A method, device, equipment and medium for reconstructing an impeller model

Abstract

The present disclosure provides a reconstruction method, device, equipment and medium for an impeller model, which belongs to the field of impeller simulation design. The reconstruction method includes: in the original impeller model, obtaining the characteristic surfaces of the blade part and the inner boundary part of the blade; interpolating each characteristic surface of the blade part based on the streamline direction of the surface parameter to obtain the original data point of each characteristic surface; in the characteristic surface of the inner boundary part of the blade, interpolating based on the surface parameter of the inner boundary part of the blade to obtain the generatrix of the inner boundary part of the blade; interpolating based on the surface parameter of the outer boundary part of the blade to obtain the generatrix of the outer boundary part of the blade; in the original data points of the characteristic surface of the blade part, smoothing the characteristic surface of the blade part to obtain the data points of the smoothed characteristic surface of the blade part; constructing a reconstructed impeller model according to the smoothed data points of the characteristic surface, the generatrix of the inner boundary part of the blade and the generatrix of the outer boundary part of the blade.

Description

Technical Field

[0001] The present disclosure relates to the field of impeller simulation design, and in particular to an impeller model reconstruction method, device, equipment and medium. Background Art

[0002] As the core component of the compressor, the geometric shape of the impeller plays a very critical role in the overall performance of the compressor. Therefore, the design of the impeller is the core of the compressor aerodynamic design.

[0003] Since the impeller design process involves multiple disciplines such as fluid mechanics and aerodynamics, if the impeller model is built from scratch and optimized by simulation, it will consume high development costs and cycles. With the development of engine and impeller machinery technology, the design schemes for impellers are also constantly accumulating. Impeller optimization design based on the existing relatively mature impeller model can significantly reduce development costs and shorten development cycles.

[0004] Therefore, there is an urgent need for a solution that can accurately and efficiently reconstruct the existing impeller model. Summary of the invention

[0005] The present disclosure provides a method, device, equipment and medium for reconstructing an impeller model, which can improve the reconstruction efficiency and accuracy of the impeller model.

[0006] The technical solution of the present disclosure is achieved as follows:

[0007] In a first aspect, the present disclosure provides a method for reconstructing an impeller model, the method comprising:

[0008] In the original impeller model, the characteristic surfaces of the blade part and the inner boundary part of the blade are obtained;

[0009] Interpolating each characteristic surface of the blade portion based on the streamline direction of the surface parameter to obtain original data points of each characteristic surface;

[0010] In the characteristic surface of the inner boundary of the blade, interpolation is performed based on the surface parameters of the inner boundary of the blade to obtain a generatrix of the inner boundary of the blade;

[0011] Interpolation is performed based on the surface parameters of the outer boundary of the blade to obtain the generatrix of the outer boundary of the blade;

[0012] Among the original data points of the characteristic curved surface of the blade part, the characteristic curved surface of the blade part is smoothed based on the connection points between the characteristic curved surfaces to obtain the data points of the characteristic curved surface of the blade part after being smoothed;

[0013] A reconstructed impeller model corresponding to the original impeller model is constructed according to the data points of the smoothed characteristic surface of the blade, the generatrix of the inner boundary of the blade, and the generatrix of the outer boundary of the blade.

[0014] In a second aspect, the present disclosure provides a reconstruction device for an impeller model, the reconstruction device comprising: an acquisition part, a blade processing part, a blade inner boundary processing part, a blade outer boundary processing part, a smoothing processing part and a construction part; wherein,

[0015] The acquisition part is configured to acquire characteristic surfaces of the blade portion, the blade inner boundary portion, and the blade outer boundary portion in the original impeller model;

[0016] The blade processing part is configured to interpolate each characteristic surface of the blade part based on the streamline direction of the surface parameter to obtain the original data point of each characteristic surface;

[0017] The blade inner boundary processing part is configured to perform interpolation based on the surface parameters of the blade inner boundary to obtain a generatrix of the blade inner boundary;

[0018] The blade outer boundary processing part is configured to interpolate based on the surface parameters of the blade outer boundary to obtain the generatrix of the blade outer boundary;

[0019] The smoothing processing part is configured to perform smoothing processing on the characteristic curved surface of the blade part based on the connection points between the characteristic curved surfaces among the original data points of the characteristic curved surface of the blade part, so as to obtain the data points of the characteristic curved surface of the blade part after being smoothed;

[0020] The construction part is configured to construct a reconstructed impeller model corresponding to the original impeller model based on the data points of the smoothed characteristic surface of the blade part, the generatrix of the inner boundary part of the blade and the generatrix of the outer boundary part of the blade.

[0021] In a third aspect, the present disclosure provides a computing device, comprising: a processor and a memory; the processor is used to execute instructions stored in the memory to implement the impeller model reconstruction method as described in the first aspect.

[0022] In a fourth aspect, the present disclosure provides a computer storage medium storing at least one instruction, wherein the at least one instruction is used to be executed by a processor to implement the impeller model reconstruction method as described in the first aspect.

[0023] The present invention provides a reconstruction method, device, equipment and medium for an impeller model; for the original impeller model, the characteristic surface and the hub surface of the blade are interpolated using the UV parameters of the surface to form data points of each characteristic surface and the hub surface, so that in the reconstruction process, the coordinate transformation process is avoided, which not only avoids the loss of precision caused by the data length in the coordinate transformation process, but also reduces the amount of calculation consumed by the coordinate transformation in the reconstruction process, thereby improving the accuracy and processing efficiency of the reconstruction. In addition, by smoothing the connection of the cross-section line of the characteristic surface, the transition area of ​​the surface satisfies the geometric continuity, slope continuity and curvature continuity, thereby improving the accuracy of the reconstruction process. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A schematic flow chart of a method for reconstructing an impeller model provided in the present invention.

