WO2023005052A1

WO2023005052A1 - Continuous fiber 3d printing path planning method for fiber orientation and structure parallel optimization

Info

Publication number: WO2023005052A1
Application number: PCT/CN2021/129415
Authority: WO
Inventors: 田小永; 黄一鸣; 郑子琪; 李武丹
Original assignee: 西安交通大学
Priority date: 2021-07-30
Filing date: 2021-11-08
Publication date: 2023-02-02
Also published as: CN113442441B; CN113442441A

Abstract

A continuous fiber 3D printing path planning method for fiber orientation and structure parallel optimization. The method comprises: constructing a fiber orientation and composite material structure parallel optimization model, taking a material density and a fiber angle as design variables, and filtering same to obtain a fiber orientation and composite material structure parallel optimization structure; discretizing the complex optimization structure into structures having simple geometric shapes, abstracting sub-regions into points by using a topology idea, connecting the points according to a positional relationship between optimization structures to which the sub-regions belong, so as to form a connected graph which includes feature information of the optimization structures, and classifying path planning as searching for Hamiltonian paths in the connected graph; taking a material density value as a weight factor of a fiber angle of a unit grid, so as to obtain a fiber trajectory direction in each sub-region of the optimization structures; sequentially connecting printing paths in the sub-regions according to the Hamiltonian paths; and generating a printing code. By means of the method, an anisotropic mechanical property of a continuous-fiber-reinforced composite material is exhibited, thereby meeting the requirements of a 3D printing process.

Description

Continuous Fiber 3D Printing Path Planning Method Based on Parallel Optimization of Fiber Orientation and Structure

technical field

The invention belongs to the technical fields of structural optimization, composite materials and additive manufacturing, and specifically relates to a continuous fiber 3D printing path planning method for parallel optimization of fiber orientation and structure.

technical background

Continuous fiber reinforced composites, as an anisotropic material, are important materials for the manufacture of advanced structures. The 3D printing process of continuous fiber-reinforced composites breaks the constraints of traditional molding and laying technology on the fiber angle direction, and prints the model with path planning information, which can realize fine control and free design of fiber orientation. Using the similar principle of fused deposition modeling (FDM) technology, the fiber dry filament and thermoplastic filament are impregnated online and printed through the printing nozzle, and its mechanical properties change according to the printing angle of the fiber path. Since the mechanical properties of continuous fiber reinforced composites along the fiber direction are much better than those perpendicular to the fiber direction, the printing direction of the fiber path in the 3D printing process has a great influence on the overall performance of the component.

The 3D printing process of continuous fiber reinforced composite materials makes it possible to optimize materials and structures in parallel and integrate them into one. Although there are certain theoretical studies on the optimization design based on the anisotropy of composite materials at home and abroad, they are not closely integrated with 3D printing technology, and the integration of microscopic fiber distribution, macroscopic topological structure information and manufacturing technology contained in the optimal design is still facing challenges. Huge challenges, unable to realize the huge potential of advanced forming technology and fiber reinforced performance, lack of corresponding path planning methods.

At present, the 3D printing technology for continuous fiber reinforced composite materials is not perfect, and its path planning methods mostly use traditional FDM techniques such as grid contour filling, contour offset path filling, and mixed path filling, which fail to fully consider continuous fiber reinforced composite materials. anisotropic mechanical properties. For the parallel optimization design of fiber orientation and composite material structure, the model includes the material density and fiber angle of each unit under the finite element discrete grid, fully considering the influence of fiber orientation on structural performance. However, this structure optimization method supports arbitrary shape output as the optimization result, and the result is not directly feasible. The traditional 3D printing path planning method cannot simultaneously realize the macroscopic topological geometric characteristics and microscopic fiber orientation of the optimized structure, and there will be problems in the printing process. Problems such as too small corners, path jumps, and path overlaps seriously affect the mechanical properties of the optimized structure and limit the development of continuous fiber reinforced composite 3D printing processes.

