Data processing method and system for 3D printer

Abstract

The invention relates to a data processing method and system for a 3D printer, and relates to the technical field of data processing, historical printing data of the 3D printer is processed and applied, and key printing data with analysis significance is determined from the historical printing data by obtaining the historical printing data of the 3D printer; and the printing performance of the 3D printer is evaluated based on the key printing data, and printing reference information is further generated based on performance evaluation data. By means of the data processing mode, performance evaluation can be conducted on the 3D printer, printing reference information can be generated through integrated analysis of key printing data of the 3D printer, the printing reference information can assist a 3D printing user in better using the 3D printer, then effective analysis and application of historical printing data of the 3D printer are achieved, and the printing quality of the 3D printer is improved. And the use difficulty of the 3D printer can be reduced.

Description

Technical Field

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

[0002] With the development of printing technology, 3D printing technology has also developed, and the application of 3D printers has become more and more extensive. 3D printers, also known as additive manufacturing equipment, work by converting digital model files into physical objects. In the 3D printer scenario, multiple printing processes are involved, such as: digital model design, slicing, printing preparation, layer-by-layer construction, and post-processing.

[0003] Currently, data processing of 3D printers is usually integrated into the printing process of 3D printers, for example, into the digital model design process to assist in the design of digital models. Summary of the invention

[0004] The purpose of the present disclosure is to provide a data processing method and system for a 3D printer, which can realize the performance evaluation of the 3D printer, as well as the effective analysis and application of the historical printing data of the 3D printer, and reduce the difficulty of using the 3D printer.

[0005] In order to achieve the above-mentioned purpose, in a first aspect, the present disclosure provides a data processing method for a 3D printer, comprising: acquiring historical printing data of the 3D printer, the historical printing data including printing data corresponding to a plurality of printing products, each printing data corresponding to a plurality of printing stages; determining key printing data satisfying preset key printing data conditions from the historical printing data, the key printing data including key printing data corresponding to a plurality of key printing products, each key printing data including key data corresponding to a plurality of printing stages; evaluating the printing performance of the 3D printer according to the key printing data to obtain performance evaluation data; generating printing reference information of the 3D printer according to the performance evaluation data, the printing reference information including printing reference information corresponding to the plurality of printing stages.

[0006] Optionally, the preset key printing data condition includes at least one of the following: a printing product condition that the key printing data needs to meet, the printing product condition including: a printing product type condition and a printing product printing times condition; a printing data feature condition that the key printing data needs to meet, the printing data feature condition including data feature conditions corresponding to multiple printing stages, the data feature conditions including: a data complexity condition and a data rarity condition; a quantity condition that the key printing data needs to meet, the quantity condition including a total quantity condition and a quantity condition corresponding to multiple printing stages.

[0007] Optionally, evaluating the printing performance of the 3D printer according to the key printing data to obtain performance evaluation data includes: determining abnormal printing data corresponding to the multiple key printing products respectively according to 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 according to input key printing product identifiers and key printing data with corresponding relationships; evaluating the printing performance of the 3D printer according to the abnormal printing data respectively corresponding to the multiple key printing products and the key printing data to obtain performance evaluation data.

[0008] Optionally, the data processing method further includes: acquiring a training data set, the training data set including multiple training samples, each training sample including: a sample printed product identification and sample printed data, wherein the sample printed data is provided with an abnormal printed data label, the sample printed data includes sample printed data corresponding to multiple printing stages, and the sample printed data corresponding to different printing stages determine the abnormal printed data labels by different abnormal data detection algorithms; 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 printing performance of the 3D printer is evaluated according to the abnormal printing data and the key printing data respectively corresponding to the multiple key printing products to obtain performance evaluation data, including: determining a first data ratio of the abnormal printing data respectively corresponding to the multiple key printing products compared to the key printing data; determining a second data ratio of the key printing data compared 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, the preset printing performance evaluation value being a printing performance evaluation value calibrated by a user; determining 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 characterize changes in the printing performance evaluation value.

