Blade quality evaluation data file construction method, system, equipment and medium

Abstract

According to the blade quality evaluation data file construction method, system and equipment and the medium, four kinds of heterogeneous data including theoretical reference, tolerance parameters, endpoint constraints and actual measurement data are associated through a standardized architecture to form a complete quality evaluation data file, full-chain data communication from design to detection is supported, and the quality evaluation data file construction efficiency is improved. And full-process digital integration is realized. High-temperature / low-temperature working conditions are adapted through tolerance zone dynamic compensation, and fluctuation in the manufacturing process is handled through local curved surface reconstruction and an automatic remeasurement mechanism, so that the dynamic adaptability is enhanced. The closed tolerance curve eliminates the fuzzy edge judgment problem of a traditional open-loop tolerance zone, so that the judgment reliability is improved, compared with a closed curve shape judgment method, classification of the structural blades is much more reasonable, the structural blade shape judgment accuracy is improved, and the defects that in an existing detection method, a negative solution is possibly generated, and the judgment accuracy is poor are overcome. And the efficiency and the precision of blade detection data processing are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of aero-engine blade detection, and relates to a method, system, equipment and medium for constructing a blade quality assessment data file. Background Art

[0002] Blades are critical components of aircraft engines, and the shape of their intake and exhaust edges (leading and trailing edges) significantly impacts the engine's aerodynamic performance. Blade leading and trailing edge shapes are typically designed as circular or elliptical arcs. However, during actual production, processing techniques often result in non-ideal arc shapes. Existing blade parameter evaluation software can only assess parameters such as leading and trailing edge thickness, arc radius, leading and trailing edge point, chord length, twist angle, and profile, but cannot effectively identify non-ideal arc shapes. Currently, the evaluation of intake and exhaust edge shapes relies primarily on manual labor. Inspectors compare magnified images of the leading and trailing edge contours with standard drawings of unqualified leading and trailing edge shapes and draw conclusions through visual inspection. This inspection method suffers from drawbacks such as a lack of standardized image magnification and highly subjective judgment results, which can lead to inconsistent results between different inspectors. Furthermore, due to mass production of blades and the large number of inspected sections, manual evaluation is labor-intensive and time-consuming, significantly impacting the efficiency of comprehensive blade quality assessment.

[0003] The existing patent "A method for detecting the shape of the intake and exhaust edges of aircraft engine blades" uses the least squares method and NURBS curve fitting to detect blade shapes. However, this method may produce negative solutions in some cases, which does not conform to physical meaning. Summary of the Invention

[0004] In response to the problems existing in the prior art, the purpose of this invention is to provide a method, system, equipment and medium for constructing a blade quality assessment data file, which overcomes the problem that negative solutions may be generated in the existing detection methods and do not conform to physical meaning, and improves the efficiency and accuracy of blade detection data processing.

[0005] The present invention is achieved through the following technical solutions: A method for constructing a blade quality assessment data file comprises the following steps: Obtain theoretical geometric parameters of the blade profile, construct a standardized data set including a reference coordinate system and an ideal surface mathematical model, and thus obtain the ideal reference components of the blade profile; Based on the theoretical geometric parameters of the blade profile, tolerance data components and endpoint constraint components associated with the blade profile are generated respectively, and a qualified data range is set; the fitting curve of the tolerance data component is a closed curve; Process the measured point cloud data, perform segmented scanning of the blade profile, and generate measured data components including the non-closed blade back data chain and the non-closed blade basin data chain; Data association is performed on the ideal reference component, tolerance data component, endpoint constraint component, and blade base and blade back measured data components of the blade profile; By referencing metadata associated with the theoretical geometric parameters of the blade profile, tolerance data components and endpoint constraint components, the qualified range of the blade is controlled and the construction of the blade quality assessment data file is completed.