[0025] Figure 2 A three-dimensional schematic diagram of the original impeller model provided for this disclosure.

[0026] Figure 3 A schematic cross-sectional view of the pressure surface of a main blade provided in the present disclosure.

[0027] Figure 4 A schematic cross-sectional view of the leading edge of a main blade provided in the present disclosure.

[0028] Figure 5 A schematic cross-sectional view of the suction surface of a main blade provided by the present disclosure.

[0029] Figure 6 A schematic cross-sectional view of the trailing edge of a main blade provided by the present disclosure.

[0030] Figure 7 A schematic cross-sectional view of the pressure surface of a splitter blade provided in the present disclosure.

[0031] Figure 8 A schematic cross-sectional view of the leading edge of a splitter blade provided in the present disclosure.

[0032] Fig. 9 A schematic cross-sectional view of the suction surface of a splitter blade provided in the present disclosure.

[0033] Fig.10 A schematic cross-sectional view of the trailing edge of a splitter blade provided by the present disclosure.

[0034] Fig.11 A schematic diagram of obtaining the generatrix of the hub surface provided in the present disclosure.

[0035] Fig.12 A schematic diagram of the busbars for obtaining the wheel cover surface provided in the present invention.

[0036] Fig.13 (A) is a schematic diagram of the original impeller model provided in the present disclosure.

[0037] Fig.13 (B) is a schematic diagram of the reconstructed impeller model provided by the present disclosure.

[0038] Fig.14 A schematic diagram of the composition of a reconstruction device for an impeller model provided in the present invention.

[0039] Fig.15 A schematic diagram of the structure of a computing device provided by the present disclosure. DETAILED DESCRIPTION

[0040] The technical solutions in the present disclosure will be described clearly and completely below in conjunction with the accompanying drawings in the present disclosure.

[0041] In the mechanical processing scenario of an impeller, it is usually necessary to transfer the design data (model) of the impeller from a computer-aided design (CAD) system to a computer-aided manufacturing (CAM) system or another CAD system to machine the impeller or optimize the design model of the impeller. In some examples, taking the processing according to the impeller model as an example, the original impeller model usually only includes simple geometric shapes, dimensions and other design data, and does not include all the information required for processing. For example, when the main blades need to be rough-machined and fine-machined by milling, the tool processing path cannot be directly programmed according to the blade surface data of the original impeller model, and the geometric data of the blade surface needs to be reconstructed according to the processing requirements before the processing path can be programmed. In some examples, taking the optimization or redesign of the impeller model as an example, the design data included in the original impeller model cannot provide the necessary data support for optimization, and the original impeller model also needs to be reconstructed or rebuilt before optimization or redesign can be performed.

[0042] In order to accurately and efficiently reconstruct the existing impeller model, see Figure 1 , which shows a reconstruction method of an impeller model provided by the present disclosure, and the reconstruction method includes steps S101 to S106.

[0043] Step S101: in the original impeller model, obtain the characteristic surfaces of the blade part and the inner boundary part of the blade.

[0044] In the present disclosure, the original impeller model refers to a model embodied by the design data such as the geometric shape and size of the impeller that needs to be reconstructed. As mentioned above, the design data of the original impeller model cannot be used to directly program the tool processing path, nor can it provide data support for design optimization, so reconstruction is required. In some examples, the original impeller model can be stored in a general data exchange file, such as iges, step file. Taking iges as an example, the present disclosure adopts the openCASCADE (OCC) software platform as an exemplary implementation environment for the technical solution of the present disclosure.

[0045] In some examples, the original impeller model may be an original model of an integral impeller with splitter blades. The impeller adopts a design scheme that combines large and small blades. Specifically, a small blade is added to the rear of the large blade channel, which can suppress or even eliminate the separation of the airflow behind the large blade, and avoid the common airflow blockage phenomenon of the blade in the front of the channel. This impeller design scheme has a much better boosting effect than a single-blade impeller while maintaining high efficiency and high stability of the working airflow.

[0046] Combination Figure 2 The three-dimensional schematic diagram of the original impeller model shown in the figure, in the present disclosure, the impeller includes a blade portion, a blade inner boundary portion and a blade outer boundary portion, wherein the blade with a larger size in the blade portion is called a main blade 21, the blade with a smaller size is called a splitter blade 22, the blade inner boundary portion is a hub 23, and the blade outer boundary portion is a wheel cover ( Figure 2 not shown).

[0047] In the present disclosure, the characteristic surface refers to the object with the smallest granularity used for reconstruction in the impeller model, that is, the technical solution of the present disclosure is to perform data interpolation based on the characteristic surface, and then form a reconstructed model of the impeller through subsequent processing means (such as smoothing processing, array processing, etc.) on the characteristic surface. In some examples, the blade part, that is, the characteristic surface of each main blade and each splitter blade can be divided into four characteristic surfaces: pressure surface, suction surface, leading edge and trailing edge.

[0048] It should be noted that in the present disclosure, the data of each characteristic surface is stored in a corresponding independent data container, for example, each characteristic surface has an independent storage space in the memory, an independent storage pointer or an independent data structure in the program. Such a setting can reduce the data coupling between the characteristic surfaces. For example, in the process of optimizing the design or processing programming of the final reconstructed model, if a specific characteristic surface needs to be independently fine-machined, the data can be directly obtained from the data container corresponding to the characteristic surface without the need for additional analysis processing to decouple the data.

[0049] Step S102: interpolating each characteristic surface of the blade portion based on the streamline direction of the surface parameter to obtain original data points of each characteristic surface.