[0010] Optionally, generating printing reference information of the 3D printer according to the performance evaluation data includes: obtaining preset printing reference information corresponding to the multiple printing stages respectively; determining, according to the performance evaluation data, an adjustment strategy for the preset printing reference information corresponding to the multiple printing stages respectively, the adjustment strategy including: at least one of an information addition and deletion strategy, an information annotation strategy and an information association strategy; according to the adjustment strategy for the preset printing reference information corresponding to the multiple printing stages respectively, adjusting the preset printing reference information corresponding to the multiple printing stages respectively to obtain the printing reference information of the 3D printer.

[0011] Optionally, the performance evaluation data is used to characterize changes in printing performance evaluation values, and determining, based on the performance evaluation data, adjustment strategies for preset printing reference information corresponding to the multiple printing stages, includes: if the changes in the printing performance evaluation values ​​represented by the performance evaluation data are that the printing performance evaluation values ​​show a constant trend, determining, based on an average printing performance evaluation value of the performance evaluation data, adjustment strategies for preset printing reference information corresponding to the multiple printing stages; if the changes in the printing performance evaluation values ​​represented by the performance evaluation data are that the printing performance evaluation values ​​show a decreasing trend, determining, based on a minimum printing performance evaluation value in the performance evaluation data, adjustment strategies for preset printing reference information corresponding to the multiple printing stages; if the changes in the printing performance evaluation values ​​represented by the performance evaluation data are that the printing performance evaluation values ​​show an increasing trend, determining, based on a maximum printing performance evaluation value in the performance evaluation data, adjustment strategies for preset printing reference information corresponding to the multiple printing stages.

[0012] Optionally, the data processing method also 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; obtaining feedback information sent by the 3D printer, the feedback information including the 3D printing user's content adjustment requirements 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.

[0013] Optionally, the data processing method also includes: determining target printing data related to the quality of printed products from the historical printing data; evaluating the printing effects of the multiple printed products according to the target printing data to obtain printing effect evaluation data; correspondingly, evaluating the printing performance of the 3D printer according to the key printing data to obtain performance evaluation data, including: 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; and a data processing device, communicatively connected to the 3D printer; wherein the 3D printer is used to report printing data to the data processing device after each 3D printing is completed, and the data processing device is used to execute the data processing method for a 3D printer as described in the first aspect.

[0015] Through the above technical solution, the historical printing data of the 3D printer is processed and applied. By obtaining the historical printing data of the 3D printer, the key printing data with analytical significance is determined, and the printing performance of the 3D printer is evaluated based on the key printing data, and printing reference information is further generated based on the performance evaluation data. This data processing method can not only evaluate the performance of the 3D printer, but also generate printing reference information through the integrated analysis of the key printing data of the 3D printer. The printing reference information can assist 3D printing users to better use the 3D printer, thereby realizing the effective analysis and application of the historical printing data of the 3D printer, and can also reduce the difficulty of using the 3D printer. Therefore, this technical solution can realize the performance evaluation of the 3D printer, as well as the effective analysis and application of the historical printing data of the 3D printer, and reduce the difficulty of using 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 THE DRAWINGS

[0017] The accompanying drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the present disclosure but do not constitute a limitation of the present disclosure. In the accompanying drawings:

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

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

[0020] Figure 3 The figure is a schematic diagram showing a comparison between historical printing data and key printing data according to an exemplary embodiment.

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

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

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

[0024] The specific implementation of the present disclosure is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the present disclosure, and is not used to limit the present disclosure.

[0025] With the development of printing technology, 3D printing technology has also developed, and the application of 3D printers has become more and more extensive. 3D printers, also known as additive manufacturing equipment, work by converting digital model files into physical objects. In the 3D printer scenario, multiple printing processes are involved, such as: digital model design, slicing, printing preparation, layer-by-layer construction, and post-processing.

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

[0027] However, in actual 3D printer scenarios, in addition to the need to integrate data processing into the specific printing process, there is also a need to apply data processing before and after the printing process. Currently, there is a lack of relevant data processing procedures before and after the printing process, which cannot meet such processing needs.

