Continuous fiber composite 3D printing path planning, manufacturing method and device

Abstract

The application belongs to the technical field of composite material additive manufacturing, and discloses a continuous fiber composite material 3D printing path planning method, a manufacturing method and a device, wherein the path planning method comprises the following steps: acquiring performance vector information of any unit node of a model part; determining a construction direction of the model part, and reorienting the unit node information; determining point cloud information of a generated support part; establishing and assigning corresponding data information of a grid point; solving a printing direction vector field with the printing direction of the model part being consistent with the direction of the first vector information as an optimization target, generating a control field and a curved surface layer; and generating a composite material printing path trajectory of the model part and a resin printing path trajectory of the support part. The application can fully utilize the axial reinforcement effect of fibers by using the advantages of robot 3D printing technology, effectively improve the required performance of a formed part, and realize the integration of design and forming.

Description

Technical Field

[0001] This invention belongs to the technical field of additive manufacturing of composite materials, and more specifically, relates to a path planning, manufacturing method and apparatus for 3D printing of continuous fiber composite materials. Background Technology

[0002] Continuous fiber composites possess excellent properties such as high specific strength, high specific stiffness, low density, high fatigue resistance, and high seismic resistance, making them widely used in aerospace, automotive manufacturing, and construction. 3D printing technology not only enables the integrated design and molding of continuous fiber composite parts but also allows for precise shape and property control during the molding process, regardless of model complexity, offering significant advantages over traditional methods.

[0003] Continuous fiber composites possess high axial strength and modulus, as well as anisotropy. Only by fully leveraging the axial reinforcing effect of the fibers on the molded parts, and combining this with the advantage of 3D printing technology's ability to mold arbitrarily complex models, can we better obtain complex fiber parts that meet the needs of industrial applications. Existing 3D printing path planning methods are not specifically designed for continuous fibers, making it difficult to fully utilize the axial reinforcing effect of the fibers. Furthermore, path design is primarily concentrated in a two-dimensional plane, which severely limits the ability to place fibers along the performance-enhancing path. Summary of the Invention

[0004] To address the aforementioned deficiencies or improvement needs of existing technologies, this invention provides a continuous fiber composite material 3D printing path planning, manufacturing method, and apparatus. It solves the problem that existing 3D printing path planning methods do not specifically design for continuous fibers, making it difficult to fully utilize the axial reinforcement effect of fibers. The invention proposes designing fiber trajectories based on the direction requiring performance enhancement, which can better leverage the axial reinforcement effect of fibers. Furthermore, the use of curved surface deposition enriches the forming direction of the model, realizing the conversion from planar printing to curved surface printing, and further improving the performance of the molded parts.

[0005] To achieve the above objectives, according to one aspect of the present invention, a path planning method for 3D printing of continuous fiber composite materials is provided, comprising:

[0006] S1. Based on the three-dimensional model of the part to be printed, obtain the performance vector information of any unit node in the model, wherein the performance vector information includes a first vector information that needs to be enhanced in terms of performance and a second vector information that is perpendicular to the direction of the first vector information.

[0007] S2, based on the second vector information, determine the construction direction of the model part on the printing platform, and obtain the position information and performance vector information of any unit node updated based on the construction direction;

[0008] S3, based on the construction direction, determine the surfaces that need to be supported in the model and generate point cloud information of the supporting parts;

[0009] S4. Establish grid points based on the bounding box of the model part. Based on the updated position information, performance vector information and point cloud information of any unit node, assign corresponding data information to any grid point.

[0010] S5. Based on the data information of the grid points, with the printing direction of the model part being consistent with the direction of the first vector information as the optimization objective, solve the printing direction vector field of the model part and the support part, and generate the control field and surface layer of the model part and the support part.

[0011] S6 generates the composite material printing path trajectory for the model part and the resin printing path trajectory for the support part for any curved surface layer.

[0012] According to the continuous fiber composite material 3D printing path planning method provided by the present invention, the performance vector information in S1 includes stress performance vector information. The stress performance vector information of any unit node is obtained by performing finite element simulation on the model part under load. The first vector information is the maximum principal stress vector, and the second vector information is the minimum principal stress vector.

[0013] According to the continuous fiber composite material 3D printing path planning method provided by the present invention, the specific steps in S2 for determining the construction direction of the model part on the printing platform based on the second vector information are as follows:

[0014] The average second vector is obtained by summing the second vector information of all unit nodes.

[0015] The direction of the average second vector is taken as the construction direction, and the construction direction is made to coincide with the Z direction of the printing platform;

[0016] In S2, the position information and performance vector information of any unit node updated based on the construction direction are obtained, specifically as follows:

[0017] Construction direction Rotate to the positive Z direction, and reorient the position information of any element node and the first vector information based on the rotation matrix. The reorientation rotation matrix is:

[0018] R(θ b ) = R Z (-ψ b )R X (θ b )R Z (ψ b );

[0019] In the formula, R Z (ψ b () is the axis of rotation Rotate around the Z-axis A rotation matrix that makes the rotation axis coincide with the X-axis. To construct the rotation angle of the direction, R X (θ b Rotate the model data around the X-axis by θ b The rotation matrix.

[0020] According to the continuous fiber composite material 3D printing path planning method provided by the present invention, S3 specifically includes:

[0021] Read the initial triangular facet information of the model part, and obtain the reoriented triangular facet information based on the construction direction;

[0022] Based on the reoriented triangular facet information, the normal vectors of the triangular facets are traversed, and triangular facets with normal vector Z direction values ​​less than preset values ​​are regarded as triangular facets to be supported.

[0023] The point cloud of the triangular facet to be supported is generated by projecting it in the Z direction and performing cyclic triangulation.

[0024] The point cloud of the triangular facet to be supported is pushed outward along the negative Z-axis to form the initial support point cloud;

[0025] The position information of the unit nodes in the model part is traversed, and the point cloud within the first preset distance neighborhood of any unit node is removed from the initial support point cloud to obtain the point cloud information of the support part.

