A fastener hole site generation method and apparatus

Abstract

The application provides a fastener hole position generation method and device, and relates to the technical field of fastener hole position generation. The specific steps comprise the following: obtaining physical point cloud data through three-dimensional scanning, and establishing a high-precision three-dimensional real scanning model through denoising, simplifying and reconstructing processing. Based on the three-dimensional real scanning model, the stress concentration points of the connecting area are identified through stress analysis, and the initial distribution area of the hole position is determined according to the distribution density. In combination with the specification parameters of the fastener, the candidate hole position set containing coordinates and hole diameters is generated in the initial area. The spatial interference check is carried out on the candidate hole position, the hole position with a spacing smaller than the minimum installation spacing is automatically removed, and the final hole position set meeting the assembly requirements is output, so that the assembly accuracy and the structural reliability are effectively ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of fastener hole generation, in particular to a fastener hole generation method and device. BACKGROUND

[0002] In the field of aerospace manufacturing, high-precision assembly of fuselage curved skin and frame structure is a key link to ensure the structural performance of the aircraft, which involves precise machining and matching of a large number of fastener holes. The traditional method mainly relies on two-dimensional drawings and manual experience for hole positioning, or directly generates numerical control machining program based on ideal CAD model. However, during the process of autoclave curing of composite skin and subsequent processes, manufacturing deviations and deformations are inevitable, and assembly errors exist in the installation process of frame structure, resulting in significant differences between the theoretical model and the physical entity. Such differences make the hole positions generated based on the theoretical model misaligned in actual assembly, and have to rely on on-site manual repair, hole repair and other remedial measures, which seriously affects the assembly efficiency and quality consistency.

[0003] Although the prior art has introduced three-dimensional scanning means to obtain point cloud data of the actual object, it is mostly limited to the detection and comparison links, and the measured data cannot be effectively integrated into the hole generation process. The current method lacks a systematic and automated technical solution that can realize the whole process closed loop from physical digital modeling, mechanical property analysis, process constraint verification to numerical control code generation. How to quickly and accurately generate hole positions that meet the structural strength requirements and conform to the process specifications according to the actual shape of the actual object is still a technical bottleneck restricting the development of high-precision digital assembly.

[0004] The above information disclosed in the background section is only used to enhance the understanding of the background of the present disclosure, and therefore it can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0005] The purpose of the present application is to provide a fastener hole generation method and device to solve the problems raised in the background.

[0006] To achieve the above purpose, the present application provides the following technical scheme:

[0007] A fastener hole generation method, the specific steps include:

[0008] Step 1: Obtain point cloud data of the curved skin and frame structure by a three-dimensional scanning device, and perform denoising, simplification and reconstruction processing on the point cloud data to obtain a three-dimensional real scanning model reflecting the actual shape of the actual object;

[0009] Step 2: Based on the three-dimensional real scanning model, identify the stress concentration points of the connection area between the curved skin and the frame structure, and determine the initial area of the hole distribution according to the distribution density of the stress concentration points and the boundary coordinates of the connection area;

[0010] Step 3: Within the three-dimensional coordinate range of the initial area, generate a hole candidate set in combination with the specification parameters of the fasteners, which includes the candidate hole center coordinates and corresponding hole diameters of each fastener; the specification parameters include fastener diameter, head diameter and minimum installation spacing;

[0011] Step 4: Based on the candidate hole center coordinates in the hole candidate set, perform spatial interference checking on the candidate holes, and eliminate the candidate holes that do not meet the requirements to obtain a set of fastener hole positions that meet the assembly requirements; the spatial interference checking refers to checking whether the spacing between adjacent holes is not less than the minimum installation spacing.

[0012] Further, the specific execution process of step 1 is as follows:

[0013] The actual curved skin and frame structure entity is scanned along a predetermined path by a three-dimensional laser scanner to obtain original three-dimensional point cloud data of its surface, which is a set of discrete points containing three-dimensional coordinate values in a global coordinate system;

[0014] A statistical outlier removal algorithm is used to denoise the original three-dimensional point cloud data, with a neighborhood point number of 50 points and a standard deviation multiplier of 1.0; a voxel grid filter is used to simplify the denoised point cloud, with a voxel edge length of 0.5 mm; the point cloud data sets obtained by multiple scans are registered by an iterative closest point algorithm to be unified in the same global coordinate system;

[0015] The preprocessed point cloud data is input into a Poisson surface reconstruction algorithm, with a reconstruction depth of 9, to generate a closed and continuous triangular mesh surface model according to the normal information of the point cloud. This model is the three-dimensional real scanning model.

[0016] Further, the logic for identifying stress center points is as follows: extract the structure parameters of the connection area from the three-dimensional real scanning model, including the curvature value of the curved skin, the cross-sectional size of the frame structure and the material thickness, input the structure parameters into a pre-set stress evaluation model, which calculates the stress values of each point in the connection area according to the structure parameters and material mechanical property parameters, and selects the points with stress values exceeding 1.2 times the allowable stress of the material as stress concentration points to generate a stress concentration point distribution map of the connection area; the material mechanical property parameters include yield strength, elastic modulus and Poisson's ratio;

[0017] The curvature value of the curved surface skin is discretized at a density of 80-100 sampling points per square meter, the cross-sectional size of the frame structure is extracted at an interval of one sampling point per 100 mm along the length direction, the material thickness is the thickness parameter preset in the design file, and all parameters are converted into associated data in a three-dimensional coordinate system and then input into the model.

