Methods, systems, control equipment and devices for reducing machining errors of composite parts

Abstract

This application relates to a method, system, control equipment, and apparatus for reducing machining errors in composite material parts. The method includes acquiring a mathematical model of the composite material part to be machined, analyzing the mathematical model, extracting reference parameters, setting multiple sampling points on a theoretical reference surface and obtaining theoretical data for these sampling points, acquiring measured data for all sampling points and pre-drilled process holes after the composite material part is fixed, establishing an initial coordinate system based on the measured data of the pre-drilled process holes, correcting the initial coordinate system using a weighted best-fit algorithm based on the theoretical and measured data of the sampling points and pre-drilled process holes to obtain a machining coordinate system, where the weight of the pre-drilled process holes is greater than or equal to the weight of the sampling points, and generating CNC machining instructions based on the machining coordinate system. This application can cut off the tolerance transfer path from the reference source, reduce cumulative hole-making errors, and improve the pass rate and assembly quality of composite material molding.

Description

Technical Field

[0001] This application relates to the field of composite material molding and manufacturing technology, and in particular, to methods, systems, control equipment and apparatus for reducing processing errors of composite material parts. Background Technology

[0002] In the aerospace field, large-size integrated carbon fiber composite parts are characterized by their large size (over 5m in length), complex structure, high molding precision, high unit cost, long reference transfer chain, and extremely high assembly and fitting precision requirements. The reference transfer accuracy of pre-drilled process holes directly determines the part's pass rate and the assembly quality of its sections.

[0003] Currently, the industry mainly divides the processing technology for large-size composite material parts into three types.

[0004] 1. Traditional process based on pre-drilled process holes as the datum. This machining process uses pre-drilled process holes, manually drilled during the forming stage, as the sole datum for datum transfer. The machining coordinate system is entirely determined by the actual position of the pre-drilled process holes. However, manually drilled process holes are inevitably affected by factors such as operator skill, fatigue, drill template clearance, and wear. The positional accuracy of the pre-drilled process holes has inherent deviations that are difficult to eliminate through traditional processes. The industry average is ±0.25mm, and for some large parts, due to manual operation errors, deviations can reach over 0.6mm. Using pre-drilled process holes with inherent deviations to establish the coordinate system causes the entire coordinate system to shift and rotate. This offset is transferred to all machining features of the part, forming a cumulative error. The larger the part size, the more obvious the error amplification effect, leading to feature deviations, assembly interference, or even the scrapping of large parts.

[0005] 2. Precision Optimization Technology Based on Automated Process Hole Drilling. To address the insufficient precision of manual hole drilling, some high-end manufacturing scenarios use automated equipment to replace manual labor. Although automation can improve the precision of drilling pre-drilled process holes, the machining process still "establishes a coordinate system based solely on the pre-drilled process hole," making it impossible to correct deviations in work-in-process parts with existing manually drilled process holes. In the industry, the drilling of pre-drilled process holes for aerospace composite parts is usually completed in the forming workshop, which belongs to a different process and area from the machining workshop. After a large number of work-in-process parts with completed manual process holes are transferred to the machining process, this solution cannot correct their deviations. At the same time, the investment in a single automated equipment exceeds one million yuan, requiring additional dedicated space and personnel, resulting in extremely high modification costs and making it difficult to promote in small-batch, multi-variety production. Therefore, it cannot solve the problem of reference deviation for a large number of existing parts, and the input-output ratio is low.

[0006] 3. Deviation Compensation Technology for Single-Feature Holes in Machining Process. To address the issue of out-of-tolerance errors in single high-precision holes during machining, some existing technologies employ a single-feature local compensation scheme. Specifically, after establishing a machining coordinate system based on the pre-drilled process hole, the coordinates of the reference point of the hole to be machined are measured and collected. The positional deviation of the single hole is calculated by comparing it with theoretical values, and the coordinates of the single hole are compensated individually in the CNC program to achieve precise machining. However, this scheme only compensates for the independent coordinates of a single feature to be machined; the overall coordinate system offset still exists, and the deviation transmission path of the pre-drilled process hole is not severed. For dozens or hundreds of machining features widely distributed on large-sized parts, it is impossible to compensate them one by one, and it cannot solve the overall offset of continuous surfaces such as contours and mating surfaces. Furthermore, individual compensation can lead to inconsistent machining references, causing new geometric tolerance deviations. Ultimately, it cannot suppress tolerance transmission, has extremely low compensation efficiency, and is unsuitable for mass production.

[0007] 4. Coordinate system reconstruction technology based on surface measurement. This type of technology reconstructs the workpiece coordinate system by measuring the coordinates of surface points on the part and using least-squares fitting to compensate for positioning deviations. However, this technology relies entirely on the surface measurement points as the fitting reference, weakening or even ignoring the reference constraint effect of pre-drilled process holes. This can easily lead to the coordinate system deviating too much from the original process reference, resulting in inconsistencies between the machining reference and the subsequent assembly reference. Furthermore, it only offsets the machining coordinate system at the software level without physically correcting the pre-drilled process holes themselves. After machining, the original positioning holes still have their original deviations, which will introduce errors again when subsequent assembly still uses the deviation holes as the reference, making it impossible to achieve consistency of the reference throughout the entire process. At the same time, this type of technology does not consider the impact of part clamping deformation, the rationality of sampling point distribution, and measurement outliers on the fitting accuracy. For large-sized, high-curvature, and weakly rigid aerospace composite material parts, the fitting accuracy fluctuates greatly and cannot meet the requirements of high-precision assembly.

[0008] Existing technologies cannot solve the problem of cumulative error throughout the entire process caused by deviations in pre-drilled process holes from the source without requiring additional high investment in equipment or secondary rework of pre-drilled process holes. Therefore, they cannot meet the production requirements of high precision, low cost, and high yield for large-size integrated composite parts. Summary of the Invention

[0009] The technical problem this application aims to solve is to address the shortcomings of existing technologies that either rely entirely on process holes as the datum, making deviation correction impossible, or rely entirely on surface measurement to reconstruct the coordinate system, resulting in the loss of process hole datums and the inability to physically solidify the datum. This application provides a method and system for reducing machining errors in composite material parts. While retaining the main datum constraint of the pre-drilled process holes, it corrects coordinate system deviations through weighted fitting and physically solidifies the datum through process-corrected holes, thereby improving the datum accuracy throughout the machining-assembly process. This application can cut off the tolerance transfer path from the datum source, reduce cumulative hole-making errors, and improve the pass rate and assembly quality of composite material molding.

[0010] To address the aforementioned technical problems, according to one aspect of this application, a method for reducing processing errors in composite material parts is provided, comprising the following steps: Step S1, obtaining a mathematical model of the composite material part to be processed, analyzing the mathematical model, and extracting reference parameters, including theoretical reference surfaces and theoretical data of pre-drilled process holes; Step S2, setting multiple sampling points on the theoretical reference surfaces and obtaining theoretical data of the sampling points, obtaining measured data of all sampling points and pre-drilled process holes detected after the composite material part to be processed is fixed, and establishing an initial coordinate system after the composite material part to be processed is fixed based on the measured data of the pre-drilled process holes; Step S3, using the pre-drilled process holes as the main reference constraint and the sampling points as surface correction supplements, correcting the initial coordinate system using a weighted best fitting algorithm based on the theoretical and measured data of all sampling points and all pre-drilled process holes to obtain a processing coordinate system, wherein the ratio of the first weight corresponding to the sampling point to the second weight corresponding to the pre-drilled process hole is 0.2∶1. To 1:1; Step S4, generate CNC machining instructions according to the machining coordinate system. The CNC machining instructions include machining instructions for the shape and features of the composite material part to be machined, and machining instructions for drilling process correction holes in the non-functional allowance area of ​​the composite material part to be machined, and use the process correction holes as the sole positioning reference for subsequent assembly.

[0011] According to an embodiment of this application, the reference parameters further include: the theoretical surface of the assembly interference-prone position and the theoretical parameters of the feature to be processed; the theoretical data of the pre-drilled process hole includes: the three-dimensional coordinates of the center of the pre-drilled process hole, the axis vector, the hole diameter tolerance, and the position tolerance; the theoretical parameters of the feature to be processed include: the three-dimensional data model of the feature to be processed, the tolerance requirements, and the machining allowance; the measured data of the sampling point is the three-dimensional coordinates of the sampling point; and the measured data of the pre-drilled process hole is the three-dimensional coordinates of the center of the pre-drilled process hole and the axis vector.

[0012] According to the embodiments of this application, in step S2, the rules for setting sampling points are as follows: the number of sampling points is greater than 30; the density of sampling points in the assembly interference area, thickness variation area, curvature variation area and the surrounding area of ​​the composite material part to be processed is greater than that in other areas; when the length of the composite material part to be processed is ≥5m, based on the number of sampling points of not less than 30 corresponding to a length of 5m, for every 1m increase in length, the number of sampling points increases by not less than 8.

[0013] According to an embodiment of this application, after setting up multiple sampling points, the sampling points are further screened. The method for screening the sampling points is as follows: based on the curvature distribution and stiffness distribution of the mathematical model of the composite material part to be processed, the entropy weight method is used to obtain the influence weight of the deviation of each sampling point on the overall fitting residual, and the influence weight is used as the contribution of each sampling point to the coordinate system fitting. Sampling points with contribution values ​​lower than a preset threshold are removed. The preset threshold is pre-set according to the curvature, stiffness and accuracy requirements of the composite material part to be processed.

[0014] According to an embodiment of this application, before setting up sampling points, a finite element model of the composite material part to be processed is constructed. Based on the material properties, vacuum adsorption force distribution, and support position, the deformation distribution of the composite material part to be processed under different vacuum adsorption forces is simulated. When setting up sampling points, areas where the simulated deformation is greater than a second set threshold are avoided. Furthermore, when the initial coordinate system is corrected using a coordinate system optimal fitting algorithm, the sampling points in areas where the simulated deformation is greater than a third set threshold are given a lower first weight. The third set threshold is less than the second set threshold. Both the third set threshold and the second set threshold are preset based on the material and thickness of the composite material part to be processed.

[0015] According to an embodiment of this application, in step S2, the method for establishing the initial coordinate system is as follows: based on the three-dimensional coordinates of the center of the pre-drilled process hole measured after the composite material part to be processed is fixed, a Cartesian coordinate system is established using the 3-2-1 positioning rule, and this is used as the initial coordinate system.

