CN117962314A - Three-dimensional modeling method and system for 3D printer based on digital twin - Google Patents
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Abstract
The invention discloses a three-dimensional modeling method and a system of a 3D printer based on digital twinning, and relates to the technical field of 3D printing, wherein the method comprehensively considers a plurality of factors such as printing parameters, environmental conditions, supporting structures and the like through digital twinning modeling and real-time monitoring technology, and calculates a printing stability coefficient DYx through real-time monitoring and analyzing printing parameter real-time data, environmental data and supporting structure data in the printing process by utilizing the digital twinning modeling technology; analyzing the environmental data and digital twin modeling, and calculating an environmental impact coefficient HJx; by monitoring the support structure data in real time, the support firmness coefficient LGx is calculated and the comprehensive evaluation coefficient PGx is calculated in a correlated manner. On the basis of comprehensive evaluation, a regulation strategy is intelligently generated, and global optimization of the 3D printing process is realized. The method is beneficial to improving printing stability, adapting to different environmental conditions, optimizing the design of the supporting structure, and finally realizing more efficient and high-quality 3D printing production.
Description
Technical Field
The invention relates to the technical field of 3D printing, in particular to a digital twinning-based three-dimensional modeling method and system for a 3D printer.
Background
Traditional 3D printing technology is widely used in different industrial fields, however, due to complex interactions of factors such as material properties, printing parameters, environmental conditions, and the like, traditional 3D printing has problems such as poor printing stability, influence of environmental factors on printing effects, and insufficient design of a support structure. These problems may lead to unstable printing quality, deformation during printing or unstable supporting structure, and the like, which affect printing efficiency and quality of the finished product.
In the printing process of the traditional 3D printer, due to inaccuracy of printing parameters or fluctuation of environmental conditions, printing stability is easily affected, so that the surface of a finished product is not smooth, interlayer adhesiveness is poor, and even interlayer peeling and other problems can occur. This limits the application of 3D printing techniques in high precision fields. Digital twin modeling is a method of mapping an actual physical system or process onto a digitized platform through mathematical modeling and simulation techniques. The application field of the printer is wide, covers a plurality of industries and fields, and is also suitable for the field of 3D printers.
Disclosure of Invention
(One) solving the technical problems
Aiming at the defects of the prior art, the invention provides a digital twinning-based three-dimensional modeling method and system for a 3D printer, which are used for solving the problems in the background art.
(II) technical scheme
In order to achieve the above purpose, the invention is realized by the following technical scheme: a 3D printer three-dimensional modeling method based on digital twinning, which comprises the following steps,
Firstly, establishing a three-dimensional digital twin digital model, importing a CAD model of an object to be printed into the three-dimensional digital twin digital model, scanning an actual object by using a 3D scanner to generate point cloud data, importing the point cloud data into the three-dimensional digital twin digital model converted for modeling, and modeling the object to be printed into the geometric shape of adjustable parameters;
Step two, monitoring and collecting first parameter real-time data, second real-time environment data and third support structure data in the whole process of the 3D printer in real time, wherein the first parameter real-time data comprise a printing head temperature wd1, a printing speed sl, a residual extrusion amount jcl and a printing head position deviation value pcz; the second real-time environmental data includes an environmental temperature wd2, an environmental humidity sd, an illumination intensity gz, and an air pollution particle concentration klnd; the third support structure data includes a support density MD, an included angle value jjz between the support structure and the surface of the print object, a support structure bottom width dbkd, a support structure upper width sbkd, and a support stress coefficient YLx;
Inputting the first parameter real-time data, the second real-time environment data and the third support structure data into a three-dimensional digital model, and analyzing and calculating to obtain the three-dimensional digital model: print stability factor DYx, environmental impact factor HJx, and support firmness factor LGx; and the print stability factor DYx, the environmental impact factor HJx, and the support firmness factor LGx are correlated to obtain a comprehensive evaluation factor PGx;
Step four, when the comprehensive evaluation coefficient PGx is larger than a first standard threshold X, the current comprehensive evaluation is shown to be in a first unqualified state; when a first unqualified state is generated, a regulation and control instruction is generated, and the printing stability coefficient DYx is compared with a first parameter threshold Q1 to obtain a first evaluation result; comparing the environmental impact coefficient HJx with a second environmental threshold Q2 to obtain a second evaluation result; comparing the support firmness coefficient LGx with a third support stability threshold Q3 to obtain a third evaluation result; and generating a corresponding regulation strategy according to the first evaluation result, the second evaluation result and the third evaluation result.
Preferably, the first step includes:
S11, importing a CAD model of an object to be printed into a three-dimensional digital twin digital model, and importing the CAD model into the three-dimensional digital twin digital model by using a standard CAD file format including STL or OBJ;
s12, scanning an actual object by using a 3D scanner to acquire point cloud data; ensuring that each part of the cover is scanned to obtain complete geometric information;
S13, importing the point cloud data into a three-dimensional digital twin digital model, and performing first processing by using a point cloud processing tool; the first processing comprises filtering, reconstructing and smoothing operations of the point cloud to obtain a clear geometric model;
s14, modeling an object to be printed into a geometric shape with adjustable parameters by using a modeling tool built in a three-dimensional digital twin digital model based on the point cloud data for second processing; the second process includes surface fitting, boundary extraction, and curve modeling steps.
Preferably, the printhead temperature wd1 is measured by a thermocouple sensor mounted on the 3D printhead; the printing rate sl is obtained through measurement of an acceleration sensor mounted on the 3D printing head; the residual extrusion amount jcl is obtained through measurement of a 3D printer extruder sensor; the print head position deviation value pcz is obtained by measuring the actual print head position through a position encoder and comparing the actual print head position with a print model preset position value of a three-dimensional digital twin digital model.
Preferably, the ambient temperature wd2 is measured by a temperature sensor installed in the region of the 3D printer; the ambient humidity sd is measured by a humidity sensor installed in the 3D printer area; the illumination intensity gz is obtained through measurement of a photoelectric sensor installed in the 3D printer area; the air pollution particle concentration klnd is obtained by resistive particle sensor measurements installed in the 3D band aged zone.
Preferably, the support density MD is obtained by acquiring the support material structure weight zl, the volume tj and the surface area bmj, and after dimensionless treatment, the support density MD is obtained by the following formula:
The included angle value jjz between the support structure and the surface of the printing object is obtained by measuring the angle between the hot bed and the support structure through an angle sensor;
The support structure bottom width dbkd and the support structure upper width sbkd are acquired by a ranging sensor;
The mode of obtaining the support stress coefficient YLx is as follows: according to the shape of the supporting structure, setting n positions, installing stress sensors, measuring and obtaining n stress values to be YI 1、Yl2、Yl3、...、Yln, and calculating to obtain a supporting stress coefficient YLx in an average mode through the following calculation:
in the formula, a is represented as a first correction constant.
