Method for aligning an aircraft composite component with a forming tool coordinate system
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BEIJING POLYTECHNIC
- Filing Date
- 2026-04-28
- Publication Date
- 2026-08-04
AI Technical Summary
现有技术中，复材部件与成型工装的坐标系对齐多依赖人工基准、少量离散特征点或整体点云配准方法，但由于复材部件曲面形态复杂、局部刚度和几何约束不均匀，易出现对齐不稳定、弱约束方向误差放大以及对噪声敏感等问题，难以同时兼顾对齐精度与可靠性，且缺乏对对齐结果不确定度的有效评估机制
Smart Images
Figure CN122508741A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of aerospace manufacturing and digital assembly technology, and more specifically, to a method for aligning the coordinate system of aircraft composite components and forming tooling. Background Technology
[0002] Due to their lightweight, high strength, and complex curved surface characteristics, aircraft composite components are widely used in the aerospace manufacturing field. During the forming, assembly, and inspection processes, a unified and accurate coordinate system correspondence with the forming tooling is typically required. In existing technologies, the coordinate system alignment between composite components and forming tooling largely relies on manual references, a small number of discrete feature points, or overall point cloud registration methods. However, due to the complex surface morphology of composite components and the uneven local stiffness and geometric constraints, problems such as alignment instability, amplified errors in weak constraint directions, and sensitivity to noise easily arise. It is difficult to simultaneously ensure alignment accuracy and reliability, and there is a lack of an effective mechanism for evaluating the uncertainty of the alignment results.
[0003] In summary, achieving high-precision and robust alignment between aircraft composite components and the coordinate system of forming tooling under complex curved surfaces and weak geometric constraints has become an urgent technical problem to be solved. Summary of the Invention
[0004] To overcome a series of shortcomings in the existing technology, the purpose of this application is to provide a method for aligning the coordinate system of an aircraft composite component with that of a forming tooling, comprising the following steps:
[0005] Step S1: Obtain the three-dimensional theoretical model of the aircraft composite component and the tooling coordinate system of the forming tooling, and extract the theoretical surface of the three-dimensional theoretical model.
[0006] Step S2: Calculate the Gaussian curvature and average curvature of each point on the theoretical surface to form a continuous curvature field distribution, and divide the theoretical surface into three functional regions: high curvature sensitive region, smooth and weakly constrained region, and transition region.
[0007] Step S3: Calculate the sensitivity matrix of each functional area to the six-degree-of-freedom pose of the aircraft composite component in the tooling coordinate system, and generate a curvature sensitivity partition map.
[0008] Step S4: Based on the curvature sensitivity zoning map, auxiliary reference points are set up and calibrated in the flat and weakly constrained area, and the theoretical coordinates of the auxiliary reference points in the tooling coordinate system are obtained.
[0009] Step S5: With the aircraft composite component in the tooling state, measure the actual coordinates of the auxiliary reference point and obtain the curved point cloud of the outer surface of the aircraft composite component.
[0010] Step S6: Based on the curvature sensitivity partition map, construct differentiated geometric constraints for the surface point cloud, and combine the theoretical coordinates and actual coordinates of the auxiliary reference points to construct the rigid body registration constraints of the reference points, forming a multi-source fusion objective function.
[0011] Furthermore, the three-dimensional theoretical model of the aircraft composite component is obtained using a digital model in STEP or IGES format generated by CATIA or NX software.
[0012] Furthermore, the method for extracting the theoretical surfaces of the three-dimensional theoretical model is as follows:
[0013] Perform topological analysis on the three-dimensional theoretical model to obtain the topological structure information of each surface patch in the model and their mutual adjacency relationships;
[0014] Based on the topological information, the surface type of each surface piece is identified, and the surface piece is divided into aerodynamic shape skin surface, internal structure bonding surface, flange transition surface and process auxiliary surface.
[0015] Based on the geometric constraint contribution of various surfaces in the coordinate system establishment process, the identified surface patches are screened, and the aerodynamic shape skin surface is selected as the main theoretical surface, while the internal structure fitting surface is selected as the auxiliary constraint surface.
[0016] For the main theoretical surface and the auxiliary constraint surface, the positional continuity and tangent continuity of adjacent surface patches at the splicing boundary are detected, and the positional gap and the included angle of the tangent direction at the splicing boundary are calculated.
[0017] When the position gap at the splicing boundary is detected to be greater than a preset gap threshold or the included angle of the tangent direction is greater than a preset included angle threshold, geometric repair processing is performed on the corresponding splicing boundary to meet the surface continuity requirements;
[0018] The surface after continuous repair is mathematically expressed using non-uniform rational B-spline surfaces to obtain the theoretical surface of the three-dimensional theoretical model.
[0019] Furthermore, the method for calculating the sensitivity matrix of each functional region to the six-degree-of-freedom pose of the aircraft composite component in the tooling coordinate system is as follows:
[0020] Using the tooling coordinate system as the reference coordinate system, the rigid body pose state of the aircraft composite component is parameterized into a six-degree-of-freedom pose parameter vector containing three translational components and three rotational components, wherein the rotational components are represented in the form of rotational vectors.
