Reverse aerodynamic performance evaluation method for fan blade

Abstract

The invention provides a reverse aerodynamic performance evaluation method for a fan blade. The method comprises the following steps: S1, establishing blade appearance point cloud data; s2, extracting a cross section airfoil profile and geometric parameters: intercepting a cross section to obtain a cross section airfoil profile under the cross section; s3, section feature recognition and normalization: calculating the chord length and torsion of the cross section; the section airfoil is normalized under the unit chord length and the horizontal chord line reference, and a point set is obtained; s4, Fourier descriptor calculation: obtaining Fourier descriptors F corresponding to each section airfoil; S5, airfoil matching and pneumatic epipolar reconstruction; S51, performing similarity calculation on the descriptors corresponding to each section airfoil and descriptors in an airfoil database, obtaining a minimum distance airfoil, judging whether the minimum distance airfoil meets a set matching condition or not, if the minimum distance airfoil meets the set matching condition, judging whether the minimum distance airfoil meets the set matching condition, and if the minimum distance airfoil meets the set matching condition, performing airfoil matching and pneumatic epipolar reconstruction; and if matching succeeds, directly calling an airfoil profile pole table in an airfoil profile database, and if matching fails, solving the use value of the airfoil profile of the section, and calculating the pneumatic polar line of the airfoil profile.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of fan blades, in particular to a method for evaluating reverse aerodynamic performance of a fan blade. BACKGROUND

[0002] With the acceleration of global energy transformation, offshore floating wind power generation has gradually become an important direction of clean energy development. Compared with traditional fixed wind turbines, floating wind turbines can be deployed in deeper waters, have advantages of rich resource potential, high power generation efficiency, and little interference with coastal landscape and fishery. In order to ensure the long-term safe operation and economy of floating wind turbines, their aerodynamic performance needs to be accurately evaluated during the experimental, manufacturing and operation stages. This not only relates to power prediction and energy yield evaluation, but also directly affects structural load calculation, fatigue life prediction and operation strategy formulation.

[0003] However, existing aerodynamic performance evaluation usually relies on blade parameters provided during the design stage of the wind turbine, including cross-sectional airfoils, chord length and twist angle distribution, thickness distribution, and corresponding aerodynamic polar curves. However, in actual engineering, there are the following outstanding problems: 1. Parameter confidentiality: the airfoil distribution and aerodynamic polar curve of the blade are important intellectual property of wind turbine manufacturers, which are usually not publicly disclosed, making it difficult to obtain key aerodynamic parameters in third-party experiments or procurement evaluation; 2. In-service deviation: during the long-term service of the wind turbine, the blade surface will be affected by wear, pollution, ice accumulation or repair treatment, resulting in deviation between the actual airfoil and the designed airfoil, and thus affecting the lift-drag force characteristics and power output; 3. Manufacturing error: during the production and manufacturing process, due to process precision, material shrinkage or mold deviation, the actual finished blade may not be completely consistent with the design target, resulting in differences in out-of-factory aerodynamic performance.

[0004] The above problems directly lead to the lack of precision of the traditional evaluation method based on "nominal design parameters" in the actual application of floating wind turbines, which may result in power curve prediction deviation, inaccurate aerodynamic load estimation, underestimation or overestimation of fatigue load, and thus affect the performance evaluation and reliability analysis of the wind turbine throughout its life cycle. SUMMARY

[0005] In view of the above-mentioned shortcomings of the prior art, the present application aims to provide a method for evaluating the reverse aerodynamic performance of a fan blade, which realizes reverse evaluation and difference diagnosis of the aerodynamic performance of the fan blade, thereby improving the accuracy and independence of experimental verification, manufacturing acceptance and operation monitoring.

[0006] To achieve the above-mentioned purpose, the present application provides a method for evaluating the reverse aerodynamic performance of a fan blade, characterized by comprising the following steps:

[0007] S1, blade shape point cloud data establishment: full surface three-dimensional scanning is performed on the target fan blade, and the scanning data is processed to obtain blade shape point cloud data, wherein, represents the three-dimensional coordinates of the i-th shape point in the blade coordinate system, N is the total number of point clouds, and the z-axis of the blade coordinate system is along the span of the blade;

[0008] S2, cross-sectional airfoil and geometric parameter extraction: R vertical cross sections are taken along the blade span at a set interval, and the cross sections are arranged along the blade span forward and backward to record a section segment, obtaining R section segments; for the point set of the blade shape points contained in the r-th section segment range , wherein represents the coordinates of the section segment in the scanning coordinate system ; then the high-frequency noise of is removed by a smoothing function,