Preferably, the print stability factor DYx is obtained by: extracting the printhead temperature wd1, the printing rate sl, the residual extrusion amount jcl and the printhead position deviation value pcz in the first parameter real-time data, and generating a printing stability coefficient DYx through the following formula after dimensionless processing:
wherein bz1 represents a preset standard printhead temperature threshold, bz2 represents a preset print rate threshold, bz3 represents a preset standard remaining extrusion amount threshold, and bz4 represents a preset standard printhead position deviation value threshold; e1, E2, E3 and E4 are expressed as preset proportionality coefficients, and E1 is more than or equal to 0.12 and less than or equal to 0.18,0.15, E2 is more than or equal to 0.22,0.20, E3 is more than or equal to 0.25, E4 is more than or equal to 0.25 and less than or equal to 0.35, and E1+E2+E3+E4 is more than or equal to 1.0; b is represented as a second correction constant;
The environmental impact coefficient HJx is obtained by the following steps: extracting an environmental temperature wd2, an environmental humidity sd, an illumination intensity gz and an air pollution particle concentration klnd in the second real-time environmental data; after dimensionless processing, the environmental impact coefficient HJx is generated by the following formula:
Wherein bz5 represents a preset standard environmental temperature threshold, bz6 represents a preset environmental humidity threshold, bz7 represents a preset standard illumination intensity threshold, and bz8 represents a preset standard air pollution particle concentration threshold; e5, E6, E7 and E8 are expressed as preset proportionality coefficients, and E5 is more than or equal to 0.15 and less than or equal to 0.22,0.12 and less than or equal to 0.18,0.22, E7 is more than or equal to 0.25,0.32 and E8 is more than or equal to 0.35, and E5+ E6+ E7+ E8 is more than or equal to 1.0; c is denoted as a third correction constant;
The support firmness coefficient LGx is obtained by the following steps: extracting third support structure data including support density MD, an included angle value jjz of the support structure and the surface of the printing object, support structure bottom width dbkd, support structure upper width sbkd and support stress coefficient YLx; after dimensionless treatment, the support-firmness coefficient LGx is generated by the following formula:
Wherein bz9 represents a preset standard support structure density threshold, bz10 represents an included angle value threshold between the preset support structure and the surface of the printing object, bz11 represents a preset standard support structure bottom width threshold, bz12 represents a preset standard support structure upper width threshold, and bz13 represents a preset standard support stress coefficient threshold;
e9, E10, E11, E12 and E13 are expressed as preset proportionality coefficients, and E9 is more than or equal to 0.20 and less than or equal to 0.22,0.10 and less than or equal to E10 and less than or equal to 0.12,0.21 and less than or equal to E11 and less than or equal to 0.25,0.11 and less than or equal to E12 and less than or equal to 0.13,0.25 and less than or equal to E12 and less than or equal to 0.28, and E9+ E10+ E11+ E12+ E13 and less than or equal to 1.0; d is denoted as a fourth correction constant.
Preferably, and generating the print stability factor DYx, the environmental impact factor HJx, and the support firmness factor LGx into a comprehensive evaluation factor PGx by the following associated formulas;
wherein, alpha is more than or equal to 0 and less than or equal to 1, beta is more than or equal to 0 and less than or equal to 1, alpha+beta=1, alpha and beta are weights, and ln 2 is logarithmic operation based on 2 natural numbers.
Preferably, if the integrated assessment coefficient PGxPGx > the first standard threshold value X, the current integrated assessment is not qualified; if the comprehensive evaluation coefficient PGx is less than or equal to a first standard threshold X, the current comprehensive evaluation is qualified, and the production is continued;
When the comprehensive evaluation fails, a first failure state is generated, and the print stability coefficient DYx is compared with a first parameter threshold Q1, so as to obtain a first evaluation result, including: when the printing stability coefficient DYx is larger than the first parameter threshold Q1, the printing stability is not qualified, and a first adjustment strategy is generated; when the printing stability coefficient DYx is less than or equal to a first parameter threshold value Q1, the printing stability meets the standard and belongs to a qualified state;
Comparing the environmental impact coefficient HJx with a second environmental threshold Q2 to obtain a second evaluation result, including: the environmental impact coefficient HJx is larger than the second environmental threshold Q2, which indicates that the environmental condition is unqualified, and a second adjustment strategy is generated; when the environmental influence coefficient HJx is less than or equal to a second environmental threshold Q2, the environmental condition is qualified;
and comparing the support firmness coefficient LGx with a third support stability threshold value Q3 to obtain a third evaluation result. Comprising the following steps: the support firmness coefficient LGx is smaller than a third support stability threshold Q3, which indicates that the firmness of the support structure is unqualified, and a third adjustment strategy is generated; and when the support firmness coefficient LGx is more than or equal to a third support stability threshold Q3, the support structure meets the standard, and the support structure is in a qualified state.
Preferably, the first adjustment strategy comprises: adjusting the temperature wd1 of the printing head to optimize the melting state, adjusting the printing speed sl to control lamination with uniform interlayer adhesiveness, adjusting the residual extrusion amount jcl to ensure that excessive material extrusion does not occur when the printing head moves, influencing the 3D printing quality, adjusting the position deviation value pcz of the printing head, ensuring accurate printing position of each layer, and avoiding structural flaws caused by position deviation;
the second adjustment strategy includes: adjusting the environment temperature wd2 and the environment humidity sd, avoiding the material from absorbing moisture or overdrying to influence the printing quality, adjusting the illumination intensity gz to provide the material to be solidified in the standard time, and adjusting the concentration klnd of air pollution particles to reduce the air pollution;
third adjustment strategy: optimizing the supporting density MD, and adjusting the included angle value jjz between the supporting structure and the surface of the printing object to provide supporting force; adjusting the support structure bottom width dbkd and upper width sbkd and optimizing the support stress coefficient YLx ensures that the support structure is stable and easy to remove.
The three-dimensional modeling system of the 3D printer based on the digital twin comprises a digital twin modeling module, a real-time monitoring module, a digital model analysis and calculation module, a state evaluation module and regulation module, a regulation strategy generation module, a digital twin model updating module and a user interface module;
The digital twin modeling module is used for establishing a three-dimensional digital twin digital model, integrating the CAD model and the processed point cloud data, and modeling the CAD model into the geometric shape of the adjustable parameters;
The real-time monitoring module is used for monitoring and collecting first parameter real-time data, second real-time environment data and third support structure data in the whole process of the 3D printer in real time;
The digital model analysis and calculation module is used for inputting data acquired in real time into a three-dimensional digital model, and obtaining a printing stability coefficient DYx, an environment influence coefficient HJx and a support firmness coefficient LGx through analysis and calculation; and the print stability factor DYx, the environmental impact factor HJx, and the support firmness factor LGx are correlated to obtain a comprehensive evaluation factor PGx;
The state evaluation module and the regulation and control module are used for performing state evaluation according to the comprehensive evaluation coefficient PGx and a set threshold value, and generating a corresponding regulation and control instruction when the comprehensive evaluation coefficient PGx is unqualified;
The regulation strategy generation module is used for generating corresponding regulation strategies when the unqualified state is found, wherein the regulation strategy generation module comprises a first regulation strategy, a second regulation strategy and a third regulation strategy, and particularly relates to the regulation of printing parameters, environmental conditions and a supporting structure;
The digital twin model updating module is used for updating the digital twin model based on the real-time monitoring data and the result of the adjustment strategy so as to continuously optimize the modeling effect and improve the prediction accuracy;
and the user interface module is used for providing a user-friendly interface and displaying real-time monitoring data, evaluation results, adjustment strategies and system states, and simultaneously allowing the user to interact and set.