[0026] The continuous fiber composite material 3D printing path planning method provided by the present invention further includes, after S2 and before S5:

[0027] Vector incompatibility processing is performed on the model. The vector incompatibility processing methods include at least one of directional turbulence processing, directional fuzzing processing based on Prim's algorithm, and vector field extrapolation based on Direchlet's energy method.

[0028] According to the continuous fiber composite material 3D printing path planning method provided by the present invention, S5 specifically includes:

[0029] An optimization model for the printing direction vector field of the model part is established. The optimization objectives are the perpendicularity between the printing direction vector field and the first vector field, and the smoothness of the printing direction vector field. The initial optimization value is the second vector field. Based on this optimization model, the printing direction vector field of the model part is solved.

[0030] Based on the printing direction vector field of the model part, the printing direction vector field of the support part is obtained by extrapolation and normalization using the energy minimization optimization method;

[0031] By integrating the printing direction vector field information of the model part and the support part, a first control field optimization model for the model part and the support part is established. The objective function is the coincidence degree between the gradient of the first control field and the printing direction vector field. The constraints include divergence constraints, monotonically increasing constraints of the construction direction control field, initial layer bottom surface constraints, and deposition thickness constraints. Solving this optimization model yields the first control field containing the model part and the support part.

[0032] A preset deposition thickness is selected to divide the first control field isosurface, and the curved surface layers of the model part and the support part are obtained at the same time.

[0033] According to the continuous fiber composite material 3D printing path planning method provided by the present invention, the composite material printing path trajectory of the generated model part in S6 specifically includes:

[0034] A third orthogonal vector field is generated based on the first vector field and the printing direction vector field of the model part. A second control field optimization model is established based on the third orthogonal vector field, where the objective function is the coincidence degree between the gradient of the second control field and the third orthogonal vector field, and the constraint condition is the divergence constraint condition. Solving the optimization model yields the second control field of the model part.

[0035] Based on the second control field, isosurfaces are divided according to the preset continuous fiber spacing to obtain an auxiliary curved surface layer;

[0036] Intersect the auxiliary curved surface layer with the curved surface layer to obtain the composite material printing path trajectory of any curved surface layer.

[0037] According to another aspect of the present invention, a method for 3D printing of continuous fiber composite materials is provided, which is based on the continuous fiber composite material 3D printing path planning method described in any of the above claims, and prints the model part and the support part based on the generated composite material printing path trajectory and the resin printing path trajectory.

[0038] According to the continuous fiber composite material 3D printing manufacturing method provided by the present invention, the extrusion amount of the composite material during the printing process of the model part is specifically as follows:

[0039]

[0040] E fiber =l p ;

[0041] Among them, e matrix E represents the resin extrusion amount. fiber For continuous fiber extrusion, w is the linewidth, t is the layer thickness, and D is the thickness. fiber d is the diameter of the fiber bundle. matrix The diameter of the resin matrix filament bundle, lp This is the print length.

[0042] According to another aspect of the present invention, a path planning device for 3D printing of continuous fiber composite materials is provided, comprising:

[0043] The performance vector analysis module is used to obtain the performance vector information of any unit node in the model based on the three-dimensional model of the part to be printed. The performance vector information includes first vector information that needs to be enhanced in terms of performance and second vector information that is perpendicular to the direction of the first vector information.

[0044] The reorientation module is used to determine the construction direction of the model part on the printing platform based on the second vector information, and to obtain the updated position information and performance vector information of any unit node based on the construction direction;

[0045] The support portion acquisition module is used to determine the surfaces that need to be supported in the model portion based on the construction direction and generate point cloud information of the support portion;

[0046] The grid point creation module is used to create grid points based on the bounding box of the model. Based on the updated position information, performance vector information and point cloud information of any unit node, it assigns corresponding data information to any grid point.

[0047] The surface layer generation module is used to solve the printing direction vector field of the model part and the support part based on the data information of the grid points, with the printing direction of the model part being consistent with the direction of the first vector information as the optimization objective, and to generate the control field and surface layer of the model part and the support part.

[0048] The path trajectory generation module is used to generate composite material printing path trajectories for the model part and resin printing path trajectories for the support part for any curved surface layer.

[0049] Overall, compared with the prior art, the continuous fiber composite material 3D printing path planning, manufacturing method, and apparatus provided by this invention offer the following advantages:

[0050] 1. A continuous fiber printing path planning and design based on performance enhancement needs is proposed. Specifically, based on performance vector analysis, the printing direction vector field is solved by model reorientation, support part point cloud generation, mesh point establishment, and optimization objective of aligning the printing direction of the model part with the direction of the first vector information. This can obtain the fiber printing path trajectory that is consistent with the direction of performance enhancement. This optimizes the printing direction of continuous fibers to fully utilize the fiber axial reinforcement effect and can better divide the curved layer. The use of curved layer deposition method increases the degree of design freedom, which is conducive to better leveraging the fiber axial reinforcement effect and improving the performance of the molded part.

[0051] 2. By utilizing the multi-degree-of-freedom characteristics of 3D printing, the design freedom is increased. Thus, by adopting a curved layer deposition method, the fiber printing path trajectory of each curved layer is basically parallel to the trajectory line of the principal stress vector that needs to be enhanced, which can better exert the axial reinforcement effect of the fiber and improve the relevant properties of the molded part.

