3D printing path planning method and system

Abstract

The present invention relates to the field of printing path planning technology, and in particular to a 3D printing path planning method and system. The method comprises the following steps: first, obtaining and analyzing product design drawings to extract printing path turning structure data; then, simulating and analyzing the conditions for the formation of edge printing sawtooth effects based on the path turning structure data, and performing structural strength weakening calculations to obtain multi-scale feature data; then, mapping the strength weakening multi-scale feature data to a strength weakening curvature mutation association graph to optimize the segmented planning of the printing path and generate corresponding learning data; finally, transmitting the segmented path parameter planning data to a terminal to achieve accurate planning of the 3D printing path. The present invention further improves the printing path planning technology by optimizing the printing path planning technology.

Description

Technical Field

[0001] The present invention relates to the technical field of printing path planning, and in particular to a 3D printing path planning method and system. Background Art

[0002] The core advantages of 3D printing lie in its high-precision, low-cost, and free-form fabrication capabilities for complex structures. It holds great potential, particularly in personalized customization and small-batch production. However, despite its significant advantages, 3D printing still faces several technical challenges, particularly in print path planning. Appropriate print path planning is crucial for improving print quality and reducing time and material waste. Currently, the accuracy of print path planning directly impacts the quality of the final printed product. Optimizing path planning is particularly crucial when dealing with complex structures and high precision requirements. Previous 3D printing path planning methods have mostly focused on simple two-dimensional slice path design. While these methods work well for simple structures, complex three-dimensional structures can be prone to excessive path deflections, resulting in jagged edges, and even negatively impacting the product's structural strength. This is particularly true during edge printing, where limitations in the print head's trajectory and material deposition methods often lead to jagged edges, resulting in uneven, step-like structures. This not only impacts the product's appearance but also weakens its structural strength, potentially compromising its performance. However, a traditional 3D printing path planning method has the problem of the sawtooth effect that is very easy to appear when printing the turning shape of the product and the inaccurate pre-analysis of the strength structure of the print, which leads to large errors in the printing path planning. Summary of the Invention

[0003] Based on this, it is necessary to provide a 3D printing path planning method and system to solve at least one of the above technical problems.

[0004] To achieve the above object, a 3D printing path planning method is provided, the method comprising the following steps:

[0005] Step S1: obtaining a design drawing of a product to be printed; performing a path turning structure analysis on the design drawing of the printed product to obtain product printing path turning structure data;

[0006] Step S2: performing a simulation analysis of the conditions for forming the edge printing serration effect based on the product printing path turning structure data to obtain the conditions for forming the edge printing serration effect; performing a structural strength weakening calculation based on the conditions for forming the edge printing serration effect to obtain multi-scale characteristic data of the structural strength weakening;

[0007] Step S3: performing strength weakening curvature mutation association mapping based on the structural strength weakening multi-scale feature data to obtain strength weakening curvature mutation association mapping data; performing printing segmented path parameter planning based on the strength weakening curvature mutation association mapping data to obtain segmented path parameter planning learning data;

[0008] Step S4: Send the segmented path parameter planning learning data to the terminal to perform 3D printing path planning.

[0009] Preferably, step S1 includes the following steps:

[0010] Step S11: Obtaining the design drawing of the product to be printed;

[0011] Step S12: performing a printing topology analysis on the design drawing of the product to be printed to obtain product printing topology data;

[0012] Step S13: performing path turning structure analysis on the product printing topological structure data to obtain product printing path turning structure data.

[0013] Preferably, step S2 includes the following steps:

[0014] Step S21: identifying the curvature mutation area of the product printing path turning structure data to obtain the printing path turning curvature mutation area;

[0015] Step S22: performing simulation analysis on the conditions for forming the edge printing serration effect according to the curvature mutation area of the printing path, to obtain the conditions for forming the edge printing serration effect;

[0016] Step S23: performing structural strength weakening calculation based on the conditions for forming the edge printing sawtooth effect to obtain printing structural strength weakening data;

[0017] Step S24: performing multi-scale feature analysis on the printed structural strength weakening data to obtain multi-scale feature data of structural strength weakening.

[0018] Preferably, step S22 includes the following steps:

[0019] Step S221: Acquire initial parameters of the 3D printer, including initial printing speed, initial parameters of the printing material melt, and initial printing feed rate;

[0020] Step S222: calculating the curvature change rate step ratio for the curvature sudden change region of the printing path to obtain the curvature change rate step ratio;

[0021] Step S223: performing a corner sharpness increment correlation analysis on the curvature mutation area of the printing path based on the curvature change rate step ratio to obtain curvature-correlated corner sharpness increment data;

[0022] Step S224: Deducing and identifying the formation conditions of abnormal accumulation inside the printing edge based on the curvature change rate step ratio and the curvature-associated corner sharpness increment data according to the initial printing speed, initial printing material melt parameters, and initial printing feed rate in the initial parameters of the 3D printer, to obtain the formation conditions of abnormal accumulation inside.

[0023] Step S225: Based on the initial printing speed, initial printing material melt parameters, and initial printing feed rate in the initial parameters of the 3D printer, the curvature change rate step ratio and the curvature-associated corner sharpness increment data are used to deduce and identify the conditions for forming abnormal concave serrations on the outer side of the printed edge to obtain the conditions for forming abnormal concave serrations on the outer side;

[0024] Step S226: performing simulation analysis on the edge printing sawtooth effect formation conditions based on the inner side abnormal accumulation formation conditions and the outer side abnormal concave sawtooth formation conditions to obtain the edge printing sawtooth effect formation conditions.

[0025] Preferably, step S23 includes the following steps:

[0026] Step S231: analyzing the sawtooth surface slope distribution deviation based on the conditions for forming the edge printing sawtooth effect, and obtaining the sawtooth surface slope distribution deviation;

[0027] Step S232: identifying the inter-layer dislocation of sawtooth steps based on the sawtooth surface slope distribution deviation and the conditions for forming the edge printing sawtooth effect, and obtaining the inter-layer dislocation data of the sawtooth steps;

[0028] Step S233: performing interface adhesion equal weakening analysis on the sawtooth step interlayer dislocation data to obtain interface adhesion equal weakening data;

[0029] Step S234: performing structural strength weakening calculation based on the interface adhesion equivalent weakening data to obtain printed structural strength weakening data.

[0030] Preferably, step S233 includes the following steps:

[0031] The effective contact area loss analysis was performed on the interlayer dislocation data of the sawtooth step to obtain the effective contact area loss data of the interlayer dislocation;

[0032] According to the interlayer dislocation effective contact area loss data, the zigzag step interlayer dislocation data is analyzed for directional mismatch heat melt heat flow distribution imbalance, and the directional mismatch heat melt heat flow distribution imbalance data is obtained;

[0033] Perform internal stress imbalance regression analysis on the direction mismatch hot melt heat flow distribution imbalance data to obtain internal stress imbalance regression data;

[0034] Based on the internal stress imbalance regression data and the direction mismatch hot melt heat flow distribution imbalance data, the density loss equivalent simulation is carried out to obtain the density loss equivalent data;

[0035] Based on the internal stress imbalance regression data, directional mismatch hot melt heat flow distribution imbalance data and density loss data, the interface adhesion equal weakening analysis was performed to obtain the interface adhesion equal weakening data.

[0036] Preferably, step S3 includes the following steps:

[0037] Step S31: performing strength weakening curvature mutation association mapping on the curvature mutation region of the printing path according to the multi-scale characteristic data of structural strength weakening, to obtain strength weakening curvature mutation association mapping data;

[0038] Step S32: normalizing the intensity weakening curvature mutation association mapping data to obtain intensity weakening curvature mutation association normalized data;

[0039] Step S33: performing printing segment path parameter planning based on the strength weakening curvature mutation correlation normalization data to obtain printing segment path parameter planning data;

[0040] Step S34: performing logic learning on the printing segmented path parameter planning data to obtain segmented path parameter planning learning data.

