Adaptive object boundary reinforced 3D printing technical method and integrated system

Abstract

The invention relates to the technical field of 3D printing, and discloses a self-adaptive object boundary reinforced 3D printing technical method and an integrated system.The method comprises the steps that a high stress area and a boundary area for printing a 3D model are determined; constructing a multi-scale network for printing the 3D model, defining a multi-region printing material for printing the 3D model, and determining a material transformation gradient of the multi-region printing material; the method comprises the following steps: constructing a sensing network and printing equipment of a to-be-printed target, and defining a multi-scale boundary strengthening path of the printing equipment; printing data of a to-be-printed target is collected through a sensing network, the empty driving distance of printing equipment is calculated, path optimization is conducted on the multi-scale boundary strengthening path, and an optimized multi-scale path is obtained; and the current printing quality of the to-be-printed target is analyzed, the optimized printing parameters of the to-be-printed target are defined, and adaptive object boundary strengthening of the to-be-printed target is executed based on the optimized printing parameters. The boundary strengthening effect of the to-be-printed target can be improved.

Description

Technical Field

[0001] The invention relates to a self-adaptive object boundary reinforcement 3D printing technical method and an integrated system, belonging to the technical field of 3D printing. Background Art

[0002] Adaptive object boundary reinforcement 3D printing technology refers to a printing technology that uses advanced software algorithms and 3D printing hardware to automatically adjust printing parameters and material properties according to the geometric characteristics of the printed object and the expected use conditions, so as to achieve enhanced physical properties (such as strength, toughness, durability, etc.) at the boundary or high stress area of ​​the object. The application of adaptive object boundary reinforcement 3D printing technology can greatly promote the development of additive manufacturing technology, enabling 3D printing to produce more complex and high-performance parts and products.

[0003] Traditional adaptive object boundary reinforcement 3D printing usually relies on preset printing parameters and single material properties, and enhances the boundary area through simple geometric modifications or adding support structures. This method often lacks specificity and flexibility, resulting in low printing efficiency, serious material waste, and difficulty in achieving precise reinforcement of complex models. Summary of the invention

[0004] The present invention provides an adaptive object boundary enhancement 3D printing technical method and an integrated system, the main purpose of which is to improve the boundary enhancement effect of a target to be printed.

[0005] To achieve the above-mentioned purpose, the present invention provides an adaptive object boundary enhancement 3D printing technology method, comprising: Obtaining a printed 3D model of the target to be printed, analyzing geometric features of the printed 3D model, wherein the geometric features include curvature, thickness, and boundary, and determining high stress areas and boundary areas of the printed 3D model according to the geometric features; Constructing a multi-scale network of the printed 3D model according to the high stress area and the boundary area, defining multi-region printing materials of the printed 3D model based on the multi-scale network, and determining a material transformation gradient of the multi-region printing materials; Constructing a sensor network and a printing device of the target to be printed, and defining a multi-scale boundary reinforcement path of the printing device according to the multi-scale network; Based on the multi-scale boundary reinforcement path, the material transformation gradient, the printing device and the multi-region printing material, the printing data of the target to be printed is collected by using the sensor network, the idle driving distance of the printing device is calculated according to the printing data, and the multi-scale boundary reinforcement path is optimized according to the idle driving distance to obtain an optimized multi-scale path; Based on the optimized multi-scale boundary enhancement path, the current printing quality of the target to be printed is analyzed, and according to the current printing quality, the optimized printing parameters of the target to be printed are defined, and the adaptive object boundary enhancement of the target to be printed is performed based on the optimized printing parameters.

[0006] Optionally, analyzing the geometric features of the printed 3D model includes: Smoothing the printed 3D model to obtain a smoothed 3D model; Performing surface subdivision on the smoothed 3D model to obtain a surface subdivision 3D model; Calculating the curvature of the tessellated 3D model; Analyzing the closure coefficient of the printed 3D model; When the closure coefficient meets a preset closure threshold, the printed 3D model is offset to obtain an offset 3D model; calculating a surface volume between the offset 3D model and the printed 3D model; Based on the surface volume, determining a thickness of the printed 3D model; Marking the boundaries of the printed 3D model; The geometric features of the printed 3D model are determined according to the curvature, the thickness, and the boundary.