Contents of the invention

In order to overcome the defects of the above-mentioned prior art, the purpose of the present invention is to provide a continuous fiber 3D printing path planning method for parallel optimization of fiber orientation and structure, which can not only realize the macroscopic topological geometric structure characteristics, but also fully consider the microscopic fiber reinforcement direction characteristics The non-overlapping and non-jumping continuous fiber 3D printing path fully utilizes the anisotropic mechanical properties of continuous fiber reinforced composites and meets the requirements of continuous fiber reinforced composites 3D printing process.

In order to achieve the above object, the technical scheme that the present invention takes is:

A continuous fiber 3D printing path planning method for parallel optimization of fiber orientation and structure, comprising the following steps:

1) Construct a parallel optimization model of fiber orientation and composite material structure, taking material density x and fiber angle θ as design variables, and its mathematical model is as follows:

In the formula, the objective function c represents the minimum compliance value; U and F represent the global displacement vector and global load vector respectively; K represents the global stiffness matrix; u _e and k _e represent the unit displacement vector and unit stiffness matrix respectively; x _min represents the relative The lowest density; p is the penalty factor; N is the number of finite element grids; V(x) and V ₀ are the material volume and the initial volume of the design domain, respectively; f is the allowable volume ratio of the composite material; v _f is the continuous fiber The volume fraction in the composite material; the material density x _e and the fiber angle θ _e under the finite element mesh are obtained by solving;

2) Filter the material density x _e and fiber angle θ _e obtained in step 1) under the finite element mesh, and set the material filter density x _set . When x _e < x _set , set x _e equal to 0. At this time The unit grid whose material density x _e is not 0 constitutes a macro topological geometric structure; according to the orthotropy of continuous fiber-reinforced composite materials, the value range of the fiber angle θ _e obtained in step 1) is from [-2π ,2π] adjusted to [-π/2,π/2] or [0,π] to obtain the result of parallel optimization of fiber orientation and structure, that is, the optimized structure;

3) Divide the optimized structure obtained in step 2) into sub-regions according to its macroscopic geometric characteristics, thereby discretizing the complex optimized structure into a finite number of structures with simple geometric characteristics; using topology to abstract each sub-region into points, And according to the position relationship of the optimal structure of the sub-area, the points are connected with each other. The interconnected point graphs form a connected graph containing the characteristic information of the optimized structure. The path planning problem of the optimized structure is classified as finding a connected graph in graph theory. The Hamiltonian path problem in , that is, to find a path that does not traverse all points repeatedly in a connected graph;

4) Calculate the fiber trajectory direction in the sub-region divided by step 3), divide it into n intervals according to the geometric characteristics of the sub-region, each interval contains n _e unit grids; then step 2) after processing Substituting the parallel optimization results of , the material density x _e value of the unit grid in the interval is used as the weight factor of the fiber angle θ _e , and thus the fiber trajectory direction θ _i of each interval is obtained, as shown in formula (3);

In the formula, θ _j represents the trajectory direction of adjacent intervals, ε represents the angle deviation between intervals, and the value of ε changes correspondingly according to the geometric characteristics of the sub-region; when the value range of the fiber angle θ _e in step 2) is different, we get The interval fiber trajectory angle θ _i will also be different, and a specific value range should be selected based on the principle that the value range boundary and the value of θ _e in the interval are far apart, so that the calculated fiber trajectory angle θ _i value is as close as possible to the interval In addition, in the local grid of the sub-area, the fiber angle _calculated by parallel optimization may not match the geometric characteristics of the sub-area, and the calculated interval fiber trajectory angle at this time should not include these local units Grid, to obtain the fiber trajectory direction in each sub-region of the optimized structure;