[0018] The distribution density of the stress concentration points in the connection region is counted, and at least 3 stress concentration points per square centimeter in the region are taken as a constraint condition. Based on the Gaussian kernel density estimation algorithm, the stress concentration point distribution diagram is analyzed to obtain the initial region of the hole position distribution.

[0019] Further, based on the three-dimensional coordinate range of the initial region, a two-dimensional grid covering the initial region is generated, wherein the grid cell side length is determined according to the minimum installation spacing and the surface curvature:

[0020] ;

[0021] In the formula, represents the ideal grid cell side length of the initial region; and are the maximum grid cell size constraint and the minimum grid cell size constraint, respectively, which are preset by the system, wherein satisfies: , is the fastener diameter, is the maximum positive tolerance value, which refers to the upper limit value of the allowable deviation range; is the minimum installation spacing; represents the average curvature of the initial region; is the preset minimum curvature radius threshold value; is the preset weight, which is used to balance the influence of the installation spacing and the surface curvature on the grid cell size, .

[0022] Further, each grid cell in the two-dimensional grid is traversed, the number of stress concentration points inside each grid cell is calculated, and the ratio of the number of stress concentration points inside each grid cell to the total number of stress concentration points inside the grid cell and all adjacent grid cells is calculated. Set a first proportion threshold value, if the ratio calculated by a certain grid cell is greater than or equal to the first proportion threshold value, the center point of the grid cell is retained, and the coordinates of the center point are included in the preliminary candidate hole position set as a preliminary candidate hole position.

[0023] generating a stress distribution density map of the initial region based on stress value data of each point in the connection region; calculating a local density value of a grid cell in which each candidate hole center coordinate in the preliminary candidate hole set is located; setting a second density threshold value, and if the local density value is greater than or equal to the second density threshold value, the hole is retained;

[0024] retaining all the final retained hole center coordinates as candidate hole center coordinates;

[0025] calculating a basic hole diameter value corresponding to each candidate hole center coordinate according to the fastener diameter and a preset tolerance fit standard:

[0026]

[0027] wherein, is the basic hole diameter value, is the fastener diameter, is a basic deviation, which is obtained by querying the preset tolerance fit standard; is a standard tolerance value, which is determined by consulting a national standard tolerance table;

[0028] determining a final hole diameter value of the candidate hole based on the basic hole diameter value and a head diameter of the fastener: comparing the head diameter with a preset counter-sunk hole generation threshold value; if the head diameter is greater than the threshold value, it is determined that the hole needs to generate a counter-sunk hole, and the final hole diameter value of the hole is determined as the head diameter; if the head diameter is less than or equal to the threshold value, the final hole diameter value of the hole is determined as the basic hole diameter value;

[0029] binding each candidate hole center coordinate with its corresponding final hole diameter value to jointly form a complete hole data unit, and a set of all hole data units is the hole candidate set.

[0030] Further, the specific execution process of step 4 is as follows:

[0031] performing verification on each candidate hole in the hole candidate set, calculating the three-dimensional Euclidean distance between each candidate hole and all other holes in the hole candidate set, screening out all other holes with a distance less than the minimum installation distance, and marking these holes as distance conflict holes;

[0032] traversing the hole groups with distance conflicts, and in each group of mutually conflicting holes, retaining the candidate hole with the highest local density value, and if the local stress density values are the same, retaining the candidate hole with a smaller tolerance band deviation absolute value, and simultaneously eliminating other candidate holes in the group that conflict with it;

[0033] ​After the above elimination processing, the set composed of the remaining candidate hole sites is the fastener hole site set meeting the assembly requirements; the output format of the fastener hole site set is converted into a code format recognizable by a numerical control machine tool, and output is performed, so as to complete the generation of the fastener hole site.

[0034] The application further provides a fastener hole site generation device for executing the fastener hole site generation method, comprising:

[0035] The data modeling module is configured to acquire point cloud data of the curved skin and the frame structure by a three-dimensional scanning device, and perform denoising, simplification and reconstruction processing on the point cloud data to obtain a three-dimensional real scanning model reflecting the actual shape of the physical object.

[0036] The stress area positioning module is configured to identify stress concentration points of a connecting area of the curved skin and the frame structure based on the three-dimensional real scanning model, and determine an initial area of hole site distribution according to the distribution density of the stress concentration points and boundary coordinates of the connecting area.

[0037] The candidate hole site generation module is configured to generate a hole site candidate set in the three-dimensional coordinate range of the initial area in combination with specification parameters of the fastener, the hole site candidate set including candidate hole site center coordinates and corresponding hole diameters of each fastener; the specification parameters include a fastener diameter, a head diameter and a minimum installation spacing.