[0007] Optionally, calculating the curvature of the tessellated 3D model includes: Determining model vertices of the tessellated 3D model; Calculating normal vectors of vertices of the model; Calculating a normal vector gradient of the normal vector; Based on the model vertices, the normal vectors and the normal vector gradients, the curvature of the tessellated 3D model is calculated using the following formula: in, Represents the curvature of the tessellated 3D model, Represents the tessellated 3D model The normal vectors of the model vertices, Represents the tessellated 3D model The normal vector gradient of the normal vector of each model vertex.

[0008] Optionally, determining the high stress area and boundary area of ​​the printed 3D model according to the geometric features includes: Mapping the curvature corresponding to the geometric feature to the model surface of the printed 3D model to obtain a color-coded curvature map; identifying regions of high curvature in the color-coded curvature map; Mapping the thickness corresponding to the geometric feature to the model surface of the printed 3D model to obtain a thickness distribution; Determining a high stress area of ​​the printed 3D model in combination with the high curvature area and the thickness distribution; Based on the corresponding boundary of the geometric feature, a boundary area of ​​the printed 3D model is determined.

[0009] Optionally, constructing a multi-scale network of the printed 3D model according to the high stress area and the boundary area includes: defining regional network nodes of the high stress area and the boundary area; constructing a rough network of network nodes in the area; constructing a mesoscopic network of the high stress region and the boundary region according to the coarse network; determining critical areas of the high stress areas and boundary areas; constructing a microscopic network of the key areas; Establishing a network bridge among the coarse network, the meso network and the micro network; Based on the network bridge, the coarse network, the mesoscopic network and the microscopic network, a multi-scale network of the printed 3D model is constructed.

[0010] Optionally, constructing the microscopic network of the key area includes: defining node distances of the key area; According to the node distance, the total energy of the key area is calculated using the following formula: in, represents the total energy of the critical area, represents the summation function, represents the spring constant, Representation Node and nodes The distance between nodes, Representation Node and nodes The equilibrium distance; defining micro-network constraints of the critical areas; Based on the microscopic network constraints and the total energy, a microscopic network of the key area is constructed.

[0011] Optionally, determining the material transformation gradient of the multi-region printing material includes: Determining the printing function requirements of the multi-region printing material corresponding to the printing of the 3D model; Defining the gradient type of the multi-region printing material according to the printing function requirement; identifying material properties of the multi-region printing material, wherein the material properties include physical properties and chemical properties; The material transformation gradient of the multi-region printing material is analyzed by the gradient type and the material property.

[0012] Optionally, defining a multi-scale boundary reinforcement path of the printing device according to the multi-scale network includes: Analyzing device performance of the printing device; Analyzing the boundary characteristics of the 3D model printed by the printing device according to the multi-scale network; Establishing a boundary model of the printed 3D model in the multi-scale network by using the boundary characteristics; Based on the device performance and the boundary characteristics, a multi-scale boundary reinforcement path of the printing device is established in the boundary model.

[0013] Optionally, the calculating, according to the printing data, an idle distance of the printing device, according to the idle distance, includes: Preprocessing the print data to obtain processed print data; Constructing a visualization path of the printing device according to the printing data; marking a non-working moving segment of the visualization path; Calculating the idle distance of the moving segment of the non-working moving segment in the visualized path; The idle distances of the moving sections are summed to obtain the idle distance of the printing device.

[0014] In order to solve the above problems, the present invention also provides an adaptive object boundary enhancement 3D printing technology system, the system comprising: A model region analysis module, used to obtain a printed 3D model of a target to be printed, analyze geometric features of the printed 3D model, wherein the geometric features include curvature, thickness, and boundary, and determine a high stress region and a boundary region of the printed 3D model according to the geometric features; A multi-scale network construction module, used to construct a multi-scale network of the printed 3D model according to the high stress area and the boundary area, define multi-region printing materials of the printed 3D model based on the multi-scale network, and determine the material transformation gradient of the multi-region printing materials; A reinforcement path construction module, used to construct a sensor network and a printing device of the target to be printed, and define a multi-scale boundary reinforcement path of the printing device according to the multi-scale network; A reinforcement path optimization module, for collecting printing data of the target to be printed by using the sensor network based on the multi-scale boundary reinforcement path, the material transformation gradient, the printing device and the multi-region printing material, calculating the idle distance of the printing device according to the printing data, and optimizing the multi-scale boundary reinforcement path according to the idle distance to obtain an optimized multi-scale path; The object boundary enhancement module is used to analyze the current printing quality of the target to be printed based on the optimized multi-scale boundary enhancement path, define the optimized printing parameters of the target to be printed according to the current printing quality, and perform adaptive object boundary enhancement of the target to be printed based on the optimized printing parameters.

