A data processing method and system for a 3D printer

Abstract

The present disclosure relates to a data processing method and system for a 3D printer, and relates to the technical field of data processing. The historical printing data of the 3D printer is processed and applied. The historical printing data of the 3D printer is obtained, the key printing data with analysis significance is determined, the printing performance of the 3D printer is evaluated based on the key printing data, and the printing reference information is generated based on the performance evaluation data. This data processing method can not only evaluate the performance of the 3D printer, but also generate the printing reference information through the integration and analysis of the key printing data of the 3D printer. The printing reference information can assist the 3D printing user to better use the 3D printer, and thus, the effective analysis and application of the historical printing data of the 3D printer are realized, and the use difficulty of the 3D printer is reduced.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of data processing, in particular, to a data processing method and system for a 3D printer. BACKGROUND

[0002] With the development of printing technology, 3D printing technology has also developed, and the application of 3D printers is becoming more and more widespread. A 3D printer, also known as an additive manufacturing device, works by converting a digital model file into a physical object. In the context of a 3D printing field, multiple printing processes are involved, such as digital model design, slicing processing, printing preparation, layer-by-layer construction, and post-processing.

[0003] Currently, data processing for a 3D printer is usually integrated into the printing process of the 3D printer, for example, into the digital model design process to assist in the design of a digital model. SUMMARY

[0004] The purpose of the present disclosure is to provide a data processing method and system for a 3D printer, which can evaluate the performance of a 3D printer, effectively analyze and apply historical printing data of a 3D printer, and reduce the difficulty of using a 3D printer.

[0005] To achieve the above purpose, in a first aspect, the present disclosure provides a data processing method for a 3D printer, comprising: obtaining historical printing data of a 3D printer, the historical printing data comprising printing data corresponding to a plurality of printing products respectively, and the printing data corresponding to each printing product comprising data corresponding to a plurality of printing stages respectively; determining key printing data from the historical printing data that satisfies a pre-set key printing data condition, the key printing data comprising key printing data corresponding to a plurality of key printing products respectively, and each key printing data comprising key data corresponding to a plurality of printing stages respectively; evaluating the printing performance of the 3D printer according to the key printing data to obtain performance evaluation data; and generating printing reference information of the 3D printer according to the performance evaluation data, the printing reference information comprising printing reference information corresponding to the plurality of printing stages respectively.

[0006] Optionally, the preset key print data condition comprises at least one of the following: a print product condition required to be met by the key print data, the print product condition comprising a type condition of the print product and a print quantity condition of the print product; a print data feature condition required to be met by the key print data, the print data feature condition comprising a plurality of data feature conditions corresponding to a plurality of print stages respectively, the data feature condition comprising a data complexity condition and a data rarity condition; and a quantity condition required to be met by the key print data, the quantity condition comprising a total quantity condition and a quantity condition corresponding to a plurality of print stages respectively.

[0007] Optionally, the performance evaluation data is obtained by evaluating the print performance of the 3D printer according to the key print data, comprising: determining abnormal print data corresponding to the plurality of key print products respectively according to the key print data corresponding to the plurality of key print products respectively and a pre-trained abnormal detection model, wherein the pre-trained abnormal detection model is used to output abnormal print data according to input key print product identification and key print data having a corresponding relationship; and evaluating the print performance of the 3D printer according to the abnormal print data corresponding to the plurality of key print products respectively and the key print data to obtain the performance evaluation data.

[0008] Optionally, the data processing method further comprises: obtaining a training data set, the training data set comprising a plurality of training samples, each training sample comprising a sample print product identification and sample print data, wherein the sample print data is provided with an abnormal print data label, the sample print data comprises sample print data corresponding to a plurality of print stages respectively, and the sample print data corresponding to different print stages is determined by different abnormal data detection algorithms to obtain an abnormal print data label; and training the abnormal detection model to be trained according to the training data set to obtain the pre-trained abnormal detection model.

[0009] Optionally, the performance evaluation data is obtained by evaluating the print performance of the 3D printer according to the key print data, comprising: determining a first data proportion of the abnormal print data corresponding to the plurality of key print products respectively compared with the key print data; determining a second data proportion of the key print data compared with the historical print data; determining a print performance evaluation value range according to the first data proportion and the second data proportion; obtaining a preset print performance evaluation value, the preset print performance evaluation value being a print performance evaluation value calibrated by a user; and determining performance evaluation data according to the print performance evaluation value range and the preset print performance evaluation value, the performance evaluation data being used to represent a change of the print performance evaluation value.

[0010] Optionally, the generating the printing reference information of the 3D printer according to the performance evaluation data comprises: obtaining preset printing reference information corresponding to the plurality of printing stages respectively; determining an adjustment strategy of the preset printing reference information corresponding to the plurality of printing stages respectively according to the performance evaluation data, the adjustment strategy comprising at least one of an information adding and deleting strategy, an information labeling strategy and an information association strategy; and adjusting the preset printing reference information corresponding to the plurality of printing stages respectively according to the adjustment strategy to obtain the printing reference information of the 3D printer.

[0011] Optionally, the performance evaluation data is used to represent a change of a printing performance evaluation value, and the determining the adjustment strategy of the preset printing reference information corresponding to the plurality of printing stages respectively according to the performance evaluation data comprises: if the change of the printing performance evaluation value represented by the performance evaluation data is that the printing performance evaluation value presents an unchanged trend, determining the adjustment strategy of the preset printing reference information corresponding to the plurality of printing stages respectively according to an average printing performance evaluation value of the performance evaluation data; if the change of the printing performance evaluation value represented by the performance evaluation data is that the printing performance evaluation value presents a downward trend, determining the adjustment strategy of the preset printing reference information corresponding to the plurality of printing stages respectively according to a lowest printing performance evaluation value in the performance evaluation data; and if the change of the printing performance evaluation value represented by the performance evaluation data is that the printing performance evaluation value presents an upward trend, determining the adjustment strategy of the preset printing reference information corresponding to the plurality of printing stages respectively according to a highest printing performance evaluation value in the performance evaluation data.

