A 3D printing intelligent control method and 3D printer

Abstract

This invention discloses a 3D printing intelligent control method and a 3D printer, relating to the field of 3D printing technology. The method includes: acquiring a 3D printing model and dividing it into detailed and basic regions; performing detailed printing nozzle blockage analysis based on detailed extrusion and cooling parameters, and optimizing the detailed cooling parameters based on the analysis results to obtain optimal detailed cooling parameters for 3D printing control of the detailed regions; similarly, optimizing the basic extrusion and cooling parameters to obtain optimal basic extrusion and cooling parameters for 3D printing control of the basic regions. This invention solves the technical problems in existing technologies where low precision in printing parameter control leads to nozzle blockage, printing warping, and loss of detail, affecting print quality. It achieves the technical effect of reducing nozzle blockage, minimizing printing warping, and improving print quality and efficiency by optimizing printing parameters in a region-specific manner.

Description

Technical Field

[0001] This invention relates to the field of 3D printing technology, specifically to a 3D printing intelligent control method and a 3D printer. Background Technology

[0002] 3D printing, also known as additive manufacturing, is the process of building objects layer by layer using digital model files. Its core principle is rapid exfoliation, combining multiple two-dimensional models into a three-dimensional object through repeated operations. Compared to traditional manufacturing methods, 3D printing offers advantages such as a direct and rapid process, as well as modularity, making production batches and varieties more flexible.

[0003] However, current 3D printing technology generally suffers from low precision in controlling printing parameters. For example, excessive or insufficient extrusion volume, as well as rapid cooling, can cause problems such as nozzle blockage, print warping, loss of detail, and poor adhesion. Summary of the Invention

[0004] This application provides a 3D printing intelligent control method and a 3D printer to solve the technical problems in the prior art that affect printing quality, such as nozzle blockage, printing warping, and loss of details, due to low control precision of printing parameters.

[0005] The first aspect of this application provides a 3D printing intelligent control method, the method comprising: an interactive 3D printing design system, acquiring a 3D printing model for 3D printing, and generating printing control parameters based on the 3D printing model, wherein the 3D printing model includes model specification parameters; dividing and identifying the 3D printing model into detailed regions and basic regions based on the model specification parameters and printing control parameters, and extracting detailed specification parameters and detailed printing control parameters of the detailed regions, as well as basic printing control parameters of the basic regions; performing detailed printing nozzle blockage analysis based on detailed extrusion parameters and detailed cooling parameters within the detailed printing control parameters, obtaining detailed nozzle blockage parameters, and deciding on a detailed optimization amplitude for optimizing the detailed cooling parameters; and, according to the detailed optimization amplitude, using... With the optimization goals of reducing nozzle clogging and print warpage, and improving print detail retention and adhesion strength, the detail cooling parameters are optimized to obtain optimal detail cooling parameters. The detail printing control parameters are then updated to control 3D printing in the detail area. Based on the basic extrusion and cooling parameters within the basic printing control parameters, a basic nozzle clogging analysis is performed to obtain basic nozzle clogging parameters, and a basic optimization amplitude is determined for optimizing the basic extrusion and cooling parameters. Following this basic optimization amplitude, with the optimization goals of reducing nozzle clogging and print warpage and improving print cooling adhesion strength, the basic extrusion and cooling parameters are optimized to obtain optimal basic extrusion and cooling parameters. The basic printing control parameters are then used to control 3D printing in the basic area.

[0006] A second aspect of this application provides a 3D printer for implementing a 3D printing intelligent control method as described in the first aspect of this application.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0008] This application provides a 3D printing intelligent control method, relating to the field of 3D printing technology. It involves dividing and identifying the 3D printing model into detailed and basic regions, and then performing detailed printing nozzle blockage analysis and optimizing the detailed cooling parameters based on detailed extrusion and cooling parameters. This yields optimal detailed cooling parameters for 3D printing control of the detailed regions. Similarly, after optimizing the basic extrusion and cooling parameters, 3D printing control of the basic regions is achieved. This solves the technical problems in existing technologies where low precision in printing parameter control leads to nozzle blockage, printing warping, and detail loss, affecting printing quality. It achieves the technical effect of reducing nozzle blockage, minimizing printing warping, and improving printing quality and efficiency by optimizing printing parameters in specific regions. Attached Figure Description