[0016] According to an embodiment of this application, in step S3, the method for correcting the initial coordinate system using a weighted best-fit algorithm to obtain the machining coordinate system is as follows: obtain the coordinate deviation of the sampling points based on the measured data and theoretical data of the sampling points, and obtain the parameter deviation of the pre-drilled process holes based on the measured data and theoretical data of the pre-drilled process holes; multiply the coordinate deviation of each sampling point by a first weight to obtain the weighted coordinate deviation of the sampling points, and multiply the parameter deviation of each pre-drilled process hole by a second weight to obtain the weighted deviation of the pre-drilled process hole parameters; with the minimum of the sum of the squares of the weighted coordinate deviations of all sampling points and the weighted deviations of the pre-drilled process hole parameters as the optimization objective, iteratively solve the problem using an optimal fitting algorithm to obtain the translation and rotation correction parameters of the initial coordinate system, and perform translation and rotation correction on the initial coordinate system based on the translation and rotation correction parameters to obtain the machining coordinate system.

[0017] According to an embodiment of this application, when the initial coordinate system is corrected using the optimal fitting algorithm, the sampling points are first dynamically optimized. The dynamic optimization steps include: after completing the first round of iterative fitting using the optimal fitting algorithm, identifying the deviation region where the coordinate deviation of the sampling points is greater than a first set threshold, adding sampling points in the deviation region, and then calling the optimal fitting algorithm again to solve the problem; repeating the above steps until the coordinate deviation of all sampling points is less than the first set threshold, terminating the iteration, and completing the dynamic optimization of the sampling points.

[0018] According to the embodiments of this application, before iteratively solving using the optimal fitting algorithm, a random sampling consensus algorithm is applied to identify and remove outlier sampling points. During the iteration process of the random sampling consensus algorithm, a temporary fitting surface is constructed based on the current random sampling sample set, and the orthogonal distance from all sampling points to the current temporary fitting surface is calculated. Sampling points whose orthogonal distance exceeds three times the standard deviation of the current iteration residual distribution are marked as potential outliers. It is set that the number of outliers removed in a single iteration does not exceed 5% of the total number of sampling points. If the number of potential outliers exceeds 5%, the potential outliers are sorted in descending order according to their orthogonal distance, and the top 5% with the largest distance are selected as outlier sampling points. If the number of potential outliers does not exceed 5%, then all potential outliers are outlier sampling points.

[0019] According to embodiments of this application, the optimal fitting algorithm includes the Levenberg-Marquardt algorithm (LM algorithm), the Gauss-Newton iterative algorithm, the genetic algorithm, and the particle swarm optimization algorithm.

[0020] According to an embodiment of this application, in step S3, the method for determining the ratio of the first weight and the second weight is as follows: a weight allocation prediction model is trained based on historical processing data. The input features of the weight allocation prediction model include the material, size, molding accuracy, historical sampling point coordinate deviation, and historical pre-drilled process hole parameter deviation of the composite material part. The output is the first weight and the second weight. The material, size, and molding accuracy of the composite material part to be processed are input into the weight allocation prediction model, and the weight allocation prediction model generates the first weight and the second weight of the part.

[0021] According to the embodiments of this application, in step S3, after obtaining the machining coordinate system, it is also necessary to verify the deviation validity of the machining coordinate system. The method for verifying the deviation validity of the machining coordinate system is as follows: calculate the coordinate deviation of all sampling points and the deviation of pre-drilled process hole parameters based on the machining coordinate system. If the coordinate deviation of all sampling points and the deviation of pre-drilled process hole parameters are within the set tolerance range, the verification is passed and the machining coordinate system is valid. If any of the coordinate deviations of all sampling points and the deviations of pre-drilled process hole parameters exceed the set tolerance, the verification is not passed. After adding sampling points to the area where the deviation exceeds the standard, step S3 is re-executed to obtain a new machining coordinate system, and the deviation validity of the new machining coordinate system is verified. If the verification is passed, step S4 is executed. If the verification is not passed, the composite material part to be processed needs to be inspected or a conformity review of the composite material part to be processed needs to be initiated.

[0022] According to an embodiment of this application, the method for reducing the processing error of composite material parts further includes step S5, which involves encrypting and storing the parameters of the processing coordinate system and the process correction holes, and completing the docking assembly at the assembly station based on the parameters of the process correction holes.

[0023] According to the embodiments of this application, the machining coordinate system is combined with the machining cutting thermal deformation prediction model and the tool wear dynamic compensation model of the composite material part to be machined to obtain the thermal deformation compensation amount and the tool wear compensation amount. When machining the shape and features of the composite material part to be machined, as well as drilling process correction holes, the machining trajectory is generated based on the machining coordinate system, the thermal deformation compensation amount and the tool wear compensation amount to complete the machining.

[0024] According to embodiments of this application, the method for reducing processing errors of composite material parts further includes establishing a digital twin model of the composite material part to be processed based on the full-process data of the processing of the composite material part to be processed.

[0025] According to another aspect of this application, a system for reducing machining errors of composite material parts is provided, comprising: a storage module for storing mathematical models of composite material parts; a model loading and parsing module for loading the corresponding mathematical model according to the composite material part to be processed, and parsing the mathematical model to obtain reference parameters, the reference parameters including theoretical reference surfaces and theoretical data of pre-drilled process holes; a setting module for setting multiple sampling points on the theoretical reference surfaces and obtaining theoretical data of the sampling points; a data acquisition module for acquiring measured data of pre-drilled process holes and sampling points; a coordinate system establishment module for establishing an initial coordinate system based on the measured data of pre-drilled process holes; a coordinate system transformation module for using pre-drilled process holes as the main reference constraint and sampling points as surface correction supplements, and using a weighted best fitting algorithm to correct the initial coordinate system to obtain a machining coordinate system based on the measured data and theoretical data of multiple sampling points and pre-drilled process holes; and a machining control module for generating CNC machining instructions according to the machining coordinate system and sending the CNC machining instructions to a CNC machining device, the CNC machining instructions including machining instructions for the shape and features of the part and machining instructions for drilling process correction holes in the part's allowance area.

[0026] According to another aspect of this application, a control device is provided, comprising: a memory for storing computer program instructions; and a processor for executing the computer program instructions to implement the above-described method.

[0027] According to another aspect of this application, an apparatus for reducing processing errors of composite material parts is provided, comprising: a processing device for machining the shape and features of the composite material part to be processed, and drilling process correction holes in the non-functional allowance area of ​​the composite material part to be processed; and a fixing device for fixing the composite material part to be processed, the fixing device including a base, a support assembly, a clamping assembly, a positioning assembly, and a vacuum pipeline, the base being fixed on the processing device, the base having multiple mounting holes, each mounting hole having a vacuum connector, the vacuum connector being connected to a vacuum device via a vacuum pipeline, the support assembly including multiple support members, each support member including a support rod and a profiled support block, the support rod having a first through hole along the axial direction, the first end of the support rod being installed in the mounting hole. The second end of the support rod is detachably connected to the profile support block. The profile support block faces away from the support rod, and the part of it that contacts the composite material part to be processed matches the theoretical profile of the composite material part to be processed. The clamping assembly includes multiple elastic clamping components, each of which is installed on the corresponding profile support block. The elastic clamping component has a second through hole along the axial direction. The first through hole and the second through hole are connected and connected to the vacuum pipeline via a vacuum connector. The positioning assembly is inserted into the pre-drilled process hole of the composite material part to be processed to perform initial positioning of the composite material part to be processed. The measuring device is used to measure the parameters of each pre-drilled process hole and each preset sampling point on the composite material part to be processed. The control device is electrically connected to the measuring device and the processing device.

[0028] According to an embodiment of this application, the computer program instructions in the control device further include, before fixing the composite material part to be processed, using a profile support block matching algorithm to obtain a profile support block for supporting the composite material part to be processed. The profile support block matching algorithm is trained and constructed based on historically stored composite material part profile data and corresponding matching profile support block samples. The output profile support block includes a stored reused profile support block and / or a newly generated custom profile support block.

[0029] Compared with the prior art, the beneficial effects of this application are as follows: The method for reducing machining errors in composite material parts disclosed in this application, while retaining the initial positioning function of pre-drilled process holes, introduces measured data from a large number of adaptive sampling points distributed on the final molding surface of the composite material part. An initial coordinate system is established using the measured data of the pre-drilled process holes. The deviation between the theoretical and measured data of the sampling points is assigned a first weight, and the deviation between the theoretical and measured data of the pre-drilled process holes is assigned a higher second weight. Based on the theoretical and measured data, a weighted best-fit algorithm is used to translate and rotate the established initial coordinate system to obtain the machining coordinate system. This overall correction of the initial coordinate system effectively cuts off the transmission path of the pre-drilled process hole deviation at its source. Assigning higher weights to pre-drilled process holes ensures they maintain high positioning constraints during fitting, guaranteeing the reliable continuation of the initial clamping datum and preventing excessive coordinate system offset. Conversely, assigning lower weights to sampling points, given their large number and coverage of the entire surface, effectively corrects overall coordinate system rotation and translation caused by individual pre-drilled process hole deviations by minimizing the sum of squared overall deviations. This weakens the impact of pre-drilled process hole deviations on the coordinate system. Essentially, it utilizes the spatial distribution information of a large-area, high-precision surface to identify and correct systematic coordinate system rotation and translation caused by individual pre-drilled process hole deviations. This cuts off the transmission path from pre-drilled process hole deviations to machining features at the datum source, reducing cumulative hole-making errors and improving the pass rate and assembly quality of composite material molding.

[0030] This application, by correcting the initial coordinate system, can simultaneously complete the datum compensation of all features to be machined in one go. Furthermore, under the machining coordinate system, within the part's allowance area, process correction holes are re-drilled, physically solidifying the corrected datum onto the part body as a unified datum for subsequent assembly. Therefore, regardless of the number of hole features or continuous mating surfaces on the composite material part to be machined, its machining datum is automatically unified to the optimal coordinate system, eliminating the need for individual feature adjustments. The compensation efficiency is significantly improved compared to the single-feature method, and the consistency of all feature datums is ensured, fundamentally avoiding geometric tolerance discrepancies caused by local compensation. The positional accuracy and surface precision of hundreds of machining features on large-sized parts are thus comprehensively guaranteed.

[0031] This application corrects the initial coordinate system, eliminating the need for rework of pre-drilled process holes and the addition of automated drilling equipment. It only requires embedding surface data acquisition and coordinate system calculation correction steps into the existing process, using machining equipment to drill new process correction holes. It can directly interface with existing CNC machining equipment and high-precision measuring equipment in the workshop, achieving a significant leap in accuracy at extremely low modification costs. It fully covers a large number of work-in-process parts in the industry with completed process hole drilling, adapting to the production of various composite parts in multiple varieties and small to medium batches, covering commonly used processing scenarios in the industry, and boasting an extremely high return on investment. Simultaneously, it avoids the structural damage risks such as composite delamination and tearing that may occur due to secondary drilling, ensuring the structural integrity of the composite material parts to be processed.

