A method for error evaluation and printing parameter optimization of curved surface 3D printing

Abstract

This application discloses an error assessment method and printing parameter optimization method for curved 3D printing. The surface layered error assessment method starts with a three-dimensional model, first planning the 3D model printing path, then combining the 3D model and the printing path. An error assessment model is established based on the relationship between printing parameters, surface position, and printing error. The error analysis point is then identified based on the error assessment model, and the surface 3D printing error is calculated. Finally, the error is compared with the expected error to determine whether the manufacturing requirements are met. The advantage of this assessment method is that the error can be assessed before 3D printing, and the printed part does not need to be measured, thus avoiding measurement errors.

Description

Technical Field

[0001] The present application relates to the field of 3D printing, and specifically to an error evaluation method and a printing parameter optimization method for curved surface 3D printing. Background Art

[0002] 3D printing technology, with its advantages of strong molding capabilities and high automation, is widely used in fields such as aerospace, automotive, and medicine. However, existing 3D printing technologies mostly use a planar layered manufacturing principle, which inevitably leads to a staircase effect when printing parts with curved contours. This seriously affects the precision and surface quality of the parts, hindering the development and application of 3D printing technology.

[0003] To address these issues, researchers in this field have proposed a surface-layered 3D printing method. This method involves slicing and layering a part based on its surface features, generating a 3D printing path on the surface, and finally producing the part using a 3D printer. This method effectively reduces the stair-step effect in printed models, but because the 3D printer's nozzle structure struggles to perfectly align with the surface contour, there are still discrepancies between the actual printed part and the ideal part's contour.

[0004] Most existing error assessment methods rely on instruments to measure and evaluate errors on printed parts. This approach has drawbacks such as high evaluation costs and long production cycles. Furthermore, the process parameters of curved layered 3D printing directly impact the accuracy and efficiency of part formation. These error assessment methods make it difficult to rationally select and optimize these process parameters before part printing. Summary of the Invention

[0005] This application provides an error assessment method and a printing parameter optimization method for curved surface 3D printing, so as to achieve rapid prediction and evaluation of 3D printed part errors and provide a basis and means for optimizing the printing parameters of high-precision parts.

[0006] To achieve the above objectives, the present application provides a method for error assessment of curved surface 3D printing, comprising the following steps:

[0007] Step 101: Create a three-dimensional surface model using computer-aided design software;

[0008] Step 102: performing path planning for 3D printing of the established curved surface three-dimensional model;

[0009] Step 103: Establish an error assessment model: Compare the path of the surface 3D printing with the three-dimensional model, calculate the printing parameters, and obtain an error assessment model between the ideal surface contour and the actual printed contour based on the relationship between the surface position and the printing error;

[0010] Step 104: Find the error analysis point: Analyze the point with the largest 3D printing error on the surface based on the error evaluation model. Input the printing parameter values into the error evaluation model determined in step 103. Then, use the control variable method to determine the influence of the surface radius r, the surface normal of the ideal profile, and the angle θ of the printing platform on the 3D printing error of the surface. Select the radius r0 and angle θ0 that have the greatest influence on the error and record them as the error analysis point.

[0011] Step 105: Calculate the surface 3D printing error: Input the printing spacing d, printing thickness h, surface radius r0, and the angle θ0 between the surface normal of the ideal profile and the printing platform into the error evaluation model determined in step 103 to obtain the surface 3D printing error δ;

[0012] Step 106: Evaluate the surface 3D printing error: Compare the error value δ calculated in step 105 with the expected error value δ0 to evaluate whether the surface 3D printing meets the manufacturing requirements.