[0028] Based on this, an embodiment of the present disclosure provides a technical solution, which processes and applies the historical printing data of a 3D printer, obtains the historical printing data of the 3D printer, determines key printing data with analytical significance, evaluates the printing performance of the 3D printer based on the key printing data, and further generates printing reference information based on the performance evaluation data.

[0029] This data processing method can not only evaluate the performance of 3D printers, but also generate printing reference information through the integrated analysis of key printing data of 3D printers. This printing reference information can assist 3D printing users to better use 3D printers, thereby achieving effective analysis and application of historical printing data of 3D printers and reducing the difficulty of using 3D printers.

[0030] Therefore, the technical solution of the embodiment of the present disclosure can be applied before and after the 3D printing process, and can further be applied to the analysis, processing and application of data of various 3D printers.

[0031] In order to facilitate understanding of the technical solution of the disclosed embodiment, a brief printing process of a 3D printer is introduced below.

[0032] In the printing process of a 3D printer, the following printing steps (stages) 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 or downloaded from an online database.

[0034] Slicing: Import the 3D model file into the slicing software. The slicing software breaks the model into a series of thin layers (usually 0.1mm to 0.3mm thick) and generates path information for each layer, which will be converted into G-code or other instruction sets that the printer can understand.

[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 melt and solidify correctly.

[0036] Material extrusion: The print head of a 3D printer is loaded with material (such as plastic filament, resin, metal powder, etc.). The print head moves across the print bed following the path generated by the slicing software while extruding the material.

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

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

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

[0040] Post-processing: As needed, the printed object can be polished, colored, coated with a protective layer, etc. to improve its appearance and durability.

[0041] Each of the above printing steps can be regarded as a printing stage.

[0042] A 3D printer usually has its own data processing module, which can process the relevant data of 3D printing and record the relevant data, for example, the data record of each printing stage (step).

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

[0044] 3D model data: STL (Stereolithography) file: This is the most common 3D printing file format, which contains the surface geometry information of the model. OBJ (Wavefront Object) file: Another commonly used 3D model file format, which can contain the geometry data and material information of the model. FBX (Filmbox) file: A 3D file format developed by Autodesk that supports complex model data and animation. 3MF (3D Manufacturing Format) file: A newer file format that aims to become a universal format for 3D printing, supporting a variety of materials and colors.

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

[0046] Path planning: The slicing software decomposes the 3D model into multiple layers of 2D slices and generates a printing path for each layer.

[0047] Printing parameters: Layer height: the height of each printed layer. Fill density: the filling degree of the internal structure. Print speed: the speed at which the print head moves. Temperature setting: the temperature of the printing material and the print bed. Support structure: For the suspended parts, support structures need to be generated to ensure the stability of the printing.

[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. Print resolution: the minimum detail size that the printer can achieve.

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

[0051] User interface interaction data: Instructions and settings entered by the user through the 3D printer's user interface. User monitoring and control of the printing process.

[0052] Software and Firmware: Slicing Software: Software that converts 3D models into G-code. Printer Firmware: Software that controls the operation of the printer hardware.

[0053] Network and cloud service data: For network-connected 3D printers, this may involve functions such as receiving model data, monitoring printing status, and remote control through the network.

[0054] Post-processing data: data that may need to be processed after printing is completed, such as support structure removal, surface polishing, coloring, etc.

[0055] The above-mentioned various types of data may be associated with the corresponding printing stages, for example, the digital modeling stage involves a three-dimensional model book, the post-processing stage involves post-processing data, etc. Therefore, for each printing stage, there are corresponding data, which can be integrated to form printing data.

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

[0057] Figure 1 is a structural block diagram of a data processing system for a 3D printer according to an exemplary embodiment. Figure 1 As shown, the data processing system includes: a 3D printer and a data processing device that is communicatively connected to the 3D printer.

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

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

[0060] In some embodiments, the data processing device may be any type of electronic device, such as a computer.

[0061] In the system, after each 3D printing is completed, the 3D printer reports the printing data to the data processing device, and the data processing device is used to process the printing data. Therefore, the embodiment of the present disclosure provides a data processing solution that can be applied to the data processing device to implement 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 exemplary embodiment. Figure 2 As shown, the data processing method includes the following steps:

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

[0064] Step S22, determining key printing data satisfying preset key printing data conditions from the historical printing data, wherein the key printing data includes key printing data corresponding to a plurality of key printing products, and each key printing data includes key data corresponding to a plurality of printing stages.