[0032] The reference positioning deviation (defined as the maximum value of the coordinate deviation of all sampling points in the corrected coordinate system) of the composite material parts to be processed in this application is significantly reduced from ±0.25mm in the traditional process to about ±0.1mm. The out-of-tolerance rate of machining features is reduced from 15%-20% in the traditional process to less than 10%, reducing the number of parts scrapped due to machining out-of-tolerance caused by pre-drilled process hole deviations and assembly interference in large-sized composite parts.

[0033] Compared with the technology of reconstructing the coordinate system based solely on surface measurement, this application retains the main datum status of the pre-drilled process hole through differentiated weight allocation, avoids excessive deviation of the coordinate system from the original clamping datum, and ensures the continuity of the machining datum and the assembly datum. At the same time, the corrected datum is physically solidified through the process correction hole, which fundamentally solves the problem that the coordinate offset at the software level cannot be transmitted to the subsequent assembly stage, and realizes the consistency of the datum throughout the machining-assembly process. Attached Figure Description

[0034] Figure 1 This is a flowchart illustrating a method for reducing processing errors of composite material parts according to an embodiment of this application.

[0035] Figure 2 This is a block diagram of a system for reducing processing errors of composite material parts according to an embodiment of this application.

[0036] Figure 3 This is a structural block diagram of a control device according to an embodiment of the present application.

[0037] Figure 4 This is a structural diagram of an apparatus for reducing processing errors of composite material parts according to an embodiment of this application.

[0038] Figure 5 for Figure 4 Enlarged view of section A.

[0039] Figure 6 This is a schematic diagram of the structure of a support component according to an embodiment of this application.

[0040] Figure 7 This is a schematic diagram of the structure of a support rod according to an embodiment of this application.

[0041] Figure 8 This is a schematic diagram of the structure of a surface support block according to an embodiment of this application.

[0042] Figure 9 This is an enlarged view of a substrate according to an embodiment of this application.

[0043] Figure 10 This is a deviation distribution diagram between the measured data and the theoretical data of each sampling point before correction in Example 1.

[0044] Figure 11 This is a distribution diagram showing the deviation between the measured data and the theoretical data of each sampling point after modification by the method of this application in Example 1.

[0045] Figure label: Storage module 110, model loading and parsing module 120, setting module 130, acquisition module 140, coordinate system establishment module 150, coordinate system transformation module 160, machining control module 170, memory 210, processor 220, bus 230, device for reducing machining errors of composite material parts 300, machining equipment 310, fixing equipment 320, base 321, mounting hole 3211, support member 322, support rod 3221, first plug 3221a, first connector 3221b, profile support block 3222, profile block 3222a, connecting rod 3222b, second plug 3222c, second connector 3222d, vacuum pipeline 323, positioning component 324, elastic clamping member 325, measuring equipment 330, control equipment 340, machining composite material parts 400. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application. Unless otherwise defined, the technical or scientific terms used herein should have the ordinary meaning understood by those skilled in the art to which this application pertains. The terms "comprising" and similar expressions used herein mean that the element or object preceding the word covers the element or object listed following the word and its equivalents, but does not exclude other elements or objects. Unless otherwise specified, the term "connection" as used herein can refer to a direct connection or an indirect connection, i.e., a connection through an intermediate object.

[0047] The terms "first," "second," and similar words used in this patent application specification and claims do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0048] The core application scenario of the method and system for reducing the processing error of composite material parts in this application is the production and manufacturing of large-size integrated carbon fiber composite material parts in the aerospace field.

[0049] Hereinafter, embodiments of this application will be described with reference to the accompanying drawings.

[0050] Figure 1 This is a flowchart illustrating a method for reducing processing errors of composite material parts according to an embodiment of this application.

[0051] See Figure 1 A method for reducing processing errors of composite material parts according to one embodiment of this application includes: Step S1: Obtain the mathematical model of the composite material part to be processed, analyze the mathematical model, and extract the reference parameters, including the theoretical reference surface and the theoretical data of the pre-drilled process holes. This provides a theoretical basis for subsequent coordinate system establishment, correction, and processing.

[0052] Step S2: Set multiple sampling points on the theoretical reference surface and obtain the theoretical data of the sampling points. Obtain the measured data of all sampling points and pre-drilled process holes after the composite material part to be processed is fixed. Establish the initial coordinate system after the composite material part to be processed is fixed based on the measured data of the pre-drilled process holes.

[0053] Specifically, after fixing the composite material part to be processed on the fixed equipment, the data of the preset sampling points and pre-drilled process holes of the composite material part to be processed are measured using measuring equipment.

[0054] Step S3: Using the pre-drilled process holes as the main reference constraint and the sampling points as the surface correction supplement, the initial coordinate system is corrected to obtain the machining coordinate system based on the theoretical and measured data of all sampling points and all pre-drilled process holes using a weighted best fitting algorithm. The ratio of the first weight corresponding to the sampling point to the second weight corresponding to the pre-drilled process hole is 0.2:1 to 1:1.

[0055] Step S4: Generate CNC machining instructions based on the machining coordinate system. The CNC machining instructions include machining instructions for the shape and features of the composite material part to be machined, and machining instructions for drilling process correction holes in the non-functional allowance area of ​​the composite material part to be machined. The process correction holes are used as the sole positioning reference for subsequent assembly.

[0056] The method for reducing machining errors of composite material parts according to embodiments of this application, while retaining the initial positioning function of pre-drilled process holes, introduces measured data from a large number of adaptive sampling points distributed on the final molding surface of the composite material part. An initial coordinate system is established using the measured data of the pre-drilled process holes. The deviation between the theoretical and measured data of the sampling points is assigned a first weight, and the deviation between the theoretical and measured data of the pre-drilled process holes is assigned a higher second weight. A weighted best-fit algorithm is used to translate and rotate the established initial coordinate system based on the theoretical and measured data to obtain the machining coordinate system. This overall correction of the initial coordinate system cuts off the transmission path of the pre-drilled process hole deviation at its source. Assigning higher weights to pre-drilled process holes ensures they maintain high positioning constraints during fitting, guaranteeing the reliable continuation of the initial clamping datum and preventing excessive coordinate system offset. Conversely, assigning lower weights to sampling points, given their large number and coverage of the entire surface, effectively corrects overall coordinate system rotation and translation caused by individual pre-drilled process hole deviations by minimizing the sum of squared overall deviations. This weakens the impact of pre-drilled process hole deviations on the coordinate system. Essentially, it utilizes the spatial distribution information of a large-area, high-precision surface to identify and correct systematic coordinate system rotation and translation caused by individual pre-drilled process hole deviations. This cuts off the transmission path from pre-drilled process hole deviations to machining features at the datum source, reducing cumulative hole-making errors and improving the pass rate and assembly quality of composite material molding.

[0057] Specifically, the process correction hole is a new process hole drilled in the non-functional allowance area of ​​the composite material part to be processed according to the processing coordinate system, and its position is different from that of the original pre-drilled process hole.

[0058] In some embodiments, the reference parameters further include: theoretical profiles of assembly locations prone to interference and theoretical parameters of the features to be processed.

[0059] The theoretical data for pre-drilled process holes include: the three-dimensional coordinates of the center of the pre-drilled process hole, the axis vector, the hole diameter tolerance, and the position tolerance.

[0060] The theoretical parameters of the features to be processed include: the three-dimensional data model of the feature, tolerance requirements, and machining allowance. Specifically, the features to be processed include the peripheral contour, connecting holes, assembly mating surfaces, and mounting grooves of the composite material part to be processed.

[0061] The measured data of the sampling points are the three-dimensional coordinates of the sampling points, and the measured data of the pre-drilled process holes are the three-dimensional coordinates of the center of the pre-drilled process holes and the axis vector.

[0062] Specifically, the measured data of the sampling points are the three-dimensional coordinates of the sampling points, and the measured data of the pre-drilled process holes are the three-dimensional coordinates of the center of the pre-drilled process holes and the axis vector.

[0063] In some embodiments, the rules for setting sampling points in step S2 are as follows: the number of sampling points is greater than 30; the density of sampling points in the assembly interference area, thickness variation area, curvature variation area and the surrounding area of ​​the composite material part to be processed is greater than that in other areas; when the length of the composite material part to be processed is ≥5m, based on the number of sampling points of not less than 30 corresponding to a length of 5m, the number of sampling points increases by not less than 8 for every 1m increase in length.

[0064] In some embodiments, after setting up multiple sampling points in step S2, the sampling points are further screened. The method for screening the sampling points is as follows: based on the curvature and stiffness distribution of the mathematical model of the composite material part to be processed, the entropy weight method is used to obtain the influence weight of the deviation of each sampling point on the overall fitting residual, and the influence weight is used as the contribution of each sampling point to the coordinate system fitting. Sampling points with a contribution value lower than a preset threshold are removed. The preset threshold is pre-set according to the curvature, stiffness, and accuracy requirements of the composite material part to be processed. This reduces the number of sampling points and shortens the data acquisition time while ensuring the fitting accuracy. It is suitable for rapid processing scenarios of large-size, high-curvature complex parts.

[0065] Specifically, when the preset threshold is 0.01, the number of sampling points can be reduced by 40%-60% and the data acquisition time can be shortened by 50% while ensuring the fitting accuracy.

[0066] In some embodiments, in step S2, before setting up sampling points, a finite element model of the composite material part to be processed is constructed. Based on material properties, vacuum adsorption force distribution, and support position, the deformation distribution of the composite material part under different vacuum adsorption forces is simulated. When setting up sampling points, areas where the simulated deformation exceeds a second set threshold are avoided. Furthermore, when correcting the initial coordinate system using a weighted best-fit algorithm, the first weight is reduced for sampling points in areas where the simulated deformation exceeds a third set threshold. The third set threshold is less than the second set threshold, and both the third and second set thresholds are pre-set based on the material and thickness of the composite material part to be processed. This effectively suppresses the interference of clamping deformation on the accuracy of coordinate system correction and improves the correction accuracy. It is suitable for processing thin-walled, low-rigidity composite material parts.

[0067] For example, the second threshold is set to 0.1 mm and the third threshold is set to 0.05 mm. When setting up sampling points, areas with simulated deformation greater than 0.1 mm are avoided. For sampling points in areas with simulated deformation greater than 0.05 mm, the first weight is reduced by 50%, which can improve the correction accuracy by 15%.