(III) beneficial effects
The invention provides a three-dimensional modeling method and system of a 3D printer based on digital twinning. The beneficial effects are as follows:
(1) According to the digital twin-based three-dimensional modeling method and system for the 3D printer, the printing stability coefficient DYx is calculated by utilizing a digital twin modeling technology through real-time monitoring and analysis of printing parameter real-time data, environment data and supporting structure data in the printing process, and an adjustment strategy is generated through an adjustment instruction, so that the printing stability is improved. This helps to avoid problems such as unsmooth surface of the finished product, poor interlayer adhesion, etc., especially in the field of high precision.
(2) According to the digital twinning-based three-dimensional modeling method and system for the 3D printer, environmental influence coefficients HJx are calculated through analysis of environmental data and digital twinning modeling, and corresponding regulation strategies are generated. This helps reduce the negative impact of environmental conditions on the printing effect, including controlling temperature and humidity, illumination intensity, and air pollution particle concentration, thereby improving print quality.
(3) According to the digital twinning-based three-dimensional modeling method and system for the 3D printer, the supporting firmness coefficient LGx is calculated by monitoring the supporting structure data in real time, and a regulation strategy is generated. This helps to optimize support density, support structure and print object surface angle, support structure bottom width, support structure upper width, support stress coefficient, etc., to ensure support structure robustness, reducing possible support structure defects.
(4) According to the digital twinning-based three-dimensional modeling method and system for the 3D printer, overall evaluation is carried out on the printer performance through the comprehensive evaluation coefficient PGx, and when PGx is larger than a threshold value, a corresponding disqualified state is generated and a regulation command is generated. And generating a regulation strategy according to the first evaluation, the second evaluation result and the third evaluation result, comprehensively optimizing the printing process, and improving the 3D printing efficiency and the quality of the finished product.
Drawings
FIG. 1 is a schematic diagram of steps of a three-dimensional modeling method of a 3D printer based on digital twinning;
Fig. 2 is a block flow diagram of a digital twinning-based three-dimensional modeling system of a 3D printer according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
The invention provides a three-dimensional modeling method of a 3D printer based on digital twinning, referring to FIG. 1, comprising the following steps,
Firstly, establishing a three-dimensional digital twin digital model, importing a CAD model of an object to be printed into the three-dimensional digital twin digital model, scanning an actual object by using a 3D scanner to generate point cloud data, importing the point cloud data into the three-dimensional digital twin digital model converted for modeling, and modeling the object to be printed into the geometric shape of adjustable parameters;
Step two, monitoring and collecting first parameter real-time data, second real-time environment data and third support structure data in the whole process of the 3D printer in real time, wherein the first parameter real-time data comprise a printing head temperature wd1, a printing speed sl, a residual extrusion amount jcl and a printing head position deviation value pcz; the second real-time environmental data includes an environmental temperature wd2, an environmental humidity sd, an illumination intensity gz, and an air pollution particle concentration klnd; the third support structure data includes a support density MD, an included angle value jjz between the support structure and the surface of the print object, a support structure bottom width dbkd, a support structure upper width sbkd, and a support stress coefficient YLx;
Inputting the first parameter real-time data, the second real-time environment data and the third support structure data into a three-dimensional digital model, and analyzing and calculating to obtain the three-dimensional digital model: print stability factor DYx, environmental impact factor HJx, and support firmness factor LGx; and the print stability factor DYx, the environmental impact factor HJx, and the support firmness factor LGx are correlated to obtain a comprehensive evaluation factor PGx;
Step four, when the comprehensive evaluation coefficient PGx is larger than a first standard threshold X, the current comprehensive evaluation is shown to be in a first unqualified state; when a first unqualified state is generated, a regulation and control instruction is generated, and the printing stability coefficient DYx is compared with a first parameter threshold Q1 to obtain a first evaluation result; comparing the environmental impact coefficient HJx with a second environmental threshold Q2 to obtain a second evaluation result; comparing the support firmness coefficient LGx with a third support stability threshold Q3 to obtain a third evaluation result; and generating a corresponding regulation strategy according to the first evaluation result, the second evaluation result and the third evaluation result.
In this embodiment, by monitoring and analyzing parameters, environmental data, and support structure information in the printing process in real time, the system can adjust printing parameters and support structures in real time, thereby improving printing stability. The application of digital twin models helps to more accurately predict and adjust for complex interactions during printing. Through the real-time monitoring and analysis to factors such as ambient temperature, humidity, illumination intensity and air pollution particle concentration, the system can adjust the parameter in the printing process to reduce the negative influence of environmental factors to the printing effect, improve the uniformity of finished product quality. Through the analysis of the support density, the included angle between the structure and the surface of the printed object, the bottom width, the upper width and the support stress coefficient, the system can optimize the design of the support structure, ensure that the support is firm and easy to remove, thereby reducing the defects of the finished product. When the comprehensive evaluation coefficient PGx exceeds a preset first standard threshold X, the system can generate a corresponding regulation and control instruction, and automatically adjust printing parameters and a supporting structure according to a specific evaluation result, so that intelligent and automatic printing regulation and control is realized. By comprehensively applying digital twin modeling and real-time monitoring, the method is beneficial to the application of the 3D printing technology in the high-precision field, reduces the possible problems in the printing process, and improves the printing precision and reliability.
Embodiment 2, which is explained in embodiment 1, please refer to fig. 1, specifically, the step one includes:
s11, importing a CAD model of an object to be printed into a three-dimensional digital twin digital model, and importing the CAD model into the three-dimensional digital twin digital model by using a standard CAD file format including STL or OBJ; this helps to ensure accuracy and compatibility of the model. The use of a generic file format facilitates sharing and use of these models among different software and systems.
S12, scanning an actual object by using a 3D scanner to acquire point cloud data; ensuring that each part of the cover is scanned to obtain complete geometric information; this step ensures accurate acquisition of the actual object geometry and enables handling of irregularly or complex shaped objects.
S13, importing the point cloud data into a three-dimensional digital twin digital model, and performing first processing by using a point cloud processing tool; the first processing comprises filtering, reconstructing and smoothing operations of the point cloud to obtain a clear geometric model; to clearly present the geometric model of the object to be printed. The point cloud processing is helpful to eliminate noise, fill in missing parts, and improve the quality of the model.