[0065] Step S23, evaluating the printing performance of the 3D printer according to the key printing data to obtain performance evaluation data.

[0066] Step S24: Generate printing reference information of the 3D printer according to the performance evaluation data, wherein the printing reference information includes printing reference information corresponding to 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 the data. Then, after storing enough data, data processing can be performed.

[0068] Therefore, the historical printing data may be the printing data reported by the 3D printer within a preset time period, or the amount of the historical printing data may satisfy the basic data processing amount. For example, the historical printing data includes the printing data corresponding to multiple printing products involved in 10 printings; for another example, according to the frequency of use of the 3D printer, data processing is set every other week, then the historical printing data is the printing data within a week, etc.

[0069] The historical printing data includes printing data corresponding to a plurality of printing products, and the plurality of printing products may be the same printing products or different printing products. If they are the same printing products, their printing data may 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] Regarding the data corresponding to the multiple printing stages, it may involve all the printing stages of the aforementioned embodiments, or only involve some stages with data analysis value. For example, the multiple printing stages may include: data modeling stage, printing preparation stage and formal printing stage. In the data modeling stage, it may involve three-dimensional modeling related data, such as: three-dimensional model; in the printing preparation stage, it may involve printing parameters, hardware parameters and material data; in the formal printing stage, it may involve printer hardware parameters and user instructions. In different application scenarios, the data to be processed by the data printing device can be configured according to the actual data analysis needs, which is not limited here.

[0072] If all of these historical printing data are processed, the efficiency may be low and there may be a waste of resources. Therefore, in step S22, the historical printing data can be pre-processed to determine key printing data therefrom, and the key printing data can be regarded as data with data analysis significance. Accordingly, the key printing data involves key printing data corresponding to multiple key printing products, and each key printing data includes key data corresponding to multiple printing stages.

[0073] With respect to the preset key printing data conditions, the determination of key printing data having data analysis value can be achieved.

[0074] As an optional implementation, the preset key printing data condition includes at least one of the following: a printing product condition that the key printing data needs to meet, the printing product condition includes: a printing product type condition and a printing product printing times condition; a printing data feature condition that the key printing data needs to meet, the printing data feature condition includes data feature conditions corresponding to multiple printing stages, the data feature conditions include: a data complexity condition and a data rarity condition; a quantity condition that the key printing data needs to meet, the quantity condition includes a total quantity condition and a quantity condition corresponding to multiple printing stages.

[0075] In some embodiments, the type condition of the printed product may be, for example, that the printed product is a type of printed product with a higher printing complexity, and the materials and slices involved are special compared to other printed products. According to the actual application scenario, the specific type may be defined in the type condition, which may be one or more types, and is not limited here.

[0076] In some embodiments, the number of prints of a printed product may not be limited to the number of prints of a current 3D printer, but may be a comprehensive number of prints obtained by statistically analyzing the printing conditions of 3D printers in the market. The number of prints condition of a printed product may define a threshold of the number of prints, which may include a minimum value and a maximum value. If it is lower than the minimum value or higher than the maximum value, the number of prints condition is considered to be met.

[0077] Therefore, relevant information of the printing product can be obtained and then compared with the printing product conditions to determine whether the printing product conditions are met.

[0078] In some embodiments, data complexity and data rarity can be determined by conventional data analysis algorithms in the art. For example, data complexity is determined based on the data type and data volume involved. The more data types and / or data volumes involved, the higher the data complexity. Data rarity is determined based on similarity with other data. If the similarity is lower, the data similarity is higher, which is not limited here. For the same printed product, the similarity between data printed at different times can be compared to determine data rarity.

[0079] Regarding the data complexity condition and the data rarity condition, they may respectively involve a complexity threshold and a rarity threshold, which may represent a higher complexity and a higher rarity, respectively.