[0009] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 This is a schematic diagram of a 3D printing intelligent control method provided in an embodiment of this application;

[0011] Figure 2 A schematic diagram illustrating the process of obtaining detailed nozzle clogging parameters in a 3D printing intelligent control method provided in this application embodiment;

[0012] Figure 3 This is a schematic diagram illustrating the process of obtaining optimal detail cooling parameters in a 3D printing intelligent control method provided in an embodiment of this application. Detailed Implementation

[0013] This application provides a 3D printing intelligent control method to solve the technical problems in the prior art, such as nozzle blockage, printing warping, and loss of details, which affect the printing quality due to the low control precision of printing parameters.

[0014] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0015] It should be noted that the terms "first," "second," etc., used in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to such processes, methods, products, or devices.

[0016] Example 1

[0017] like Figure 1 As shown, this application provides a 3D printing intelligent control method, the method comprising:

[0018] P10: An interactive 3D printing design system acquires a 3D printing model for 3D printing and generates printing control parameters based on the 3D printing model, wherein the 3D printing model includes model specification parameters.

[0019] Optionally, the system interacts with a 3D printing design system to access 3D model data stored within the system and obtain a user-selected or specified 3D printing model. This 3D printing model is a three-dimensional digital file describing the shape, size, and other relevant features of the object to be printed. Furthermore, the 3D printing model includes model specification parameters, such as the overall dimensions (length, width, height), the dimensions, volume, and weight of each part. Further, the 3D printing model is analyzed, and printing control parameters are generated based on the model specification parameters. These printing control parameters are key data guiding the 3D printer to print according to the model, including but not limited to layer height, extrusion speed, printing temperature, and printing speed, serving as the basis for subsequent printing parameter optimization.

[0020] P20: Based on the model specification parameters and printing control parameters, the 3D printed model is divided into detailed areas and basic areas, and the detailed specification parameters and detailed printing control parameters of the detailed areas, as well as the basic printing control parameters of the basic areas, are extracted and obtained.

[0021] Furthermore, step P20 in this embodiment of the application also includes:

[0022] P21: Based on the model specification parameters, extract the regions within the 3D printed model whose geometric specification parameters are less than or equal to the detail specification threshold, and divide and mark them to obtain the detail regions;

[0023] P22: Based on the model specification parameters, extract the regions within the 3D printed model whose geometric specification parameters are greater than or equal to the basic specification threshold, and delineate and mark them to obtain the basic region;

[0024] P23: Extract the detail specifications and detail printing control parameters of the detail area from the model specification parameters and printing control parameters.

[0025] P24: Extract the basic printing control parameters of the basic area from the model specification parameters and printing control parameters.

[0026] It should be understood that, based on the model specifications and printing control parameters, the 3D printed model is divided into a detail area and a basic area. The detail area refers to the small, complex parts of the model that require precise printing. The basic area, on the other hand, consists of larger, less complex parts, such as the product's base. The specifications and printing control parameters for both the detail and basic areas are extracted, including the detailed specifications and printing control parameters for the detail area, and the basic printing control parameters for the basic area.

[0027] Specifically, firstly, based on the model specification parameters, regions within the 3D printed model whose geometric specifications are less than or equal to a detail specification threshold are extracted as detail regions. The detail specification threshold can be set according to specific application requirements and model characteristics to distinguish areas requiring fine printing. Simultaneously, based on the model specification parameters, regions whose geometric specifications are greater than a base specification threshold are extracted as base regions. The base specification threshold is also set according to specific needs to distinguish areas that do not require excessively fine printing.

[0028] Furthermore, from the model specification parameters and printing control parameters, specification parameters related to the detail areas, such as size and shape, are extracted as detail specification parameters, and printing control parameters related to the detail areas, such as extrusion parameters and cooling parameters, are extracted as detail printing control parameters to guide the precise printing of the detail areas. Similarly, printing control parameters related to the base area are extracted as base printing control parameters for the base area.

[0029] In summary, the methods of region segmentation and parameter extraction help improve the accuracy and efficiency of 3D printing. By using different printing control parameters for different regions, it is possible to ensure accurate printing of detailed areas, while increasing printing speed in basic areas while maintaining quality, thus providing basic data for optimizing subsequent printing processes.