[0021] Sampling points are selected in each functional area according to the preset sampling density, and the normal distance from each sampling point to the corresponding theoretical surface is calculated under the current pose parameter vector to form the geometric residual of the sampling point;
[0022] The geometric residuals are differentiated with respect to the six degrees of freedom pose parameters to obtain the pose sensitivity vectors corresponding to each sampling point. The pose sensitivity vectors are then combined row by row to construct the Jacobian matrix.
[0023] Based on the Jacobian matrix, the sensitivity matrix of the six-degree-of-freedom pose is calculated by transpose-product operation.
[0024] Furthermore, the method for setting up auxiliary reference points in the gentle, weakly constrained region is as follows:
[0025] Based on the sensitivity matrix analysis results corresponding to the smooth weak constraint region, the weak constraint direction and the number of weak constraint directions of the aircraft composite component in the tooling coordinate system are determined.
[0026] Based on the number of weak constraint directions and the spatial distribution range of the gentle weak constraint area, the number of auxiliary reference points is determined. When there is one weak constraint direction, no less than three auxiliary reference points are set up; when there are two weak constraint directions, no less than four auxiliary reference points are set up.
[0027] For the weak constraint direction, the spatial distribution of auxiliary reference points is planned so that the auxiliary reference points form a geometric configuration with a preset spatial span in the weak constraint direction.
[0028] Furthermore, the method for constructing differentiated geometric constraints on surface point clouds based on curvature-sensitive partitioning maps is as follows:
[0029] Based on the curvature sensitivity partitioning map, each point cloud data point is labeled as a high curvature sensitive area point, a transition area point, or a flat and weakly constrained area point.
[0030] The reference weights of the geometric constraints are determined based on the measurement noise level of the surface point cloud, and the reference weights are taken as the square of the reciprocal of the standard deviation of the measurement noise.
[0031] For point cloud data points labeled as high curvature sensitive areas, transition areas, or flat, weakly constrained areas, a normal distance constraint from the point to the theoretical surface is constructed. The constraint weight of high curvature sensitive areas is set to 1.5 to 2.0 times the baseline weight, the constraint weight of transition areas is set to the baseline weight, and the constraint weight of flat, weakly constrained areas is set to 0.3 to 0.5 times the baseline weight, thus forming a differentiated weighted geometric constraint system.
[0032] Furthermore, the method for constructing rigid body registration constraints for reference points by combining the theoretical and actual coordinates of auxiliary reference points is as follows:
[0033] A pose transformation model is established to transform the actual measured coordinates of the auxiliary reference points in the tooling coordinate system to a pose aligned with the three-dimensional theoretical model.
[0034] Obtain the actual measured coordinates and corresponding theoretical coordinates of each auxiliary reference point in the tooling coordinate system, and establish a one-to-one correspondence between the two.
[0035] Based on the pose transformation model, pose transformation is performed on the actual measured coordinates of each auxiliary reference point, and the rigid body registration constraint of the reference point is constructed by the spatial deviation between the transformed coordinates and the corresponding theoretical coordinates.
[0036] The registration constraints of each auxiliary reference point are summarized to form the rigid body registration constraint terms for the reference points.
[0037] Furthermore, the method for aligning the aircraft composite component with the coordinate system of the forming tooling also includes the following steps:
[0038] Step S7: Solve the multi-source fusion objective function, calculate the Fisher information matrix of the six-degree-of-freedom pose parameters, identify the weak constraint direction and introduce prior soft constraints for compensation, and obtain the final pose transformation parameters.
[0039] Step S8: Based on the final pose transformation parameters, perform coordinate transformation on the surface point cloud, calculate the registration residual distribution between it and the 3D theoretical model, evaluate the alignment accuracy and pose parameter uncertainty, and establish the coordinate system correspondence between the aircraft composite component and the forming tooling accordingly.
[0040] Furthermore, step S7 includes the following steps:
[0041] The multi-source fusion objective function is solved iteratively to obtain preliminary estimates of the six-degree-of-freedom pose parameters;
[0042] Based on the Jacobian information of the multi-source fusion objective function at the optimal estimation point, the Fisher information matrix corresponding to the six-degree-of-freedom pose parameters is calculated to characterize the information distribution characteristics in each pose parameter direction.
[0043] Feature analysis is performed on the Fisher information matrix, and weak constraint directions with insufficient information in the pose parameter space are identified based on the amount of information corresponding to each feature direction.
[0044] For the identified weak constraint directions, a soft constraint term based on prior pose parameters is introduced, and the soft constraint term is added to the multi-source fusion objective function and solved again to compensate for the insufficient constraints in the weak constraint directions.
[0045] Based on the solution results after introducing prior soft constraints, the final pose transformation parameters are obtained as the output result of multi-source fusion alignment.
[0046] Furthermore, step S8 includes the following steps:
[0047] Based on the final determined pose transformation parameters, coordinate transformation is performed on the curved point cloud of the aircraft composite component so that the curved point cloud and the three-dimensional theoretical model are in the same coordinate system.