S14, modeling an object to be printed into a geometric shape with adjustable parameters by using a modeling tool built in a three-dimensional digital twin digital model based on the point cloud data for second processing; the second process includes surface fitting, boundary extraction, and curve modeling steps. This step includes surface fitting, boundary extraction and curve modeling, making the model more geometrically shaped with tunable parameters. This provides a more flexible basis for subsequent analysis and optimization.
Example 3, which is an explanation of example 1, referring to fig. 1, specifically, the printhead temperature wd1 is measured by a thermocouple sensor mounted on the 3D printhead; the printing rate sl is obtained through measurement of an acceleration sensor mounted on the 3D printing head; the residual extrusion amount jcl is obtained through measurement of a 3D printer extruder sensor; the print head position deviation value pcz is obtained by measuring the actual print head position through a position encoder and comparing the actual print head position with a print model preset position value of a three-dimensional digital twin digital model.
In this embodiment, the thermocouple sensor is mounted on the 3D printhead to measure the temperature, which is helpful for monitoring the temperature change in the printing process in real time. This is important for optimizing the molten state of the printing material and improving the printing quality. With an acceleration sensor mounted on the 3D printhead, the print rate can be measured in real time. Such measurements help control interlayer adhesion, ensure uniformity of lamination, and thereby improve print accuracy and stability. The remaining extrusion amount can be monitored by measurement of the 3D printer extruder sensor. And the position encoder is used for measuring the actual position of the printing head and comparing the actual position with a preset position value of the three-dimensional digital twin digital model, so that the position deviation of the printing head can be monitored in real time. This ensures that the print position of each layer is accurate, avoiding positional deviations that result in structural imperfections. Has important function for avoiding excessive material extrusion when the printing head moves, thereby influencing the printing quality.
Embodiment 4, which is an explanation of embodiment 1, referring to fig. 1, specifically, the ambient temperature wd2 is measured by a temperature sensor installed in the 3D printer area; the ambient humidity sd is measured by a humidity sensor installed in the 3D printer area; the illumination intensity gz is obtained through measurement of a photoelectric sensor installed in the 3D printer area; the air pollution particle concentration klnd is obtained by resistive particle sensor measurements installed in the 3D band aged zone.
In this embodiment, by installing a temperature sensor in the 3D printer area, the ambient temperature can be measured in real time. This has a significant impact on the curing of the material and the stability of the printing process, as temperature changes may lead to changes in the properties of the material. The change in ambient humidity can be monitored in real time using humidity sensors installed in the 3D printer area. Humidity has an effect on the hygroscopicity of some 3D printing materials, so control of humidity helps to avoid variations in material properties, thereby improving the stability of printing. The illumination intensity is measured by the photoelectric sensor, so that the illumination condition can be monitored in real time. This is critical to the visibility of some materials that require photo-curing or during printing, so control of the illumination intensity helps to improve the print quality. The concentration of pollutant particles in the air is measured by using the resistance type particle sensor, so that the cleanliness of the environment can be monitored. In particular in some environments where environmental requirements are high, such as in the medical or precision manufacturing field, air quality is critical to print quality.
Example 5, this example is illustrated in example 1, referring specifically to fig. 1, the support density MD is obtained by acquiring the support material structure weight zl, the volume tj and the surface area bmj, and after dimensionless processing, the support density MD is obtained by the following formula:
The included angle value jjz between the support structure and the surface of the printing object is obtained by measuring the angle between the hot bed and the support structure through an angle sensor;
The support structure bottom width dbkd and the support structure upper width sbkd are acquired by a ranging sensor;
The mode of obtaining the support stress coefficient YLx is as follows: according to the shape of the supporting structure, setting n positions, installing stress sensors, measuring and obtaining n stress values to be YI 1、Yl2、Yl3、...、Yln, and calculating to obtain a supporting stress coefficient YLx in an average mode through the following calculation:
in the formula, a is represented as a first correction constant.
In this embodiment, the support density MD is obtained by acquiring the weight zl, the volume tj and the surface area bmj of the support material structure, and applying a corresponding formula after dimensionless processing. The acquisition of the supporting density is helpful for optimizing the design of the supporting structure, so that the supporting structure is more suitable for different printing objects, and the effect of the supporting structure is improved. The angle between the hot bed and the supporting structure is measured by the angle sensor, so that the value of the included angle between the supporting structure and the surface of the printed object can be accurately obtained. This has a critical effect on the design of the support structure and the stability of the printed object. The distance measuring sensor is used for collecting the width information of the bottom and the upper part of the supporting structure, so that the shape and the size of the supporting structure can be better controlled, and the supporting firmness is improved. Stress sensors are arranged at different positions of the supporting structure, stress values are obtained through measurement, and then the average value is calculated to obtain the supporting stress coefficient YLx. This helps to evaluate the stress conditions of the support structure, providing critical information for the design and optimization of the support.
Embodiment 6, which is an explanation of embodiment 1, please refer to fig. 1, specifically, the print stability factor DYx is obtained by: extracting the printhead temperature wd1, the printing rate sl, the residual extrusion amount jcl and the printhead position deviation value pcz in the first parameter real-time data, and generating a printing stability coefficient DYx through the following formula after dimensionless processing:
wherein bz1 represents a preset standard printhead temperature threshold, bz2 represents a preset print rate threshold, bz3 represents a preset standard remaining extrusion amount threshold, and bz4 represents a preset standard printhead position deviation value threshold; e1, E2, E3 and E4 are expressed as preset proportionality coefficients, and E1 is more than or equal to 0.12 and less than or equal to 0.18,0.15, E2 is more than or equal to 0.22,0.20, E3 is more than or equal to 0.25, E4 is more than or equal to 0.25 and less than or equal to 0.35, and E1+E2+E3+E4 is more than or equal to 1.0; b is represented as a second correction constant;
The environmental impact coefficient HJx is obtained by the following steps: extracting an environmental temperature wd2, an environmental humidity sd, an illumination intensity gz and an air pollution particle concentration klnd in the second real-time environmental data; after dimensionless processing, the environmental impact coefficient HJx is generated by the following formula:
Wherein bz5 represents a preset standard environmental temperature threshold, bz6 represents a preset environmental humidity threshold, bz7 represents a preset standard illumination intensity threshold, and bz8 represents a preset standard air pollution particle concentration threshold; e5, E6, E7 and E8 are expressed as preset proportionality coefficients, and E5 is more than or equal to 0.15 and less than or equal to 0.22,0.12 and less than or equal to 0.18,0.22, E7 is more than or equal to 0.25,0.32 and E8 is more than or equal to 0.35, and E5+ E6+ E7+ E8 is more than or equal to 1.0; c is denoted as a third correction constant;
The support firmness coefficient LGx is obtained by the following steps: extracting third support structure data including support density MD, an included angle value jjz of the support structure and the surface of the printing object, support structure bottom width dbkd, support structure upper width sbkd and support stress coefficient YLx; after dimensionless treatment, the support-firmness coefficient LGx is generated by the following formula:
Wherein bz9 represents a preset standard support structure density threshold, bz10 represents an included angle value threshold between the preset support structure and the surface of the printing object, bz11 represents a preset standard support structure bottom width threshold, bz12 represents a preset standard support structure upper width threshold, and bz13 represents a preset standard support stress coefficient threshold; e9, E10, E11, E12 and E13 are expressed as preset proportionality coefficients, and E9 is more than or equal to 0.20 and less than or equal to 0.22,0.10 and less than or equal to E10 and less than or equal to 0.12,0.21 and less than or equal to E11 and less than or equal to 0.25,0.11 and less than or equal to E12 and less than or equal to 0.13,0.25 and less than or equal to E12 and less than or equal to 0.28, and E9+ E10+ E11+ E12+ E13 and less than or equal to 1.0; d is denoted as a fourth correction constant.