[0041] Preferably, step S33 includes the following steps:

[0042] Step S331: performing linear scale division of the printing path based on the intensity weakening curvature mutation correlation normalization data to obtain linear scale division data of the printing path;

[0043] Step S332: performing printing acceleration matching between different divided paths on the linear scale division data of the printing path according to the strength weakened curvature mutation correlation normalization data, to obtain printing acceleration matching data between the different divided paths;

[0044] Step S333: performing extrusion amount / extrusion temperature matching based on the printing acceleration matching data and the strength weakening curvature mutation correlation normalization data to obtain extrusion amount / extrusion temperature matching data between different divided paths;

[0045] Step S334: performing retraction speed path mapping matching according to the printing acceleration matching data and the extrusion amount / extrusion temperature matching data to obtain retraction speed path mapping matching data;

[0046] Step S335: performing printing segment path parameter planning based on the printing acceleration matching data, the extrusion amount / extrusion temperature matching data, and the retraction speed path mapping matching data to obtain printing segment path parameter planning data.

[0047] Preferably, the present invention further provides a 3D printing path planning system for executing the 3D printing path planning method described above, the 3D printing path planning system comprising:

[0048] The path turning structure analysis module is used to obtain the design drawings of the product to be printed; perform path turning structure analysis on the design drawings of the printed product to obtain the product printing path turning structure data;

[0049] The structural strength weakening calculation module is used to simulate and analyze the conditions for the formation of edge printing serration effect based on the product printing path turning structure data to obtain the conditions for the formation of edge printing serration effect; based on the conditions for the formation of edge printing serration effect, the structural strength weakening calculation is performed to obtain multi-scale characteristic data of structural strength weakening;

[0050] The printing segmented path parameter planning module is used to perform strength weakening curvature mutation association mapping based on the multi-scale characteristic data of structural strength weakening to obtain strength weakening curvature mutation association mapping data; perform printing segmented path parameter planning based on the strength weakening curvature mutation association mapping data to obtain segmented path parameter planning learning data;

[0051] The execution feedback module is used to send the segmented path parameter planning learning data to the terminal to execute 3D printing path planning.

[0052] The beneficial effect of the present invention is that by analyzing the path turning structure of printed product design drawings, turning points and key areas of the product printing path can be extracted. This analysis process provides basic data for subsequent path planning. By obtaining and analyzing the path turning structure data, areas that have adverse effects during the printing process, such as excessively dense path turns or complex geometric shapes, can be more accurately identified, thereby laying a good foundation for optimizing the printing path, reducing unnecessary turns, and improving printing accuracy. By simulating and analyzing the conditions for the formation of edge printing serrations, edge unevenness that occurs during the printing process can be predicted. Edge printing serrations often result in an uneven product surface, affecting the appearance quality and even the structural strength. Through this step, the conditions for the occurrence of serrations can be accurately simulated, and structural strength weakening calculations can be performed to obtain multi-scale feature data, thereby providing strong data support for optimized design and path planning. This step not only improves print quality but also provides the necessary basis for subsequent optimization measures. By mapping the strength weakening curvature mutation association of the structural strength weakening multi-scale feature data, it is possible to accurately identify weakened areas in the printing path and correlate them with key factors such as curvature mutations. This process helps reveal the unevenness of the structural strength distribution and converts this information into key data for optimizing the printing path. Through this analysis, the printing path can be precisely adjusted to ensure that the weakened parts during the printing process are effectively compensated, avoiding product structural instability or insufficient strength caused by improper path planning. The optimized segmented path parameter planning learning data is transmitted to the terminal, and 3D printing path planning is executed. This process achieves precise control of the printing path, automatically adjusting the printer's path parameters based on previous analysis and calculation results, avoiding errors caused by manual intervention, and improving printing accuracy and speed. Through accurate path planning, not only can time and material waste during the printing process be effectively reduced, but the quality and reliability of the final product can also be improved, ensuring that it meets the expected structural strength and appearance requirements. Therefore, the present invention is an improvement to a traditional 3D printing path planning method. It solves the problems of the traditional 3D printing path planning method, which has the problem of the serration effect that is very easy to appear in the printing of the product's turning shape and the inaccurate pre-analysis of the printed strength structure, resulting in large errors in the printing path planning. It improves the accuracy of the serration effect that is very easy to appear in the printing of the product's turning shape and the pre-analysis of the printed strength structure, and reduces the error in the printing path planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 A schematic diagram of a 3D printing path planning method;

[0054] Figure 2 for Figure 1 Detailed implementation steps of step S2 in FIG.

[0055] Figure 3 for Figure 1 Detailed implementation steps of step S3 in FIG. DETAILED DESCRIPTION

[0056] See also Figures 1 to 3 , a 3D printing path planning method, the method comprising the following steps:

[0057] Step S1: obtaining a design drawing of a product to be printed; performing a path turning structure analysis on the design drawing of the printed product to obtain product printing path turning structure data;

[0058] Step S2: performing a simulation analysis of the conditions for forming the edge printing serration effect based on the product printing path turning structure data to obtain the conditions for forming the edge printing serration effect; performing a structural strength weakening calculation based on the conditions for forming the edge printing serration effect to obtain multi-scale characteristic data of the structural strength weakening;

[0059] Step S3: performing strength weakening curvature mutation association mapping based on the structural strength weakening multi-scale feature data to obtain strength weakening curvature mutation association mapping data; performing printing segmented path parameter planning based on the strength weakening curvature mutation association mapping data to obtain segmented path parameter planning learning data;

[0060] Step S4: Send the segmented path parameter planning learning data to the terminal to perform 3D printing path planning.

[0061] In the embodiment of the present invention, reference Figure 1 The above is a schematic flow chart of the steps of a 3D printing path planning method of the present invention. In this example, the 3D printing path planning method includes the following steps:

[0062] Step S1: obtaining a design drawing of a product to be printed; performing a path turning structure analysis on the design drawing of the printed product to obtain product printing path turning structure data;

[0063] In an embodiment of the present invention, the design drawings of the product to be printed are obtained by industrial-grade CAD modeling software (such as SolidWorks or AutoCAD) and converted into an STL format model. Subsequently, a geometric processing module based on mesh analysis (such as the CGAL library) is used to perform triangular mesh traversal analysis on the STL model, extract the normal vector of each facet, and mark the area where the angle between faces exceeds 15 degrees as the preliminary turning area. Then, high-density point sampling is performed on these turning areas along the model contour line direction, with a sampling point set every 0.1 mm, and the curvature estimation method in differential geometry (such as principal curvature estimation) is used to calculate the local curvature of the point set, thereby constructing the product printing path turning structure data. The data consists of the position of each turning area, the curvature change rate, the turning angle, the spatial coordinates, and the direction of the local normal vector, and is saved as a multidimensional vector table structure for subsequent analysis.

[0064] Step S2: performing a simulation analysis of the conditions for forming the edge printing serration effect based on the product printing path turning structure data to obtain the conditions for forming the edge printing serration effect; performing a structural strength weakening calculation based on the conditions for forming the edge printing serration effect to obtain multi-scale characteristic data of the structural strength weakening;

[0065] In one embodiment of the present invention, based on the structural data of the printing path transition, finite element simulation software (such as ANSYS) was used to construct a temperature and stress field model for the edge region. The simulation boundary conditions were set as an initial printing temperature of 200°C, PLA material, an initial feed rate of 50 mm / s, and a nozzle diameter of 0.4 mm. By simulating the material's thermal-mechanical coupling behavior within the transition region simulation path, the critical threshold for edge accumulation or concavity formation at different printing speeds and feed rates was evaluated, and the conditions for the formation of the edge jagged effect in the printing were determined. Furthermore, using a material micromechanics model, the structural thermal deformation in the critical point region was combined with the flow retention of the extruded material at sharp angles. The evolutionary paths of edge tensile stress concentration or abnormal internal material accumulation caused by the sharp transition of the printing path were extracted. Static calculations were performed on the structural strength changes caused by these paths. The shear stress distribution at the material joint and the stress attenuation trend at the interlayer bonding interface were calculated. Multi-scale characteristic data of structural strength weakening were output, mainly including the local stress concentration factor at the path mutation point, the interlayer misalignment distance, the local temperature gradient value, and the attenuation ratio of the interfacial bonding force.