[0015] Compared with the problems described in the background technology, firstly, by comprehensively analyzing the geometric features of the printed 3D model, constructing a multi-scale network, and defining multi-region printing materials and their transformation gradients, the high stress area and boundary area of ​​the target to be printed are accurately identified and strengthened. Then, by constructing an integrated system of the sensor network and the printing device, and defining a multi-scale boundary strengthening path, the efficiency and quality of the 3D printing are significantly improved. The optimization of the multi-scale path reduces the idle distance of the printing device, improves the continuity of the printing process and the material utilization rate. Finally, based on the optimized multi-scale boundary strengthening path, the scheme can analyze the printing quality in real time and adaptively adjust the printing parameters to ensure the mechanical properties and reliability of the printed target. Therefore, the present invention can improve the boundary strengthening effect of the target to be printed. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic diagram of a process flow of an adaptive object boundary enhancement 3D printing technology method provided by an embodiment of the present invention; Figure 2 A schematic diagram of a module for implementing the adaptive object boundary enhancement 3D printing technology method provided by an embodiment of the present invention.

[0017] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0018] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0019] The embodiment of the present application provides an adaptive object boundary reinforcement 3D printing technology method. The execution subject of the adaptive object boundary reinforcement 3D printing technology method includes but is not limited to at least one of the electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided by the embodiment of the present application. In other words, the adaptive object boundary reinforcement 3D printing technology method can be executed by software or hardware installed in a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0020] Embodiment 1: Reference Figure 1 FIG. 1 is a flow chart of an adaptive object boundary enhancement 3D printing technology method provided by an embodiment of the present invention. In this embodiment, the adaptive object boundary enhancement 3D printing technology method includes: S1. Obtain a printed 3D model of a target to be printed, analyze geometric features of the printed 3D model, wherein the geometric features include curvature, thickness, and boundary, and determine high stress areas and boundary areas of the printed 3D model based on the geometric features.

[0021] It should be explained that the target to be printed refers to a specific object or part to be manufactured by 3D printing technology, and the printed 3D model refers to a digital representation of the target to be printed, which is created by 3D modeling software.

[0022] The present invention analyzes the geometric features of the printed 3D model, wherein the geometric features include curvature, thickness and boundaries which can be used as a basis for subsequent regional analysis of the 3D model.

[0023] In detail, the analyzing the geometric features of the printed 3D model includes: Smoothing the printed 3D model to obtain a smoothed 3D model; Performing surface subdivision on the smoothed 3D model to obtain a surface subdivision 3D model; Calculating the curvature of the tessellated 3D model; Analyzing the closure coefficient of the printed 3D model; When the closure coefficient meets a preset closure threshold, the printed 3D model is offset to obtain an offset 3D model; calculating a surface volume between the offset 3D model and the printed 3D model; Based on the surface volume, determining a thickness of the printed 3D model; Marking the boundaries of the printed 3D model; The geometric features of the printed 3D model are determined according to the curvature, the thickness, and the boundary.

[0024] Among them, the smoothed 3D model refers to optimizing the surface of the original 3D model through a mathematical algorithm to reduce surface noise and unnecessary details, thereby obtaining a smoother and continuous model, the tessellated 3D model refers to a model in which the facets of the original 3D model are further subdivided into smaller facets, the curvature refers to a measure describing the degree of curvature of the 3D model surface, the closure coefficient refers to a parameter used to describe the degree of closure of the 3D model, the closure threshold refers to a standard for judging whether the degree of closure of the model is sufficient for the next offset operation, the offset 3D model refers to a model obtained by performing an equidistant offset operation on the surface of the original 3D model, the surface volume refers to the volume difference between the offset 3D model and the original 3D model, the thickness refers to the size of the 3D model in a direction perpendicular to its surface, the boundary refers to the dividing line between different surfaces or regions on the 3D model, and the geometric features include the curvature, thickness and boundary of the printed 3D model.