[0006] Preferably, the tolerance parameter components are obtained, specifically: Setting the number of measurement points for theoretical geometric parameters of the blade profile; generating tolerance data components associated with theoretical geometric parameters of the blade profile; The fitting curves of the tolerance data components are closed curves, which are respectively the inner tolerance curve and the outer tolerance curve of the blade profile; The qualified data range of the tolerance data component is set; wherein the inner tolerance closed curve is used to define the minimum allowable contour boundary, and the outer tolerance closed curve is used to define the maximum allowable contour boundary.

[0007] Preferably, the endpoint constraint component is obtained, specifically: Based on the theoretical geometric parameters of the blade profile, the endpoint constraint components associated with the blade profile are defined, including the blade root reference endpoint, the blade tip feature endpoint and the tenon connection endpoint, and the tolerance judgment criteria independent of the main blade profile are set.

[0008] Preferably, the ideal reference component, tolerance data component, endpoint constraint component, and blade base and blade back measured data components of the blade profile are data-associated as follows: Establish a data index layer on the top layer of the blade quality assessment data file structure; Storing the spatial coordinate mapping relationship of each data component in the metadata layer of the blade quality assessment data file structure; The original data sets of each component are stored in the bottom data layer of the blade quality assessment data file structure.

[0009] Preferably, the blade qualified range association control is achieved by referencing metadata associated with the theoretical geometric parameters of the blade profile, the tolerance data component and the endpoint constraint component, specifically including: The mathematical expressions of the inner tolerance closed curve and the outer tolerance closed curve are defined in the metadata; Establish a cross-section smooth closed curve generation module based on the cubic spline interpolation algorithm; Configure the tolerance zone dynamic compensation parameters to ensure the curvature continuity error of the closed curve is ≤0.01mm -1 .

[0010] Preferably, the qualified range of the theoretical geometric parameters of the blade profile extends between the inner tolerance and the outer tolerance of the tolerance data, specifically: The theoretical reference value of the blade profile is set as the mid-plane between the inner tolerance closed curve and the outer tolerance closed curve of the tolerance data component; The allowable deviation range varies continuously between the inner tolerance boundary value L1 and the outer tolerance boundary value L2 of the tolerance data component, satisfying ; Establish an adaptive expansion algorithm to automatically adjust according to the blade operating temperature changes Boundary value, the adjustment range shall not exceed ±15% of the theoretical reference value.

[0011] Preferably, the qualified range of the measured data component is specifically: The matching error Δx between the measured blade data point cloud and the blade theoretical profile should satisfy: ; Wherein, L1 is the inner tolerance boundary value of the fitting curve of the tolerance data component and L2 is the outer tolerance boundary value; Establish a dynamic compensation mechanism for measured data and activate the local surface reconstruction algorithm when a single point is out of tolerance; Configure abnormal data isolation areas and start the automatic re-measurement process for sections with continuous deviations of ≥3 data points.

[0012] A blade quality assessment data file construction system, comprising: Theoretical benchmark establishment module, tolerance parameter configuration module, endpoint constraint creation module and measured data construction module; Theoretical benchmark establishment module is used to obtain the theoretical geometric parameters of the blade profile and construct a standardized data set including the benchmark coordinate system and the ideal surface mathematical model, so as to obtain the ideal benchmark component; A tolerance parameter configuration module is used to generate tolerance data components associated with the theoretical geometric parameters of the blade profile based on the theoretical geometric parameters of the blade profile, and to set a qualified data range; An endpoint constraint creation module is used to generate endpoint constraint components associated with the blade profile based on theoretical geometric parameters of the blade profile and set a qualified data range; The measured data construction module is used to process the measured point cloud data, scan in segments, generate measured data components including the non-closed leaf back data chain and the non-closed leaf basin data chain, and integrate the discrete point cloud filtering algorithm and feature point matching engine; A data association module is used to associate the ideal reference component, tolerance data component, endpoint constraint component, and blade base and blade back measured data components of the blade profile; The data file construction module is used to realize the associated control of the blade's qualified range through metadata reference associated with the theoretical geometric parameters of the blade profile, tolerance data components and endpoint constraint components, and complete the construction of the blade quality assessment data file.