[0030] P30: Based on the detail extrusion parameters and detail cooling parameters in the detail printing control parameters, perform detail printing nozzle blockage analysis, obtain detail nozzle blockage parameters, and decide on the detail optimization amplitude to optimize the detail cooling parameters.

[0031] Furthermore, such as Figure 2 As shown, step P30 in this embodiment further includes:

[0032] P31: Obtain the detail extrusion parameters and detail cooling parameters from the detail printing control parameters;

[0033] P32: Based on historical data of detailed 3D printing, collect sample detail extrusion parameter set and sample detail cooling parameter set, and obtain the printing nozzle blockage parameter caused by excessively fast extrusion cooling under different detail extrusion parameters and different detail cooling parameters, and obtain sample detail nozzle blockage parameter set;

[0034] P33: Train the detail nozzle blockage analyzer using the aforementioned set of sample detail extrusion parameters, set of sample detail cooling parameters, and set of sample detail nozzle blockage parameters;

[0035] P34: Using the aforementioned detail nozzle blockage analyzer, detail printing nozzle blockage analysis is performed on the detail extrusion parameters and detail cooling parameters to obtain detail nozzle blockage parameters.

[0036] Optionally, detailed areas require precise printing using a base parameter with a smaller extrusion volume. When the extrusion volume is small, rapid cooling may cause the nozzle to become blocked immediately after extrusion. Therefore, based on the detailed extrusion parameters and detailed cooling parameters in the detailed printing control parameters, the nozzle blockage that may occur during the printing process is analyzed to obtain detailed nozzle blockage parameters, such as the degree of blockage. Based on these parameters, the magnitude of the optimization of the detailed cooling parameters is determined. The larger the blockage parameter, the larger the corresponding detail optimization magnitude.

[0037] Specifically, firstly, detail extrusion parameters and detail cooling parameters are extracted from the detail printing control parameters as input data for analyzing nozzle clogging. Further, based on historical 3D printing data, particularly for detail printing, sample detail extrusion parameter sets and sample detail cooling parameter sets are collected. Simultaneously, parameters related to nozzle clogging caused by excessively rapid extrusion and cooling under different combinations of detail extrusion and cooling parameters are obtained, forming a sample detail nozzle clogging parameter set.

[0038] Furthermore, using the aforementioned set of sample detail extrusion parameters, sample detail cooling parameters, and sample detail nozzle clogging parameters, and combining them with a machine learning algorithm for supervised training, a detail nozzle clogging analyzer is obtained. This analyzer can predict the risk of nozzle clogging during printing based on given detail extrusion and cooling parameters. Using this analyzer, the risk of detail printing nozzle clogging is predicted based on the current detail extrusion and cooling parameters, obtaining predicted parameters for possible nozzle clogging under the current parameter combination, i.e., detail nozzle clogging parameters, which serve as an optimization reference for printing control parameters.

[0039] Furthermore, step P30 in this embodiment of the application also includes:

[0040] P35: Based on historical data of nozzle clogging in print details, collect a set of sample detail nozzle clogging parameters, and based on the magnitude data of adjustments to detail cooling parameters, collect a set of sample detail optimization magnitudes.

[0041] P36: Using the sample detail nozzle clogging parameter set and the sample detail optimization amplitude set, a detail optimization decision maker is constructed based on a decision tree;

[0042] P37: Using the aforementioned detail optimization decision-maker, the detail nozzle clogging parameters are classified and decided to obtain the detail optimization amplitude.

[0043] Specifically, based on historical data of nozzle clogging during detail printing, a sample set of detail nozzle clogging parameters is collected, and simultaneously, the magnitude data of adjustments to detail cooling parameters during these clogging events are obtained, forming a sample set of detail optimization magnitudes. Further, the sample set of detail nozzle clogging parameters and the sample set of detail optimization magnitudes are used as training data, and training is performed using the decision tree principle. The decision tree algorithm is a commonly used supervised learning algorithm that can construct a tree-structured model, i.e., a detail optimization decision-maker, by learning the features of the sample data (here, nozzle clogging parameters) and the corresponding target values ​​(here, optimization magnitudes). This model is used to classify and decide on new nozzle clogging parameters and output the corresponding optimization magnitudes.