[0025] Further, the calculating the curvature of the tessellated 3D model includes: Determining model vertices of the tessellated 3D model; Calculating normal vectors of vertices of the model; Calculating a normal vector gradient of the normal vector; Based on the model vertices, the normal vectors and the normal vector gradients, the curvature of the tessellated 3D model is calculated using the following formula: in, Represents the curvature of the tessellated 3D model, Represents the tessellated 3D model The normal vectors of the model vertices, Represents the tessellated 3D model The normal vector gradient of the normal vector of each model vertex.

[0026] The model vertex refers to one of the basic elements that make up the 3D model, that is, a point on the model surface, the normal vector refers to a vector perpendicular to a point on the 3D model surface, and the normal vector gradient refers to the rate of change of the normal vector in space.

[0027] The present invention determines the high stress area and boundary area of ​​the printed 3D model based on the geometric features, which can serve as the data basis for the subsequent adaptive object boundary reinforcement path analysis.

[0028] In detail, determining the high stress area and boundary area of ​​the printed 3D model according to the geometric features includes: Mapping the curvature corresponding to the geometric feature to the model surface of the printed 3D model to obtain a color-coded curvature map; identifying regions of high curvature in the color-coded curvature map; Mapping the thickness corresponding to the geometric feature to the model surface of the printed 3D model to obtain a thickness distribution; Determining a high stress area of ​​the printed 3D model in combination with the high curvature area and the thickness distribution; Based on the corresponding boundary of the geometric feature, a boundary area of ​​the printed 3D model is determined.

[0029] Among them, the color-coded curvature map refers to a visual representation method of encoding the curvature value of the 3D model surface by color, the high curvature area is an area represented by a specific color (usually warm colors, such as red or yellow) in the color-coded curvature map, the thickness distribution refers to the distribution of thickness values ​​at each point on the 3D model surface, the high stress area refers to an area that may be subjected to higher mechanical stress during printing or use, and the boundary area refers to the edge or interface area in the 3D model.

[0030] Optionally, mapping the curvature corresponding to the geometric feature to the model surface of the printed 3D model to obtain a color-coded curvature map can be achieved by writing a script using MATLAB, Python (particularly using matplotlib and numpy libraries) or other programming languages ​​to map the curvature value to a color space.

[0031] S2. Construct a multi-scale network of the printed 3D model according to the high stress area and the boundary area, define multi-region printing materials of the printed 3D model based on the multi-scale network, and determine the material transformation gradient of the multi-region printing materials.

[0032] The present invention constructs a multi-scale network of the printed 3D model based on the high stress areas and boundary areas, which can accurately simulate and optimize the performance of the high stress areas and boundary areas, thereby improving the overall strength and reliability of the printed structure.

[0033] In detail, constructing the multi-scale network of the printed 3D model according to the high stress area and the boundary area includes: defining regional network nodes of the high stress area and the boundary area; constructing a rough network of network nodes in the area; constructing a mesoscopic network of the high stress region and the boundary region according to the coarse network; determining critical areas of the high stress areas and boundary areas; constructing a microscopic network of the key areas; Establishing a network bridge among the coarse network, the meso network and the micro network; Based on the network bridge, the coarse network, the mesoscopic network and the microscopic network, a multi-scale network of the printed 3D model is constructed.

[0034] Among them, the regional network nodes refer to representative points defined in the high stress areas and boundary areas of the 3D model, the coarse network refers to a preliminary network structure, which connects the regional network nodes to form a large-scale network covering the entire model, the mesoscopic network refers to a network further refined on the basis of the coarse network, which describes the local characteristics of the high stress areas and boundary areas in more detail, including more complex connections and interactions, the key areas refer to particularly important areas identified in the mesoscopic network, the microscopic network refers to a more refined network constructed in the key areas, which takes into account the influence of the microstructure of the material, such as grain structure, defects, etc., and is used to simulate and analyze the behavior at the microscale, the network bridge refers to the intermediate layer or interface used to connect the coarse network, the mesoscopic network and the microscopic network, and the multi-scale network refers to a comprehensive network integrating the coarse network, the mesoscopic network and the microscopic network, which can describe and analyze the geometric and physical properties of the 3D model at different scales, thereby providing a more comprehensive understanding and prediction of the behavior of the model.

