according to the root mean square error between the Bezier curve and the curve in the optimized first blade profile being less than the set tolerance value. The constraint condition forms the corresponding Bezier curve in the second blade. In the process of converting each curve to be converted, the tolerance value It is the maximum geometric difference between the blade profile before and after switching, and is a key indicator to ensure the quality of the conversion, that is, the quality of the first blade profile after the Bezier curve is fitted and optimized. It can be calculated by the following formula:

[0065]

[0066] in, Indicates the arc length of the curve to be converted in the optimized first blade profile. For example, when the curve to be converted is the pressure surface curve, represents the arc length of the pressure surface curve in the optimized first blade profile. Specifically, N sampling points are set on the pressure surface curve in the optimized first blade profile. Among the N sampling points, The coordinates of the sampling points are , so the arc length of the pressure surface curve in the first blade profile can be obtained by Calculated, where Indicates the starting point of the pressure surface curve in the optimized first airfoil. is the tolerance coefficient, and its value depends on the manufacturing accuracy of the impeller machining equipment. It is usually in the range of Tolerance factor If the value is set too large, it means that the allowable error range is too wide, and there may be large geometric errors during the blade switching process, which will be detrimental to the subsequent blade optimization and cause the optimal blade obtained by the final optimization to deviate from the expected aerodynamic performance. Although a setting that is too small can theoretically achieve higher precision, it will cause the blade switching process to take too long, increase the computational burden, and a too small tolerance coefficient will also lead to a mismatch with the actual machining accuracy, resulting in unnecessary waste of computing resources.

[0067] For details, see Figure 6 , converting the optimized first blade profile into a second blade profile described by a Bezier curve parameter blade profile solution, which may specifically include:

[0068] S601: uniformly collect m first sampling points on the curve to be converted in the optimized first blade profile, and construct a Order Bezier curve.

[0069] In some examples, since the order of the Bezier curve parameter profile in the present disclosure is at least 3, the value of n may be set to 3.

[0070] For step S601, specifically, Figure 7 As shown, the implementation process of constructing an n-order Bezier curve using the Bezier curve interpolation algorithm may include:

[0071] S701: Setting a corresponding parameter value for each of m first sampling points on the curve to be converted.

[0072] Specifically, set the set of m first sampling points , in this set, The first sampling point is ,in, express and set the starting point of the curve to be converted The coordinates are For the First sampling point , set the corresponding parameter value , the parameter value The range is .

[0073] It should be noted that the Bezier curve is a parametric curve. In order to map discrete sampling points to the parameter domain of the Bezier curve, the sampling points are parameterized by the above parameter values to establish a connection between the sampling points and the Bezier curve. Figure 8 The exemplary curve shown sets the end point of the curve to be converted The coordinates are , No. First sampling point According to the corresponding parameter value You can follow Calculated.

[0074] S702: Utilize the first sampling point and the parameter value corresponding to the first sampling point according to the lowest order n Constructs a Bezier curve.

[0075] In this disclosure, the minimum order is 3, that is, the minimum number of control points is 4, and the Bezier curve expression is constructed as follows: .in, The first i control points, whose coordinates are expressed as , It is the first control point of the Bezier curve, which is consistent with the first endpoint of the curve; It is the last control point of the Bezier curve, which is consistent with the last endpoint of the curve; represents the Bernstein polynomial.

[0076] The above sampling points and corresponding parameter values After substituting the above expression, a linear equation system is formed. By solving this linear equation system using numerical optimization algorithms such as the least squares method, a set of control points of the above Bezier curve can be obtained.

[0077] S602: Obtain a root mean square error between the constructed Bezier curve and the first sampling point.

[0078] It's important to note that the root mean square error (RMS) is an objective metric that can quantify the quality of the fit. It directly measures the degree of agreement between the Bezier curve and the optimized first blade profile curve. The smaller the value, the more accurate the fit. Furthermore, the RMS error is sensitive to large error points, and the error data is relatively intuitive.

[0079] In the present disclosure, the method of obtaining the root mean square error includes two optional examples.

[0080] In one example, based on the X-coordinate values of m first sampling points on the curve to be converted, sampling is performed on the Bezier curve to obtain m second sampling points on the Bezier curve corresponding to the m first sampling points; and a root mean square error (RMS) between the m first sampling points and the m second sampling points is obtained.

