A method of 3D printing a protective material

Abstract

The application relates to the field of 3D printing technology, and specifically discloses a method for 3D printing protective material, which comprises the following steps: S1, model scanning, S2, surface calculation, S3, designing a protective shell, S4, selecting printing material, S5, material printing and S6, post-processing; the application can customize the design of a protective shell or structure according to the specific surface shape of an object, ensure the best fitting and protection effect, realize the accurate fitting and adaptation of complex shapes through surface scanning and algorithm optimization, improve the adaptability and performance of the protective shell, the thickness optimization algorithm can minimize the use amount of material while ensuring the strength, save the cost and improve the sustainability, the multi-material printing technology is used to combine the advantages of different materials in one protective shell, improve the overall performance and function, the protective shell can be customized according to individual needs to meet the specific needs of different application scenarios, and thus the individualization degree of the product and the customer satisfaction are improved.

Description

Technical Field

[0001] This invention belongs to the field of 3D printing technology, specifically relating to a method for 3D printing protective materials. Background Technology

[0002] With the continuous advancement of modern technology, especially in the field of protective material design and manufacturing, traditional manufacturing methods are gradually becoming unable to meet the growing demands for personalization, high precision, and high efficiency. Particularly in scenarios requiring customized protective shells or structures, such as industrial machinery protection, sports equipment, medical device shells, and aerospace equipment, traditional manufacturing methods are not only time-consuming and costly, but also struggle to accurately adapt to complex and varied object surface shapes, thus limiting the adaptability and performance of protective materials.

[0003] Against this backdrop, the emergence of 3D printing technology has brought about a revolutionary change in the manufacturing of protective materials. 3D printing, also known as additive manufacturing, enables the precise printing of materials according to a pre-set three-dimensional model through layer-by-layer deposition, thereby achieving customized manufacturing of objects with complex shapes. In the field of protective materials, 3D printing technology can not only achieve high-precision surface shape adaptation, ensuring optimal fit between the protective shell and the object's surface, but also greatly improve production efficiency and reduce manufacturing costs. However, existing technologies still have certain shortcomings in the adaptability and performance of 3D-printed protective materials.

[0004] To further improve the adaptability and performance of 3D printed protective materials, the inventors proposed a method for 3D printing protective materials to solve the above problems. Summary of the Invention

[0005] The purpose of this invention is to provide a method for 3D printing protective materials to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for 3D printing protective materials includes the following steps:

[0008] S1. Model scanning: Use a 3D scanner to perform a full scan of the object to be protected, obtain accurate 3D data of its surface, save it as a point cloud or mesh model, and use point cloud data processing software to process the scanned data, remove noise and redundant data, and obtain a clean surface model.

[0009] S2. Surface calculation: Perform surface analysis, surface fitting and thickness optimization to obtain the mathematical model of the protective shell;

[0010] S3. Design the protective shell. Based on the mathematical model obtained in step S2, use genetic algorithm and particle swarm optimization (PSO) algorithm to further adjust the shell design and automatically generate a 3D model of the protective shell. The 3D model is fully adapted to the surface of the object, and necessary structural features are added as needed.

[0011] S4. Select printing material. Choose the corresponding 3D printing material according to the required protection properties.

[0012] S5. Material printing: Based on the complexity of the shell design and the material properties, set appropriate printing parameters, including layer height, infill density, printing speed and support structure. Import the optimized 3D model into the printing software, generate G-code and start printing.

[0013] S6. Post-processing: Remove the support structure generated during the printing process, perform grinding and polishing surface treatment to ensure the smoothness and precision of the shell. Based on the test results, make necessary design adjustments and optimizations, reprint and test until the protective shell fully meets expectations.

[0014] Preferred point cloud data processing software includes MeshLab and Geomagic.

[0015] Preferably, in step S2, the surface analysis uses computational geometry algorithms to analyze the surface features of the object and identify key geometric structures, including convex surfaces, concave surfaces, and planar regions.

[0016] Surface fitting uses surface fitting algorithms, including least squares fitting and Bezier surface fitting, to fit the surface of the object and generate an accurate mathematical model.

[0017] Thickness optimization uses finite element analysis (FEA) and topology optimization algorithms to determine the optimal thickness and structure of the protective shell, ensuring the best protection with minimal material usage.