[0038] The hole site optimization and verification module is configured to perform spatial interference verification on the candidate hole sites based on the candidate hole site center coordinates in the hole site candidate set, eliminate candidate hole sites that do not meet the requirements, and obtain a fastener hole site set meeting the assembly requirements; the spatial interference verification refers to verifying whether the spacing between adjacent hole sites is not less than the minimum installation spacing.

[0039] Compared with the prior art, the application has the following beneficial effects:

[0040] The application directly acquires the accurate geometric shape of the surface of the physical object through high-precision three-dimensional scanning and reconstruction technology, and the generated three-dimensional real scanning model completely eliminates the hole site mispositioning problem caused by the deviation between the theoretical model and the physical object, thereby ensuring the accuracy of the hole site center coordinates from the source and avoiding residual stress caused by forced assembly. Secondly, stress analysis based on the real scanning model can accurately identify the stress concentration area, thereby realizing scientific optimization of hole site distribution, effectively dispersing the load by increasing the hole site density in the high stress area, reducing the hole site in the low stress area to achieve weight reduction, and perfectly balancing the structural safety and lightweight requirements. Finally, the fully automated spatial interference verification process ensures that each generated hole site meets the minimum spacing requirement, eliminates the omissions that may be caused by manual intervention, and significantly improves the assembly efficiency, connection reliability and product quality consistency. BRIEF DESCRIPTION OF DRAWINGS

[0041] Figure 1 The overall method flowchart of the present application is shown in the figure;

[0042] Figure 2 The 3D strip image of the average curvature and the ideal grid cell length is shown in the figure;

[0043] Figure 3 The parallel coordinate diagram of the minimum installation spacing and the ideal grid cell length is shown in the figure;

[0044] Figure 4 The overall system module diagram of the present application is shown in the figure. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical scheme and advantages of the present application more clear and obvious, the present application is further described in detail below in combination with specific embodiments.

[0046] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present application should be understood as the general meaning understood by those skilled in the art to which the present application belongs. The "first", "second" and similar words used in the present application do not represent any order, quantity or importance, but are only used to distinguish different components. "Include" or "contain" and similar words mean that the elements or objects before the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connected" or "connected" and similar words are not limited to physical or mechanical connection, but can include electrical connection, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to represent relative positional relationship, when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0047] EMBODIMENT

[0048] Please refer to Figures 1-3 The present application provides a technical scheme:

[0049] A fastener hole generation method, the specific steps include:

[0050] Step 1: Obtain the point cloud data of the curved skin and the frame structure by a three-dimensional scanning device, and perform denoising, simplification and reconstruction processing on the point cloud data to obtain a three-dimensional real scanning model reflecting the actual shape of the real object;

[0051] In this embodiment, the specific execution process of step 1 is as follows:

[0052] The actual curved skin and frame structure entity is scanned along a predetermined path by a three-dimensional laser scanner to obtain original three-dimensional point cloud data of the surface, the point cloud data being a collection of discrete points containing three-dimensional coordinate values in a global coordinate system;

[0053] A statistical outlier removal algorithm is used to denoise the original three-dimensional point cloud data, with a neighborhood point number of 50 points and a standard deviation multiplier of 1.0; a voxel grid filter is used to simplify the denoised point cloud, with a voxel edge length of 0.5 mm; the point cloud data sets obtained by multiple scans are registered by an iterative closest point algorithm and unified to the same global coordinate system;

[0054] The preprocessing operations of denoising, simplifying and registering the original three-dimensional point cloud data are key steps for constructing a high-precision three-dimensional real scanning model. The necessity lies in that: first, environmental noise and measurement errors are inevitably introduced during three-dimensional scanning, and the statistical outlier removal algorithm can effectively filter out these discrete noise points, improving the purity of the point cloud data and laying a foundation for the accuracy of subsequent model reconstruction. Second, the amount of original three-dimensional point cloud data is usually extremely large, and direct processing will bring a huge computational burden; the point cloud simplification by the voxel grid filter can significantly reduce the data volume and improve the processing efficiency while maintaining the main geometric features of the model. Finally, for the point cloud data sets obtained by multiple scans, since the viewing angle and coordinate system are different each time, the iterative closest point algorithm is used for accurate registration to unify all the data to the same global coordinate system, thereby ensuring that the three-dimensional model reconstructed finally is a complete and seamless entity, which truly reflects the actual assembly form of the curved skin and frame structure. These preprocessing steps jointly ensure the reliability and accuracy of subsequent stress analysis and hole site generation.

[0055] The preprocessed point cloud data is input into a Poisson surface reconstruction algorithm, with a reconstruction depth of 9, to generate a closed and continuous triangular mesh surface model according to the normal information of the point cloud, which is the three-dimensional real scanning model.

[0056] Step 1 obtains the point cloud data of the curved skin and frame structure by a three-dimensional scanning device, and performs denoising, simplification and reconstruction processing to obtain a three-dimensional real scanning model in a true form. The significance of this process lies in laying a foundation for the entire hole site generation method and ensuring that the subsequent stress analysis and hole site design are based on accurate structure data. By obtaining a high-precision three-dimensional model, design errors caused by inaccurate data are avoided, and the reliability of the overall scheme is improved.