[0012] Optionally, the data processing method further comprises: sending the printing reference information to the 3D printer, so that the 3D printer displays the printing reference information to a 3D printing user; obtaining feedback information sent by the 3D printer, the feedback information comprising a content adjustment requirement of the 3D printing user for the printing reference information; updating the printing reference information of the 3D printer according to the content adjustment requirement, and sending the updated printing reference information to the 3D printer.

[0013] Optionally, the data processing method further comprises: determining target printing data related to a printing product quality from the historical printing data; and evaluating a printing effect of the plurality of printing products according to the target printing data to obtain printing effect evaluation data. Correspondingly, the evaluating the printing performance of the 3D printer according to the key printing data to obtain performance evaluation data comprises: evaluating the printing performance of the 3D printer according to the key printing data and the printing effect evaluation data to obtain performance evaluation data.

[0014] In a second aspect, the present disclosure provides a data processing system for a 3D printer, comprising: a 3D printer; a data processing device, which is communicatively connected with the 3D printer; wherein the 3D printer is configured to report printing data to the data processing device after each time of completing 3D printing, and the data processing device is configured to execute the data processing method for the 3D printer as described in the first aspect.

[0015] By the above technical solution, the historical printing data of the 3D printer is processed and applied, the historical printing data of the 3D printer is obtained, the key printing data with analysis significance is determined therefrom, the printing performance of the 3D printer is evaluated based on the key printing data, and the printing reference information is generated based on the performance evaluation data. This data processing manner can not only evaluate the performance of the 3D printer, but also generate the printing reference information through the integrated analysis of the key printing data of the 3D printer, which can assist the 3D printing user to better use the 3D printer, and thus, the effective analysis and application of the historical printing data of the 3D printer are realized, and the use difficulty of the 3D printer is reduced. Therefore, the technical solution can realize the performance evaluation of the 3D printer, the effective analysis and application of the historical printing data of the 3D printer, and the reduction of the use difficulty of the 3D printer.

[0016] Other features and advantages of the present disclosure will be described in detail in the following detailed description. BRIEF DESCRIPTION OF DRAWINGS

[0017] The accompanying drawings are included to provide a further understanding of the present disclosure and constitute a part of the specification, which together with the detailed description, serve to explain the present disclosure. In the drawings:

[0018] Figure 1 FIG. 1 is a structural block diagram of a data processing system for a 3D printer according to an exemplary embodiment.

[0019] Figure 2 FIG. 2 is a flow chart of a data processing method for a 3D printer according to an exemplary embodiment.

[0020] Figure 3 FIG. 3 is a comparison schematic diagram of historical printing data and key printing data according to an exemplary embodiment.

[0021] Figure 4 FIG. 4 is an example diagram of performance evaluation data according to an exemplary embodiment.

[0022] Figure 5 FIG. 5 is a structural block diagram of a data processing device for a 3D printer according to an exemplary embodiment.

[0023] Figure 6 is a block diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0024] The specific embodiments of the present disclosure will be described below in detail with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely intended to illustrate and explain the present disclosure, and are not intended to limit the present disclosure.

[0025] With the development of printing technology, 3D printing technology has also developed, and 3D printers have been increasingly widely used. A 3D printer, also known as an additive manufacturing device, works by converting a digital model file into a physical object. In a 3D printing field, multiple printing processes are involved, such as digital model design, slicing processing, printing preparation, layer-by-layer construction, and post-processing.

[0026] Currently, data processing of a 3D printer is usually integrated into a printing process of the 3D printer, for example, into a digital model design process, to assist in the design of a digital model.

[0027] However, in an actual 3D printing field, in addition to the demand for integrating data processing into a specific printing process, there is also a demand for applying data processing before and after the printing process. Currently, there is a lack of related data processing processes before and after the printing process, so that this type of processing demand cannot be met.

[0028] Based on this, the embodiments of the present disclosure provide a technical solution that processes and applies historical printing data of a 3D printer. By obtaining historical printing data of a 3D printer, key printing data with analytical significance is determined, and the printing performance of the 3D printer is evaluated based on the key printing data. Further, printing reference information is generated based on the performance evaluation data.

[0029] This data processing method not only can evaluate the performance of a 3D printer, but also can generate printing reference information through the integration and analysis of key printing data of a 3D printer. The printing reference information can assist 3D printing users to better use a 3D printer, and thus, the effective analysis and application of historical printing data of a 3D printer can be achieved, and the difficulty of using a 3D printer can be reduced.

[0030] Therefore, the technical solution of the embodiments of the present disclosure can be applied before and after a 3D printing process, and thus can be applied to analyze, process, and apply data of various 3D printers.

[0031] In order to facilitate understanding of the technical solution of the embodiments of the present disclosure, a brief printing process of a 3D printer will be introduced.

[0032] In the printing process of a 3D printer, the following printing steps (phases) are usually involved:

[0033] Digital model design: Use computer-aided design software to create a three-dimensional model. The model can be designed by the user himself or downloaded from an online database.

[0034] Slicing: Import the three-dimensional model file into slicing software. The slicing software will decompose the model into a series of thin layers (usually 0.1mm to 0.3mm thick) and generate path information for each layer, which will be converted into G-code or other printer-understandable instruction sets.

[0035] Printing preparation: According to the size of the model and the printing material, set the printer parameters such as layer height, filling density, printing speed, temperature, etc. Preheat the printer, especially the print head and print bed, to ensure that the material can be properly melted and solidified.