[0048] In a unified coordinate system, the registration residual between the transformed surface point cloud and the three-dimensional theoretical model is calculated to obtain the registration residual value corresponding to each point cloud point.
[0049] The registration residual values are summarized to construct a registration residual distribution;
[0050] The registration residual distribution was statistically analyzed, and the registration residuals in different functional areas were statistically analyzed according to the curvature sensitivity zoning results.
[0051] Based on the statistical analysis results of the registration residuals, the alignment accuracy between the aircraft composite parts and the forming tooling is evaluated, and it is determined whether the alignment results meet the preset process tolerance requirements.
[0052] Based on the estimation results of the pose transformation parameters, the uncertainty of the pose parameters is calculated to characterize the reliability of the alignment result;
[0053] Under the condition that the alignment accuracy meets the process tolerance requirements, the coordinate system correspondence between the aircraft composite component and the forming tooling is established based on the final pose transformation parameters.
[0054] Compared with the prior art, this application has the following beneficial effects:
[0055] Based on theoretical surface curvature sensitivity analysis, this application integrates differentiated weighted surface point cloud constraints with auxiliary reference point rigid body registration and weak constraint compensation to achieve high-precision and robust alignment between aircraft composite components and the coordinate system of forming tooling. Attached Figure Description
[0056] Figure 1 This is a flowchart illustrating a method for aligning the coordinate system of an aircraft composite component with a molding tooling, as disclosed in an embodiment of this application. Detailed Implementation
[0057] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of the embodiments of this invention will be described in more detail below with reference to the accompanying drawings. In the drawings, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The described embodiments are some embodiments of this invention, but not all embodiments.
[0058] Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0059] The embodiments and directional terms described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.
[0060] like Figure 1 As shown, a method for aligning an aircraft composite component with a forming tooling coordinate system includes the following steps:
[0061] Step S1: Obtain the three-dimensional theoretical model of the aircraft composite component and the tooling coordinate system of the forming tooling, and extract the theoretical surface of the three-dimensional theoretical model.
[0062] Step S2: Calculate the Gaussian curvature and average curvature of each point on the theoretical surface to form a continuous curvature field distribution, and divide the theoretical surface into three functional regions: high curvature sensitive region, smooth and weakly constrained region, and transition region.
[0063] Step S3: Calculate the sensitivity matrix of each functional area to the six-degree-of-freedom pose of the aircraft composite component in the tooling coordinate system, and generate a curvature sensitivity partition map.
[0064] Step S4: Based on the curvature sensitivity zoning map, auxiliary reference points are set up and calibrated in the flat and weakly constrained area, and the theoretical coordinates of the auxiliary reference points in the tooling coordinate system are obtained.
[0065] Step S5: With the aircraft composite component in the tooling state, measure the actual coordinates of the auxiliary reference point and obtain the curved point cloud of the outer surface of the aircraft composite component.
[0066] Step S6: Based on the curvature sensitivity partitioning map, construct differentiated geometric constraints for the surface point cloud, and combine the theoretical coordinates and actual coordinates of the auxiliary reference points to construct rigid body registration constraints for the reference points, forming a multi-source fusion objective function;
[0067] Step S7: Solve the multi-source fusion objective function, calculate the Fisher information matrix of the six-degree-of-freedom pose parameters, identify the weak constraint direction and introduce prior soft constraints for compensation, and obtain the final pose transformation parameters.
[0068] Step S8: Based on the final pose transformation parameters, perform coordinate transformation on the surface point cloud, calculate the registration residual distribution between it and the three-dimensional theoretical model, evaluate the alignment accuracy and pose parameter uncertainty, and establish the coordinate system correspondence between the aircraft composite component and the forming tooling accordingly.
[0069] This invention proposes a method for aligning the coordinate system of aircraft composite components and forming tooling. Through curvature-driven functional partitioning, multi-source geometry and reference point fusion constraints, and pose uncertainty compensation, it achieves high-precision alignment between the composite components and the tooling coordinate system, effectively improving the stability and alignment accuracy of pose calculation. This method reduces reliance on manual experience and single measurement data, significantly reduces errors introduced by weakly constrained regions, and can still establish a unified and reliable coordinate system correspondence under complex surface and weak geometric features.
[0070] Furthermore, the three-dimensional theoretical model of the aircraft composite component is obtained using a digital model in STEP or IGES format generated by CATIA or NX software.
[0071] Furthermore, the method for establishing the tooling coordinate system is as follows:
[0072] No fewer than four process reference holes shall be set in the non-working surface area of the forming tooling as spatial references for establishing and verifying the tooling coordinate system;
[0073] A calibrated laser tracker was used to measure the three-dimensional spatial coordinates of the center of each process reference hole to obtain the corresponding spatial coordinate data.