[0068] Specifically, the second and third set thresholds can be adjusted according to the material and thickness of the composite material part to be processed.

[0069] In some embodiments, in step S2, the method for establishing the initial coordinate system is as follows: based on the three-dimensional coordinates of the center of the pre-drilled process hole measured after the composite material part to be processed is fixed, a Cartesian coordinate system is established using the 3-2-1 positioning rule, and this is used as the initial coordinate system.

[0070] Specifically, before establishing the initial coordinate system, the three-dimensional coordinates of the center of the pre-drilled process hole measured by the measuring equipment are first converted into coordinates in the machine tool coordinate system through a transformation relationship. Then, the Cartesian rectangular coordinate system is established using the 3-2-1 positioning rule as the initial coordinate system.

[0071] In some embodiments, in step S3, the method for correcting the initial coordinate system to obtain the machining coordinate system is as follows: obtain the coordinate deviation of the sampling points based on the measured data and theoretical data of the sampling points, and obtain the parameter deviation of the pre-drilled process holes based on the measured data and theoretical data of the pre-drilled process holes.

[0072] The weighted coordinate deviation of each sampling point is obtained by multiplying the coordinate deviation of each sampling point by the first weight, and the weighted deviation of each pre-drilled process hole parameter is obtained by multiplying the parameter deviation of each pre-drilled process hole by the second weight.

[0073] With the goal of minimizing the sum of squared weighted coordinate deviations of sampling points and pre-drilled process hole parameters, the translation and rotation correction parameters of the initial coordinate system are obtained by using the optimal fitting algorithm. The machining coordinate system is then obtained by translating and rotating the initial coordinate system according to the translation and rotation correction parameters.

[0074] Specifically, when obtaining the sampling point coordinate deviation and the pre-drilled process hole parameter deviation, the measured data of the sampling points and the measured data of the pre-drilled process holes are first converted into coordinates in the machine tool coordinate system through a transformation relationship. Then, they are compared with the theoretical data to obtain the sampling point coordinate deviation and the pre-drilled process hole parameter deviation.

[0075] In some embodiments, before optimizing the iterative solution using the optimal fitting algorithm, a random sampling consensus algorithm is applied to identify and remove outlier sampling points. During the iteration of the random sampling consensus algorithm, a temporary fitting surface is constructed based on the current random sampling sample set, and the orthogonal distance from all sampling points to the current temporary fitting surface is calculated. Sampling points whose orthogonal distance exceeds three times the standard deviation of the current iteration residual distribution are marked as potential outliers. It is set that the number of outliers removed in a single iteration does not exceed 5% of the total number of sampling points. If the number of potential outliers exceeds 5%, the potential outliers are sorted in descending order of orthogonal distance, and the top 5% with the largest distance are selected as outlier sampling points. If the number of potential outliers does not exceed 5%, then all potential outliers are outlier sampling points.

[0076] In some embodiments, when using the optimal fitting algorithm to correct the initial coordinate system, the sampling points are first dynamically optimized. The dynamic optimization steps include: after completing the first round of iterative fitting using the optimal fitting algorithm, identifying the deviation regions where the coordinate deviation of the sampling points is greater than a first set threshold, adding sampling points in the deviation regions, and then calling the optimal fitting algorithm again for iterative fitting; repeating the above steps until the coordinate deviation of all sampling points is less than the first set threshold, terminating the iteration, and completing the dynamic optimization of the sampling points. Dynamic optimization of the sampling points can improve the accuracy of coordinate system correction.

[0077] In some embodiments, in step S3, the method for determining the ratio of the first weight and the second weight is as follows: a weight allocation prediction model is trained based on historical processing data. The input features of the weight allocation prediction model include the material, size, molding accuracy, historical sampling point coordinate deviation, and historical pre-drilled process hole parameter deviation of the composite material part. The output is the first weight and the second weight. The material, size, and molding accuracy of the composite material part to be processed are input into the weight allocation prediction model, and the weight allocation prediction model generates the first weight and the second weight of the composite material part to be processed.

[0078] Specifically, when the deviation of the pre-drilled process hole is ≤0.6mm, the weight ratio of the first weight and the second weight is 1.

[0079] In some embodiments, after obtaining the machining coordinate system in step S3, it is also necessary to verify the validity of the machining coordinate system by deviation. The method for verifying the validity of the machining coordinate system by deviation is as follows: Calculate the coordinate deviation of all sampling points and the deviation of pre-drilled process hole parameters based on the machining coordinate system. If the coordinate deviation of all sampling points and the deviation of pre-drilled process hole parameters are within the set tolerance range, the verification is passed and the machining coordinate system is valid. If any of the coordinate deviations of all sampling points and the deviations of pre-drilled process hole parameters exceed the set tolerance, the verification fails. After adding sampling points to the areas where the deviation exceeds the standard, step S3 is executed again to obtain a new machining coordinate system, and the deviation validity of the new machining coordinate system is verified. If the verification is passed, proceed to step S4. If the verification fails, the composite material part to be processed needs to be inspected or a conformity review of the composite material part to be processed needs to be initiated.

[0080] In some embodiments, the optimal fitting algorithm includes: the Levenberg-Marquardt algorithm (LM algorithm), the Gauss-Newton iterative algorithm, the genetic algorithm, and the particle swarm optimization algorithm.

[0081] Specifically, when using the LM algorithm, the termination conditions for iteration are: 1. The deviation of the coordinate system parameters between two adjacent iterations is less than a preset threshold of 0.05mm. 2. The number of iterations reaches a preset upper limit of 50. Iteration stops when either condition is met, and the translation and rotation correction parameters of the initial coordinate system are output after iteration stops.

[0082] Specifically, the method for generating CNC machining instructions in step S4 is as follows: the original CNC machining program is compensated for overall coordinates according to the machining coordinate system to generate the compensated CNC machining toolpath; at the same time, based on the actual axis deviation of the pre-drilled process hole, the toolpath axis of the hole feature to be machined is compensated for angles to ensure that the coincidence of the axis of the feature to be machined with the theoretical design axis meets the requirements.

[0083] Specifically, in step S4, the steps for drilling the process correction hole are as follows: Discard the original pre-drilled process hole position and drill a process correction hole in the lug area of ​​the composite material part to be processed, serving as the sole reference for subsequent assembly. Drilling parameters: Use a carbide drill bit, rotation speed 2500 r / min~3000 r / min, feed rate 0.05 mm / r~0.08 mm / r; Reaming parameters: Use a carbide reamer of the same specification, rotation speed 800 r / min~1000 r / min, feed rate 0.1 mm / r~0.15 mm / r, ensuring hole wall roughness and positional accuracy.

[0084] In some embodiments, the method for reducing the machining error of composite material parts further includes step S5, which involves encrypting and storing the parameters of the machining coordinate system and the process correction holes, and completing the docking assembly at the assembly station based on the parameters of the process correction holes. The corrected coordinate system and the process correction hole parameters are synchronized to the assembly station to achieve full lifecycle control of errors, thereby significantly improving the assembly pass rate.

[0085] In some embodiments, the machining coordinate system is combined with a machining cutting thermal deformation prediction model and a tool wear dynamic compensation model for the composite material part to be machined to obtain thermal deformation compensation and tool wear compensation. When performing shape and feature machining on the composite material part to be machined, and drilling process correction holes, a machining trajectory is generated based on the machining coordinate system, thermal deformation compensation, and the tool wear compensation to complete the machining. A unified compensation command using multi-source error fusion is adopted to further improve the final machining accuracy and eliminate new errors that may arise from cutting thermal deformation, tool wear, and subsequent assembly deviations during machining.

[0086] In some embodiments, the method for reducing the processing error of composite material parts further includes establishing a digital twin model of the composite material part to be processed based on the full-process data of the processing procedure. Actual corrections and deviation data are fed back to the design end, forming a digital twin closed loop of "design-manufacturing-inspection-feedback," continuously optimizing the design tolerance allocation of the part, the surface trimming of the molding die, and the processing parameters, thereby continuously improving the first-pass yield of the part from the source.

[0087] One embodiment of this application also provides a system for reducing processing errors in composite material parts.

[0088] Figure 2 This is a block diagram of a system for reducing processing errors of composite material parts according to an embodiment of this application.

[0089] See Figure 2 The system for reducing the processing error of composite material parts includes: a storage module 110, a model loading and parsing module 120, a setting module 130, an acquisition module 140, a coordinate system establishment module 150, a coordinate system transformation module 160, and a processing control module 170.

[0090] Storage module 110 is used to store mathematical models of composite material parts.

[0091] The model loading and parsing module 120 is used to load the corresponding mathematical model of the composite material part to be processed, and to parse the mathematical model to obtain the reference parameters. The reference parameters include the theoretical reference surface and the theoretical data of the pre-drilled process holes.

[0092] The setting module 130 is used to set multiple sampling points on the theoretical reference surface and obtain the theoretical data of the sampling points.

[0093] The acquisition module 140 is used to acquire measured data from pre-drilled process holes and sampling points.

[0094] The coordinate system establishment module 150 is used to establish an initial coordinate system based on the measured data of the pre-drilled process holes.

[0095] The coordinate system transformation module 160 is used to correct the initial coordinate system by using the pre-drilled process hole as the main reference constraint and the sampling point as the surface correction supplement. Based on the measured data and theoretical data of multiple sampling points and pre-drilled process holes, the weighted best fitting algorithm is used to correct the initial coordinate system to obtain the machining coordinate system.

[0096] The machining control module 170 is used to generate CNC machining instructions according to the machining coordinate system and send the CNC machining instructions to the CNC machining device. The CNC machining instructions include machining instructions for the shape and features of the part and machining instructions for drilling process correction holes in the part's allowance area.

[0097] One embodiment of this application also provides a control device.

[0098] Figure 3 This is a structural block diagram of a control device according to an embodiment of the present application.

[0099] See Figure 3 According to one embodiment of this application, the control device includes a memory 210 and a processor 220. Both the processor 220 and the memory 210 can be connected via a bus 230.

[0100] Processor 220 can perform various actions and processes according to computer program instructions stored in memory 210. Specifically, processor 220 can be an integrated circuit chip with signal processing capabilities. The processor can be a general-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor, and can be based on x86 or ARM architecture.

[0101] Memory 210 stores computer program instructions that, when executed by processor 220, implement the method described above for reducing machining errors in composite material parts. Memory 210 may be volatile memory or non-volatile memory, or may include both. Non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory may be random access memory (RAM), which serves as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct memory bus random access memory (DRRAM). It should be noted that the memory used in the methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0102] One embodiment of this application also provides an apparatus for reducing processing errors in composite material parts.

