A 3D printing modeling method for heterogeneous material parts

Abstract

The application discloses a 3D printing modeling method for heterogeneous material parts, which comprises the following steps: 1) obtaining each layer slice contour and filling path of a heterogeneous material part model to be printed, and constructing a feature point set E of the model in a geometric space; 2) constructing a parameter space transformation function matrix H, and transforming the feature point set E of the model from the geometric space to the parameter space of the parameter space transformation function matrix H; 3) constructing a material space distribution change matrix F, and obtaining the material volume fraction of each feature point by using the material space distribution change matrix F, and completing material modeling. The application directly uses the slice filling path points as the material feature points in the model, avoids manufacturing errors caused by the traditional voxel method or the finite element method, quickly obtains the material value of the feature points by the space transformation method, avoids the limitation of directly defining the material transformation on the model geometric space, and therefore can obtain a heterogeneous part model with an arbitrary complex transformation.

Description

Technical Field

[0001] This invention belongs to the field of 3D printing, specifically relating to a 3D printing modeling method for heterogeneous material parts. Background Technology

[0002] Heterogeneous material parts refer to novel material parts in which two or more materials are continuously or discontinuously distributed within the part to meet specific functional requirements. With the continuous development of 3D printing technology in recent years, especially its "layer-by-layer material stacking" manufacturing concept, the manufacturing of heterogeneous material parts has become more feasible and flexible.

[0003] When constructing models of heterogeneous parts, voxel methods or mesh methods are typically used to obtain data points within the model after establishing a digital model of the part. This method is not only computationally intensive and inaccurate, but also fails to consider subsequent fabrication processes, leading to secondary errors in 3D printing layer slicing. Regarding material calculation methods for heterogeneous parts, the most commonly used interpolation and gradient source methods are unsuitable for parts with complex material variations. While B-spline surface methods can construct complex parts, spline surfaces require a series of control points and basis functions, making them complex to implement and currently only existing in the theoretical research stage, lacking practical application. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the present invention aims to provide a 3D printing modeling method for heterogeneous material parts. This method is geared towards 3D printing manufacturing processes, utilizes the filling path of slices to obtain the internal data information of the parts, and generates various types of heterogeneous material distribution models based on spatial transformation methods.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for 3D printing modeling of heterogeneous material parts, comprising the following steps:

[0007] 1) Obtain the slice outlines and filling paths of each layer of the heterogeneous material part model to be printed, and construct the feature point set E of the model in geometric space;

[0008] 2) Construct the parameter space transformation function matrix H, and transform the feature point set E of the model from the geometric space to the parameter space of the parameter space transformation function matrix H;

[0009] 3) Construct the material spatial distribution variation matrix F, and use the material spatial distribution variation matrix F to obtain the material volume fraction of each feature point to complete the material modeling.

[0010] In step 1), firstly, a geometric model of the heterogeneous material part to be printed is constructed, then the slice contours of each layer of the model are calculated, and secondly, the internal filling path points of each slice contour are obtained. The slice contour points and filling path points together form the feature point set E of the model in geometric space.

[0011] Discretize each internal filling path to obtain precise path points.

[0012] In step 2),

[0013] 1. For any feature point p(x,y,z)∈E in the geometric space of the heterogeneous material part model to be printed, establish the parameter space transformation function matrix.

[0014] H(p) = [h1(p),h2(p),...,h i (p),...,h m [(p)]=[u1,u2,...,u m ]

[0015] Among them, h i (p) is the i-th parameter space transformation function, i = 1, 2, ..., m, where m is the total number of transformation types, u i To utilize h i (p) After spatial transformation of the model feature points p(x,y,z), the model is obtained in parameter space V. i The parameter points below.

[0016] The parameter space transformation function can be any one or more of the following: basic transformation, scan transformation, distance transformation, or hybrid distance transformation.

[0017] The basic transformation is as follows: Establish a local coordinate system CYS for parameter transformation, transform the model feature points p(x,y,z) in the model feature point set E to the local coordinate system CYS to obtain p'(x',y',z'), and then perform the corresponding coordinate transformation.