[0074] Select the centers of three non-collinear process reference holes from the process reference holes, and establish the tooling coordinate system according to the following rules:
[0075] The center of one of the process reference holes is taken as the origin of the coordinate system;
[0076] The direction vector pointing from the origin to the center of the second process reference hole is normalized and determined as the positive direction of the X-axis.
[0077] The positive Y-axis direction is determined by normalizing the vertical component of the center of the third process reference hole relative to the positive X-axis direction.
[0078] According to the right-hand rule, the positive direction of the Z-axis is determined by the positive directions of the X-axis and Y-axis.
[0079] Compare the theoretical coordinates of the remaining process reference holes with their measured coordinates. When the deviation is not greater than the preset threshold, the tooling coordinate system is confirmed to be established.
[0080] The method for establishing the tooling coordinate system described in this invention constructs a stable and unified three-dimensional tooling coordinate system by setting process reference holes on non-working surfaces and combining this with high-precision measurement using a laser tracker. This enables the reliable establishment and rapid verification of the tooling spatial reference. This method avoids the cumulative errors and subjective uncertainties caused by traditional manual alignment and can maintain the consistency and traceability of the coordinate system even under complex tooling conditions.
[0081] Furthermore, the method for extracting the theoretical surfaces of the three-dimensional theoretical model is as follows:
[0082] Perform topological analysis on the three-dimensional theoretical model to obtain the topological structure information of each surface patch in the model and their mutual adjacency relationships;
[0083] Based on the topological information, the surface type of each surface piece is identified, and the surface piece is divided into aerodynamic shape skin surface, internal structure bonding surface, flange transition surface and process auxiliary surface.
[0084] Based on the geometric constraint contribution of various surfaces in the coordinate system establishment process, the identified surface patches are screened, and the aerodynamic shape skin surface is selected as the main theoretical surface, while the internal structure fitting surface is selected as the auxiliary constraint surface.
[0085] For the main theoretical surface and the auxiliary constraint surface, the positional continuity and tangent continuity of adjacent surface patches at the splicing boundary are detected, and the positional gap and the included angle of the tangent direction at the splicing boundary are calculated.
[0086] When the position gap at the splicing boundary is detected to be greater than a preset gap threshold or the included angle of the tangent direction is greater than a preset included angle threshold, geometric repair processing is performed on the corresponding splicing boundary to meet the surface continuity requirements;
[0087] The surface after continuous repair is mathematically expressed using non-uniform rational B-spline surfaces to obtain the theoretical surface of the three-dimensional theoretical model.
[0088] The theoretical surface extraction method of this invention involves performing topological analysis and surface type identification on a three-dimensional theoretical model to select surfaces that have key constraints on the coordinate system establishment. Furthermore, it performs continuity detection and geometric repair on the splicing boundaries to construct continuous, smooth, high-quality theoretical surfaces. This method effectively avoids the impact of model discretization errors and surface discontinuities on subsequent registration accuracy, providing a stable and reliable geometric benchmark for high-precision alignment of composite components and molding fixtures.
[0089] Furthermore, the Gaussian curvature and mean curvature at each point on the theoretical surface are calculated to form a continuous curvature field distribution, including the following steps:
[0090] Obtain the parameterized mathematical expression S(u,v) of the theoretical surface, establish the mapping relationship between the parameter domain and the physical space, and set the sampling strategy in the parameter domain according to the geometric complexity of the theoretical surface;
[0091] According to the sampling strategy, multiple sampling points covering the theoretical surface are generated in the parameter domain, wherein the distribution of sampling points satisfies that the relative rate of change of curvature between adjacent sampling points is not greater than a preset rate of change threshold (10%), and the maximum spacing between sampling points in physical space is not greater than a preset proportion (2%) of the component feature size.
[0092] For each sampling point, calculate the first-order partial derivative vector S of the theoretical surface in the parameter direction. u S v and the second-order partial derivative vector S uu S uv S vv And based on the first-order partial derivative vector S u S v Calculate the surface unit normal vector n at the corresponding sampling point;
[0093] According to the first-order partial derivative vector S u S v and the second-order partial derivative vector S uu S uv S vv Calculate the first fundamental form coefficients E, F, G and the second fundamental form coefficients L, M, N of the surface, respectively, where E = S u ·S u F=S u ·S v G=S v ·S v L=n·S uu M=n·S uv N = n·S vv ;
[0094] Based on the first and second fundamental form coefficients, calculate the Gaussian curvature K and the mean curvature H at each sampling point, where K = (LN - M 2 ) / (EG-F 2 );H=(EN-2FM+GL) / [2(EG-F 2 )];
[0095] The Gaussian curvature and average curvature calculated at the sampling points are mapped to the corresponding positions on the theoretical surface to form continuous curvature distribution data.
[0096] The curvature calculation method described in this invention accurately obtains the Gaussian curvature and average curvature of each point on the theoretical surface through parametric modeling and adaptive sampling, constructing a continuous and stable curvature field distribution. This method effectively reflects the changes in the geometric characteristics of the surface, avoids errors introduced by uneven sampling or numerical instability, and provides a reliable geometric basis for the functional zoning of the surface and subsequent pose constraint modeling.