[0057] Compared with the prior art, the advantages of step 1 mainly lie in the comprehensiveness and accuracy of data processing. The traditional method may rely on manual measurement or simplified model, resulting in information loss or inaccuracy. While the present application can obtain more detailed and realistic structural morphology by adopting advanced three-dimensional laser scanning technology and efficient point cloud processing algorithm, ensuring that the subsequent identification of stress concentration points and hole position design are more scientific. In addition, the triangular mesh model generated by the Poisson surface reconstruction algorithm used in step 1 provides better surface smoothness and detail presentation, ensuring the adaptability between the fastener and the structure during assembly, further improving the efficiency and safety of assembly.

[0058] Step 2: Based on the three-dimensional real scanning model, identify the stress concentration points of the connection area between the curved skin and the frame structure, and determine the initial area of hole distribution according to the distribution density of the stress concentration points and the boundary coordinates of the connection area.

[0059] In this embodiment, the logic for identifying stress concentration points is as follows: extract the structural parameters of the connection area from the three-dimensional real scanning model, including the curvature value of the curved skin, the cross-sectional size of the frame structure and the material thickness, input the structural parameters into the preset stress evaluation model, the model calculates the stress value of each point in the connection area according to the structural parameters and material mechanical property parameters, selects the point whose stress value exceeds 1.2 times of the allowable stress of the material as the stress concentration point, and generates a stress concentration point distribution map of the connection area; the material mechanical property parameters include yield strength, elastic modulus and Poisson's ratio;

[0060] Among them, the curvature value of the curved skin is discretized at a density of 80-100 sampling points per square meter, the cross-sectional size of the frame structure is extracted at an interval of one sampling point per 100 mm along the length direction, and the material thickness adopts the thickness parameter preset in the design file, all parameters are converted into associated data in the three-dimensional coordinate system and input into the model;

[0061] The distribution density of stress concentration points in the connection area is counted, and at least 3 stress concentration points per square centimeter in the area are taken as the constraint condition, the stress concentration point distribution map is analyzed based on the Gaussian kernel density estimation algorithm, and the initial area of hole distribution is obtained.

[0062] After obtaining the stress concentration point distribution map of the connection area, the specific process of determining the initial area of the hole site distribution is as follows: first, based on the stress concentration point distribution map, a Gaussian kernel density estimation algorithm is used to scan and analyze the entire connection area to generate a continuous stress concentration point density distribution cloud map. This cloud map can directly reflect the aggregation degree of stress concentration points in space. Then, taking at least 3 stress concentration points per square centimeter as a threshold, the above density distribution cloud map is segmented and extracted to screen out all continuous areas that meet or exceed the density threshold. Finally, the outer bounding box of the screened high-density area is connected and smoothed, and is cut and corrected in combination with the known connection area boundary coordinates. The continuous three-dimensional space range determined is the initial area where the fastener hole distribution needs to be generated. This method ensures that the hole site is generated preferentially in the key area where the stress concentration phenomenon is significant and the connection strength requirement is higher.

[0063] Step 2 identifies the stress concentration points of the connection area between the curved skin and the frame structure based on the three-dimensional real scanning model, and determines the initial area of hole site distribution according to the distribution density of stress concentration points and the boundary coordinates of the connection area. The importance of this process lies in that it provides a scientific basis for hole site design. By accurately identifying stress concentration points, the area that needs to be strengthened can be effectively located, thereby ensuring the reasonable layout of hole sites and enhancing the safety and stability of the structure.

[0064] Compared with the prior art, the advantage of step 2 lies in the comprehensive analysis of stress distribution and the application of data-driven decision-making. Traditional methods often rely on experience or simple stress analysis, lacking true reflection of the actual stress state. However, the present application extracts the structural parameters of the three-dimensional model and combines the mechanical properties of the material to identify stress concentration points using a rigorous stress evaluation model, thereby forming a more accurate preliminary distribution area of hole sites. This method not only improves the scientificity of hole site design, but also effectively reduces the potential risk of structural failure, improving the reliability and efficiency of the overall assembly.

[0065] Step 3: Within the three-dimensional coordinate range of the initial area, a hole site candidate set is generated in combination with the specification parameters of the fastener, the hole site candidate set including the candidate hole site center coordinates and corresponding hole diameters of each fastener; the specification parameters include the fastener diameter, head diameter and minimum installation spacing;

[0066] In this embodiment, based on the three-dimensional coordinate range of the initial area, a two-dimensional grid covering the initial area is generated by grid division, wherein the grid cell side length is determined according to the minimum installation spacing and the surface curvature:

[0067] ;

[0068] In the formula, denotes the ideal mesh cell edge length of the initial region; and are the maximum mesh cell size constraint and the minimum mesh cell size constraint, respectively, preset by the system, wherein satisfies: , is the fastener diameter, is the maximum positive tolerance value, indicating the upper limit value of the allowable deviation range; is the minimum installation spacing; denotes the average curvature of the initial region; is the preset minimum curvature radius threshold value; is the preset weight used to balance the influence of the installation spacing and the surface curvature on the mesh cell size, .