[0066] Step S3: performing strength weakening curvature mutation association mapping based on the structural strength weakening multi-scale feature data to obtain strength weakening curvature mutation association mapping data; performing printing segmented path parameter planning based on the strength weakening curvature mutation association mapping data to obtain segmented path parameter planning learning data;

[0067] In an embodiment of the present invention, a graph structure analysis algorithm is used to perform high-dimensional feature mapping on multi-scale feature data of structural strength weakening. A Gaussian kernel function is used to perform regression fitting on the nonlinear mapping relationship between curvature changes in the turning region and local strength drops, generating strength weakening curvature mutation correlation mapping data. This data is used to construct a multi-path segmentation scheduling model. A segmentation weighting strategy is used to divide the associated regions into paths, with 0.5 mm as the minimum unit of path division, and printing parameters are set for each segment. Then, based on a hierarchical feature normalization algorithm (using Z-score normalization), physical quantities such as curvature, speed, and extrusion volume for all path segments are standardized to eliminate dimensional differences in physical quantities and form a normalized path dataset. Subsequently, a heuristic search algorithm (such as A*) is introduced to optimize the planning of printing path segments. For each path segment, based on the normalized data and the acceleration transformation requirements of adjacent paths, the acceleration increment is set to no more than 2 mm / s², the maximum speed is set to 60 mm / s, and the extrusion temperature is set to no more than 215°C. This generates printing segment path parameter planning data.

[0068] Step S4: Send the segmented path parameter planning learning data to the terminal to perform 3D printing path planning.

[0069] In an embodiment of the present invention, during the logic learning phase, a support vector regression (SVR) algorithm is used to perform error assessment and model feedback learning on the generated path parameter data. Training input features include local curvature, printing speed, material temperature, nozzle acceleration, and path inclination angle, and the output is a path interlayer adhesion stability score. This model undergoes 5-fold cross-validation with a data sample size greater than 10,000 groups to ensure stability. After training, a path segmentation parameter matching model is output and used to reoptimize the segmentation parameters to form the final segmented path parameter planning learning data. This learning data is exported to the 3D printing terminal via a G-code generation module, enabling high-precision path control and highly reliable structure printing path planning.

[0070] Step S1 includes the following steps:

[0071] Step S11: Obtaining the design drawing of the product to be printed;

[0072] Step S12: performing a printing topology analysis on the design drawing of the product to be printed to obtain product printing topology data;

[0073] Step S13: performing path turning structure analysis on the product printing topological structure data to obtain product printing path turning structure data.

[0074] In an embodiment of the present invention, a complete three-dimensional product model is obtained using a high-precision CAD modeling tool (such as Autodesk Inventor 2022). The model must contain a solid geometry structure with completely closed boundaries and no overlapping or duplicate boundary faces. After modeling is completed, the file is exported to a standard STL format, and the number of triangular facets must be greater than 50,000 to ensure model accuracy. After importing the STL file, the model is checked for integrity, including facet orientation consistency, boundary closure, and automatic hole filling. All boundaries are ensured to be closed entities with no self-intersections, overlapping, or missing facet areas. An STL verification module (such as Cleaning Filters in Meshlab) is used to clean the mesh to ensure that the model data used for subsequent topological structure analysis is free of geometric anomalies. Print topological structure analysis is performed based on the cleaned STL file. First, a three-dimensional mesh processing library (such as CGAL 5.5.2) is used to construct the edge adjacency graph structure of the STL facets, extract the normal vector of each facet, and construct a facet-adjacent facet relationship mapping table. Next, a topological region segmentation operation was performed. The angle between adjacent faces was used to determine whether they constituted a structural unit boundary. A threshold of 25 degrees was set, and any angle greater than this threshold was marked as a potential topological boundary. Multiple topological partitions were formed within the entire model based on spatial connectivity. Each topological partition was numbered and recorded as a separate printed region. Furthermore, the internal structure of each topological partition was simulated by slice thickness simulation using an evenly spaced slicing method with a slice thickness of 0.2 mm to generate a set of two-dimensional cross-sectional contours. Each layer's contour boundary was constructed by combining the intersection of faces and slices. Bilinear interpolation was used to determine the precise location of the intersection points, and the contour data for each layer was recorded as vector contour structure information. This information was used for subsequent path generation and curvature extraction. The generated printed topological structure data was subjected to path turning structure analysis. A geometric analysis algorithm based on curve discretization was used to process the contour lines of each layer. The line segment method was used to segment each layer with a segment length of 0.1 mm, and the angle between each adjacent line segment was calculated. All points with angles greater than 15 degrees are marked as path turning points, and their two-dimensional coordinates within the layer and the angle values with adjacent path segments are recorded. Subsequently, the normal vector difference analysis method is used to estimate the curvature change rate around each turning point. That is, with the point as the center, 5 path points are taken before and after, and the local average curvature change rate of the segment area is calculated. The curvature mutation intensity of the point is output in millimeters. After completion, the path turning points identified in all layers of the entire model are further mapped and synthesized in three dimensions to establish a complete product printing path turning structure data set. The data set includes the spatial coordinates (X, Y, Z) of the turning point, the layer number, the turning angle, the local curvature change rate, the adjacent path direction vector, the contour index value within the layer, etc. All turning structure data are output in CSV format and loaded into the subsequent analysis module for sawtooth effect analysis and path parameter planning.

[0075] Step S2 includes the following steps:

[0076] Step S21: identifying the curvature mutation area of the product printing path turning structure data to obtain the printing path turning curvature mutation area;

[0077] Step S22: performing simulation analysis on the conditions for forming the edge printing serration effect according to the curvature mutation area of the printing path, to obtain the conditions for forming the edge printing serration effect;

[0078] Step S23: performing structural strength weakening calculation based on the conditions for forming the edge printing sawtooth effect to obtain printing structural strength weakening data;

[0079] Step S24: performing multi-scale feature analysis on the printed structural strength weakening data to obtain multi-scale feature data of structural strength weakening.

[0080] As an example of the present invention, refer to Figure 2 As shown, in this example, step S2 includes:

[0081] Step S21: identifying the curvature mutation area of the product printing path turning structure data to obtain the printing path turning curvature mutation area;

[0082] In the embodiment of the present invention, based on the product printing path turning structure data obtained in step S13, the identification operation of the curvature mutation area is performed. First, the tangential angle of the path segment before and after each turning point is calculated, and the points with an angle greater than 20 degrees are selected as preliminary mutation candidate points. The differential geometry analysis method is used to calculate the discrete curvature of the 5th order neighborhood of the candidate point, and the three-point curvature formula of the discrete path is used to calculate the local curvature maximum value and change rate. All curvature change rates are greater than 3.5 Regions with sudden changes in curvature are marked as regions of curvature mutation. A region expansion algorithm based on continuous curvature gradients is further used to expand the sudden change points into continuous curvature mutation segments, each of which is at least 0.3 mm long and contains at least five points of high curvature. For each segment, the path coordinates of its start and end points, as well as the curvature and derivative values of all points within the segment, are recorded and output as a dataset of sudden change segment features. This process is implemented using a custom Python script combined with NumPy and SciPy, and the data is uniformly stored in structured JSON format for subsequent use.

[0083] Step S22: performing simulation analysis on the conditions for forming the edge printing serration effect according to the curvature mutation area of the printing path, to obtain the conditions for forming the edge printing serration effect;

[0084] In the embodiment of the present invention, based on the data of the curvature mutation area of the printing path obtained in step S21, a simulation analysis of the conditions for the formation of the edge printing sawtooth effect is performed. First, the curvature mutation area data is loaded, and the initial parameters of the 3D printer are set, including the printing speed ( )、Nozzle diameter( d=0.4 mm ), material melt viscosity ( μ=130 Pa·s , based on experimental measurements of ABS material at 240°C), the feed rate is set to 0.18 mm per layer. The local path corner sharpness is calculated based on the tangential change rate of each point in the mutation section, and the corner increment angle corresponding to each corner is analyzed using the gradient ratio method based on the curvature increment. The calculation method is the difference ratio of the angle change between each mutation point and the two nearest points on both sides. Points with a result greater than 1.5 are considered to be locations with abnormally intense edge transitions. Combined with the nozzle movement direction, the material inertia response time (in μ and The average hysteresis angle (2.3°) and thermosetting molding time (based on an experimentally determined ABS cooling time of 0.6s) were calculated to derive the conditions for material accumulation and concavity at high-curvature turning points. Whenever the tangent direction of the nozzle path changes by more than 18° within 0.6 seconds, the area is recorded as an abnormal accumulation or concavity segment and labeled as a sawtooth accumulation or concavity zone, depending on whether it occurs on the inside or outside of the path. Ultimately, the accumulation or concavity type, location coordinates, formation triggering conditions, and corresponding curvature change ratio within each sudden change region are output, forming a complete dataset of conditions for the formation of edge sawtooth effects.