[0052] 3. Establishing and assigning grid point data information can effectively integrate the position and vector information of the model and support parts, facilitating the establishment of optimization models and enabling simultaneous optimization solutions for both the model and support parts;

[0053] 4. A stress adaptation path planning design based on curved layer deposition was carried out for continuous fiber composite materials, which made full use of the characteristics of continuous fiber composite materials and improved the continuity and smoothness of the path. Attached Figure Description

[0054] Figure 1 This is a flowchart of the continuous fiber composite material 3D printing path planning method provided by the present invention;

[0055] Figure 2 This is a flowchart of the stress adaptation path planning and manufacturing method for 3D printing of continuous fiber reinforced composite material robots provided by the present invention;

[0056] Figure 3 This is a schematic diagram of the load constraint of the part model provided by the present invention;

[0057] Figure 4 This is a schematic diagram of the maximum principal stress vector field distribution provided by the present invention;

[0058] Figure 5 This is a schematic diagram of the maximum principal stress vector field distribution after reorientation provided by the present invention;

[0059] Figure 6 This is a schematic diagram of the reoriented model triangulation provided by the present invention;

[0060] Figure 7 This is a schematic diagram of the detected support area provided by the present invention;

[0061] Figure 8 This is a schematic diagram of the vertex point cloud of the subdivided support triangle provided by the present invention;

[0062] Figure 9 This is a schematic diagram of the processed support point cloud provided by the present invention;

[0063] Figure 10 This is a schematic diagram of the maximum principal stress vector field distribution based on grid points provided by the present invention;

[0064] Figure 11 This is a schematic diagram of the maximum principal stress vector field distribution after directional turbulence processing provided by the present invention;

[0065] Figure 12 This is a schematic diagram of the maximum principal stress vector field distribution after directional fuzzification provided by the present invention;

[0066] Figure 13 This is a schematic diagram of the maximum principal stress vector field distribution after extrapolation and normalization provided by the present invention;

[0067] Figure 14 This is a schematic diagram of the printed direction vector field distribution of the model provided by the present invention;

[0068] Figure 15 This is a schematic diagram of the printed direction vector field distribution of the model part and the support part provided by the present invention;

[0069] Figure 16 This is a schematic diagram of the surface layer division of the model part provided by the present invention;

[0070] Figure 17 This is a schematic diagram of the curved surface layer division of the support portion provided by the present invention;

[0071] Figure 18 This is a schematic diagram of the third orthogonal vector field distribution provided by the present invention;

[0072] Figure 19 This is a schematic diagram of the auxiliary curved surface layer division provided by the present invention;

[0073] Figure 20 This is a schematic diagram of the intersection trajectory lines of the partial curved surface layer and the auxiliary curved surface layer of the model provided by the present invention;

[0074] Figure 21 This is a schematic diagram of the Z-axis projection of the single-curved surface layer provided by the present invention;

[0075] Figure 22 This is a schematic diagram of the fiber printing path trajectory optimization process provided by the present invention. Detailed Implementation

[0076] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0077] Please see Figure 1This invention provides a continuous fiber composite material 3D printing path planning method. This method, during the 3D forming process of the part to be printed, rationally plans the fiber printing path based on the performance characteristic distribution of the complex model, such as the mechanical property distribution, ensuring that the fiber orientation is substantially parallel to the direction requiring performance enhancement. This leverages the axial performance advantages of the fibers to guarantee better forming performance. The method includes:

[0078] S1. Based on the 3D model of the part to be printed, obtain the performance vector information of any unit node in the model. The model is divided into multiple unit nodes, which can be determined through finite element simulation. The performance vector information of any unit node reflects the relevant performance at that unit node. The performance vector information includes a first vector information that needs performance enhancement and a second vector information perpendicular to the direction of the first vector information. The first vector information may include direction information, that is, the direction information that needs performance enhancement at the unit node. The printing path of the composite material can be planned according to the direction information, so that the continuous fiber axis is printed as much as possible along the direction of the first vector information, thereby utilizing the fiber axis advantage to enhance performance. The second vector information may also include direction information, that is, the direction of the second vector information is perpendicular to the direction of the first vector information, which is used to determine the construction direction when printing the model part.

[0079] S2, based on the second vector information, determine the construction direction of the model part on the printing platform, and obtain the updated position information and performance vector information of any unit node based on the construction direction; that is, reorient the model part according to the direction of the second vector information, and determine the construction direction, which is to determine the placement direction of the model part on the printing platform; the direction of the second vector information can be placed along the Z-axis of the printing platform, so that the fiber axis is parallel to the direction of the first vector information during the forming and printing process of the model part along the Z-axis. After determining the construction direction, it is necessary to reorient the position information and performance vector information of the unit nodes to determine the position and vector information under the new placement posture.

[0080] S3. Based on the construction direction, determine the surfaces of the model that need to be supported and generate point cloud information of the supporting parts; for complex models, there may be suspended surfaces that need to be supported during the printing process. The surfaces that need to be supported after the model is reoriented can be determined first, and the point cloud information of the supporting parts can be generated accordingly. During the printing process, the supporting parts are printed synchronously according to the point cloud information of the supporting parts.

[0081] S4. Grid points are established based on the bounding box of the model. Based on the updated position information, performance vector information and point cloud information of any unit node, the corresponding data information is assigned to any grid point. Establishing grid points facilitates printing according to the grid point data information.

[0082] S5, based on the grid point data, with the goal of aligning the printing direction of the model part with the direction of the first vector information, the printing direction vector field of the model part and the support part is solved, and the control field and surface layer of the model part and the support part are generated. By establishing a printing direction vector field optimization model, with the goal of aligning the printing direction of the model part with the direction of the first vector information, the printing direction vector field of the model part can be optimized and solved. Based on the printing direction vector field of the model part, the printing direction vector field of the support part can be obtained. Then, by combining the printing direction vector fields of the model part and the support part, the control field can be generated, and the surface layer can be determined. This method for determining the printing direction vector field, control field, and surface layer not only optimizes the printing direction of continuous fibers to fully utilize the axial reinforcement effect of the fibers, but also better divides the surface layer. The use of the surface layer deposition method increases the design freedom, which is conducive to better utilizing the axial reinforcement effect of the fibers and improving the required performance of the molded part.