[0013] In some embodiments of the present application, the specific method of planning the printing path for the model in step 102 includes:

[0014] 1) Plan the surface 3D printing path according to the surface layering method;

[0015] 2) Projecting the plane path onto the curved surface to generate a curved printing path;

[0016] 3) Plan the curved surface 3D printing path according to the plane layering method;

[0017] In some embodiments of the present application, the error evaluation model is established in step 103, specifically:

[0018] 1) Plan the surface 3D printing path according to the surface layering method, and the error analysis model is

[0019]

[0020] 2) Surface 3D printing is achieved by planning the printing path in a plane and then projecting it onto the surface

[0021] Path, the error analysis model is:

[0022]

[0023] 3) Error analysis model based on the curved printing path generated by plane layering:

[0024]

[0025] Where δ is the error of surface 3D printing, r is the radius of the surface; θ is the angle between the surface normal of the ideal contour and the printing platform, d is the printing spacing; h is the printing thickness;

[0026] In some embodiments of the present application, δ is the error of surface 3D printing, which is the distance between the local normal vector of the ideal surface profile and the actual processed surface profile.

[0027] In some embodiments of the present application, a parameter optimization method for curved layered 3D printing is also provided:

[0028] Step 201: Create a three-dimensional surface model and plan a printing path;

[0029] Step 202: Selecting a suitable error evaluation model according to the surface 3D printing path planning method;

[0030] Step 203: Find the surface feature points, determine the surface radius r and the angle θ between the surface normal of the ideal profile and the printing platform in the error assessment model;

[0031] Step 204: List the configurable printing spacing values into an array D and arrange them from largest to smallest, naming them d1, d2, d3, ...d n ; List the configurable print thickness values into an array H and arrange them in descending order, naming them h1, h2, h3...h n .

[0032] Step 205: Analyze the printing parameters that may affect the error value in the error evaluation model, and set the printing parameters as variables. If the variable is the printing spacing, select array D; if the variable is the printing thickness, select array H;

[0033] Step 206: Substitute the first value in the array selected in step 205 into the error evaluation model to calculate the error value δ;

[0034] Step 207: Compare the calculated error value δ with the expected error value δ0. If the calculated error value is smaller than the expected error value, set the printing parameter to the actual printing parameter value; if the calculated error value is larger than the expected error value, select the next printing parameter in the array in step 205, and continue to calculate and compare until the error value is smaller than the expected error value.

[0035] In some embodiments of the present application, the specific steps for finding the surface feature points in step 203 are: first determine the printing spacing d and the printing thickness h, and then analyze the influence of the surface radius r, the surface normal of the ideal contour and the angle θ of the printing platform on the surface error according to the error evaluation model selected in step 202, and select the radius and angle that have the greatest impact on the error and record them as the surface feature points.

[0036] The surface error assessment method proposed in this application starts with a 3D model. The 3D model printing path is first planned, and then the 3D model and printing path are combined. An error assessment model is established based on the relationship between printing parameters, surface position, and printing error. The error analysis point is then identified based on the error assessment model, and the surface 3D printing error is calculated. Finally, the error is compared with the expected error to determine whether the manufacturing requirements are met. The advantage of this assessment method is that it can assess the error before 3D printing, and it does not require measurement of the printed part, thus avoiding measurement errors.

[0037] The parameter optimization method for curved 3D printing proposed in this application first selects an appropriate error assessment model. It then analyzes the error assessment model to identify surface feature points and variables that affect the error. The printing parameters are then adjusted from large to small. Finally, the printing parameters are substituted into the error assessment model and compared with the expected error values to optimize the optimal printing parameters. Compared to other methods, the surface layered 3D printing parameter optimization method proposed in this application does not require frequent printing, thus avoiding waste of time and resources. It optimizes printing parameters, improves print quality, and reduces material and time losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solution in the embodiment of the present method, the following briefly introduces the drawings required for describing the embodiment.