[0050] It should be noted that the complete surface can be represented by a surface parameter equation. In the present disclosure, the surface parameters include U-direction parameters (also referred to as U parameters) and V-direction parameters (also referred to as V parameters). The two families of parameters, U-direction and V-direction, constitute the entire surface. When the U parameter takes a fixed value, the surface parameter equation can represent a spatial curve on the surface along the V parameter direction, also called a V-direction curve; similarly, when the V parameter takes a fixed value, the surface parameter equation can represent a spatial curve on the surface along the U parameter direction, also called a U-direction line.

[0051] In the present disclosure, for each characteristic surface (pressure surface, suction surface, leading edge, trailing edge) of a blade portion (main blade or splitter blade), multiple fixed values ​​are selected according to the streamline direction of any surface parameter (such as U parameter or V parameter), and the characteristic surface is divided into corresponding sections based on each of the multiple fixed values, and each section line corresponds to a space curve. On each section line (or space curve), data interpolation is performed along another surface parameter (such as V parameter or U parameter) to obtain data points of each section line (space curve), and then the data points of the space curves of all fixed values ​​can be formed into the original data points of the complete characteristic surface.

[0052] It should be noted that since the original data points obtained by interpolation are obtained based on the UV parameters that conform to the characteristic surface itself, there is no need to reconstruct the local coordinate system for each surface. Therefore, in the subsequent reconstruction process, there is no need to perform coordinate transformation for different local coordinate systems. This not only avoids the loss of precision caused by data length during the coordinate transformation process, but also reduces the amount of calculation consumed by coordinate transformation during the reconstruction process, thereby improving the reconstruction accuracy and processing efficiency.

[0053] In some examples, the original data points of each feature surface are stored in a corresponding independent storage space to facilitate subsequent independent machining path programming or design optimization of the specific feature surface without the need for data decoupling.

[0054] Step S103: interpolating the characteristic surface of the inner boundary of the blade based on the surface parameters of the inner boundary of the blade to obtain a generatrix of the inner boundary of the blade.

[0055] In the present disclosure, the inner boundary of the blade, i.e., the characteristic curved surface of the hub, is a regular revolution surface, the UV parameters of which are perpendicular to each other, and the horizontal direction is set as the U direction, the vertical direction is set as the V direction, and data is interpolated along the V direction at the middle point of the U direction, so that the generatrix of the characteristic curved surface of the hub, i.e., the generatrix of the inner boundary of the blade, can be obtained. In some examples, based on the generatrix, the characteristic curved surface of the hub is obtained by rotating 360 degrees with the central axis of the hub.

[0056] Step S104: interpolating based on the surface parameters of the outer boundary of the blade to obtain a generatrix of the outer boundary of the blade.

[0057] In the present disclosure, the outer boundary of the blade, i.e., the wheel cover, refers to the outer covering surface or boundary surface in the impeller structure, which is usually connected to the outer edge of the blade, i.e., it is tangent to the side of each blade (main blade and splitter blade) and is used to close the outer part of the impeller. The wheel cover corresponds to the wheel hub and together form a complete closed structure of the impeller.

[0058] In some examples, the largest virtual surface can be expanded in the UV parameter direction of the surface based on the side of the main blade. In the virtual surface, the generatrix of the wheel cover surface can be interpolated in a similar way to the hub. The real area of ​​the wheel cover surface can be obtained by rotating the generatrix 360 degrees around the central axis of the impeller.

[0059] For the above-mentioned steps S102, S103 and S104, since the characteristic surfaces they are respectively targeted at are in different components of the impeller, their sequence is not limited in the specific implementation process, that is, these three steps can be executed in parallel by way of example, and the present disclosure does not make specific limitations on this.

[0060] Step S105: among the original data points of the characteristic curved surface of the blade portion, smoothing is performed on the characteristic curved surface of the blade portion based on the connection points between the characteristic curved surfaces to obtain data points of the smoothed characteristic curved surface of the blade portion.

[0061] After obtaining the original data points of the characteristic surfaces of the main blade or splitter blade, namely the pressure surface, suction surface, leading edge and trailing edge, through the aforementioned step S102, smoothing processing is required to avoid the phenomenon of misalignment, disconnection, etc. in the transition area of ​​the characteristic surface, which reduces the quality of surface reconstruction.

[0062] In some examples, the order of the cross-sectional lines of the characteristic surfaces of the blade can be set as "leading edge-pressure surface-trailing edge-suction surface". According to this order, the points between the cross-sectional lines of each characteristic surface are: the connecting point C1 of the cross-sectional lines of the leading edge and the pressure surface; the connecting point C2 of the cross-sectional lines of the pressure surface and the trailing edge; the connecting point C3 of the cross-sectional lines of the trailing edge and the suction surface; the connecting point C4 of the cross-sectional lines of the suction surface and the leading edge. At these connecting points, a cubic spline function can be constructed, and interpolation is performed based on the constraints set for the function to obtain the data points after the characteristic surfaces of the blade portion are smoothed. In some examples, the above constraints can be: the function value of the cubic spline function at the connecting point is continuous, and the first-order derivative and the second-order derivative of the cubic spline function at the connecting point are both continuous.

[0063] It can be understood that the data points of each characteristic surface after being smoothed are also stored in the corresponding data container, and the data points of these characteristic surfaces after being smoothed can form the blade reconstruction data with smooth surface transition.

[0064] Step S106: constructing a reconstructed impeller model corresponding to the original impeller model according to the data points of the smoothed characteristic surface of the blade, the generatrix of the inner boundary of the blade, and the generatrix of the outer boundary of the blade.

