Method, device and equipment for determining geometric characteristics of centrifugal fan blades and medium

Abstract

The present disclosure relates to the technical field of computer-aided detection of fluid machinery, and particularly relates to a centrifugal fan blade geometric feature determination method, device, equipment and medium, which is used to solve the problems of large calculation amount and low processing efficiency of traditional determination methods of middle camber lines, and the method comprises: determining a first camber line point set and a second camber line point set for representing the surface shape of the centrifugal fan blade; for a first point in the first camber line point set, a nonlinear analytical model is established based on the parametric representation of an inscribed circle, the nonlinear analytical model defines a geometric tangent constraint based on the first point and an unknown second point on the second camber line; the position of the unknown second point on the second camber line is determined according to the nonlinear analytical model; the center point of the inscribed circle is calculated based on the first point and the determined second point; the middle camber line is fitted based on the traversal of all first points in the first camber line point set and the use of multiple center points; and at least one geometric feature of the centrifugal fan blade is determined by using the middle camber line.

Description

Technical Field

[0001] This disclosure relates to the field of computer-aided detection technology for fluid machinery, and in particular to a method, apparatus, equipment and medium for determining the geometric features of centrifugal fan blades. Background Technology

[0002] In the manufacturing and quality control of high-performance turbomachinery (such as centrifugal fans and aero-engine turbines), blade geometry is a core factor determining its aerodynamic performance, efficiency, and safety. Therefore, accurately measuring key geometric features after blade manufacturing to verify their conformity with original design parameters is a crucial quality assurance step. The mean camber line, as a fundamental geometric element describing blade curvature, is the basis for determining several key aerodynamic parameters such as blade wrap angle and installation angle. Therefore, accurate and rapid analysis of the mean camber line is the core of the entire geometric feature determination process.

[0003] Currently, traditional techniques used in this field to determine the arc of blades are computationally intensive and have low processing efficiency. Summary of the Invention

[0004] In view of this, the present disclosure aims to provide a method, apparatus, device and medium for determining the geometric features of centrifugal fan blades; it can solve the technical problems of traditional methods for determining the arc of blades, which involve large computational load and low processing efficiency.

[0005] The technical solution of this disclosure embodiment is implemented as follows:

[0006] In a first aspect, embodiments of this disclosure provide a method for determining the geometric features of centrifugal fan blades, including:

[0007] Determine the first and second arc point sets to characterize the surface shape of centrifugal fan blades;

[0008] For the first point in the first arc point set, a nonlinear analytical model is established based on the parameterized representation of the inscribed circle, wherein the nonlinear analytical model is constrained by a geometric tangency constraint based on the first point and an unknown second point on the second arc.

[0009] Based on the nonlinear analytical model, determine the position of the unknown second point on the second arc;

[0010] Based on the first point and the determined second point, calculate the center point of the inscribed circle;

[0011] Based on traversing all the first points in the first arc point set and fitting the middle arc using multiple center points,

[0012] Using the mid-arc line, at least one geometric feature of the centrifugal fan blade is determined.

[0013] Secondly, embodiments of this disclosure provide a device for determining the geometric features of centrifugal fan blades, including:

[0014] The point set determination module is used to determine a first arc point set and a second arc point set for characterizing the surface shape of centrifugal fan blades;

[0015] The model building module is used to build a nonlinear analytical model for the first point in the first arc point set based on the parameterized representation of the inscribed circle. The nonlinear analytical model is based on the first point and an unknown second point on the second arc to constrain a geometric tangency constraint.

[0016] The location determination module is used to determine the coordinates of the unknown second point on the second arc based on a nonlinear analytical model.

[0017] The data calculation module is used to calculate the coordinates of the center point of the inscribed circle based on the coordinates of the first point and the determined second point;

[0018] The arc generation module generates a middle arc based on a set of center point coordinates calculated by traversing all the first points in the first arc point set;

[0019] The feature determination module determines at least one geometric feature of the centrifugal fan blade based on the mid-arc line.

[0020] Thirdly, embodiments of this disclosure provide an electronic device, which includes a processor and a memory; the processor is used to execute instructions stored in the memory to implement the centrifugal fan blade geometric feature determination method of the first aspect.

[0021] Fourthly, embodiments of this disclosure provide a computer storage medium storing at least one instruction, which is executed by a processor to implement the centrifugal fan blade geometric feature determination method of the first aspect.