5) Lay the materials in the sub-area according to the fiber trajectory direction of the sub-area obtained in step 4), and the laying distance is the 3D printing scanning distance h _i in different intervals of the sub-area, i=1,2,..., n; According to the 3D printing process of continuous fiber reinforced composite materials, there is a proportional relationship between the scanning distance h and the fiber volume fraction v _f , and the fiber volume fraction v _f has been determined in step 1) as a parallel optimization parameter, so the 3D printing process is maximized The scanning distance h(v _fmax ) under the fiber content and the scanning distance h(v _f ) under the fiber content set in the parallel optimization are used as the manufacturing constraints of the 3D printing process, that is, h(v _fmax )≤h _i ≤h(v _f ), To satisfy the continuous fiber-reinforced composite structure and meet the target performance requirements and 3D printing process requirements, the scanning interval h _i in the interval should be as close as possible to the scanning interval h(v _f ) under the fiber content set in parallel optimization;

6) Adjust the scanning interval h _i according to the manufacturing constraints in step 5), and determine the laying in the sub-region by combining the connected graph containing the optimized structural feature information obtained in step 3) on the basis of satisfying the structural characteristics of the sub-region The number of fibers makes the number of paths contained in the sub-regions connected based on the Hamiltonian path in the connectivity graph equal, thereby obtaining the continuous fiber 3D printing path of each sub-region of the optimized structure;

7) Connect the sub-region printing paths obtained in step 6) sequentially according to the Hamiltonian path obtained in step 3), and determine the allowable minimum corner radius r _min as another manufacturing constraint according to the specific material and device characteristics during connection, so that when the sub-regions are connected The print radius r _print ≥ r _min ;

8) After the above path planning, the path is output according to the ratio of the feed amount of the base material and the printing distance, and the printed G-code code is generated for printing by the 3D printer.

In the step 3), if there is no Hamiltonian path in the connected graph containing the optimized structural feature information, or the contained Hamiltonian path cannot plan the printing path, then the existing part of the connected graph, that is, the sub-region, is divided into Multiple points, that is, multiple sub-regions; or adding points in the connected graph, that is, adding a new sub-region, specifically refers to adding a new structure in the optimized structure until there is at least one hash in the connected graph containing the characteristic information of the optimized structure The density path is used as the planning basis for the continuous fiber 3D printing path.

In the step 5), according to the printing path of the sub-region initially obtained according to the fiber trajectory direction θ _i and the scanning distance h _i of each interval, different sub-regions are used to divide the interval range, and the printing path obtained will also be different; if If the printing path cannot show the shape characteristics of the sub-region, go back to step 4) to adjust the division range until there is at least one printing path in each sub-region that can realize the macroscopic geometric characteristics of the optimized structure and the 3D process printing requirements.

The beneficial effects of the present invention are:

The invention combines the continuous fiber reinforced composite material, structure optimization and 3D printing process to complete the continuous fiber 3D printing path planning for parallel optimization of fiber orientation and composite material structure. Compared with the prior art, the present invention introduces the Hamiltonian path idea into 3D printing path planning, regards the printing path planning problem of complex structures as the Hamiltonian path problem of connected graphs, and the printing path generated based on the Hamiltonian path has no The jump point greatly improves the printing efficiency of complex components; at the same time, it fully considers the fiber angle and material density in the parallel optimization of fiber orientation and composite material structure, based on the topological geometric characteristics of the macro-optimized structure, micro-fiber distribution direction and 3D printing process The continuous fiber printing path is planned with manufacturing constraints, and the obtained printing path can give full play to the advantages of the anisotropic mechanical properties of the continuous fiber reinforced composite material and meet the requirements of the 3D printing process.

The invention has good applicability, introduces the directional characteristics of the anisotropic composite material into the structure optimization and 3D printing process, realizes the precise control of the fiber orientation of the composite material during the printing process, and effectively solves the problem of the current continuous fiber-reinforced composite material. The manufacturing problems of carrying complex structures, thereby promoting the structural optimization of continuous fiber reinforced composite materials and the development of 3D printing technology.

Description of drawings

Figure 1 is a flow chart of the present invention.