[0069] Table 1: Ideal mesh cell edge length statistics

[0070]

[0071] According to the data in Table 1, it can be observed that the calculation results of the mesh cell edge length effectively coordinate the balance between the assembly process requirements and the surface geometric characteristics. The calculation results show that the finally determined mesh size is always constrained within the maximum and minimum size range preset by the system, and its value trend is clearly influenced by the minimum installation spacing and the surface curvature: when the surface curvature is larger, the calculation tends to produce smaller mesh size to adapt to the complex surface morphology; when the minimum installation spacing requirement is higher, the calculation result is increased accordingly to meet the space requirement of the assembly process.

[0072] Further analysis shows that the formula flexibly adjusts the influence strength of the above two types of factors through the weight factor, reflecting its adaptive ability to multi-objective constraints when performing mesh division. All data sets show that the calculation results do not exceed the preset size boundary, and the change law with the curvature and installation spacing is consistent, verifying the rationality and reliability of the formula in engineering application, which can provide a mesh basis that meets both geometric accuracy and assembly requirements for subsequent hole position generation.

[0073] In the above formula, the dependent variable denotes the ideal mesh cell edge length of the initial region. Its physical meaning is the best mesh size dynamically calculated to adapt to the assembly requirements and geometric form of a specific position. The technical effect of this variable lies in the adaptive regulation of mesh density: in high curvature areas, the mesh size is automatically reduced to generate denser mesh to accurately fit the complex surface, and in low curvature areas, the mesh size is increased To improve the computational efficiency by generating sparse grid, while ensuring that the grid size always meets the constraints of the minimum installation spacing of the fastener, thereby laying the geometric foundation for subsequent generation of high-quality, assemblyable candidate hole sites.

[0074] The independent variables in the formula are all related to the dependent variable There is a direct correlation: And is the boundary constraint of the grid cell edge length, used to limit the value range to avoid excessive grid size leading to sparse hole sites or excessive calculation; is the core process parameter of hole layout, directly determining the minimum distance between holes, so it needs to be affected by the size of ; reflects the degree of surface curvature, and the area with greater curvature needs smaller grid edge length to adapt to the curvature of the surface, so it is included in the calculation through to standardize the impact of curvature on the grid; is used to balance the impact of installation spacing and surface curvature on , so that is more in line with actual assembly requirements.

[0075] is positively correlated with , the larger the installation spacing requirement, the larger the grid size that can be used; is negatively correlated with the curvature , the greater the average curvature of the area, indicating that the surface is more curved, the smaller the required grid cell edge length to ensure accuracy; is positively correlated with , which limits the infinite encryption of the grid in high-curvature areas. The weight factor determines the influence of and on the final result , achieving a balance between process and geometric factors.

[0076] The formula has high formal rationality, and its structure cleverly realizes the optimal value solving under multiple constraints through the nesting of min and max functions. The outer min function ensures that the calculation result will not exceed the maximum grid size allowed by the system, meeting the requirements of computational efficiency and resource constraints; the inner max function ensures that the calculation result will not be smaller than the minimum grid size , complying with the physical feasibility rules of fastener installation. The core calculation term The linear weighting form intuitively reflects the design idea of trade-off between assembly process requirements and geometric complexity, and the weight factor makes the trade-off process controllable and adjustable. The entire formula structure is compact, logical, and each variable has clear physical meaning and clear mathematical relationship, fully embodying the constraint and optimization idea in engineering design.

[0077] Traverse each grid cell in the two-dimensional grid, calculate the ratio of the number of stress concentration points inside each grid cell to the total number of stress concentration points inside the grid cell and all its adjacent grid cells; Set a first proportion threshold, if the ratio calculated by a certain grid cell is greater than or equal to the first proportion threshold, retain the center point of the grid cell and include its coordinates in the preliminary candidate hole set as a preliminary candidate hole;

[0078] Based on the stress value data of each point in the connection area, generate a stress distribution density map of the initial area; Calculate the local density value of the grid cell where each candidate hole center coordinate in the preliminary candidate hole set is located; Set a second density threshold, if its local density value is greater than or equal to the second density threshold, retain the hole;

[0079] The final retained all hole center coordinates are used as candidate hole center coordinates;

[0080] According to the fastener diameter and the preset tolerance fit standard, calculate the basic hole diameter value corresponding to each candidate hole center coordinate:

[0081] ;

[0082] In the formula, is the basic hole diameter value, is the fastener diameter, is the basic deviation, which is obtained by querying the preset tolerance fit standard; is the standard tolerance value, which is determined by consulting the national standard tolerance table;

[0083] Through the above calculation formula, the basic hole diameter value can be calculated to obtain a hole that meets the design requirements and ensures the normal work of the fastener in actual processing. The dependent variable is used to represent the diameter size of the hole to ensure good fit between the hole and the fastener, thereby improving the accuracy and reliability of the overall assembly.