[0022] This disclosure provides a method, apparatus, device, and medium for determining the geometric features of centrifugal fan blades. By using a nonlinear analytical model, the position of an unknown second point on a second arc is determined, transforming the search for the second point from a time-consuming traversal search problem into a model-solving problem. For any first point on the first arc, the position of its corresponding second point can be determined by directly solving the model or numerical approximation, without needing to traverse the second arc again. The computational process required to determine the arc is simplified from a double traversal to a single traversal of the first arc's point set, thereby reducing the overall time complexity of the algorithm. Attached Figure Description

[0023] Figure 1 A flowchart illustrating a method for determining the geometric features of centrifugal fan blades, provided in an embodiment of this disclosure.

[0024] Figure 2 This is a schematic diagram of a two-dimensional profile of a primitive blade provided in an embodiment of this disclosure.

[0025] Figure 3 This is a schematic diagram of solving the arc from the inscribed circle according to an embodiment of the present disclosure.

[0026] Figure 4 This is a schematic diagram of key parameters of a medium arc provided in an embodiment of this disclosure.

[0027] Figure 5 This is a schematic diagram of a device for determining the geometric features of centrifugal fan blades, provided in an embodiment of this disclosure.

[0028] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure.

[0029] The accompanying drawings have illustrated specific embodiments of this disclosure, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concepts of this disclosure to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0030] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that this disclosure will be more comprehensive and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0031] Furthermore, the accompanying drawings are merely illustrative of this disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0032] Currently, the traditional techniques used in this field to analyze the mid-curve of blades are based on the geometric constraint of the inscribed circle, meaning the mid-curve is the trajectory of the centers of all inscribed circles simultaneously tangent to the pressure and suction surfaces of the blade. To find the center points of these inscribed circles, traditional methods generally employ a geometric search algorithm, which has a fundamental structural flaw in its implementation. Specifically, this algorithm requires a double-loop traversal of the discrete point sets on the two curves. Its execution logic is as follows: using a point on the first curve as a reference, it sequentially traverses all points on the second curve, using complex geometric calculations to determine whether the inscribed circle constraints defined by these two points meet a preset accuracy threshold. Only after traversing all points on the second curve can the unique second point corresponding to the first point that satisfies the condition be determined. Subsequently, the algorithm selects the next point on the first curve and repeats the entire traversal process until all the center points constituting the complete mid-curve are found.

[0033] This double-traversal algorithm structure results in a computational load that is directly proportional to the product of the number of sampling points on the two arcs, leading to high time complexity. In modern high-precision manufacturing, to ensure the accuracy of the final identification parameters (e.g., at the micrometer level), the number of sampling points on the blade profile is enormous. This causes the total computational load to increase exponentially, with a single detection often taking several minutes.

[0034] With the development of high-speed data acquisition technologies such as 3D optical scanning, the time for hardware to acquire high-density point clouds on the blade surface has been reduced to the second level. However, the low efficiency of the backend data processing algorithms still results in a serious production bottleneck in the entire inspection process. This minute-level computational delay makes it impractical to perform 100% full-size online inspection (In-line Metrology) on every blade that comes off the production line within the production cycle. As a last resort, an inefficient offline sampling inspection method is adopted, which not only reduces production efficiency but also increases the risk of defective products flowing into the next process.

[0035] Existing geometric search methods based on double traversal suffer from fundamental drawbacks when processing high-density blade profile data, including enormous computational load, severe time consumption, and low efficiency. This deficiency causes software processing speed to lag far behind hardware acquisition speed, creating an efficiency bottleneck in the entire automated inspection process and failing to meet the urgent needs of modern manufacturing for high-throughput, high-precision, and online full-size quality control.

[0036] Based on this, this disclosure proposes a method for determining the geometric characteristics of centrifugal fan blades, such as... Figure 1 As shown, the method for determining the geometric features of centrifugal fan blades may include steps S110 to S160.

[0037] In step S110, a first set of arc points and a second set of arc points are determined to characterize the surface shape of the centrifugal fan blades.

[0038] In some examples of this disclosure, the first arc point set and the second arc point set refer to the sets of discrete points on the two main curves that constitute the two-dimensional cross-sectional profile of the blade, which typically correspond to the pressure surface and suction surface of the blade.

[0039] Specifically, a large number of three-dimensional coordinate points on the blade surface can be obtained through non-contact measurement technologies such as three-dimensional optical scanning. Then, through geometric projection, these three-dimensional points are mapped onto a preset two-dimensional plane to obtain a preliminary two-dimensional profile. To ensure the accuracy and stability of subsequent calculations, these initial point sets will undergo data processing, such as generating smooth mathematical curves through curve fitting. Then, according to the accuracy requirements, the curves will be resampled at high density to finally obtain high-quality, high-density first and second arc point sets, laying a solid foundation for establishing accurate mathematical models.

[0040] In step S120, a nonlinear analytical model is established for the first point in the first arc point set based on the parameterized representation of the inscribed circle.