Fig. 2 is a schematic diagram of parallel optimization of fiber orientation and composite material structure in the present invention.

Fig. 3 is a schematic diagram of sub-region division processing of the optimized structure in the present invention.

Fig. 4 is a schematic diagram of a Hamiltonian path containing optimized structural feature information in the present invention.

Fig. 5 is a schematic diagram of laying materials in sub-regions according to the present invention.

Fig. 6 is a schematic diagram of path planning in the present invention.

Fig. 7 is a 3D printed component based on parallel optimization of fiber orientation and composite material structure according to the present invention.

Detailed ways

Below in conjunction with accompanying drawing and embodiment the present invention will be described in further detail

Referring to Figure 1, a continuous fiber 3D printing path planning method for parallel optimization of fiber orientation and structure, including the following steps:

2) Filter the material density x _e and fiber angle θ _e obtained in step 1) under the finite element mesh, and set the material filter density x _set . When x _e < x _set , set x _e equal to 0. At this time The unit grid whose material density x _e is not 0 constitutes a macro topological geometric structure; according to the orthotropy of continuous fiber-reinforced composite materials, the value range of the fiber angle θ _e obtained in step 1) is from [-2π ,2π] is adjusted to [-π/2,π/2] or [0,π], the two ranges of values are selected in step 4), and the result of parallel optimization of fiber orientation and structure is obtained, that is, the optimized structure;

In this example, through the structural design of the composite material, a structural model of parallel optimization of fiber orientation and composite material structure is obtained. As shown in Figure 2, the classic model MBB beam is used as an example to illustrate, and each unit is obtained through finite element analysis and optimization solution The material density and fiber angle in the grid, the redundant unit grid is deleted by filtering, leaving the shaded part in Figure 2, which is the optimized structure of the fiber reinforced composite MBB beam; due to the optimization of the fiber orientation and composite material structure is Parallel processing, each unit grid contained in its structure contains its corresponding fiber angle value;

Considering the complexity of the optimized structure, if there is no Hamiltonian path in the connected graph containing the characteristic information of the optimized structure, or the contained Hamiltonian path cannot plan the printing path, then the existing points in the connected graph, that is, sub-regions, are divided into Multiple points, that is, multiple sub-regions; or adding points in the connected graph, that is, adding a new sub-region, specifically refers to adding a new structure in the optimized structure model until there is at least one The Ha density path is used as the planning basis for the continuous fiber 3D printing path;

In this embodiment, subregions are divided according to the geometric shape characteristics of the optimized structure. As shown in FIG. 3, the geometric shape of the optimized structure is judged and analyzed, and the thin rod structure in FIG. Disassemble the complex optimization structure into 16 simple rod-shaped structures, such as the 16 sub-regions selected in the box in Figure 3;

In this embodiment, the idea of topology is used to convert each sub-region into a point, and the connection relationship between points represents the intersection information of the optimized structure, thereby converting the complex topological geometric structure into a connected graph, as shown in Figure 4, the connected graph Each node in represents the sub-area corresponding to its number, thus transforming the path planning problem into the problem of establishing a Hamiltonian path in the connected graph. The Hamiltonian path is a path that does not traverse all points repeatedly. The printing path of the area, as shown in Figure 4, constructs a new sub-area (*1, *2, *3) as a new connection point in the Hamiltonian path, the sub-area *1 is the derived area of the sub-area 3, and the sub-area *2 is the derived area of sub-area 2, and sub-area *3 is the derived area of sub-area 16; with node 3 in the connectivity graph as the starting point, connect sub-area nodes 3, 16, 1, 2, *1, 11 in sequence . planning basis;

4) Since the fiber angle θ _e is a discrete value in the calculation results of parallel optimization, the direction of the fiber trajectory on the printing path cannot be directly obtained. The direction of the fiber trajectory in the sub-area divided in step 3) is calculated. According to the geometry of the sub-area Divide it into n intervals, and each interval contains n _e unit grids; then substitute the parallel optimization results processed in step 2), and the material density x _e value of the unit grid in the interval is taken as its fiber angle θ The weight factor of _e , thus obtaining the fiber trajectory direction θ _i of each interval, as shown in formula (3);