[0036] Material extrusion: The print head of the 3D printer is equipped with materials such as plastic filaments, resins, metal powders, etc. The print head moves on the print bed according to the path generated by the slicing software, while extruding the material.

[0037] Layer-by-layer construction: The print head extrudes material layer by layer on the print bed, and each layer of material solidifies on the print bed to form a solid object. After each layer is completed, the print bed is lowered by a layer height of thickness, and the print head continues to extrude material on the new layer.

[0038] Support structure: For overhanging parts in the model, the printer will first print a support structure to support these parts. After printing is completed, the support structure usually needs to be manually removed.

[0039] Printing completion: Once all layers have been printed, the printer stops working. The printed object needs to be cooled down and then removed from the print bed.

[0040] Post-processing: According to needs, polish, color, and apply protective layers to the printed object to improve its appearance and durability.

[0041] Each of the above printing steps can be considered as a printing phase.

[0042] For a 3D printer, it usually has its own data processing module, which can realize the processing of related data of 3D printing, and can also realize the recording of related data, such as the data recording of each printing phase (step).

[0043] For example, when processing data, a 3D printer usually involves the following data:

[0044] Three-dimensional model data: STL (Stereolithography) file: This is the most common 3D printing file format, containing surface geometry information of the model. OBJ (Wavefront Object) file: Another commonly used 3D model file format, which can contain geometry data and material information of the model. FBX (Filmbox) file: A 3D file format developed by Autodesk, supporting complex model data and animation. 3MF (3D Manufacturing Format) file: A newer file format aimed at becoming a universal format for 3D printing, supporting multiple materials and colors.

[0045] Data generated by slicing software: G-code: A widely used instruction set generated by slicing software, used to guide the movement of the 3D printer's print head and material extrusion.

[0046] Path planning: Slicing software decomposes three-dimensional models into multiple two-dimensional slices and generates print paths for each layer.

[0047] Printing parameters: Layer height: The height of each layer printed. Filling density: The filling degree of the internal structure. Printing speed: The speed of the print head movement. Temperature settings: The temperature of the printing material and the print bed. Support structure: For overhanging parts, support structures need to be generated to ensure the stability of the print.

[0048] Material data: Material type: such as nylon, metal, resin, etc. Material properties: including melting point, shrinkage, strength, toughness, etc.

[0049] Printer hardware parameters: Print head size: The diameter of the print head. Print bed size: The size limit of the print bed. Printing resolution: The smallest detail size that the printer can achieve.

[0050] Monitoring data: Temperature monitoring: Real-time monitoring of the temperature of the print head and the print bed. Print speed monitoring: Monitoring the movement speed of the print head. Material consumption monitoring: Monitoring the use of materials.

[0051] User interface interaction data: User input instructions and settings through the user interface of the 3D printer. User monitoring and control of the printing process.

[0052] Software and firmware: Slicing software: Software that converts three-dimensional models into G-code. Printer firmware: Software that controls the operation of the printer hardware.

[0053] Network and cloud service data: For 3D printers connected to the network, it may involve receiving model data, monitoring print status, remote control, etc. through the network.

[0054] Post-processing data: data that may need to be performed after printing, such as removal of support structures, surface polishing, coloring, etc.

[0055] The above various data can have a correlation relationship with the corresponding printing stages as described above, for example: the digital modeling stage involves three-dimensional model writing; the post-processing stage involves post-processing data, etc. Thus, for each printing stage, there is a corresponding data, and these data can be integrated to form printing data.

[0056] In order to realize the processing of data before and after the printing process, the third party device can realize the corresponding data processing function.

[0057] Figure 1 is a structural block diagram of a data processing system for a 3D printer according to an example embodiment, as shown in Figure 1 The data processing system includes a 3D printer and a data processing device in communication with the 3D printer.

[0058] Among them, the 3D printer and the data processing device can adopt wired connection, wireless connection and Bluetooth connection and other communication connection modes, which are not limited here.

[0059] In some embodiments, the data processing device can be connected to multiple 3D printers at the same time and perform data processing on multiple 3D printers respectively, which is not limited here.

[0060] In some embodiments, the data processing device can be various electronic devices, such as computers, etc.

[0061] In this system, the 3D printer reports the printing data to the data processing device after completing the 3D printing each time, and the data processing device is used to process the printing data. Thus, the present disclosure provides a data processing scheme that can be applied to the data processing device to realize data processing for the 3D printer.

[0062] Figure 2 is a flow chart of a data processing method for a 3D printer according to an example embodiment, as shown in Figure 2 The data processing method includes the following steps:

[0063] Step S21, obtaining the historical printing data of the 3D printer, the historical printing data including printing data corresponding to a plurality of printing products respectively, and the printing data corresponding to each printing product including data corresponding to a plurality of printing stages respectively.

[0064] In step S22, key printing data satisfying a preset key printing data condition is determined from the historical printing data, the key printing data including key printing data corresponding to each of a plurality of key printing products, and each key printing data including key data corresponding to each of a plurality of printing stages.

[0065] In step S23, the printing performance of the 3D printer is evaluated according to the key printing data, and performance evaluation data is obtained.

[0066] In step S24, printing reference information of the 3D printer is generated according to the performance evaluation data, and the printing reference information includes printing reference information corresponding to each of a plurality of printing stages.

[0067] In step S21, since the 3D printer uploads relevant data to the data processing device after each printing is completed, the data processing device can store these data. Then, after storing a sufficient amount of data, data processing can be performed.

[0068] Therefore, the historical printing data can be printing data reported by the 3D printer within a preset time period, or the amount of data of the historical printing data can satisfy a basic data processing amount. For example, the historical printing data includes printing data corresponding to a plurality of printing products involved in 10 times of printing; for another example, according to the usage frequency of the 3D printer, it is set to perform data processing once every week, and the historical printing data is the printing data within one week, etc.