[0097] Furthermore, the method for dividing the theoretical surface into three functional regions—high curvature sensitive region, gentle weak constraint region, and transition region—is as follows:
[0098] Obtain the Gaussian curvature and mean curvature at each point on the theoretical surface, and perform global statistical analysis on the absolute values of the Gaussian curvature and the mean curvature respectively.
[0099] Based on the statistical analysis results, the lower quartile Q1 and upper quartile Q3 of the absolute value distribution of Gaussian curvature and the absolute value distribution of mean curvature are calculated respectively, and used as the curvature determination threshold for functional region division.
[0100] Based on the relationship between the absolute values of Gaussian curvature and average curvature at each point on the theoretical surface and the quantile threshold, the functional attributes of the surface points are determined:
[0101] When the absolute value of the Gaussian curvature and the absolute value of the average curvature of a point on the surface are both greater than the corresponding Q3, it is classified as a high curvature sensitive region.
[0102] When the absolute value of the Gaussian curvature and the absolute value of the mean curvature of a point on the surface are both less than the corresponding Q1, it is classified as a gentle, weakly constrained region.
[0103] The remaining surface points are divided into transition zones, and adjacent surface points with the same functional attributes are aggregated to form corresponding functional regions.
[0104] The functional region division method of this invention performs global statistical analysis on the curvature characteristics of theoretical surfaces and adaptively determines the thresholds for high and low curvature, thereby achieving an objective division of the functional attributes of surface points. This method can accurately distinguish regions with significant differences in their contribution to pose constraints, avoiding the subjectivity caused by manually setting thresholds.
[0105] Furthermore, the method for calculating the sensitivity matrix of each functional region to the six-degree-of-freedom pose of the aircraft composite component in the tooling coordinate system is as follows:
[0106] Using the tooling coordinate system as the reference coordinate system, the rigid body pose state of the aircraft composite component is parameterized into a six-degree-of-freedom pose parameter vector containing three translational components and three rotational components, wherein the rotational components are represented in the form of rotational vectors.
[0107] Sampling points are selected in each functional area according to the preset sampling density, and the normal distance from each sampling point to the corresponding theoretical surface is calculated under the current pose parameter vector to form the geometric residual of the sampling point;
[0108] The geometric residuals are differentiated with respect to the six degrees of freedom pose parameters to obtain the pose sensitivity vectors corresponding to each sampling point. The pose sensitivity vectors are then combined row by row to construct the Jacobian matrix.
[0109] Based on the Jacobian matrix, the sensitivity matrix of the six-degree-of-freedom pose is calculated by transpose-product operation.
[0110] The pose sensitivity calculation method of this invention parameterizes the pose of composite components into a six-degree-of-freedom model and constructs a Jacobian matrix based on the geometric residuals of sampling points within each functional region, quantitatively characterizing the constraint capability of different regions on pose parameters. This method can objectively reflect the sensitivity differences of surface geometric features to translation and rotation components, providing a precise mathematical basis for the generation of curvature sensitivity partitioning maps and subsequent differentiated constraint configuration.
[0111] Furthermore, the method for setting up auxiliary reference points in the gentle, weakly constrained region is as follows:
[0112] Based on the sensitivity matrix analysis results corresponding to the smooth weak constraint region, the weak constraint direction and the number of weak constraint directions of the aircraft composite component in the tooling coordinate system are determined.
[0113] Based on the number of weak constraint directions and the spatial distribution range of the gentle weak constraint area, the number of auxiliary reference points is determined. When there is one weak constraint direction, no less than three auxiliary reference points are set up; when there are two weak constraint directions, no less than four auxiliary reference points are set up.
[0114] For the weak constraint direction, the spatial distribution of auxiliary reference points is planned so that the auxiliary reference points form a geometric configuration with a preset spatial span in the weak constraint direction.
[0115] The auxiliary reference point layout method of this invention analyzes the pose sensitivity characteristics of a gently confined region, specifically identifies the weak constraint direction, and adaptively determines the number and spatial configuration of reference points. This method effectively enhances the geometric constraint capability of the weak constraint direction, avoids errors introduced by redundant or improperly distributed reference points, and provides stable and reliable reference support for subsequent multi-source fusion pose solving.
[0116] Furthermore, the actual coordinates of the auxiliary reference points are measured using a laser tracker, and the curved point cloud of the outer surface of the aircraft composite component is acquired using a structured light scanner.
[0117] Furthermore, the method for constructing differentiated geometric constraints on surface point clouds based on curvature-sensitive partitioning maps is as follows:
[0118] Based on the curvature sensitivity partitioning map, each point cloud data point is labeled as a high curvature sensitive area point, a transition area point, or a flat and weakly constrained area point.
[0119] The reference weights of the geometric constraints are determined based on the measurement noise level of the surface point cloud, and the reference weights are taken as the square of the reciprocal of the standard deviation of the measurement noise.