[0085] Step S23: performing structural strength weakening calculation based on the conditions for forming the edge printing sawtooth effect to obtain printing structural strength weakening data;

[0086] In this embodiment of the present invention, a structural strength weakening calculation is performed based on the sawtooth effect formation condition data from step S22. A fitting mapping method based on the slope gradient and stacking height is used to calculate the change in effective interlayer overlap area in edge sawtooth regions. First, the normal vector angle of each printed layer within the sawtooth region is calculated. When the path normal angle between adjacent layers exceeds 10°, interlayer misalignment is considered, and the interlayer effective bonding area reduction rate is calculated. For stacking regions, for example, regions with a stacking height exceeding 1.25 times the nozzle layer thickness (0.2 mm) are marked as over-stacked. The coverage area of the underlying layer is calculated using the path width, with a reduction factor of 0.8. For recessed regions, a profile is derived based on the depth of the path boundary edge depression. When the depression depth exceeds 0.15 mm, the connection area between the path and the adjacent layer decreases by more than 20%, resulting in insufficient bonding strength. The strength weakening factor for each region is calculated based on the geometric overlap area, combining the path width (set to 0.48 mm) and the path spacing (set to 0.5 mm). All results are recorded per path unit segment (0.5 mm in length), including the corresponding serration type, interlayer misalignment angle, percentage reduction in effective bonding area, expected shear strength reduction, etc., and output as printed structure strength weakening data.

[0087] Step S24: performing multi-scale feature analysis on the printed structural strength weakening data to obtain multi-scale feature data of structural strength weakening.

[0088] In an embodiment of the present invention, a multi-scale feature analysis operation is performed on the structural strength weakening data output from step S23. First, the path unit segment is used as the basic scale, and the scale is aggregated upward to the hierarchical scale and the regional scale. Using the multi-resolution grid analysis method, the entire printed structure is divided into printing sub-region units with 5 layers as units. The density distribution of the weakened path segments is statistically analyzed in each unit, and the average shear strength weakening ratio of each region is calculated. Further, a wavelet transform analysis is performed in each region to detect the fluctuation frequency of the local shear strength weakening value with space, and to screen out regions with frequent weakening alternations (i.e., intensity disturbance regions with a frequency greater than 2 Hz). Such regions are marked as highly sensitive weakening regions. In addition, a principal direction component analysis is performed on each layer of the path structure to record the degree of concentration of the strength weakening section. When the path direction changes by less than 15° but the strength weakening value changes significantly, the region is marked as a latent structural degradation region. The final output is a multi-scale feature dataset, including the strength weakening value of the unit path segment, the average weakening rate of each layer, the sub-region shear strength disturbance frequency value, the weakening path distribution direction index, etc., providing structural input information for subsequent path planning and parameter compensation.

[0089] Step S22 includes the following steps:

[0090] Step S221: Acquire initial parameters of the 3D printer, including initial printing speed, initial parameters of the printing material melt, and initial printing feed rate;

[0091] Step S222: calculating the curvature change rate step ratio for the curvature sudden change region of the printing path to obtain the curvature change rate step ratio;

[0092] Step S223: performing a corner sharpness increment correlation analysis on the curvature mutation area of the printing path based on the curvature change rate step ratio to obtain curvature-correlated corner sharpness increment data;

[0093] Step S224: Deducing and identifying the formation conditions of abnormal accumulation inside the printing edge based on the curvature change rate step ratio and the curvature-associated corner sharpness increment data according to the initial printing speed, initial printing material melt parameters, and initial printing feed rate in the initial parameters of the 3D printer, to obtain the formation conditions of abnormal accumulation inside.

[0094] Step S225: Based on the initial printing speed, initial printing material melt parameters, and initial printing feed rate in the initial parameters of the 3D printer, the curvature change rate step ratio and the curvature-associated corner sharpness increment data are used to deduce and identify the conditions for forming abnormal concave serrations on the outer side of the printed edge to obtain the conditions for forming abnormal concave serrations on the outer side;

[0095] Step S226: performing simulation analysis on the edge printing sawtooth effect formation conditions based on the inner side abnormal accumulation formation conditions and the outer side abnormal concave sawtooth formation conditions to obtain the edge printing sawtooth effect formation conditions.

[0096] In an embodiment of the present invention, the initial parameters of the 3D printer are obtained, specifically by calling the firmware setting interface of the printing system controller to read the printing process parameters. The initial printing speed is set to 50 mm / s, based on the default speed of a commercial FDM 3D printer (such as the Ultimaker S3). The printing material is ABS engineering plastic, whose initial melt parameters include a melt temperature of 240°C, a melt viscosity of 130 Pa·s (this value is measured by a Brookfield rheometer at a set temperature), and a thermal conductivity of 0.18 W / (m·K). The initial printing feed is set to 0.2 mm per layer, the nozzle diameter is 0.4 mm, the path width is 0.48 mm, and the path spacing is 0.5 mm. These parameters are uniformly stored as a two-dimensional structured array to facilitate direct reference in subsequent calculation steps. The curvature change rate step ratio is calculated for the curvature mutation region of the printing path. First, the path mutation region is discretized and the path is extracted. Each turning segment is discretized into path nodes with an equidistant spacing of 0.2 mm. The differential curvature algorithm is used to calculate the first-order derivative curvature for each node and its two adjacent nodes. and the second-order derivative curvature . Then calculate the curvature change rate ( ), calculate the ratio of the change rate of two adjacent nodes to obtain the step ratio ΔK. Screen all points with ΔK values greater than 3.5 as abnormal curvature change points, and record the corresponding path coordinates, distance between points, ΔK value, and node sequence number. Based on the curvature change rate step ratio, perform corner sharpness increment correlation analysis on the curvature mutation area of the printing path. Obtain the initial sharpness angle by comparing the tangent angle of the path before and after the curvature mutation point. , and set the corresponding sharpness increment rule based on the ΔK value. When the ΔK value is between 3.5 and 5.0, the corresponding sharpness increment is set to 10°; when the ΔK value is between 5.0 and 7.0, the sharpness increment is 15°; when the ΔK value exceeds 7.0, the increment is set to 18°. Add this increment to the initial sharpness angle Finally, the final curvature-associated corner sharpness value R is obtained. All calculated values are recorded as an associated data set, including the path segment start and end coordinates, the original sharpness angle, the ΔK value, the sharpness increment, and the final sharpness angle. The output structure is a path segment array with five-tuple attributes. Based on the initial speed of the 3D printer, the initial parameters of the printing material melt, and the feed rate, the curvature change rate step ratio and the corner sharpness increment data are used to deduce and identify the conditions for the formation of abnormal inner corner accumulation. First, the accumulation time T of the material in the curvature sudden change section is calculated by combining the path motion direction and printing speed. This is calculated by dividing the path length by the speed. The material melt has an inertial hysteresis effect in the flow direction when the path makes a sharp turn. The hysteresis angle is set to 2.3° based on the melt viscosity and nozzle thrust. When the path tangent angle changes beyond the hysteresis angle and the sharpness angle exceeds 28°, the nozzle will continue to accumulate material in the inner corner area, forming a pile. All areas that meet the above angle conditions, have a ΔK value greater than 4.0, and a path radius less than 1.5 mm are marked as abnormal inner corner accumulation segments. The volume of the accumulation area was estimated using a 3D voxel profile. Effective accumulation was defined as an accumulation height exceeding 1.25 times the normal path height (0.2 mm). The accumulation point, path segment number, accumulation height, accumulation angle, and accumulation time parameters were output. Based on the same initial printer parameters, ΔK value, and sharpness angle data, the conditions for forming abnormal stretching concave serrations on the outer side of the printing path were deduced. At the corners of the outer side of the path, insufficient nozzle steering can cause material tension to fail to fill the area, resulting in concave serrations. The critical triggering condition for concave serrations was determined by matching the material solidification time (set to 0.6 s) with the nozzle path tangent steering rate. A corner segment of the path was designated as a high-risk area for concave formation if the nozzle achieved a change in direction angle greater than 15° within 0.6 s and a curvature change rate ΔK exceeding 5.0. After extracting the outer boundary of the nozzle path, the length of the unfilled area is calculated using the angle between line segments and the average propulsion rate. The coordinates of the outer concave areas, the estimated depth of the concave areas (marked as significant concave areas exceeding 0.15 mm), the corresponding corner angles, and the material solidification delay parameters are recorded. The conditions for the formation of inner abnormal accumulation and the formation of outer concave serrations obtained in steps S224 and S225 are integrated to complete the simulation analysis of the conditions for the formation of the overall edge serration effect. Using a spatial distribution analysis method, the inner and outer abnormal areas are mapped to the overall printing path coordinate system and annotated according to the path number. A region overlap search algorithm is used to mark complex serration areas where inner accumulation and outer concave areas overlap within the same region. A set of attribute labels is created for each region, including curvature value, ΔK value, sharpness angle, accumulation / sag type, affected path layer number, affected area, and structural orientation angle. This ultimately creates a structured dataset of edge serration conditions, which is used to guide subsequent path optimization and parameter modification. The data structure is a nested multidimensional array, supporting path-level, layer-level, and structure-level indexing.