In this embodiment, the print stability factor DYx is generated by extracting the print head temperature wd1, the print rate sl, the remaining extrusion amount jcl, and the print head position deviation value pcz in the first parameter real-time data, and performing dimensionless processing, and by a corresponding formula. The method is beneficial to monitoring key parameters in the printing process in real time, evaluating the printing stability, and generating corresponding regulation and control instructions according to the set threshold value, so that the printing quality is improved. The environmental impact coefficient HJx is generated by extracting the environmental temperature wd2, the environmental humidity sd, the illumination intensity gz, and the air pollution particle concentration klnd in the second real-time environmental data, performing dimensionless processing, and using a corresponding formula. This helps to understand how much environmental factors affect the printing effect, providing guidance for adjusting the printing parameters. The third support structure data including the support density MD, the angle value jjz between the support structure and the surface of the print object, the support structure bottom width dbkd, the support structure upper width sbkd, and the support stress coefficient YLx are extracted, dimensionless processing is performed, and the support firmness coefficient LGx is generated by a corresponding formula. The method is favorable for evaluating the firmness of the support structure, and corresponding regulation and control strategies are generated according to the set threshold value, so that the effect and stability of the support are improved. The correction constant and the scaling factor are introduced into the formula, and the setting of the parameters can be adjusted according to specific requirements, so that the system is more flexible and adapts to different printing scenes.
Embodiment 7, which is an explanation made in embodiment 1, please refer to fig. 1 specifically, and generates a comprehensive evaluation coefficient PGx by the following associated formulas with respect to the print stability coefficient DYx, the environmental impact coefficient HJx, and the support firmness coefficient LGx;
wherein, alpha is more than or equal to 0 and less than or equal to 1, beta is more than or equal to 0 and less than or equal to 1, alpha+beta=1, alpha and beta are weights, and ln 2 is logarithmic operation based on 2 natural numbers.
In this embodiment, by taking the print stability factor DYx, the environmental impact factor HJx, and the support firmness factor LGx into account in the calculation of the comprehensive evaluation factor PGx, various impact factors in the 3D printing process can be more comprehensively considered, and the comprehensive grasp of the overall quality is improved. The weight and the logarithmic operation based on 2 are introduced, so that the influence of different factors is reasonably distributed in comprehensive evaluation. The design is helpful to adjust the relative importance of different factors according to actual conditions, so that the system is more flexible to adapt to different processes and requirements. The logarithmic operation based on 2 can compress the numerical range to a certain extent, and the influence of extreme numerical values on comprehensive evaluation is avoided to be too large, so that the system is more stable and robust.
Example 8, which is an explanation of example 1, please refer to fig. 1, specifically, if the integrated evaluation coefficient PGxPGx > the first standard threshold value X, it is explained that the current integrated evaluation is not acceptable; if the comprehensive evaluation coefficient PGx is less than or equal to a first standard threshold X, the current comprehensive evaluation is qualified, and the production is continued;
When the comprehensive evaluation fails, a first failure state is generated, and the print stability coefficient DYx is compared with a first parameter threshold Q1, so as to obtain a first evaluation result, including: when the printing stability coefficient DYx is larger than the first parameter threshold Q1, the printing stability is not qualified, and a first adjustment strategy is generated; when the printing stability coefficient DYx is less than or equal to a first parameter threshold value Q1, the printing stability meets the standard and belongs to a qualified state;
Comparing the environmental impact coefficient HJx with a second environmental threshold Q2 to obtain a second evaluation result, including: the environmental impact coefficient HJx is larger than the second environmental threshold Q2, which indicates that the environmental condition is unqualified, and a second adjustment strategy is generated; when the environmental influence coefficient HJx is less than or equal to a second environmental threshold Q2, the environmental condition is qualified;
and comparing the support firmness coefficient LGx with a third support stability threshold value Q3 to obtain a third evaluation result. Comprising the following steps: the support firmness coefficient LGx is smaller than a third support stability threshold Q3, which indicates that the firmness of the support structure is unqualified, and a third adjustment strategy is generated; and when the support firmness coefficient LGx is more than or equal to a third support stability threshold Q3, the support structure meets the standard, and the support structure is in a qualified state.
In this embodiment, the system realizes multi-level evaluation of multiple key factors in the 3D printing process by comprehensively judging three evaluation results (printing stability, environmental conditions, supporting structure). Such comprehensive consideration helps to more fully and accurately identify problems, avoiding the limitations of single factor evaluation. For each evaluation result, the system generates a corresponding adjustment strategy. For example, in the case of unqualified print stability, by comparing the print stability coefficient DYx with the first parameter threshold Q1, the system can generate a specific print stability adjustment policy, thereby realizing a refined solution to the problem. The system has a real-time feedback mechanism because the data is monitored and collected in real time, and an adjustment strategy is generated immediately when the comprehensive evaluation is unqualified. This helps to adjust and correct problems in time, improving the flexibility and efficiency of the production process. Each evaluation result is compared with a set threshold value, and the threshold values can be set and adjusted according to specific requirements. This allows for a more customizable system that can accommodate different process and material requirements. By real-time evaluation and adjustment, the system can avoid producing unacceptable products during printing. This helps to improve production efficiency, reduce reject rate, and at the same time ensure product quality meets the standards.
Embodiment 9, which is an explanation of embodiment 8, referring to fig. 1, specifically, the first adjustment strategy includes: adjusting the temperature wd1 of the printing head to optimize the melting state, adjusting the printing speed sl to control lamination with uniform interlayer adhesiveness, adjusting the residual extrusion amount jcl to ensure that excessive material extrusion does not occur when the printing head moves, influencing the 3D printing quality, adjusting the position deviation value pcz of the printing head, ensuring accurate printing position of each layer, and avoiding structural flaws caused by position deviation; by optimizing the molten state, it is possible to ensure uniform melting of the material at a proper temperature, improving the printing quality. The uniform lamination of interlayer adhesiveness is controlled, so that problems such as interlayer peeling can be prevented, and printing stability can be improved. Ensuring that the printhead is not moved with excessive material extrusion and thus avoiding negative impact on print quality. The printing position of each layer is ensured to be accurate, structural flaws caused by position deviation are avoided, and the accuracy of geometric shapes is improved.