[0009] obtaining the continuous closed contour cross-sectional airfoil under the cross section;

[0010] S3, cross-sectional feature recognition and normalization: each cross-sectional airfoil obtained in step S3 is processed as follows: S31, identify the leading edge point and the trailing edge point of the cross-sectional airfoil, and the coordinates of the two are recorded as and

[0011] respectively; S32, calculate the chord length and the twist of the cross section, wherein

[0012] ; ;

[0013] S33, normalize the cross-sectional airfoil under the unit chord length and horizontal chord line reference: wherein represents a two-dimensional rotation matrix rotating counterclockwise around the origin, and the point set is recorded as the normalized airfoil coordinate point set;

[0014] S4, Fourier descriptor calculation: each normalized cross-sectional airfoil in step S3 is processed as follows:

[0015] S41, resample the normalized cross-sectional airfoil in step S3 into points according to equal arc length, and construct a complex sequence , wherein is an imaginary unit;

[0016] S42, the complex sequence is subjected to a discrete Fourier transform, , the Fourier descriptor of the cross-sectional airfoil is defined as and is subjected to normalization processing , wherein is the selected Fourier order is the coefficient amplitude of the order;

[0017] S5, airfoil matching and aerodynamic polar reconstruction:

[0018] S51, the descriptor corresponding to each cross-sectional airfoil is calculated with the descriptor in the airfoil database to obtain a similarity distance , and the minimum distance airfoil is obtained accordingly;

[0019] S52, it is judged whether the minimum distance airfoil meets the set matching condition, if yes, it is considered that the matching is successful, and the airfoil polar attached in the existing airfoil database is directly called, if not, it is considered that the matching fails, and the of the cross-sectional airfoil is calculated using numerical solution to calculate the aerodynamic polar thereof.

[0020] Further, in the step S1, the target wind turbine blade is subjected to full-surface three-dimensional scanning to obtain scanning point original cloud data of the blade shape ; then the scanning point cloud data is subjected to conversion processing to obtain the coordinates of the scanning points in the blade coordinate system, thereby obtaining the shape point cloud data of the blade. .

[0021] Further, in the step S1, the shape point cloud data of the blade is further subjected to denoising processing to remove abnormal points.

[0022] Further, in the step S2, the number R of cross sections takes a value in the range of 10-20.

[0023] Further, in the step S2, takes a value in the range of , and L is the length of the blade.

[0024] Further, in the step S2, the smoothing function is obtained by B-spline fitting or local polynomial smoothing.

[0025] Further, in the step S4, the number of sampling points takes a value in the range of 100-200.

[0026] Further, in the step S51, the similarity distance The calculation method is as follows: , The covariance matrix of the descriptors in the airfoil database is calculated using the following formula. ,in The current number of airfoils in the airfoil database, It is the mean of all sample descriptors in the airfoil database.

[0027] Furthermore, step S52 also includes: when the matching fails, the descriptor and pole table data corresponding to the airfoil section are added to the existing airfoil database.

[0028] Furthermore, it also includes: S6, aerodynamic and geometric parameter output: obtaining the combination of geometric control parameters and aerodynamic characteristic parameters for each airfoil section. ,Will By inputting the blade element momentum model or CFD simulation, the aerodynamic torque, thrust distribution and power output of the blade can be calculated, thereby realizing the performance evaluation and difference analysis of the blade in the experimental, manufacturing and operation stages.

[0029] As described above, the method for evaluating the reverse aerodynamic performance of wind turbine blades according to the present invention has the following beneficial effects:

[0030] 1) It can perform reverse evaluation from physical geometry without prior airfoil and polar line, enabling reverse evaluation and difference diagnosis of wind turbine blade aerodynamic performance, thereby improving the accuracy and independence of experimental verification, manufacturing acceptance and operation monitoring stages, and eliminating dependence on manufacturers; 2) It can adapt to in-service changes and naturally cover shape drift caused by wear, contamination and repair; 3) It can achieve quantitative manufacturing consistency, measuring production deviations with dual indicators of geometry and aerodynamic response; 4) It can seamlessly interface with tools such as BEM / FAST, with low computational cost, batch application, and convenient engineering implementation; 5) It can access a larger airfoil library, more aerodynamic correction models and field data, and has good scalability. Attached Figure Description

[0031] Figure 1 This is a schematic flowchart of the reverse aerodynamic performance evaluation method of the present invention. Detailed Implementation

[0032] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification.