[0018] Preferably, the protective properties in step S4 include impact resistance, chemical corrosion resistance, and high temperature resistance.

[0019] Preferably, noise removal in step S1 is expressed as follows:

[0020]

[0021] Where pi is a point in the point cloud;

[0022] p i ′ represents the denoised point;

[0023] N(i) is the set of neighborhood points of point pi;

[0024] To smooth the point cloud data obtained from 3D scanning, the influence of noise and discrete points is reduced by averaging the neighboring points N(i) around point pi, thereby obtaining smoother and more accurate surface data.

[0025] Preferably, in step S2, the surface analysis uses the least squares method to fit the plane, as shown below:

[0026]

[0027] a is the normal vector of the fitted plane, and b is the parameter of the plane;

[0028] pi is a point in the point cloud;

[0029] zi is the height value of the point;

[0030] By fitting a plane in the point cloud data using the least squares method, we can find a plane that minimizes the sum of the squared distances from each point in the point cloud to that plane.

[0031] Preferably, the surface fitting in step S2 is expressed as follows:

[0032]

[0033] S(u,v) is a Bezier surface;

[0034] Pi j is a control point;

[0035] B i n and B j m These are Bezier basis functions;

[0036] Complex 3D surfaces are fitted using Bezier surfaces, with control points Pij and Bezier basis functions Bj. i n and B j m Used to generate smooth curved surfaces, suitable for fitting complex, free-form surfaces.

[0037] Preferably, the thickness optimization in step S2 is expressed as follows:

[0038] min ρ C(ρ)=f T u(ρ)

[0039] subject to:K(ρ)u(ρ)=f,V(ρ)≤Vmax,0≤ρ≤1

[0040] Where ρ is the material density distribution;

[0041] C(ρ) is the structural compliance;

[0042] f is the external force vector;

[0043] u is the displacement vector;

[0044] K(ρ) is the stiffness matrix;

[0045] V(ρ) is the material volume;

[0046] Vmax is the maximum volume limit;

[0047] To determine the optimal structure and thickness distribution of the protective enclosure, the optimal material distribution ρ is found under a given material volume Vρ constraint by minimizing the structural compliance C(ρ) to ensure maximum stiffness and minimum weight of the structure.

[0048] Preferably, the genetic algorithm in step S3 is represented as follows:

[0049] F(x) = αS(x) + βW(x) + γM(x)

[0050] Where x is the design variable;

[0051] α, β, γ are weighting coefficients;

[0052] S(x) is the intensity;

[0053] W(x) is the weight;

[0054] M(x) is the material cost;

[0055] Used in genetic algorithms to evaluate the merits of each design scheme, the goal is to maximize the fitness function. S(x), W(x), and M(x) represent the strength, weight, and material cost of the design, and the weighting coefficients α, β, and γ are used to balance the influence of different factors.

[0056] Compared with the prior art, the beneficial effects of the present invention are:

[0057] (1) The present invention can customize the design of protective shells or structures according to the specific object surface shape to ensure the best fit and protection effect. Through surface scanning and algorithm optimization, it can achieve accurate fitting and adaptation of complex shapes, improve the adaptability and performance of the protective shell. The thickness optimization algorithm can minimize the amount of material used while ensuring strength, save costs and improve sustainability.

[0058] (2) This invention utilizes multi-material printing technology to combine the advantages of different materials in a protective shell, thereby improving the overall performance and function. The protective shell can be customized according to individual needs to meet the specific needs of different application scenarios, thereby improving the personalization of the product and customer satisfaction. Attached Figure Description

[0059] Figure 1 This is a flowchart of a method for 3D printing protective materials according to the present invention. Detailed Implementation

[0060] 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 some embodiments of the present invention, and not all 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.

[0061] Example 1:

[0062] Please see Figure 1 As shown, a method for 3D printing protective materials includes the following steps:

[0063] S1. Model scanning: Use a 3D scanner to perform a full scan of the object to be protected, obtain accurate 3D data of its surface, save it as a point cloud or mesh model, and use point cloud data processing software to process the scanned data, remove noise and redundant data, and obtain a clean surface model.