[0018] The scanning transformation is as follows: First, obtain the parametric equation of the scanning curve, and calculate the foot of the perpendicular M from the model feature point p(x,y,z) to the scanning curve. p Then calculate the foot of the perpendicular M. p The arc length s of the curve from the starting point of the scan p Construct the scan transformation function h(p) = u = s p .

[0019] The distance transformation function is constructed as h(p) = u = d p , where d p This represents the shortest distance from the model feature point p(x,y,z) to the reference feature.

[0020] The hybrid distance transformation function is represented by the inverse coupling distance, h(p)=u=[a1,a2,......,a n ], Where, d j (j = 1, 2, ..., n, where n is the total number of reference boundaries) represents the shortest distance from the model feature point p(x, y, z) to the j-th reference boundary.

[0021] In step 3), when any feature point p(x,y,z) of the model in geometric space is transformed into H(p) = [u1,u2,...,u] using the parameter space transformation matrix H, the result is: H(p) = [u1,u2,...,u] m After that, for each parameter space V i The parameter point u below i Establish material j with respect to parameter point u i Distribution change function f ij (u i ), and 0≤f ij (u i Given that )≤1, j=1,2…n, where n is the total number of materials, construct a material space transformation matrix.

[0022]

[0023] Then the volume fraction of feature point p(x,y,z) with respect to material j is: Where, ω ij Let be the weighting factor of material j with respect to the i-th transformation.

[0024] The beneficial effects of this invention are: directly using slice-filled path points as material feature points inside the model, avoiding manufacturing errors caused by traditional voxel methods or finite element methods, and quickly obtaining material values ​​of feature points through spatial transformation, avoiding the limitations of directly defining material transformation in the geometric space of the model, thus enabling the acquisition of heterogeneous part models with arbitrarily complex transformations. Attached Figure Description

[0025] Figure 1 This is a flowchart illustrating the technical process of the present invention.

[0026] Figure 2 a, Figure 2 b、 Figure 2 c is a schematic diagram of obtaining internal feature points of the model using 3D printing slicing and fill path algorithms.

[0027] Figure 3 This is a schematic diagram of the distribution of the two materials under rectangular coordinate transformation.

[0028] Figure 4 This is a schematic diagram of the distribution of two materials under cylindrical coordinate transformation.

[0029] Figure 5 This is a schematic diagram of the distribution of two materials under spherical coordinate transformation.

[0030] Figure 6 This is a schematic diagram of the distribution of the two materials under scanning transformation.

[0031] Figure 7 This is a schematic diagram of the distribution of the two materials under distance transformation.

[0032] Figure 8 This is a schematic diagram of the distribution of the three materials under mixed distance transformation. Detailed Implementation

[0033] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0034] like Figure 1 As shown, this invention discloses a 3D printing modeling method for heterogeneous material parts, which includes the following steps:

[0035] 1) Obtain the slice outlines and filling paths of each layer of the heterogeneous material part model to be printed, and construct the feature point set E of the model in geometric space;

[0036] First, construct the geometric model of the heterogeneous material part to be printed. Then, calculate the slice contours of each layer of the model. Next, obtain the internal filling path points of each slice contour. The slice contour points and filling path points together form the feature point set E of the model in geometric space.

[0037] At the same time, each internal filling path can be discretized to obtain more precise filling path points, so as to satisfy the construction of the feature point set E.

[0038] 2) Construct the parameter space transformation function matrix H, and transform the feature points of the feature point set E of the model in geometric space to the parameter points in the parameter space of the parameter space transformation function matrix H;

[0039] In step 2),

[0040] 1. For any feature point p(x,y,z)∈E in the geometric space of the heterogeneous material part model to be printed, establish the parameter space transformation function matrix.

[0041] H(p) = [h1(p),h2(p),...,h i (p),...,h m[(p)]=[u1,u2,...,u m ]

[0042] Among them, h i (p) is the i-th parameter space transformation function, i = 1, 2, ..., m, where m is the total number of transformation types, u i To utilize h i (p) After spatial transformation of the model feature points p(x,y,z), the model is obtained in parameter space V. i The parameter points below.

