Modeling method, device and equipment for fan blade and storage medium

Abstract

The invention provides a fan blade modeling method, device and equipment and a storage medium, and the method comprises the steps: obtaining local blade point cloud data corresponding to each scanning position in a plurality of scanning positions; wherein the plurality of scanning positions meet a preset requirement; performing point cloud data processing on the local blade point cloud data to obtain blade point cloud data corresponding to the fan blade; performing segmented modeling based on the blade point cloud data to obtain a plurality of segmented three-dimensional models; splicing the segmented three-dimensional models to obtain a blade three-dimensional model corresponding to the fan blade; and performing parametric modeling based on the blade three-dimensional model to obtain a blade parametric model. According to the technical scheme, a more accurate fan blade model can be efficiently established.

Description

Technical Field

[0001] This application relates to the technical field of wind power, and particularly relates to a modeling method, device, equipment and storage medium for wind turbine blades. Background Art

[0002] With the rapid development of wind power generation technology, the size and complexity of wind turbine blades are constantly increasing. When cutting retired wind turbine blades, in order to better formulate cutting plans, it is necessary to obtain the three-dimensional model of the wind turbine blades.

[0003] In related technologies, although it is possible to obtain the point cloud data of the external structure of wind turbine blades, there are still many problems in the process of point cloud data processing and modeling, which cannot meet the cutting requirements of high precision and high efficiency. Summary of the Invention

[0004] This application aims to solve at least one of the technical problems in related technologies to some extent.

[0005] In a first aspect, this application proposes a modeling method for wind turbine blades. The method includes: obtaining local blade point cloud data corresponding to each of a plurality of scanning positions, where the plurality of scanning positions meet a preset requirement; performing point cloud data processing on the local blade point cloud data to obtain blade point cloud data corresponding to the wind turbine blade; performing segmented modeling based on the blade point cloud data to obtain a plurality of segmented three-dimensional models; splicing the segmented three-dimensional models to obtain a blade three-dimensional model corresponding to the wind turbine blade; performing parametric modeling based on the blade three-dimensional model to obtain a blade parametric model.

[0006] In one implementation, the performing segmented modeling based on the blade point cloud data to obtain a plurality of segmented three-dimensional models includes: dividing the wind turbine blade into a plurality of blade segments; obtaining segmented point cloud data corresponding to each blade segment based on the blade point cloud data; respectively performing modeling based on the segmented point cloud data corresponding to each blade segment to obtain the segmented three-dimensional model corresponding to each blade segment.

[0007] In an optional implementation, the blade segments include at least one of the following: root; transition section; airfoil section; tip.

[0008] In one implementation, the preset requirement includes at least one of the following: the scanning coverage rate is greater than a preset first threshold; the scanning coverage rate is greater than a preset first threshold; the target overlap degree corresponding to adjacent scanning positions is greater than or equal to a preset second threshold.

[0009] In one implementation, the point cloud data processing includes at least one of the following: point cloud denoising; point cloud registration; point cloud coordinate transformation.

[0010] In one implementation, the method further includes: performing surface continuity fitting on the blade parametric model.

[0011] In a second aspect, the present application provides a modeling device for a wind turbine blade. The device includes: an acquisition module configured to acquire local blade point cloud data corresponding to each of a plurality of scanning positions, where the plurality of scanning positions meet a preset requirement; a first processing module configured to process the local blade point cloud data to obtain blade point cloud data corresponding to the wind turbine blade; a first modeling module configured to perform segmented modeling based on the blade point cloud data to obtain a plurality of segmented three-dimensional models; a second processing module configured to splice the segmented three-dimensional models to obtain a blade three-dimensional model corresponding to the wind turbine blade; and a second modeling module configured to perform parametric modeling based on the blade three-dimensional model to obtain a blade parametric model.

[0012] In one implementation, the first modeling module may be configured to: divide the wind turbine blade into a plurality of blade segments; acquire segmented point cloud data corresponding to each blade segment based on the blade point cloud data; and perform modeling respectively based on the segmented point cloud data corresponding to each blade segment to obtain the segmented three-dimensional model corresponding to each blade segment.

[0013] In an alternative implementation, the blade segment includes at least one of the following: a root; a transition segment; an airfoil segment; a tip.