The second adjustment strategy includes: adjusting the environment temperature wd2 and the environment humidity sd, avoiding the material from absorbing moisture or overdrying to influence the printing quality, adjusting the illumination intensity gz to provide the material to be solidified in the standard time, and adjusting the concentration klnd of air pollution particles to reduce the air pollution; avoiding the problem of moisture absorption or overdry of the material and ensuring that the quality of the material is not affected by environmental conditions. The material is solidified in the standard time, so that the solidification speed in the printing process can be controlled, and the printing quality can be improved. The particle pollution in the air is reduced, and the influence of the environment on the printing quality is ensured to be minimized.
Third adjustment strategy: optimizing the supporting density MD, and adjusting the included angle value jjz between the supporting structure and the surface of the printing object to provide supporting force; adjusting the support structure bottom width dbkd and upper width sbkd and optimizing the support stress coefficient YLx ensures that the support structure is stable and easy to remove. Ensure that the support structure fully supports the printed object and avoid the excessive or insufficient support problem. Providing proper supporting force and ensuring firm supporting structure. The shape of the support structure is optimized to more closely conform to the shape of the printed object. Stability and easy removability of the support structure are ensured to reduce the impact on the finished product.
The three-dimensional modeling system of the 3D printer based on the digital twin comprises a digital twin modeling module, a real-time monitoring module, a digital model analysis and calculation module, a state evaluation module and regulation module, a regulation strategy generation module, a digital twin model updating module and a user interface module;
The digital twin modeling module is used for establishing a three-dimensional digital twin digital model, integrating the CAD model and the processed point cloud data, and modeling the CAD model into the geometric shape of the adjustable parameters;
The real-time monitoring module is used for monitoring and collecting first parameter real-time data, second real-time environment data and third support structure data in the whole process of the 3D printer in real time;
The digital model analysis and calculation module is used for inputting data acquired in real time into a three-dimensional digital model, and obtaining a printing stability coefficient DYx, an environment influence coefficient HJx and a support firmness coefficient LGx through analysis and calculation; and the print stability factor DYx, the environmental impact factor HJx, and the support firmness factor LGx are correlated to obtain a comprehensive evaluation factor PGx;
The state evaluation module and the regulation and control module are used for performing state evaluation according to the comprehensive evaluation coefficient PGx and a set threshold value, and generating a corresponding regulation and control instruction when the comprehensive evaluation coefficient PGx is unqualified;
The regulation strategy generation module is used for generating corresponding regulation strategies when the unqualified state is found, wherein the regulation strategy generation module comprises a first regulation strategy, a second regulation strategy and a third regulation strategy, and particularly relates to the regulation of printing parameters, environmental conditions and a supporting structure;
The digital twin model updating module is used for updating the digital twin model based on the real-time monitoring data and the result of the adjustment strategy so as to continuously optimize the modeling effect and improve the prediction accuracy;
and the user interface module is used for providing a user-friendly interface and displaying real-time monitoring data, evaluation results, adjustment strategies and system states, and simultaneously allowing the user to interact and set.
Specific data examples: assume that: the following data were collected:
Printhead temperature wd1 = 200 ℃; print rate sl=50 mm/s; the residual extrusion amount jcl =5 mm3/s;
The printhead position deviation value pcz=0.2 mm; ambient temperature wd2 = 25 ℃; ambient humidity sd=50%; light intensity luxgz = 800lux;
air pollution particle concentration klnd =20 μg/m3; support density md=0.003 g/mm3;
The included angle value jjz =45 between the supporting structure and the surface of the printing object; support structure bottom width dbkd = 2mm;
The support structure upper width sbkd = 1mm; the support stress coefficient YLx =150 MPa;
Meanwhile, preset parameter values and proportionality coefficients are used:
A standard printhead temperature threshold bz1=220℃;
A preset print rate threshold bz2=60 mm/s;
Presetting a standard residual extrusion quantity threshold bz3=8mm3/s;
Presetting a standard printhead position deviation value threshold bz4=0.3 mm; a preset standard ambient temperature threshold bz5=30 ℃;
Preset ambient humidity threshold bz6=60%; preset standard illumination intensity threshold uxbz7 =1000 lux; presetting a standard air pollution particle concentration threshold bz8=30 mug/m < 3 >;
presetting a standard support structure density threshold bz9=0.005 g/mm3;
Presetting an included angle value threshold bz10=60 between the supporting structure and the surface of the printing object;
presetting a standard support structure bottom width threshold bz11=3 mm;
presetting a standard support structure upper width threshold bz12=2mm;
Presetting a standard support stress coefficient threshold bz13=200 MPa;
Scaling factor:
E1＝0.15；E2＝0.20；E3＝0.22；E4＝0.25；E5＝0.18；E6＝0.15；E7＝0.25；
E8 =0.32; e9 =0.22; e10 =0.12; e11 =0.24; e12 =0.12; e13 =0.30; a second correction constant b=0.05; c=0.03; d=0.05;
Substituting the formula to obtain
DYx ≡0.06818+0.08333+0.176+0.3333+0.05≡ 0.7108; DYx ≡ 0.7108 under this data example. This value can be used in a subsequent comprehensive evaluation process;
substituting the formula to obtain:
HJx≈0.15+0.125+0.3125+0.2133+0.03HJx≈0.15+0.125+0.3125+0.2133+0.03≈0.8318；
thus, the environmental impact coefficient HJx under this data example is about 0.8318. This value can be used in the subsequent comprehensive evaluation process.
Substituting the formula to obtain:
LGx is approximately 0.2933; the support factor LGx for this data example is about 0.2933. This value can be used in the subsequent comprehensive evaluation process.
As is known, DYx ≡ 0.7108; HJx ≡ 0.8318; LGx is approximately 0.2933;
now, substituting these values into the associated formulas generates the composite evaluation coefficients PGx. Let a weight α=0.6, a weight β=0.4, and use a natural logarithm ln2 based on 2. Substitution formula:
The overall evaluation coefficient PGx is about 1.2242; the first standard threshold X is set to 1.2. Therefore PGx is greater than X.
Thereby, a first reject state is generated.
A first evaluation of print stability was made.
The print stability factor DYx is compared to a first parameter threshold Q1. Let Q1 be 0.7.
If DYx > Q1, print stability is indicated to be unacceptable. In this example DYx is greater than Q1. Thus, generating a first adjustment strategy may include adjusting printhead temperature, print rate, remaining squeeze-out, or printhead position offset values, etc., to optimize print stability. A second evaluation is made for environmental conditions.