[0013] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method for constructing a blade quality assessment data file are implemented.

[0014] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method for constructing a blade quality assessment data file. Compared with the prior art, the present invention has the following beneficial technical effects: The present invention provides a method for constructing a blade quality assessment data file, which associates four types of heterogeneous data, namely theoretical benchmarks, tolerance parameters, endpoint constraints, and measured data, through a standardized architecture to form a complete quality assessment data file, supporting data connectivity throughout the entire chain from design to testing, and realizing digital integration of the entire process. Dynamic compensation of tolerance bands is used to adapt to high / low temperature working conditions, and local surface reconstruction and automatic re-measurement mechanisms are used to cope with fluctuations in the manufacturing process, thereby enhancing dynamic adaptability. Closed tolerance curves eliminate the fuzzy edge judgment problem of traditional open-loop tolerance bands, thereby improving the reliability of judgment; non-closed data chain processing adapts to the asymmetric feature scanning requirements of blade surfaces. Compared with the closed curve shape determination method, the present invention realizes a much more reasonable classification of constructed blades, thereby improving the accuracy of constructed blade shape judgment, overcoming the problem that negative value solutions may be generated in existing detection methods and do not conform to physical meaning, thereby improving the efficiency and accuracy of blade detection data processing.

[0015] Furthermore, a smooth closed curve (curvature continuity error ≤ 0.01 mm) was generated by the cubic spline interpolation algorithm. -1 ), which solves the curvature mutation problem caused by traditional linear interpolation or circular arc approximation, and makes the tolerance zone boundary more consistent with the actual machining error distribution.

[0016] Furthermore, the single-point deviation triggers the local surface reconstruction algorithm of the present invention, which repairs the data through the moving least squares method to avoid the overall data being scrapped. Continuous deviations of ≥3 points are automatically re-measured. Combined with the abnormal isolation zone design, manual intervention is reduced and detection efficiency is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 Constructing a system diagram for the blade quality assessment data file of the present invention; Figure 2 This is a flow chart of the specific processing of blades in the embodiment; Figure 3 Schematic diagram of the outline corresponding to the blade theoretical reference module and the tolerance parameter module of the present invention; Figure 4 For the present invention Figure 3 A partial enlarged schematic diagram.

[0018] Figure 5 It is a schematic diagram of the blade partitioning of the present invention.

[0019] Figure 6 This is a schematic diagram of the blade partition theory and actual fitting of the present invention; Among them, 1- the contour corresponding to the theoretical reference module, 2- the inner tolerance curve corresponding to the tolerance parameter module, 3- the outer tolerance curve corresponding to the tolerance parameter module, 4- the blade top contour corresponding to the measured data module, 5- the blade back contour corresponding to the measured data module, 6- the leading edge contour corresponding to the endpoint constraint module, and 7- the trailing edge contour corresponding to the endpoint constraint module. DETAILED DESCRIPTION

[0020] The present invention will be further described in detail below with reference to specific embodiments, which are intended to explain the present invention rather than to limit it.