[0084] determining a final hole diameter value of the candidate hole site based on the base hole diameter value and a head diameter of the fastener: comparing the head diameter with a preset counter-sunk hole generation threshold value; if the head diameter is greater than the threshold value, determining that a counter-sunk hole needs to be generated for the hole site, and determining the final hole diameter value of the hole site as the head diameter; if the head diameter is less than or equal to the threshold value, determining the final hole diameter value of the hole site as the base hole diameter value;

[0085] binding the center coordinates of each candidate hole site with the corresponding final hole diameter value to form a complete hole site data unit, and the collection of all hole site data units is the candidate hole site set.

[0086] Step 3 is to generate a candidate hole site set by combining the three-dimensional coordinate range of the initial region and the specification parameters of the fastener. The significance of this process is to provide a clear candidate range for subsequent hole site verification and selection. By systematically integrating parameters such as the diameter, head diameter, and minimum installation distance of each fastener, a hole site that meets the assembly requirements can be effectively generated. This not only reduces the error of manual intervention, but also ensures the rationality and scientificity of the hole site design.

[0087] Compared with the prior art, the advantage of step 3 is its data-driven generation method. Traditional methods often rely on empirical rules or simple size relationships to determine the hole site, lacking systematization and precision. By considering multiple specification parameters, the invention systematically generates a candidate hole site set, ensuring that the hole layout meets actual engineering requirements. In addition, through the management of the candidate set, unqualified hole sites can be quickly eliminated in subsequent steps, thereby improving the efficiency of hole site generation and reducing potential assembly risks. This method not only improves the flexibility of hole site generation, but also enhances the reliability of the overall assembly process.

[0088] Step 4: based on the center coordinates of the candidate hole sites in the candidate hole site set, performing spatial interference verification on the candidate hole sites to eliminate candidate hole sites that do not meet the requirements, and obtaining a fastener hole site set that meets the assembly requirements; the spatial interference verification refers to verifying whether the distance between adjacent hole sites is greater than the minimum installation distance;

[0089] In this embodiment, the specific execution process of step 4 is as follows:

[0090] For each candidate hole site in the candidate hole site set, calculate the three-dimensional Euclidean distance between each candidate hole site and all other hole sites in the candidate hole site set, and select all other hole sites with a distance less than the minimum installation distance, and mark these hole sites as distance conflict hole sites;

[0091] In the group of hole positions with spacing conflicts, the candidate hole position with the highest local density value is retained in each group of mutually conflicting hole positions, and if the local stress density values are the same, the candidate hole position with the smaller absolute value of tolerance band deviation is retained, and other candidate hole positions in conflict with it in the group are removed;

[0092] After the above removal processing, the set of remaining candidate hole positions constitutes a fastener hole position set that meets the assembly requirements; the output format of the fastener hole position set is converted into a code format that can be recognized by a numerical control machine tool, and output is performed, thereby completing the generation of the fastener hole position.

[0093] The setting of the spatial interference checking and conflict optimization processing steps is the final guarantee to ensure that the generated hole position scheme has engineering feasibility and assembly reliability. The core purpose is: first, through three-dimensional Euclidean distance calculation and minimum installation spacing comparison, spatial interference checking is performed, which can identify hole positions with excessively close spacing due to initial grid division or stress distribution screening, thereby fundamentally avoiding problems such as installation tools being unable to operate, connecting parts interfering with each other, or local material strength being weakened due to excessively small hole spacing. Second, when processing the hole position group with spacing conflicts, the optimization removal rule based on local stress density value priority and tolerance band deviation is used, which aims to make an intelligent decision based on mechanical performance; this rule prioritizes retaining hole positions distributed in high-stress areas to ensure that the key mechanical performance of the connecting structure is maximally guaranteed, and then considers the machining precision factor, thereby achieving an optimal balance between mechanical performance and manufacturability while solving spatial conflicts. Finally, the optimized hole position set is converted into numerical control code output, realizing seamless connection from the design scheme to the manufacturing instruction and completing the closed loop of automatic assembly.

[0094] Step 4 ensures that the final output fastener hole position set meets the actual assembly requirements by performing spatial interference checking on the hole position candidate set. The key significance of this process is that it effectively avoids assembly problems caused by insufficient hole spacing, thereby improving the safety and reliability of the overall assembly. Through a systematic checking process, it can quickly identify and remove candidate hole positions that do not meet the requirements, ensuring the scientificity and practicality of the selected hole positions.

[0095] Compared with the prior art, the advantage of step 4 lies in its comprehensive checking mechanism. Traditional methods often determine whether a hole position is qualified through simple size comparison, lacking depth analysis of spatial interference. However, the present invention performs comprehensive interference checking through three-dimensional Euclidean distance calculation combined with the requirement of minimum installation spacing. This method not only improves the accuracy of hole positions, but also effectively reduces potential risks in complex assembly environments, ensuring the rationality of hole position design and the smooth progress of the assembly process, thereby greatly improving the efficiency and success rate of automatic assembly.