[0103] Figure 4This is a structural diagram of an apparatus for reducing processing errors of composite material parts according to an embodiment of this application.

[0104] See Figure 4 The device 300 for reducing the processing error of composite material parts includes a processing device 310, a fixing device 320, a measuring device 330 and a control device 340.

[0105] The processing equipment 310 is used to process the shape and features of the composite material part 400 to be processed, and to drill process correction holes in the non-functional allowance area of ​​the composite material part 400 to be processed.

[0106] Specifically, both the pre-drilled process holes and the process correction holes are located in the allowance area of ​​the composite material part to be processed (400).

[0107] Specifically, the processing equipment 310 is a CNC machining device. The CNC machining device can be a five-axis CNC machining center or a three-axis CNC machining center. For example, the CNC machining device includes a machine tool body, a CNC system, a spindle unit, and a tool magazine, with a positioning accuracy ≤0.08mm and a repeatability ≤0.05mm.

[0108] The fixing device 320 is used to fix the composite material part 400 to be processed. The fixing device 320 includes: a base 321, a support assembly, a clamping assembly, a positioning assembly 324, and a vacuum line 323.

[0109] The substrate 321 is fixed on the processing equipment 310, and the substrate 321 is provided with a plurality of mounting holes 3211. Each mounting hole 3211 is provided with a vacuum connector, and each vacuum connector is connected to a vacuum device (not shown in the figure) via a vacuum pipeline 323.

[0110] Figure 6 This is a schematic diagram of the structure of a support component according to an embodiment of this application.

[0111] The support assembly includes multiple support members 322. See also... Figure 6 Each support member 322 includes a support rod 3221 and a profiled support block 3222. The support rod 3221 has a first end and a second end that are disposed opposite to each other, so as to... Figure 6Looking at the direction, the first end of the support rod 3221 is the lower end, and the second end is the upper end. The support rod 3221 has a first through hole along its axial direction. The first end of the support rod 3221 is installed in the mounting hole 3211, and the second end is detachably connected to the profile support block 3222. This allows for the fixing of different composite material parts 400 without needing to remanufacture the entire fixing device 320, only the profile support block 3222 needs to be replaced. Specifically, only the profile support block 3222 needs to be processed using 3D printing equipment (cost 0.05~0.1 million yuan / piece, cycle 2~3 days). Specifically, the profile support block 3222 and the support rod 3221 are connected using a standardized plug method.

[0112] The profile support block 3222 has a second through hole along its axial direction. After the profile support block 3222 is installed on the support rod 3221, the first through hole and the second through hole are connected. The side of the profile support block 3222 facing away from the support rod 3221 is the profile side. The part of the profile side of the profile support block 3222 that contacts the composite material part to be processed matches the theoretical profile of the composite material part to be processed, thereby achieving full-profile surface contact support. The support force is evenly distributed across the entire surface of the part, fundamentally avoiding local stress concentration and elastic deformation. For large-size thin-walled skins with a thickness ≤3mm, the clamping deformation of this application is ≤0.05mm, which is far superior to the existing flexible clamping fixtures with a clamping deformation of 0.1mm~0.3mm. The replaceable profile support blocks and standardized plugs allow for quick-plug connection. Therefore, replacing a set of profile blocks only takes 30 minutes, and the support accuracy can be guaranteed without additional adjustment.

[0113] Specifically, after the first end of the support rod 3221 is installed in the mounting hole 3211, the passage formed by the first through hole and the second through hole is connected to the vacuum pipeline via a vacuum connector. The vacuum seal is integrated inside the support rod and the profile support block. When the support rod and the profile support block are connected, the vacuum circuit docking is automatically completed, eliminating the need for a separate connection of the vacuum pipeline and further simplifying the clamping process.

[0114] Figure 7 This is a schematic diagram of the structure of a support rod according to an embodiment of this application.

[0115] See Figure 7 The first end of the support rod 3221 is provided with a first plug 3221a that matches the mounting hole 3211 and a first connector 3221b that connects to the vacuum connector. The cross-section of the outer contour of the first connector 3221b is non-circular, for example, the cross-section of the outer contour of the first connector 3221b is rectangular, square, etc., to prevent the support rod 3221 from rotating relative to the mounting hole 3211.

[0116] Figure 8 This is a schematic diagram of the structure of a surface support block according to an embodiment of this application.

[0117] See Figure 8 The profile support block 3222 includes: a profile block 3222a, a connecting rod 3222b, a second plug 3222c, and a second connector 3222d. The profile block 3222a is fixedly installed on the upper end of the connecting rod 3222b, the second plug 3222c is fixedly installed on the lower end of the connecting rod 3222b, the upper end of the second plug 3222c is installed on the lower end of the connecting rod 3222b, and the second connector 3222d is installed on the lower end of the second plug 3222c. The length of the connecting rod 3222b is determined according to the composite material part 400 to be processed, and the length is sufficient to ensure that the profile block 3222a and the corresponding position of the composite material part 400 to be processed are in close contact.

[0118] Specifically, some of the profile blocks 3222a can be flexible support blocks. When the profile of the composite material part 400 to be processed changes little, they can elastically deform according to the profile of the composite material part 400 to be processed, so that the profile blocks 3222a conform to the profile of the composite material part 400 to be processed. This reduces the number of profile blocks 3222a that need to be replaced and saves replacement time. Specifically, the proportion of profile blocks 3222a that are flexible support blocks does not exceed 1 / 3 of the total number of profile support blocks 3222, so as to avoid the fixed position of the composite material part 400 to be processed shifting due to insufficient rigid support.

[0119] The clamping assembly includes multiple elastic clamping elements 325, each of which is mounted on a corresponding profile support block 3222.

[0120] Specifically, the elastic clamping element 325 can be a vacuum suction cup communicating with the second through hole or an O-ring sealing ring surrounding the opening of the second through hole. The sealing pressure of the elastic clamping element 325 is ≥-0.09MPa, ensuring that the elastic clamping element 325 firmly adheres to the composite material part 400 to be processed without leakage.

[0121] Specifically, see Figure 6 and Figure 8 The profile support block 3222 has a mounting groove on the side facing away from the support rod 3221. The elastic clamping member 325 is installed in the mounting groove. The design of the mounting groove and the elastic clamping member 325 makes it possible for the elastic clamping member 325 to smoothly transition with the side of the profile support block 3222 facing away from the support rod 3221 when the vacuum equipment is evacuated and the elastic clamping member 325 is deformed under pressure. There is no height difference, so the composite material part 400 to be processed can be tightly adsorbed onto the profile support block 3222, so that the support member 322 can provide good support for the composite material part 400 to be processed.

[0122] The fixed equipment features a modular, replaceable design for multiple support components. The profile support blocks are customized to the part's profile and use universal plugs for detachable connection, ensuring support accuracy without additional adjustments. When changing to different models of parts to be processed, only the profile support blocks need to be replaced, eliminating the need to remanufacture the entire machining fixture. Therefore, this fixed equipment allows a single tooling base to be adapted to various composite material parts with different configurations, such as fuselage skin, wing panels, and honeycomb sandwich panels, increasing tooling reuse rate by over 80%. Compared to traditional processes that require customized tooling for each type of part, the fixed equipment in this application significantly reduces tooling design and manufacturing cycles and material costs, lowering manufacturing costs by over 60% and shortening preparation time by over 80%. It is particularly suitable for the production of diverse, small-to-medium batch aerospace composite parts, giving the high-precision machining system extremely high flexibility and economy.

[0123] The profile blocks are pre-machined and can be quickly and easily connected to the tooling base via standardized plugs. Replacing a set of profile blocks takes only 30 minutes, and the support accuracy is guaranteed without additional adjustments. At the same time, the vacuum seal is integrated inside the plug slot, and the vacuum circuit is automatically connected when the plug is connected, eliminating the need for a separate vacuum pipeline and further simplifying the clamping process.

[0124] The fixed equipment has no moving parts, resulting in a simple, reliable structure and an extremely low failure rate. The only vulnerable parts are the O-ring and the upper profile block, which are low-cost and easy to replace. The tooling base can be reused for a long time, with a service life of over 10 years, reducing total life-cycle maintenance costs by more than 70%.

[0125] The positioning component 324 is inserted into the pre-drilled process hole of the composite material part 400 to perform initial positioning of the composite material part 400.

[0126] Specifically, the positioning component 324 consists of multiple positioning pins. The allowance area of ​​the composite material part 400 to be processed is provided with drilling process holes. Positioning pins are inserted into the drilling process holes to initially position the composite material part 400 to be processed with the fixing device 320.

[0127] The measuring device 330 is used to measure the parameters of each pre-drilled process hole and each preset sampling point on the composite material part 400 to be processed.

[0128] Specifically, the measuring device 330 has a measuring accuracy of not less than 0.05 mm. For example, it can be any one of a laser tracker, a 3D structured light scanner, or a portable coordinate measuring machine.

[0129] Specifically, the parameters collected by the measuring device 330 include the three-dimensional coordinates of the sampling point, the center coordinates of the pre-drilled process hole, the axis vector, the hole diameter tolerance, and the position tolerance.

[0130] Specifically, the calibration of the measurement coordinate system of the measuring device 330 and the machine tool coordinate system of the processing device 310 adopts the target ball method. Specifically, the steps for calibrating the measurement coordinate system and the machine tool coordinate system using the target ball method are as follows: First, at least six non-collinear standard target balls are evenly distributed on the upper surface of the substrate 321. The measuring device 330 is used to collect the three-dimensional coordinates of all target balls to establish the measurement coordinate system. Then, the spindle probe of the processing device 310 is used to collect the coordinates of the same target balls to establish the machine tool coordinate system. The transformation relationship between the two coordinate systems (transformation matrix) is solved through the coordinate transformation matrix to complete the calibration, with a calibration accuracy ≤ 0.02 mm. When establishing the initial coordinate system of the composite material part 400 after fixing based on the measured data of the pre-drilled process hole, the three-dimensional coordinates of the center of the pre-drilled process hole measured by the measuring device 330 are first converted to coordinates in the machine tool coordinate system through a transformation relationship. Then, the 3-2-1 positioning rule is used to establish a Cartesian rectangular coordinate system as the initial coordinate system.

[0131] The control device 340 is electrically connected to the machining device 310 and the measuring device 330. After receiving the parameters of the sampling points and pre-drilled process holes measured by the measuring device 330, the control device 340 calculates the CNC machining instructions according to the above-mentioned method for reducing the machining error of composite material parts, and sends the CNC machining instructions to the machining device 310.