[0041] The nonlinear analytical model uses an unknown second point on the first and second arcs to constrain a geometric tangency constraint.

[0042] In some examples disclosed herein, a nonlinear analytical model is established for a first point in the first arc point set. A nonlinear analytical model refers to one or a set of mathematical equations that accurately and nonlinearly describe the inherent constraints that the blade geometry must satisfy. Specifically, the nonlinear analytical model is established based on the parameterized representation of the inscribed circle. The inscribed circle is a virtual circle that is simultaneously tangent to both the first and second arcs, and its center is a point constituting the middle arc.

[0043] Parametric representation is a method of describing geometric objects (such as the position and radius of the center point of an inscribed circle) using variables (parameters). The core of the nonlinear analytical model is a geometric tangency constraint: the center point of the inscribed circle must simultaneously lie at the intersection of the normal line (the line perpendicular to the tangent) at the first point and the normal line at the unknown second point. By expressing this series of geometric relationships using parametric equations and performing algebraic elimination, a nonlinear analytical model containing only a single variable related to the position of the unknown second point can be obtained.

[0044] In step S130, the position of the unknown second point on the second arc is determined according to the nonlinear analytical model.

[0045] In some examples disclosed herein, efficient numerical computation methods are used to solve the complex nonlinear analytical model established in the previous step, thereby accurately locating the unique point on the second arc that satisfies the geometric tangency constraint. Since the model is "nonlinear," it means it cannot be solved directly like a simple linear equation. A numerical approximation method is used, starting with a reasonable initial guess (e.g., using the position of the first point as an initial approximation of the second point's position). Then, utilizing the mathematical principles inherent in the nonlinear analytical model itself, through repeated and systematic correction calculations, this approximation gradually and rapidly converges to the true solution. When the difference between two correction calculations is less than a preset, extremely small precision threshold, the precise location of the unknown second point can be considered found. Through this step, this method completely avoids the inefficient process of traversing the second arc point by point.

[0046] In step S140, the center point of the inscribed circle is calculated based on the first point and the determined second point.

[0047] In some examples disclosed herein, with the positions of the two key tangent points, the first and second points, already determined, the geometric properties of the inscribed circle (including the center position and radius) jointly defined by them are uniquely locked. The calculation process is deterministic; for example, the position of the center point can be directly obtained by solving for the intersection of the normals of these two points. The center point of this calculated inscribed circle is essentially a discrete point constituting the final mid-curve. Therefore, this step serves as a bridge connecting the single-point constraint solution with the generation of the final mid-curve, transforming the complex model solution results from the preceding steps into a specific geometric element constituting the final target curve.

[0048] In step S150, the arc is fitted by traversing all the first points in the first arc point set and using multiple center points.

[0049] In some examples disclosed herein, the solution process for a single point is systematically extended to the entire blade profile, and the discrete solution results are ultimately integrated into a continuous, smooth engineering curve. Here, traversal refers to systematically and sequentially treating each point in the first arc point set as the "first point" and repeatedly executing the aforementioned steps S120 to S140 to calculate the corresponding inscribed circle center point. A discrete point cloud representing the shape of the mid-arc line is generated. However, discrete point clouds are not practical for engineering analysis, so fitting is necessary. A continuous curve that smoothly passes through all these center points is found using methods such as spline curve fitting. This ultimately generated curve is the mid-arc line of the blade.

[0050] In step S160, at least one geometric feature of the centrifugal fan blade is determined using the mid-arc line.

[0051] In some examples disclosed herein, geometric features include several specific parameters such as the blade's inner diameter, outer diameter (determined by the start and end points of the mid-curve, respectively), wrap angle (the angle between the two endpoints of the mid-curve relative to the center of rotation), mounting angle (the angle between the chord of the mid-curve and a specific direction), and thickness distribution (determined by a series of inscribed circle radii recorded during the traversal). By performing geometric measurements and calculations on the mid-curve, the values ​​of these features can be accurately obtained, thus providing reliable, quantitative data support for blade quality inspection, performance evaluation, or reverse engineering.

[0052] This disclosed method for determining the geometric features of centrifugal fan blades uses a nonlinear analytical model to determine the position of an unknown second point on the second arc. This transforms the process of finding the second point from a time-consuming traversal search problem into a model-solving problem. For any first point on the first arc, the position of its corresponding second point can be determined by directly solving the model or through numerical approximation, without needing to traverse the second arc again. The computational process required to determine the arc is simplified from a double traversal to a single traversal of the first arc's point set, thereby reducing the overall time complexity of the algorithm.

[0053] Specifically, the centrifugal fan blades can first be scanned using a 3D scanning device to obtain a 3D coordinate dataset. The 3D scanning device can be a non-contact, high-speed measurement device such as a laser scanner or structured light scanner, which can acquire the 3D coordinate points on the blade surface in a very short time, forming point cloud data.