The environmental impact coefficient HJx is compared to a second environmental threshold Q2. Let Q2 be 0.8. If HJx > Q2, this indicates that the environmental condition is unacceptable. In this example HJx is greater than Q2. Thus, a second adjustment strategy is generated, which may include adjusting ambient temperature, humidity, illumination intensity, or air pollution particle concentration, etc., to improve the environmental conditions. A third evaluation is made for the support structure.
The support firmness coefficient LGx is compared with a third support stability threshold Q3. Let Q3 be 0.3.
If LGx < Q3, it indicates that the support structure is not strong. In this example, LGx is less than Q3.
Thus, generating a third adjustment strategy may include optimizing support density, support structure-to-print object surface angle, support structure bottom width, support structure upper width, or support stress coefficient, etc., to promote support structure firmness.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. A three-dimensional modeling method of a 3D printer based on digital twinning is characterized by comprising the following steps: comprises the steps of,
Firstly, establishing a three-dimensional digital twin digital model, importing a CAD model of an object to be printed into the three-dimensional digital twin digital model, scanning an actual object by using a 3D scanner to generate point cloud data, importing the point cloud data into the three-dimensional digital twin digital model converted for modeling, and modeling the object to be printed into the geometric shape of adjustable parameters;
Step two, monitoring and collecting first parameter real-time data, second real-time environment data and third support structure data in the whole process of the 3D printer in real time, wherein the first parameter real-time data comprise a printing head temperature wd1, a printing speed sl, a residual extrusion amount jcl and a printing head position deviation value pcz; the second real-time environmental data includes an environmental temperature wd2, an environmental humidity sd, an illumination intensity gz, and an air pollution particle concentration klnd; the third support structure data includes a support density MD, an included angle value jjz between the support structure and the surface of the print object, a support structure bottom width dbkd, a support structure upper width sbkd, and a support stress coefficient YLx;
Inputting the first parameter real-time data, the second real-time environment data and the third support structure data into a three-dimensional digital model, and analyzing and calculating to obtain the three-dimensional digital model: print stability factor DYx, environmental impact factor HJx, and support firmness factor LGx; and the print stability factor DYx, the environmental impact factor HJx, and the support firmness factor LGx are correlated to obtain a comprehensive evaluation factor PGx;
Step four, when the comprehensive evaluation coefficient PGx is larger than a first standard threshold X, the current comprehensive evaluation is shown to be in a first unqualified state; when a first unqualified state is generated, a regulation and control instruction is generated, and the printing stability coefficient DYx is compared with a first parameter threshold Q1 to obtain a first evaluation result; comparing the environmental impact coefficient HJx with a second environmental threshold Q2 to obtain a second evaluation result; comparing the support firmness coefficient LGx with a third support stability threshold Q3 to obtain a third evaluation result; and generating a corresponding regulation strategy according to the first evaluation result, the second evaluation result and the third evaluation result.
2. The digital twinning-based 3D printer three-dimensional modeling method of claim 1, wherein: the first step comprises the following steps:
S11, importing a CAD model of an object to be printed into a three-dimensional digital twin digital model, and importing the CAD model into the three-dimensional digital twin digital model by using a standard CAD file format including STL or OBJ;
s12, scanning an actual object by using a 3D scanner to acquire point cloud data; ensuring that each part of the cover is scanned to obtain complete geometric information;
S13, importing the point cloud data into a three-dimensional digital twin digital model, and performing first processing by using a point cloud processing tool; the first processing comprises filtering, reconstructing and smoothing operations of the point cloud to obtain a clear geometric model;
s14, modeling an object to be printed into a geometric shape with adjustable parameters by using a modeling tool built in a three-dimensional digital twin digital model based on the point cloud data for second processing; the second process includes surface fitting, boundary extraction, and curve modeling steps.
3. The digital twinning-based 3D printer three-dimensional modeling method of claim 1, wherein: the printhead temperature wd1 is measured by a thermocouple sensor mounted on the 3D printhead; the printing rate sl is obtained through measurement of an acceleration sensor mounted on the 3D printing head; the residual extrusion amount jcl is obtained through measurement of a 3D printer extruder sensor; the print head position deviation value pcz is obtained by measuring the actual print head position through a position encoder and comparing the actual print head position with a print model preset position value of a three-dimensional digital twin digital model.
4. The digital twinning-based 3D printer three-dimensional modeling method of claim 1, wherein:
The ambient temperature wd2 is measured by a temperature sensor installed in the 3D printer area; the ambient humidity sd is measured by a humidity sensor installed in the 3D printer area; the illumination intensity gz is obtained through measurement of a photoelectric sensor installed in the 3D printer area; the air pollution particle concentration klnd is obtained by resistive particle sensor measurements installed in the 3D band aged zone.
5. The digital twinning-based 3D printer three-dimensional modeling method of claim 1, wherein: the supporting density MD is obtained by acquiring the structural weight zl, the volume tj and the surface area bmj of the supporting material, and the supporting density MD is obtained by the following formula after dimensionless treatment:
The included angle value jjz between the support structure and the surface of the printing object is obtained by measuring the angle between the hot bed and the support structure through an angle sensor;
The support structure bottom width dbkd and the support structure upper width sbkd are acquired by a ranging sensor;
The mode of obtaining the support stress coefficient YLx is as follows: according to the shape of the supporting structure, setting n positions, installing stress sensors, measuring and obtaining n stress values to be YI 1、Yl2、Yl3、...、Yln, and calculating to obtain a supporting stress coefficient YLx in an average mode through the following calculation:
in the formula, a is represented as a first correction constant.