[0132] Specifically, the measuring device 330 is bidirectionally connected to the control device 340 via a local area network (LAN) to transmit the collected measured data in real time. The machining device 310 is also bidirectionally connected to the control device 340 via the LAN. The machining device 310 receives CNC machining commands from the control device 340 and simultaneously feeds back the machine tool's operating status and actual machining data to the control device 340. After receiving the CNC machining commands from the control device 340, the control device 340 executes the machining operation on the composite material part to be processed, completing the precise machining of all the features to be processed.

[0133] Specifically, the measuring equipment includes laser trackers, blue light shape scanners, etc.

[0134] In some embodiments, the computer program instructions in the control device 340 further include, before fixing the composite material part to be processed, using a profile support block matching algorithm to obtain profile support blocks for supporting the composite material part to be processed. The profile support block matching algorithm is constructed based on historically stored composite material part profile data and corresponding adapted profile support blocks. The profile support blocks output by the profile support block matching algorithm include stored reused profile support blocks and / or newly generated customized profile support blocks. This shortens the changeover preparation time and reduces the complexity of tooling management. Specifically, the profile support block matching algorithm outputs the profile of the profile side of the profile support block.

[0135] In some embodiments, before assembling the processed composite material parts, the actual surface data of the processed composite material parts and the reference feature data of the docking structure are collected by measuring equipment. The assembly coordinate system is corrected according to the above-mentioned method for reducing the processing error of composite material parts, so as to guide the processed composite material parts to complete the precise fit with the docking structure and completely eliminate the cumulative error of the entire process from processing to assembly.

[0136] Specifically, if the composite material part to be processed is not removed from the fixed equipment after processing and is directly assembled, the measuring equipment only needs to measure the reference feature data of the docking structure, and does not need to repeatedly measure the actual surface data of the processed composite material part.

[0137] The working process of the device 300 for reducing machining errors of composite material parts is as follows: Step 1: The control device 340 acquires the mathematical model of the composite material part to be processed, analyzes the mathematical model, and extracts the reference parameters.

[0138] Step 2: Install the composite material part to be processed on the fixing device 320 and fix it through the pre-drilled process holes and positioning pins on the composite material part to be processed.

[0139] Step 3: The control device 340 pre-sets multiple sampling points on the theoretical reference surface and obtains the theoretical data of the sampling points. The measuring device 330 measures the measured data of each sampling point and each pre-drilled process hole of the composite material part to be processed, and sends the measured data to the control device 340. The control device 340 establishes an initial coordinate system for the fixed composite material part based on the measured data of the pre-drilled process holes. Then, it sets a first weight value and a second weight value, and uses a weighted best fitting algorithm to correct the initial coordinate system to obtain the processing coordinate system. Based on the processing coordinate system, it generates CNC machining instructions for processing the composite material part to be processed and drilling the process correction holes, and sends the CNC machining instructions to the processing device 310.

[0140] Step 4: The processing equipment 310 re-processes the corrected hole according to the received CNC machining instructions and processes the features to be processed.

[0141] Step 5: The control device 340 stores the parameters of the machining coordinate system and the process correction hole. The assembly station completes the docking assembly based on the process correction hole parameters.

[0142] Example 1 Single-skin laminate component processing The material for the single-curved skin laminate is carbon fiber epoxy resin unidirectional tape prepreg. The part has external dimensions of 8500mm × 1600mm, a single-curved structure, and exhibits thickness variations due to layer loss. Four φ10H7 positioning process holes were manually pre-drilled using a drilling template; the maximum positional deviation of these pre-drilled holes was measured to be 0.22mm. Processing features include a skin edge profile tolerance of ±1mm, 128 φ6.4mm assembly connection holes, and a mating surface tolerance of ±0.2mm for the upper and lower end frames.

[0143] The steps for processing single-curve skin laminate parts are as follows: Step 1: Control device 340 acquires the mathematical model of the single-curved skin laminate part, analyzes the mathematical model, and extracts the three-dimensional coordinates of the center of the four pre-drilled process holes, the axis vector, the hole diameter tolerance, the position tolerance, the theoretical surface of the lost layer area, the skin cutting edge contour, the 128 connecting holes, the three-dimensional digital model of the upper and lower mating surfaces waiting to be processed, the tolerance requirements, and the processing allowance.

[0144] Step 2: Hoist the single-curved skin laminate component onto the fixed equipment 320, discard the holes with large deviations, and complete the rough positioning by matching the three positioning pins with the pre-drilled process holes (clearance fit H7 / h6).

[0145] Step 3: Using a laser tracker, preset sampling points are set on the surface of the single-curved skin laminate component. The sampling points are densified in the assembly area, areas with thickness variations, and areas with curvature variations, totaling 90 sampling points (with at least 8 sampling points per meter increment). The laser tracker sequentially collects the actual three-dimensional coordinates of each sampling point, and simultaneously collects the actual coordinates of the three sections of the four pre-drilled process holes: the hole opening, the hole center, and the hole bottom. The three-dimensional coordinates of the hole center and the axis vector are calculated, and the data is transmitted to the control device 340 in real time.

[0146] Step 4: The control device 340 selects the three actual hole positions of the pre-drilled process holes with the smallest deviations and establishes a Cartesian coordinate system, i.e., the initial coordinate system, using the 3-2-1 rule. The first weight is set to 1, and the second weight is also set to 1 (since the maximum positional deviation of the pre-drilled process holes is 0.22mm, which is less than 0.6mm, the weight ratio of the first and second weights is set to 1:1). The control device 340 uses the Levenberg-Marquardt algorithm to solve for the translation and rotation correction parameters of the initial coordinate system. The iteration stops when the deviation between two adjacent parameters reaches 0.003mm (less than the threshold of 0.05mm) after the 15th iteration, thus obtaining the translation and rotation correction parameters of the initial coordinate system. The initial coordinate system is then corrected based on these parameters to obtain the machining coordinate system. The maximum deviation of all sampling points is verified to be 0.038mm, and since all sampling point deviations are within the preset range, the coordinate system is confirmed to be valid.

[0147] Step 5: The control device 340 generates CNC machining instructions for machining the single-curved skin laminate part and for machining the process correction holes according to the machining coordinate system and sends them to the machining device 310. The machining device 310 drills process correction holes (φ12H7, drilling: carbide drill bit, speed 2800r / min, feed rate 0.06mm / r; reaming: carbide reamer, speed 900r / min, feed rate 0.12mm / r) in the allowance area of ​​the single-curved skin laminate part according to the CNC machining instructions. The corrected reference is physically solidified on the part as the positioning reference for subsequent frame assembly. Then, the machining of all the shapes and features of the single-curved skin laminate part is completed.

[0148] Step 6: Control device 340 encrypts and stores the parameters of the machining coordinate system and process correction holes, and synchronizes them to the MES system (Manufacturing Execution System) of the assembly station. The assembly station uses the parameters of the process correction holes as a reference to complete the precise docking of the single-curved skin laminate part and the frame segment.

[0149] Figure 10 This is a deviation distribution diagram between the measured data and theoretical data of each sampling point before correction in Example 1; Figure 11 This is a deviation distribution diagram between the measured data and the theoretical data of each sampling point after modification by the method of this application in Example 1. Green indicates that the deviation is within the tolerance range, blue indicates that the deviation is within the tolerance but the margin is insufficient, and red indicates that the deviation exceeds the tolerance.

[0150] like Figure 10 , Figure 11 As shown, there are many data points exceeding the tolerance in the deviation between the measured data and the theoretical data at each sampling point. However, after coordinate system transformation, there are no data points exceeding the tolerance in the deviation between the measured data and the theoretical data at each sampling point.

[0151] Comparative Example 1 Single-skin laminate component processing The single-curved skin laminate component is from the same batch as that in Example 1.

[0152] The single-curved skin laminate component is hoisted onto the fixed device 320. Holes with significant deviations are discarded, and rough positioning is achieved by using three locating pins in conjunction with pre-drilled process holes (clearance fit H7 / h6). Based on the actual positions of the pre-drilled process holes, a Cartesian coordinate system is established using the 3-2-1 rule. This coordinate system is used as the machining coordinate system. The control device 340 generates CNC machining instructions for the single-curved skin laminate component according to this coordinate system and sends them to the machining device 310. The machining device 310 completes the machining of all features of the single-curved skin laminate component according to the received CNC machining instructions. Subsequent assembly still uses the pre-drilled process holes as the sole docking reference to complete the segment assembly.

[0153] Table 1 shows the following parameters for Example 1 and Comparative Example 1: reference positioning deviation (pre-drilled process hole deviation), maximum deviation of assembly hole position, maximum deviation of skin edge profile, maximum deviation of skin edge profile, first pass rate of machining, first pass rate of assembly, and single-piece production cycle.

[0154] Table 1

[0155] According to the data in Table 1, the maximum deviations in datum positioning (pre-drilled process hole deviation), assembly hole position, skin edge contour, and skin edge contour in Example 1 are all significantly lower than those in Comparative Example 1. The first-pass yield and first-pass yield of machining and assembly in Example 1 are significantly higher than those in Comparative Example 1. The single-piece production cycle in Example 1 is significantly shorter than that in Comparative Example 1. This indicates that the method for reducing machining errors in composite material parts proposed in this application can reduce machining deviations caused by pre-drilled process hole deviations and part scrap due to assembly interference in large-size composite parts, and can improve production efficiency.

[0156] Example 2 Processing of Hypercurvature Stiffened Panels The double-curvature stiffened panel is made of carbon fiber epoxy resin unidirectional tape prepreg, integrally co-cured and molded. The panel skin is 3mm thick and has 15 azimuth cap-shaped stringers, each 35mm high. The panel dimensions are 12000mm × 2200mm, with a double-curvature structure. Twelve φ12H7 positioning holes were manually drilled, with a maximum positional deviation of 0.8mm, exceeding the standard internal control. Processing features include a panel edge profile tolerance of ±0.5mm, 216 assembly connection holes, and front and rear edge mating surfaces with a positional tolerance of ±0.2mm.

[0157] The steps for processing hyperbolic stiffened panel parts are as follows: Step 1: The control device 340 acquires the mathematical model of the double-curvature stiffened panel component, analyzes the mathematical model, and extracts the three-dimensional coordinates of the center of the 12 pre-drilled process holes, the axis vector, the hole diameter tolerance, and the positional tolerance; the three-dimensional data model, tolerance requirements, and machining allowance of the features to be processed; the theoretical profiles of the stringer cap waist and cap top areas; and the theoretical profiles of the panel curvature variation locations. (Since the double-curvature stiffened panel component is formed entirely using a female mold, the relative positions between the stringers are relatively fixed, but affected by the panel curing springback, the stringer cap waist and cap top areas are used as the theoretical profiles of the assembly interference locations, and the theoretical profiles of the panel curvature variation locations also need to be extracted simultaneously.)