[0021] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0022] See also Figure 1 and Figure 3 In one embodiment of the present invention, a method for constructing a blade quality assessment data file is provided, which is characterized by comprising the following steps: S100, establishing a theoretical benchmark module: setting theoretical geometric parameters of the blade profile, and constructing a standardized data set including a benchmark coordinate system and an ideal surface mathematical model; S200, establishing a tolerance parameter module: generating a tolerance data component associated with the blade profile, wherein the tolerance data component includes an inner tolerance closed curve and an outer tolerance closed curve, wherein the inner tolerance closed curve defines the minimum allowable profile boundary, and the outer tolerance closed curve defines the maximum allowable profile boundary, see Figure 3 and Figure 4 ; S300, establishing an endpoint constraint module: defining endpoint data components, including a blade root reference endpoint, a blade tip feature endpoint, and a tenon connection endpoint, and setting a tolerance judgment standard independent of the main profile; S400, build measured data module: process measured point cloud data, generate measured data components including non-closed leaf back data and non-closed leaf basin data, integrate discrete point cloud filtering algorithm and feature point matching engine, see Figure 5 ; like Figure 6 As shown, four types of heterogeneous data, namely theoretical benchmarks, tolerance parameters, endpoint constraints, and measured data, are linked through a standardized architecture to form a complete quality assessment data file, supporting data connectivity throughout the entire chain from design to testing and realizing digital integration of the entire process.

[0023] Dynamic compensation of the tolerance zone (±15% boundary adjustment) adapts to high / low temperature working conditions; local surface reconstruction and automatic re-measurement mechanisms cope with manufacturing process fluctuations, enhancing dynamic adaptability.

[0024] Closed tolerance curves eliminate the ambiguity of edge determination in traditional open-loop tolerance bands, improving determination reliability. Independent endpoint constraint components prevent misjudgment of key features by the main profile tolerance. Non-closed data link processing adapts to the asymmetric feature scanning requirements of blade surfaces.

[0025] The theoretical benchmark module, tolerance parameter module, endpoint constraint module, and measured data module are associated with each other through a hierarchical file structure, specifically including: S210, establishing a data index layer at the top level of the file structure; S220, storing the spatial coordinate mapping relationship of each data component in the metadata layer; S230: Storing the original data sets of each component in the bottom data layer.

[0026] Hierarchical data storage (index layer, metadata layer, underlying data layer) supports rapid retrieval and traceability, improving data access efficiency. A three-tiered data architecture (index layer, metadata layer, underlying data layer) enables structured association of multi-source data. The index layer improves data retrieval efficiency (hash table + R-tree index). The metadata layer ensures data consistency through spatial coordinate mapping (UUID identification). The UUID unique identifier provides an independent traceability label for each data component, meeting the AS9100D quality traceability requirements in the aviation field. The invention's qualified range association control (metadata reference) achieves dynamic linkage between theoretical, tolerance, and measured data.

[0027] The qualified range association control is achieved by referencing metadata associated with the theoretical benchmark module, tolerance parameter module, endpoint constraint module, and measured data module, specifically including: S310, defining mathematical expressions of an inner tolerance closed curve and an outer tolerance closed curve in metadata; S320, establishing a cross-section smooth closed curve generation module based on a cubic spline interpolation algorithm; The parameterized expression of the cubic spline interpolation algorithm is: Piecewise Function

[0028] in, a i node xi The segmentation coefficient of the reference coordinate value at the theoretical contour, b i For nodes x i The first-order derivative coefficient of c i For nodes x i The second-order derivative coefficient of d i For nodes x i The third-order derivative coefficient of x i are the node coordinates.

[0029] S330, configure the tolerance zone dynamic compensation parameters to ensure the curvature continuity error of the closed curve is ≤0.01mm -1 .

[0030] Smooth closed curve generated by cubic spline interpolation algorithm (curvature continuity error ≤ 0.01mm) -1 ), which solves the curvature mutation problem caused by traditional linear interpolation or circular arc approximation, and makes the tolerance zone boundary more consistent with the actual machining error distribution.

[0031] The qualified range extension configuration of the theoretical geometric parameters, tolerance data components, and endpoint data components of the blade profile corresponding to the theoretical reference module, tolerance parameter module, and endpoint constraint module is as follows: S410, setting the theoretical profile reference value as the mid-plane between the inner tolerance closed curve and the outer tolerance closed curve; S420, the deviation range is allowed to continuously change between the inner tolerance boundary value L1 and the outer tolerance boundary value L2, satisfying ; Full circumferential envelope control is achieved through internal / external tolerance closed curves, avoiding the risk of missed judgment in traditional single-section sampling.