[0044] Furthermore, the detail optimization decision-maker is used to classify and decide on the detail nozzle clogging parameters. Based on the input nozzle clogging parameters, the decision-maker searches and matches within a tree structure, ultimately outputting one or more detail optimization amplitudes. These amplitudes indicate how to adjust the detail cooling parameters to reduce the risk of nozzle clogging. By using the detail optimization decision-maker, a more intelligent and efficient nozzle clogging optimization process can be achieved, improving printing continuity and stability, and reducing downtime and print failure risks caused by nozzle clogging.

[0045] P40: Based on the aforementioned detailed optimization amplitude, with the optimization direction of reducing nozzle clogging and printing warping, and improving the detail retention and adhesion strength of the print, the detailed cooling parameters are optimized to obtain the optimal detailed cooling parameters. The detailed printing control parameters are then updated to control the 3D printing of the detailed area.

[0046] Furthermore, such as Figure 3 As shown, step P40 in this embodiment further includes:

[0047] P41: Obtain the detailed cooling parameter space for the detailed region;

[0048] P42: With the optimization goals of reducing nozzle clogging and print warping, and improving print detail retention and adhesion strength, a detail cooling function is constructed as follows:

[0049]

[0050] Where DCF represents the fitness of detail, w1, w2, w3, and w4 are weights, and Z is the weight of the value. xb To update the nozzle clogging parameters of the details obtained by analyzing the optimized details cooling parameters combined with the details extrusion parameters, Z xa For detailed nozzle clogging parameters, Q x To analyze and obtain the detail printing warpage of the detail area based on the optimized detail cooling parameters combined with the detail extrusion parameters, D represents the detail retention of the detail area printed based on the optimized detail cooling parameters combined with the detail extrusion parameters. X To analyze and obtain the bonding strength of the printed detail area based on the optimized detail cooling parameters and detail extrusion parameters, F y Preset bonding strength;

[0051] P43: Within the detailed cooling parameter space, the detailed cooling parameters are adjusted according to the detailed optimization amplitude to generate the first detailed cooling parameters;

[0052] P44: Using the aforementioned detail cooling function, combined with the detail extrusion parameters and detail specification parameters, analyze and calculate the first detail fit of the first detail cooling parameter;

[0053] P45: Continue optimizing the detail cooling parameters within the detail cooling parameter space until convergence, and output the detail cooling parameters with the highest detail fitness to obtain the optimal detail cooling parameters.

[0054] It should be understood that excessively rapid cooling of the extruded printing material can lead to nozzle blockage and print layer warping, while excessively slow cooling can cause the extruded material to deform and fail to solidify, resulting in loss of detail and reduced bond strength, thus affecting the accuracy and strength of the printed product. Based on the optimization amplitude for detail, the optimization direction is to reduce nozzle blockage and print warping, and improve the retention of print detail and bond strength. The cooling parameters for detail areas are then optimized. After optimization, the detail printing control parameters are updated to control the 3D printing of detailed areas.

[0055] Specifically, firstly, the range of detail cooling parameters that might be used when cooling detailed areas is determined, i.e., the detail cooling parameter space. Furthermore, to quantify the impact of different combinations of cooling parameters on print quality, and with the optimization direction of reducing nozzle clogging and print warping, and improving print detail retention and adhesion strength, a detail cooling function is constructed:

[0056] Where DCF represents the fitness of detail, w1, w2, w3, and w4 are weights, and Z is the weight of the value. xb To update the nozzle clogging parameters of the details obtained by analyzing the optimized details cooling parameters combined with the details extrusion parameters, Z xa For detailed nozzle clogging parameters, Q x To analyze and obtain the detail printing warpage of the detail area based on the optimized detail cooling parameters combined with the detail extrusion parameters, D represents the detail retention of the detail area printed based on the optimized detail cooling parameters combined with the detail extrusion parameters. X To analyze and obtain the bonding strength of the printed detail area based on the optimized detail cooling parameters and detail extrusion parameters, F y This is the preset bonding strength.