[0065] In some examples, since the blades (main blades and splitter blades) in the impeller model are usually evenly distributed around the hub, in the process of constructing the reconstructed impeller model, the reconstructed data of a group of blades (one main blade and one splitter blade) can be arrayed around the central axis of the hub to form a reconstructed impeller model. Specifically, for each main blade and splitter blade, the corresponding reconstructed data of each main blade and splitter blade can be formed based on the data points after all its characteristic surfaces are smoothed. By rotating the generatrix of the inner boundary of the blade and the generatrix of the outer boundary of the blade 360 ​​degrees according to the central axis of the impeller, the reconstructed data of the hub and the wheel cover can be obtained respectively. Based on these reconstructed data, the reconstructed data of a group of blades (one main blade and one splitter blade) are arranged on the surface of the hub in an array, so as to finally obtain a reconstructed impeller model corresponding to the original impeller model.

[0066] Through the above technical solution, for the original impeller model, the characteristic surface and the hub surface of the blade are interpolated using the UV parameters of the surface to form data points of each characteristic surface and the hub surface, so that the coordinate transformation process is avoided during the reconstruction process. This not only avoids the loss of accuracy caused by the data length during the coordinate transformation process, but also reduces the amount of calculation consumed by the coordinate transformation during the reconstruction process, thereby improving the accuracy and processing efficiency of the reconstruction. In addition, by smoothing the connection of the cross-section lines of the characteristic surface, the transition area of ​​the surface meets the geometric continuity, slope continuity, and curvature continuity, thereby improving the accuracy of the reconstruction process.

[0067] With respect to the above technical solution, in some possible implementations, step S101 may be implemented as follows: after the original impeller model is imported into the OCC software platform, the OCC software platform may intuitively display the original impeller model according to the design data such as the geometric shape and size in the original impeller model, such as Figure 2 After receiving the selection instruction of the user or designer for the characteristic surface in the displayed original impeller model, the design data such as the geometric shape and size of the characteristic surface can be obtained. The design data of the selected characteristic surface in the original impeller model can be used as the basic data for model reconstruction of the technical solution disclosed in the present invention.

[0068] In view of the above technical solution, in some possible implementations, the step S102 interpolates each characteristic surface of the blade part based on the streamline direction of the surface parameter to obtain the original data points of each characteristic surface, including:

[0069] For each characteristic curved surface of the blade portion, divide at least one cross section along the first curved surface parameter direction to obtain a cross-sectional line corresponding to each cross section;

[0070] Interpolate each section line along the direction of the second surface parameter to obtain data points of each section line;

[0071] The data points of all cross-section lines of each characteristic surface constitute the original data points of each characteristic surface.

[0072] For the above implementation, in some examples, each main blade and splitter blade can be divided into four characteristic surfaces: pressure surface, suction surface, leading edge and trailing edge. For each characteristic surface selected by the user or designer according to the above implementation, Figure 3 Taking a pressure surface of a main blade as an example, the cross section is divided according to the direction of the first surface parameter in the surface parameters of the pressure surface, such as along the direction of the U parameter (for example Figure 3 The characteristic surface is evenly divided into multiple sections, for example, 9 sections, in the direction from the intersection point U0 of the pressure surface and the wheel cover to the intersection point U1 of the pressure surface and the wheel hub. For each section, interpolation is performed based on the UV parameter equation according to the direction of the second surface parameter, that is, along the direction of the V parameter (for example Figure 3 By interpolating the data points of each section line (in the direction from V0 to V1 on the pressure surface), for example, 50 interpolation points, the data points of each section line can be obtained. Finally, the data points of all section lines are summarized according to the direction of the section divided by the U parameter, and the original data points of the pressure surface can be obtained.

[0073] It can be understood that for other characteristic surfaces of the main blades and each characteristic surface of the splitter blades, interpolation can be performed according to the above example to obtain the original data points of each characteristic surface of the main blades and the splitter blades. It should be noted that since the impeller model is usually a regular rotation model, the characteristic surfaces of each main blade are the same, and the characteristic surfaces of each splitter blade are also the same. Therefore, in the specific implementation process, it is not necessary to obtain the original data points for the characteristic surfaces of all main blades and splitter blades by interpolation, but only the original data points of each characteristic surface of a single main blade and a single splitter blade need to be obtained by interpolation.

[0074] In some examples, for the main blade or the splitter blade, the connection points of each characteristic surface will be smoothed during the implementation of the subsequent step S105. Based on the sequence of the characteristic surfaces that are smoothed, the cross-sectional lines of adjacent characteristic surfaces should have connection points. For example, taking the sequence of characteristic surfaces as "leading edge-pressure surface-trailing edge-suction surface", according to this sequence, the direction of the first curve parameter of the leading edge characteristic surface is consistent with the direction of the first curve parameter of the adjacent pressure surface, the number of cross sections obtained by division is consistent, and each cross-sectional line of the leading edge characteristic surface has a corresponding cross-sectional line in the pressure surface. In addition, according to this sequence, the pressure surface and the trailing edge, and the trailing edge and the suction surface also satisfy the consistency in the direction of the first curve parameter, the consistency in the number of cross sections obtained by division, and each cross-sectional line of each characteristic surface has a corresponding cross-sectional line in the adjacent characteristic surface.

[0075] by Figure 3 As an example, refer to the main blade shown in Figure 4 , Figure 5 as well as Figure 6 , which respectively shows the cross-sectional division of the leading edge, suction surface and trailing edge. Figure 3 , Figure 4 , Figure 5 and Figure 6 It can be seen that in the present disclosure, the cross-sectional lines of the pressure surface and the leading edge are connected, the cross-sectional lines of the leading edge and the suction surface are connected, and the cross-sectional lines of the suction surface and the trailing edge are connected. Figure 7 , Figure 8 , Fig. 9 , Fig.10 The cross-sectional division of the pressure surface, leading edge, suction surface and trailing edge of the splitter blade is shown. It can also be seen that the cross-sectional lines of the pressure surface and the leading edge are connected, the cross-sectional lines of the leading edge and the suction surface are connected, and the cross-sectional lines of the suction surface and the trailing edge are connected.