[0014] In one implementation, the preset requirement includes at least one of the following: a scanning coverage rate greater than a preset first threshold; a target overlap degree corresponding to adjacent scanning positions greater than or equal to a preset second threshold.

[0015] In one implementation, the point cloud data processing includes at least one of the following: point cloud denoising; point cloud registration; point cloud coordinate transformation.

[0016] In one implementation, the device further includes a third processing module configured to perform surface continuity fitting on the blade parametric model.

[0017] In a third aspect, the present application provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor, where the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the modeling method of the wind turbine blade as described in the first aspect.

[0018] In a fourth aspect, the present application provides a computer-readable storage medium for storing instructions that, when executed, implement the method as described in the first aspect.

[0019] In a fifth aspect, the present application provides a computer program product including a computer program which, when executed by a processor, implements the steps of the method for modeling a wind turbine blade as described in the first aspect.

[0020] The method, apparatus, device and storage medium for modeling a wind turbine blade provided by the present application can perform point cloud data processing on local blade point cloud data obtained at multiple scanning positions to obtain the blade point cloud data of the wind turbine blade, perform segmented modeling based on the blade point cloud data to obtain a plurality of segmented three-dimensional models, and splice and parametrically model the segmented three-dimensional models to obtain a blade parametric model corresponding to the wind turbine blade. It can efficiently establish a more accurate wind turbine blade model.

[0021] Additional aspects and advantages of the present application will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of the present application. Description of the Drawings

[0022] The above and / or additional aspects and advantages of the present application will become apparent and be readily understood from the following description of the embodiments in conjunction with the drawings, where:

[0023] Figure 1 is a schematic flow chart of a method for modeling a wind turbine blade provided by an embodiment of the present application;

[0024] Figure 2 is a schematic flow chart of another method for modeling a wind turbine blade provided by an embodiment of the present application;

[0025] Figure 3 is a schematic structural diagram of a device for modeling a wind turbine blade provided by an embodiment of the present application;

[0026] Figure 4 is a schematic structural diagram of another device for modeling a wind turbine blade provided by an embodiment of the present application;

[0027] Figure 5 is a schematic structural diagram of an electronic device provided by an embodiment of the present application. Detailed Embodiments

[0028] Embodiments of the present application will be described in detail below. Examples of the embodiments are shown in the drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary and are intended to explain the present application and should not be construed as limiting the present application.

[0029] The method and apparatus for modeling a wind turbine blade according to embodiments of the present application will be described below with reference to the drawings.

[0030] Figure 1 This is a schematic flowchart of a method for modeling a wind turbine blade provided by an embodiment of the present application. As Figure 1 shown, the method may include but is not limited to the following steps:

[0031] Step S101: Obtain local blade point cloud data corresponding to each of multiple scanning positions.

[0032] Among them, in the embodiments of the present application, the above-mentioned multiple scanning positions are positions that can meet preset requirements.

[0033] Among them, in the embodiments of the present application, the above-mentioned preset requirements include: the scanning coverage rate is greater than a preset first threshold; the target overlap degree corresponding to adjacent scanning positions is greater than or equal to a preset second threshold.

[0034] Exemplarily, the positions and angles of the scanner can be selected in advance according to the size and shape of the wind turbine blade to ensure that the scanning coverage rate is greater than or equal to 90%, and at least 4 targets are set at each scanning position to ensure that the target overlap degree of adjacent scanning positions is greater than or equal to 30%, so as to obtain the local blade point cloud data obtained by scanning the wind turbine blade at each scanning position that meets the above requirements.

[0035] Step S102: Perform point cloud data processing on the local blade point cloud data to obtain the blade point cloud data corresponding to the wind turbine blade.

[0036] Among them, in the embodiments of the present application, the above-mentioned point cloud data processing includes at least one of the following: point cloud denoising, point cloud registration, and point cloud coordinate transformation.

[0037] Exemplarily, perform point cloud coordinate transformation on the local blade point cloud data corresponding to each scanning position respectively to convert the point cloud data from the original coordinate system to the geodetic coordinate system, then perform point cloud denoising on the converted point cloud data, and perform point cloud registration on the denoised multiple local blade point cloud data by using the station-by-station splicing registration and iterative closest point algorithm to obtain the blade point cloud data corresponding to the wind turbine blade.