[0081] Specifically, in Figure 9 In the coordinate system shown, the curve to be converted is the pressure surface curve of the first blade profile, and the first The first sampling point is Based on the X coordinate value of the first sampling point , the corresponding Bezier curve The second sampling point is According to the coordinate values of all first sampling points and the corresponding second sampling points, the root mean square error between the constructed Bezier curve and the sampling points is calculated according to the following formula: :

[0082] .

[0083] In another example, based on the intersection of the normals of the m first sampling points on the curve to be converted and the Bezier curve, m second sampling points on the Bezier curve corresponding to the m first sampling points are obtained; and the root mean square error of the m first sampling points and the m second sampling points is obtained.

[0084] Specifically, if Figure 10 As shown, the curve to be converted is the pressure surface curve of the first blade profile, and the The first sampling point is Get The normal on the curve to be converted, such as Figure 10 As shown by the dotted line. Calculate the intersection of the normal and the Bezier curve, and use the intersection as the intersection of the normal and the Bezier curve. The corresponding The second sampling point is According to the coordinate values of all first sampling points and the corresponding second sampling points, the root mean square error between the constructed Bezier curve and the sampling points is calculated according to the following formula: :

[0085] .

[0086] S603: Determine whether the root mean square error is less than the set tolerance value. If so, execute S604 to obtain Otherwise, go to S605.

[0087] It should be noted that if the root mean square error between the Bezier curve obtained by the above construction and the first sampling point is less than the tolerance value, it means that the Bezier curve has met the fitting accuracy requirements, and the curve shape can be adjusted and controlled through the control points on the Bezier curve, that is, the conversion process from the first blade profile to the second blade profile is completed.

[0088] Otherwise, you need to determine whether increasing the complexity of the Bezier curve (for example, increasing its order) can improve the accuracy of the fit.

[0089] S605: Judgment The root mean square error between the first sampling point and the Bezier curve Is it less than the root mean square error between the n-1 order Bezier curve and the first sampling point? If so, then the Bezier curve is upgraded. , and go to S601, thereby constructing a Bezier curve interpolation algorithm based on the m first sampling points Otherwise, go to S604 and obtain Control points on a degree Bézier curve.

[0090] It should be noted that if , indicating that the order upgrade is effective in the fitting process and can significantly improve the fitting accuracy. In this case, the order upgrade can be continued to improve the fitting accuracy.

[0091] if , which means that the Bezier curve has begun to overfit, or has reached the best in the current fitting process. Continuing to increase the order will cause the curve shape to become too complex or have undesirable oscillations, which no longer meets the smoothness required by the project. In this case, although the set tolerance value may not be fully achieved, The goal is to stop the order upgrade and use the fitting result of the currently achieved optimal order as the second blade profile obtained by the final transformation, and the conversion process from the first blade profile to the second blade profile is completed.

[0092] Once the conversion process is complete, a set of control points for a Bezier curve approximating the curve to be converted with a specified accuracy (satisfying the required tolerance or achieving the best fit) is obtained. This signifies that the blade profile has successfully switched from the optimized first blade profile to the Bezier curve parameter blade profile, providing a foundation for subsequent refined optimization.

[0093] for Figure 6 In the conversion process shown, the curve to be converted can be the pressure surface curve of the optimized first blade profile, or can be the suction surface curve of the optimized first blade profile.

[0094] S204: performing flow field calculation optimization on the second blade profile to evaluate aerodynamic performance indicators, and iteratively adjusting design parameters of the Bezier curve parameter blade profile according to the aerodynamic performance indicators to obtain an optimal blade profile.

[0095] In the present disclosure, the process of iteratively adjusting the design parameters of the Bezier curve parameter blade according to the aerodynamic performance index is similar to the aforementioned process of iteratively adjusting the design parameters of the double arc blade according to the aerodynamic performance index, and will not be repeated here.