[0076] With respect to the above technical solution, in some possible implementations, interpolation is performed on the characteristic surface of the inner boundary of the blade based on the surface parameters of the inner boundary of the blade to obtain the generatrix of the inner boundary of the blade, including:

[0077] In the characteristic surface of the inner boundary of the blade, the middle value of the surface parameter in the horizontal direction among the surface parameters of the inner boundary of the blade is taken as the starting point, and data interpolation is performed along the vertical direction to obtain the generatrix of the inner boundary of the blade.

[0078] For the above implementation, specifically, the inner boundary of the blade is the hub, and the hub surface is a regular revolution surface, which can be formed by a generatrix rotating around the central axis of the hub. The central axis of the hub is usually consistent with the central axis of the impeller. For the hub surface, the UV parameters of the curved surface are perpendicular to each other. In this disclosure, the horizontal direction is the U parameter direction, and the vertical direction is the V parameter direction, such as Fig.11 As shown in the figure, the upper left corner of the characteristic surface of the hub is set as U0, and the upper right corner is set as U1. Then the middle value of the U parameter direction of the characteristic surface of the hub is (U0+U1) / 2. Starting from this middle value, follow the V parameter direction (i.e. Fig.11 The data is interpolated according to the UV parameter equation of the surface (in the direction from V0 to V1 in the figure), so as to obtain the generatrix of the characteristic surface of the wheel hub.

[0079] With respect to the above technical solution, in some possible implementations, interpolating the surface parameters of the outer boundary of the blade to obtain the generatrix of the outer boundary of the blade includes:

[0080] Based on the side surface of the main blade of the blade part, the largest virtual surface is expanded in the direction of the surface UV parameter of the side surface;

[0081] Taking the middle value of the surface parameter in the horizontal direction of the virtual surface as the starting point, data interpolation is performed along the vertical direction to obtain the generatrix of the outer boundary of the blade.

[0082] For the above implementation, specifically, the outer boundary of the blade is the wheel cover, which is tangent to the side of each blade (main blade and splitter blade). The maximum virtual surface expanded from the side of the selected main blade in the direction of the surface UV parameter can be obtained based on Open CASCADE, and then the wheel cover generatrix data can be interpolated using a method similar to the hub surface.

[0083] Specifically, if Fig.12 For the virtual surface shown in , the horizontal direction is the U parameter direction, the vertical direction is the V parameter direction, the upper left corner point of the characteristic surface of the wheel cover is set as U0, and the upper right corner point is set as U1. Then the middle value of the U parameter direction of the characteristic surface of the wheel cover is (U0+U1) / 2. Taking this middle value as the starting point, data interpolation is performed along the V parameter direction according to the UV parameter equation of the surface, so that the actual generatrix of the characteristic surface of the wheel cover can be obtained.

[0084] In some examples, after the actual generatrix of the wheel cover is obtained, it can be discretized and interpolated and smoothed by a cubic spline function to obtain the generatrix of the outer boundary of the blade after smoothing.

[0085] With respect to the above technical solution, in some possible implementations, among the original data points of the characteristic surface of the blade portion, the characteristic surface of the blade portion is smoothed based on the connection points between the characteristic surfaces to obtain the data points of the characteristic surface of the blade portion after being smoothed, including:

[0086] From the original data points of the characteristic curved surface of the blade portion, a first connection point between the cross-sectional line of the leading edge of the blade portion and the cross-sectional line of the pressure surface, a second connection point between the cross-sectional line of the pressure surface of the blade portion and the cross-sectional line of the trailing edge, a third connection point between the cross-sectional line of the trailing edge of the blade portion and the cross-sectional line of the suction surface, and a fourth connection point between the cross-sectional line of the suction surface of the blade portion and the cross-sectional line of the leading edge are sequentially determined;

[0087] For each of the first connection point, the second connection point, the third connection point, and the fourth connection point, fitting a corresponding cubic spline function;

[0088] Interpolation is performed based on the cubic spline function corresponding to each connection point and the set constraint conditions to obtain data points after the characteristic surface of the blade portion is smoothed.

[0089] For the above implementation, taking the order of "leading edge-pressure surface-trailing edge-suction surface" as an example, the connection points between the cross-sectional lines of the characteristic surfaces of the main blade or the splitter blade are: the cross-sectional line connection point C1 between the leading edge and the pressure surface; the cross-sectional line connection point C2 between the pressure surface and the trailing edge; the cross-sectional line connection point C3 between the trailing edge and the suction surface; the cross-sectional line connection point C4 between the suction surface and the leading edge. At these connection points, a cubic spline function can be constructed, and interpolation is performed based on the constraints set for the function to obtain the data points after the characteristic surface of the blade portion is smoothed. In some examples, the above constraints may be: the function value of the cubic spline function at the connection point is continuous, and the first-order derivative and the second-order derivative of the cubic spline function at the connection point are both continuous.

[0090] For example, taking C1 as an example, the cubic spline function for connecting the characteristic surfaces is as follows:

[0091]

[0092] Where i=1, 2, ..., n, i represents the i-th segment of the cubic spline function, x represents the x component of the coordinate point on the cubic spline function; S i (x) represents the i-th segment of the cubic spline function.

[0093] Next, the cubic spline function is solved using the original data points of each characteristic surface of the impeller obtained in the above steps to obtain the coefficients of each segment of the spline function ( , , , ) value.

[0094] Finally, for each spline segment, the parameters In [x i ,x i+1 ] is interpolated based on the above constraints to obtain the smoothed data points.