[0054] After acquiring the 3D coordinate dataset, it needs to be projected onto a predefined 2D plane. This predefined 2D plane can be a key cross-section perpendicular to the impeller's rotation axis. Through projection, the high-dimensional 3D point cloud data is reduced in dimensionality, forming a series of discrete points that represent the blade's profile at that cross-section.

[0055] However, the point sets obtained directly from the projection of the original scan data—the first initial point set and the second initial point set—may contain problems such as noise, uneven density, and data redundancy, which are detrimental to subsequent high-precision differentiation and geometric operations. Therefore, further refinement processing of these two initial point sets is required.

[0056] Before refining, the two-dimensional image obtained from the projection needs to be processed first. This can be done by extracting connected components, referring to... Figure 2 This method can separate different geometric elements in a binarized image, typically including positioning circles, upper arcs, and lower arcs. By recording the row and column indices of all pixels in each region, the image coordinates of all points on each curve are obtained.

[0057] To convert the pixel coordinates or device coordinates obtained from scanning into engineering coordinates with actual physical meaning, coordinate transformation is usually required. If there is a positioning circle on the blade with known actual size and position, the coordinate transformation relationship can be established by fitting the positioning circle. For example, given the starting points of the image coordinates of three points on positioning circle 23 in the image. Midpoint End point The center of the circle in the image coordinate system can be determined by solving the following system of equations:

[0058]

[0059] Where the superscript p represents the image coordinate system, This represents the radius of positioning circle 23 in the image. After determining the center and radius of the circle in the image, we combine this with the known center and radius of the positioning circle in the actual coordinate system. The image coordinates of any point can be converted to actual coordinates using the following conversion formula ( ):

[0060]

[0061] Through this transformation, the first and second initial point sets obtain coordinates with real physical dimensions.

[0062] In this embodiment, a smooth and continuous mathematical expression of the blade profile is obtained by fitting the first initial point set and the second initial point set to their respective first and second polynomial functions. The principle of "fitting" here is to find a mathematical curve that best approximates the given discrete point set. For example, the least squares method can be used to find a set of polynomial coefficients that minimizes the sum of the squared distances from all initial points to the polynomial curve. Through this step, we transform the discrete, imperfect point set into an accurate, differentiable mathematical function, such as a fourth-order polynomial of the following form:

[0063]

[0064] Where x and y are the coordinates of a point on the curve. , , These are the polynomial coefficients obtained by solving the least squares method.

[0065] After obtaining the continuous polynomial function, to ensure the accuracy of subsequent calculations, resampling can be performed based on the first and second polynomial functions with a preset precision to generate a first arc point set and a second arc point set. Specifically, using the obtained continuous function, sampling points of arbitrary density can be generated. For example, if the preset precision is at the micrometer level, new, very dense sampling points can be generated on the continuous function with a micrometer-level step size. The point sets generated after resampling are the first arc point set and the second arc point set.

[0066] In some examples, the geometric constraint problem for determining the center point of the inscribed circle can be transformed into a problem of solving algebraic equations. (See also...) Figure 3 The inscribed circle 25 refers to a virtual circle that is simultaneously tangent to the first arc 21 and the second arc 22, and its center is a point that constitutes the middle arc 24. The geometric tangency constraint is physically and geometrically definite and unique. In the embodiments of this disclosure, this constraint is specifically manifested as the center point being the intersection of the normal at the first point and the normal at the unknown second point.

[0067] When transforming the geometric constraint problem for determining the center point of the inscribed circle 25 into an algebraic equation problem, we can first establish a system of equations to parametrically represent the coordinates of the center point based on the first point and the unknown second point. Parametric representation is a mathematical method that uses variables (parameters) to describe the position of a geometric object. Let the coordinates of the center of the inscribed circle 25 be ( radius is For the first point in the first arc point set ( ) and its normal direction angle are And for the unknown second point in the set of points on the second arc ( ) and its normal direction angle are The following system of parametric equations can be established:

[0068]

[0069]

[0070] in, It is an unknown parameter representing the radius of the inscribed circle 25; () are the unknown coordinates of the center point of the inscribed circle 25; ), The coordinates and normal angle of the first point on the first arc 21 are known; ), These are the coordinates and normal angle of an unknown second point on the second arc 22, where... yes The function can be determined by the fitted second polynomial function and its derivative.