[0096] It should be noted that since the optimized first blade profile has eliminated most of the non-optimal areas and is a preliminary optimal solution, this provides a smaller initial search range for optimizing the second blade profile after it is converted to a Bezier curve parameter blade profile. Compared to directly using the original blade geometry as the initial search range for the Bezier curve parameter blade profile, since most of the non-optimal areas have been eliminated, the overall optimization efficiency is improved, enabling the technical solution provided by the present disclosure to achieve a higher design level within a limited optimization cycle, thereby improving the blade design efficiency while enhancing the blade's aerodynamic performance indicators.

[0097] Based on the same inventive concept as the above technical solution, see Figure 11, which shows the composition of a blade profile design device provided by the present disclosure, the device 110 may include: a forming part 1101, a first optimization part 1102, a conversion part 1103 and a second optimization part 1104, wherein,

[0098] The forming portion 1101 is configured to form a first blade profile of the blade using a first blade profile scheme;

[0099] The first optimization part 1102 is configured to optimize the first blade profile based on an aerodynamic performance index to obtain an optimized first blade profile;

[0100] The conversion part 1103 is configured to describe the optimized first blade profile using design parameters in a second blade profile solution to obtain a second blade profile; wherein the complexity of the second blade profile solution is higher than that of the first blade profile solution;

[0101] The second optimization part 1104 is configured to optimize the second blade profile to form the optimal blade profile of the blade.

[0102] In some examples, the first optimization portion 1102 is configured to evaluate aerodynamic performance indicators by performing flow field calculation optimization on the first blade profile, and iteratively adjust design parameters of the double-arc blade profile according to the aerodynamic performance indicators to obtain an optimized first blade profile.

[0103] In some examples, the first optimization portion 1102 is configured to:

[0104] forming computational fluid dynamics (CFD) mesh data of the first blade profile;

[0105] simulating the behavior of fluid passing through the blade channel based on the CFD mesh data of the first blade profile to obtain aerodynamic performance data of the blade surface;

[0106] forming an objective function of an aerodynamic performance index of the first blade profile according to the aerodynamic performance data;

[0107] The design parameters of the first blade profile are iteratively adjusted according to the objective function of the aerodynamic performance index until the objective function value of the aerodynamic performance index meets a set condition, so as to obtain the optimized first blade profile.

[0108] In some examples, the first blade profile solution includes a double-arc blade profile, and the second blade profile solution includes a Bezier curve parameter blade profile.

[0109] In some examples, the converting portion 1103 is configured to perform the following steps:

[0110] S1: uniformly collect m first sampling points on the curve to be converted in the optimized first blade profile, and construct a Bezier curve interpolation algorithm based on the m first sampling points Order Bezier curve;

[0111] S2: Get the The root mean square error between the first sampling point and the first Bezier curve;

[0112] S3: Determine whether the root mean square error is less than the set tolerance value; if so, execute S4: obtain the The control point on the order Bezier curve; otherwise, go to S5;

[0113] S5: Determine the The root mean square error between the first sampling point and the Bezier curve Is it less than the root mean square error between the n-1 order Bezier curve and the first sampling point? If so, upgrade , and go to S1 to construct a Bezier curve interpolation algorithm based on the m first sampling points Otherwise, go to S4: get the Control points on a degree Bézier curve.

[0114] In some examples, the converting portion 1103 is configured to:

[0115] Setting a corresponding parameter value for each of the m first sampling points on the curve to be converted;

[0116] Using the first sampling point and the parameter value corresponding to the first sampling point according to the lowest order n Constructs a Bezier curve.

[0117] In some examples, the conversion portion 1103 is configured to:

[0118] Based on the X coordinate values of the m first sampling points on the curve to be converted, Sampling on a Bezier curve of order 1 to obtain m second sampling points on the Bezier curve corresponding to the m first sampling points; and obtaining a root mean square error between the m first sampling points and the m second sampling points;

[0119] or,

[0120] Based on the normal of the m first sampling points on the curve to be converted and the The intersection of the order Bezier curves is obtained. m second sampling points on the order Bezier curve corresponding to the m first sampling points; and obtaining a root mean square error between the m first sampling points and the m second sampling points.