In the formula, θ _j represents the trajectory direction of adjacent intervals, ε represents the angle deviation between intervals, and the value of ε changes correspondingly according to the geometric characteristics of the sub-region; when the value range of the fiber angle θ _e in step 2) is different, we get The interval fiber trajectory angle θ _i will also be different, and a specific value range should be selected based on the principle that the value range boundary and the value of θ _e in the interval are far apart, so that the calculated fiber trajectory angle θ _i value is as close as possible to the interval In order to maximize the anisotropic performance advantages of continuous fiber reinforced composites, the parallel optimization calculation results θ _e in the sub-area may appear in the local mesh of the sub-area. If the characteristics do not match, the calculated interval fiber trajectory angle should not include these local unit grids to improve the manufacturability of the optimized structure; the fiber trajectory direction in each sub-region of the optimized structure is obtained, which is the planning of the continuous fiber path in the sub-region Provide evidence;

In this embodiment, the geometric shape judgment and analysis of the sub-regions obtained in step 3) are performed, and the sub-regions are divided into a limited number of intervals according to the shape characteristics. The included unit fiber optimization angle θ _e is corrected, and the material density x _e value is used as the weight factor of the fiber angle θ _e to calculate the fiber trajectory direction θ _i of each interval; as shown in Figure 5, some sub-regions 3 and The area 12 is divided into different intervals according to its shape characteristics, so as to ensure that the overall direction of the laid material matches the structural geometric characteristics of the sub-area, and the fiber laying direction in different intervals changes correspondingly according to the calculated θ _i value;

5) Lay the materials in the sub-area according to the fiber trajectory direction of the sub-area obtained in step 4), and the laying distance is the 3D printing scanning distance h _i in different intervals of the sub-area, i=1,2,..., n; According to the 3D printing process of continuous fiber reinforced composite materials, there is a proportional relationship between the scanning distance h and the fiber volume fraction v _f , and the fiber volume fraction v _f has been determined in step 1) as a parallel optimization parameter, so the 3D printing process is maximized The scanning distance h(v _fmax ) under the fiber content and the scanning distance h(v _f ) under the fiber content set in the parallel optimization are used as the manufacturing constraints of the 3D printing process, that is, h(v _fmax )≤h _i ≤h(v _f ), To meet the target performance requirements and 3D printing process requirements for the continuous fiber reinforced composite structure, among them, h _i is less than h(v _fmax ) to ensure that the printing path will not overlap in the sub-area and improve the mechanical properties of the manufactured structure, while The scanning interval h _i in the interval should be as close as possible to the scanning interval h(v _f ) under the fiber content set in parallel optimization to reduce material loss;

According to the printing path of the sub-area preliminarily obtained according to the fiber trajectory direction θ _i and the scanning distance h _i of each interval, if different sub-areas are used to divide the interval range, the printing path obtained will be different; if the printing path cannot show the sub-area Shape features, then go back to step 4) to adjust the range of the segmentation interval until there is at least one printing path in each sub-region that can realize the macroscopic geometric characteristics of the optimized structure and the requirements of 3D process printing;

In this embodiment, for 3D printing continuous fiber reinforced composite materials, the fiber volume fraction corresponds to the material coefficient of the 3D printing process parameters, the printing spacing and the layer thickness, and the printing spacing is negatively correlated with the fiber volume fraction, and the local Structural enlarged view, the distance between tracks is the printing distance, the printing distance h _i needs to be smaller than and as close as possible to the printing distance value h(v _f ) corresponding to the fiber volume fraction calculated in step 1), so as to meet the path planning Optimize the mechanical properties of the structure; and need to be smaller than the printing spacing value h(v _fmax ) corresponding to the maximum volume fraction of the 3D printing process to meet the manufacturing requirements of the 3D printing process;