[0083] S6 generates the composite material printing path trajectory of the model part and the resin printing path trajectory of the support part for any curved surface layer; the composite material printing path of the model part and the resin printing path of the support part can be obtained based on the control field of the model part and the curved surface layer of the support part.

[0084] Furthermore, the performance vector information in S1 includes stress performance vector information. The stress performance vector information of any unit node is obtained through finite element simulation of the model under load. The first vector information is the maximum principal stress vector, and the second vector information is the minimum principal stress vector. That is, finite element simulation of the three-dimensional model under load can be performed on the actual application scenario of the part to be printed. Through simulation, the stress performance vector information of any unit node can be obtained, that is, the maximum principal stress vector and the minimum principal stress vector at any unit node can be obtained. The maximum principal stress vector indicates the direction in which performance enhancement is needed at that unit node. Based on the stress performance vector information, printing path planning and manufacturing can be performed to obtain a molded part with enhanced stress performance.

[0085] Furthermore, this invention is not only applicable to fiber orientation design under stress fields, but also to fiber orientation design considering thermal conductivity, electromagnetic properties, biological properties, etc. By assigning different weights to different properties and controlling the vector direction, the fiber orientation can be designed to obtain components that meet the performance requirements.

[0086] The performance vector information can include at least one of stress performance vector information, thermal conductivity vector information, electromagnetic performance vector information, and biological performance vector information. Specifically, taking thermal conductivity vector information as an example, thermal field simulation can be performed on the model. By analyzing the heating conditions at the unit nodes, the first vector information requiring thermal conductivity enhancement at the unit nodes can be determined, and then the second vector information can be determined. When the performance vector information includes multiple performance vector information, different weights can be assigned to different performance vector information according to actual needs. The total first vector information is determined by the sum of the weights of the first vector information corresponding to each performance vector information, and then the total second vector information is determined based on the total first vector information.

[0087] Furthermore, the present invention provides a 3D printing manufacturing method for continuous fiber composite materials. Based on the above-mentioned continuous fiber composite material 3D printing path planning method, the manufacturing method further includes, on the basis of the above-mentioned path planning method, printing the model part and the support part based on the generated composite material printing path trajectory and the resin printing path trajectory.

[0088] In some specific embodiments, taking stress performance vector information as an example, this invention provides a stress adaptation path planning and manufacturing method for 3D printing of continuous fiber reinforced composite material robots. Figure 2 The flowchart shown is for this method, which mainly includes the following steps:

[0089] (1) Perform finite element simulation of the model under load to obtain stress vector distribution information on the element nodes.

[0090] Create a part model and apply loads such as Figure 3 As shown, finite element simulation of the model under load is performed using simulation software, including but not limited to ANSYS and ABAQUS, to obtain the principal stress vector distribution information on the element nodes, such as... Figure 4 The diagram shows the distribution of the extracted maximum principal stress vector field.

[0091] Furthermore, methods for obtaining stress vector distribution information on element nodes include Euler angle transformation or stress tensor eigenvalue decomposition.

[0092] For Euler angle transformation, for example, when using ANSYS software to obtain the principal stress vector distribution information on element nodes, the simulation software exports the vector principal stress information, i.e., θ1, θ2, and θ3, and performs ZXY Euler angle transformation. The formula is:

[0093]

[0094] The corresponding column vectors are the principal stress vectors, with the three column vectors corresponding to the minimum principal stress vector, the intermediate principal stress vector, and the maximum principal stress vector, respectively.

[0095] For stress tensor eigenvalue decomposition, for example, when using ABAQUS software to obtain the principal stress vector distribution information on element nodes, the simulation software outputs a 3×3 stress tensor at the node, and eigenvalue decomposition is applied to each stress tensor:

[0096]

[0097] The three principal stresses [σ1, σ2, σ3] are determined by sorting them from largest to smallest. The eigenvectors associated with the maximum principal stress σ1 are defined as the directions of the maximum principal stresses. The eigenvectors associated with the minimum principal stress σ3 are defined as the directions of the minimum principal stresses. (2) Determine the construction direction of the model on the printing platform and redirect the model data.

[0098] Specifically, in S2, the construction direction of the model part on the printing platform is determined based on the second vector information as follows:

[0099] The average second vector is obtained by summing the second vector information of all unit nodes.

[0100] The direction of the average second vector is taken as the construction direction, and the construction direction is made to coincide with the Z direction of the printing platform.

[0101] When planning the stress adaptation path, since the direction of the minimum principal stress is perpendicular to the direction of the maximum principal stress, to ensure that the fiber bundle orientation is parallel to the direction of the maximum principal stress, the direction of the minimum principal stress needs to be set to be related to the printing direction. Specifically, based on the minimum principal stress vector information of the model, the average minimum principal stress vector is calculated, and this vector direction is used as the construction direction of the model on the printing platform. The construction direction is as follows:

[0102]

[0103] In the formula N a Let n be the set of all unit nodes. i It is a single unit node.

[0104] Furthermore, the build direction refers to the orientation of the model on the printing platform. The build direction needs to be rotated to the positive Z-axis (0,0,1), and the model data needs to be reoriented. The model data includes node position information and performance vector information.

[0105] Furthermore, the specific steps for reorienting the model data, namely obtaining the updated position information and performance vector information of any unit node based on the construction direction, are as follows:

[0106] Set the construction direction Coordinates are (x b0 ,y b0 ,z b0 If the coordinates of the rotation axis are , then the coordinates of the rotation axis are Rotation angle is

[0107] Rotate the axis of rotation around the Z-axis To align the rotation axis with the X-axis, the rotation matrix is:

[0108]

[0109] Rotate the model data around the X-axis by θ b The rotation matrix is:

[0110]

[0111] Finally, to rotate the model data back to its previous position, it is necessary to multiply by the rotation matrix R. Z (-ψ b ).