[0121] Please refer to Figure 12 , which shows a structural block diagram of a computing device provided by an exemplary embodiment of the present disclosure. In some examples, the computing device 120 can be at least one of a smart phone, a smart watch, a desktop computer, a laptop computer, a virtual reality terminal, an augmented reality terminal, a wireless terminal and a laptop computer. The computing device 120 has a communication function and can access a wired network or a wireless network. The computing device 120 can generally refer to one of a plurality of terminals, and those skilled in the art will know that the number of the above terminals can be more or less. In some examples, the computing device 120 can receive data based on the wired network or wireless network to which it is connected. It can be understood that the computing device 120 undertakes the calculation and processing work of the technical solution of the present disclosure, and the present disclosure does not limit this.

[0122] like Figure 12 As shown, the computing device in the present disclosure may include one or more of the following components: a processor 1210 and a memory 1220 .

[0123] Optionally, the processor 1210 utilizes various interfaces and circuits to connect various components within the computing device. It executes instructions, programs, code sets, or instruction sets stored in the memory 1220, as well as accesses data stored in the memory 1220, to perform various functions of the computing device and process data. Optionally, the processor 1210 can be implemented in at least one hardware form: a digital signal processing (DSP), a field-programmable gate array (FPGA), or a programmable logic array (PLA). The processor 1210 can integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), a neural network processing unit (NPU), and a baseband chip. The CPU primarily processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing content displayed on the touchscreen display; the NPU is used to implement artificial intelligence (AI) functions; and the baseband chip handles wireless communications. It is understandable that the above-mentioned baseband chip may not be integrated into the processor 1210, but may be implemented by a separate chip.

[0124] Memory 1220 may include random access memory (RAM) or read-only memory (ROM). Optionally, memory 1220 includes non-transitory computer-readable storage medium. Memory 1220 may be used to store instructions, programs, code, code sets, or instruction sets. Memory 1220 may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), and instructions for implementing each of the above method embodiments. The data storage area may store data created based on the use of the computing device.

[0125] In addition, those skilled in the art will understand that the structures of the computing devices shown in the above figures do not constitute limitations on the computing devices. The computing devices may include more or fewer components than shown, or may combine certain components or arrange the components differently. For example, the computing devices may also include a display screen, a camera assembly, a microphone, a speaker, a radio frequency circuit, an input unit, sensors (such as an accelerometer, an angular velocity sensor, a light sensor, etc.), an audio circuit, a WiFi module, a power supply, a Bluetooth module, and other components, which will not be described in detail here.

[0126] The present disclosure further provides a computer-readable storage medium storing at least one instruction, wherein the at least one instruction is configured to be executed by a processor to implement the airfoil design method as described in the above embodiments.

[0127] The present disclosure also provides a computer program product, which includes computer instructions stored in a computer-readable storage medium; a processor of a computing device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computing device executes to implement the blade design method described in each of the above embodiments.

[0128] Those skilled in the art will appreciate that in one or more of the above examples, the functions described in this disclosure can be implemented using hardware, software, firmware, or any combination thereof. When implemented using software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any media that facilitates the transmission of computer programs from one place to another. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0129] It should be noted that the technical solutions described in this disclosure can be combined arbitrarily without conflict.

[0130] The above description is only a specific embodiment of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any technician familiar with the technical field can easily think of changes or replacements within the technical scope disclosed in the present disclosure, and they should all be covered by the protection scope of the present disclosure.

Claims

1. A method for blade profile design, characterized in that: The method comprises: forming a first blade profile of the blade using a first blade profile solution including a double arc blade profile; Optimizing the first blade profile based on aerodynamic performance indicators to obtain an optimized first blade profile; Describing the optimized first blade profile using design parameters in a second blade profile solution including a Bezier curve parameter blade profile to obtain a second blade profile; wherein the complexity of the second blade profile solution is higher than that of the first blade profile solution; Optimizing the second blade profile to form an optimal blade profile of the blade; The method of describing the optimized first blade profile using design parameters in a second blade profile solution including a Bezier curve parameter blade profile to obtain the second blade profile includes: S1: uniformly collect m first sampling points on the curve to be converted in the optimized first blade profile, and construct a Bezier curve interpolation algorithm based on the m first sampling points Order Bezier curve; S2: Get the The root mean square error between the first sampling point and the first Bezier curve; S3: Determine whether the root mean square error is less than the set tolerance value; if so, execute S4: obtain the The control point on the order Bezier curve; otherwise, go to S5; S5: Determine the The root mean square error between the first sampling point and the Bezier curve Is it less than the root mean square error between the n-1 order Bezier curve and the first sampling point? If so, upgrade , and go to S1 to construct a Bezier curve interpolation algorithm based on the m first sampling points Otherwise, go to S4: get the Control points on a Bézier curve.