[0080] Regarding the quantity conditions, there are the total quantity conditions and the quantity conditions corresponding to the multiple printing stages, which respectively define the total quantity of key printing data and the quantity of each printing stage. According to the importance of different printing stages, the corresponding data quantity can be different, for example, the data quantity of the 3D modeling stage is higher than the data quantity of the post-printing processing stage.

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

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

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

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

[0085] Figure 3 FIG. 1 is a schematic diagram showing a comparison between historical printing data and key printing data according to an exemplary embodiment. Figure 3 As shown, the historical printing data involves the printing data of 10 printing products at various printing stages. By screening the key printing data conditions, the printing data of 5 of the printing products at various printing stages can be obtained.

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

[0087] As an optional implementation, step S23 includes: determining abnormal printing data corresponding to multiple key printing products respectively according to key printing data corresponding to 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 according to input key printing product identifiers and key printing data with corresponding relationships; and evaluating the printing performance of the 3D printer according to the abnormal printing data and key printing data corresponding to multiple key printing products respectively to obtain performance evaluation data.

[0088] In this embodiment, abnormal printing data detection is implemented using an abnormal detection model, and a performance evaluation result is determined based on the abnormal printing data detection result.

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

[0090] Therefore, before using the model to detect abnormal data, the key printing data corresponding to multiple key printing products can be converted into the form required by the model input data. For example, the key printing products are converted into identifiers, and the corresponding key printing data are converted into feature sequences, such as: multiple printing parameters constitute a printing parameter sequence, and the model parameters of a three-dimensional model constitute a three-dimensional model feature sequence.

[0091] Furthermore, the identification + feature sequence is input into the anomaly detection model, and the anomaly 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 anomaly detection model may be a large model or a random forest model, etc.

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

[0094] As an optional implementation, the pre-training process of the model includes: obtaining a training data set, the training data set includes multiple training samples, each training sample includes: a sample printed product identification and sample printed data, wherein the sample printed data is provided with an abnormal printed data label, the sample printed data includes sample printed data corresponding to multiple printing stages, and the sample printed data corresponding to different printing stages determine the abnormal printed data labels through different abnormal data detection algorithms; training the anomaly detection model to be trained according to the training data set to obtain a pre-trained anomaly detection model.

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

[0096] For example, abnormal data detection algorithms include: various outlier detection algorithms and clustering-based abnormal detection algorithms. The abnormal detection algorithms 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, if the amount of data is large, a clustering-based abnormal detection algorithm can be applied to quickly detect abnormal data.

[0097] Therefore, a variety of anomaly detection algorithms are used to detect abnormal data of printing data in different printing stages, so that the annotation of samples has differences, which can improve the generalization performance of the model.

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

[0099] Furthermore, performance evaluation may be performed based on abnormal printing data and key printing data respectively corresponding to a plurality of key printing products.

[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 respectively corresponding to multiple key printing products to obtain performance evaluation data, including: determining a first data ratio of the abnormal printing data corresponding to the multiple key printing products compared to the key printing data; determining a second data ratio of the key printing data compared 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, the preset printing performance evaluation value is a printing performance evaluation value calibrated by the user; determining performance evaluation data according to the printing performance evaluation value range and the preset printing performance evaluation value, the performance evaluation data is used to characterize changes in the printing performance evaluation value.

[0101] In this embodiment, a relatively simple data ratio statistical method is used to evaluate the printer performance. The first data ratio can be understood as: the ratio of the data volume of abnormal printing data corresponding to multiple key printing products to the data volume of key printing data; the second data ratio can be understood as: the ratio of the data volume of key printing data to the data volume of historical printing data.

[0102] In the embodiment of the present disclosure, the data volume can be counted by data items. For example, in a piece of printing data, if three printing stages are involved, and the numbers of data items in the three printing stages are 3, 10 and 20 respectively, then the data volume of the piece of printing data is 33. Abnormal printing data can also be mapped to abnormal data items, so that the data volume can be counted.

[0103] Further, according to the first data ratio and the second data ratio, a printing performance evaluation value range may be determined.

[0104] In some embodiments, a printing performance evaluation table can be preset, which includes three items of data: a first data ratio, a second data ratio and a printing performance evaluation value range. Different first data ratios and second data ratios correspond to different printing performance evaluation value ranges.