[0120] For point cloud data points labeled as high curvature sensitive areas, transition areas, or flat, weakly constrained areas, a normal distance constraint from the point to the theoretical surface is constructed. The constraint weight of high curvature sensitive areas is set to 1.5 to 2.0 times the baseline weight, the constraint weight of transition areas is set to the baseline weight, and the constraint weight of flat, weakly constrained areas is set to 0.3 to 0.5 times the baseline weight, thus forming a differentiated weighted geometric constraint system.
[0121] The differentiated geometric constraint construction method of this invention introduces a curvature-sensitive partition map to implement hierarchical weighted constraints on surface point clouds according to functional regions. This allows high-information regions to fully utilize pose constraints while avoiding excessive interference in low-information regions. This method effectively suppresses the adverse effects of measurement noise and weak geometric features on the solution results, improving the stability and overall alignment accuracy of multi-source fusion pose calculation.
[0122] Furthermore, the method for constructing rigid body registration constraints for reference points by combining the theoretical and actual coordinates of auxiliary reference points is as follows:
[0123] A pose transformation model is established to transform the actual measured coordinates of the auxiliary reference points in the tooling coordinate system to a pose aligned with the three-dimensional theoretical model.
[0124] Obtain the actual measured coordinates and corresponding theoretical coordinates of each auxiliary reference point in the tooling coordinate system, and establish a one-to-one correspondence between the two.
[0125] Based on the pose transformation model, pose transformation is performed on the actual measured coordinates of each auxiliary reference point, and the rigid body registration constraint of the reference point is constructed by the spatial deviation between the transformed coordinates and the corresponding theoretical coordinates.
[0126] The registration constraints of each auxiliary reference point are summarized to form the rigid body registration constraint terms for the reference points.
[0127] The rigid body registration constraint construction method for reference points described in this invention establishes a unified pose transformation model and performs rigid body registration between the measured coordinates and theoretical coordinates of auxiliary reference points to form stable discrete geometric constraints. This method effectively compensates for the shortcomings of surface geometric constraints in weak feature regions, enhances the observability and robustness of the overall pose calculation, and provides key support for the reliable construction of multi-source fusion objective functions.
[0128] The multi-source fusion objective function of this invention integrates the weighted geometric constraints of the surface point cloud and the rigid body registration constraints of the auxiliary reference points into the same optimization framework, achieving the synergistic fusion of continuous surface information and discrete reference information. By introducing weighting coefficients and adjustment factors, the contributions of different constraint sources can be flexibly balanced, improving the stability, accuracy, and adaptability to weakly constrained situations in pose solving.
[0129] Furthermore, step S7 includes the following steps:
[0130] The multi-source fusion objective function is solved iteratively to obtain preliminary estimates of the six-degree-of-freedom pose parameters;
[0131] Based on the Jacobian information of the multi-source fusion objective function at the optimal estimation point, the Fisher information matrix corresponding to the six-degree-of-freedom pose parameters is calculated to characterize the information distribution characteristics in each pose parameter direction.
[0132] Feature analysis is performed on the Fisher information matrix, and weak constraint directions with insufficient information in the pose parameter space are identified based on the amount of information corresponding to each feature direction.
[0133] For the identified weak constraint directions, a soft constraint term based on prior pose parameters is introduced, and the soft constraint term is added to the multi-source fusion objective function and solved again to compensate for the insufficient constraints in the weak constraint directions.
[0134] Based on the solution results after introducing prior soft constraints, the final pose transformation parameters are obtained as the output result of multi-source fusion alignment.
[0135] The pose solving and uncertainty compensation method of this invention iteratively optimizes the multi-source fusion objective function and introduces Fisher information matrix to analyze the information distribution of pose parameters, adaptively identifying and compensating for weak constraint directions. This method effectively improves the stability and reliability of pose calculation under insufficient constraints, avoids excessive sensitivity of the calculation results to local geometric features or noise, and ensures the accuracy and consistency of the final pose transformation parameters.
[0136] Furthermore, step S8 includes the following steps:
[0137] Based on the final determined pose transformation parameters, coordinate transformation is performed on the curved point cloud of the aircraft composite component so that the curved point cloud and the three-dimensional theoretical model are in the same coordinate system.
[0138] In a unified coordinate system, the registration residual between the transformed surface point cloud and the three-dimensional theoretical model is calculated to obtain the registration residual value corresponding to each point cloud point.
[0139] The registration residual values are summarized to construct a registration residual distribution;
[0140] The registration residual distribution was statistically analyzed, and the registration residuals in different functional areas were statistically analyzed according to the curvature sensitivity zoning results.
[0141] Based on the statistical analysis results of the registration residuals, the alignment accuracy between the aircraft composite parts and the forming tooling is evaluated, and it is determined whether the alignment results meet the preset process tolerance requirements.
[0142] Based on the estimation results of the pose transformation parameters, the uncertainty of the pose parameters is calculated to characterize the reliability of the alignment result;
[0143] Under the condition that the alignment accuracy meets the process tolerance requirements, the coordinate system correspondence between the aircraft composite component and the forming tooling is established based on the final pose transformation parameters.