[0035] Furthermore, the construction of the microscopic network of the key area includes: defining node distances of the key area; According to the node distance, the total energy of the key area is calculated using the following formula: in, represents the total energy of the critical area, represents the summation function, represents the spring constant, Representation Node and nodes The distance between nodes, Representation Node and nodes The equilibrium distance; defining micro-network constraints of the critical areas; Based on the microscopic network constraints and the total energy, a microscopic network of the key area is constructed.

[0036] Among them, the node distance refers to the Euclidean distance between two adjacent nodes in the micro network, the total energy refers to the sum of the energy of the interaction forces between all nodes, the summation function refers to the function used to accumulate the interactions between all pairs of nodes in the network, the spring constant refers to the strength of the interaction between nodes in the network, the equilibrium distance refers to the ideal distance between two nodes in the network when no external force is applied, and the micro network constraint condition refers to a set of conditions that must be met when constructing a micro network, such as restrictions on node positions, network connectivity, and the maximum distance between nodes.

[0037] It should be explained that the multi-region printing material means that during the 3D printing process, a printed object is composed of two or more materials with different properties.

[0038] The present invention determines the material transformation gradient of the multi-region printing material so that the printed boundary enhancement is more detailed.

[0039] In detail, determining the material transformation gradient of the multi-region printing material includes: Determining the printing function requirements of the multi-region printing material corresponding to the printing of the 3D model; Defining the gradient type of the multi-region printing material according to the printing function requirement; identifying material properties of the multi-region printing material, wherein the material properties include physical properties and chemical properties; The material transformation gradient of the multi-region printing material is analyzed by the gradient type and the material property.

[0040] Among them, the printing function requirements refer to the specific performance and functional requirements that the 3D model needs to meet after printing is completed, such as mechanical properties, thermal properties, electrical properties and other properties; the gradient type refers to the change pattern of material properties in the 3D model; the physical property refers to the property exhibited by the material without changing its chemical composition; the chemical property refers to the property exhibited by the material in a chemical reaction, such as reactivity, corrosion resistance and other properties; the material transformation gradient refers to the degree to which the material properties change gradually or suddenly according to a predetermined gradient type in different areas of the 3D model.

[0041] Optionally, the material transformation gradient of the multi-region printed material analyzed by the gradient type and the material property can be simulated and analyzed by material property modeling software (such as COMSOL Multiphysics, ANSYS, etc.).

[0042] S3. Construct a sensor network and a printing device for the target to be printed, and define a multi-scale boundary reinforcement path for the printing device according to the multi-scale network.

[0043] It should be explained that the sensor network refers to a system network composed of a series of sensor nodes, and the printing device refers to a machine used to perform 3D printing tasks.

[0044] The present invention defines a multi-scale boundary reinforcement path of the printing device based on the multi-scale network, which can serve as a basis for subsequent boundary reinforcement.

[0045] In detail, the multi-scale boundary reinforcement path of the printing device is defined according to the multi-scale network, including: Analyzing device performance of the printing device; Analyzing the boundary characteristics of the 3D model printed by the printing device according to the multi-scale network; Establishing a boundary model of the printed 3D model in the multi-scale network by using the boundary characteristics; Based on the device performance and the boundary characteristics, a multi-scale boundary reinforcement path of the printing device is established in the boundary model.

[0046] Among them, the device performance refers to the performance and ability of the printing device when performing its designed functions, the boundary characteristics refer to the specific properties of the printed 3D model in the boundary area, the boundary model refers to a mathematical or computational model established on a multi-scale network for simulating and analyzing the boundary area of ​​the printed 3D model, and the multi-scale boundary enhancement path refers to a set of enhancement paths designed to improve the performance of the printing device in the boundary area.

[0047] Optionally, the boundary model of the printed 3D model established in the multi-scale network through the boundary characteristics can be simulated using FEA software (such as ANSYS, Abaqus, COMSOL Multiphysics, etc.).

[0048] S4. Based on the multi-scale boundary reinforcement path, the material transformation gradient, the printing device and the multi-region printing material, the printing data of the target to be printed is collected by using the sensor network. According to the printing data, the idle driving distance of the printing device is calculated. According to the idle driving distance, the multi-scale boundary reinforcement path is optimized to obtain an optimized multi-scale path.