[0095] This constraint can be expressed as:

[0096] The continuity of the function value at the connection point can be obtained by S i (C1) = S i+1 (C1) means;

[0097] The continuity of the first-order derivative at the connection point can be obtained by S i ´(C1)=S i+1 ´(C1) indicates;

[0098] The continuity of the second-order derivative at the connection point can be obtained by S i ´´(C1)=S i+1 ´´ (C1) indicates.

[0099] It can be understood that after all the connection points are smoothed according to the above example, data points of the smoothed characteristic surface of the blade portion are obtained.

[0100] With respect to the above technical solution, in some possible implementations, the reconstructed impeller model corresponding to the original impeller model is constructed according to the data points of the smoothed characteristic surface of the blade portion, the generatrix of the inner boundary portion of the blade, and the generatrix of the outer boundary portion of the blade, including:

[0101] Based on the data points of the smoothed characteristic surface of the blade part, a blade array is constructed according to the layout quantity and spacing angle;

[0102] According to the generatrix of the inner boundary of the blade and the generatrix of the outer boundary of the blade, geometric model data of the inner boundary of the blade and the outer boundary of the blade are respectively constructed;

[0103] The reconstructed impeller model is constructed using the geometric model data of the blade array and the inner and outer boundaries of the blades.

[0104] It should be noted that the main blades and splitter blades are usually evenly distributed around the hub. Based on this, the spacing between adjacent main blades or splitter blades can be determined according to the number of main blades and splitter blades. In the present disclosure, the spacing can be characterized by a spacing angle.

[0105] In some examples, a layout number Num indicated by a user may be received, and an interval angle Angle=360° / Num between adjacent blades may be calculated according to the layout number Num.

[0106] In some examples, the original impeller model can also be used to obtain the number of impellers and the spacing angle. Specifically, first obtain the hub center axis L axis , and obtain any point P on the axis aixs and unit vector N. Next, obtain the center point P1 of the first blade surface and the center point P2 of the second blade surface. Then, obtain the coordinates of points P1 and P2 on the axis L respectively. axis The projection point Proj on P1 、Proj P2 Then, calculate the points P1 and P2 relative to their positions on the axis L. axis The projection vector on (may be marked as Vec1) and (Vec2). Finally, the angle θ between the vectors Vec1 and Vec2 is calculated as the interval angle Angle, and the number of blades Num=360° / Angle is calculated based on the interval angle Angle.

[0107] After obtaining the number and spacing angle of the main blades and splitter blades, the blades can be arranged in an array based on a rotation array to obtain a blade array. Specifically, first obtain a set of blade data formed by smoothed data points and a rotation axis (e.g., L axis ). Then specify the rotation angle interval (such as Angle) and the number of blades to be laid out (such as Num). Next, use a loop algorithm to rotate the object around the rotation axis by the specified angle Angle each time, and copy a copy of the blade data to the new position. Repeat this process until a blade array with the specified number of layouts is generated.

[0108] In addition, for the inner boundary portion and the outer boundary portion of the blade, the corresponding generatrixes can also be arranged according to the above rotation axis (for example, L axis ) is rotated to obtain the geometric model data of the inner boundary and the outer boundary of the blade.

[0109] After obtaining the data of the blade array and the geometric model data of the inner boundary of the blade and the outer boundary of the blade, these data can be imported into the OCC platform, so as to construct a reconstructed impeller model using the geometric basic library of the OCC platform, such as Fig.13 In the OCC platform, the original impeller model is presented as follows Fig.13 As shown in (A) in .

[0110] For the impeller model reconstructed by the aforementioned technical solution, the present disclosure also exemplarily converts the impeller model based on the OCC platform into Fig.13 The reconstructed impeller model shown in (B) is similar to that shown in Fig.13 The geometric surface of the original impeller model shown in (A) is compared, and the maximum positive and negative deviation range is [-0.00049mm, +0.000406mm]. Based on this deviation range, it can be seen that the technical solution provided by the present disclosure has a high reconstruction accuracy.

[0111] Based on the same inventive concept as the above technical solution, see Fig.14 , which shows a reconstruction device 140 of an impeller model provided by the present disclosure, the reconstruction device 140 of the impeller model comprises: an acquisition part 1401, a blade processing part 1402, a blade inner boundary processing part 1403, a blade outer boundary processing part 1404, a smoothing processing part 1405 and a construction part 1406; wherein,

[0112] The acquisition part 1401 is configured to acquire characteristic surfaces of the blade part, the inner boundary part of the blade and the outer boundary part of the blade in the original impeller model;

[0113] The blade processing part 1402 is configured to interpolate each characteristic surface of the blade part based on the streamline direction of the surface parameter to obtain the original data point of each characteristic surface;

[0114] The blade inner boundary processing part 1403 is configured to perform interpolation based on the surface parameters of the blade inner boundary to obtain the generatrix of the blade inner boundary;

[0115] The blade outer boundary processing part 1404 is configured to interpolate based on the surface parameters of the blade outer boundary to obtain the generatrix of the blade outer boundary;

[0116] The smoothing processing part 1405 is configured to perform smoothing processing on the characteristic curved surface of the blade part based on the connection points between the characteristic curved surfaces among the original data points of the characteristic curved surface of the blade part, so as to obtain the data points of the characteristic curved surface of the blade part after being smoothed;

[0117] The construction part 1406 is configured to construct a reconstructed impeller model corresponding to the original impeller model based on the data points of the smoothed characteristic surface of the blade portion, the generatrix of the inner boundary portion of the blade, and the generatrix of the outer boundary portion of the blade.

[0118] In some examples, the blade processing portion 1402 is configured to:

[0119] For each characteristic curved surface of the blade portion, divide at least one cross section along the first curved surface parameter direction to obtain a cross-sectional line corresponding to each cross section;

[0120] Interpolate each section line along the direction of the second surface parameter to obtain data points of each section line;

[0121] The data points of all cross-section lines of each characteristic surface constitute the original data points of each characteristic surface.