[0057] Furthermore, within the detail cooling parameter space, the detail cooling parameters are adjusted according to the detail optimization amplitude to generate a first set of trial detail cooling parameters, namely the first detail cooling parameters. Then, the detail extrusion parameters, detail specification parameters, and the first detail cooling parameters are substituted into the detail cooling function for calculation to obtain the first detail fitness of the first detail cooling parameters. The first detail fitness reflects the expected print quality under the first detail parameters. Similarly, referring to the above method, iterative optimization of the detail cooling parameters is performed within the detail cooling parameter space until the detail fitness reaches its maximum value or the optimization process converges. The output detail cooling parameters at this point are the optimal detail cooling parameters. The optimal detail cooling parameters can improve print detail retention and adhesion strength while reducing nozzle clogging and print warping. This not only improves printing efficiency but also enhances the quality and reliability of printed products.

[0058] Furthermore, step P44 in this embodiment of the application also includes:

[0059] P44-1: Based on the detailed extrusion parameters and the first detailed cooling parameters, the first updated detailed nozzle blockage parameters are obtained through analysis;

[0060] P44-2: Based on the historical 3D printing data of the detailed area, collect the sample detail extrusion parameter set and the sample detail specification parameter set as analysis input, collect the sample detail printing warpage set, the sample detail retention set and the sample bonding strength set as analysis output, and construct the detail printing warpage analysis branch, the detail retention analysis branch and the bonding strength analysis branch.

[0061] P44-3: Using the aforementioned detail printing warpage analysis branch, detail retention analysis branch, and adhesive strength analysis branch, detail printing analysis is performed on the detail extrusion parameters, detail specification parameters, and first detail cooling parameters to obtain the first detail printing warpage, first detail retention, and first adhesive strength. Based on the aforementioned detail cooling function, the first detail fit is calculated.

[0062] Optionally, using the aforementioned detail nozzle clogging analyzer, a first updated detail nozzle clogging parameter is obtained based on the detail extrusion parameters and the first detail cooling parameter. This parameter reflects the expected nozzle clogging situation under the current parameter combination. Further, sample detail extrusion parameter sets and sample detail specification parameter sets are collected from historical 3D printing data of the detail region as analysis inputs. Simultaneously, output parameters corresponding to these input parameters are collected, namely, sample detail printing warpage sets, sample detail retention sets, and sample bond strength sets. These sample data are used to train or construct three analysis branches: a detail printing warpage analysis branch, a detail retention analysis branch, and a bond strength analysis branch. These branches can predict the corresponding print quality parameters based on the input detail parameters.

[0063] Furthermore, using the aforementioned detail printing warpage analysis branch, detail retention analysis branch, and bond strength analysis branch, detail printing analysis is performed on the detail extrusion parameters, detail specification parameters, and first detail cooling parameters. Each analysis branch outputs a predicted value: first detail printing warpage, first detail retention, and first bond strength. Using these predicted values ​​and the aforementioned detail cooling function, a first detail fitness is calculated. The first detail fitness reflects the expected printing quality under the current parameter combination and can serve as a reference for optimizing printing parameters.

[0064] P50: Based on the basic extrusion parameters and basic cooling parameters within the basic printing control parameters, perform basic printing nozzle blockage analysis, obtain basic nozzle blockage parameters, and decide on the basic optimization amplitude for optimizing the basic extrusion parameters and basic cooling parameters.

[0065] In one possible embodiment of this application, the base extrusion parameters and base cooling parameters are optimized in accordance with the process described above for optimizing detailed cooling parameters. First, based on historical data from basic 3D printing, a set of sample base extrusion parameters and a set of sample base cooling parameters are collected. Then, the nozzle clogging parameters caused by excessively rapid extrusion cooling under different base extrusion and cooling parameters are obtained, resulting in a set of sample base nozzle clogging parameters. These sets are then used as training data to train a base nozzle clogging analyzer. Finally, the base nozzle clogging analyzer is used to perform clogging analysis on the current base extrusion and cooling parameters to obtain the base nozzle clogging parameters.

[0066] Furthermore, a basic optimization decision-maker is trained to classify and make decisions on the basic nozzle blockage parameters, thereby obtaining basic optimization amplitudes, which can be used as optimization references for basic extrusion parameters and basic cooling parameters.