[0097] Step S23 includes the following steps:

[0098] Step S231: analyzing the sawtooth surface slope distribution deviation based on the conditions for forming the edge printing sawtooth effect, and obtaining the sawtooth surface slope distribution deviation;

[0099] Step S232: identifying the inter-layer dislocation of sawtooth steps based on the sawtooth surface slope distribution deviation and the conditions for forming the edge printing sawtooth effect, and obtaining the inter-layer dislocation data of the sawtooth steps;

[0100] Step S233: performing interface adhesion equal weakening analysis on the sawtooth step interlayer dislocation data to obtain interface adhesion equal weakening data;

[0101] Step S234: performing structural strength weakening calculation based on the interface adhesion equivalent weakening data to obtain printed structural strength weakening data.

[0102] In an embodiment of the present invention, the conditions for forming the edge printing sawtooth effect are analyzed for the deviation of the slope distribution of the sawtooth surface. First, the path coordinate set of the sawtooth area is extracted from the data output in step S226, and a surface mesh model is constructed based on the three-dimensional coordinate points. The path points of the sawtooth area are meshed using the Delaunay triangulation method to obtain a continuous surface topology. The normal vector of each triangular face is calculated, and then the local slope of the surface at each point is obtained based on the angle between the component of the normal vector on the Z axis and the normal vector of the adjacent face. Subsequently, the deviation between all local slopes and the average value of the theoretical design surface normal of the area is calculated, and the slope distribution standard deviation, maximum deviation value and deviation variance ratio are statistically obtained to form a slope deviation distribution map of the sawtooth surface area. In a set of experimental data, using a 0.1 mm × 0.1 mm grid accuracy, the slope deviation range of a single sawtooth unit is obtained to be ±12°, with a standard deviation of 4.5°. This value exceeds the preset deviation threshold of 3°, so the area is marked as a slope deviation abnormal area. The conditions for the formation of serrations in edge printing are analyzed by using the slope distribution deviation of the sawtooth surface to identify serrations in interlayer misalignment. First, the contour edge lines of areas with slope deviation are extracted from each printed layer. Based on the coordinates of the path points in the same XY plane, the Z-axis height difference and the horizontal misalignment along the XY axes are calculated between corresponding points on the edge lines of two adjacent layers. Using the nearest neighbor path point pairing algorithm, the Euclidean distance and the projection values along each axis are calculated between each pair of paired points. If the XY projection length exceeds 0.05 mm while the Z-axis layer height remains constant at 0.2 mm, the point is recorded as a serration misalignment. The number of misalignment points between all adjacent layers is counted, and a density analysis is performed on concentrated areas of misalignment points. If the number of misalignment points exceeds three per unit area (1 mm²) and the concentrated area spans three consecutive layers, the area is considered to have a significant step misalignment structure. The output includes the misalignment path number, coordinates, adjacent layer difference, misalignment direction (X / Y), and interlayer offset angle. The interfacial adhesion isotropic weakening analysis is performed on the serration misalignment data. First, the length of the material overlap formed by the nozzle in the dislocated layer was calculated based on the XY-axis horizontal offset of the dislocated region. A model for calculating the effective bond area of the overlap region was established, combining the cooling shrinkage rate of the molten material (1.2% linear shrinkage for ABS), the path width (0.48 mm), and the extrusion thickness (0.2 mm). Using known material tensile test results, the interfacial shear bond strength of ABS solidified below 20°C was taken as a benchmark of 3.5 MPa. For path segments with an overlap area reduction of more than 15%, the bond strength was set to 0.75 times the benchmark value; for overlap area reductions of more than 25%, the bond strength was set to 0.5 times the benchmark value. For all path segments with equally weakened bond strength, a bond force distribution dataset was generated for each interlayer region. This dataset includes the path number, original bond area, effective overlap area after offset, bond strength reduction factor, and the bond strength value after reduction (in MPa).Based on the above-mentioned interfacial bond weakening data, a structural strength weakening calculation is performed. This step uses a regional mechanical equivalent analysis method, dividing the region with weakened bonding into independent structural units and treating each structural unit as a quasi-isotropic structure. By setting the loading direction of the entire printed part (e.g., vertical downward compression), the force response capacity of each structural unit in the loading direction is calculated. Using a layered integration method, the equivalent compression modulus and yield strength in the Z-axis direction are calculated for each unit with weakened bonding strength in each layer. The mechanical response parameters of all weakened regions are compared with the original design parameters to obtain the strength weakening ratio of each region. Taking experimental data as an example, if the bonding area in a certain path unit is reduced by 20% and the weakened strength is 65% of the original value, and the structure in which the path is located bears a concentrated load of 18N, the bearing capacity of the weakened path is only 11.7N as originally designed. By calculating all path segments within the entire printed body one by one, a strength distribution map of the entire printed structure and a list of weakened path identifiers are output for subsequent path parameter optimization planning.

[0103] Step S233 includes the following steps:

[0104] The effective contact area loss analysis was performed on the interlayer dislocation data of the sawtooth step to obtain the effective contact area loss data of the interlayer dislocation;

[0105] According to the interlayer dislocation effective contact area loss data, the zigzag step interlayer dislocation data is analyzed for directional mismatch heat melt heat flow distribution imbalance, and the directional mismatch heat melt heat flow distribution imbalance data is obtained;

[0106] Perform internal stress imbalance regression analysis on the direction mismatch hot melt heat flow distribution imbalance data to obtain internal stress imbalance regression data;

[0107] Based on the internal stress imbalance regression data and the direction mismatch hot melt heat flow distribution imbalance data, the density loss equivalent simulation is carried out to obtain the density loss equivalent data;

[0108] Based on the internal stress imbalance regression data, directional mismatch hot melt heat flow distribution imbalance data and density loss data, the interface adhesion equal weakening analysis was performed to obtain the interface adhesion equal weakening data.