[0032] S430. Establish an adaptive expansion algorithm to automatically adjust the L1 / L2 boundary value according to the change in the blade operating temperature, with the adjustment range not exceeding ±15% of the reference value.

[0033] The execution of the adaptive expansion algorithm includes: Input the real-time temperature T to obtain the material thermal expansion coefficient α; Calculate compensation amount ,in is the reference temperature, is the initial boundary value; Update the boundary value, that is, the new inner tolerance boundary value , the new outer tolerance boundary value

[0034] The adaptive expansion algorithm compensates the tolerance band boundaries in real time based on temperature (adjustment range ±15%), avoiding the tedious process of manual recalibration due to temperature changes required by traditional methods.

[0035] The qualified range control of the measured data component of the measured data module includes: S510, the matching error between the measured data point cloud and the theoretical contour should meet the following requirements: ; S520, establish a dynamic compensation mechanism for measured data, and start a local surface reconstruction algorithm when a single point exceeds the tolerance; S530: Configure an isolation zone for abnormal data and initiate an automatic retest process for sections with ≥3 consecutive out-of-tolerance data points. This automatic retest mechanism (triggered by ≥3 points) reduces manual intervention and, combined with the R-tree index, quickly locates abnormal areas, improving data cleaning efficiency by 40%.

[0036] Among them, the local surface reconstruction algorithm adopts the moving least squares method; the moving least squares method performs weighted fitting on the neighborhood of the out-of-difference point through a Gaussian weight function, effectively suppressing noise interference and reducing the local matching error between the reconstructed surface and the theoretical model to below 0.015mm, meeting the micron-level precision requirements of aircraft engine blades.

[0037] The steps of the evaluation data file construction method include: S610, loading the data theory benchmark module, tolerance parameter module, and endpoint constraint module to parse the module contents and extract key parameters and data, such as section coordinate point parameters, tolerance values, etc.; S620, converting the theoretical geometric parameters of the blade profile, the tolerance data component, and the endpoint data component into a subdivision NURBS curve at level 5; S630: Convert the measured data components of the measured data module into NURBS curves.

[0038] The steps of the evaluation data file construction method further include: S710, through dynamic fitting, curvature calculation and error analysis; S720, automatically analyzes and evaluates and issues a profile report that complies with GBT 1958-2017 standards.

[0039] Specifically: Dynamic Fitting: Input data: measured point cloud data link (non-closed blade back / base data link) Execution algorithm: a. Use the moving least squares (MLS) method to perform surface fitting and define the fitting function; b. Set the iteration termination condition: the change rate of the residual error between two consecutive fits is ≤ 0.5%; Output: fitting surface equation and control point set; Curvature calculation: Execution method: Calculation objects: fitting surface and theoretical model NURBS surface; a. Calculate the principal curvature for any point P on the surface; b. Generate a curvature distribution cloud map and mark the areas of maximum positive curvature and minimum negative curvature; Error analysis Judgment criterion: Theoretical model tolerance zone (inner / outer tolerance closed curve) Execution process: a. Calculate the minimum distance from each measured point to the theoretical surface b. Statistical deviation indicators; c. Generate an error heat map and mark the coordinates of the out-of-tolerance areas and the deviation values; Contour assessment Evaluation standard: GB / T 1958-2017 "Geometric Technical Specifications for Products (GPS) - Profile Testing" Calculation of key parameters:

[0040] Automated process: a. Call the metadata layer's UUID identifier to match the detection item; b. Extract raw point cloud deviation data from the underlying data layer; c. Generate a report in PDF / XML dual format based on XSLT template transformation; See Dynamic Compensation Feedback Exception handling mechanism: a. When When , S520 local surface reconstruction is triggered; b. Perform R-tree spatial indexing on the coordinates of the out-of-tolerance points and associate them with the compensation parameters of the machining machine tools; Figure 2 In one embodiment of the present invention, a schematic diagram of data generated by a method for detecting the double-notch blade profile of the inlet and exhaust edges of a precision forged blade is provided.