[0069] In the historical printing data, printing data corresponding to a plurality of printing products is included, and the plurality of printing products can be the same printing product or different printing products. If they are the same printing product, their printing data can be the same or different.

[0070] Therefore, the printing data corresponding to each printing product can be distinguished according to the reporting time, or the storage time of the data processing device, etc.

[0071] As for the data corresponding to each of a plurality of printing stages, it can involve all the printing stages of the foregoing embodiments, or only involve some stages with data analysis value. For example, the plurality of printing stages can include a data modeling stage, a printing preparation stage, and a formal printing stage. In the data modeling stage, three-dimensional modeling related data such as a three-dimensional model can be involved; in the printing preparation stage, printing parameters, hardware parameters, and material data, etc. can be involved; in the formal printing stage, printer hardware parameters and user instructions, etc. can be involved. In different application scenarios, data required to be processed by the data printing device can be configured according to actual data analysis requirements, which is not limited herein.

[0072] If all the historical printing data are processed, the efficiency is low and resources are wasted. Therefore, in step S22, the historical printing data are preprocessed to determine key printing data, which can be considered as data with data analysis significance. Accordingly, the key printing data involves key printing data corresponding to a plurality of key printing products respectively, and each key printing data includes key data corresponding to a plurality of printing stages respectively.

[0073] The preset key printing data condition can be used to determine the key printing data with data analysis value.

[0074] As an optional implementation, the preset key printing data condition includes at least one of the following: a printing product condition that needs to be met by the key printing data, the printing product condition including a type condition of the printing product and a printing frequency condition of the printing product; a printing data feature condition that needs to be met by the key printing data, the printing data feature condition including a data feature condition corresponding to a plurality of printing stages respectively, the data feature condition including a data complexity condition and a data rarity condition; and a quantity condition that needs to be met by the key printing data, the quantity condition including a total quantity condition and a quantity condition corresponding to a plurality of printing stages respectively.

[0075] In some embodiments, the type condition of the printing product may, for example, be that the printing product is a printing product type with high printing complexity, which involves materials, slicing, etc., that are more special than other printing products. According to the actual application scenario, a specific type can be limited in the type condition, which can be one or more, which is not limited here.

[0076] In some embodiments, the printing frequency of the printing product can not be limited to the printing frequency of the current 3D printer, but a comprehensive printing frequency obtained by statistical analysis of the 3D printer printing situation in the market. The printing frequency condition of the printing product can limit the threshold of the printing frequency, which can include a minimum value and a maximum value. If the printing frequency is lower than the minimum value or higher than the maximum value, it is considered to meet the printing frequency condition.

[0077] Therefore, the related information of the printing product can be obtained and compared with the printing product condition to determine whether the printing product condition is met.

[0078] In some embodiments, the data complexity and the data rarity can be determined by conventional data analysis algorithms in the art. For example, the data complexity is determined based on the data types involved and the data volume, etc. The more data types and / or data volume involved, the higher the data complexity. The data rarity is determined based on the similarity to other data. The lower the similarity, the higher the data rarity, which is not limited herein. Wherein, for the same printing product, the similarity between different printing data can be compared to determine the data rarity.

[0079] Regarding the data complexity condition and the data rarity condition, a complexity threshold and a rarity threshold can be involved respectively, which can represent a higher complexity and a higher rarity respectively.

[0080] Regarding the quantity condition, a total quantity condition and a plurality of printing stage quantity conditions are involved, which limit the total quantity of key printing data and the quantity of each printing stage respectively. Wherein, according to the importance of different printing stages, the corresponding data quantity can be different, for example: the data quantity of the three-dimensional modeling stage is higher than that of the post-printing processing stage.

[0081] Regarding the specific data quantity limit value, it can be set in combination with different application scenarios, for example, according to the analysis accuracy of the application scenario for data, the higher the required analysis accuracy, the more data quantity is needed.

[0082] Therefore, according to the quantity condition, data selection can be performed to determine the key printing data.

[0083] Further, the key printing data is equivalent to the specific printing data selected from the historical printing data.

[0084] It can be understood that the key printing data condition can be flexibly configured according to the application scenario, and is not limited to the condition proposed in the embodiments of the present disclosure.

[0085] Figure 3 is a comparison diagram of historical printing data and key printing data according to an exemplary embodiment, as Figure 3 As shown, the historical printing data involves the printing data of 10 printing products at each printing stage. Through the screening of the key printing data condition, the printing data of 5 printing products at each printing stage can be obtained.

[0086] In step S23, the printing performance of the 3D printer is evaluated according to the key printing data, and performance evaluation data is obtained.

[0087] As an optional implementation, the step S23 comprises: determining the abnormal printing data corresponding to the plurality of key printing products respectively according to the key printing data corresponding to the plurality of key printing products respectively and the pre-trained abnormality detection model, wherein the pre-trained abnormality detection model is configured to output the abnormal printing data according to the input key printing data and the key printing product identifier having the corresponding relationship; and evaluating the printing performance of the 3D printer according to the abnormal printing data corresponding to the plurality of key printing products respectively and the key printing data, to obtain the performance evaluation data.

[0088] In this implementation, the abnormal printing data detection is realized by using the abnormality detection model, and the performance evaluation result is determined according to the abnormal printing data detection result.

[0089] Regarding the abnormality detection model, the abnormal printing data can be output according to the input key printing data and the key printing product identifier having the corresponding relationship.

[0090] Therefore, before the model is used to detect the abnormal data, the key printing data corresponding to the plurality of key printing products respectively can be converted into a form required by the model input data. For example, the key printing product is converted into an identifier, and the corresponding key printing data is converted into a feature sequence, for example, a plurality of printing parameters constitute a printing parameter sequence, model parameters of a three-dimensional model constitute a three-dimensional model feature sequence, and the like.