[0109] In an embodiment of the present invention, when analyzing the effective contact area loss of sawtooth step interlayer misalignment data, the coordinate data of each pair of misaligned interlayer path segments is first extracted, and their overlap areas are analyzed using a two-dimensional XY projection perspective. A coordinate point overlap mapping method is used to calculate the overlapping area of adjacent path segments, where the previous layer's path segments are defined as the upper layer boundary line segment set A, and the next layer's path segments are defined as the lower layer boundary line segment set B. The overlapping area between the boundaries is then calculated. If the overlap width of the two path segments in the XY direction is less than 70% of the path nozzle extrusion width (0.4 mm)—that is, the overlap width is less than 0.28 mm—then the path segment is considered to have lost effective contact area. Under ABS material conditions, for segments with a layer height of 0.2 mm and an overlap length less than 0.28 mm, the lost area can reach over 40% of the original effective contact area. This step outputs the start and end coordinates of each misaligned path segment, the theoretical contact area, the actual overlap area, the loss ratio, and the corresponding layer number and direction vector. In analyzing the heat flux distribution imbalance of directional mismatch hot melt based on the loss of effective contact area due to interlayer misalignment, the heat conduction direction vector for each path segment is first defined. The main heat flux direction is calculated based on the angle between the path extension direction and the material ejection direction. For upper and lower path pairs with misaligned path segments, their melting center trajectories are marked and a heat flux vector model is constructed. Because the reduction in effective contact area will shorten or offset the local melt heat conduction path, a heat gradient vector field analysis method is used to calculate the rate of change of heat flux density in the Z-axis direction. It is found that when the misalignment angle exceeds 15° and the contact area loss rate exceeds 30%, the heat flux density in the main conduction direction decreases by an average of more than 12%, while the heat diffusion area in non-main directions increases by 16%. Through statistical regression between the heat flux change vector and the path misalignment angle, the heat flux distribution imbalance data for directional mismatch hot melt are output, including the heat flux vector deviation angle for each path segment, the change in heat conduction per unit area, and the heat flux distribution difference coefficient in each direction. In the process of internal stress imbalance regression analysis of the imbalance data of heat flux distribution of directional mismatch, the stress calculation of the local area of the dislocation path segment is carried out by establishing a thermal-mechanical coupling finite difference grid model. , cooling shrinkage strain of 1.2%, path width of 0.48mm, and path thickness of 0.2mm, the simulated hot melt zone cooling rate is 12°C / s. Combined with the heat flux distribution data, a non-uniform temperature gradient field is set in the imbalance area, and the thermal stress tensor is solved at each node. It is found that when the thermal stress direction of the end of the path is inconsistent with that of the middle of the sawtooth, the maximum shear stress offset exceeds 22%. The dislocation segments are divided into three categories: mild (stress offset less than 10%), moderate (10%-20%), and severe (more than 20%). The thermal stress difference, residual strain and shrinkage rate are recorded respectively to form the internal stress imbalance regression data, including the thermal-stress mapping relationship, stress change amplitude and thermal-mechanical non-synergy index of each path segment. In the process of performing density loss isometry simulation based on the internal stress imbalance regression data and the direction mismatch hot melt heat flux distribution imbalance data, the three-dimensional voxel grid method is used to numerically simulate the material filling degree in the dislocation area. The path region was divided into 0.1 mm³ voxel units, and density was assigned within each voxel, taking into account material shrinkage, porosity formation probability, and microscopic porosity changes in the melt-weakened region. In regions where thermal stress excursion exceeded 15%, the porosity per unit volume increased by an average of 5.2%, reaching as high as 8.7% in the most severe areas. The overall density reduction was estimated by combining the shrinkage of the path segments during cooling with the loss of overlap area. The final output, equivalent density loss data, included the path number, voxel density reduction, total volume porosity, volume shrinkage, and density excursion statistics. During the analysis of interfacial adhesion equivalent weakening based on internal stress imbalance regression data, directional mismatched melt heat flow distribution imbalance data, and density loss data, these three types of data were combined to establish an equivalent weakening model for interfacial performance. First, the change in the effective area of the bonding surface was evaluated at the microscale. Then, weighting factors (area loss factor, area loss factor, and density loss factor) were assigned to the three parameters, taking into account the reduction in melt penetration depth caused by directional heat flow conduction differences and the probability of internal crack propagation caused by residual thermal stress. , heat flow offset factor β=0.4 , stress perturbation factor γ=0.3 ). The equivalent bond strength of the final path segment is calculated using the linear combination of the three factors. For example, a path segment with a base bond strength of 3.5 MPa is weakened to 1.9 MPa under the influence of the three factors. All weakened path segments form a bond weakening dataset, including the path number, bond strength value after weakening, weakening percentage, weakening type identification label, and location coordinates.

[0110] Step S3 includes the following steps:

[0111] Step S31: performing strength weakening curvature mutation association mapping on the curvature mutation region of the printing path according to the multi-scale characteristic data of structural strength weakening, to obtain strength weakening curvature mutation association mapping data;

[0112] Step S32: normalizing the intensity weakening curvature mutation association mapping data to obtain intensity weakening curvature mutation association normalized data;

[0113] Step S33: performing printing segment path parameter planning based on the strength weakening curvature mutation correlation normalization data to obtain printing segment path parameter planning data;

[0114] Step S34: performing logic learning on the printing segmented path parameter planning data to obtain segmented path parameter planning learning data.

[0115] As an example of the present invention, refer to Figure 3 As shown, in this example, step S3 includes:

[0116] Step S31: performing strength weakening curvature mutation association mapping on the curvature mutation region of the printing path according to the multi-scale characteristic data of structural strength weakening, to obtain strength weakening curvature mutation association mapping data;

[0117] In an embodiment of the present invention, a strength weakening curvature mutation association mapping is performed on the curvature mutation area of the printing path turning point based on the multi-scale characteristic data of structural strength weakening. First, the printed structure strength weakening data output in step S234 is called. The data set contains the coordinate index of each path unit, the corresponding structural stress weakening value, the density deviation coefficient, and the reduction amplitude of the interface adhesion force. Then, all the curvature mutation points in the path geometry model are selected, and the second-order differential processing is performed with the path point set as input. The points where there are mutations in the continuous derivative of the path, that is, the points where the curvature change rate step ratio is greater than 0.3 are extracted as the boundaries of the curvature mutation area. Then, within the neighborhood of each curvature mutation point with a radius of 1.5 mm, a local spatial grid is established, and spatially superimposed with the strength weakening data. The structural weakening value is associated with the corresponding curvature point through a two-way index matching method. This process uses a multi-scale Gaussian kernel weighted method to normalize and aggregate the weakening strength values of each associated path segment, and outputs the average structural strength weakening value corresponding to each mutation curvature point and the distance difference data between its maximum shear stress position and the mutation point, forming strength weakening curvature mutation association mapping data.

[0118] Step S32: normalizing the intensity weakening curvature mutation association mapping data to obtain intensity weakening curvature mutation association normalized data;

[0119] In an embodiment of the present invention, the intensity weakening curvature mutation association mapping data obtained in step S31 is normalized by local range normalization. First, the set of structural weakening values corresponding to all mutation points is counted, and the maximum and minimum values are extracted therefrom. The range normalization formula is used to convert the value of each data point to the interval [0,1]. Since there is an obvious concentration trend in the weakening values at some mutation points, the quantile segmented normalization strategy is used to linearly stretch the first 20% and the last 20% of the data respectively, so as to enhance the differential expression in the overall distribution and avoid the submergence of weak signals. During the processing, in order to enhance the discrimination of the normalized data for the plasticity parameters of different path segments, the curvature value of each mutation point, the weakening value normalization result, the offset from the path center and the corresponding structural layer height are mapped to a unified four-tuple set, which is output as the normalization processing result.

[0120] Step S33: performing printing segment path parameter planning based on the strength weakening curvature mutation correlation normalization data to obtain printing segment path parameter planning data;

[0121] In this embodiment of the present invention, segmented printing path parameter planning is performed based on the normalized data associated with the strength-weakening curvature mutation generated in step S32. First, based on the normalized mutation point weakening value, the printing path is divided into three regions: high-risk (normalized value greater than 0.75), medium-risk (normalized value between 0.45 and 0.75), and low-risk (normalized value less than 0.45). Differentiated printing parameters are set for path segments with different risk levels. Taking PLA material as an example, under the conditions of a nozzle diameter of 0.4mm, a printing temperature of 200°C, and a standard layer height of 0.2mm, the low-risk zone maintains an initial printing speed of 60mm / s and a feed rate of 100%. The medium-risk zone reduces the printing speed to 48mm / s and increases the feed rate to 110%. The high-risk zone further reduces the speed to 38mm / s and increases the printing temperature to 205°C to enhance melt adhesion. Furthermore, a path overlap control strategy is implemented within the high-risk zone path segments, which overlaps adjacent path segments by 0.05mm laterally to ensure stable fill density. The final output is the printing segment path parameter planning data, including the path segment number, printing speed, feed rate, temperature, path overlap control value and its corresponding risk level label.

[0122] Step S34: performing logic learning on the printing segmented path parameter planning data to obtain segmented path parameter planning learning data.

[0123] In an embodiment of the present invention, logical learning is performed on the planning data of the printing segment path parameters. A decision tree logic learning algorithm based on path structure characteristics and parameter combinations is used to perform learning and analysis on historical printing data. The planning parameters of each path segment in step S33 and its corresponding curvature value, curvature change rate, historical printing defect record, shear stress simulation result, and defect density value of the final specimen constitute a training sample set, and the input features include path curvature characteristics, structural weakening characteristics, segment parameter set and physical printing feedback index. In the decision tree generation process, the final weakening degree of structural strength and the density reduction amplitude are used as classification basis to construct a multi-layer node decision path. The information gain rate is used as the segmentation criterion to output the optimal parameter combination rule for each type of path segment to form segment path parameter planning learning data, including path segment feature vector, optimal printing parameter recommendation combination, learning error rate and corresponding risk level comparison table. The learning data is used for automatic adjustment and optimization of path parameters in subsequent printing tasks.