[0105] In some embodiments, when the higher the print performance evaluation value, the better the print performance, the highest and lowest print performance evaluation values ​​are set to form a maximum range. If the first data ratio and the second data ratio are both high or both low, the print performance evaluation value range can be a relatively middle range in the maximum range, and the evaluation values ​​in the range corresponding to both high are lower than the evaluation values ​​in the range corresponding to both low. If the first data ratio and the second data ratio are different, when the first data ratio is higher and the second data ratio is lower, the print performance evaluation value range can be a range close to the minimum value in the maximum range, and when the first data ratio is lower and the second data ratio is higher, 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 ratio corresponding to each printing performance evaluation value range may be a specific ratio value or a ratio value range.

[0107] Furthermore, by performing a table lookup operation based on the first data ratio and the second data ratio, the range of the printing performance evaluation value can be determined.

[0108] Furthermore, the preset printing performance evaluation value is a printing performance evaluation value calibrated by the user, which may be the best performance evaluation value of the 3D printer, for example, a performance evaluation value measured by the user when first using the printer.

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

[0110] In the embodiment of the present disclosure, the performance evaluation data characterizes the change of the printing performance evaluation value, so it may involve a plurality of printing performance evaluation values ​​that change sequentially, and these plurality of printing performance evaluation values ​​may be within the printing performance evaluation value range.

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

[0112] Figure 4 is an example diagram of performance evaluation data according to an exemplary embodiment. Figure 4 As shown, the range of printing performance evaluation values ​​involves two boundary values, namely A and B, 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, the Q value is taken as the minimum value, and random sampling is performed in the middle to obtain multiple printing performance evaluation values. In the second case, if Q is between A and B, Q is taken as the maximum value, the A value is taken as the minimum value, and random sampling is performed in the middle to obtain multiple printing performance evaluation values. In the third case, if Q is greater than B, the B value is taken as the maximum value, the midpoint value of A and B is taken as the minimum value, and random sampling is performed in the middle to obtain multiple printing performance evaluation values.

[0113] The above-mentioned random sampling may adopt a conventional random sampling algorithm in the art, which is not limited here.

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

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

[0116] In this embodiment, the plurality of printing stages correspond to preset printing reference information respectively, and the preset printing reference information can guide the relevant operations of each printing stage of the 3D printer. For example, in the three-dimensional modeling stage, its printing reference information can involve the model reference information of the three-dimensional modeling; in the preparation printing stage, its printing reference information can involve the selection rules of the material parameters, printing parameters, etc. Thus, 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 thus the performance evaluation data can be used to determine the adjustment strategy.

[0118] The adjustment strategy may involve at least one of an information addition and deletion strategy, an information marking strategy, and an information association strategy. The information addition and deletion strategy is used to add or delete information. The information marking strategy is used to mark key information. The information association strategy is used to associate relevant 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 of 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 the multiple printing stages is determined according to the 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 shows a downward trend, the adjustment strategy for the preset printing reference information corresponding to the multiple printing stages is determined according to the lowest printing performance evaluation value in 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 shows an upward trend, the adjustment strategy for 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.

[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 regarded as a small difference between the evaluation values. The decreasing trend can be regarded 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 regarded 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 size relationship between the printing performance evaluation value and the preset printing performance evaluation value is compared. If the printing performance evaluation value is greater than or equal to the preset printing performance evaluation value, the information marking strategy and the information association strategy can be configured, that is, on the basis of the existing reference information, some key information markings and information associations can be added. If the printing performance evaluation value is less than or equal to the preset printing performance evaluation value, the information addition and deletion strategy, the information marking strategy and the information association strategy can be configured, that is, the reference information needs to be adjusted more comprehensively.

[0122] In some embodiments, the specific forms of information addition and deletion strategies, information annotation strategies, and information association strategies may be pre-configured. When it is determined that a certain strategy is needed, the pre-configured strategy can be directly executed. For example, the information addition and deletion strategy involves adding 3D printer usage protection information to reduce damage to the 3D printer; deleting certain products that can be printed by the 3D printer to avoid printing problems caused by low performance. The information annotation strategy involves annotating important parameter configuration rules, parameter configuration rules that cannot have errors, etc. The information association strategy involves associating information that has a large impact on each other, such as associating three-dimensional modeling parameters with material parameters.