[0043] Based on the material variation characteristics, any parameter space transformation function h(p) can be defined in the following ways: basic transformation, scan transformation, distance transformation, or mixed distance transformation.

[0044] The basic transformation is as follows: Establish a local coordinate system CYS for parameter transformation, transform the feature points p(x,y,z) in the feature point set E to the local coordinate system CYS to obtain p'(x',y',z'), and then perform the corresponding coordinate transformation.

[0045] Coordinate transformations include rectangular coordinate transformations, cylindrical coordinate transformations, and spherical coordinate transformations.

[0046] Cartesian coordinate transformation is suitable for situations where the material changes along a straight line. The Cartesian coordinate transformation function is constructed as: h(p)=u=[x',y',z'];

[0047] Cylindrical coordinate transformation is suitable for cases where the material undergoes radial changes around a straight line. The cylindrical coordinate transformation function is constructed as follows:

[0048] Spherical coordinate transformation is suitable for cases where the material undergoes radial changes centered at a certain point. The spherical coordinate transformation function is constructed as follows:

[0049] The scanning transformation is suitable for situations where the material changes along a scanning curve. Specifically, it involves: first, obtaining the parametric equation of the scanning curve, and then calculating the foot of the perpendicular M from the feature point p(x,y,z) to the scanning curve. p Then calculate the foot of the perpendicular M. p The arc length s of the curve from the starting point of the scan p Construct the scan transformation function h(p) = u = s p .

[0050] Distance transformation is suitable for situations where the material's distance relative to a reference feature changes. The distance transformation function is constructed as h(p) = u = d p , where d p This represents the shortest distance from the model feature point p(x,y,z) to the reference feature.

[0051] The hybrid distance transformation is suitable for situations where the distance between a material and a reference feature varies, and the reference features are made of different materials. Consider n different materials, each corresponding to a unique reference boundary, and these reference boundaries are not connected. Since the closer a feature point p is to the reference boundary of a certain material, the larger its volume fraction, the hybrid distance transformation function is represented by the inverse coupling distance: h(p) = u = [a1, a2, ..., a...]. n ], Where, d j (j = 1, 2, ..., n, where n is the total number of reference boundaries) represents the shortest distance from the model feature point p(x, y, z) to the j-th reference boundary.

[0052] 3) Construct the material spatial distribution variation matrix F, and use the material spatial distribution variation matrix F to obtain the material volume fraction of each feature point to complete the material modeling.

[0053] In step 3), when any feature point p(x,y,z) of the model in geometric space is transformed into H(p) = [u1,u2,...,u] using the parameter space transformation matrix H, the result is: H(p) = [u1,u2,...,u] m After that, for each parameter space V i The parameter point u below i Establish material j with respect to parameter point u i Distribution change function f ij (u i ), and 0≤f ij (u i Given that )≤1, j=1,2…n, where n is the total number of materials, construct a material space transformation matrix.

[0054]

[0055] Then the volume fraction of feature point p(x,y,z) with respect to material j is: Where, ω ij Let be the weighting factor of material j with respect to the i-th transformation.

[0056] Figure 2 The diagram illustrates the use of 3D printing slicing and fill path algorithms to obtain feature points within a model. Following this method, the geometric model is first sliced ​​to obtain features such as... Figure 2 (a) shows the slice contours of each layer. Then, by applying the offset path filling algorithm to each slice contour, the following can be obtained: Figure 2 (b) shows the path points to be filled. If a grid filling algorithm is used, the following can be obtained: Figure 2 (c) shows the fill path points.

[0057] Figure 3This is a schematic diagram of the distribution of two materials under rectangular coordinate transformation, where f 11 (u1)=f 11 (x,y,z)=sin(z); f 12 (u1)=1-f 11 (u1).

[0058] Figure 4 This is a schematic diagram of the distribution of two materials under cylindrical coordinate transformation, where f 11 (u1)=f 11 (r,θ,z)=sin(4*θ); f 12 (u1)=1-f 11 (u1).

[0059] Figure 5 This is a schematic diagram of the distribution of two materials under spherical coordinate transformation, where f 12 (u1)=1-f 11 (u1).