[0144] The alignment result evaluation method of this invention statistically analyzes the registration residuals between the transformed surface point cloud and the three-dimensional theoretical model, and evaluates the alignment effect of different functional areas separately by combining curvature sensitivity partitioning, thereby achieving a comprehensive judgment on alignment accuracy and reliability. This method can not only objectively determine whether the alignment result meets the process tolerance requirements, but also quantify the uncertainty of pose parameters, providing a basis for the reliable establishment of the coordinate system correspondence between aircraft composite components and forming tooling.
[0145] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A method for aligning the coordinate system of an aircraft composite component with a forming tooling, characterized in that, Includes the following steps: Step S1: Obtain the three-dimensional theoretical model of the aircraft composite component and the tooling coordinate system of the forming tooling, and extract the theoretical surface of the three-dimensional theoretical model. Step S2: Calculate the Gaussian curvature and average curvature of each point on the theoretical surface to form a continuous curvature field distribution, and divide the theoretical surface into three functional regions: high curvature sensitive region, smooth and weakly constrained region, and transition region. Step S3: Calculate the sensitivity matrix of each functional area to the six-degree-of-freedom pose of the aircraft composite component in the tooling coordinate system, and generate a curvature sensitivity partition map. Step S4: Based on the curvature sensitivity zoning map, auxiliary reference points are set up and calibrated in the flat and weakly constrained area, and the theoretical coordinates of the auxiliary reference points in the tooling coordinate system are obtained. Step S5: With the aircraft composite component in the tooling state, measure the actual coordinates of the auxiliary reference point and obtain the curved point cloud of the outer surface of the aircraft composite component. Step S6: Based on the curvature sensitivity partition map, construct differentiated geometric constraints for the surface point cloud, and combine the theoretical coordinates and actual coordinates of the auxiliary reference points to construct the rigid body registration constraints of the reference points, forming a multi-source fusion objective function.
2. The method for aligning the coordinate system of an aircraft composite component with a forming tooling according to claim 1, characterized in that, The three-dimensional theoretical model of the aircraft composite component is obtained using a digital model in STEP or IGES format generated by CATIA or NX software.
3. The method for aligning the coordinate system of an aircraft composite component with a forming tooling according to claim 1, characterized in that, The method for extracting the theoretical surface of a three-dimensional theoretical model is as follows: Perform topological analysis on the three-dimensional theoretical model to obtain the topological structure information of each surface patch in the model and their mutual adjacency relationships; Based on the topological information, the surface type of each surface piece is identified, and the surface piece is divided into aerodynamic shape skin surface, internal structure bonding surface, flange transition surface and process auxiliary surface. Based on the geometric constraint contribution of various surfaces in the coordinate system establishment process, the identified surface patches are screened, and the aerodynamic shape skin surface is selected as the main theoretical surface, while the internal structure fitting surface is selected as the auxiliary constraint surface. For the main theoretical surface and the auxiliary constraint surface, the positional continuity and tangent continuity of adjacent surface patches at the splicing boundary are detected, and the positional gap and the included angle of the tangent direction at the splicing boundary are calculated. When the position gap at the splicing boundary is detected to be greater than a preset gap threshold or the included angle of the tangent direction is greater than a preset included angle threshold, geometric repair processing is performed on the corresponding splicing boundary to meet the surface continuity requirements; The surface after continuous repair is mathematically expressed using non-uniform rational B-spline surfaces to obtain the theoretical surface of the three-dimensional theoretical model.
4. The method for aligning the coordinate system of an aircraft composite component with a forming tooling according to claim 3, characterized in that, The method for calculating the sensitivity matrix of each functional region to the six-degree-of-freedom pose of the aircraft composite component in the tooling coordinate system is as follows: Using the tooling coordinate system as the reference coordinate system, the rigid body pose state of the aircraft composite component is parameterized into a six-degree-of-freedom pose parameter vector containing three translational components and three rotational components, wherein the rotational components are represented in the form of rotational vectors. Sampling points are selected in each functional area according to the preset sampling density, and the normal distance from each sampling point to the corresponding theoretical surface is calculated under the current pose parameter vector to form the geometric residual of the sampling point; The geometric residuals are differentiated with respect to the six degrees of freedom pose parameters to obtain the pose sensitivity vectors corresponding to each sampling point. The pose sensitivity vectors are then combined row by row to construct the Jacobian matrix. Based on the Jacobian matrix, the sensitivity matrix of the six-degree-of-freedom pose is calculated by transpose-product operation.
5. The method for aligning the coordinate system of an aircraft composite component with a forming tooling according to claim 1, characterized in that, The method for setting up auxiliary reference points in a flat, weakly constrained region is as follows: Based on the sensitivity matrix analysis results corresponding to the smooth weak constraint region, the weak constraint direction and the number of weak constraint directions of the aircraft composite component in the tooling coordinate system are determined. Based on the number of weak constraint directions and the spatial distribution range of the gentle weak constraint area, the number of auxiliary reference points is determined. When there is one weak constraint direction, no less than three auxiliary reference points are set up; when there are two weak constraint directions, no less than four auxiliary reference points are set up. For the weak constraint direction, the spatial distribution of auxiliary reference points is planned so that the auxiliary reference points form a geometric configuration with a preset spatial span in the weak constraint direction.