[0123] Furthermore, the preset printing reference information corresponding to the multiple printing stages is adjusted through the adjustment strategy to obtain the printing reference information of the 3D printer.

[0124] In some embodiments, the preset printing reference information corresponding to the multiple printing stages may be relatively comprehensive information.

[0125] After step S24, the method may further include: sending the printing reference information to the 3D printer so that the 3D printer displays the printing reference information to the 3D printing user; obtaining feedback information sent by the 3D printer, the feedback information including the 3D printing user's content adjustment requirements 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 embodiment, the printing reference information is sent to the 3D printer so that it can be displayed to the user. The 3D printer is generally equipped with a visualization module to realize information display.

[0127] For users, they can propose adjustment requirements, and then update the printing reference information according to the adjustment requirements, such as information addition requirements, information deletion requirements, information marking requirements, etc. For data processing equipment, new reference information can be added from the existing database, and information can be adjusted.

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

[0129] In this embodiment, the printing effect can also be evaluated from the perspective of the printed product in combination with data related to product quality in the printing data. Data related to product quality include, for example, post-processing parameters of the printed product, test parameters of the printed product, etc.

[0130] Regarding the method of evaluating the printing effect, reference can be made to the mature 3D printing technology in the art, which will not be introduced in detail here. For example, the test data is compared with the estimated data, and the printing effect is determined according to the difference.

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

[0133] In this implementation, the same implementation as the above embodiment can be used to first determine the initial performance evaluation data based on the key printing data, then determine the influence weight of the initial performance evaluation data based on the printing effect evaluation data, and determine the final performance evaluation data based on the initial performance evaluation data and the influence weight. For example, the initial performance evaluation value is multiplied by the influence weight to obtain the final performance evaluation value.

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

[0135] Through the technical solution of the embodiment of the present disclosure, the performance evaluation of the 3D printer can be realized, as well as the effective analysis and application of the historical printing data of the 3D printer can be realized, and the difficulty of using the 3D printer can be reduced.

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

[0137] The acquisition module 501 is used to 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.

[0138] The evaluation module 502 is used to determine key printing data that meets preset key printing data conditions from the historical printing data, wherein the key printing data includes key printing data corresponding to multiple key printing products, and each key printing data includes key data corresponding to multiple printing stages. The printing performance of the 3D printer is evaluated based on the key printing data to obtain performance evaluation data.

[0139] The generating module 503 is used to generate printing reference information of the 3D printer according to the performance evaluation data, wherein the printing reference information includes printing reference information corresponding to the multiple printing stages respectively.

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

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

[0142] The processor 601 is used to control the overall operation of the electronic device 600 to complete all or part of the steps in the data processing method for a 3D printer. The memory 602 is used to store various types of data to support the operation of the electronic device 600. For example, these data may include instructions for any application or method used to operate on the electronic device 600, and application-related data, such as contact data, sent and received messages, pictures, audio, video, etc. The memory 602 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, referred to as EPROM), programmable read-only memory (Programmable Read-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, magnetic disk or optical disk. The multimedia component 603 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone, which is used to receive external audio signals. The received audio signal may be further stored in the memory 602 or sent through the communication component 605. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 604 provides an interface between the processor 601 and other interface modules, and the above-mentioned other interface modules may be keyboards, mice, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 605 is used for 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 may include: Wi-Fi module, Bluetooth module, NFC module.

[0143] In an exemplary embodiment, the electronic device 600 may be implemented by one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned XXXX method.

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

[0145] In another exemplary embodiment, a computer program product is further provided. The computer program product includes a computer program executable by a processor. When the computer program is executed by the processor, the steps of the data processing method for a 3D printer are implemented.

[0146] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings; however, the present disclosure is not limited to the specific details in the above embodiments. Within the technical concept of the present disclosure, a variety of simple modifications can be made to the technical solution of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0147] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present disclosure will not further describe various possible combinations.