[0033] It is to be understood that the structures, proportions, sizes, etc. shown in the drawings accompanying the present specification are shown by way of illustration only and are meant as examples of elements used to describe the embodiments disclosed herein. Therefore, the actual dimensions, relationships, and / or proportions of the elements shown in the figures are not meant to be limiting and should not be interpreted as limiting the scope of the disclosure. Any structural, proportional, or dimensional changes can be made to the elements disclosed herein without departing from the scope of the disclosure. Also, the terms "upper," "lower," "left," "right," "intermediate," and "one" and the like as used herein are only intended to aid in describing the embodiments disclosed herein and are not meant to be limiting. Any changes in the relative positions of the elements, or the relative relationships between the elements, without changing the technical content, are also considered to be within the scope of the disclosure.

[0034] It should also be noted that when an element is referred to as being "on" or "connected to" another element, it can be directly on or connected to the other element or intervening elements can also be present. In contrast, when an element is referred to as being "connected" to another element, it can be directly connected to the other element or connected to the other element through intervening elements.

[0035] In addition, the terms "first", "second", and the like, as used in this application, are only used for descriptive purposes and should not be construed as indicating or implying relative importance or an indicated number of technical features. Therefore, the features defined as "first", "second" can explicitly or implicitly include at least one of the features. In addition, the technical solutions of various embodiments can be combined with each other, but it must be based on the realization of ordinary skilled in the art, when the combination of technical solutions appears contradictory or unachievable, it should be considered that the combination of technical solutions does not exist, nor within the scope of protection claimed in this application.

[0036] Referring to Figure 1 The present application provides a method for evaluating the reverse aerodynamic performance of a fan blade, comprising the following steps:

[0037] S1, blade shape point cloud data establishment: full surface three-dimensional scanning is performed on the target fan blade, and the scanning data is processed to obtain the shape point cloud data of the blade, wherein, represents the three-dimensional coordinates of the i-th shape point in the blade coordinate system, that is, , and is divided into the , and The coordinates under the axis, N is the total number of point clouds, and the z-axis of the blade coordinate system is along the spanwise direction of the blade. During scanning, due to the misalignment between the scanning coordinate system and the blade coordinate system, there are errors and abnormal data in the scanning process, and therefore the step preferably comprises:

[0038] S11, using a 3D scanner to perform full-surface three-dimensional scanning on the target fan blade to obtain original scanning point cloud data of the blade profile ; represents the three-dimensional coordinates of the i-th profile point in the scanning coordinate system, and N is the total number of scanning point clouds.

[0039] S12, then the scanning point cloud data is converted and processed to obtain the coordinates of the scanning points in the blade coordinate system, thereby obtaining the required profile point cloud data of the blade , specifically, the coordinate registration process is represented as:

[0040]

[0041] wherein, is a global coordinate transformation function, is a rotation matrix, is a translation vector, and both are determined according to the specific circumstances of the scanning work. Preferably, the original scanning point cloud data is also subjected to denoising processing to effectively remove abnormal points. In this way, the initial scanning point coordinates are uniformly converted into the blade coordinate system, thereby establishing the blade profile point cloud data in the blade coordinate system.

[0042] S2, extraction of cross-sectional airfoils and geometric parameters: R cross sections perpendicular to the spanwise direction are taken at a set interval along the spanwise direction of the blade, and the interval between any two adjacent cross sections is preferably the same. The cross sections are divided into R segments along the spanwise direction of the blade , and the point set of the blade profile points contained in the r-th segment is denoted as , and , wherein represents the coordinates of the segment in the blade coordinate system ; then the smoothing function is used to smooth to remove high-frequency noise, , and the cross-sectional airfoil of the continuous closed contour under the cross section is obtained.

[0043] In this step, in order to balance the accuracy and the efficiency of implementation, R is preferably in the range of 10-20, wherein is in the range of L is the length of the blade, thereby ensuring a proper number of subsections with a proper spanwise width. In this step, preferably, the smoothing function can be obtained in the way of B-spline fitting or local polynomial smoothing, which can be achieved by existing methods. Through this step, the cross-sectional airfoil of the continuous closed profile under each cross-section can be obtained.

[0044] S3, cross-section feature recognition and normalization: for each cross-sectional airfoil obtained in step S3, the following processing is performed:

[0045] S31, identify the leading edge point and the trailing edge point of the cross-sectional airfoil, and the coordinates of the two points are respectively denoted as and . Among them, the identification of the leading edge point and the trailing edge point can be achieved by existing conventional methods, which can be determined according to the coordinates of each point in , for example, when the chord line in the cross-sectional airfoil is along the axis, the points with the maximum and minimum horizontal coordinate values can be regarded as the leading edge point and the trailing edge point.