[0064] S2. Surface calculation: Perform surface analysis, surface fitting and thickness optimization to obtain the mathematical model of the protective shell;

[0065] S3. Design the protective shell. Based on the mathematical model obtained in step S2, use genetic algorithm and particle swarm optimization (PSO) algorithm to further adjust the shell design and automatically generate a 3D model of the protective shell. The 3D model is fully adapted to the surface of the object, and necessary structural features are added as needed.

[0066] S4. Select printing materials. Based on the required protective properties, including impact resistance, chemical corrosion resistance, and high temperature resistance, select the corresponding 3D printing materials, such as TPU, PETG, and ASA.

[0067] S5. Material printing: Based on the complexity of the shell design and the material properties, set appropriate printing parameters, including layer height, infill density, printing speed and support structure. Import the optimized 3D model into the printing software, generate G-code and start printing.

[0068] S6. Post-processing: Remove the support structure generated during the printing process, perform grinding and polishing surface treatment to ensure the smoothness and precision of the shell. Based on the test results, make necessary design adjustments and optimizations, reprint and test until the protective shell fully meets expectations.

[0069] Specifically, point cloud data processing software includes MeshLab and Geomagic.

[0070] Specifically, in step S2, surface analysis uses computational geometry algorithms to analyze the surface features of the object and identify key geometric structures, including convex surfaces, concave surfaces, and planar regions.

[0071] Surface fitting uses surface fitting algorithms, including least squares fitting and Bezier surface fitting, to fit the surface of the object and generate an accurate mathematical model.

[0072] Thickness optimization uses finite element analysis (FEA) and topology optimization algorithms to determine the optimal thickness and structure of the protective shell, ensuring the best protection with minimal material usage.

[0073] Specifically, the protective properties in step S4 include impact resistance, chemical corrosion resistance, and high temperature resistance.

[0074] Specifically, noise removal in step S1 is represented as follows:

[0075]

[0076] Where pi is a point in the point cloud;

[0077] p i ′ represents the denoised point;

[0078] N(i) is the set of neighborhood points of point pi;

[0079] To smooth the point cloud data obtained from 3D scanning, the influence of noise and discrete points is reduced by averaging the neighboring points N(i) around point pi, thereby obtaining smoother and more accurate surface data.

[0080] Specifically, in step S2, the surface analysis uses the least squares method to fit the plane, as shown below:

[0081]

[0082] a is the normal vector of the fitted plane, and b is the parameter of the plane;

[0083] pi is a point in the point cloud;

[0084] zi is the height value of the point;

[0085] By fitting a plane in the point cloud data using the least squares method, we can find a plane that minimizes the sum of the squared distances from each point in the point cloud to that plane.

[0086] Specifically, the surface fitting in step S2 is expressed as:

[0087]

[0088] S(u,v) is a Bezier surface;

[0089] Pi j is a control point;

[0090] B i n and B j m These are Bezier basis functions;

[0091] Complex 3D surfaces are fitted using Bezier surfaces, with control points Pij and Bezier basis functions Bj. i n and B j m Used to generate smooth curved surfaces, suitable for fitting complex, free-form surfaces.

[0092] Specifically, the thickness optimization in step S2 is expressed as follows:

[0093] min ρ C(ρ)=f T u(ρ)

[0094] subject to:K(ρ)u(ρ)=f,V(ρ)≤Vmax,0≤ρ≤1

[0095] Where ρ is the material density distribution;

[0096] C(ρ) is the structural compliance;

[0097] f is the external force vector;

[0098] u is the displacement vector;

[0099] K(ρ) is the stiffness matrix;

[0100] V(ρ) is the material volume;

[0101] Vmax is the maximum volume limit;

[0102] To determine the optimal structure and thickness distribution of the protective enclosure, the optimal material distribution ρ is found under a given material volume Vρ constraint by minimizing the structural compliance C(ρ) to ensure maximum stiffness and minimum weight of the structure.

[0103] Specifically, the genetic algorithm in step S3 is represented as follows:

[0104] F(x) = αS(x) + βW(x) + γM(x)

[0105] Where x is the design variable;

[0106] α, β, γ are weighting coefficients;

[0107] S(x) is the intensity;

[0108] W(x) is the weight;

[0109] M(x) is the material cost;

[0110] Used in genetic algorithms to evaluate the merits of each design scheme, the goal is to maximize the fitness function. S(x), W(x), and M(x) represent the strength, weight, and material cost of the design, and the weighting coefficients α, β, and γ are used to balance the influence of different factors.