[0049] It should be explained that the printing data refers to various information related to the target to be printed collected through the sensor network, including structure data, material data, printing process data and other data.

[0050] The present invention calculates the idle distance of the printing device based on the printing data, which can be used as a basis for subsequent path optimization.

[0051] In detail, the calculating the idle distance of the printing device according to the printing data includes: Preprocessing the print data to obtain processed print data; Constructing a visualization path of the printing device according to the printing data; marking a non-working moving segment of the visualization path; Calculating the idle distance of the moving segment of the non-working moving segment in the visualized path; The idle distances of the moving sections are summed to obtain the idle distance of the printing device.

[0052] Among them, the processed printing data refers to the data after a series of cleaning, conversion and formatting operations are performed on the original printing data, the visualization path refers to the graphical representation of the moving path of the printing device, the non-working moving segment refers to the moving segment where the print head does not deposit material, the moving segment idle distance refers to the specific distance the print head moves in the non-working moving segment, and the idle distance refers to the sum of the idle distances of all non-working moving segments of the print head during the entire printing process.

[0053] Optionally, constructing the visualization path of the printing device according to the printing data can be implemented by using 3Dmax software.

[0054] The present invention optimizes the multi-scale boundary reinforcement path according to the idle distance, and obtains an optimized multi-scale path to improve the printing reinforcement efficiency. The optimized multi-scale path refers to the path after the multi-scale boundary reinforcement path is optimized for the idle distance. In detail, the path optimization of the multi-scale boundary reinforcement path can be optimized by an algorithm in graph theory (such as a shortest path algorithm, a minimum spanning tree algorithm, etc.).

[0055] S5. Based on the optimized multi-scale boundary enhancement path, analyze the current printing quality of the target to be printed, define optimized printing parameters of the target to be printed according to the current printing quality, and perform adaptive object boundary enhancement of the target to be printed based on the optimized printing parameters.

[0056] It should be explained that the current printing quality refers to the printing effect and performance indicators achieved by the printing target during the actual printing process, and the optimized printing parameters refer to a series of printing settings adjusted according to the printing target and the characteristics of the printer in order to improve the printing quality, such as printing speed, printing temperature, layer thickness and other parameters.

[0057] Finally, the present invention performs adaptive object boundary enhancement of the target to be printed based on the optimized printing parameters to achieve precise boundary enhancement of the target to be printed.

[0058] Compared with the problems described in the background technology, firstly, by comprehensively analyzing the geometric features of the printed 3D model, constructing a multi-scale network, and defining multi-region printing materials and their transformation gradients, the high stress area and boundary area of ​​the target to be printed are accurately identified and strengthened. Then, by constructing an integrated system of the sensor network and the printing device, and defining a multi-scale boundary strengthening path, the efficiency and quality of the 3D printing are significantly improved. The optimization of the multi-scale path reduces the idle distance of the printing device, improves the continuity of the printing process and the material utilization rate. Finally, based on the optimized multi-scale boundary strengthening path, the scheme can analyze the printing quality in real time and adaptively adjust the printing parameters to ensure the mechanical properties and reliability of the printed target. Therefore, the present invention can improve the boundary strengthening effect of the target to be printed.

[0059] Embodiment 2: like Figure 2 The figure shows a functional module diagram of an adaptive object boundary enhancement 3D printing technology system of the present invention.