[0122] In some examples, the blade portion includes a main blade and a splitter blade; and the characteristic curved surfaces of the blade portion include: a pressure surface, a suction surface, a leading edge, and a trailing edge.

[0123] In some examples, the blade inner boundary processing portion 1403 is configured to:

[0124] In the characteristic surface of the inner boundary of the blade, the middle value of the surface parameter in the horizontal direction among the surface parameters of the inner boundary of the blade is taken as the starting point, and data interpolation is performed along the vertical direction to obtain the generatrix of the inner boundary of the blade.

[0125] In some examples, the blade outer boundary processing portion 1404 is configured to:

[0126] Based on the side surface of the main blade of the blade part, the largest virtual surface is expanded in the direction of the surface UV parameter of the side surface;

[0127] Taking the middle value of the surface parameter in the horizontal direction of the virtual surface as the starting point, data interpolation is performed along the vertical direction to obtain the generatrix of the outer boundary of the blade.

[0128] In some examples, the smoothing portion 1405 is configured to:

[0129] From the original data points of the characteristic curved surface of the blade portion, a first connection point between the cross-sectional line of the leading edge of the blade portion and the cross-sectional line of the pressure surface, a second connection point between the cross-sectional line of the pressure surface of the blade portion and the cross-sectional line of the trailing edge, a third connection point between the cross-sectional line of the trailing edge of the blade portion and the cross-sectional line of the suction surface, and a fourth connection point between the cross-sectional line of the suction surface of the blade portion and the cross-sectional line of the leading edge are sequentially determined;

[0130] For each of the first connection point, the second connection point, the third connection point, and the fourth connection point, fitting a corresponding cubic spline function;

[0131] Interpolation is performed based on the cubic spline function corresponding to each connection point and the set constraint conditions to obtain data points after the characteristic surface of the blade portion is smoothed.

[0132] In some examples, the building portion 1406 is configured to:

[0133] Based on the data points of the smoothed characteristic surface of the blade part, a blade array is constructed according to the layout quantity and spacing angle;

[0134] According to the generatrix of the inner boundary of the blade and the generatrix of the outer boundary of the blade, geometric model data of the inner boundary of the blade and the outer boundary of the blade are respectively constructed;

[0135] The reconstructed impeller model is constructed using the geometric model data of the blade array and the inner and outer boundaries of the blades.

[0136] Please refer to Fig.15 , which shows a structural block diagram of a computing device 150 provided by an exemplary embodiment of the present disclosure. In some examples, the computing device 150 may be at least one of a smart phone, a smart watch, a desktop computer, a laptop, a virtual reality terminal, an augmented reality terminal, a wireless terminal, and a laptop portable computer. The computing device 150 has a communication function and can access a wired network or a wireless network. The computing device 150 may generally refer to one of a plurality of terminals, and those skilled in the art may know that the number of the above terminals may be more or less. In some examples, the computing device 150 may receive data based on the wired network or wireless network to which it is connected. It can be understood that the computing device 150 undertakes the calculation and processing work of the technical solution of the present disclosure, and the present disclosure does not limit this.

[0137] like Fig.15 As shown, the computing device 150 in the present disclosure may include one or more of the following components: a processor 1510 and a memory 1520 .

[0138] Optionally, the processor 1510 uses various interfaces and lines to connect various parts within the entire computing device, and executes various functions of the computing device and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 1520, and calling data stored in the memory 1520. Optionally, the processor 1510 can be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), and programmable logic array (PLA). The processor 1510 can integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), a neural network processor (NPU), and a baseband chip. Among them, the CPU mainly processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing the content that needs to be displayed on the touch display; the NPU is used to implement artificial intelligence (AI) functions; and the baseband chip is used to process wireless communications. It is understandable that the above-mentioned baseband chip may not be integrated into the processor 1510, but may be implemented by a separate chip.

[0139] The memory 1520 may include a random access memory (RAM) or a read-only memory (ROM). Optionally, the memory 1520 includes a non-transitory computer-readable storage medium. The memory 1520 may be used to store instructions, programs, codes, code sets, or instruction sets. The memory 1520 may include a program storage area and a data storage area, wherein 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.), instructions for implementing the above various method embodiments, etc.; the data storage area may store data created according to the use of the computing device, etc.

[0140] In addition, those skilled in the art can understand that the structure of the computing device shown in the above drawings does not constitute a limitation on the computing device, and the computing device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. For example, the computing device also includes a display screen, a camera assembly, a microphone, a speaker, a radio frequency circuit, an input unit, a sensor (such as an acceleration sensor, 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.

[0141] The present disclosure also provides a computer storage medium storing at least one instruction, wherein the at least one instruction is used to be executed by a processor to implement the impeller model reconstruction method described in the above embodiments.

[0142] 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 impeller model reconstruction method described in the above-mentioned embodiments.

[0143] Those skilled in the art should be aware that in one or more of the above examples, the functions described in the present 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. Storage media can be any available media that can be accessed by a general or special-purpose computer.

[0144] It should be noted that the technical solutions described in the present disclosure can be combined arbitrarily without conflict.