[0091] Further, the identifier + feature sequence is input into the abnormality detection model, and the abnormality detection model can output an abnormal printing data sequence. Based on the abnormal printing data sequence, specific abnormal data can be located.

[0092] In some embodiments, the abnormality detection model can be a large model and a random forest model, etc.

[0093] In order to realize the abnormal printing data detection function of the abnormality detection model, the model needs to be pre-trained.

[0094] As an optional implementation, the pre-training process of the model comprises: obtaining a training data set, the training data set comprising a plurality of training samples, each training sample comprising a sample printing product identifier and sample printing data, wherein the sample printing data is provided with an abnormal printing data label, the sample printing data comprises sample printing data corresponding to a plurality of printing stages respectively, and the sample printing data corresponding to different printing stages is determined by different abnormal data detection algorithms to determine the abnormal printing data label; training the abnormality detection model to be trained according to the training data set to obtain the pre-trained abnormality detection model.

[0095] In this implementation, the training data set can be configured by collecting printing data of various 3D printers. The abnormal printing data label can be determined by an abnormal data detection algorithm, and the abnormal data detection algorithm corresponding to the sample printing data of different printing stages is different.

[0096] For example, the abnormal data detection algorithm includes various outlier detection algorithms and clustering-based anomaly detection algorithms. The abnormal detection algorithm corresponding to each printing stage can be determined according to the data characteristics of each printing stage. For example, the higher the data complexity, the higher the accuracy of the applicable abnormal detection algorithm. For another example, a large amount of data can be suitable for clustering-based anomaly detection algorithm, which can quickly detect abnormal data.

[0097] Therefore, by using multiple abnormal detection algorithms to detect abnormal data of printing data in different printing stages, the labeling of the sample has differences, which can improve the generalization performance of the model.

[0098] The model is trained by the training data set, so that the model can learn the characteristics of the abnormal printing data, and the pre-trained abnormal detection model can identify the abnormal printing data from the key printing data.

[0099] Further, based on the abnormal printing data and the key printing data corresponding to the plurality of key printing products respectively, the performance evaluation can be performed.

[0100] As an optional implementation, the printing performance of the 3D printer is evaluated according to the abnormal printing data and the key printing data corresponding to the plurality of key printing products respectively, and the performance evaluation data is obtained, including: determining a first data ratio of the abnormal printing data corresponding to the plurality of key printing products compared with the key printing data; determining a second data ratio of the key printing data compared with the historical printing data; determining a printing performance evaluation value range according to the first data ratio and the second data ratio; obtaining a preset printing performance evaluation value, the preset printing performance evaluation value being a printing performance evaluation value calibrated by a user; determining the performance evaluation data according to the printing performance evaluation value range and the preset printing performance evaluation value, the performance evaluation data being used to represent the change of the printing performance evaluation value.

[0101] In this implementation, the performance of the printer is evaluated by using a relatively simple data ratio statistical method. The first data ratio can be understood as the ratio of the data amount of the abnormal printing data corresponding to the plurality of key printing products to the data amount of the key printing data. The second data ratio can be understood as the ratio of the data amount of the key printing data to the data amount of the historical printing data.

[0102] In the embodiments of the present disclosure, regarding the data amount, the data amount can be counted by data items. For example, in a piece of print data, if three print stages are involved, and the number of data items of the three print stages is 3, 10 and 20 respectively, then the data amount of the piece of print data is 33. Regarding the abnormal print data, the abnormal data items can also be corresponded, and then the data amount can be counted.

[0103] Further, according to the first data proportion and the second data proportion, the print performance evaluation value range can be determined.

[0104] In some embodiments, a print performance evaluation table can be preset, and the print performance evaluation table includes three data: the first data proportion, the second data proportion and the print performance evaluation value range. Different first data proportions and second data proportions correspond to different print performance evaluation value ranges.

[0105] In some embodiments, in the case that the higher the print performance evaluation value, the better the print performance, the maximum range can be set by setting the maximum value and the minimum value of the print performance evaluation value. If the first data proportion and the second data proportion are both high or both low, the print performance evaluation value range can be a relatively intermediate range in the maximum range, and the evaluation value in the range corresponding to the higher first data proportion and the second data proportion is lower than the evaluation value in the range corresponding to the lower first data proportion and the second data proportion. If the first data proportion and the second data proportion have differences, in the case that the higher the first data proportion, the lower the second data proportion, the print performance evaluation value range can be a range close to the minimum value in the maximum range, and in the case that the lower the first data proportion, the higher the second data proportion, the print performance evaluation value range can be a range close to the maximum value in the maximum range.

[0106] In the evaluation table, the proportion corresponding to each print performance evaluation value range can be a specific proportion value or a proportion value range.

[0107] Further, by the first data proportion and the second data proportion, the print performance evaluation value range can be determined by the table lookup operation.

[0108] Further, the preset print performance evaluation value can be the print performance evaluation value calibrated by the user, which can be the best performance evaluation value of the 3D printer, for example, the performance evaluation value measured by the user at the beginning of use.

[0109] Further, according to the print performance evaluation value range and the preset print performance evaluation value, the performance evaluation data can be determined.

[0110] In the embodiments of the present disclosure, the performance evaluation data represents the change of the print performance evaluation value, so it can involve a plurality of print performance evaluation values that change in sequence, and the plurality of print performance evaluation values can be located in the print performance evaluation value range.

[0111] Therefore, the preset printing performance evaluation value can be compared with the printing performance evaluation value range, and the performance evaluation data can be generated according to the comparison result.