2. The method according to claim 1, characterized in that The step of optimizing the first blade profile based on the aerodynamic performance index to obtain the optimized first blade profile includes: The aerodynamic performance indicators are evaluated by performing flow field calculation optimization on the first blade profile, and the design parameters of the double-arc blade profile are iteratively adjusted according to the aerodynamic performance indicators to obtain the optimized first blade profile.

3. The method according to claim 2, characterized in that The method of performing flow field calculation optimization on the first blade profile to evaluate aerodynamic performance indicators and iteratively adjusting design parameters of the double arc blade profile according to the aerodynamic performance indicators to obtain an optimized first blade profile includes: forming computational fluid dynamics (CFD) mesh data of the first blade profile; simulating the behavior of fluid passing through the blade channel based on the CFD mesh data of the first blade profile to obtain aerodynamic performance data of the blade surface; forming an objective function of an aerodynamic performance index of the first blade profile according to the aerodynamic performance data; The design parameters of the first blade profile are iteratively adjusted according to the objective function of the aerodynamic performance index until the objective function value of the aerodynamic performance index meets a set condition, so as to obtain the optimized first blade profile.

4. The method according to claim 1, wherein The method constructs the m first sampling points using the Bezier curve interpolation algorithm Order Bezier curves, including: Setting a corresponding parameter value for each of the m first sampling points on the curve to be converted; Using the first sampling point and the parameter value corresponding to the first sampling point according to the lowest order n Constructs a Bezier curve.

5. The method according to claim 1, wherein The acquisition of The root mean square error between the first sampling point and the Bezier curve of order 1 includes: Based on the X coordinate values of the m first sampling points on the curve to be converted, Sampling on a Bezier curve of order 1 to obtain m second sampling points on the Bezier curve corresponding to the m first sampling points; and obtaining a root mean square error between the m first sampling points and the m second sampling points; or, Based on the normal of the m first sampling points on the curve to be converted and the The intersection of the order Bezier curves is obtained. m second sampling points on the order Bezier curve corresponding to the m first sampling points; and obtaining a root mean square error between the m first sampling points and the m second sampling points.

6. A blade design device, characterized in that: The device comprises: a forming part, a first optimizing part, a converting part and a second optimizing part, wherein: The forming portion is configured to form a first blade profile of the blade using a first blade profile scheme including a double arc blade profile; The first optimization part is configured to optimize the first blade profile based on an aerodynamic performance index to obtain an optimized first blade profile; The conversion portion is configured to describe the optimized first blade profile using design parameters in a second blade profile solution including a Bezier curve parameter blade profile to obtain a second blade profile; wherein the complexity of the second blade profile solution is higher than that of the first blade profile solution; The second optimization part is configured to optimize the second blade profile to form an optimal blade profile of the blade; Wherein, the conversion part is configured to: S1: uniformly collect m first sampling points on the curve to be converted in the optimized first blade profile, and construct a Bezier curve interpolation algorithm based on the m first sampling points Order Bezier curve; S2: Get the The root mean square error between the first sampling point and the first Bezier curve; S3: Determine whether the root mean square error is less than the set tolerance value; if so, execute S4: obtain the The control point on the order Bezier curve; otherwise, go to S5; S5: Determine the The root mean square error between the first sampling point and the Bezier curve Is it less than the root mean square error between the n-1 order Bezier curve and the first sampling point? If so, upgrade , and go to S1 to construct a Bezier curve interpolation algorithm based on the m first sampling points Otherwise, go to S4: get the Control points on a Bézier curve.

7. A computing device, characterized in that The computing device includes a processor and a memory; the processor is configured to execute instructions stored in the memory to implement the blade profile design method according to any one of claims 1 to 5.

8. A computer storage medium, characterized in that The storage medium stores at least one instruction, and the at least one instruction is used to be executed by a processor to implement the airfoil design method according to any one of claims 1 to 5.

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