[0067] P60: Based on the aforementioned basic optimization amplitude, with the optimization direction of reducing nozzle blockage and printing warping and improving the bonding strength of printing cooling, the basic extrusion parameters and basic cooling parameters are optimized to obtain the optimal basic extrusion parameters and optimal basic cooling parameters. The basic printing control parameters are then used to control the 3D printing of the basic area.

[0068] Furthermore, step P60 in this embodiment of the application also includes:

[0069] P61: Obtain the basic extrusion parameter space and basic cooling parameter space for printing the basic area;

[0070] P62: With the optimization direction of reducing nozzle clogging and print warping, and improving the adhesion strength of print cooling, a basic optimization function is constructed as follows:

[0071]

[0072] Wherein, POF is the basic fitness, w5, w6, and w7 are weights, and Z is the weight. cb To update the base nozzle clogging parameters obtained from the analysis of the optimized base extrusion parameters and base cooling parameters, Z ca Based on the nozzle clogging parameter, Q c To analyze and obtain the detailed printing warpage of the base area based on the optimized base extrusion parameters and base cooling parameters, F c To analyze and obtain the bond strength of the printed base area based on the optimized base extrusion parameters and base cooling parameters, F y Preset bonding strength;

[0073] P63: Based on the basic optimization function and the basic optimization amplitude, optimize the basic extrusion parameters and the basic cooling parameters within the basic cooling parameter space to obtain the optimal basic extrusion parameters and the optimal basic cooling parameters.

[0074] Optionally, the large extrusion volume in the base area can lead to rapid cooling and material accumulation and blockage in the nozzles. Therefore, the base nozzle blockage parameters are analyzed to reduce nozzle blockage and print warping, with the optimization goal of improving the adhesion strength during print cooling. Both base extrusion and base cooling parameters are optimized. However, since the base area does not have print details, the optimization does not aim to improve detail retention.

[0075] Specifically, the basic extrusion parameter space and basic cooling parameter space for printing the basic area are first obtained. The basic extrusion parameter space contains all possible combinations of basic extrusion parameters, which are used to control the material extrusion amount, speed, etc. of the basic area. The basic cooling parameter space contains all possible combinations of basic cooling parameters, which are used to control the cooling speed, method, etc. of the basic area.

[0076] Furthermore, to quantify the impact of different parameter combinations on print quality and find the optimal parameter combination to reduce nozzle clogging and print warping, and to improve the adhesion strength during print cooling, a basic optimization function is constructed:

[0077] Among them, POF is the basic fitness score, which reflects the quality of printing; w5, w6, and w7 are weights; and Z is the weighted average. cb To update the base nozzle clogging parameters obtained from the analysis of the optimized base extrusion parameters and base cooling parameters, Z ca Based on the nozzle clogging parameter, Q c To analyze and obtain the detailed printing warpage of the base area based on the optimized base extrusion parameters and base cooling parameters, F c To analyze and obtain the bond strength of the printed base area based on the optimized base extrusion parameters and base cooling parameters, F y This is the preset bonding strength.

[0078] Furthermore, referring to the above-described process of optimizing the detailed cooling parameters, within the basic cooling parameter space, multiple sets of basic extrusion parameters and multiple sets of basic cooling parameters are generated according to the basic optimization amplitude. Multiple basic fitness values ​​are then calculated using the basic optimization function, and the basic extrusion parameters and basic cooling parameters with the highest fitness values ​​are extracted as the optimal basic extrusion parameters and optimal basic cooling parameters. These optimal basic extrusion parameters and optimal basic cooling parameters can minimize nozzle clogging in the basic printing area, reduce print warpage, and improve the adhesion strength of the printed cooling. This, in turn, improves printing efficiency and the quality and reliability of the printed products.

[0079] In summary, the embodiments of this application have at least the following technical effects:

[0080] This application divides and identifies the detailed area and the basic area of ​​the 3D printed model, and performs detailed printing nozzle blockage analysis and optimizes the detailed cooling parameters based on the detailed extrusion parameters and detailed cooling parameters to obtain the optimal detailed cooling parameters for 3D printing control of the detailed area. Similarly, after optimizing the basic extrusion parameters and basic cooling parameters, the 3D printing control of the basic area is performed.