[0071] After establishing two sets of parametric equations, this method obtains a nonlinear analytical model by performing algebraic elimination on the equations. Algebraic elimination refers to using a series of algebraic operations (such as equation substitution) to eliminate variables in the equations that are related to the coordinates of the center point (…). ) and radius All related unknown parameters were eliminated, resulting in a value that only contained the second unknown point. The relevant single-variable mathematical equation. This final mathematical equation is the nonlinear analytical model, and its specific form is as follows:

[0072]

[0073] Nonlinear analytical models are nonlinear and usually cannot be solved directly. However, the location of an unknown second point can be determined by numerically approximating the roots of the nonlinear analytical model. Numerical approximation refers to obtaining an approximate solution that is infinitely close to the exact solution through a series of calculations, rather than directly solving for the exact solution.

[0074] In this embodiment, the position of the first point can be used as an initial approximation of the unknown position of the second point. Specifically, the x-coordinate of the first point can be used as an approximation. Set as the unknown x-coordinate of the second point The initial value of the iteration, i.e. After setting an initial approximation value, the position of the unknown second point can be repeatedly corrected based on the initial approximation value and the nonlinear analytical model until the corrected position satisfies the preset convergence condition. Correction utilizes the mathematical laws inherent in the nonlinear analytical model to calculate a correction amount, which is then applied to the current approximation value to obtain a new approximation value that is closer to the true solution. For example, Newton's iteration method can be used as the basis for correction, and its iterative formula is:

[0075]

[0076] Where k is the number of iterations; It is the first The iteration yielded Approximate solution; It is the function value of the model at the current approximate solution; It is the derivative of the model with the current approximate solution, and its expression is:

[0077]

[0078] The correction process is repeated, and each time it is performed, the approximate solution becomes more accurate. The solution is considered more precise when the difference between two consecutive corrections is less than a preset accuracy threshold. (That is, satisfying the "convergence condition"), for example The iterative calculation terminates, and the final position obtained at this point is considered to be the precise position of the unknown second point.

[0079] The specific process involves selecting an initial approximation value for the iteration. For simplicity, let the initial value be... ,calculate ;

[0080] According to the formula Iteration yields new approximations. ,calculate ;

[0081] If or Then the iteration terminates. That is, the exact location of the second point is unknown; otherwise, it is... replace Continue iterative calculations; finally, the solution is obtained using the above method. Then, based on the initial system of equations, we can obtain... This refers to the center and radius of the inscribed circle 25. Iterate through all points on the lower arc. The centers and radii of a series of inscribed circles 25 can then be obtained. These points on the mid-arc 24 formed by the centers of the inscribed circles 25 can be represented as follows:

[0082]

[0083] The set consisting of the radii of the inscribed circles is represented as:

[0084]

[0085] This is a discrete point cloud that can represent the shape of the mid-curve 24. Then, through fitting, such as using spline curve fitting or other mathematical methods, a continuous curve that most accurately and smoothly passes through all these center points is found. This final generated curve is the mid-curve 24 of the blade.

[0086] After determining the mid-curve 24, at least one geometric feature of the centrifugal fan blade can be determined based on the aforementioned mid-curve 24. In some examples, refer to Figure 4 Geometric features can include blade inner diameter, blade outer diameter, blade chord length, maximum blade thickness, blade thickness distribution, blade wrap angle, blade mounting angle, and blade inlet or outlet angle. The calculation formulas are as follows:

[0087] blade inner diameter :

[0088]

[0089] Among them, the inner diameter of the blade The starting point of the middle arc 24 ( The distance from the origin of the coordinate system.

[0090] blade outer diameter :

[0091]

[0092] Among them, the outer diameter of the blade The endpoint of the middle arc 24 ( The distance from the origin of the coordinate system.

[0093] Leaf chord length :

[0094]

[0095] Among them, the chord length of the blade This is the straight-line distance between the starting and ending points of the middle arc 24.

[0096] Maximum blade thickness (Not shown):

[0097]

[0098] Maximum blade thickness It is twice the maximum value of the radius of all inscribed circles calculated during the traversal process.

[0099] Blade thickness distribution (Not shown):

[0100]

[0101] Among them, the blade thickness distribution It is obtained by associating the radii of a series of inscribed circles 25 with the positions of the middle arc 24 recorded during the traversal process.

[0102] Corner :

[0103]

[0104] Among them, the corner The impeller center, the starting point of the middle arc line 24 ( ) and the endpoint of the middle arc 24 ( The angle formed by ).

[0105] Installation corner :

[0106]

[0107] Among them, the installation angle It is the angle between the chord and the tangent to the outer diameter.

[0108] Entrance corner :

[0109]

[0110] Exit Angle :

[0111]

[0112] Among them, the entrance corner and exit angle The middle arc 24 is at the starting point ( ) and endpoint ( The tangent angle at ().

