CN117077233A - Generation management system for 3D model - Google Patents

Generation management system for 3D model Download PDF

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CN117077233A
CN117077233A CN202311337129.7A CN202311337129A CN117077233A CN 117077233 A CN117077233 A CN 117077233A CN 202311337129 A CN202311337129 A CN 202311337129A CN 117077233 A CN117077233 A CN 117077233A
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printing
generation
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subsystem
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CN117077233B (en
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周飞
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Zhuhai Bense Molding Imaging Material Research Institute Co ltd
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Zhuhai Bense Molding Imaging Material Research Institute Co ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
    • B29C64/00—Additive manufacturing, i.e. manufacturing of three-dimensional [3D] objects by additive deposition, additive agglomeration or additive layering, e.g. by 3D printing, stereolithography or selective laser sintering
    • B29C64/30—Auxiliary operations or equipment
    • B29C64/386—Data acquisition or data processing for additive manufacturing
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B33—ADDITIVE MANUFACTURING TECHNOLOGY
    • B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y50/00—Data acquisition or data processing for additive manufacturing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00—Details relating to the application field
    • G06F2113/10—Additive manufacturing, e.g. 3D printing
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

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Abstract

The application relates to the field of data management, and particularly discloses a generation management system for a 3D model, which comprises a material supply subsystem, a parameter management subsystem, a 3D model generation subsystem and a user intervention interface; according to the application, the 3D feedback control model is established, the printing index of the 3D model is regulated, and the regulation strategy is set according to the error signal obtained by the 3D feedback control model so as to adapt to the requirements of different areas, the supporting structure is automatically generated and regulated through the supporting structure generation algorithm, the occurrence of weak parts can be reduced through real-time monitoring and regulation, the printing failure and the generation of waste materials can be reduced through automatically regulating the printing parameters, the resource utilization rate is improved, the printing interruption caused by uneven feeding or material clamping is avoided, the time and labor cost are saved, the stability of the printing process is ensured, and the risks of the printing interruption and the printing failure are reduced.

Description

Generation management system for 3D model
Technical Field
The application relates to the technical field of data management, in particular to a generation management system for a 3D model.
Background
A 3D model, i.e. a three-dimensional model, is a mathematical representation describing the shape and position of an object using three-dimensional coordinates, in computer graphics, a 3D model usually consists of vertices, edges and faces, where there is a certain topological relation between the vertices, edges and faces, which relation determines the geometry of the model. In the process of generating the 3D model, uneven feeding or clamping of printing materials often occurs, which causes uneven printing layers, too weak partial areas and insufficient adhesiveness between the printing layers, thereby affecting the overall strength and stability of the printed object.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, the present application provides a generation management system for a 3D model, by establishing a 3D feedback control model, adjusting a 3D model printing index, and setting an adjustment policy according to an error signal obtained by the 3D feedback control model, automatically generating and adjusting a support structure through a support structure generation algorithm, by monitoring and adjusting in real time, the occurrence of weak portions can be reduced, and automatically adjusting printing parameters can reduce printing failure and waste generation, thereby avoiding printing interruption caused by uneven feeding or material jam, and solving the problems set forth in the above-mentioned background art.
In order to achieve the above purpose, the present application provides the following technical solutions:
the generation management system for the 3D model comprises a material supply subsystem, a parameter management subsystem, a 3D model generation subsystem and a user intervention interface, wherein the material supply subsystem is used for collecting a 3D model printing index set, and the 3D model printing index set comprises a printing speed, a printing layer thickness, a printing area complexity, a 3D model surface smoothness and a printing material residual quantity; the 3D model generation subsystem is used for establishing a 3D feedback control model and adjusting printing indexes of the 3D model, and automatically generating and adjusting a support structure through a support structure generation algorithm; the user intervention interface is used for triggering a user intervention mechanism and notifying an operator to perform manual intervention; the material supply subsystem is connected with the parameter management subsystem, the parameter management subsystem is connected with the 3D model generation subsystem, and the 3D model generation subsystem is connected with the user intervention interface.
As a further scheme of the application, the 3D model generation subsystem comprises an intelligent feeding module, a material conveying belt, a multiple printing head, a heating module, a cooling module, a monitoring module, a control module and a post-processing module, wherein the monitoring module is connected with the control module, the control module is respectively connected with the post-processing module, the heating module and the cooling module are respectively connected with the intelligent feeding module, the intelligent feeding module is connected with the material conveying belt, and the material conveying belt is connected with the multiple printing head.