[0060] Figure 6 This is a schematic diagram of the distribution of two materials under scanning transformation, where f 11 (u1)=f 11 (s) = sin(50*s); f 12 (u1)=1-f 11 (u1).

[0061] Figure 7 This is a schematic diagram of the distribution of two materials under distance transformation, where f 11 (u1)=f 11 (d p )=d p f 12 (u1)=1-f 11 (u1), where the reference boundary feature is the model surface.

[0062] Figure 8 This is a schematic diagram of the distribution of the three materials under mixed distance transformation, f 11 (u1)=f 11 (a1,a2,a3)=a1,f 12 (u1)=f 12 (a1,a2,a3)=a2,f 13 (u1)=f 13 (a1,a2,a3)=a3, according to the mixed distance transformation function, we can obtain:

[0063]

[0064]

[0065]

[0066] Where d1, d2, and d3 represent the shortest distances from each model feature point to reference boundary 1, reference boundary 2, and reference boundary 3, respectively.

[0067] The embodiments should not be regarded as limitations on the present invention, but any improvements made based on the spirit of the present invention should be within the protection scope of the present invention.

Claims

1. A method for 3D printing modeling of heterogeneous material parts, characterized in that: It comprises the following steps: 1) Obtain the contour of each layer slice and the filling path of the heterogeneous material part model to be printed, and construct the feature point set of the model under the geometric space E ; 2) Constructing the parameter space transformation function matrix H and the feature point set of the model E from the geometric space transformation to the parameter space transformation function matrix H under the parameter space; 3) Constructing the material spatial distribution change matrix F and using the material spatial distribution change matrix F Obtaining the material volume fraction of each feature point, completing material modeling, In step 2), Any feature point of a heterogeneous material part model to be printed in a geometric space p ( x , y , z )∈ E , a parameter space transformation function matrix wherein h i p is a parameter space transformation function of the i th transformation type, i =1,2,…, m , m is the total number of transformation types, u i h i p p x y z V i parameter points in the parameter space​​​​​​​​ The parameter space transformation function is one of basic transformation, scan transformation, distance transformation or mixed distance transformation, The basic transformation is as follows: a parameter transformation local coordinate system CYS is established, model feature points in a model feature point set E p ( x , y , z ) are transformed to the local coordinate system CYS to obtain p '( x ', y ', z '), and then corresponding coordinate transformation is performed;​ The scan conversion is as follows: firstly, a parametric equation of a scan curve is obtained, a foot point of model feature points p ( x , y , z ) to the scan curve is calculated M p , then a curve arc length M p of the foot point to a scan starting point is calculated s p , and a scan conversion function is constructed; The distance transform function is constructed as wherein d p is the shortest distance from the model feature point p ( x , y , z ) to the reference feature; The mixed distance transformation function is represented by a coupled inverse distance, , , j =1,2… n , n is the total number of materials, d k represent the shortest distance from the model feature points p ( x , y , z ) to the first k reference boundary, k =1,2… w , w is the total number of reference boundaries.

2. The method of claim 1, wherein: In step 1), firstly, a geometric model of the heterogeneous material part to be printed is constructed, and then the contour of each layer slice of the model is calculated, secondly, the internal filling path points of each layer slice contour are obtained, wherein the slice contour points and the filling path points jointly constitute a feature point set of the model in the geometric space E .

3. The heterogeneous material part 3D printing modeling method according to claim 1, characterized in that: Discretize each internal filling path to obtain precise path points.

4. The method of claim 1, wherein: In step 3), when using the parameter space transformation function matrix... H Arbitrary feature points of the model in geometric space p ( x , y , z Transformed into: Then, for each parameter space V i The parameter points below u i Establish materials j Regarding parameter points u i Distribution change function f ij ( u i ), and 0≤ f ij ( u i )≤1, j =1,2…, n, n To determine the total number of materials, construct the material space transformation function matrix. then the feature points p ( x , y , z ) are related to the volume fraction of the material j wherein ω ij is a weight factor for the material j with respect to the first i transformation.​

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