[0113] By performing the aforementioned geometric measurements and calculations on the mid-arc line 24, the numerical values ​​of these characteristics can be accurately obtained, thereby providing reliable and quantitative data support for blade quality inspection, performance evaluation, or reverse engineering.

[0114] The following specific example illustrates the difference between the method of this disclosure and the conventional method. Specifically, the conventional method and the method of this disclosure are executed using the same blade, the same processor, and the same memory. The lower arc length of the blade is 105 mm, the upper arc length is 98 mm, the processor is an Intel(R) Core(TM) Ultra 5 235H (2.40 GHz), and the memory is 16 GB of DDR5 memory (4800 MHz). The specific results are shown in Table 1.

[0115] Table 1

[0116]

[0117] The data shown in Table 1 clearly demonstrates the significant technical effects brought about by the embodiments of this disclosure. Firstly, when the number of first-order iterations (lower arc) is the same, i.e., when processing the same number of reference points, the traditional algorithm requires significantly more second-order iterations. This is essentially a point-by-point traversal of the upper arc to find the corresponding tangent point. In stark contrast, the average number of double iterations in the algorithm of this disclosure is only about 60. This is not a traversal, but rather the average number of computational steps required for Newton's iteration method to converge when solving nonlinear analytical models. Furthermore, the total number of iterations in this disclosure decreases exponentially. As shown in Table 1, the total number of iterations in the traditional algorithm is... The total number of iterations of the algorithm in this embodiment is sharply reduced to This represents a reduction of more than three orders of magnitude. Ultimately, the traditional algorithm takes 227.6 seconds, nearly four minutes, to complete a single geometric feature determination, resulting in a high time cost. In contrast, the algorithm in this disclosure, while maintaining the same accuracy, completes all calculations in just 0.213 seconds, representing a speed improvement of over 1000 times. This leap from minutes to sub-seconds is not only a significant numerical improvement but also makes 100% online full-size detection, previously impossible due to excessive time consumption, a practical reality. This solves the bottleneck problem in existing technologies where software processing speed lags far behind hardware acquisition speed.

[0118] This embodiment fundamentally changes the algorithm's structure and reduces computation time by transforming the geometric search problem of determining the center arc 24 of the blade into a nonlinear analytical model solution problem. It solves the pain point of mismatch between software processing speed and high-speed 3D scanning hardware acquisition speed in existing technologies, eliminating the efficiency bottleneck in the entire automated inspection process. This makes it possible to perform 100% full-size, high-precision online quality inspection on every blade produced within the production cycle, greatly improving product reliability and reducing the risk of performance degradation or potential failure due to geometric deviations. Since the algorithm's time complexity is linear, users can meet the most stringent accuracy requirements by increasing the initial sampling point density without sacrificing computational efficiency, achieving a balance between high precision and high efficiency, which is particularly important for the inspection of ultra-high precision components such as aero-engine blades. When determining key parameters such as the blade's inlet and outlet angles, a discrete-point difference formula is used for calculation, without relying on a specific form of curve fitting to the center arc 24. This method enhances the applicability and robustness of this disclosure to various complex blade shapes (such as single circular arcs, double circular arcs, and even free curves), ensuring accurate parameter identification results in different design scenarios.

[0119] Further reference Figure 5 As shown, this example embodiment also provides a centrifugal fan blade geometric feature determination device 500, including a point set determination module 510, a model building module 520, a position determination module 530, a data calculation module 540, an arc generation module 550, and a feature determination module 560. Wherein:

[0120] The point set determination module 510 can be used to determine a first arc point set and a second arc point set for characterizing the surface shape of centrifugal fan blades;

[0121] The model building module 520 can be used to build a nonlinear analytical model for the first point in the first arc point set based on the parameterized representation of the inscribed circle. The nonlinear analytical model is based on an unknown second point on the first and second arcs to constrain a geometric tangency constraint.

[0122] The position determination module 530 can be used to determine the coordinates of an unknown second point on the second arc based on a nonlinear analytical model;

[0123] The data calculation module 540 can be used to calculate the coordinates of the center point of the inscribed circle based on the coordinates of the first point and the determined second point;

[0124] The arc generation module 550 can generate a middle arc based on a set of center point coordinates calculated by traversing all the first points in the first arc point set;

[0125] The feature determination module 560 can determine at least one geometric feature of the centrifugal fan blade based on the mid-arc line.

[0126] In some examples, the point set determination module 510 can also be used to scan the centrifugal fan blades with a 3D scanning device to obtain a 3D coordinate dataset; project the 3D coordinate dataset onto a preset 2D plane to generate a first arc point set and a second arc point set.