As a further scheme of the application, the intelligent feeding module builds a 3D model generation quality index evaluation model through integrating the printing speed, the printing layer thickness, the printing area complexity, the 3D model surface smoothness and the printing material residual quantity so as to evaluate the generation quality of the 3D model, wherein the formula of the 3D model generation quality index evaluation model is as follows:
；
wherein:generating quality index for 3D model, < >>For the printing speed +.>For printing layer thickness>For the complexity of the print area +.>For 3D model surface smoothness, +.>To the remaining amount of printing material.
As a further scheme of the application, the control module in the 3D model generation subsystem comprises a data processing unit, an anomaly detection unit, a parameter adjustment unit, a material management unit, a notification unit and a circulation unit, wherein the data processing unit is connected with the anomaly detection unit, the anomaly detection unit is connected with the parameter adjustment unit, the parameter adjustment unit is connected with the material management unit, the material management unit is connected with the notification unit, and the notification unit is connected with the circulation unit.
As a further scheme of the application, the parameter adjusting unit adjusts the printing index of the 3D model through the 3D feedback control model, and the construction steps of the 3D feedback control model are as follows:
step one, setting a printing evaluation index: setting a printing speed, a printing layer thickness, a printing area complexity, a 3D model surface smoothness and a printing material residual quantity;
step two, a 3D feedback control model is established: the control equation of the 3D feedback control model is:
；
；
wherein:is at->Input variable of time, ">For error signal, the setpoint +.>And output variable +.>Difference between->Is proportional gain->Is an integralGain (L)>For differential gain +.>For +.>The value of the inner-range is set,for a minute time interval, < >>Is the rate of change of the minute time interval;
step three, setting an adjustment strategy: an adjustment strategy is set based on the error signal and the printer is recalibrated.
As a further scheme of the present application, the third step sets an adjustment policy, and the specific steps of setting the adjustment policy according to the error signal are as follows:
step 1, for each output variable individualCalculate its error signal +.>；
Step 2, based on the error signalThe non-dominant layer is divided into a plurality of layers,
step 3, initializing the non-dominant layer number to 0, and for each output variable individualChecking whether there is an output variable individual +.>So that->I.e. the output variable individual is at time interval +.>The error in the input variable is greater than or equal to the output variable individualIs used for the error of (a),
step 4, when there is no output variable individualAt this time, the output variable is individual->Adding to the current non-dominant layer, and increasing the number of non-dominant layers by 1;
step 5, for each non-dominant layer, calculating its non-dominant solution level, i.e. the average error of all individuals in the layer;
and 6, carrying out rapid non-dominant sorting on the output variable individuals according to the non-dominant layer number, and adjusting parameters of the printer according to the sorting result so as to reduce error signals.
As a further scheme of the application, the material management unit controls the uniformity of the 3D model printing layer through a support structure generation algorithm, and the specific steps of the support structure generation algorithm are as follows:
step A1, geometric analysis of a target model: performing geometric analysis on the target model, wherein the geometric analysis comprises the steps of identifying a suspension part, a suspension edge, a detail area and a region to be supported of the target model;
step A2, a support structure generation strategy: determining the position, density, thickness, shape and connection mode of the support structure according to the geometric analysis;
step A3, creation of a supporting structure: determining the position of a supporting point through an automatic detection algorithm, and determining a supporting path and a connecting mode according to the position of the supporting point;
step A4, optimizing and adjusting: the optimization and adjustment are carried out according to the size of the suspended part of the target model, the printing speed, the model purpose, the property of the printing material and the use purpose of the supporting material.
The application provides a technical effect and advantages of a generation management system for a 3D model, which are as follows:
1. the application can ensure the uniformity of the printing layer, reduce the occurrence of weak parts by real-time monitoring and adjustment, and can reduce printing failure and waste generation by automatically adjusting printing parameters, thereby improving the resource utilization rate;
2. the application avoids printing interruption caused by uneven feeding or material clamping, can save time and labor cost, ensures the stability of the printing process, and reduces the risks of printing interruption and failure.
Drawings
FIG. 1 is a schematic diagram of a system for generating and managing 3D models according to the present application;
fig. 2 is a schematic structural diagram of a control module in the 3D model generating subsystem according to the present application.