[0124] Step S33 includes the following steps:

[0125] Step S331: performing linear scale division of the printing path based on the intensity weakening curvature mutation correlation normalization data to obtain linear scale division data of the printing path;

[0126] Step S332: performing printing acceleration matching between different divided paths on the linear scale division data of the printing path according to the strength weakened curvature mutation correlation normalization data, to obtain printing acceleration matching data between the different divided paths;

[0127] Step S333: performing extrusion amount / extrusion temperature matching based on the printing acceleration matching data and the strength weakening curvature mutation correlation normalization data to obtain extrusion amount / extrusion temperature matching data between different divided paths;

[0128] Step S334: performing retraction speed path mapping matching according to the printing acceleration matching data and the extrusion amount / extrusion temperature matching data to obtain retraction speed path mapping matching data;

[0129] Step S335: performing printing segment path parameter planning based on the printing acceleration matching data, the extrusion amount / extrusion temperature matching data, and the retraction speed path mapping matching data to obtain printing segment path parameter planning data.

[0130] In an embodiment of the present invention, linear scale division of a printing path is performed based on normalized data associated with intensity-weakened curvature mutations. The operation method is to construct a path segment division function using the normalized value in the normalized data as a control variable. The specific process is as follows: First, the normalized value Ri of each path point in the normalized data is obtained. The entire path is divided into several continuous segments based on its size. The linear scale division rule is set as follows: when the normalized value is greater than 0.75, the path segment length is 2.0mm; when the normalized value is between 0.45 and 0.75, the path segment length is 3.5mm; and when the normalized value is less than 0.45, the path segment length is 5.0mm. According to this division rule, the entire path is stepped equidistantly. At each step point, a one-time fitting and smoothing process is performed on the path directional derivative to ensure curvature continuity within each path segment. The output result is the path segment number, start and end coordinates, normalized value range, and corresponding linear scale length, forming the linear scale division data of the printing path. The linear scale division data of the printing path obtained in step S331 and the normalized data associated with intensity-weakened curvature mutations obtained in step S32 are used to match the printing acceleration between the different divided paths. The acceleration matching relationship is set using the linear scale length L and the normalized value R of each path segment as joint inputs. When the path segment length is less than or equal to 2.0mm and the normalized value is greater than 0.75, the acceleration is set to 400mm / s²; when the path segment length is between 2.0 and 3.5mm and the normalized value is between 0.45 and 0.75, the acceleration is set to 600mm / s²; when the path segment length is greater than 3.5mm and the normalized value is less than 0.45, the acceleration is set to 900mm / s². To prevent impact errors caused by acceleration jumps between different path segments, linear transition acceleration interpolation control is introduced at the path segment boundaries. That is, acceleration linear interpolation is used to buffer within 0.8mm before and after the boundary to keep the acceleration change rate within 300mm / s³. This step outputs the acceleration value corresponding to each path segment, the coordinates of the path boundary points, and the acceleration change slope information to form printing acceleration matching data. Based on print acceleration matching data and normalized data associated with strength-weakening curvature mutations, the extrusion rate and extrusion temperature are matched for different path segments. The process begins by jointly indexing the normalized value with the acceleration data and creating a mapping table. For path segments with lower acceleration and higher normalized values, indicating high structural strength requirements and low motion impact, enhanced melt sufficiency is required. Therefore, the extrusion temperature is increased to 205°C and the extrusion rate is set to 1.08 times the base rate. For path segments with medium normalized values and an acceleration of 600 mm / s², the extrusion temperature is set to 200°C and the extrusion rate is set to 1.03 times the base rate. The base rate refers to the default material extrusion rate used by the device under standard printing conditions, i.e., the standard reference value for achieving normal print quality under normal printing conditions without any risk classification or parameter optimization. For segments with lower normalized values and an acceleration of 900 mm / s², the temperature is lowered to 195°C to prevent buildup, and the extrusion rate is controlled at the standard rate or reduced to 0.95 times.This mapping outputs the extrusion volume percentage, temperature setting value, and path segment index for each path segment, forming extrusion volume / extrusion temperature matching data. "Extrusion volume / extrusion temperature matching based on printing acceleration matching data and strength weakening curvature mutation correlation normalization data" involves the coordinated optimization of two core parameters: printing acceleration and the normalized curvature strength weakening value on the printing path. Specifically, path acceleration data (such as 400mm / s², 600mm / s², 900mm / s², etc.) and the normalized structural strength weakening value (a dimensionless parameter in the range of 0-1) are jointly mapped. Differentiated control measures are implemented for different risk areas: High-risk area (normalized value > 0.75 and low acceleration): increase the extrusion temperature to 205°C and increase the extrusion volume to 1.08 times the base amount to enhance material melting and adhesion; medium-risk area (normalized value 0.45-0.75 and medium acceleration): maintain the standard temperature at 200°C and fine-tune the extrusion volume to 1.03 times; low-risk area (normalized value < 0.45 and high acceleration): Lower the temperature to 195°C and reduce the extrusion volume to 0.95 times to prevent material accumulation.

[0131] "Extrusion volume / extrusion temperature matching" refers to the coordinated adjustment of the material extrusion volume and heating temperature (i.e., extrusion temperature) during the 3D printing process, based on the structural performance requirements of different path segments and the motion characteristics of the printer nozzle, to achieve optimal molding quality. Specifically, for each path segment, according to its structural strength weakening degree and printing motion acceleration, the appropriate extrusion temperature and extrusion volume are set to ensure sufficient melting of the material. The optimal material extrusion parameter combination is comprehensively determined, including the extrusion temperature setting value and extrusion volume adjustment ratio corresponding to each different path segment. This data reflects the refined printing parameters formulated by regulating the material melting state and feed speed in different path segments to meet the molding quality and structural performance requirements. It is the key basis for achieving differentiated printing control, improving overall printing quality and structural reliability, so as to ensure the stability of filling density and interlayer bonding, thereby achieving the purpose of finely controlling printing quality and enhancing structural reliability.

[0132] Retraction speed path mapping is performed based on print acceleration matching data and extrusion rate / temperature matching data. This operation constructs a three-dimensional mapping function based on path acceleration and extrusion temperature. Specifically, when the acceleration is below 500mm / s² and the temperature is above 202°C, melt accumulation is likely to form, so the retraction speed is set to 38mm / s and the retraction length is 1.8mm. When the acceleration is 600mm / s² and the temperature is 200°C, the retraction speed is set to 32mm / s and the retraction length is 1.5mm. When the acceleration is greater than 800mm / s² and the temperature is less than 196°C, the retraction speed is set to 28mm / s and the retraction length is 1.2mm. Interpolation buffer zones are also set within the path boundary intervals to prevent sudden changes in retraction speed from causing transient pressure anomalies. The output data includes the path segment index, retraction speed, retraction length, and the coordinates of the retraction trigger point, forming the retraction speed path mapping data. The print acceleration matching data, extrusion rate / temperature matching data, and retraction speed path mapping data are integrated to plan the printing path parameters for each segment. The operation method is to integrate all control parameters in the path segment unit, and a single parameter set includes the start and end coordinates of the segment, path segment length, curvature change rate, normalization value, acceleration, temperature, extrusion volume ratio, retraction speed and retraction length. To ensure the continuity of parameters between path segments, parameter change control thresholds are set to force the temperature change between adjacent path segments to not exceed 4°C, the extrusion volume change to not exceed 10%, and the acceleration change to not exceed 300. , with the retraction speed varying by no more than 10 mm / s. The final output format is a path segment parameter table, arranged sequentially by segment number, recording the detailed set values for each control variable. This parameter planning data is directly used to drive the printing device to execute differentiated printing path control, enabling active compensation for weakened structural performance areas and process optimization.