[0041] In another embodiment of the present invention, a computer device is provided, comprising a processor and a memory, wherein the memory is used to store a computer program, wherein the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is suitable for implementing one or more instructions, specifically for loading and executing one or more instructions to implement a corresponding method flow or corresponding function. The processor described in the embodiment of the present invention can perform an operation of a blade quality assessment data file construction method.

[0042] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory). The computer-readable storage medium is a memory device in a computer device, used to store programs and data. It is understood that the computer-readable storage medium herein may include both built-in storage media in the computer device and, of course, extended storage media supported by the computer device. The computer-readable storage medium provides storage space, which stores the terminal's operating system. Furthermore, the storage space also stores one or more instructions suitable for being loaded and executed by a processor. These instructions may be one or more computer programs (including program code). It should be noted that the computer-readable storage medium herein may be high-speed RAM memory or non-volatile memory, such as at least one disk storage device. The processor may load and execute the one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the method for constructing a blade quality assessment data file in the above-mentioned embodiment.

[0043] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0044] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0045] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0046] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0047] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

[0048] It should be noted that the terms "including" and "having" and any variations thereof in the specification and claims of the present invention and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or are inherent to these processes, methods, products or apparatuses.

[0049] It will be understood that when used in this specification and the appended claims, the terms “comprises” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0050] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one skilled in the art to which this invention pertains. The terms used in this specification of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0051] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Any ordinary technician in this industry can smoothly implement the present invention as shown in the drawings and described above. However, any equivalent changes, modifications and evolutions made by technicians familiar with this profession without departing from the scope of the technical solution of the present invention using the technical content disclosed above are all equivalent embodiments of the present invention. At the same time, any equivalent changes, modifications and evolutions made to the above embodiments based on the essential technology of the present invention are still within the scope of protection of the technical solution of the present invention.

Claims

1. A method for constructing a blade quality assessment data file, characterized in that: The following steps are involved: Obtain theoretical geometric parameters of the blade profile, construct a standardized data set including a reference coordinate system and an ideal surface mathematical model, and thus obtain the ideal reference components of the blade profile; Based on the theoretical geometric parameters of the blade profile, tolerance data components and endpoint constraint components associated with the blade profile are generated respectively, and a qualified data range is set; the fitting curve of the tolerance data component is a closed curve; Process the measured point cloud data, perform segmented scanning of the blade profile, and generate measured data components including the non-closed blade back data chain and the non-closed blade basin data chain; Data association is performed on the ideal reference component, tolerance data component, endpoint constraint component, and blade base and blade back measured data components of the blade profile; By referencing metadata associated with the theoretical geometric parameters of the blade profile, tolerance data components and endpoint constraint components, the qualified range of the blade is controlled and the construction of the blade quality assessment data file is completed.

2. The method for constructing a blade quality assessment data file according to claim 1, characterized in that: Get the tolerance parameter components, specifically: Setting the number of measurement points for theoretical geometric parameters of the blade profile; generating tolerance data components associated with theoretical geometric parameters of the blade profile; The fitting curves of the tolerance data components are closed curves, which are respectively the inner tolerance curve and the outer tolerance curve of the blade profile; The qualified data range of the tolerance data component is set; wherein the inner tolerance closed curve is used to define the minimum allowable contour boundary, and the outer tolerance closed curve is used to define the maximum allowable contour boundary.

3. The method for constructing a blade quality assessment data file according to claim 1, characterized in that: Get the endpoint constraint components, specifically: Based on the theoretical geometric parameters of the blade profile, the endpoint constraint components associated with the blade profile are defined, including the blade root reference endpoint, the blade tip feature endpoint and the tenon connection endpoint, and the tolerance judgment criteria independent of the main blade profile are set.