Detailed Description
The technical solutions of the present embodiment will be clearly and completely described below with reference to the drawings in the embodiment of the present application, and it is apparent that the described embodiment is only a part of the embodiment of the present application, not all the embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Example 1. The generation management system for the 3D model comprises a material supply subsystem, a parameter management subsystem, a 3D model generation subsystem and a user intervention interface, wherein the material supply subsystem is used for collecting a 3D model printing index set, and the 3D model printing index set comprises a printing speed, a printing layer thickness, a printing area complexity, a 3D model surface smoothness and a printing material residual quantity; the 3D model generation subsystem is used for establishing a 3D feedback control model and adjusting printing indexes of the 3D model, and automatically generating and adjusting a support structure through a support structure generation algorithm; the user intervention interface is used for triggering a user intervention mechanism, and abnormal conditions and automatically adjusted information can be displayed on the user interface, so that a user can know the printing process in real time and can perform manual intervention when needed.
The material supply subsystem is connected with the parameter management subsystem, the parameter management subsystem is connected with the 3D model generation subsystem, and the 3D model generation subsystem is connected with the user intervention interface.
In the embodiment of the application, the 3D model generation subsystem comprises an intelligent feeding module, a material conveying belt, a multiple printing head, a heating module, a cooling module, a monitoring module, a control module and a post-processing module, wherein the monitoring module is connected with the control module, the control module is respectively connected with the post-processing module, the heating module and the cooling module are connected with the intelligent feeding module, the intelligent feeding module is connected with the material conveying belt, and the material conveying belt is connected with the multiple printing head.
The intelligent feeding module can monitor the feeding condition of materials in real time, is beneficial to preventing uneven feeding, and the material conveying belt can ensure that the materials are stably and uniformly conveyed to the printing head all the time, so that the problem of uneven feeding is reduced; multiple printheads use multiple printheads to increase printing speed while reducing the material feed rate required for each printhead, helping to mitigate the effects of uneven feed; the heating module melts or sinters the printing material; the cooling module is used to rapidly cool the material being printed to ensure that they solidify or fix between the layers; the monitoring module is provided with a temperature sensor, a pressure sensor, a position sensor and a speed sensor, and monitors various parameters in the printing process in real time; the control module establishes a 3D feedback control model and automatically adjusts printing parameters to adapt to the requirements of different areas and prevent the occurrence of weak areas; the post-treatment module is used to remove support structures, spray surface coatings, grind and paint to improve the quality and appearance of the model.
When the mobile phone shell is customized by using the 3D model, the model of the mobile phone shell is designed by using 3D modeling software on a computer, then a model file is sent to a 3D printer, after the model file is received by the 3D printer, the intelligent feeding module starts to work, and according to the requirement of the model file, the types and colors of materials are automatically adjusted, for example, hard plastics are needed for the main body part of the mobile phone shell, and soft rubber is needed for the logo part. After the intelligent feed module has adjusted the material, the material conveyor belt conveys the material to the multiple printheads. The multiple printing heads are used for superposing materials layer by layer according to parameters set by the model files to form the shape of the mobile phone shell, and in the process, the multiple printing heads are used for adjusting printing speed, printing layer thickness, printing area complexity, 3D model surface smoothness and printing material remaining quantity parameters according to instructions of the control module so as to ensure printing quality. During printing, the heating module heats the material to a molten state so that the printhead can stack the material layer upon layer. The cooling module cools the printed mobile phone shell in the printing process and after the printing is finished so as to ensure the stability of the shape and the structure of the mobile phone shell. The monitoring module is responsible for monitoring the whole printing process in real time, such as the temperature of the printing head, the consumption condition of the material and the printing progress, and when abnormal conditions occur, the monitoring module reports the abnormal conditions to the control module. The control module receives information from the monitoring module and analyzes the situation, when the printing parameters need to be adjusted, the control module sends instructions to the multiple printing heads, the heating module and the cooling module, and the control module feeds back the printing progress and the printing state to a user in real time. After printing, the post-processing module carries out subsequent processing on the printed mobile phone shell, including cleaning waste materials generated in the printing process, removing the supporting structure and polishing the surface, so as to improve the appearance and quality of the mobile phone shell.