[0038] Step S103: Perform segmented modeling based on the blade point cloud data to obtain multiple segmented three-dimensional models.

[0039] Exemplarily, divide the hierarchical blade into multiple blade segments, and perform segmented modeling based on the point cloud data corresponding to each segment in the blade point cloud data to obtain the segmented three-dimensional model corresponding to each blade segment.

[0040] Step S104: Splice the segmented three-dimensional models to obtain the blade three-dimensional model corresponding to the wind turbine blade.

[0041] Exemplarily, the segmented three-dimensional models corresponding to the blade segments are spliced according to the actual positional relationships of the respective blade segments to obtain the blade three-dimensional model corresponding to the wind turbine blade.

[0042] Step S105: Perform parametric modeling based on the blade three-dimensional model to obtain the blade parametric model.

[0043] Exemplarily, determine the variable parameters and constraints of the blade three-dimensional model, use parametric modeling software to extract the geometric features of the blade three-dimensional model, and set parameters and relationships for the geometric features based on the variable parameters and constraints of the blade three-dimensional model. And establish the blade parametric model according to the geometric features.

[0044] By implementing the embodiments of the present application, the point cloud data of the local blades obtained at multiple scanning positions can be processed to obtain the point cloud data of the wind turbine blade, and segmented modeling can be performed based on the point cloud data of the blade to obtain multiple segmented three-dimensional models, and the segmented three-dimensional models are spliced and parametrically modeled to obtain the blade parametric model corresponding to the wind turbine blade. It is possible to efficiently establish a more accurate wind turbine blade model.

[0045] In some embodiments, the point cloud data corresponding to each segment can be obtained respectively based on the point cloud data of the blade, and segmented modeling can be performed based on the point cloud data corresponding to each segment. As an example, please refer to Figure 2 , Figure 2 which is a schematic flow chart of another modeling method for a wind turbine blade provided by the embodiments of the present application. As shown in Figure 2 , the method may include but is not limited to the following steps:

[0046] Step S201: Obtain the local blade point cloud data corresponding to each scanning position among multiple scanning positions.

[0047] In the embodiments of the present application, step S201 can be implemented in any one of the embodiments of the present application, and the embodiments of the present application do not make any limitations in this regard and will not be elaborated further.

[0048] Step S202: Process the local blade point cloud data to obtain the point cloud data of the wind turbine blade corresponding thereto.

[0049] In the embodiments of the present application, step S202 can be implemented in any one of the embodiments of the present application, and the embodiments of the present application do not make any limitations in this regard and will not be elaborated further.

[0050] Step S203: Divide the wind turbine blade into multiple blade segments.

[0051] Among them, in the embodiments of the present application, the multiple blade segments of each wind turbine blade may include: a root; a transition section; an airfoil section; a tip.

[0052] Step S204: Obtain the segmented point cloud data corresponding to each blade segment based on the blade point cloud data.

[0053] Exemplarily, perform point cloud segmentation on the blade point cloud data based on the divided blade segments to obtain the segmented point cloud data corresponding to each blade segment.

[0054] Step S205: Respectively perform modeling based on the segmented point cloud data corresponding to each blade segment to obtain the segmented three-dimensional model corresponding to each blade segment.

[0055] Exemplarily, respectively perform three-dimensional modeling based on the segmented point cloud data corresponding to each blade segment to obtain the segmented three-dimensional model corresponding to each blade segment.

[0056] Step S206: Piece together the segmented three-dimensional models to obtain the blade three-dimensional model corresponding to the wind turbine blade.

[0057] Exemplarily, piece together the three-dimensional models corresponding to each blade segment according to the actual positional relationship of the blade segments to obtain the blade three-dimensional model corresponding to the wind turbine blade.

[0058] Step S207: Perform parametric modeling based on the blade three-dimensional model to obtain the blade parametric model.

[0059] In the embodiments of the present application, step S207 can be implemented in any one of the embodiments of the present application. The embodiments of the present application do not make any limitations in this regard and will not be elaborated further.