7) Connect the sub-region printing paths obtained in step 6) sequentially according to the Hamiltonian path obtained in step 3), and determine the allowable minimum corner radius r _min as another manufacturing constraint according to the specific material and device characteristics during connection, so that when the sub-regions are connected The printing radius r _print ≥ r _min in order to avoid structural defects caused by too small corners during the printing process; according to the characteristics of the Hamiltonian path, the printing path obtained according to the above steps does not have nozzle jumps when printing complex geometric structures, which is extremely Greatly improved part printing efficiency and material forming effect;

In this embodiment, according to the Hamiltonian path information in step 3), the sub-regions are connected in sequence, and the connected sub-regions should have the same number of fibers, and the track spacing can be adjusted according to the printing spacing constraints in step 5), so that adjacent sub-regions At the same time, set another manufacturing constraint minimum printing radius, so that the radius of gyration of the path at the junction of the sub-regions is not lower than the minimum printing radius, so as to ensure the printing quality of the optimized structure, and obtain the parallel optimization of fiber orientation and composite material structure. Print path, as shown in Figure 6;

8) After the above path planning, the path is output according to the ratio of the feed amount of the base material and the printing distance, and the printed G-code code is generated for printing by the 3D printer;

In this embodiment, the path is output according to the ratio of the feed amount of the matrix material to the printing distance, and the printed G-code code is generated for printing by the 3D printer. The 3D printing component based on the parallel optimization of the fiber orientation and the composite material structure is shown in Figure 7. Finally, a non-overlapping and non-jumping continuous fiber 3D printing path that can not only realize the macroscopic topological geometric structure characteristics, but also fully consider the microscopic continuous fiber distribution direction is obtained, which meets the requirements of the 3D printing process.

Claims

A continuous fiber 3D printing path planning method for parallel optimization of fiber orientation and structure, characterized in that it comprises the following steps:

1) Construct a parallel optimization model of fiber orientation and composite material structure, taking material density x and fiber angle θ as design variables, and its mathematical model is as follows:

In the formula, the objective function c represents the minimum compliance value; U and F represent the global displacement vector and global load vector respectively; K represents the global stiffness matrix; u e and k e represent the unit displacement vector and unit stiffness matrix respectively; x min represents the relative The lowest density; p is the penalty factor; N is the number of finite element grids; V(x) and V 0 are the material volume and the initial volume of the design domain, respectively; f is the allowable volume ratio of the composite material; v f is the continuous fiber The volume fraction in the composite material; the material density x e and the fiber angle θ e under the finite element mesh are obtained by solving;

2) Filter the material density x e and fiber angle θ e obtained in step 1) under the finite element mesh, and set the material filter density x set . When x e < x set , set x e equal to 0. At this time The unit grid whose material density x e is not 0 constitutes a macro topological geometric structure; according to the orthotropy of continuous fiber-reinforced composite materials, the value range of the fiber angle θ e obtained in step 1) is from [-2π ,2π] adjusted to [-π/2,π/2] or [0,π] to obtain the result of parallel optimization of fiber orientation and structure, that is, the optimized structure;

3) Divide the optimized structure obtained in step 2) into sub-regions according to its macroscopic geometric characteristics, thereby discretizing the complex optimized structure into a finite number of structures with simple geometric characteristics; using topology to abstract each sub-region into points, And according to the position relationship of the optimal structure of the sub-area, the points are connected with each other. The interconnected point graphs form a connected graph containing the characteristic information of the optimized structure. The path planning problem of the optimized structure is classified as finding a connected graph in graph theory. The Hamiltonian path problem in , that is, to find a path that does not traverse all points repeatedly in a connected graph;