6. The method for aligning the coordinate system of an aircraft composite component with a forming tooling according to claim 1, characterized in that, The method for constructing differentiated geometric constraints on surface point clouds based on curvature-sensitive partitioning maps is as follows: Based on the curvature sensitivity partitioning map, each point cloud data point is labeled as a high curvature sensitive area point, a transition area point, or a flat and weakly constrained area point. The reference weights of the geometric constraints are determined based on the measurement noise level of the surface point cloud, and the reference weights are taken as the square of the reciprocal of the standard deviation of the measurement noise. For point cloud data points labeled as high curvature sensitive areas, transition areas, or flat, weakly constrained areas, a normal distance constraint from the point to the theoretical surface is constructed. The constraint weight of high curvature sensitive areas is set to 1.5 to 2.0 times the baseline weight, the constraint weight of transition areas is set to the baseline weight, and the constraint weight of flat, weakly constrained areas is set to 0.3 to 0.5 times the baseline weight, thus forming a differentiated weighted geometric constraint system.
7. The method for aligning the coordinate system of an aircraft composite component with a forming tooling according to claim 1, characterized in that, The method for constructing rigid body registration constraints for reference points by combining the theoretical and actual coordinates of auxiliary reference points is as follows: A pose transformation model is established to transform the actual measured coordinates of the auxiliary reference points in the tooling coordinate system to a pose aligned with the three-dimensional theoretical model. Obtain the actual measured coordinates and corresponding theoretical coordinates of each auxiliary reference point in the tooling coordinate system, and establish a one-to-one correspondence between the two. Based on the pose transformation model, pose transformation is performed on the actual measured coordinates of each auxiliary reference point, and the rigid body registration constraint of the reference point is constructed by the spatial deviation between the transformed coordinates and the corresponding theoretical coordinates. The registration constraints of each auxiliary reference point are summarized to form the rigid body registration constraint terms for the reference points.
8. A method for aligning the coordinate system of an aircraft composite component with a forming tooling according to any one of claims 1-7, characterized in that, The method for aligning the aircraft composite component with the coordinate system of the forming tooling also includes the following steps: Step S7: Solve the multi-source fusion objective function, calculate the Fisher information matrix of the six-degree-of-freedom pose parameters, identify the weak constraint direction and introduce prior soft constraints for compensation, and obtain the final pose transformation parameters. Step S8: Based on the final pose transformation parameters, perform coordinate transformation on the surface point cloud, calculate the registration residual distribution between it and the three-dimensional theoretical model, evaluate the alignment accuracy and pose parameter uncertainty, and establish the coordinate system correspondence between the aircraft composite component and the forming tooling accordingly.
9. The method for aligning the coordinate system of an aircraft composite component with a forming tooling according to claim 8, characterized in that, Step S7 includes the following steps: The multi-source fusion objective function is solved iteratively to obtain preliminary estimation results of the six-degree-of-freedom pose parameters; Based on the Jacobian information of the multi-source fusion objective function at the optimal estimation point, the Fisher information matrix corresponding to the six-degree-of-freedom pose parameters is calculated to characterize the information distribution characteristics in each pose parameter direction. Feature analysis is performed on the Fisher information matrix, and weak constraint directions with insufficient information in the pose parameter space are identified based on the amount of information corresponding to each feature direction. For the identified weak constraint directions, a soft constraint term based on prior pose parameters is introduced, and the soft constraint term is added to the multi-source fusion objective function and solved again to compensate for the insufficient constraints in the weak constraint directions. Based on the solution results after introducing prior soft constraints, the final pose transformation parameters are obtained as the output result of multi-source fusion alignment.
10. The method for aligning the coordinate system of an aircraft composite component with a forming tooling according to claim 8, characterized in that, Step S8 includes the following steps: Based on the final determined pose transformation parameters, coordinate transformation is performed on the curved point cloud of the aircraft composite component so that the curved point cloud and the three-dimensional theoretical model are in the same coordinate system. In a unified coordinate system, the registration residual between the transformed surface point cloud and the three-dimensional theoretical model is calculated to obtain the registration residual value corresponding to each point cloud point. The registration residual values are summarized to construct the registration residual distribution; The registration residual distribution was statistically analyzed, and the registration residuals in different functional areas were statistically analyzed according to the curvature sensitivity zoning results. Based on the statistical analysis results of the registration residuals, the alignment accuracy between the aircraft composite parts and the forming tooling is evaluated, and it is determined whether the alignment results meet the preset process tolerance requirements. Based on the estimation results of the pose transformation parameters, the uncertainty of the pose parameters is calculated to characterize the reliability of the alignment result; Under the condition that the alignment accuracy meets the process tolerance requirements, the coordinate system correspondence between the aircraft composite component and the forming tooling is established based on the final pose transformation parameters.