[0158] Step 2: Hoist the double-curvature stiffened wall panel component onto the fixed equipment 320, discard the holes with large deviations, and complete the rough positioning by using 3 positioning pins to cooperate with the pre-drilled process holes (clearance fit H7 / h6).

[0159] Step 3: Using a laser tracker, pre-sampling points are preset on the surface of the double-curvature stiffened panel component. 170 sampling points are preset in the assembly interference area, the stiffener thickness variation area, and the area with gentle curvature changes (sampling points increase by at least 8 per meter). Based on the curvature and stiffness distribution of the mathematical model of the double-curvature stiffened panel component, the entropy weight method is used to obtain the influence weight of each sampling point deviation on the overall fitting residual. This influence weight is used as the contribution of each sampling point to the coordinate system fitting. Sampling points with contribution values ​​below a preset threshold are eliminated, resulting in 72 selected sampling points. The laser tracker sequentially collects the actual three-dimensional coordinates of the 72 sampling points, and simultaneously collects the actual coordinates of the three sections of the 12 pre-drilled process holes: the hole opening, the hole center, and the hole bottom. The three-dimensional coordinates of the hole center and the axis vector are calculated, and the data is transmitted to the control device 340 in real time.

[0160] Step 4: Select the three pre-drilled process holes with the smallest deviations. Based on the actual hole positions of these three pre-drilled process holes, the control device 340 establishes a Cartesian coordinate system, i.e., the initial coordinate system, using the 3-2-1 rule. The first weight is set to 1, and the second weight to 2. (Due to the large size of the double-curvature stiffened panel and the 0.8mm deviation of the pre-drilled process holes, the ratio of the first and second weights is set to 1:2 to strengthen the constraint of the pre-drilled process holes on the overall coordinate system and prevent excessive deviation from the initial clamping state). The control device 340 uses the Levenberg-Marquardt algorithm to solve for the translation and rotation correction parameters of the initial coordinate system. The iteration terminates when the deviation between two adjacent parameters reaches 0.004mm (less than the threshold of 0.05mm) on the 18th iteration, obtaining the translation and rotation correction parameters of the initial coordinate system. The initial coordinate system is then corrected based on these parameters to obtain the machining coordinate system. The maximum deviation of all sampling points was verified to be 0.42mm (this deviation is located in the area of ​​large rebound after curing at the top of the stringer cap, which does not affect the overall coordinate system fitting accuracy). The stringer shape does not interfere with the assembly parts, and the positional deviation of other pre-drilled process holes is within the preset range. The coordinate system is confirmed to be effective, and the 0.8mm deviation of the pre-drilled process holes is effectively isolated.

[0161] Step 5: The control device 340 generates CNC machining instructions for machining the double-curvature stiffened panel part and for machining the process correction holes according to the machining coordinate system and sends them to the machining device 310. The machining device 310 drills process correction holes (φ12H7, drilling: carbide drill bit, speed 2800r / min, feed rate 0.06mm / r; reaming: carbide reamer, speed 900r / min, feed rate 0.12mm / r) in the allowance area of ​​the double-curvature stiffened panel part according to the CNC machining instructions, and physically solidifies the corrected reference onto the part; then completes the machining of all the shapes and features of the double-curvature stiffened panel part.

[0162] Step 6: Control device 340 encrypts and stores the parameters of the machining coordinate system and process correction holes, and synchronizes them to the MES (Manufacturing Execution System) at the assembly station. Simultaneously, it synchronizes the three-dimensional coordinate points of the double-curvature stiffened panel surface under the machining coordinate system to the digital assembly twin system, achieving virtual pre-assembly verification. The assembly station completes the assembly of the double-curvature stiffened panel based on the parameters of the process correction holes.

[0163] Implementation results: Before the correction, the maximum deviation of the pre-drilled process holes was 0.8mm. After the correction, the positional deviation of all features of the holes based on the process correction was ≤±0.17mm, meeting the ±0.2mm requirement. No rework was required for the out-of-tolerance pre-drilled process holes. The production cycle of a single piece was shortened by 35%. The processing accuracy fluctuation of 8 wall panels in the same batch was ≤0.25mm, and the batch yield was 95%.

[0164] Example 3 Machining of underwing fairing honeycomb sandwich structure The underwing fairing honeycomb sandwich structure has a panel made of carbon fiber epoxy resin prepreg and a core material of aramid honeycomb (20mm high), integrally co-cured. The component measures 1400mm × 800mm and has a single-curved leading edge structure. Three φ8H7 positioning holes are manually drilled, with a maximum positional deviation of 0.21mm. Eighty-six φ4.8mm riveting holes and upper and lower mating surfaces of the leading edge are to be machined, with a positional tolerance of ±0.2mm. Four maintenance openings are also included, with a contour tolerance of ±0.5mm.

[0165] The steps for processing the honeycomb sandwich structure of the underwing fairing are as follows: Step 1: Control device 340 acquires the mathematical model of the honeycomb sandwich structure of the underwing fairing, analyzes the mathematical model, extracts the mating surface of the leading edge outer skin and the stabilizer box section as the theoretical surface of the assembly interference position, and acquires the center three-dimensional coordinates, axis vector, hole diameter tolerance and position tolerance of the three pre-drilled process holes, as well as the three-dimensional data model, tolerance requirements and machining allowance of the 86 riveting holes and 4 maintenance openings.

[0166] Step 2: Hoist the underwing fairing honeycomb sandwich structure onto the fixed equipment 320, discard the holes with large deviations, and complete the rough positioning by matching the two positioning pins with the pre-drilled process holes (clearance fit H7 / h6).

[0167] Step 3: Preset sampling points. Preset 50 sampling points in the assembly interference area, thickness variation area, and area with gentle curvature changes (incrementing by at least 8 sampling points per meter). Use a blue light profile scanner to scan the overall outline of the underwing fairing honeycomb sandwich structure to obtain the actual three-dimensional coordinates of the 50 sampling points. Simultaneously, collect the actual coordinates of the three sections of the three pre-drilled process holes: the opening, middle, and bottom of the holes. Calculate the three-dimensional coordinates of the hole center and the axis vector. Transmit the data to the control device 340 in real time.

[0168] Step 4: Select the two pre-drilled process holes with the smallest deviations. The control device 340 establishes an initial coordinate system based on the actual hole positions of these two pre-drilled process holes. A first weight is set to 1, and a second weight to 3 (because the size of the underwing fairing honeycomb sandwich structure is small, and the deviation of the pre-drilled process holes is less than 0.3mm, the ratio of the first weight to the second weight is set to 1:3 to balance the constraints of the pre-drilled process holes and the surface correction). The control device 340 uses the Levenberg-Marquardt algorithm to solve for the translation and rotation correction parameters of the initial coordinate system. The iteration terminates when the deviation between two adjacent parameters reaches 0.004mm (less than the threshold of 0.05mm) on the 8th iteration, obtaining the translation and rotation correction parameters of the initial coordinate system. The initial coordinate system is then corrected based on these parameters to obtain the machining coordinate system. Verification confirms the coordinate system's validity by checking that the maximum deviation of all sampling points is 0.28mm.

[0169] Step 5: The control device 340 generates CNC machining instructions for machining the honeycomb sandwich structure of the underwing fairing and for machining the process correction holes according to the machining coordinate system and sends them to the machining device 310. According to the CNC machining instructions, the machining device 310 drills process correction holes (φ10H7, using carbide drill bit, rotation speed 3000r / min, feed rate 0.05mm / r, reamer finishing) in the allowance area of ​​the honeycomb sandwich structure of the underwing fairing, and physically solidifies the corrected reference onto the part; then completes the machining of all the shape and features of the honeycomb sandwich structure of the underwing fairing, and then uses a special tool for sandwich structure to complete the drilling and reaming of all riveting holes to avoid splitting of the honeycomb core.

[0170] Step 6: Control device 340 encrypts and stores the parameters of the machining coordinate system and process correction holes, and synchronizes them to the MES system (Manufacturing Execution System) of the assembly station as the positioning reference for the assembly of the leading edge and the stabilizer box segment.

[0171] Implementation results: Before the correction, the maximum deviation of the pre-drilled process holes was 0.21mm. After the correction, the positional deviation of all features was ≤±0.15mm, meeting the design tolerance requirements. There was no honeycomb core splitting or panel delamination in the maintenance openings. The first-pass yield of assembly increased from 65% in the traditional process to over 90%.

[0172] The above description is merely a specific implementation of the embodiments of this application, but the protection scope of the embodiments of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the embodiments of this application should be covered within the protection scope of the embodiments of this application. Therefore, the protection scope of the embodiments of this application should be determined by the protection scope of the appended claims.

Claims

1. A method for reducing machining errors in composite material parts, characterized in that, Includes the following steps: Step S1: Obtain the mathematical model of the composite material part to be processed, analyze the mathematical model, and extract the reference parameters, which include the theoretical reference surface and the theoretical data of the pre-drilled process holes; Step S2: Set multiple sampling points on the theoretical reference surface and obtain theoretical data of the sampling points; obtain measured data of all the sampling points and pre-drilled process holes after the composite material part to be processed is fixed; and establish the initial coordinate system of the composite material part to be processed after it is fixed based on the measured data of the pre-drilled process holes. Step S3: Using the pre-drilled process holes as the main reference constraint and the sampling points as the surface correction supplement, the initial coordinate system is corrected using a weighted best fitting algorithm based on the theoretical and measured data of all the sampling points and all the pre-drilled process holes to obtain the machining coordinate system. The ratio of the first weight corresponding to the sampling point to the second weight corresponding to the pre-drilled process hole is 0.2:1 to 1:

1. Step S4: Generate CNC machining instructions based on the machining coordinate system. The CNC machining instructions include: machining instructions for the shape and features of the composite material part to be machined, and machining instructions for drilling process correction holes in the non-functional allowance area of ​​the composite material part to be machined, and use the process correction holes as the sole positioning reference for subsequent assembly.

2. The method for reducing machining errors of composite material parts according to claim 1, characterized in that, The reference parameters also include: theoretical profiles of assembly locations prone to interference and theoretical parameters of features to be processed. The theoretical data for the pre-drilled process hole includes: the three-dimensional coordinates of the center of the pre-drilled process hole, the axis vector, the hole diameter tolerance, and the positional tolerance. The theoretical parameters of the feature to be processed include: the three-dimensional data model of the feature to be processed, tolerance requirements, and machining allowance. The measured data of the sampling point is the three-dimensional coordinate of the sampling point, and the measured data of the pre-drilled process hole is the three-dimensional coordinate of the center and the axis vector of the pre-drilled process hole.