4) Calculate the fiber trajectory direction in the sub-region divided by step 3), divide it into n intervals according to the geometric characteristics of the sub-region, each interval contains n e unit grids; then step 2) after processing Substituting the parallel optimization results of , the material density x e value of the unit grid in the interval is used as the weight factor of the fiber angle θ e , and thus the fiber trajectory direction θ i of each interval is obtained, as shown in formula (3);

In the formula, θ j represents the trajectory direction of adjacent intervals, ε represents the angle deviation between intervals, and the value of ε changes correspondingly according to the geometric characteristics of the sub-region; when the value range of the fiber angle θ e in step 2) is different, we get The interval fiber trajectory angle θ i will also be different, and a specific value range should be selected based on the principle that the value range boundary and the value of θ e in the interval are far apart, so that the calculated fiber trajectory angle θ i value is as close as possible to the interval In addition, in the local grid of the sub-area, the fiber angle calculated by parallel optimization may not match the geometric characteristics of the sub-area, and the calculated interval fiber trajectory angle at this time should not include these local units Grid, to obtain the fiber trajectory direction in each sub-region of the optimized structure;

5) Lay the materials in the sub-area according to the fiber trajectory direction of the sub-area obtained in step 4), and the laying distance is the 3D printing scanning distance h i in different intervals of the sub-area, i=1,2,..., n; According to the 3D printing process of continuous fiber reinforced composite materials, there is a proportional relationship between the scanning distance h and the fiber volume fraction v f , and the fiber volume fraction v f has been determined in step 1) as a parallel optimization parameter, so the 3D printing process is maximized The scanning distance h(v fmax ) under the fiber content and the scanning distance h(v f ) under the fiber content set in the parallel optimization are used as the manufacturing constraints of the 3D printing process, that is, h(v fmax )≤h i ≤h(v f ), To satisfy the continuous fiber-reinforced composite structure and meet the target performance requirements and 3D printing process requirements, the scanning interval h i in the interval should be as close as possible to the scanning interval h(v f ) under the fiber content set in parallel optimization;

6) Adjust the scanning interval h i according to the manufacturing constraints in step 5), and determine the laying in the sub-region by combining the connected graph containing the optimized structural feature information obtained in step 3) on the basis of satisfying the structural characteristics of the sub-region The number of fibers makes the number of paths contained in the sub-regions connected based on the Hamiltonian path in the connectivity graph equal, thereby obtaining the continuous fiber 3D printing path of each sub-region of the optimized structure;

7) Connect the sub-region printing paths obtained in step 6) sequentially according to the Hamiltonian path obtained in step 3), and determine the allowable minimum corner radius r min as another manufacturing constraint according to the specific material and device characteristics during connection, so that when the sub-regions are connected The print radius r print ≥ r min ;

8) After the above path planning, the path is output according to the ratio of the feed amount of the base material and the printing distance, and the printed G-code code is generated for printing by the 3D printer.
A continuous fiber 3D printing path planning method for parallel optimization of fiber orientation and structure according to claim 1, characterized in that: in said step 3), if there is no Hamiltonian path in the connected graph containing optimized structural feature information , or the contained Hamiltonian path cannot plan the printing path, then divide the existing points in the connected graph, that is, sub-regions, into multiple points, that is, multiple sub-regions; or add points in the connected graph, that is, add new sub-regions Region, specifically refers to adding a new structure in the optimized structure until at least one Hard density path exists in the connected graph containing the characteristic information of the optimized structure as the planning basis for the continuous fiber 3D printing path.
A continuous fiber 3D printing path planning method for parallel optimization of fiber orientation and structure according to claim 1, characterized in that: in the step 5), according to the fiber trajectory direction θ i and scanning interval h i of each interval The printing path of the obtained sub-region adopts different sub-regions to divide the interval range, and the obtained printing path will also be different; if the printing path cannot show the shape characteristics of the sub-region, then go back to step 4) to adjust the division interval range, Until there is at least one printing path in each sub-region, the macroscopic geometric characteristics of the optimized structure and the printing requirements of the 3D process can be realized.