Example 2. When customizing athletic shoes through 3D models, customers prepare the required raw materials, including vamp materials and sole materials, according to the needs after selecting the style, color and sole materials of the athletic shoes. After being ready, the material conveyor belt conveys the raw material to the multiple printheads. The multiple printing heads are used for superposing raw materials layer by layer according to the style and the color selected by a customer to form the shape of the customized sports shoe, and the printing heads adjust parameters according to the instruction of the control module in the process so as to ensure the printing quality. The heating module heats the material to a molten state so that the printing head can stack the material layer by layer, and the cooling module cools the printed customized sneaker in the printing process and after the printing is finished so as to ensure the stability of the shape and the structure of the customized sneaker. The monitoring module monitors the whole printing process in real time, including the temperature of the printing head, the consumption condition of materials and the printing progress, and when abnormal conditions are found, the monitoring module immediately reports to the control module. The control module receives the information of the monitoring module, analyzes the situation, and sends instructions to the multiple printing heads, the heating module and the cooling module when the printing parameters need to be adjusted, and feeds the printing progress and the printing state back to the user in real time. After printing, the post-processing module performs subsequent processing on the printed customized sneakers, including cleaning waste materials generated in the printing process, polishing the surface and removing the supporting structure, so as to improve the appearance and quality of the sneakers. After receiving the customized sports shoes, the customer selects whether to further carry out surface treatment or other personalized treatments according to the requirements of the customer.
In the embodiment of the application, an intelligent feeding module constructs a 3D model generation quality index evaluation model through integrating printing speed, printing layer thickness, printing area complexity, 3D model surface smoothness and printing material remaining amount so as to evaluate the generation quality of the 3D model, wherein the formula of the 3D model generation quality index evaluation model is as follows:
；
wherein:generating quality index for 3D model, < >>For the printing speed +.>For printing layer thickness>For the complexity of the print area +.>For 3D model surface smoothness, +.>To the remaining amount of printing material.
By constructing a mathematical model, the generation quality of the 3D model can be converted into a specific quantization index, so that the generation quality of different models can be conveniently compared and evaluated, and a basis is provided for optimizing the printing process and improving the printing quality. The influence degree of different printing parameters on the generation quality can be analyzed through the evaluation model, the parameters can be conveniently and pertinently adjusted in the printing process, the purpose of improving the generation quality is achieved, and the possible quality problems can be found in advance, so that preventive measures are taken, and the risk of failed printing is reduced.
In the embodiment of the application, a control module in the 3D model generation subsystem comprises a data processing unit, an abnormality detection unit, a parameter adjustment unit, a material management unit, a notification unit and a circulation unit, wherein the data processing unit is connected with the abnormality detection unit, the abnormality detection unit is connected with the parameter adjustment unit, the parameter adjustment unit is connected with the material management unit, the material management unit is connected with the notification unit, and the notification unit is connected with the circulation unit.
Example 3. When a 3D model is created and it is desired to be able to print it out using a 3D printer, for this purpose, the operator uploads the 3D model file to the 3D model generation subsystem, the data processing unit first parses the model file, extracting information about the model size, material and printing parameters therein; the abnormality detection unit performs preliminary analysis on the extracted information, and checks whether an abnormality exists, including damage to the model file and incorrect setting of printing parameters; and according to the 3D feedback control model and the set printing evaluation index, the parameter adjusting unit automatically adjusts relevant parameters of the printer so as to ensure that the printed model meets the quality requirement. The material management unit is used for managing printing materials in the printer, and before printing, the material management unit can automatically select proper printing materials according to the requirements of the model file and load the materials into the printer; the notification unit reports the state of the printer to an operator in real time in the printing process, wherein the state comprises the printing progress and the residual material information, and when an abnormality occurs in the printing process, the notification unit immediately notifies the operator to process; the circulation unit is used for controlling the whole printing process, and after all the printing tasks are completed, the circulation unit informs an operator that printing is completed and starts to carry out the next printing task.