[0112] Figure 4 is an example diagram of performance evaluation data according to an example embodiment, as Figure 4 As shown, the printing performance evaluation value range involves two boundary values, A and B respectively, and the preset printing performance evaluation value is Q. In the first case, if Q is less than A, the midpoint value of A and B is taken as the maximum value, and Q is taken as the minimum value, and a plurality of printing performance evaluation values are randomly sampled in the middle. In the second case, if Q is between A and B, Q is taken as the maximum value, and A is taken as the minimum value, and a plurality of printing performance evaluation values are randomly sampled in the middle. In the third case, if Q is greater than B, B is taken as the maximum value, and the midpoint value of A and B is taken as the minimum value, and a plurality of printing performance evaluation values are randomly sampled in the middle.

[0113] The random sampling described above can use a conventional random sampling algorithm in the art, which is not limited here.

[0114] Further, in step S24, the printing reference information of the 3D printer is generated according to the performance evaluation data.

[0115] As an optional implementation, step S24 includes: obtaining a plurality of preset printing reference information corresponding to a plurality of printing stages respectively; determining an adjustment strategy of the plurality of preset printing reference information corresponding to the plurality of printing stages respectively according to the performance evaluation data, the adjustment strategy including at least one of information addition and deletion strategy, information labeling strategy and information association strategy; and adjusting the plurality of preset printing reference information corresponding to the plurality of printing stages respectively according to the adjustment strategy to obtain the printing reference information of the 3D printer.

[0116] In this implementation, the plurality of printing stages correspond to the preset printing reference information respectively, and the preset printing reference information can guide the related operations of each printing stage of the 3D printer. For example, the printing reference information of the three-dimensional modeling stage can involve the model reference information of three-dimensional modeling; the printing reference information of the preparation printing stage can involve the selection rules of material parameters, printing parameters, etc. Therefore, the preset printing reference information can assist the printing user to perform the 3D printing operation.

[0117] Based on the performance evaluation data, the preset printing reference information can be adjusted, and therefore, the performance evaluation data can be used to determine the adjustment strategy.

[0118] The adjustment strategy may include at least one of an information addition and deletion strategy, an information labeling strategy, and an information association strategy. The information addition and deletion strategy is used to add or delete information. The information labeling strategy is used to label key information. The information association strategy is used to associate related information.

[0119] In some embodiments, based on the performance evaluation data, an adjustment strategy for preset printing reference information corresponding to multiple printing stages is determined, including: if the change in the printing performance evaluation value represented by the performance evaluation data is that the printing performance evaluation value shows a constant trend, the adjustment strategy for the preset printing reference information corresponding to multiple printing stages is determined based on the average printing performance evaluation value of the performance evaluation data; if the change in the printing performance evaluation value represented by the performance evaluation data is that the printing performance evaluation value shows a downward trend, the adjustment strategy for the preset printing reference information corresponding to multiple printing stages is determined based on the lowest printing performance evaluation value in the performance evaluation data; if the change in the printing performance evaluation value represented by the performance evaluation data is that the printing performance evaluation value shows an upward trend, the adjustment strategy for the preset printing reference information corresponding to multiple printing stages is determined based on the highest printing performance evaluation value in the performance evaluation data.

[0120] In this embodiment, the constant trend, the decreasing trend, and the increasing trend are an overall trend. For example, the constant trend can be considered as a small difference between the evaluation values. The decreasing trend can be considered as an overall decrease from the first evaluation value to the last evaluation value. Even if there are increasing values, their proportion is very small. The increasing trend can be considered as an overall increase from the first evaluation value to the last evaluation value. Even if there are decreasing values, their proportion is very small.

[0121] In some embodiments, based on any printing performance evaluation value (average, maximum, or minimum), the printing performance evaluation value is compared with a preset printing performance evaluation value. If the printing performance evaluation value is greater than or equal to the preset printing performance evaluation value, an information annotation strategy and an information association strategy can be configured. That is, based on the existing reference information, some key information annotations and information associations can be added. If the printing performance evaluation value is less than or equal to the preset printing performance evaluation value, an information addition and deletion strategy, an information annotation strategy, and an information association strategy can be configured. That is, more comprehensive adjustments to the reference information are required.

[0122] In some embodiments, the specific forms of the information adding and deleting strategy, the information labeling strategy, and the information association strategy can be preconfigured, and when it is determined that a certain strategy is needed, the preconfigured strategy can be directly executed. For example, the information adding and deleting strategy involves adding 3D printer usage protection information to reduce damage to the 3D printer, and deleting certain products that can be printed by the 3D printer to avoid problems caused by low performance. The information labeling strategy involves labeling important parameter configuration rules and parameter configuration rules without errors. The information association strategy involves associating information that has a greater impact on each other, for example, associating three-dimensional modeling parameters and material parameters.

[0123] Further, the printing reference information of the 3D printer is obtained by adjusting the preset printing reference information corresponding to the plurality of printing stages respectively through the adjustment strategy.

[0124] In some embodiments, the preset printing reference information corresponding to the plurality of printing stages respectively can be relatively comprehensive information.

[0125] After step S24, the method can further include: sending the printing reference information to the 3D printer to enable the 3D printer to display the printing reference information to the 3D printing user; obtaining feedback information sent by the 3D printer, the feedback information including content adjustment requirements of the 3D printing user for the printing reference information; updating the printing reference information of the 3D printer according to the content adjustment requirements, and sending the updated printing reference information to the 3D printer.

[0126] In this implementation, the printing reference information is sent to the 3D printer so that it can be displayed to the user. The 3D printer is generally configured with a visualization module to realize information display.

[0127] For the user, adjustment requirements can be proposed, and then the printing reference information is updated according to the adjustment requirements. For example, information adding requirements, information deleting requirements, information labeling requirements, and the like. For the data processing device, new reference information can be added from the existing database, and information adjustment can be performed.