[0081] This technology achieves the desired effect of reducing nozzle clogging, minimizing print warping, and improving print quality and efficiency by optimizing print parameters in specific regions.

[0082] Example 2

[0083] Based on the same inventive concept as the 3D printing intelligent control method in the foregoing embodiments, this application provides a 3D printer.

[0084] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0085] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0086] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application intends to include such modifications and variations.

Claims

1. A 3D printing intelligent control method, characterized in that, The method includes: An interactive 3D printing design system acquires a 3D printing model for 3D printing and generates printing control parameters based on the 3D printing model, wherein the 3D printing model includes model specification parameters; Based on the model specification parameters and printing control parameters, the 3D printed model is divided and identified into detailed and basic regions, and detailed specification parameters and detailed printing control parameters of the detailed regions, as well as basic printing control parameters of the basic regions, are extracted. The process of dividing and identifying detailed and basic regions within the 3D printed model based on the model specification parameters and printing control parameters, and extracting detailed specification parameters and detailed printing control parameters of the detailed regions, as well as basic printing control parameters of the basic regions, includes: extracting regions within the 3D printed model whose geometric specification parameters are less than or equal to a detailed specification threshold, and identifying and identifying them to obtain detailed regions; extracting regions within the 3D printed model whose geometric specification parameters are greater than or equal to a basic specification threshold, and identifying them to obtain basic regions; extracting detailed specification parameters and detailed printing control parameters of the detailed regions within the model specification parameters and printing control parameters; and extracting basic printing control parameters of the basic regions within the model specification parameters and printing control parameters. Based on the detail extrusion parameters and detail cooling parameters in the detail printing control parameters, a detail printing nozzle blockage analysis is performed to obtain the detail nozzle blockage parameters, and a decision is made to obtain the detail optimization amplitude for optimizing the detail cooling parameters. Based on the aforementioned detailed optimization amplitude, with the optimization direction of reducing nozzle clogging and printing warping, and improving the detail retention and adhesion strength of the print, the detail cooling parameters are optimized to obtain the optimal detail cooling parameters, and the detail printing control parameters are updated to control the 3D printing of the detail area. Based on the basic extrusion parameters and basic cooling parameters within the basic printing control parameters, a basic printing nozzle blockage analysis is performed to obtain the basic nozzle blockage parameters, and a decision is made to obtain the basic optimization amplitude for optimizing the basic extrusion parameters and basic cooling parameters. Based on the aforementioned basic optimization amplitude, with the optimization direction of reducing nozzle blockage and printing warping and improving the bonding strength of printing cooling, the basic extrusion parameters and basic cooling parameters are optimized to obtain the optimal basic extrusion parameters and optimal basic cooling parameters. The basic printing control parameters are then used to control the 3D printing of the basic area.

2. The 3D printing intelligent control method according to claim 1, characterized in that, Based on the detail extrusion parameters and detail cooling parameters within the detail printing control parameters, a detail printing nozzle blockage analysis is performed to obtain the detail nozzle blockage parameters, including: Obtain the detail extrusion parameters and detail cooling parameters from the detail printing control parameters; Based on historical data of detailed 3D printing, we collected a set of sample detail extrusion parameters and a set of sample detail cooling parameters, and obtained the printing nozzle blockage parameters caused by excessively rapid extrusion and cooling under different detail extrusion parameters and different detail cooling parameters, thus obtaining a set of sample detail nozzle blockage parameters. The detailed nozzle blockage analyzer is trained using the aforementioned set of sample detail extrusion parameters, sample detail cooling parameters, and sample detail nozzle blockage parameters. The detailed nozzle blockage analyzer is used to perform detailed printing nozzle blockage analysis on the detailed extrusion parameters and detailed cooling parameters to obtain detailed nozzle blockage parameters.

3. The 3D printing intelligent control method according to claim 1, characterized in that, The decision-making process obtains detailed optimization magnitudes for optimizing detailed cooling parameters, including: Based on historical data of nozzle clogging, a set of sample nozzle clogging parameters was collected, and based on the magnitude data of adjustments to detail cooling parameters, a set of sample detail optimization magnitudes was collected. Using the sample detail nozzle clogging parameter set and the sample detail optimization amplitude set, a detail optimization decision maker is constructed based on a decision tree; The detailed optimization decision-maker is used to classify and decide on the detailed nozzle clogging parameters to obtain the detailed optimization amplitude.