[0127] In some examples, the point set determination module 510 can also be used to project a three-dimensional coordinate dataset onto a preset two-dimensional plane, a first initial point set and a second initial point set; respectively, using the least squares method, to fit the first initial point set and the second initial point set into their respective first polynomial functions and second polynomial functions; based on the first polynomial function and the second polynomial function, to resample according to a preset precision, so as to generate a first arc point set and a second arc point set.

[0128] In some examples, the location determination module 530 can also be used to determine the location of an unknown second point by numerically approximating the roots of a nonlinear analytical model.

[0129] In some examples, the position determination module 530 can also be used to take the position of the first point as an initial approximation of the position of the unknown second point; based on the initial approximation and the nonlinear analytical model, the position of the unknown second point is corrected until the corrected position satisfies the preset convergence condition.

[0130] In some examples, the model building module 520 can also be used to build a system of equations for parametrically representing the coordinates of the center point based on the first point and the unknown second point, respectively, and to obtain a nonlinear analytical model by performing algebraic elimination on the system of equations; wherein, the geometric tangency constraint includes the center point being the intersection of the normal at the first point and the normal at the unknown second point.

[0131] In some examples, at least one geometric feature is identified, including at least one selected from the group consisting of: blade inner diameter, blade outer diameter, blade chord length, blade maximum thickness, blade thickness distribution, blade wrap angle, blade mounting angle, blade inlet angle, or blade outlet angle.

[0132] It should be understood that the above-described device embodiments are merely illustrative, and the device disclosed herein can be implemented in other ways. For example, the division of units / modules in the above embodiments is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units, modules, or components may be combined, integrated into another system, or some features may be ignored or not executed.

[0133] Furthermore, unless otherwise specified, the functional units / modules in the various embodiments of this disclosure can be integrated into one unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated together. The integrated units / modules described above can be implemented in hardware or as software program modules.

[0134] When integrated units / modules are implemented in hardware, the hardware can be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor can be any suitable hardware processor, such as a CPU, GPU, FPGA, DSP, and ASIC, etc. Unless otherwise specified, the storage unit can be any suitable magnetic or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc.

[0135] If the integrated unit / module is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMSDD). Based on this understanding, the technical solution of this disclosure, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this disclosure. The aforementioned memory includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0136] Please refer to Figure 6 This diagram illustrates a structural block diagram of an electronic device provided in an exemplary embodiment of this disclosure. In some examples, the electronic device may be at least one of devices such as a smartphone, smartwatch, desktop computer, laptop, virtual reality terminal, augmented reality terminal, wireless terminal, and laptop computer. The electronic device has communication capabilities and can access wired or wireless networks. The term "electronic device" can refer to one of multiple terminals; those skilled in the art will understand that the number of terminals may be more or less. It is understood that the electronic device undertakes the computational and processing work of the technical solution of this disclosure, and the embodiments of this disclosure do not limit this aspect.

[0137] like Figure 6 As shown, the electronic device 600 may include at least one processor 610, a memory 620, and a communication interface 630.

[0138] The memory 620 is used to store programs. Specifically, the program may include program code, which includes computer operation instructions.

[0139] The memory 620 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0140] The processor 610 executes computer execution instructions stored in the memory 620 to implement the centrifugal fan blade geometric feature determination method described in the foregoing method embodiments. The processor 610 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this disclosure.

[0141] The electronic device 600 may also include a communication interface 630, through which it can communicate and interact with external devices. In specific implementations, if the communication interface 630, memory 620, and processor 610 are implemented independently, they can be interconnected via a bus to complete communication. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc., but this does not imply that there is only one bus or one type of bus.

[0142] Optionally, in a specific implementation, if the communication interface 630, memory 620 and processor 610 are integrated on a single chip, then the communication interface 630, memory 620 and processor 610 can communicate through an internal interface.

[0143] This disclosure also provides a computer storage medium, which may include various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory, a random access memory, a disk, or an optical disk. Specifically, the computer storage medium stores program instructions, which are used for the centrifugal fan blade geometric feature determination method in the above embodiments.

[0144] This disclosure also provides a computer program product, which includes computer instructions stored in a computer storage medium; a processor of an electronic device reads the computer instructions from the computer storage medium and executes the computer instructions, causing the electronic device to perform the centrifugal fan blade geometric feature determination method of the above embodiments.

[0145] Those skilled in the art will recognize that the functions described in the embodiments of this disclosure in one or more of the foregoing examples can be implemented using hardware, software, firmware, or any combination thereof. When implemented in software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transfer of a computer program from one place to another. Storage media can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0146] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0147] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention applied herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not claimed herein.