[0046] S32, calculate the chord length and the twist of the cross-section, denote the number of the cross-section, and the calculation formula is:

[0047] ;

[0048] ;

[0049] S33, normalize the cross-sectional airfoil under the unit chord length and horizontal chord line reference:

[0050] ,

[0051] wherein represents a two-dimensional rotation matrix rotating counterclockwise by around the origin, and the point set is denoted as the normalized airfoil coordinate point set. In this way, the initial cross-sectional airfoil is normalized, which is used to represent the of the cross-sectional airfoil is also converted to the normalized .

[0052] S4, Fourier descriptor calculation: for each normalized cross-sectional airfoil in step S3, the following processing is performed:

[0053] S41, resample the cross-sectional airfoil into points according to equal arc length, and construct a complex sequence , wherein is the imaginary unit. Preferably, the number of sampling points The value range of the cross-section airfoil is 100-200, so as to ensure accurate description of the blade cross-section airfoil.

[0054] S42, a plurality of sequences are subjected to discrete Fourier transform (DFT), the Fourier descriptor of the cross-section airfoil is defined as and normalized , wherein is the selected Fourier order (generally 20-60), is the coefficient amplitude of the i-th order.

[0055] In the above manner, the normalized Fourier descriptor of each cross-section airfoil is obtained, and is represented by , wherein r represents the number of the cross-section airfoil.

[0056] S5, airfoil matching and aerodynamic polar reconstruction:

[0057] S51, the descriptor corresponding to each cross-section airfoil is compared with the descriptor in the existing airfoil database to obtain a similarity distance , and the minimum distance airfoil is obtained accordingly. Preferably, the similarity distance is calculated as follows:

[0058]

[0059]

[0060] , wherein is the covariance matrix of the descriptor in the airfoil database, is the number of airfoils in the airfoil database, is the mean value of all sample descriptors in the airfoil database, which is determined by the existing airfoil database.

[0061] S52, whether the minimum distance airfoil satisfies the set matching condition is determined, specifically, a determination value may be set, if , it is considered that the condition is satisfied, and the matching is successful, if , it is considered that the condition is not satisfied, and the matching fails.

[0062] If the matching is successful, i.e. , the airfoil polar attached in the existing airfoil database is directly called: , wherein is the lift coefficient polar, ​​​is the drag coefficient polar line, is the angle of attack, is the local Reynolds number. This method does not need to be calculated again, and the calculation efficiency is high.

[0063] If the matching fails, that is, , the Using numerical solution, the solution method can adopt the existing XFoil or Viterna method to calculate the aerodynamic polar line. Preferably, at the same time, the descriptor corresponding to the cross-sectional airfoil is also added to the existing airfoil database:

[0064] ,

[0065] Thus, the self-learning and continuous expansion of the database are realized.

[0066] S6, aerodynamic and geometric parameter output:

[0067] After the above steps S1-S5, the geometric control parameters and aerodynamic characteristic parameters of the cross-sectional airfoil obtained by each cross section are obtained, denoted as These data are input into the blade momentum (BEM) model or CFD simulation for calculating the blade aerodynamic moment, thrust distribution and power output, so as to realize the performance evaluation and difference analysis of the blade in the experimental, manufacturing and running stages.

[0068] The reverse aerodynamic performance evaluation method of the fan blade of the present application has the following intended effects:

[0069] 1) The prior airfoil and polar line are not needed, and the reverse evaluation and difference diagnosis of the aerodynamic performance of the fan blade can be realized by reverse evaluation from the real geometry, so as to improve the accuracy and independence of the experimental verification, manufacturing acceptance and running monitoring stages, and the dependence on manufacturers can be eliminated; 2) it can adapt to in-service changes, and naturally cover the shape drift caused by wear, pollution and repair; 3) it can realize the quantification of manufacturing consistency, and measure the production deviation by geometric + aerodynamic response double indicators; 4) it can be seamlessly connected with BEM / FAST tools, has low calculation cost, can be applied in batches, and is convenient for engineering landing; 5) it can access larger airfoil library, more aerodynamic correction models and field data, and has good expandability.

[0070] In summary, the present application effectively overcomes the various shortcomings in the prior art and has high industrial utilization value.

[0071] The above embodiments are only illustrative of the principles of the present application and its efficacy, and are not intended to limit the present application. Any modification or change made by any person skilled in the art without departing from the spirit and scope of the present application shall be covered by the claims of the present application.