[0060] The adaptive object boundary reinforcement 3D printing technology system 200 of the present invention can be installed in an electronic device. According to the functions to be implemented, the adaptive object boundary reinforcement 3D printing technology system can include an application scenario analysis module 201, a multi-scale network construction module 202, a reinforcement path construction module 203, a reinforcement path optimization module 204 and an object boundary reinforcement module 205. The module of the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0061] In the embodiment of the present invention, the functions of each module / unit are as follows: The model region analysis module 201 is used to obtain a printed 3D model of a target to be printed, analyze geometric features of the printed 3D model, wherein the geometric features include curvature, thickness and boundary, and determine a high stress region and a boundary region of the printed 3D model according to the geometric features; The multi-scale network construction module 202 is used to construct a multi-scale network of the printed 3D model according to the high stress area and the boundary area, define multi-region printing materials of the printed 3D model based on the multi-scale network, and determine the material transformation gradient of the multi-region printing materials; The reinforcement path construction module 203 is used to construct the sensor network and printing device of the target to be printed, and define the multi-scale boundary reinforcement path of the printing device according to the multi-scale network; The reinforcement path optimization module 204 is used to collect the printing data of the target to be printed by using the sensor network based on the multi-scale boundary reinforcement path, the material transformation gradient, the printing device and the multi-region printing material, calculate the idle driving distance of the printing device according to the printing data, and optimize the multi-scale boundary reinforcement path according to the idle driving distance to obtain an optimized multi-scale path; The object boundary enhancement module 205 is used to analyze the current printing quality of the target to be printed based on the optimized multi-scale boundary enhancement path, define the optimized printing parameters of the target to be printed according to the current printing quality, and perform adaptive object boundary enhancement of the target to be printed based on the optimized printing parameters.

[0062] In detail, the modules in the adaptive object boundary enhancement 3D printing technology system 200 in the embodiment of the present invention are used in the same manner as described above. Figure 1 The adaptive object boundary enhancement 3D printing technical method described in the invention is the same technical means and can produce the same technical effect, so it will not be repeated here.

[0063] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0064] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for adaptive object boundary enhancement 3D printing technology, characterized in that: The method comprises: Obtaining a printed 3D model of the target to be printed, analyzing geometric features of the printed 3D model, wherein the geometric features include curvature, thickness, and boundary, and determining high stress areas and boundary areas of the printed 3D model according to the geometric features; Constructing a multi-scale network of the printed 3D model according to the high stress area and the boundary area, defining multi-region printing materials of the printed 3D model based on the multi-scale network, and determining a material transformation gradient of the multi-region printing materials; Constructing a sensor network and a printing device of the target to be printed, and defining a multi-scale boundary reinforcement path of the printing device according to the multi-scale network; Based on the multi-scale boundary reinforcement path, the material transformation gradient, the printing device and the multi-region printing material, the printing data of the target to be printed is collected by using the sensor network, the idle driving distance of the printing device is calculated according to the printing data, and the multi-scale boundary reinforcement path is optimized according to the idle driving distance to obtain an optimized multi-scale path; Based on the optimized multi-scale boundary enhancement path, the current printing quality of the target to be printed is analyzed, and according to the current printing quality, the optimized printing parameters of the target to be printed are defined, and the adaptive object boundary enhancement of the target to be printed is performed based on the optimized printing parameters.

2. The adaptive object boundary enhancement 3D printing technology method according to claim 1, characterized in that: The analyzing the geometric features of the printed 3D model includes: Smoothing the printed 3D model to obtain a smoothed 3D model; Performing surface subdivision on the smoothed 3D model to obtain a surface subdivision 3D model; Calculating the curvature of the tessellated 3D model; Analyzing the closure coefficient of the printed 3D model; When the closure coefficient meets a preset closure threshold, the printed 3D model is offset to obtain an offset 3D model; calculating a surface volume between the offset 3D model and the printed 3D model; Based on the surface volume, determining a thickness of the printed 3D model; Marking the boundaries of the printed 3D model; The geometric features of the printed 3D model are determined according to the curvature, the thickness, and the boundary.

3. The adaptive object boundary enhancement 3D printing technology method according to claim 2, characterized in that: The calculating the curvature of the tessellated 3D model comprises: Determining model vertices of the tessellated 3D model; Calculating normal vectors of vertices of the model; Calculating a normal vector gradient of the normal vector; Based on the model vertices, the normal vectors and the normal vector gradients, the curvature of the tessellated 3D model is calculated using the following formula: in, Represents the curvature of the tessellated 3D model, Represents the tessellated 3D model The normal vectors of the model vertices, Represents the tessellated 3D model The normal vector gradient of the normal vector of each model vertex.

4. The adaptive object boundary enhancement 3D printing technology method according to claim 3, characterized in that: Determining the high stress area and boundary area of ​​the printed 3D model according to the geometric features includes: Mapping the curvature corresponding to the geometric feature to the model surface of the printed 3D model to obtain a color-coded curvature map; identifying regions of high curvature in the color-coded curvature map; Mapping the thickness corresponding to the geometric feature to the model surface of the printed 3D model to obtain a thickness distribution; Determining a high stress area of ​​the printed 3D model in combination with the high curvature area and the thickness distribution; Based on the corresponding boundary of the geometric feature, a boundary area of ​​the printed 3D model is determined.