[0112] The total rotation matrix is ​​as follows:

[0113] R(θ b ) = R Z (-ψ b )R X (θ b )R Z (ψ b );

[0114] Reorientation can be achieved by left-multiplying the node position information and performance vector information by the rotation matrix, such as... Figure 5 The diagram shows the distribution of the maximum principal stress vector field after reorientation.

[0115] (3) Search for the surfaces that need to be supported according to the construction direction in step (2) and generate a support point cloud.

[0116] Read the initial triangular facet information of the model, and reorient the initial triangular facet information as in step (2). The triangulation diagram of the model after reorientation is shown below. Figure 6 As shown.

[0117] Furthermore, the supporting triangular facets are inspected, with the suspension angle set to θ. h Based on the reoriented triangular facet information, the normal vectors of the triangular facets are traversed, and the Z-direction value of the normal vector is set to a value less than a preset value, such as -sin(θ). h The triangular facets that are considered to require additional support are referred to as the triangular facets to be supported, such as... Figure 7 The diagram shows the detected area to be supported.

[0118] Further, the point cloud of the supporting facets is generated for the detected triangular facets to be supported. The steps are as follows: the triangular facets to be supported are projected in the Z-direction and subjected to iterative Delaunay triangulation. In each iteration, the midpoints of the edges of the triangular facets are added. After triangulation, the edge length of the triangular facets is checked; if it is less than the subdivision precision, the iteration stops. The point cloud composed of the vertices of the subdivided triangular facets to be supported is shown below. Figure 8 As shown, the point cloud of the triangular facet to be supported is generated.

[0119] Further, point cloud generation for the supporting portion is performed. The vertex point cloud of the triangular facet to be supported is pushed outward along the negative Z-axis to form the initial supporting point cloud, which can be pushed outward to Z=0. The position information of the unit nodes in the model part of step (2) is traversed, and the point cloud within the first preset distance neighborhood of any unit node is removed from the initial supporting point cloud, that is, the point cloud contained in the unit node position information δ distance-neighborhood is removed. The processed supporting point cloud is as follows: Figure 9 As shown, the point cloud information of the supporting part can be determined.

[0120] (4) Create mesh points based on the model bounding box, and assign model information, support information and stress vector information to the mesh points.

[0121] Based on the model's bounding box, i.e. [X min ,X max ,Y min ,Y max Z min Z max And the grid point division accuracy is used to establish grid points.

[0122] Furthermore, the established grid points are assigned model information, support information, or no information. Based on the unit node position information in step (2) and the point cloud information of the support part in step (3), model-support point cloud position information is established. The nearest unit node or support part point cloud in the second preset distance neighborhood of any grid point is searched, that is, the δ distance-neighborhood of the grid point is searched. The nearest model-support point in the neighborhood is found, and the unit node information (i.e., model information) or support point cloud information (i.e., support information) of any grid point is assigned accordingly. The maximum principal stress vector information of the grid point in the model part is also assigned. If no unit node or support part point cloud is found in the neighborhood, that is, no model-support point is found in the neighborhood, the grid point is assigned no information, that is, the grid point is neither a point in the model part nor a point in the support part.

[0123] Furthermore, the mesh points, which have been given model information, are assigned first vector information, such as the maximum principal stress vector information, as follows: Figure 10 The diagram shows the distribution of the first vector field based on grid points, such as the maximum principal stress vector field.

[0124] (5) Perform vector incompatibility processing on the model to improve manufacturability. Vector incompatibility processing methods include at least one of directional turbulence processing, directional fuzzing processing based on Prim's algorithm, and vector field extrapolation based on Direchlet's energy method.

[0125] To improve the manufacturability of printing, it is necessary to handle the incompatibility of the first vector field based on grid points, such as the maximum principal stress vector field. In some specific embodiments, the vector incompatibility handling of the model part can be carried out sequentially through directional turbulence processing, directional fuzzing processing based on the Prim algorithm, and vector field extrapolation based on the Direchlet energy method. Taking stress path planning as an example, the specific steps are as follows:

[0126] The maximum principal stress vector field is subjected to directional turbulence processing. Adjacent vector pairs whose directions undergo turbulence changes are retrieved, with compatibility conditions set as follows:

[0127]

[0128] In the formula, N M Let n be the set of adjacent node pairs in the grid points of the model. i n j This represents adjacent node pairs, where η is the turbulence incompatibility precision. Adjacent vector pairs that do not meet the compatibility conditions are discarded. The schematic diagram of the maximum principal stress vector field distribution after directional turbulence processing is shown below. Figure 11 As shown.

[0129] Furthermore, the maximum principal stress vector field is subjected to directional ambiguity processing. Since the direction of the maximum principal stress can have both positive and negative solutions, adjacent vector pairs may have completely opposite directions; this is directional ambiguity. Without directional ambiguity processing, manufacturability would be significantly affected. Prim's algorithm is used for directional ambiguity processing, and a minimum Euclidean spanning tree is constructed. The edge weights in the directional ambiguity processing are set as follows:

[0130]

[0131] In the formula M M Let m be any set of node pairs in the model part. i m j Represents any pair of nodes, |m i m j | represents the distance between node pairs. Following Prim's algorithm, the minimum tree is traversed and direction is propagated, setting vectors with opposite directions to be of the same direction. A schematic diagram of the maximum principal stress vector field distribution after direction fuzzification is shown below. Figure 12 As shown.

[0132] Furthermore, the vector field of the incompatible region is extrapolated and normalized using the Dirichlet energy minimization optimization method. The vector field extrapolation optimization objective is:

[0133]

[0134] The constraint condition is the maximum principal stress vector field in the compatible region after directional turbulence treatment. The schematic diagrams of the extrapolated and normalized maximum principal stress vector field distributions are shown below. Figure 13 As shown.