4. The method for constructing a blade quality assessment data file according to claim 1, characterized in that: The ideal reference component, tolerance data component, endpoint constraint component, and measured data components of the blade base and blade back are associated with each other, specifically: Establish a data index layer on the top layer of the blade quality assessment data file structure; Storing the spatial coordinate mapping relationship of each data component in the metadata layer of the blade quality assessment data file structure; The original data sets of each component are stored in the bottom data layer of the blade quality assessment data file structure.

5. The method for constructing a blade quality assessment data file according to claim 1, characterized in that: By referencing metadata associated with the theoretical geometric parameters, tolerance data components, and endpoint constraint components of the blade profile, the associated control of the blade's qualified range is achieved, including: The mathematical expressions of the inner tolerance closed curve and the outer tolerance closed curve are defined in the metadata; Establish a cross-section smooth closed curve generation module based on the cubic spline interpolation algorithm; Configure the tolerance zone dynamic compensation parameters to ensure the curvature continuity error of the closed curve is ≤0.01mm -1 .

6. The method for constructing a blade quality assessment data file according to claim 1, characterized in that: The qualified range of the theoretical geometric parameters of the blade profile extends between the inner tolerance and the outer tolerance of the tolerance data, specifically: The theoretical reference value of the blade profile is set as the mid-plane between the inner tolerance closed curve and the outer tolerance closed curve of the tolerance data component; The allowable deviation range varies continuously between the inner tolerance boundary value L1 and the outer tolerance boundary value L2 of the tolerance data component, satisfying ; An adaptive expansion algorithm is established to automatically adjust the L1 / L2 boundary value according to the changes in blade operating temperature, and the adjustment range does not exceed ±15% of the theoretical reference value.

7. The method for constructing a blade quality assessment data file according to claim 6, characterized in that: The qualified range of measured data components is as follows: Matching error between measured blade data point cloud and blade theoretical profile Should meet the following requirements: ; Wherein, L1 is the inner tolerance boundary value of the fitting curve of the tolerance data component and L2 is the outer tolerance boundary value; Establish a dynamic compensation mechanism for measured data and activate the local surface reconstruction algorithm when a single point is out of tolerance; Configure abnormal data isolation areas and start the automatic re-measurement process for sections with continuous deviations ≥ preset n data points.

8. A blade quality assessment data file construction system, based on a blade quality assessment data file construction method according to any one of claims 1 to 7, characterized in that: include, Theoretical benchmark establishment module, tolerance parameter configuration module, endpoint constraint creation module and measured data construction module; Theoretical benchmark establishment module is used to obtain the theoretical geometric parameters of the blade profile and construct a standardized data set including the benchmark coordinate system and the ideal surface mathematical model, so as to obtain the ideal benchmark component; A tolerance parameter configuration module is used to generate tolerance data components associated with the theoretical geometric parameters of the blade profile based on the theoretical geometric parameters of the blade profile, and to set a qualified data range; An endpoint constraint creation module is used to generate endpoint constraint components associated with the blade profile based on theoretical geometric parameters of the blade profile and set a qualified data range; The measured data construction module is used to process the measured point cloud data, scan in segments, generate measured data components including the non-closed leaf back data chain and the non-closed leaf basin data chain, and integrate the discrete point cloud filtering algorithm and feature point matching engine; A data association module is used to associate the ideal reference component, tolerance data component, endpoint constraint component, and blade base and blade back measured data components of the blade profile; The data file construction module is used to realize the associated control of the blade's qualified range through metadata reference associated with the theoretical geometric parameters of the blade profile, tolerance data components and endpoint constraint components, and complete the construction of the blade quality assessment data file.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method for constructing a blade quality assessment data file as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for constructing a blade quality assessment data file as described in any one of claims 1 to 7 are implemented.

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