[0128] As an optional implementation, the data processing method further includes: determining target printing data related to the quality of the printed product from historical printing data; and evaluating the printing effect of the plurality of printed products according to the target printing data to obtain printing effect evaluation data.

[0129] In this implementation, the printing effect can be evaluated from the perspective of the printed product in combination with the data related to the quality of the product in the printing data. The data related to the quality of the product, for example, post-processing parameters of the printed product, test parameters of the printed product, and the like.

[0130] As to the manner of evaluating the printing effect, the mature 3D printing technology in the art can be referred to, and no specific introduction is made herein. For example, the test data is compared with the estimated data, and the printing effect is determined according to the difference.

[0131] Further, on the basis of the printing effect evaluation data, the performance evaluation can also be performed in combination with the key printing data.

[0132] Therefore, as an optional implementation, the printing performance of the 3D printer is evaluated according to the key printing data to obtain performance evaluation data, including: the printing performance of the 3D printer is evaluated according to the key printing data and the printing effect evaluation data to obtain performance evaluation data.

[0133] In this implementation, the initial performance evaluation data can be determined according to the key printing data in the same manner as the foregoing embodiments, and then the influence weight of the initial performance evaluation data is determined according to the printing effect evaluation data, and the final performance evaluation data is determined in combination with the influence weight on the basis of the initial performance evaluation data. For example, the initial performance evaluation value is multiplied by the influence weight to obtain the final performance evaluation value.

[0134] Wherein, the better the printing effect represented by the printing effect evaluation data is, the higher the influence weight is, and the influence weight is greater than 1, and the worse the printing effect represented by the printing effect evaluation data is, the lower the influence weight is, and the influence weight is less than 1.

[0135] Through the technical solutions of the embodiments of the present disclosure, the performance evaluation of the 3D printer can be realized, and the effective analysis and application of the historical printing data of the 3D printer can be realized, and the use difficulty of the 3D printer is reduced.

[0136] Figure 5 is a structural block diagram of a data processing device for a 3D printer according to an exemplary embodiment, as shown in Figure 5 The device comprises:

[0137] The acquisition module 501 is configured to acquire historical printing data of a 3D printer, wherein the historical printing data comprises printing data corresponding to a plurality of printing products respectively, and the printing data corresponding to each printing product comprises data corresponding to a plurality of printing stages respectively.

[0138] The evaluation module 502 is configured to determine key printing data satisfying a preset key printing data condition from the historical printing data, wherein the key printing data comprises key printing data corresponding to a plurality of key printing products respectively, and each key printing data comprises key data corresponding to a plurality of printing stages respectively. The printing performance of the 3D printer is evaluated according to the key printing data to obtain performance evaluation data.

[0139] The generating module 503 is configured to generate printing reference information of the 3D printer according to the performance evaluation data, wherein the printing reference information comprises printing reference information corresponding to each of the plurality of printing stages.

[0140] The embodiments of the device can refer to the foregoing embodiments, and will not be repeated here.

[0141] Figure 6 is a block diagram of an electronic device 600 according to an example embodiment. As shown, the electronic device 600 can include a processor 601, a memory 602. The electronic device 600 can also include one or more of a multimedia component 603, an input / output (I / O) interface 604, and a communication component 605. Figure 6

[0142] ​The processor 601 is configured to control overall operations of the electronic device 600 to complete all or part of the steps of the above-described data processing method for a 3D printer. The memory 602 is configured to store various types of data to support operations of the electronic device 600, which can include, for example, instructions for any application or method operating on the electronic device 600, and application-related data, such as contact data, sent and received messages, pictures, audio, video, and the like. The memory 602 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as a static random access memory (SRAM), an electrically erasable programmable read-only memory (EEPROM), an erasable programmable read-only memory (EPROM), a programmable read-only memory (PROM), a read-only memory (ROM), a magnetic memory, a flash memory, a magnetic disk, or an optical disk. The multimedia component 603 can include a screen and an audio component. The screen can be, for example, a touch screen, and the audio component is configured to output and / or input audio signals. For example, the audio component can include a microphone configured to receive external audio signals. The received audio signals can be further stored in the memory 602 or transmitted through the communication component 605. The audio component also includes at least one speaker configured to output audio signals. The I / O interface 604 provides an interface between the processor 601 and other interface modules, which can be a keyboard, a mouse, a button, and the like. The buttons can be virtual buttons or physical buttons. The communication component 605 is configured to perform wired or wireless communication between the electronic device 600 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, near field communication (NFC), 2G, 3G, or 4G, or a combination of one or more of them, so the corresponding communication component 605 can include a Wi-Fi module, a Bluetooth module, and an NFC module.

[0143] In an exemplary embodiment, the electronic device 600 can be implemented by one or more Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), controller, microcontroller, microprocessor or other electronic elements for performing the above-described XXXX method.

[0144] In another exemplary embodiment, a computer readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the above-described data processing method for a 3D printer. For example, the computer readable storage medium can be the above-described memory 602 including program instructions, and the above-described program instructions can be executed by the processor 601 of the electronic device 600 to complete the above-described XXXX method.

[0145] In another exemplary embodiment, a computer program product is also provided, which contains a computer program capable of being executed by a processor, and the computer program, when executed by the processor, implements the steps of the above-described data processing method for a 3D printer.

[0146] The preferred embodiments of the present disclosure are described in detail above with reference to the accompanying drawings, but the present disclosure is not limited to the specific details in the above-described embodiments. Within the technical concept range of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all belong to the protection range of the present disclosure.

[0147] In addition, it should be noted that each specific technical feature described in the above-described specific embodiments can be combined in any appropriate manner without contradiction, and in order to avoid unnecessary repetition, the present disclosure will not further describe various possible combination manners.

[0148] In addition, various different embodiments of the present disclosure can also be combined in any appropriate manner, as long as it does not deviate from the idea of the present disclosure, and it should be considered as the disclosed content of the present disclosure.