[0135] (6) Solve the printing direction vector field of the model and support parts based on the grid point data information, and generate the control field and surface layer. The specific process of step (6) is as follows: establish an optimization model of the printing direction vector field of the model part, generate the printing direction vector field of the support part through extrapolation, integrate the printing direction vector field information of the model part and the support part, establish an optimization model of the control field of the model part and the support part, simultaneously optimize and solve the control field of the model part and the support part, and generate the surface layer through isosurface division. Specifically:

[0136] Establish a printing direction vector field optimization model for the model part, and set the optimization objective as the perpendicularity E between the printing direction vector field and the first vector field, i.e., the maximum principal stress vector field. pcz And the smoothness E of the printing direction vector field. pph The optimization objective formula is as follows:

[0137]

[0138] In the formula, M is the set of grid points in the model. For grid point m i The printing direction vector, w cz and w ph The weights for verticality and smoothness are respectively set, and the initial values ​​are set to the second vector field, i.e., the minimum principal stress vector field. The optimization model is solved to obtain the printing direction vector field of the model part, such as... Figure 14 The image shows a schematic diagram of the printed direction vector field distribution of the model.

[0139] Furthermore, based on the printing direction vector field of the model part, the printing direction vector field of the support part is extrapolated and normalized using the Dirichlet energy minimization optimization method, with the optimization objective being:

[0140]

[0141] In the formula N MS Given the set of adjacent node pairs in the mesh of the model and support parts, and the constraint condition being the printing direction vector field of the model part, the extrapolation and normalization yield the printing direction vector field distributions of the model and support parts as follows: Figure 15 As shown.

[0142] Furthermore, by integrating the printing direction vector field information of the model and support parts, a first control field optimization model for the model and support parts is established. The objective function is the degree of coincidence between the gradient of the first control field and the printing direction vector field, and the objective function formula is:

[0143]

[0144] In the formula, MS is the set of mesh points for the model part and the support part, and G p As the first control field, The first control field at grid point ms i gradient at, For grid points ms i The printing direction vector at that location.

[0145] Furthermore, the constraints include divergence constraints, monotonically increasing constraints of the construction direction control field, initial layer bottom surface constraints, and deposition thickness constraints, as expressed in the following formula:

[0146]

[0147] The specific steps for setting constraints are as follows:

[0148] Setting divergence constraints to limit the average curvature of the surface layer can prevent printhead interference and collisions and limit the turning radius during printing, thus improving manufacturability. The formula is as follows:

[0149]

[0150] In the formula H pm This represents the maximum average curvature of the surface layer.

[0151] To prevent the generated surface layers from interleaving, a monotonically increasing constraint condition is set for the construction direction control field. This is achieved by calculating the first-order difference along the third dimension, i.e., the Z-axis, as shown in the following formula:

[0152] G p (xi,yi,zi)-G p (xi,yi,zi+1)<=0;

[0153] To set initial layer bottom surface constraints, the first layer should be printed horizontally when printing the bottom surface, meaning the control field value of the bottom surface should be 0. The formula is as follows:

[0154]

[0155] MS in the formula z＝0 This represents the set of grid points located on the bottom surface.

[0156] Set a deposition thickness constraint condition to ensure that the reciprocal of the field gradient modulus reflects the deposition thickness at that point, and set the deposition thickness range to [t]. min ,t max The preset deposition thickness is t. a The deposition thickness constraint is:

[0157]

[0158] Furthermore, the established optimization model is solved to obtain the first control field, which includes the model part and the support part. A preset deposition thickness t is selected. a By performing isosurface partitioning of the first control field, the surface layers of both the model and support parts can be obtained simultaneously. A schematic diagram of the surface layer partitioning for the model and support parts is shown below. Figure 16 and Figure 17 As shown.

[0159] (7) Generate the composite material printing path trajectory of the model part and the resin printing path trajectory of the support part.

[0160] The specific steps for generating the composite material printing path trajectory for the model are as follows:

[0161] A third orthogonal vector field is generated based on the first vector field of the model, namely the maximum principal stress vector field and the printing direction vector field, such as... Figure 18 As shown, the second control field G is established from this third orthogonal vector field. q The optimized model is as follows:

[0162]

[0163] The first equation is a divergence constraint condition, used to limit the turning radius of the fiber printing path, improve path smoothness, and reduce fiber damage. In the equation, H... qm The first equation represents the maximum average curvature of the path trajectory. The second equation is the objective function, which is the degree of coincidence between the gradient of the second control field and the third orthogonal vector field, where q... m It is the third orthogonal vector at some nodes of the model.

[0164] Further, the established optimization model is solved to obtain the second control field of the model part. Isosurfaces are generated and intersected with the surface layer generated in step (6) to obtain trajectory lines. Specifically, the isosurfaces of the second control field are divided according to the fiber spacing to obtain auxiliary surface layers such as... Figure 19 As shown.

[0165] Furthermore, the trajectory line obtained by intersecting the auxiliary surface layer and the model partial surface layer generated in step (6) is the composite material printing path trajectory, such as... Figure 20 As shown.

[0166] Furthermore, composite material printing path trajectory optimization is performed, generating the optimized composite material printing path trajectory using a contour offset and stress parallel strategy. Taking a single curved surface layer as an example, the specific optimization steps are as follows:

[0167] Select a single surface layer, such as Figure 21 The diagram shown is a schematic diagram of a single curved surface layer projected in the Z direction. Figure 22 The diagram illustrates the fiber printing path trajectory optimization process. The first contour bias layer is biased to form a second and third contour bias layer. The first and second contour bias layers are retained. The intersection point is obtained by intersecting the third contour bias layer with the fiber trajectory line. Figure 22 As shown in intersection points 1 and 2, the third contour bias layer is removed, and the area between the first and third contour bias layers is also removed, as shown in the figure. Figure 22 As shown in the diagram, the intersecting line segments are removed. Finally, the intersection points are connected to improve the continuity of the path, as shown in the diagram. Figure 22 Intersection points 1 and 2 are connected. Simultaneously, corner optimization is performed to reduce fiber damage during printing.