[0096] Please refer to Figure 4 A fastener hole site generation device comprises:

[0097] A data modeling module is configured to acquire point cloud data of a curved skin and a frame structure by a three-dimensional scanning device, and to perform denoising, simplification and reconstruction processing on the point cloud data to obtain a three-dimensional real scanning model reflecting the actual shape of the real object.

[0098] A stress area positioning module is configured to identify stress concentration points of a connection area of the curved skin and the frame structure based on the three-dimensional real scanning model, and to determine an initial area of hole site distribution according to the distribution density of the stress concentration points and the boundary coordinates of the connection area.

[0099] A candidate hole site generation module is configured to generate a candidate hole site set in the three-dimensional coordinate range of the initial area in combination with the specification parameters of the fastener, the candidate hole site set including candidate hole site center coordinates and corresponding hole diameters corresponding to each fastener, and the specification parameters including a fastener diameter, a head diameter and a minimum installation spacing.

[0100] A hole site optimization and verification module is configured to perform spatial interference verification on the candidate hole sites based on the candidate hole site center coordinates in the candidate hole site set, to eliminate candidate hole sites that do not meet the requirements, and to obtain a fastener hole site set that meets the assembly requirements, and the spatial interference verification refers to checking whether the spacing between adjacent hole sites is not less than the minimum installation spacing.

[0101] The above formulas are all dimensionless numerical calculations, the formulas are obtained by collecting a large amount of data to simulate the nearest real situation, and the preset parameters in the formulas are set by a person skilled in the art according to the actual situation.

[0102] The above embodiments can be realized wholly or partially by software, hardware, firmware or any other combination. When realized by software, the above embodiments can be realized in the form of a computer program product wholly or partially. Those skilled in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized by hardware or software methods depends on the specific application and design constraints of the technical solutions.

[0103] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, which can be located in one place or distributed on multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiments.

[0104] The above merely provides the specific implementation of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of the changes or replacements within the technical range disclosed by the present application, which should be covered in the protection scope of the present application.

Claims

1. A method for generating fastener hole positions, applied to the automated assembly of curved fuselage skin and frame structure, characterized in that, The specific steps include: Step 1: Obtain point cloud data of curved skin and frame structure through 3D scanning equipment, and perform noise reduction, simplification and reconstruction processing on the point cloud data to obtain a 3D real scan model that reflects the actual shape of the object. Step 2: Based on the three-dimensional real scan model, identify the stress concentration points in the connection area between the curved skin and the frame structure. According to the distribution density of the stress concentration points and the boundary coordinates of the connection area, determine the initial area for hole distribution. Step 3: Within the three-dimensional coordinate range of the initial region, and in conjunction with the specifications of the fasteners, generate a candidate set of hole positions. The candidate set of hole positions includes the center coordinates of the candidate hole positions and the corresponding hole diameters for each fastener. The specifications include the fastener diameter, head diameter, and minimum installation spacing. Step 3 specifically includes: based on the three-dimensional coordinate range of the initial region, dividing it into a grid to generate a two-dimensional grid covering the initial region; Traverse each grid cell in the two-dimensional grid, calculate the ratio of the number of stress concentration points inside each grid cell to the total number of stress concentration points inside that grid cell and all its adjacent grid cells; set a first ratio threshold, if the ratio calculated for a certain grid cell is greater than or equal to the first ratio threshold, then retain the center point of that grid cell and include its coordinates in the preliminary candidate hole location set as a preliminary candidate hole location; Based on the stress value data of each point in the connected area, a stress distribution density map of the initial area is generated; the local density value of the grid cell where the center coordinates of each candidate hole in the preliminary candidate hole set is located is calculated; a second density threshold is set, and if its local density value is greater than or equal to the second density threshold, the hole is retained; The center coordinates of all the holes that are ultimately retained will be used as the candidate center coordinates of the holes. Based on the fastener diameter and the preset tolerance fit standard, calculate the basic hole diameter value corresponding to the center coordinates of each candidate hole position: In the formula, Based on the aperture value, For the diameter of the fastener, The basic deviation is obtained by referring to the preset tolerance and fit standards; The standard tolerance value is determined by referring to the national standard tolerance table. Based on the basic hole diameter value and the head diameter of the fastener, the final hole diameter value of the candidate hole position is determined: the head diameter is compared with a preset countersunk hole generation threshold; if the head diameter is greater than the threshold, it is determined that the hole position needs to generate a countersunk hole, and the final hole diameter value of the hole position is determined as the head diameter; if the head diameter is less than or equal to the threshold, the final hole diameter value of the hole position is determined as the basic hole diameter value. The center coordinates of each candidate borehole location are bound to its corresponding final borehole diameter value to form a complete borehole location data unit. The set of all borehole location data units is the candidate borehole location set. Step 4: Based on the center coordinates of the candidate holes in the candidate hole set, perform spatial interference verification on the candidate holes, remove the candidate holes that do not meet the requirements, and obtain a set of fastener holes that meet the assembly requirements; the spatial interference verification refers to verifying whether the distance between adjacent holes is not less than the minimum installation distance.