[0039] Figure 1 Flowchart of the error evaluation method for surface layered 3D printing;

[0040] Figure 2 Flowchart of the parameter optimization method for surface layered 3D printing;

[0041] Figure 3 Error model diagram of the surface printing path generated by surface layering;

[0042] Figure 4 The error model diagram of the curved printing path is generated by projecting the plane path onto the curved surface;

[0043] Figure 5 Error model diagram of the curved surface printing path generated by plane layering;

[0044] Figure 6 Three-dimensional model diagrams of some embodiments of this application;

[0045] Figure 7 Curves showing the relationship between the radius r of the curved surface, the angle θ between the curved surface normal of the ideal profile and the printing platform, and the error in some embodiments of the present application.

[0046] Specific example method

[0047] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0048] Example 1

[0049] In some embodiments of the present application, the obtained curved 3D printing path is generated by projecting the planar printing path onto the curved surface, and the printed model is a semicircle, such as Figure 5 shown.

[0050] The error evaluation method for surface layered 3D printing in this example is as follows:

[0051] Step 101: Use UG NX to create a 3D surface model, such as Figure 5 shown.

[0052] Step 102: Plan a 3D printing path for the three-dimensional surface model. The method used in this example is to plan the printing path in a plane and then project the path onto the surface.

[0053] Step 103: Compare the surface printing path planned in step 102 with the 3D model in step 101, calculate the printing parameters, the relationship between the surface position and the printing error, establish an error evaluation model, and achieve accurate prediction of the surface 3D printing error. The error model of the path planning method used in this example is

[0054]

[0055] Step 104: Find the error analysis point. Analyze the point with the largest error in the 3D printing of the curved surface based on the error evaluation model. Input the printing parameter values (in this embodiment, the spacing d = 0.04mm) into step 103 to determine the error evaluation model. Then, using the control variable method, determine the influence of the curved surface radius r, the surface normal of the ideal contour, and the angle θ of the printing platform on the curved surface 3D printing error, as shown in the following figure: Figure 6 , it can be seen that the error is most affected by the point where θ is 0° and the radius is the smallest. Since the model in this example is a semicircle with equal radius, the point where the angle between the surface normal of the ideal contour and the printing platform is 0° is selected as the error analysis point.

[0056] Step 105: Calculate the surface 3D printing error. Input the print spacing d, print thickness h, surface radius r0, and the angle θ0 between the surface normal of the ideal profile and the printing platform into the error evaluation model determined in step 103 to obtain the surface 3D printing error δ.

[0057] Step 106: Evaluate the surface 3D printing error. Compare the error value δ calculated in step 105 with the expected error value δ0 to evaluate whether the surface 3D printing meets the manufacturing requirements.

[0058] Example 2:

[0059] The specific method for optimizing the parameters of surface layered 3D printing in this example is as follows:

[0060] Step 201: Create a 3D model and perform path planning. The model used in this example is Figure 5 As shown in FIG, the printing path planning method is to project the path planned on the plane onto the curved surface.

[0061] Step 202: Select an appropriate error model:

[0062]

[0063] Step 203: Determine the printing spacing d = 0.04 mm, analyze the influence of the radius r and the angle θ between the surface normal of the ideal profile and the printing platform and the error, and Figure 6 It can be seen that the error is most affected by the point where θ is 0° and the radius is the smallest. Since the model in this example is a semicircle with equal radius, the point where the angle between the surface normal of the ideal contour and the printing platform is 0° is selected as the surface feature point.

[0064] Step 204: List the configurable printing spacing values into an array D and arrange them from largest to smallest, naming them d1, d2, d3, ...d n ; List the configurable print thickness values into an array H and arrange them in descending order, naming them h1, h2, h3...h n .

[0065] Step 205: In the error model of this example, the parameter that affects the error is the printing distance. The printing distance is a variable of this example, and array D is selected.

[0066] Step 206: Select the first value d1 in the array D and substitute it into the formula to calculate the error value δ.

[0067] Step 207: Compare the calculated error value δ with the expected error value δ0. If the calculated error value is smaller than the expected error value, set the printing parameter to the actual printing parameter value; if the calculated error value is larger than the expected error value, select the next printing parameter in array D, and continue to calculate and compare until the error value is smaller than the expected error value.