[0148] In addition, various embodiments of the present disclosure may be arbitrarily combined, and as long as they do not violate the concept of the present disclosure, they should also be regarded as the contents disclosed by 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; Determine key printing data satisfying preset key printing data conditions from the historical printing data, wherein the key printing data includes key printing data corresponding to a plurality of key printing products, and each key printing data includes key data corresponding to a plurality of printing stages; Evaluating the printing performance of the 3D printer according to the key printing data to obtain performance evaluation data; Printing reference information of the 3D printer is generated according to the performance evaluation data, wherein the printing reference information includes printing reference information corresponding to the multiple printing stages respectively.

2. The data processing method according to claim 1, characterized in that: The preset key printing data condition includes at least one of the following: The key printing data needs to satisfy the printing product conditions, wherein the printing product conditions include: the type of printing product and the number of printing times of the printing product; Printing data characteristic conditions that the key printing data needs to satisfy, the printing data characteristic conditions including data characteristic conditions corresponding to a plurality of printing stages respectively, the data characteristic conditions including: data complexity conditions and data rarity conditions; The key printing data needs to meet quantity conditions, where the quantity conditions include a total quantity condition and quantity conditions corresponding to multiple printing stages.

3. The data processing method according to claim 1, characterized in that: The step of evaluating the printing performance of the 3D printer according to the key printing data to obtain performance evaluation data includes: Determine the abnormal printing data corresponding to the plurality of key printing products respectively according to the key printing data respectively corresponding to the plurality of key printing products and the pre-trained abnormality detection model, wherein the pre-trained abnormality detection model is used to output the abnormal printing data according to the key printing product identifiers and key printing data having a corresponding relationship input; The printing performance of the 3D printer is evaluated according to the abnormal printing data and the key printing data respectively corresponding to the multiple key printing products to obtain performance evaluation data.

4. The data processing method according to claim 3, characterized in that: The data processing method further includes: Acquire a training data set, the training data set includes a plurality of training samples, each training sample includes: a sample printed product identification and sample printed data, wherein the sample printed data is provided with an abnormal printed data label, the sample printed data includes 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 the abnormal printed 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.

5. The data processing method according to claim 3, characterized in that: The step of evaluating the printing performance of the 3D printer according to the abnormal printing data and the key printing data respectively corresponding to the plurality of key printing products to obtain performance evaluation data includes: Determine 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.

6. The data processing method according to claim 1, characterized in that: 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; Determine, according to the performance evaluation data, adjustment strategies for the preset printing reference information respectively corresponding to the plurality of printing stages, wherein the adjustment strategies include: at least one of an information addition and deletion strategy, an information marking strategy, and an information association strategy; According to the adjustment strategies 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.

7. The data processing method according to claim 6, characterized in that: The performance evaluation data is used to characterize the change of the printing performance evaluation value, and the step of determining the adjustment strategies of the preset printing reference information respectively corresponding to the plurality of printing stages according to the performance evaluation data includes: If the change of the printing performance evaluation value represented by the performance evaluation data is that the printing performance evaluation value shows a constant trend, determining adjustment strategies for the preset printing reference information respectively corresponding to the multiple printing stages according to the 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 shows a downward trend, determining adjustment strategies for the preset printing reference information respectively corresponding to the multiple printing stages according to the lowest printing performance evaluation value in the performance evaluation data; If the change of the printing performance evaluation value represented by the performance evaluation data is an upward trend, the adjustment strategies of the preset printing reference information respectively corresponding to the multiple printing stages are determined according to the highest printing performance evaluation value in the performance evaluation data.

8. The data processing method according to claim 1, characterized in that: 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.

9. The data processing method according to claim 1, characterized in that: The data processing method further includes: Determining target printing data related to the quality of printed products from the historical printing data; According to the target printing data, the printing effects of the plurality of printing products are evaluated to obtain printing effect evaluation data; Correspondingly, 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.

10. 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 used to report the printing data to the data processing device after each 3D printing is completed, and the data processing device is used to execute the data processing method for a 3D printer according to any one of claims 1 to 9.

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