2. The fastener hole generation method according to claim 1, characterized in that: The specific execution process of step 1 is as follows: The actual curved skin and frame structure entity is scanned along a predetermined path by a 3D laser scanner to obtain the original 3D point cloud data of its surface. This point cloud data is a set of discrete points containing 3D coordinate values ​​in the global coordinate system. The original 3D point cloud data was denoised using a statistical outlier removal algorithm, with a neighborhood of 50 points and a standard deviation multiplier of 1.

0. The denoised point cloud was then simplified using a voxel mesh filter, with a voxel side length of 0.5 mm. The point cloud dataset obtained through multiple scans was then registered using an iterative nearest-point algorithm to unify it into the same global coordinate system. The preprocessed point cloud data is input into the Poisson surface reconstruction algorithm, and the reconstruction depth is set to 9. A closed and continuous triangular mesh surface model is generated based on the normal information of the point cloud. This model is the three-dimensional real scan model.

3. The fastener hole generation method according to claim 2, characterized in that: The logic for identifying stress concentration points is as follows: Structural parameters of the connection region are extracted from the 3D real-scan model, including the curvature value of the curved skin, the cross-sectional dimensions of the frame structure, and the material thickness. These structural parameters are then input into a preset stress assessment model. This model calculates the stress values ​​at each point in the connection region based on the structural parameters and material mechanical property parameters. Points with stress values ​​exceeding 1.2 times the allowable stress of the material are selected as stress concentration points to generate a stress concentration point distribution map of the connection region. The material mechanical property parameters include yield strength, elastic modulus, and Poisson's ratio. Among them, the curvature value of the curved skin is discretized according to the density of 80-100 sampling points per square meter, the cross-sectional dimensions of the frame structure are extracted at an interval of one sampling point every 100mm along the length direction, the material thickness adopts the thickness parameters preset in the design file, and all parameters are uniformly converted into associated data in the three-dimensional coordinate system and then input into the model. The distribution density of stress concentration points in the connected region is statistically analyzed. With the constraint that there are at least 3 stress concentration points per square centimeter in any region, the stress concentration point distribution map is analyzed based on the Gaussian kernel density estimation algorithm to obtain the initial region of hole location distribution.

4. The fastener hole generation method according to claim 3, characterized in that: The side length of the grid cell is determined based on the minimum installation spacing and the surface curvature: In the formula, This represents the ideal grid cell side length of the initial region; and These are the maximum and minimum mesh cell size constraints, preset by the system. satisfy: , For the diameter of the fastener, This is the maximum positive tolerance value, referring to the upper limit of the allowable deviation range; Minimum installation spacing; This represents the average curvature of the initial region; This is a preset minimum radius of curvature threshold; Preset weights are used to balance the effects of installation spacing and surface curvature on mesh cell size. .

5. The fastener hole generation method according to claim 1, characterized in that: The specific execution process of step 4 is as follows: For each candidate hole in the hole position candidate set, a verification is performed, and the three-dimensional Euclidean distance between each candidate hole position and all other holes in the hole position candidate set is calculated. All holes with a distance less than the minimum installation spacing are filtered out and marked as spacing conflict holes. Traverse the groups of holes with conflicting spacing. In each group of conflicting holes, retain the candidate hole with the highest local density value. If the local stress density values ​​are the same, retain the candidate hole with the smaller absolute value of the tolerance zone deviation, and at the same time remove other candidate holes in the group that conflict with it. After the above elimination process, the set of remaining candidate holes is the set of fastener holes that meet the assembly requirements. The output format of the fastener hole set is converted into a code format that can be recognized by CNC machine tools and then output, thereby completing the generation of fastener hole positions.

6. A fastener hole position generating device, characterized in that: The fastener hole position generating apparatus is used to perform the fastener hole position generating method according to any one of claims 1-5, comprising: The data modeling module is used to acquire point cloud data of curved skin and frame structure through 3D scanning equipment, and to perform noise reduction, simplification and reconstruction processing on the point cloud data to obtain a 3D real scan model that reflects the actual shape of the object. The stress area positioning module, based on the three-dimensional real scan model, identifies stress concentration points in the connection area between the curved skin and the frame structure, and determines the initial area for hole distribution based on the distribution density of the stress concentration points and the boundary coordinates of the connection area. The candidate hole position generation module is used to generate a candidate hole position set within the three-dimensional coordinate range of the initial region, in combination with the specification parameters of the fastener. The candidate hole position set includes the center coordinates of the candidate hole position and the corresponding hole diameter for each fastener. The specification parameters include the fastener diameter, head diameter and minimum installation spacing. The hole position optimization and verification module performs spatial interference verification on the candidate hole positions based on the center coordinates of the candidate hole positions in the candidate hole position set, and removes the candidate hole positions that do not meet the requirements, thereby obtaining a set of fastener hole positions that meet the assembly requirements; the spatial interference verification refers to verifying whether the distance between adjacent hole positions is not less than the minimum installation distance.

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