3. The method for reducing machining errors of composite material parts according to claim 1, characterized in that, In step S2, the rules for setting the sampling points are as follows: the number of sampling points is greater than 30; the density of sampling points in the assembly interference area, thickness variation area, curvature variation area and surrounding area of ​​the composite material part to be processed is greater than that in other areas; when the length of the composite material part to be processed is ≥5m, the number of sampling points is based on no less than 30 sampling points corresponding to a length of 5m, and the number of sampling points increases by no less than 8 for every 1m increase in length.

4. The method for reducing machining errors of composite material parts according to claim 3, characterized in that, After setting up multiple sampling points, the sampling points are further screened. The method for screening the sampling points is as follows: based on the curvature distribution and stiffness distribution of the mathematical model of the composite material part to be processed, the entropy weight method is used to obtain the influence weight of the deviation of each sampling point on the overall fitting residual, and the influence weight is used as the contribution of each sampling point to the coordinate system fitting. Sampling points with contribution values ​​lower than a preset threshold are removed. The preset threshold is pre-set according to the curvature, stiffness and accuracy requirements of the composite material part to be processed.

5. The method for reducing machining errors of composite material parts according to claim 3, characterized in that, Before setting up the sampling points, a finite element model of the composite material part to be processed is constructed. Based on the material properties, vacuum adsorption force distribution, and support position, the deformation distribution of the composite material part to be processed under different vacuum adsorption forces is simulated. When setting up the sampling points, areas where the simulated deformation is greater than the second set threshold are avoided. When the initial coordinate system is corrected using the weighted best fitting algorithm, the first weight of the sampling points in areas where the simulated deformation is greater than the third set threshold is reduced. The third set threshold is less than the second set threshold. Both the third set threshold and the second set threshold are preset according to the material and thickness of the composite material part to be processed.

6. The method for reducing machining errors of composite material parts according to claim 1, characterized in that, In step S2, the method for establishing the initial coordinate system is as follows: based on the three-dimensional coordinates of the center of the pre-drilled process hole measured after the composite material part to be processed is fixed, a Cartesian coordinate system is established using the 3-2-1 positioning rule, and this is used as the initial coordinate system.

7. The method for reducing machining errors of composite material parts according to claim 1, characterized in that, In step S3, the method for correcting the initial coordinate system using a weighted best-fit algorithm to obtain the machining coordinate system is as follows: The coordinate deviation of the sampling points is obtained based on the measured data and theoretical data of the sampling points. The parameter deviation of the pre-drilled process holes is obtained based on the measured data and theoretical data of the pre-drilled process holes. Multiply the coordinate deviation of each sampling point by the first weight to obtain the weighted coordinate deviation of the sampling point, and multiply the parameter deviation of each pre-drilled process hole by the second weight to obtain the weighted deviation of the pre-drilled process hole parameter. The optimization objective is to minimize the sum of the squares of the weighted coordinate deviations of all the sampling points and the weighted deviations of the pre-drilled process hole parameters. An optimal fitting algorithm is used to iteratively solve the problem to obtain the translation and rotation correction parameters of the initial coordinate system. The initial coordinate system is then translated and rotated according to the translation and rotation correction parameters to obtain the machining coordinate system.

8. The method for reducing machining errors of composite material parts according to claim 7, characterized in that, When the initial coordinate system is corrected using the optimal fitting algorithm, the sampling points are first dynamically optimized. The dynamic optimization steps include: after completing the first round of iterative fitting using the optimal fitting algorithm, identifying the deviation region where the coordinate deviation of the sampling points is greater than a first set threshold, adding sampling points in the deviation region, and then calling the optimal fitting algorithm again to solve the problem; repeating the above steps until the coordinate deviation of all sampling points is less than the first set threshold, terminating the iteration, and completing the dynamic optimization of the sampling points.

9. The method for reducing machining errors of composite material parts according to claim 7, characterized in that, Before iteratively solving the optimal fitting algorithm, a random sampling consensus algorithm is applied to identify and remove outlier sampling points. During the iteration of the random sampling consensus algorithm, a temporary fitting surface is constructed based on the current random sampling sample set, and the orthogonal distance from all sampling points to the current temporary fitting surface is calculated. Sampling points whose orthogonal distance exceeds three times the standard deviation of the current iteration residual distribution are marked as potential outliers. The number of outliers removed in a single iteration is set not to exceed 5% of the total number of sampling points. If the number of potential outliers exceeds 5%, the potential outliers are sorted in descending order of orthogonal distance, and the top 5% with the largest distance are selected as outlier sampling points. If the number of potential outliers does not exceed 5%, then all potential outliers are outlier sampling points.

10. The method for reducing machining errors of composite material parts according to claim 7, characterized in that, The optimal fitting algorithm includes the Levenberg-Marquardt algorithm, the Gauss-Newton iterative algorithm, the genetic algorithm, and the particle swarm optimization algorithm.

11. The method for reducing machining errors of composite material parts according to claim 1, characterized in that, In step S3, the method for determining the ratio of the first weight and the second weight is as follows: a weight allocation prediction model is trained based on historical processing data. The input features of the weight allocation prediction model include the material, size, molding accuracy, historical sampling point coordinate deviation, and historical pre-drilled process hole parameter deviation of the composite material part. The output is the first weight and the second weight. The material, size, and molding accuracy of the composite material part to be processed are input into the weight allocation prediction model, and the weight allocation prediction model generates the first weight and the second weight of the composite material part to be processed.

12. The method for reducing machining errors of composite material parts according to claim 1, characterized in that, In step S3, after obtaining the machining coordinate system, it is also necessary to verify the deviation validity of the machining coordinate system. The method for verifying the deviation validity of the machining coordinate system is as follows: The coordinate deviations of all sampling points and the deviations of pre-drilled process holes are calculated based on the machining coordinate system. If the coordinate deviations of all sampling points and the deviations of pre-drilled process holes are within the set tolerance range, the machining coordinate system is verified and is valid. If any of the coordinate deviations of all sampling points and the deviations of pre-drilled process holes exceed the set tolerance, the verification fails. After adding sampling points to the areas where the deviations exceed the standard, step S3 is re-executed to obtain a new machining coordinate system, and the validity of the deviations of the new machining coordinate system is verified. If the verification passes, step S4 is executed. If the verification fails, the composite material part to be processed needs to be inspected or a qualification review of the composite material part to be processed needs to be initiated.

13. The method for reducing machining errors of composite material parts according to claim 1, characterized in that, It also includes step S5, which involves encrypting and storing the parameters of the machining coordinate system and the process correction hole, and then using the parameters of the process correction hole as a reference to complete the docking assembly at the assembly station.

14. The method for reducing machining errors of composite material parts according to claim 1, characterized in that, The machining coordinate system is combined with the machining cutting thermal deformation prediction model and the tool wear dynamic compensation model of the composite material part to be processed to obtain the thermal deformation compensation amount and the tool wear compensation amount. When machining the shape and features of the composite material part to be processed, and drilling the process correction hole in the allowance area, the machining trajectory is generated based on the machining coordinate system, the thermal deformation compensation amount and the tool wear compensation amount to complete the machining.

15. The method for reducing machining errors of composite material parts according to claim 1, characterized in that, It also includes establishing a digital twin model of the composite material part to be processed based on the full-process data of the processing of the composite material part to be processed.

16. A system for reducing machining errors in composite material parts, characterized in that, include: Storage module, used to store mathematical models of composite material parts; The model loading and parsing module is used to load the corresponding mathematical model of the composite material part to be processed, and to parse the mathematical model to obtain the reference parameters. The reference parameters include theoretical reference surfaces and theoretical data of pre-drilled process holes. A setting module is used to set multiple sampling points on the theoretical reference surface and obtain the theoretical data of the sampling points; The data acquisition module is used to acquire measured data from the pre-drilled process holes and the sampling points; The coordinate system establishment module is used to establish an initial coordinate system based on the measured data of the pre-drilled process holes; A coordinate system transformation module is used to correct the initial coordinate system to obtain a machining coordinate system, based on the measured and theoretical data of multiple sampling points and the pre-drilled process hole as the main datum constraint and the sampling points as the surface correction supplement, using a weighted best-fit algorithm. The machining control module is used to generate CNC machining instructions based on the machining coordinate system and send the CNC machining instructions to the CNC machining device. The CNC machining instructions include machining instructions for the shape and features of the workpiece and machining instructions for drilling process correction holes in the allowance area of ​​the workpiece.

17. A control device, characterized in that, include: Memory is used to store computer program instructions; as well as A processor for executing the computer program instructions to implement the method of any one of claims 1 to 15.

18. An apparatus for reducing processing errors in composite material parts, characterized in that, include: Processing equipment is used to process the shape and features of the composite material part to be processed, and to drill process correction holes in the non-functional allowance area of ​​the composite material part to be processed. A fixing device is used to fix the composite material part to be processed. The fixing device includes a base, a support assembly, a clamping assembly, a positioning assembly, and a vacuum pipeline. The base is fixed on the processing equipment. The base has multiple mounting holes, and each mounting hole has a vacuum connector. The vacuum connector is connected to a vacuum device via the vacuum pipeline. The support assembly includes multiple support members. Each support member includes a support rod and a profile support block. The support rod has a first through hole along its axial direction. The first end of the support rod is installed in the mounting hole, and the second end of the support rod is connected to the profile support block. The support block is detachably connected. The side of the profile support block facing away from the support rod is matched with the theoretical profile of the composite material part to be processed. The clamping assembly includes multiple elastic clamping elements. Each elastic clamping element is installed on the corresponding profile support block. The elastic clamping element has a second through hole along the axial direction. The first through hole and the second through hole are connected and connected to the vacuum pipeline through the vacuum connector. The positioning assembly is inserted into the pre-drilled process hole of the composite material part to be processed to perform initial positioning of the composite material part to be processed. Measuring equipment is used to measure the parameters of each pre-drilled process hole and each preset sampling point on the composite material part to be processed; and The control device of claim 17, wherein the control device is electrically connected to the measuring device and the processing device.

19. The apparatus for reducing processing errors of composite material parts according to claim 18, characterized in that, The computer program instructions in the control device also include, before fixing the composite material part to be processed, using a profile support block matching algorithm to obtain profile support blocks for supporting the composite material part to be processed. The profile support block matching algorithm is constructed based on historically stored composite material part profile data and corresponding matching profile support block samples. The output profile support blocks include stored reused profile support blocks and / or newly generated custom profile support blocks.

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