5. The adaptive object boundary enhancement 3D printing technology method according to claim 4, characterized in that: The step of constructing a multi-scale network of the printed 3D model according to the high stress area and the boundary area comprises: defining regional network nodes of the high stress area and the boundary area; constructing a rough network of network nodes in the area; constructing a mesoscopic network of the high stress region and the boundary region according to the coarse network; determining critical areas of the high stress areas and boundary areas; constructing a microscopic network of the key areas; Establishing a network bridge among the coarse network, the meso network and the micro network; Based on the network bridge, the coarse network, the mesoscopic network and the microscopic network, a multi-scale network of the printed 3D model is constructed.

6. The adaptive object boundary enhancement 3D printing technology method according to claim 5, characterized in that: The step of constructing the microscopic network of the key area comprises: defining node distances of the key area; According to the node distance, the total energy of the key area is calculated using the following formula: in, represents the total energy of the critical area, represents the summation function, represents the spring constant, Representation Node and nodes The distance between nodes, Representation Node and nodes The equilibrium distance; defining micro-network constraints of the critical areas; Based on the microscopic network constraints and the total energy, a microscopic network of the key area is constructed.

7. The adaptive object boundary enhancement 3D printing technology method according to claim 6, characterized in that: Determining the material transformation gradient of the multi-region printing material includes: Determining the printing function requirements of the multi-region printing material corresponding to the printing of the 3D model; Defining the gradient type of the multi-region printing material according to the printing function requirement; identifying material properties of the multi-region printing material, wherein the material properties include physical properties and chemical properties; The material transformation gradient of the multi-region printing material is analyzed by the gradient type and the material property.

8. The adaptive object boundary enhancement 3D printing technology method according to claim 7, characterized in that: Defining a multi-scale boundary reinforcement path of the printing device according to the multi-scale network includes: Analyzing device performance of the printing device; Analyzing the boundary characteristics of the 3D model printed by the printing device according to the multi-scale network; Establishing a boundary model of the printed 3D model in the multi-scale network by using the boundary characteristics; Based on the device performance and the boundary characteristics, a multi-scale boundary reinforcement path of the printing device is established in the boundary model.

9. The adaptive object boundary enhancement 3D printing technology method according to claim 8, characterized in that: The step of calculating the idle distance of the printing device according to the printing data includes: Preprocessing the print data to obtain processed print data; Constructing a visualization path of the printing device according to the printing data; marking a non-working moving segment of the visualization path; Calculating the idle distance of the moving segment of the non-working moving segment in the visualized path; The idle distances of the moving sections are summed to obtain the idle distance of the printing device.

10. An adaptive object boundary enhancement 3D printing technology system, characterized in that: The system comprises: A model region analysis module, used to obtain a printed 3D model of a target to be printed, analyze geometric features of the printed 3D model, wherein the geometric features include curvature, thickness, and boundary, and determine a high stress region and a boundary region of the printed 3D model according to the geometric features; A multi-scale network construction module, used to construct a multi-scale network of the printed 3D model according to the high stress area and the boundary area, define multi-region printing materials of the printed 3D model based on the multi-scale network, and determine the material transformation gradient of the multi-region printing materials; A reinforcement path construction module, used to construct a sensor network and a printing device of the target to be printed, and define a multi-scale boundary reinforcement path of the printing device according to the multi-scale network; A reinforcement path optimization module, for collecting printing data of the target to be printed by using the sensor network based on the multi-scale boundary reinforcement path, the material transformation gradient, the printing device and the multi-region printing material, calculating the idle distance of the printing device according to the printing data, and optimizing the multi-scale boundary reinforcement path according to the idle distance to obtain an optimized multi-scale path; The object boundary enhancement module is used to analyze the current printing quality of the target to be printed based on the optimized multi-scale boundary enhancement path, define the optimized printing parameters of the target to be printed according to the current printing quality, and perform adaptive object boundary enhancement of the target to be printed based on the optimized printing parameters.

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