[0060] By implementing the embodiments of the present application, the segmented point cloud data of each blade segment can be obtained based on the blade point cloud data, so as to establish a segmented three-dimensional model based on the segmented point cloud data of each blade segment, and piece together the segmented three-dimensional models to obtain the blade three-dimensional model. It is possible to efficiently establish a more accurate wind turbine blade model.

[0061] In some embodiments, the above method further includes: performing surface continuity fitting on the blade parametric model.

[0062] Exemplarily, use G1 and G2 level surface continuity fitting techniques to process the blade parametric model to improve the smoothness and symmetry of the model surface.

[0063] Please refer to Figure 3 , Figure 3 which is a schematic structural diagram of a modeling device for a wind turbine blade provided by an embodiment of the present application. As Figure 3As shown in the figure, the device 300 includes: an acquisition module 301, configured to acquire local blade point cloud data corresponding to each of multiple scanning positions; wherein, the multiple scanning positions meet a preset requirement; a first processing module 302, configured to perform point cloud data processing on the local blade point cloud data to obtain blade point cloud data corresponding to the wind turbine blade; a first modeling module 303, configured to perform segmented modeling based on the blade point cloud data to obtain multiple segmented three-dimensional models; a second processing module 304, configured to splice the segmented three-dimensional models to obtain a blade three-dimensional model corresponding to the wind turbine blade; a second modeling module 305, configured to perform parametric modeling based on the blade three-dimensional model to obtain a blade parametric model.

[0064] In one implementation, the first modeling module 303 may be configured to: divide the wind turbine blade into multiple blade segments; acquire segmented point cloud data corresponding to each blade segment based on the blade point cloud data; and perform modeling respectively based on the segmented point cloud data corresponding to each blade segment to obtain a segmented three-dimensional model corresponding to each blade segment.

[0065] In an optional implementation, the blade segment includes at least one of the following: a root; a transition segment; an airfoil segment; a tip.

[0066] In one implementation, the preset requirement includes at least one of the following: the scanning coverage rate is greater than a preset first threshold; the target overlap degree corresponding to adjacent scanning positions is greater than or equal to a preset second threshold.

[0067] In one implementation, the point cloud data processing includes at least one of the following: point cloud denoising; point cloud registration; point cloud coordinate transformation.

[0068] In one implementation, the above device further includes a third processing module. As an example, please refer to Figure 4 , Figure 4 which is a schematic structural diagram of another modeling device for a wind turbine blade provided by an embodiment of the present application. As shown in Figure 4 , the device 400 further includes a third processing module 406, configured to perform surface continuity fitting on the blade parametric model. Wherein, Figure 4 the modules 401-405 in Figure 3 have the same structure and function as the modules 301-305 in

[0069] Through the device of the embodiment of the present application, local blade point cloud data obtained from multiple scanning positions can be subjected to point cloud data processing to obtain blade point cloud data of the wind turbine blade, and segmented modeling can be performed based on the blade point cloud data to obtain multiple segmented three-dimensional models, and the segmented three-dimensional models can be spliced and parametrically modeled to obtain a blade parametric model corresponding to the wind turbine blade. It can efficiently establish a more accurate wind turbine blade model.

[0070] It should be noted that the foregoing explanations of the embodiments of the modeling method for the fan blade are also applicable to the modeling device for the fan blade in this embodiment, and will not be elaborated herein.

[0071] To implement the above embodiments, the present application also proposes an electronic device. Please refer to Figure 5 , Figure 5 which is a schematic structural diagram of the electronic device provided by the embodiments of the present application. As Figure 5 shown, the electronic device 500 includes: a processor 501, and a memory 502 communicatively connected to the processor 501; the memory 502 stores computer-executable instructions; the processor 501 executes the computer-executable instructions stored in the memory to implement the method provided in the foregoing embodiments.

[0072] To implement the above embodiments, the present application also proposes a computer-readable storage medium storing computer-executable instructions, which are used to implement the method provided in the foregoing embodiments when executed by a processor.

[0073] To implement the above embodiments, the present application also proposes a computer program product including a computer program, which implements the method provided in the foregoing embodiments when executed by a processor.

[0074] Wherein, in the description of the present application, unless otherwise specified, " / " means "or". For example, A / B may represent A or B; herein, "and / or" is merely a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone.