In the embodiment of the application, the parameter adjusting unit adjusts the printing index of the 3D model through the 3D feedback control model, and the construction steps of the 3D feedback control model are as follows:
step one, setting a printing evaluation index: setting a 3D model printing index set for evaluation, wherein the set comprises printing speed, printing layer thickness, printing area complexity, 3D model surface smoothness and printing material residual quantity;
step two, a 3D feedback control model is established: the control equation of the 3D feedback control model is:
；
；
wherein:is at->Input variable of time, ">For error signal, the setpoint +.>And output variable +.>Difference between->Is proportional gain->For integral gain +.>For differential gain +.>For +.>The value of the inner-range is set,for a minute time interval, < >>Is the rate of change of the minute time interval;
step three, setting an adjustment strategy: an adjustment strategy is set based on the error signal and the printer is recalibrated.
The operator sets an index set for evaluating the printing quality of the 3D model, including printing speed, printing layer thickness, printing area complexity, 3D model surface smoothness and printing material residual quantity; constructing a 3D feedback control model, and monitoring differences in the printing process in real time by calculating an error signal, wherein the input variable of the model is the error signalThe signal indicates the setpoint +.>And the actual output variable +.>Differences between; calculating a control output by using a control equation according to the error signal by the 3D feedback control model; setting an adjustment strategy according to an error signal by the model, and determining the adjustment direction and the amplitude of the parameter according to the real-time error signal; the control output is applied to the 3D printer through the control module, and the parameters of the printer are calibrated to enable the actual printing index to approach the expected value, and the actual printing index is continuously monitoredThe error signal is adjusted, so that the printing quality, efficiency and consistency are improved. The 3D feedback control model monitors parameters of the printing process in real time, including printing speed, printing layer thickness, printing area complexity, surface smoothness and printing material residual quantity, so that problems and anomalies can be found timely; by calculating the error signal, whether the printing parameters need to be adjusted in the printing process can be determined, and the problems in the printing process can be found and corrected in time, so that the generation quality of the 3D model is improved. Defects and non-uniformity caused by inaccurate parameters are reduced.
In the embodiment of the application, the third step sets the adjustment strategy, and the specific steps of setting the adjustment strategy according to the error signal are as follows:
step 1, for each output variable individualCalculate its error signal +.>；
Step 2, based on the error signalThe non-dominant layer is divided into a plurality of layers,
step 3, initializing the non-dominant layer number to 0, and for each output variable individualChecking whether there is an output variable individual +.>So that->I.e. the output variable individual is at time interval +.>The error in the input variable is greater than or equal to the output variable individualIs used for the error of (a),
step 4, when there is no output variable individualAt this time, the output variable is individual->Adding to the current non-dominant layer, and increasing the number of non-dominant layers by 1;
step 5, for each non-dominant layer, calculating its non-dominant solution level, i.e. the average error of all individuals in the layer;
and 6, carrying out rapid non-dominant sorting on the output variable individuals according to the non-dominant layer number, and adjusting parameters of the printer according to the sorting result so as to reduce error signals.
The adjustment strategy is used for optimizing the printing quality and efficiency of the 3D model, improving the self-adaptability of the system, ensuring that the printed 3D model meets the design requirement, and timely adjusting the printing parameters according to the error signal, so that the output variable in the printing process is close to or meets the expected value, thereby being beneficial to reducing the defects in manufacturing and improving the printing quality. By means of real-time monitoring and adjustment, printing resources are effectively utilized, unnecessary pauses and waste in the printing process are reduced, printing efficiency is improved, and printing failure caused by improper parameter setting is avoided.
In the embodiment of the application, the material management unit controls the uniformity of the 3D model printing layer through a support structure generation algorithm, and the specific steps of the support structure generation algorithm are as follows:
step A1, geometric analysis of a target model: performing geometric analysis on the target model, wherein the geometric analysis comprises the steps of identifying a suspension part, a suspension edge, a detail area and a region to be supported of the target model;
step A2, a support structure generation strategy: determining the position, density, thickness, shape and connection mode of the support structure according to the geometric analysis;
step A3, creation of a supporting structure: determining the position of a supporting point through an automatic detection algorithm, and determining a supporting path and a connecting mode according to the position of the supporting point;
step A4, optimizing and adjusting: the optimization and adjustment are carried out according to the size of the suspended part of the target model, the printing speed, the model purpose, the property of the printing material and the use purpose of the supporting material.
The support structure generation algorithm can help to generate a proper support structure, so that the success rate of printing of the 3D model is improved, printing failure caused by factors of suspended parts is reduced, stability in the printing process is guaranteed, problems of model deformation, warping and the like are reduced, printing quality is improved, a proper support structure is generated according to the characteristics of a target model, unnecessary material waste is reduced, printing cost is reduced, the success rate and quality of printing of the 3D model are improved, material waste is reduced, printing time is shortened, various printing scenes are adapted, and the intelligent level of a system is improved.