[0168] Furthermore, the resin printing path trajectory of the support part is planned, and the filling method of the resin printing path trajectory of the support part includes, but is not limited to, straight line filling, triangular filling, concentric filling, grid filling, and spiral icosahedral filling.

[0169] (8) Based on the co-extrusion process, the deposition thickness is controlled and the resin extrusion amount is calculated.

[0170] Co-extrusion process is used to control the deposition thickness of curved layers. In the co-extrusion process, fiber filaments and resin materials are heated and impregnated inside the print head and then extruded together for printing. The deposition thickness can be changed by adjusting the amount of resin extruded.

[0171] Furthermore, the resin extrusion amount e matrix The calculation formula is:

[0172]

[0173] Continuous fiber extrusion amount E fiber The formula is: E fiber =l p ;

[0174] In the formula, w is the line width, t is the layer thickness, and D is the layer thickness. fiber d is the diameter of the fiber bundle. matrix The diameter of the resin matrix filament bundle, l p This is the print length.

[0175] (9) Model printing based on a robot printing platform.

[0176] The robotic printing platform's end effector comprises two printing nozzles: a fiber printing nozzle based on a co-extrusion process and a resin printing nozzle based on an FDM process. The fiber printing nozzle based on the co-extrusion process includes two feed ports: one for feeding fiber tow and the other for feeding the resin matrix. The fiber tow includes, but is not limited to, dry fibers such as carbon fiber, glass fiber, and boron fiber, or fiber-reinforced prepregs.

[0177] The resin printhead is used to print the support portion, and the material is a water-soluble resin or an easily separable resin, including but not limited to PVA, AquaSys GP, HIPS, and BVOH. Furthermore, when using water-soluble materials, the support portion can be filled with a porous structure, such as a spiral icosahedral filling method, which can increase the contact area and improve pore connectivity, thereby increasing the dissolution rate.

[0178] Furthermore, the present invention also provides a continuous fiber composite material 3D printing path planning device, which is used to implement the continuous fiber composite material 3D printing path planning method described in any of the above claims. This device can be understood in conjunction with the above method, and includes:

[0179] The performance vector analysis module is used to obtain the performance vector information of any unit node in the model based on the three-dimensional model of the part to be printed. The performance vector information includes first vector information that needs to be enhanced in terms of performance and second vector information that is perpendicular to the direction of the first vector information.

[0180] The reorientation module is used to determine the construction direction of the model part on the printing platform based on the second vector information, and to obtain the updated position information and performance vector information of any unit node based on the construction direction;

[0181] The support portion acquisition module is used to determine the surfaces that need to be supported in the model portion based on the construction direction and generate point cloud information of the support portion;

[0182] The grid point creation module is used to create grid points based on the bounding box of the model. Based on the updated position information, performance vector information and point cloud information of any unit node, it assigns corresponding data information to any grid point.

[0183] The surface layer generation module is used to solve the printing direction vector field of the model part and the support part based on the data information of the grid points, with the printing direction of the model part being consistent with the direction of the first vector information as the optimization objective, and to generate the control field and surface layer of the model part and the support part.

[0184] The path trajectory generation module is used to generate composite material printing path trajectories for the model part and resin printing path trajectories for the support part for any curved surface layer.

[0185] Furthermore, the present invention also provides a continuous fiber composite material 3D printing path planning and manufacturing system. This system includes the aforementioned continuous fiber composite material 3D printing path planning and manufacturing device, and also includes a robotic printing platform. Specifically, the robotic printing platform may include a multi-axis robotic arm, a printing nozzle, and a forming platform. The printing nozzle is mounted at the end of the multi-axis robotic arm, which drives the printing nozzle to perform multi-degree-of-freedom motion. The printing nozzle is used to print the part to be printed on the forming platform. The robotic printing platform is used to implement the continuous fiber composite material 3D printing path planning and manufacturing method described above under the control of the aforementioned continuous fiber composite material 3D printing path planning and manufacturing device.

[0186] This invention provides a stress-adaptive path planning and manufacturing method for robot 3D printing of continuous fiber reinforced composite materials. This method utilizes the stress distribution characteristics of parts under load constraints, combined with the high axial strength and modulus of continuous fiber reinforced composite materials, to achieve the alignment of fiber orientation with the stress direction. Furthermore, by leveraging the advantages of multi-degree-of-freedom 3D printing technology, it enables the conversion from planar printing to curved surface printing. This method can fully utilize the axial reinforcement effect of the fibers, better leverage the axial reinforcement effect of the fibers, improve the mechanical properties of the molded parts, and achieve integration from design to molding.

[0187] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A path planning method for 3D printing of continuous fiber composite materials, characterized in that, include: S1. Based on the three-dimensional model of the part to be printed, obtain the performance vector information of any unit node in the model, wherein the performance vector information includes a first vector information that needs to be enhanced in terms of performance and a second vector information that is perpendicular to the direction of the first vector information. S2, based on the second vector information, determine the construction direction of the model part on the printing platform, and obtain the position information and performance vector information of any unit node updated based on the construction direction; S3, based on the construction direction, determine the surfaces that need to be supported in the model and generate point cloud information of the supporting parts; S4. Establish grid points based on the bounding box of the model part. Based on the updated position information, performance vector information and point cloud information of any unit node, assign corresponding data information to any grid point. S5. Based on the data information of the grid points, with the printing direction of the model part being consistent with the direction of the first vector information as the optimization objective, solve the printing direction vector field of the model part and the support part, and generate the control field and surface layer of the model part and the support part. S6 generates the composite material printing path trajectory for the model part and the resin printing path trajectory for the support part for any curved surface layer. In S2, the construction direction of the model part on the printing platform is determined based on the second vector information as follows: The average second vector is obtained by summing the second vector information of all unit nodes. The direction of the average second vector is taken as the construction direction, and the construction direction is made to coincide with the Z direction of the printing platform; In S2, the position information and performance vector information of any unit node updated based on the construction direction are obtained, specifically as follows: Construction direction Rotate to the positive Z direction, and reorient the position information of any element node and the first vector information based on the rotation matrix. The reorientation rotation matrix is: ； In the formula, For the axis of rotation Rotation around the Z-axis A rotation matrix that makes the rotation axis coincide with the X-axis. To construct the rotation angle of the direction, Rotate the model data around the X-axis The rotation matrix.