[0075] In the description of the foregoing embodiments, the descriptions referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0076] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the technical features indicated. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "a plurality" is at least two, such as two, three, etc., unless otherwise specifically defined.

[0077] Any process or method description represented in a flowchart or described otherwise herein may be understood to represent code modules, segments, or portions including one or more executable instructions for implementing custom logic functions or processes. The scope of the preferred embodiments of the present application includes additional implementations, where functions may be performed in a substantially simultaneous manner or in a reverse order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0078] Logic and / or steps represented in a flowchart or described otherwise herein, for example, may be considered as an ordered list of executable instructions for implementing a logical function, which may be specifically implemented in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device. For the purposes of this specification, a "computer-readable medium" may be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. More specific examples (non-exhaustive list) of the computer-readable medium include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium may even be paper or other suitable medium on which the program can be printed, as the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpretation, or other appropriate processing as necessary, and then stored in a computer memory.

[0079] It should be understood that various parts of the present application can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logic functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), and the like.

[0080] Those of ordinary skill in the art can understand that all or part of the steps carried by the methods in the above embodiments can be completed by instructing relevant hardware through a program. The program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0081] In addition, in each of the embodiments of the present application, the functional units can be integrated into a processing module, or each unit can exist physically alone, or two or more units can be integrated into a module. The above integrated module can be implemented in the form of hardware or in the form of a software functional module. When the above integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0082] The above-mentioned storage medium can be a read-only memory, a magnetic disk, an optical disk, or the like. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A modeling method for a fan blade, characterized in that including: obtaining local blade point cloud data corresponding to each of a plurality of scanning positions, wherein the plurality of scanning positions meet a preset requirement; performing point cloud data processing on the local blade point cloud data to obtain blade point cloud data corresponding to a wind turbine blade; performing segmented modeling based on the blade point cloud data to obtain a plurality of segmented three-dimensional models; stitching the segmented three-dimensional models to obtain a blade three-dimensional model corresponding to the wind turbine blade; performing parametric modeling based on the blade three-dimensional model to obtain a blade parametric model.

2. The method according to claim 1, wherein The performing segmented modeling based on the blade point cloud data to obtain a plurality of segmented three-dimensional models includes: dividing the wind turbine blade into a plurality of blade segments; obtaining segmented point cloud data corresponding to each blade segment based on the blade point cloud data; respectively performing modeling based on the segmented point cloud data corresponding to each blade segment to obtain the segmented three-dimensional model corresponding to each blade segment.

3. The method according to claim 2, wherein The blade segment includes at least one of the following: root; transition section; airfoil section; tip.

4. The method according to claim 1, characterized in that, The preset requirement includes at least one of the following: the scanning coverage rate is greater than a preset first threshold; the target overlap degree corresponding to adjacent scanning positions is greater than or equal to a preset second threshold.

5. The method according to claim 1, characterized in that, The point cloud data processing includes at least one of the following: point cloud denoising; point cloud registration; point cloud coordinate transformation.

6. The method according to claim 1, characterized in that, The method further includes: performing surface continuity fitting on the blade parametric model.

7. A modeling device for a fan blade, characterized in that including: an acquisition module, configured to obtain local blade point cloud data corresponding to each of a plurality of scanning positions, wherein the plurality of scanning positions meet a preset requirement; a first processing module, configured to perform point cloud data processing on the local blade point cloud data to obtain blade point cloud data corresponding to a wind turbine blade; a first modeling module, configured to perform segmented modeling based on the blade point cloud data to obtain a plurality of segmented three-dimensional models; a second processing module, configured to stitch the segmented three-dimensional models to obtain a blade three-dimensional model corresponding to the wind turbine blade; a second modeling module, configured to perform parametric modeling based on the blade three-dimensional model to obtain a blade parametric model.

8. An electronic device, characterized in that, including: a processor and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, computer-executable instructions are stored in the computer-readable storage medium, and when the computer-executable instructions are executed by a processor, they are used to implement the method according to any one of claims 1 to 6.

10. A computer program product, characterized in that, including a computer program, which when executed by a processor, implements the method according to any one of claims 1 to 6.

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