According to the embodiment of the application, the 3D feedback control model is built, the printing index of the 3D model is adjusted, the adjustment strategy is set according to the error signal obtained by the 3D feedback control model so as to adapt to the requirements of different areas, the supporting structure is automatically generated and adjusted through the supporting structure generation algorithm, the occurrence of weak parts can be reduced through real-time monitoring and adjustment, the printing parameters can be automatically adjusted so as to reduce the printing failure and the waste, the resource utilization rate is improved, the printing interruption caused by uneven feeding or material clamping is avoided, the time and labor cost are saved, the stability of the printing process is ensured, and the risks of the printing interruption and the printing failure are reduced.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Finally: the foregoing description of the preferred embodiments of the application is not intended to limit the application to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the application are intended to be included within the scope of the application.

Claims (6)

1. The generation management system for the 3D model comprises a material supply subsystem, a parameter management subsystem, a 3D model generation subsystem and a user intervention interface, and is characterized in that the material supply subsystem is connected with the parameter management subsystem, the parameter management subsystem is connected with the 3D model generation subsystem, and the 3D model generation subsystem is connected with the user intervention interface;
the material supply subsystem is used for collecting a 3D model printing index set, wherein the 3D model printing index set comprises printing speed, printing layer thickness, printing area complexity, 3D model surface smoothness and printing material residual quantity;
the 3D model generation subsystem is used for establishing a 3D feedback control model and adjusting 3D model printing indexes, and automatically generates and adjusts a supporting structure through a supporting structure generation algorithm, the 3D model generation subsystem comprises an intelligent feeding module, and the intelligent feeding module is used for constructing a 3D model generation quality index evaluation model through comprehensive printing speed, printing layer thickness, printing area complexity, 3D model surface smoothness and printing material surplus so as to evaluate the generation quality of the 3D model, wherein the formula of the 3D model generation quality index evaluation model is as follows:
；
wherein:generating quality index for 3D model, < >>For the printing speed +.>For printing layer thickness>For the complexity of the print area +.>For 3D model surface smoothness, +.>A remaining amount of printing material;
the user intervention interface is used for triggering a user intervention mechanism and notifying an operator to perform manual intervention.
2. The system of claim 1, wherein the 3D model generation subsystem further comprises a material conveyor belt, a multiple print head, a heating module, a cooling module, a monitoring module, a control module, and a post-processing module, the monitoring module is connected to the control module, the control module is connected to the post-processing module, the heating module, and the cooling module are respectively connected to the intelligent feed module, the intelligent feed module is connected to the material conveyor belt, and the material conveyor belt is connected to the multiple print head.
3. The system according to claim 1, wherein the control module in the 3D model generation subsystem includes a data processing unit, an abnormality detection unit, a parameter adjustment unit, a material management unit, a notification unit, and a circulation unit, the data processing unit is connected to the abnormality detection unit, the abnormality detection unit is connected to the parameter adjustment unit, the parameter adjustment unit is connected to the material management unit, the material management unit is connected to the notification unit, and the notification unit is connected to the circulation unit.
4. A generation management system for a 3D model according to claim 3, wherein the parameter adjustment unit adjusts the 3D model print index through a 3D feedback control model, and the 3D feedback control model is constructed by:
step one, setting a printing evaluation index: setting a printing speed, a printing layer thickness, a printing area complexity, a 3D model surface smoothness and a printing material residual quantity;
step two, a 3D feedback control model is established: the control equation of the 3D feedback control model is:
；
；
wherein:is at->Input variable of time, ">For error signal, the setpoint +.>And output variable +.>Difference between->Is proportional gain->For integral gain +.>For differential gain +.>For +.>Values in>For a minute time interval, < >>Is the rate of change of the minute time interval;
step three, setting an adjustment strategy: an adjustment strategy is set based on the error signal and the printer is recalibrated.