[0068] Example 3

[0069] The difference from Example 1 is that the surface 3D printing path is planned according to the surface layering method, and the error analysis model is

[0070]

[0071] Example 4

[0072] The difference from Example 1 is that the curved surface printing path is generated based on the plane layering, and the error analysis model is:

[0073]

[0074] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for error assessment of curved surface 3D printing, characterized in that: The method comprises the following steps: Step 101: establishing a three-dimensional surface model using computer-aided design software; Step 102: performing 3D printing path planning on the established three-dimensional surface model; Step 103: Establish an error evaluation model: Compare the path of the surface 3D printing with the three-dimensional surface model, calculate the relationship between the printing parameters, the surface position and the printing error, and obtain an error evaluation model between the ideal surface contour and the actual printed contour; Step 104: Find the error analysis point: Analyze the point with the largest 3D printing error on the surface based on the error evaluation model: Input the printing parameter values d and h into the error evaluation model determined in step 103, and use the control variable method to determine the influence of the radius r on the surface, the surface normal of the ideal contour, and the angle θ on the printing platform on the 3D printing error of the surface. Select the radius r0 and angle θ0 that have the greatest influence on the error and record them as the error analysis point; Step 105: Calculate the surface 3D printing error: Input the printing spacing d, printing thickness h, surface radius r0, and the angle θ0 between the surface normal of the ideal profile and the printing platform into the error evaluation model determined in step 103 to obtain the surface 3D printing error δ; Step 106: Evaluate the surface 3D printing error: compare the error value δ calculated in step 105 with the expected error value δ0 to evaluate whether the surface 3D printing meets the manufacturing requirements; The method for path planning in step 102 is to plan the curved surface 3D printing path according to the surface layering method, or to plan the printing path in a plane and then project it onto the surface to obtain the curved surface 3D printing path; or to plan the curved surface 3D printing path according to the plane layering method; When the path planning method in step 102 is to plan the surface 3D printing path according to the surface layering method, the error evaluation model is: Alternatively, when the path planning method in step 102 is to plan the printing path in a plane and then project it onto a curved surface to obtain a curved 3D printing path, the error evaluation model is: Alternatively, when the path planning method in step 102 is a curved printing path generated by plane layering, the error evaluation model:

2. A parameter optimization method for curved surface 3D printing, characterized in that: The following steps are involved: Step 201: Create a three-dimensional surface model and plan a printing path; Step 202: Selecting a suitable error evaluation model according to the surface 3D printing path planning method; Step 203: Find the surface feature points, determine the surface radius r and the angle θ between the surface normal of the ideal profile and the printing platform in the error assessment model; Step 204: List the configurable printing spacing values into an array D and arrange them from largest to smallest, naming them d1, d2, d3, ...d n ; List the configurable print thickness values into an array H and arrange them in descending order, naming them h1, h2, h3...h n ; Step 205: Analyze the printing parameters that may affect the error value in the error evaluation model and select a suitable array. If the variable is the printing spacing, select array D; If the variable is printing thickness, select array H; Step 206: Substitute the first value in the array selected in step 205 into the error evaluation model to calculate the error value δ; Step 207: Compare the calculated error value δ with the expected error value δ0. If the calculated error value is smaller than the expected error value, set the printing parameter to the actual printing parameter value; if the calculated error value is larger than the expected error value, select the next printing parameter in the array in step 205, and continue to calculate and compare until the error value is smaller than the expected error value.

3. The parameter optimization method for curved surface 3D printing according to claim 2, characterized in that: In step 203, the surface feature points are found specifically as follows: first, the printing spacing d and the printing thickness h are determined, and then, based on the error evaluation model, the influence of the radius r on the surface, the surface normal of the ideal contour, and the angle θ of the printing platform on the surface error is analyzed, and the radius and angle that have the greatest influence on the error are selected and recorded as the surface feature points.

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