[0145] The above is only a specific embodiment of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present disclosure, which should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A method for reconstructing an impeller model, characterized in that: The reconstruction method comprises: In the original impeller model, the characteristic surfaces of the blade part and the inner boundary part of the blade are obtained; Interpolating each characteristic surface of the blade portion based on the streamline direction of the surface parameter to obtain original data points of each characteristic surface; In the characteristic curved surface of the inner boundary of the blade, interpolation is performed based on the curved surface parameters of the inner boundary of the blade to obtain a generatrix of the inner boundary of the blade; Interpolating based on the surface parameters of the outer boundary of the blade to obtain a generatrix of the outer boundary of the blade; Among the original data points of the characteristic curved surface of the blade portion, smoothing is performed on the characteristic curved surface of the blade portion based on the connection points between the characteristic curved surfaces to obtain data points of the characteristic curved surface of the blade portion after smoothing; A reconstructed impeller model corresponding to the original impeller model is constructed according to the data points of the smoothed characteristic curved surface of the blade portion, the generatrix of the inner boundary portion of the blade, and the generatrix of the outer boundary portion of the blade.

2. The reconstruction method according to claim 1, characterized in that: The method of interpolating each characteristic surface of the blade portion based on the streamline direction of the surface parameter to obtain original data points of each characteristic surface includes: For each characteristic curved surface of the blade portion, divide at least one cross section along the first curved surface parameter direction to obtain a cross-sectional line corresponding to each cross section; Interpolate each section line along the direction of the second surface parameter to obtain data points of each section line; The data points of all cross-section lines of each characteristic surface constitute the original data points of each characteristic surface.

3. The reconstruction method according to claim 1, characterized in that: The blade portion includes a main blade and a splitter blade; the characteristic curved surfaces of the blade portion include: a pressure surface, a suction surface, a leading edge and a trailing edge.

4. The reconstruction method according to claim 1, characterized in that: In the characteristic surface of the inner boundary of the blade, interpolation is performed based on the surface parameters of the inner boundary of the blade to obtain the generatrix of the inner boundary of the blade, including: In the characteristic curved surface of the inner boundary of the blade, data interpolation is performed along the vertical direction with the middle value of the curved surface parameters in the horizontal direction among the curved surface parameters of the inner boundary of the blade as the starting point to obtain the generatrix of the inner boundary of the blade.

5. The reconstruction method according to claim 1, characterized in that: The interpolation based on the surface parameters of the outer boundary of the blade to obtain the generatrix of the outer boundary of the blade includes: Based on the side surface of the main blade in the blade portion, a maximum virtual curved surface is expanded in the curved surface UV parameter direction of the side surface; Taking the middle value of the surface parameter in the horizontal direction of the virtual surface as a starting point, data interpolation is performed along the vertical direction to obtain the generatrix of the outer boundary of the blade.

6. The reconstruction method according to claim 1, characterized in that: In the original data points of the characteristic curved surface of the blade portion, the characteristic curved surface of the blade portion is smoothed based on the connection points between the characteristic curved surfaces to obtain the smoothed data points of the characteristic curved surface of the blade portion, including: Among the original data points of the characteristic curved surface of the blade portion, a first connection point between the cross-sectional line of the leading edge of the blade portion and the cross-sectional line of the pressure surface, a second connection point between the cross-sectional line of the pressure surface of the blade portion and the cross-sectional line of the trailing edge, a third connection point between the cross-sectional line of the trailing edge of the blade portion and the cross-sectional line of the suction surface, and a fourth connection point between the cross-sectional line of the suction surface of the blade portion and the cross-sectional line of the leading edge are sequentially determined; For each of the first connection point, the second connection point, the third connection point and the fourth connection point, fitting a corresponding cubic spline function; Interpolation is performed based on the cubic spline function corresponding to each connection point and the set constraint conditions to obtain data points of the characteristic curved surface of the blade portion after being smoothed.

7. The reconstruction method according to claim 1, characterized in that: The step of constructing a reconstructed impeller model corresponding to the original impeller model according to the data points of the smoothed characteristic curved surface of the blade portion, the generatrix of the inner boundary portion of the blade, and the generatrix of the outer boundary portion of the blade comprises: Based on the data points of the smoothed characteristic curved surface of the blade portion, a blade array is constructed according to the layout quantity and spacing angle; Constructing geometric model data of the inner boundary of the blade and the outer boundary of the blade respectively according to the generatrix of the inner boundary of the blade and the generatrix of the outer boundary of the blade; The reconstructed impeller model is constructed using the geometric model data of the blade array and the blade inner boundary and the blade outer boundary.

8. A device for reconstructing an impeller model, characterized in that: The reconstruction device comprises: an acquisition part, a blade processing part, a blade inner boundary processing part, a blade outer boundary processing part, a smoothing processing part and a construction part; wherein, The acquisition part is configured to acquire characteristic surfaces of the blade portion, the blade inner boundary portion, and the blade outer boundary portion in the original impeller model; The blade processing part is configured to interpolate each characteristic surface of the blade part based on the streamline direction of the surface parameter to obtain original data points of each characteristic surface; The blade inner boundary processing part is configured to perform interpolation based on the surface parameters of the blade inner boundary portion to obtain the generatrix of the blade inner boundary portion; The blade outer boundary processing part is configured to perform interpolation based on the surface parameters of the blade outer boundary portion to obtain the generatrix of the blade outer boundary portion; The smoothing processing part is configured to perform smoothing processing on the characteristic curved surface of the blade part based on the connection points between the characteristic curved surfaces among the original data points of the characteristic curved surface of the blade part, so as to obtain the data points of the characteristic curved surface of the blade part after being smoothed; The construction part is configured to construct a reconstructed impeller model corresponding to the original impeller model based on the data points of the smoothed characteristic surface of the blade portion, the generatrix of the inner boundary portion of the blade, and the generatrix of the outer boundary portion of the blade.

9. A computing device, characterized in that The computing device comprises: a processor and a memory; the processor is used to execute instructions stored in the memory to implement the impeller model reconstruction method according to any one of claims 1 to 7.

10. A computer storage medium, characterized in that: The computer storage medium stores at least one instruction, and the at least one instruction is used to be executed by a processor to implement the impeller model reconstruction method according to any one of claims 1 to 7.

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