5. The system for generating and managing a 3D model according to claim 4, wherein the step three sets an adjustment policy, and the specific steps of setting the adjustment policy according to the error signal are as follows:
step 1, for each output variable individualCalculate its error signal +.>；
Step 2, based on the error signalThe non-dominant layer is divided into a plurality of layers,
step 3, initializing the non-dominant layer number to 0, and for each output variable individualChecking whether there is an output variable individualSo that->I.e. the time of the output variable individualInterval->The error in the output variable is greater than or equal to the individual +.>Is used for the error of (a),
step 4, when there is no output variable individualAt this time, the output variable is individual->Adding to the current non-dominant layer, and increasing the number of non-dominant layers by 1;
step 5, for each non-dominant layer, calculating its non-dominant solution level, i.e. the average error of all individuals in the layer;
and 6, carrying out rapid non-dominant sorting on the output variable individuals according to the non-dominant layer number, and adjusting parameters of the printer according to the sorting result so as to reduce error signals.
6. A generation management system for a 3D model according to claim 3, wherein the material management unit controls the uniformity of the 3D model print layer by a support structure generation algorithm, the specific steps of the support structure generation algorithm are:
step A1, geometric analysis of a target model: performing geometric analysis on the target model, wherein the geometric analysis comprises the steps of identifying a suspension part, a suspension edge, a detail area and a region to be supported of the target model;
step A2, a support structure generation strategy: determining the position, density, thickness, shape and connection mode of the support structure according to the geometric analysis;
step A3, creation of a supporting structure: determining the position of a supporting point through an automatic detection algorithm, and determining a supporting path and a connecting mode according to the position of the supporting point;
step A4, optimizing and adjusting: the optimization and adjustment are carried out according to the size of the suspended part of the target model, the printing speed, the model purpose, the property of the printing material and the use purpose of the supporting material.
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Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190086899A1 (en) * 2017-09-21 2019-03-21 Hangzhou Regenovo Biotechnology Co., Ltd. On-line Monitoring Method and System for Three-dimensional Printing
CN113320143A (en) * 2021-06-29 2021-08-31 华中科技大学 Continuous 3D printing method and quality evaluation method of polymer continuous fiber composite layer
US20210325848A1 (en) * 2018-08-09 2021-10-21 The Research Foundation For The State University Of New York Method for automated 3d print quality assessment and redesign
CN114379079A (en) * 2022-01-14 2022-04-22 杭州捷诺飞生物科技股份有限公司 Control method and device for 3D printing and electronic equipment
CN115958792A (en) * 2022-12-06 2023-04-14 深圳市智能派科技有限公司 Printing quality analysis method and system of 3D printer
US20230194445A1 (en) * 2017-06-28 2023-06-22 University Of Maryland College Park System and method for in-situ x-ray diffraction-based real-time monitoring of microstructure properties of printing objects
CN116628810A (en) * 2023-05-23 2023-08-22 中国建筑第八工程局有限公司 Unmanned building 3D printing construction method and system
CN116749518A (en) * 2023-08-21 2023-09-15 珠海本色成型成像材料研究院有限公司 Printing and forming management system for 3D model

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20230194445A1 (en) * 2017-06-28 2023-06-22 University Of Maryland College Park System and method for in-situ x-ray diffraction-based real-time monitoring of microstructure properties of printing objects
US20190086899A1 (en) * 2017-09-21 2019-03-21 Hangzhou Regenovo Biotechnology Co., Ltd. On-line Monitoring Method and System for Three-dimensional Printing
US20210325848A1 (en) * 2018-08-09 2021-10-21 The Research Foundation For The State University Of New York Method for automated 3d print quality assessment and redesign
CN113320143A (en) * 2021-06-29 2021-08-31 华中科技大学 Continuous 3D printing method and quality evaluation method of polymer continuous fiber composite layer
CN114379079A (en) * 2022-01-14 2022-04-22 杭州捷诺飞生物科技股份有限公司 Control method and device for 3D printing and electronic equipment
CN115958792A (en) * 2022-12-06 2023-04-14 深圳市智能派科技有限公司 Printing quality analysis method and system of 3D printer
CN116628810A (en) * 2023-05-23 2023-08-22 中国建筑第八工程局有限公司 Unmanned building 3D printing construction method and system
CN116749518A (en) * 2023-08-21 2023-09-15 珠海本色成型成像材料研究院有限公司 Printing and forming management system for 3D model

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
吕福顺 等: "PEEK的3D打印参数优化及铣削试验研究", 《组合机床与自动化加工技术》, pages 43 - 45 *

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