2. The continuous fiber composite material 3D printing path planning method as described in claim 1, characterized in that, The performance vector information in S1 includes stress performance vector information. The stress performance vector information of any element node is obtained by performing finite element simulation on the model under load. The first vector information is the maximum principal stress vector, and the second vector information is the minimum principal stress vector.

3. The continuous fiber composite material 3D printing path planning method as described in claim 1, characterized in that, S3 specifically includes: Read the initial triangular facet information of the model part, and obtain the reoriented triangular facet information based on the construction direction; Based on the reoriented triangular facet information, the normal vectors of the triangular facets are traversed, and triangular facets with normal vector Z direction values ​​less than preset values ​​are regarded as triangular facets to be supported. The point cloud of the triangular facet to be supported is generated by projecting it in the Z direction and performing cyclic triangulation. The point cloud of the triangular facet to be supported is pushed outward along the negative Z-axis to form the initial support point cloud; The position information of the unit nodes in the model part is traversed, and the point cloud within the first preset distance neighborhood of any unit node is removed from the initial support point cloud to obtain the point cloud information of the support part.

4. The continuous fiber composite material 3D printing path planning method according to any one of claims 1-3, characterized in that, The following are included after S2 and before S5: Vector incompatibility processing is performed on the model. The vector incompatibility processing methods include at least one of directional turbulence processing, directional fuzzing processing based on Prim's algorithm, and vector field extrapolation based on Direchlet's energy method.

5. The continuous fiber composite material 3D printing path planning method according to any one of claims 1-3, characterized in that, S5 specifically includes: An optimization model for the printing direction vector field of the model part is established. The optimization objectives are the perpendicularity between the printing direction vector field and the first vector field, and the smoothness of the printing direction vector field. The initial optimization value is the second vector field. Based on this optimization model, the printing direction vector field of the model part is solved. Based on the printing direction vector field of the model part, the printing direction vector field of the support part is obtained by extrapolation and normalization using the energy minimization optimization method; By integrating the printing direction vector field information of the model part and the support part, a first control field optimization model for the model part and the support part is established. The objective function is the coincidence degree between the gradient of the first control field and the printing direction vector field. The constraints include divergence constraints, monotonically increasing constraints of the construction direction control field, initial layer bottom surface constraints, and deposition thickness constraints. Solving this optimization model yields the first control field containing the model part and the support part. A preset deposition thickness is selected to divide the first control field isosurface, and the curved surface layers of the model part and the support part are obtained at the same time.

6. The continuous fiber composite material 3D printing path planning method as described in claim 5, characterized in that, The composite material printing path trajectory in the generated model section of S6 specifically includes: A third orthogonal vector field is generated based on the first vector field and the printing direction vector field of the model part. A second control field optimization model is established based on the third orthogonal vector field, where the objective function is the coincidence degree between the gradient of the second control field and the third orthogonal vector field, and the constraint condition is the divergence constraint condition. Solving the optimization model yields the second control field of the model part. Based on the second control field, isosurfaces are divided according to the preset continuous fiber spacing to obtain an auxiliary curved surface layer; Intersect the auxiliary curved surface layer with the curved surface layer to obtain the composite material printing path trajectory of any curved surface layer.

7. A method for 3D printing continuous fiber composite materials, characterized in that, The continuous fiber composite material 3D printing path planning method according to any one of claims 1-6 is used to print the model part and the support part based on the generated composite material printing path trajectory and resin printing path trajectory.

8. The 3D printing manufacturing method for continuous fiber composite materials as described in claim 7, characterized in that, The specific amount of composite material extruded during the model printing process is as follows: ； ； in, e matrix This refers to the amount of resin extruded. E fiber This refers to the continuous fiber extrusion rate. w For line width, t For layer thickness, D fiber The diameter of the fiber bundle, d matrix The diameter of the resin matrix filament bundle. l p This is the print length.

9. A path planning device for 3D printing of continuous fiber composite materials, characterized in that, The method for implementing the continuous fiber composite material 3D printing path planning method according to any one of claims 1-6 includes: The performance vector analysis module is used to obtain the performance vector information of any unit node in the model based on the three-dimensional model of the part to be printed. The performance vector information includes first vector information that needs to be enhanced in terms of performance and second vector information that is perpendicular to the direction of the first vector information. The reorientation module is used to determine the construction direction of the model part on the printing platform based on the second vector information, and to obtain the updated position information and performance vector information of any unit node based on the construction direction; The support portion acquisition module is used to determine the surfaces that need to be supported in the model portion based on the construction direction and generate point cloud information of the support portion; The grid point creation module is used to create grid points based on the bounding box of the model. Based on the updated position information, performance vector information and point cloud information of any unit node, it assigns corresponding data information to any grid point. The surface layer generation module is used to solve the printing direction vector field of the model part and the support part based on the data information of the grid points, with the printing direction of the model part being consistent with the direction of the first vector information as the optimization objective, and to generate the control field and surface layer of the model part and the support part. The path trajectory generation module is used to generate composite material printing path trajectories for the model part and resin printing path trajectories for the support part for any curved surface layer.

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