Claims

1. A data processing method for a 3D printer, characterized in that: include: Acquire historical printing data of the 3D printer, wherein the historical printing data includes printing data corresponding to a plurality of printing products, and the printing data corresponding to each printing product includes data corresponding to a plurality of printing stages; Determining key print data that meets preset key print data conditions from the historical print data, the key print data including key print data corresponding to a plurality of key print products, each key print data including key data corresponding to a plurality of printing stages; wherein the preset key print data conditions include at least one of the following: a print product condition that the key print data needs to meet, the print product condition including a print product type condition and a print count condition; a print data feature condition that the key print data needs to meet, the print data feature condition including data feature conditions corresponding to a plurality of printing stages, the data feature conditions including a data complexity condition and a data rarity condition; and a quantity condition that the key print data needs to meet, the quantity condition including a total quantity condition and quantity conditions corresponding to a plurality of printing stages; Evaluating the printing performance of the 3D printer based on the key printing data to obtain performance evaluation data; the evaluating the printing performance of the 3D printer based on the key printing data to obtain performance evaluation data includes: determining abnormal printing data corresponding to the multiple key printing products respectively based on the key printing data respectively corresponding to the multiple key printing products and a pre-trained abnormality detection model, wherein the pre-trained abnormality detection model is used to output abnormal printing data based on input key printing product identifiers and key printing data having a corresponding relationship; evaluating the printing performance of the 3D printer based on the abnormal printing data respectively corresponding to the multiple key printing products and the key printing data to obtain performance evaluation data; Printing reference information of the 3D printer is generated according to the performance evaluation data, where the printing reference information includes printing reference information corresponding to the multiple printing stages respectively.

2. The data processing method according to claim 1, wherein: The data processing method further includes: Acquire a training data set, the training data set including a plurality of training samples, each training sample including: a sample printed product identifier and sample printed data, wherein the sample printed data is provided with an abnormal printing data label, the sample printed data including sample printed data corresponding to a plurality of printing stages, and the sample printed data corresponding to different printing stages are subjected to different abnormal data detection algorithms to determine abnormal printing data labels; The anomaly detection model to be trained is trained according to the training data set to obtain the pre-trained anomaly detection model.

3. The data processing method according to claim 1, wherein: The step of evaluating the printing performance of the 3D printer based on the abnormal printing data and the key printing data respectively corresponding to the plurality of key printing products to obtain performance evaluation data includes: determining a first data ratio of the abnormal printing data respectively corresponding to the plurality of key printing products to the key printing data; determining a second data ratio of the key printing data to the historical printing data; determining a printing performance evaluation value range according to the first data ratio and the second data ratio; Obtaining a preset printing performance evaluation value, where the preset printing performance evaluation value is a printing performance evaluation value calibrated by a user; Performance evaluation data is determined according to the printing performance evaluation value range and the preset printing performance evaluation value, and the performance evaluation data is used to characterize changes in the printing performance evaluation value.

4. The data processing method according to claim 1, wherein: Generating printing reference information of the 3D printer according to the performance evaluation data includes: Acquire preset printing reference information corresponding to the plurality of printing stages respectively; Determining, based on the performance evaluation data, adjustment strategies for the preset printing reference information corresponding to the multiple printing stages, the adjustment strategies comprising at least one of an information addition and deletion strategy, an information annotation strategy, and an information association strategy; According to the adjustment strategy of the preset printing reference information respectively corresponding to the multiple printing stages, the preset printing reference information respectively corresponding to the multiple printing stages is adjusted to obtain the printing reference information of the 3D printer.

5. The data processing method according to claim 4, characterized in that: The performance evaluation data is used to represent changes in the printing performance evaluation value, and determining, based on the performance evaluation data, adjustment strategies for the preset printing reference information corresponding to the plurality of printing stages, respectively, includes: If the change in the printing performance evaluation value represented by the performance evaluation data shows that the printing performance evaluation value shows a constant trend, determining adjustment strategies for the preset printing reference information corresponding to the plurality of printing stages respectively according to the average printing performance evaluation value of the performance evaluation data; If the change in the printing performance evaluation value represented by the performance evaluation data is a downward trend, determining, based on the lowest printing performance evaluation value in the performance evaluation data, adjustment strategies for the preset printing reference information corresponding to the multiple printing stages respectively; If the change in the printing performance evaluation value represented by the performance evaluation data shows an upward trend, the adjustment strategy of the preset printing reference information corresponding to the multiple printing stages is determined according to the highest printing performance evaluation value in the performance evaluation data.

6. The data processing method according to claim 1, wherein: The data processing method further includes: Sending the printing reference information to the 3D printer, so that the 3D printer displays the printing reference information to a 3D printing user; Acquiring feedback information sent by the 3D printer, wherein the feedback information includes a content adjustment requirement of the 3D printing user for the printing reference information; The printing reference information of the 3D printer is updated according to the content adjustment requirement, and the updated printing reference information is sent to the 3D printer.

7. The data processing method according to claim 1, wherein: The data processing method further includes: determining target printing data related to the quality of printed products from the historical printing data; evaluating printing effects of the plurality of printing products according to the target printing data to obtain printing effect evaluation data; Correspondingly, the printing performance of the 3D printer is evaluated based on the key printing data to obtain performance evaluation data, including: The printing performance of the 3D printer is evaluated based on the key printing data and the printing effect evaluation data to obtain performance evaluation data.

8. A data processing system for a 3D printer, characterized in that: include: 3D printers; A data processing device, communicatively connected to the 3D printer; The 3D printer is configured to report printing data to the data processing device after each 3D printing is completed, and the data processing device is configured to execute the data processing method for a 3D printer according to any one of claims 1 to 7.

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