[0133] The present invention also provides a 3D printing path planning system for executing the 3D printing path planning method described above, the 3D printing path planning system comprising:

[0134] The path turning structure analysis module is used to obtain the design drawings of the product to be printed; perform path turning structure analysis on the design drawings of the printed product to obtain the product printing path turning structure data;

[0135] The structural strength weakening calculation module is used to simulate and analyze the conditions for the formation of edge printing serration effect based on the product printing path turning structure data to obtain the conditions for the formation of edge printing serration effect; based on the conditions for the formation of edge printing serration effect, the structural strength weakening calculation is performed to obtain multi-scale characteristic data of structural strength weakening;

[0136] The printing segmented path parameter planning module is used to perform strength weakening curvature mutation association mapping based on the multi-scale characteristic data of structural strength weakening to obtain strength weakening curvature mutation association mapping data; perform printing segmented path parameter planning based on the strength weakening curvature mutation association mapping data to obtain segmented path parameter planning learning data;

[0137] The execution feedback module is used to send the segmented path parameter planning learning data to the terminal to execute 3D printing path planning.

[0138] The foregoing description is intended only to provide specific embodiments of the present invention, which will enable those skilled in the art to understand and implement the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not intended to be limited to the embodiments shown herein, but is to be construed in the widest possible manner consistent with the principles and novel features disclosed herein.

Claims

1. A 3D printing path planning method, characterized in that: The following steps are involved: Step S1: Obtain the design drawing of the product to be printed; Perform path turning structure analysis on the printed product design drawings to obtain product printing path turning structure data; Step S2: performing a simulation analysis of the conditions for forming the edge printing serration effect based on the product printing path turning structure data to obtain the conditions for forming the edge printing serration effect; performing a structural strength weakening calculation based on the conditions for forming the edge printing serration effect to obtain multi-scale characteristic data of the structural strength weakening; Step S3: performing strength weakening curvature mutation association mapping based on the structural strength weakening multi-scale feature data to obtain strength weakening curvature mutation association mapping data; performing printing segmented path parameter planning based on the strength weakening curvature mutation association mapping data to obtain segmented path parameter planning learning data; Step S4: Send the segmented path parameter planning learning data to the terminal to perform 3D printing path planning.

2. The 3D printing path planning method according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: Obtaining the product design drawing to be printed; Step S12: performing a printing topology analysis on the design drawing of the product to be printed to obtain product printing topology data; Step S13: performing path turning structure analysis on the product printing topological structure data to obtain product printing path turning structure data.

3. The 3D printing path planning method according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: identifying the curvature mutation area of the product printing path turning structure data to obtain the printing path turning curvature mutation area; Step S22: performing simulation analysis on the conditions for forming the edge printing serration effect according to the curvature mutation area of the printing path, to obtain the conditions for forming the edge printing serration effect; Step S23: performing structural strength weakening calculation based on the conditions for forming the edge printing sawtooth effect to obtain printing structural strength weakening data; Step S24: performing multi-scale feature analysis on the printed structural strength weakening data to obtain multi-scale feature data of structural strength weakening.

4. The 3D printing path planning method according to claim 3, characterized in that: Step S22 includes the following steps: Step S221: Acquire initial parameters of the 3D printer, including initial printing speed, initial parameters of the printing material melt, and initial printing feed rate; Step S222: calculating the curvature change rate step ratio for the curvature sudden change region of the printing path to obtain the curvature change rate step ratio; Step S223: performing a corner sharpness increment correlation analysis on the curvature mutation area of the printing path based on the curvature change rate step ratio to obtain curvature-correlated corner sharpness increment data; Step S224: Deducing and identifying the formation conditions of abnormal accumulation inside the printing edge based on the curvature change rate step ratio and the curvature-associated corner sharpness increment data according to the initial printing speed, initial printing material melt parameters, and initial printing feed rate in the initial parameters of the 3D printer, to obtain the formation conditions of abnormal accumulation inside. Step S225: Based on the initial printing speed, initial printing material melt parameters, and initial printing feed rate in the initial parameters of the 3D printer, the curvature change rate step ratio and the curvature-associated corner sharpness increment data are used to deduce and identify the conditions for forming abnormal concave serrations on the outer side of the printed edge to obtain the conditions for forming abnormal concave serrations on the outer side; Step S226: performing simulation analysis on the edge printing sawtooth effect formation conditions based on the inner side abnormal accumulation formation conditions and the outer side abnormal concave sawtooth formation conditions to obtain the edge printing sawtooth effect formation conditions.

5. The 3D printing path planning method according to claim 4, characterized in that: Step S23 includes the following steps: Step S231: analyzing the sawtooth surface slope distribution deviation based on the conditions for forming the edge printing sawtooth effect, and obtaining the sawtooth surface slope distribution deviation; Step S232: identifying the inter-layer dislocation of sawtooth steps based on the sawtooth surface slope distribution deviation and the conditions for forming the edge printing sawtooth effect, and obtaining the inter-layer dislocation data of the sawtooth steps; Step S233: performing interface adhesion equal weakening analysis on the sawtooth step interlayer dislocation data to obtain interface adhesion equal weakening data; Step S234: performing structural strength weakening calculation based on the interface adhesion equivalent weakening data to obtain printed structural strength weakening data.

6. The 3D printing path planning method according to claim 4, characterized in that: Step S233 includes the following steps: The effective contact area loss analysis was performed on the interlayer dislocation data of the sawtooth step to obtain the effective contact area loss data of the interlayer dislocation; According to the interlayer dislocation effective contact area loss data, the zigzag step interlayer dislocation data is analyzed for directional mismatch heat melt heat flow distribution imbalance, and the directional mismatch heat melt heat flow distribution imbalance data is obtained; Perform internal stress imbalance regression analysis on the direction mismatch hot melt heat flow distribution imbalance data to obtain internal stress imbalance regression data; Based on the internal stress imbalance regression data and the direction mismatch hot melt heat flow distribution imbalance data, the density loss equivalent simulation is carried out to obtain the density loss equivalent data; Based on the internal stress imbalance regression data, directional mismatch hot melt heat flow distribution imbalance data and density loss data, the interface adhesion equal weakening analysis was performed to obtain the interface adhesion equal weakening data.

7. The 3D printing path planning method according to claim 3, characterized in that: Step S3 includes the following steps: Step S31: performing strength weakening curvature mutation association mapping on the curvature mutation region of the printing path according to the multi-scale characteristic data of structural strength weakening, to obtain strength weakening curvature mutation association mapping data; Step S32: normalizing the intensity weakening curvature mutation association mapping data to obtain intensity weakening curvature mutation association normalized data; Step S33: performing printing segment path parameter planning based on the strength weakening curvature mutation correlation normalization data to obtain printing segment path parameter planning data; Step S34: performing logic learning on the printing segmented path parameter planning data to obtain segmented path parameter planning learning data.

8. The 3D printing path planning method according to claim 7, characterized in that: Step S33 includes the following steps: Step S331: performing linear scale division of the printing path based on the intensity weakening curvature mutation correlation normalization data to obtain linear scale division data of the printing path; Step S332: performing printing acceleration matching between different divided paths on the linear scale division data of the printing path according to the strength weakened curvature mutation correlation normalization data, to obtain printing acceleration matching data between the different divided paths; Step S333: performing extrusion amount / extrusion temperature matching based on the printing acceleration matching data and the strength weakening curvature mutation correlation normalization data to obtain extrusion amount / extrusion temperature matching data between different divided paths; Step S334: performing retraction speed path mapping matching according to the printing acceleration matching data and the extrusion amount / extrusion temperature matching data to obtain retraction speed path mapping matching data; Step S335: performing printing segment path parameter planning based on the printing acceleration matching data, the extrusion amount / extrusion temperature matching data, and the retraction speed path mapping matching data to obtain printing segment path parameter planning data.

9. A 3D printing path planning system, characterized in that: For executing the 3D printing path planning method according to claim 1, the 3D printing path planning system comprises: The path turning structure analysis module is used to obtain the design drawings of the product to be printed; perform path turning structure analysis on the design drawings of the printed product to obtain the product printing path turning structure data; The structural strength weakening calculation module is used to simulate and analyze the conditions for the formation of edge printing serration effect based on the product printing path turning structure data to obtain the conditions for the formation of edge printing serration effect; based on the conditions for the formation of edge printing serration effect, the structural strength weakening calculation is performed to obtain multi-scale characteristic data of structural strength weakening; The printing segmented path parameter planning module is used to perform strength weakening curvature mutation association mapping based on the multi-scale characteristic data of structural strength weakening to obtain strength weakening curvature mutation association mapping data; perform printing segmented path parameter planning based on the strength weakening curvature mutation association mapping data to obtain segmented path parameter planning learning data; The execution feedback module is used to send the segmented path parameter planning learning data to the terminal to execute 3D printing path planning.

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