Claims

1. A method for evaluating the reverse aerodynamic performance of wind turbine blades, characterized in that: Includes the following steps: S1. Blade Shape Point Cloud Data Establishment: Perform a full-surface 3D scan of the target wind turbine blade and process the scan data to obtain the blade's shape point cloud data. ,in, This represents the three-dimensional coordinates of the i-th shape point in the blade coordinate system, where N is the total number of point clouds, and the z-axis of the blade coordinate system is along the span of the blade. S2. Extraction of cross-sectional airfoil and geometric parameters: R cross-sections perpendicular to the span are cut along the blade span at a set interval, and the cross-sections are then arranged along the blade span. The range is denoted as a segment, resulting in R segments; the set of points containing the blade shape within the range of the r-th segment is... ,in This indicates that the segment is in the scan coordinate system. The coordinates; then smoothed using a smoothing function. Remove high-frequency noise. To obtain the cross-sectional airfoil with a continuous closed profile under this cross-section; S3. Cross-sectional feature identification and normalization: For each cross-sectional airfoil obtained in step S3, the following processing is performed: S31. Identify the leading and trailing edge points of the airfoil section, and denot their coordinates as follows: and ; S32. Calculate the chord length of the cross-section. With twist ,in , ； S33. Normalize the airfoil section under a unit chord length and horizontal chord reference: ,in Represents a counterclockwise rotation around the origin. A two-dimensional rotation matrix, a set of points Let be the set of normalized airfoil coordinate points; S4. Fourier descriptor calculation: The normalized airfoil sections from step S3 are processed as follows: S41. Resample the normalized airfoil section from step S3 according to the equal arc length. Construct a complex sequence from points. ,in The imaginary unit; S42, For complex sequences Perform a discrete Fourier transform. The Fourier descriptor for the cross-section airfoil is defined as follows: And perform normalization processing. ,in The selected Fourier order For the first The magnitude of the order coefficient; S5. Airfoil matching and aerodynamic pole reconstruction: S51. Descriptors corresponding to each airfoil section Descriptors in the airfoil database Perform similarity calculation to obtain the similarity distance. And based on this, the minimum distance airfoil is obtained. ; S52, Determining the minimum distance airfoil If the set matching conditions are met, the match is considered successful, and the airfoil pole table attached to the existing airfoil database is directly called. If the conditions are not met, the match is considered unsuccessful, and the airfoil section is then processed. The aerodynamic poles are calculated using numerical methods.

2. The method for evaluating the reverse aerodynamic performance of wind turbine blades according to claim 1, characterized in that: In step S1, a full-surface three-dimensional scan of the target wind turbine blade is performed to obtain the original cloud data of the scan points of the blade's shape. Then, the scanned point cloud data is transformed to obtain the coordinates of the scanned points in the blade coordinate system, thus obtaining the blade's shape point cloud data. .

3. The method for evaluating the reverse aerodynamic performance of wind turbine blades according to claim 1 or 2, characterized in that: In step S1, the point cloud data of the blade's shape is further denoised to remove outliers.

4. The method for evaluating the reverse aerodynamic performance of wind turbine blades according to claim 1, characterized in that: In step S2, the number of cross sections R ranges from 10 to 20.

5. The method for evaluating the reverse aerodynamic performance of wind turbine blades according to claim 1 or 4, characterized in that: In step S2 The range of values ​​is L is the blade length.

6. The method for evaluating the reverse aerodynamic performance of wind turbine blades according to claim 1, characterized in that: In step S2, the smoothing function is obtained through B-spline fitting or local polynomial smoothing.

7. The method for evaluating the reverse aerodynamic performance of wind turbine blades according to claim 1, characterized in that: In step S4, the number of sampling points The value range is 100~200.

8. The method for evaluating the reverse aerodynamic performance of wind turbine blades according to claim 1, characterized in that: In step S51, the similarity distance The calculation method is as follows: , The covariance matrix of the descriptors in the airfoil database is calculated using the following formula. ,in The current number of airfoils in the airfoil database, It is the mean of all sample descriptors in the airfoil database.

9. The method for evaluating the reverse aerodynamic performance of wind turbine blades according to claim 1, characterized in that: Step S52 further includes: when the matching fails, the descriptor and pole table data corresponding to the airfoil section are also added to the existing airfoil database.

10. The method for evaluating the reverse aerodynamic performance of wind turbine blades according to claim 1, characterized in that: Also includes: S6. Aerodynamic and geometric parameter output: Obtain the combination of geometric control parameters and aerodynamic characteristic parameters for each airfoil section. ,Will By inputting the blade element momentum model or CFD simulation, the aerodynamic torque, thrust distribution and power output of the blade can be calculated, thereby realizing the performance evaluation and difference analysis of the blade in the experimental, manufacturing and operation stages.

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