[0148] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A method for determining the geometric features of centrifugal fan blades, characterized in that, include: Determine the first and second arc point sets to characterize the surface shape of centrifugal fan blades; For the first point in the first arc point set, a nonlinear analytical model is established based on the parameterized representation of the inscribed circle, wherein the nonlinear analytical model is based on an unknown second point on the first and second arcs to constrain a geometric tangency constraint. Based on the nonlinear analytical model, determine the position of the unknown second point on the second arc; Based on the first point and the determined second point, calculate the center point of the inscribed circle; Based on traversing all the first points in the first arc point set and fitting the middle arc using multiple center points; Using the aforementioned mid-arc line, at least one geometric feature of the centrifugal fan blade is determined; The step of determining the position of the unknown second point on the second arc according to the nonlinear analytical model includes: The location of the unknown second point is determined by numerically approximating the roots of the nonlinear analytical model. The step of determining the location of the unknown second point by numerically approximating the roots of the nonlinear analytical model includes: The position of the first point is used as an initial approximation of the position of the unknown second point; Based on the initial approximation and the nonlinear analytical model, the position of the unknown second point is corrected until the corrected position satisfies the preset convergence condition. The step of establishing a nonlinear analytical model for the first point in the first arc point set, based on the parameterized representation of the inscribed circle, includes: Based on the first point and the unknown second point, establish a system of equations to parameterize the coordinates of the center point, and obtain the nonlinear analytical model by performing algebraic elimination on the system of equations. The geometric tangency constraint includes the fact that the center point is the intersection of the normal at the first point and the normal at the unknown second point.

2. The method for determining the geometric features of centrifugal fan blades according to claim 1, characterized in that, The determination of the first arc point set and the second arc point set for characterizing the surface shape of the centrifugal fan blades includes: The centrifugal fan blades are scanned using a 3D scanning device to obtain a 3D coordinate dataset. The three-dimensional coordinate dataset is projected onto a preset two-dimensional plane to generate the first arc point set and the second arc point set.

3. The method for determining the geometric features of centrifugal fan blades according to claim 2, characterized in that, The step of projecting the three-dimensional coordinate dataset onto a preset two-dimensional plane to generate the first arc point set and the second arc point set includes: The three-dimensional coordinate dataset is projected onto a preset two-dimensional plane to obtain a first initial point set and a second initial point set; Using the least squares method, the first initial point set and the second initial point set are fitted to their respective first polynomial functions and second polynomial functions; Based on the first polynomial function and the second polynomial function, resampling is performed according to a preset precision to generate the first arc point set and the second arc point set.

4. The method for determining the geometric features of centrifugal fan blades according to claim 1, characterized in that, The geometric features include at least one of the following: blade inner diameter, blade outer diameter, blade chord length, blade maximum thickness, blade thickness distribution, blade wrap angle, blade mounting angle, blade inlet angle, and blade outlet angle.

5. A device for determining the geometric features of centrifugal fan blades, characterized in that, include: The point set determination module is used to determine a first arc point set and a second arc point set for characterizing the surface shape of centrifugal fan blades; The model building module is used to build a nonlinear analytical model for the first point in the first arc point set based on the parameterized representation of the inscribed circle, wherein the nonlinear analytical model is based on an unknown second point on the first and second arcs to limit a geometric tangency constraint. The position determination module is used to determine the position of the unknown second point on the second arc based on the nonlinear analytical model. The data calculation module is used to calculate the center point of the inscribed circle based on the first point and the determined second point; The arc generation module generates a middle arc based on a set of center point coordinates calculated by traversing all the first points in the first arc point set; The feature determination module determines at least one geometric feature of the centrifugal fan blade based on the mid-arc line; The step of determining the position of the unknown second point on the second arc according to the nonlinear analytical model includes: The location of the unknown second point is determined by numerically approximating the roots of the nonlinear analytical model. The step of determining the location of the unknown second point by numerically approximating the roots of the nonlinear analytical model includes: The position of the first point is used as an initial approximation of the position of the unknown second point; Based on the initial approximation and the nonlinear analytical model, the position of the unknown second point is corrected until the corrected position satisfies the preset convergence condition. The step of establishing a nonlinear analytical model for the first point in the first arc point set, based on the parameterized representation of the inscribed circle, includes: Based on the first point and the unknown second point, establish a system of equations to parameterize the coordinates of the center point, and obtain the nonlinear analytical model by performing algebraic elimination on the system of equations. The geometric tangency constraint includes the fact that the center point is the intersection of the normal at the first point and the normal at the unknown second point.

6. An electronic device, characterized in that, The electronic device includes a processor and a memory; the processor is used to execute instructions stored in the memory to implement the centrifugal fan blade geometric feature determination method as described in any one of claims 1 to 4.

7. A computer storage medium, characterized in that, The computer storage medium stores at least one instruction, which is executed by a processor to implement the centrifugal fan blade geometric feature determination method as described in any one of claims 1 to 4.

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