4. The 3D printing intelligent control method according to claim 1, characterized in that, Based on the aforementioned detailed optimization amplitude, with the optimization direction being to reduce nozzle clogging and print warping, and to improve print detail retention and adhesion strength, the detail cooling parameters are optimized to obtain the optimal detail cooling parameters, including: Obtain detailed cooling parameter space for the detailed region; With the optimization goals of reducing nozzle clogging and print warping, and improving print detail retention and adhesion strength, a detail cooling function is constructed as follows: ； DCF stands for detail fitness. , , and As weight, To update the nozzle clogging parameters obtained by analyzing the optimized detailed cooling parameters in conjunction with the detailed extrusion parameters, For detailed nozzle clogging parameters, To analyze and obtain the detail warpage of the printed detail area based on the optimized detail cooling parameters and detail extrusion parameters, D represents the detail retention of the printed detail area based on the optimized detail cooling parameters and detail extrusion parameters. To analyze and obtain the bonding strength of the printed detail area based on the optimized detail cooling parameters and detail extrusion parameters, Preset bonding strength; Within the detailed cooling parameter space, the detailed cooling parameters are adjusted according to the detailed optimization amplitude to generate the first detailed cooling parameters; Using the aforementioned detail cooling function, combined with the detail extrusion parameters and detail specification parameters, the first detail fitness of the first detail cooling parameter is analyzed and calculated; Continue optimizing the detail cooling parameters within the detail cooling parameter space until convergence, and output the detail cooling parameters with the highest detail fitness to obtain the optimal detail cooling parameters.

5. The 3D printing intelligent control method according to claim 4, characterized in that, Using the aforementioned detail cooling function, combined with the detail extrusion parameters and detail specification parameters, the first detail fitness of the first detail cooling parameter is analyzed and calculated, including: Based on the detailed extrusion parameters and the first detailed cooling parameters, the first updated detailed nozzle blockage parameters are obtained through analysis. Based on the historical 3D printing data of the detailed area, the sample detail extrusion parameter set and sample detail specification parameter set are collected as analysis inputs. The sample detail printing warpage set, sample detail retention set and sample bonding strength set are collected as analysis outputs, and detail printing warpage analysis branch, detail retention analysis branch and bonding strength analysis branch are constructed respectively. Using the aforementioned detail printing warpage analysis branch, detail retention analysis branch, and adhesive strength analysis branch, detail printing analysis is performed on the detail extrusion parameters, detail specification parameters, and first detail cooling parameters to obtain the first detail printing warpage, first detail retention, and first adhesive strength. Based on the detail cooling function, the first detail fit is calculated.

6. The 3D printing intelligent control method according to claim 1, characterized in that, Based on the aforementioned basic optimization amplitude, with the optimization direction of reducing nozzle clogging and print warping, and improving the adhesion strength of print cooling, the basic extrusion parameters and basic cooling parameters are optimized to obtain the optimal basic extrusion parameters and optimal basic cooling parameters, including: Obtain the basic extrusion parameter space and basic cooling parameter space for printing the basic region; With the optimization goals of reducing nozzle clogging and print warping, and improving the bond strength during print cooling, a basic optimization function is constructed as follows: ； Among them, POF is the basic fitness. , and As weight, To update the base nozzle clogging parameters obtained from the analysis based on the optimized base extrusion parameters and base cooling parameters, Based on the basic nozzle clogging parameters, To analyze and obtain the detailed printing warpage of the base area based on the optimized base extrusion parameters and base cooling parameters, To analyze and obtain the bond strength of the printed base area based on the optimized base extrusion parameters and base cooling parameters, Preset bonding strength; Based on the basic optimization function and the basic optimization magnitude, the basic extrusion parameters and the basic cooling parameters are optimized within the basic cooling parameter space to obtain the optimal basic extrusion parameters and the optimal basic cooling parameters.

7. A 3D printer, characterized in that, Used to implement a 3D printing intelligent control method as described in any one of claims 1 to 6.

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