[0111] In an example of a printed stone-carved protective shell:

[0112] Step 1: Model Scanning

[0113] A 3D scanner was used to scan the stone carving from all angles to obtain 3D point cloud data of its surface.

[0114] The resulting point cloud data file is: stone_statue.ply.

[0115] Point cloud noise reduction:

[0116] Import point cloud data using MeshLab software and apply mean filtering for noise reduction.

[0117] The number of neighboring points is set to 10.

[0118] The denoised point cloud data file: stone_statue_denoised.ply.

[0119] Step 2: Surface Calculation

[0120] ① Surface analysis:

[0121] The surface feature analysis was performed using the open3D library in Python to identify the convex, concave, and planar areas of the stone carving.

[0122] ② Surface fitting:

[0123] The surface of the stone carving was fitted using the Bezier surface fitting algorithm.

[0124] The number of control points selected is n=10, m=10.

[0125] The fitted surface equation S(u,v) is obtained.

[0126] ③Thickness optimization:

[0127] Thickness optimization is performed using finite element analysis software (such as ANSYS).

[0128] Input the geometric data of the stone carving surface and the expected load conditions, and set the maximum material volume constraint Vmax = 100cm. 3 .

[0129] Step 3: Design the protective casing

[0130] Automatic shell generation:

[0131] Based on the optimization results, a 3D model of the protective shell was designed using SolidWorks or Fusion 360 software. This ensured that the inner cavity of the shell perfectly fit the stone carving surface.

[0132] Algorithm optimization:

[0133] The shell design is optimized using a genetic algorithm, with the objective function set as follows:

[0134] F(x)=0.5S(x)+0.3W(x)+0.2M(x)

[0135] Step 5: Select printing materials

[0136] Material selection:

[0137] TPU material was chosen because of its high strength and chemical resistance.

[0138] Material parameters: Density ρ = 1.22 g / cm³ 3 The tensile strength σt = 55 MPa.

[0139] Step 6: Material Printing

[0140] Print settings:

[0141] The floor height h = 0.2 mm.

[0142] The fill density ρf = 20%.

[0143] Printing speed vp = 60mm / s.

[0144] Model import and printing:

[0145] Import the designed 3D model into 3D printing software (such as Cura) to generate G-code.

[0146] Start printing and monitor the printing process in real time.

[0147] Step 8: Post-processing

[0148] Support removal and surface treatment:

[0149] Remove the supporting structure and treat the surface with sandpaper or a polishing tool.

[0150] The dimensions of the stone carving are: 10cm long, 7cm wide, and 5cm high.

[0151] Scanning accuracy: 0.1mm.

[0152] Maximum material volume: 100cm³ 3 .

[0153] Material selection: TPU, density 1.22g / cm³ 3 Tensile strength 55MPa.

[0154] Printing parameters: layer height 0.2mm, infill density 20%, printing speed 60mm / s.

[0155] As can be seen from the above, the present invention can customize the design of protective shells or structures according to the specific surface shape of objects, ensuring the best fit and protection effect. Through surface scanning and algorithm optimization, it can achieve accurate fitting and adaptation of complex shapes, improve the adaptability and performance of protective shells, and the thickness optimization algorithm can minimize the amount of material used while ensuring strength, saving costs and improving sustainability.

[0156] This invention utilizes multi-material printing technology to combine the advantages of different materials in a single protective shell, thereby improving overall performance and functionality. The protective shell can be customized according to individual needs to meet the specific requirements of different application scenarios, thus improving the personalization of the product and customer satisfaction.

[0157] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0158] The accompanying drawings of the embodiments disclosed in this invention only involve structures relevant to the embodiments disclosed in this invention. Other structures can be referred to with common designs. Unless otherwise specified, the same embodiment and different embodiments of this invention can be combined with each other.