6. The digital twinning-based 3D printer three-dimensional modeling method of claim 1, wherein: the print stability factor DYx is obtained by the following steps: extracting the printhead temperature wd1, the printing rate sl, the residual extrusion amount jcl and the printhead position deviation value pcz in the first parameter real-time data, and generating a printing stability coefficient DYx through the following formula after dimensionless processing:
wherein bz1 represents a preset standard printhead temperature threshold, bz2 represents a preset print rate threshold, bz3 represents a preset standard remaining extrusion amount threshold, and bz4 represents a preset standard printhead position deviation value threshold; e1, E2, E3 and E4 are expressed as preset proportionality coefficients, and E1 is more than or equal to 0.12 and less than or equal to 0.18,0.15, E2 is more than or equal to 0.22,0.20, E3 is more than or equal to 0.25, E4 is more than or equal to 0.25 and less than or equal to 0.35, and E1+E2+E3+E4 is more than or equal to 1.0; b is represented as a second correction constant;
The environmental impact coefficient HJx is obtained by the following steps: extracting an environmental temperature wd2, an environmental humidity sd, an illumination intensity gz and an air pollution particle concentration klnd in the second real-time environmental data; after dimensionless processing, the environmental impact coefficient HJx is generated by the following formula:
Wherein bz5 represents a preset standard environmental temperature threshold, bz6 represents a preset environmental humidity threshold, bz7 represents a preset standard illumination intensity threshold, and bz8 represents a preset standard air pollution particle concentration threshold; e5, E6, E7 and E8 are expressed as preset proportionality coefficients, and E5 is more than or equal to 0.15 and less than or equal to 0.22,0.12 and less than or equal to 0.18,0.22, E7 is more than or equal to 0.25,0.32 and E8 is more than or equal to 0.35, and E5+ E6+ E7+ E8 is more than or equal to 1.0; c is denoted as a third correction constant;
The support firmness coefficient LGx is obtained by the following steps: extracting third support structure data including support density MD, an included angle value jjz of the support structure and the surface of the printing object, support structure bottom width dbkd, support structure upper width sbkd and support stress coefficient YLx; after dimensionless treatment, the support-firmness coefficient LGx is generated by the following formula:
Wherein bz9 represents a preset standard support structure density threshold, bz10 represents an included angle value threshold between the preset support structure and the surface of the printing object, bz11 represents a preset standard support structure bottom width threshold, bz12 represents a preset standard support structure upper width threshold, and bz13 represents a preset standard support stress coefficient threshold; e9, E10, E11, E12 and E13 are expressed as preset proportionality coefficients, and E9 is more than or equal to 0.20 and less than or equal to 0.22,0.10 and less than or equal to E10 and less than or equal to 0.12,0.21 and less than or equal to E11 and less than or equal to 0.25,0.11 and less than or equal to E12 and less than or equal to 0.13,0.25 and less than or equal to E12 and less than or equal to 0.28, and E9+ E10+ E11+ E12+ E13 and less than or equal to 1.0; d is denoted as a fourth correction constant.
7. The digital twinning-based 3D printer three-dimensional modeling method of claim 1, wherein: and generates a comprehensive evaluation coefficient PGx from the print stability coefficient DYx, the environmental impact coefficient HJx, and the support firmness coefficient LGx by the following correlation formula;
wherein, alpha is more than or equal to 0 and less than or equal to 1, beta is more than or equal to 0 and less than or equal to 1, alpha+beta=1, alpha and beta are weights, and ln 2 is logarithmic operation based on 2 natural numbers.
8. The digital twinning-based 3D printer three-dimensional modeling method of claim 1, wherein: if the comprehensive evaluation coefficient PGxPGx is greater than the first standard threshold X, the current comprehensive evaluation is not qualified; if the comprehensive evaluation coefficient PGx is less than or equal to a first standard threshold X, the current comprehensive evaluation is qualified, and the production is continued;
When the comprehensive evaluation fails, a first failure state is generated, and the print stability coefficient DYx is compared with a first parameter threshold Q1, so as to obtain a first evaluation result, including: when the printing stability coefficient DYx is larger than the first parameter threshold Q1, the printing stability is not qualified, and a first adjustment strategy is generated; when the printing stability coefficient DYx is less than or equal to a first parameter threshold value Q1, the printing stability meets the standard and belongs to a qualified state;
Comparing the environmental impact coefficient HJx with a second environmental threshold Q2 to obtain a second evaluation result, including: the environmental impact coefficient HJx is larger than the second environmental threshold Q2, which indicates that the environmental condition is unqualified, and a second adjustment strategy is generated; when the environmental influence coefficient HJx is less than or equal to a second environmental threshold Q2, the environmental condition is qualified;
and comparing the support firmness coefficient LGx with a third support stability threshold value Q3 to obtain a third evaluation result. Comprising the following steps: the support firmness coefficient LGx is smaller than a third support stability threshold Q3, which indicates that the firmness of the support structure is unqualified, and a third adjustment strategy is generated; and when the support firmness coefficient LGx is more than or equal to a third support stability threshold Q3, the support structure meets the standard, and the support structure is in a qualified state.
9. The digital twinning-based 3D printer three-dimensional modeling method of claim 8, wherein: the first adjustment strategy includes: adjusting the temperature wd1 of the printing head to optimize the melting state, adjusting the printing speed sl to control lamination with uniform interlayer adhesiveness, adjusting the residual extrusion amount jcl to ensure that excessive material extrusion does not occur when the printing head moves, influencing the 3D printing quality, adjusting the position deviation value pcz of the printing head, ensuring accurate printing position of each layer, and avoiding structural flaws caused by position deviation;
the second adjustment strategy includes: adjusting the environment temperature wd2 and the environment humidity sd, avoiding the material from absorbing moisture or overdrying to influence the printing quality, adjusting the illumination intensity gz to provide the material to be solidified in the standard time, and adjusting the concentration klnd of air pollution particles to reduce the air pollution;
third adjustment strategy: optimizing the supporting density MD, and adjusting the included angle value jjz between the supporting structure and the surface of the printing object to provide supporting force; adjusting the support structure bottom width dbkd and upper width sbkd and optimizing the support stress coefficient YLx ensures that the support structure is stable and easy to remove.
10. A digital twin based 3D printer three-dimensional modeling system, comprising a digital twin based 3D printer three-dimensional modeling method according to any of the preceding claims 1 to 9, characterized in that: the system comprises a digital twin modeling module, a real-time monitoring module, a digital model analysis and calculation module, a state evaluation module, a regulation and control strategy generation module, a digital twin model updating module and a user interface module;
The digital twin modeling module is used for establishing a three-dimensional digital twin digital model, integrating the CAD model and the processed point cloud data, and modeling the CAD model into the geometric shape of the adjustable parameters;
The real-time monitoring module is used for monitoring and collecting first parameter real-time data, second real-time environment data and third support structure data in the whole process of the 3D printer in real time;
The digital model analysis and calculation module is used for inputting data acquired in real time into a three-dimensional digital model, and obtaining a printing stability coefficient DYx, an environment influence coefficient HJx and a support firmness coefficient LGx through analysis and calculation; and the print stability factor DYx, the environmental impact factor HJx, and the support firmness factor LGx are correlated to obtain a comprehensive evaluation factor PGx;
The state evaluation module and the regulation and control module are used for performing state evaluation according to the comprehensive evaluation coefficient PGx and a set threshold value, and generating a corresponding regulation and control instruction when the comprehensive evaluation coefficient PGx is unqualified;
The regulation strategy generation module is used for generating corresponding regulation strategies when the unqualified state is found, wherein the regulation strategy generation module comprises a first regulation strategy, a second regulation strategy and a third regulation strategy, and particularly relates to the regulation of printing parameters, environmental conditions and a supporting structure;
The digital twin model updating module is used for updating the digital twin model based on the real-time monitoring data and the result of the adjustment strategy so as to continuously optimize the modeling effect and improve the prediction accuracy;
and the user interface module is used for providing a user-friendly interface and displaying real-time monitoring data, evaluation results, adjustment strategies and system states, and simultaneously allowing the user to interact and set.
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