[0159] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for 3D printing protective materials, characterized in that, Includes the following steps: S1. Model scanning: Use a 3D scanner to perform a full scan of the object to be protected, obtain accurate 3D data of its surface, save it as a point cloud or mesh model, and use point cloud data processing software to process the scanned data, remove noise and redundant data, and obtain a clean surface model. S2. Surface calculation: Perform surface analysis, surface fitting and thickness optimization to obtain the mathematical model of the protective shell; S3. Design the protective shell. Based on the mathematical model obtained in step S2, use genetic algorithm and particle swarm optimization (PSO) algorithm to further adjust the shell design and automatically generate a 3D model of the protective shell. The 3D model is fully adapted to the surface of the object, and necessary structural features are added as needed. S4. Select printing material. Choose the corresponding 3D printing material according to the required protection properties. S5. Material printing: Based on the complexity of the shell design and the material properties, set appropriate printing parameters, including layer height, infill density, printing speed and support structure. Import the optimized 3D model into the printing software, generate G-code and start printing. S6. Post-processing: Remove the support structure generated during the printing process, perform grinding and polishing surface treatment to ensure the smoothness and precision of the shell. Based on the test results, make necessary design adjustments and optimizations, reprint and test until the protective shell fully meets expectations.

2. The method for 3D printing protective materials according to claim 1, characterized in that: Point cloud data processing software includes MeshLab and Geomagic.

3. The method for 3D printing protective materials according to claim 1, characterized in that: In step S2, surface analysis uses computational geometry algorithms to analyze the surface features of the object and identify key geometric structures, including convex surfaces, concave surfaces, and planar regions. Surface fitting uses surface fitting algorithms, including least squares fitting and Bezier surface fitting, to fit the surface of an object and generate an accurate mathematical model. Thickness optimization uses finite element analysis (FEA) and topology optimization algorithms to determine the optimal thickness and structure of the protective shell, ensuring the best protection with minimal material usage.

4. The method for 3D printing protective materials according to claim 1, characterized in that: The protective properties in step S4 include impact resistance, chemical corrosion resistance, and high temperature resistance.

5. The method for 3D printing protective materials according to claim 1, characterized in that: The noise removal in step S1 is represented as follows: Where pi is a point in the point cloud; p i ′ represents the denoised point; N(i) is the set of neighborhood points of point pi; To smooth the point cloud data obtained from 3D scanning, the influence of noise and discrete points is reduced by averaging the neighboring points N(i) around point pi, thereby obtaining smoother and more accurate surface data.

6. The method for 3D printing protective materials according to claim 1, characterized in that: In step S2, the surface analysis uses the least squares method to fit the plane, which is expressed as: a is the normal vector of the fitted plane, and b is the parameter of the plane; pi is a point in the point cloud; zi is the height value of the point; By fitting a plane in the point cloud data using the least squares method, we can find a plane that minimizes the sum of the squared distances from each point in the point cloud to that plane.

7. The method for 3D printing protective materials according to claim 1, characterized in that: The surface fitting in step S2 is expressed as: S(u,v) is a Bezier surface; Pij is a control point; and These are Bezier basis functions; Complex 3D surfaces are fitted using Bezier surface modeling, with control points Pij and Bezier basis functions B. i n and B j m Used to generate smooth curved surfaces, suitable for fitting complex, free-form surfaces.

8. The method for 3D printing protective materials according to claim 1, characterized in that: The thickness optimization in step S2 is represented as follows: minutes ρ C(ρ)=f T u(r) subject to:K(ρ)u(ρ)=f,V(ρ)≤Vmax,0≤ρ≤1 Where ρ is the material density distribution; C(ρ) is the structural compliance; f is the external force vector; u is the displacement vector; K(ρ) is the stiffness matrix; V(ρ) is the material volume; Vmax is the maximum volume limit; To determine the optimal structure and thickness distribution of the protective enclosure, the optimal material distribution ρ is found under a given material volume Vρ constraint by minimizing the structural compliance C(ρ) to ensure maximum stiffness and minimum weight of the structure.

9. The method for 3D printing protective materials according to claim 1, characterized in that: The genetic algorithm in step S3 is represented as follows: F(x) = αS(x) + βW(x) + γM(x) Where x is the design variable; α, β, γ are weighting coefficients; S(x) is the intensity; W(x) is the weight; M(x) is the material cost; Used in genetic algorithms to evaluate the merits of each design scheme, the goal is to maximize the fitness function. S(x), W(x), and M(x) represent the strength, weight, and material cost of the design, and the weighting coefficients α, β, and γ are used to balance the influence of different factors.

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