3D printing method, printer and medium

Abstract

The application relates to a 3D printing method, a printer and a medium, and the method comprises the following steps: determining whether a specified printing mode of a to-be-printed model is an intelligent exposure mode according to a slicing file; if not, slicing the to-be-printed model according to the slicing file to obtain multiple segments, and each segment model comprises multiple layers of models; determining a recommended printing mode as any one of a normal printing mode, a high-speed printing mode and an ultra-high-speed printing mode according to the similarity between each segment model and / or each layer of models; and performing printing of the to-be-printed model according to the determined recommended printing mode. The application realizes the effect that one printer indirectly has the function of multiple printers, and the printing mode of the printer is convenient to switch; the time cost and the labor cost of 3D printing are greatly saved, the energy saving requirement is met, and the application scenarios are wide.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of 3D, in particular to a 3D printing method, a printer and a medium. BACKGROUND

[0002] The current common light-curing 3D printer mode is single and has only one use, and there is no machine to realize switching of multiple modes for printing. For example, a common printer only has a common printing mode and can only perform conventional printing. In the printing model, a more efficient mode such as high-speed printing and super-speed printing cannot be used according to the size of the model or the idea of the user, so a large amount of time and labor is needed to adjust. The common printer cannot heat the resin, and in many cases, even after adjustment, the ideal printing effect cannot be achieved. SUMMARY

[0003] The embodiments of the present application are aimed at the above-mentioned situation, and propose a 3D printing method, a printer and a medium. The method can intelligently recommend a suitable printing mode according to the model condition, and realize efficient and fast printing.

[0004] In a first aspect, the embodiments of the present application provide a 3D printing method. The method is applied to a 3D printer, and the method comprises the following steps.

[0005] Determining whether a specified printing mode of a to-be-printed model is an intelligent exposure mode according to a slice file;

[0006] If not, the to-be-printed model is divided into multiple segments according to the slice file, and each segment of the model contains multiple layers of the model;

[0007] Determining a recommended printing mode according to the similarity between each segment of the model and / or each layer of the model;

[0008] Performing printing of the to-be-printed model according to the determined recommended printing mode.

[0009] In a second aspect, the embodiments of the present application further provide a 3D printer, which comprises a processor and a memory arranged to store computer executable instructions, the executable instructions, when executed, causing the processor to perform any of the above-mentioned methods.

[0010] In a third aspect, the embodiments of the present application further provide a computer readable storage medium, which stores one or more programs, the one or more programs, when executed by a 3D printer comprising multiple application programs, causing the 3D printer to perform any of the above-mentioned methods.

[0011] The method adopted by the embodiments of the present application can at least achieve the following beneficial effects:

[0012] The application reads a slice file of a to-be-printed model, determines whether the slice file specifies an intelligent exposure mode, if not, divides the to-be-printed model into multiple segments, and divides each segment into multiple layers of the model containing the same number of layers, and then intelligently recommends a suitable printing mode for the to-be-printed model according to the similarity between layers of a segment of the model and / or the similarity between segments of different segments of the model, such as a normal printing mode, a high-speed printing mode and an ultra-high-speed printing mode, and finally performs printing of the to-be-printed model according to the determined recommended printing mode. The application can intelligently recommend a suitable printing mode for different models, and can switch for each model at the beginning of printing, realizing the effect of a printer indirectly having the function of multiple printers, and the printing mode switching is convenient; greatly saving the time cost of 3D printing, and meeting the energy saving requirement, and being widely applicable. BRIEF DESCRIPTION OF DRAWINGS

[0013] The drawings described herein are used to provide further understanding of the application, and form a part of the application. The illustrative embodiments of the application and their descriptions serve to explain the application, and do not constitute an improper limitation on the application. In the drawings:

[0014] Figure 1 A flowchart of a 3D printing method according to one embodiment of the application is shown;

[0015] Figure 2 A flowchart of determining a recommended printing mode according to one embodiment of the application is shown;

[0016] Figure 3 A flowchart of a high-speed printing mode according to one embodiment of the application is shown;

[0017] Figure 4 A flowchart of an ultra-high-speed printing mode according to one embodiment of the application is shown;

[0018] Figure 5 A flowchart of an intelligent exposure mode according to one embodiment of the application is shown;

[0019] Figure 6 A structural diagram of a 3D printing device according to one embodiment of the application is shown;

[0020] Figure 7 A structural diagram of a 3D printing device according to one embodiment of the application is shown; DETAILED DESCRIPTION

[0021] In order to make the purposes, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be described below in connection with specific embodiments of the present application and corresponding drawings. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0022] The technical solutions provided by the embodiments of the present application will be described in detail below in connection with the drawings.

[0023] The currently used light-curing 3D printer mode is single and has a single purpose. In view of the fact that there is a lack of a machine that can switch between multiple modes for printing, the present application proposes a 3D printer and a 3D printing method based on the 3D printer, Figure 1 A flowchart of a 3D printing method according to an embodiment of the present application is shown, as shown in Figure 1 The present application at least includes steps S110-S140:

[0024] Step S110: Determine whether the specified printing mode of the to-be-printed model is an intelligent exposure mode according to a slicing file.

[0025] The 3D printer of the present application can be controlled by a local control interface, or can be connected to a mobile phone or a tablet computer to control the 3D printer. Specifically, after the 3D printer receives a printing task issued by the local control interface, mobile phone APP or tablet computer, the 3D printer analyzes the slicing file corresponding to the printing task to determine whether the intelligent exposure mode has been selected in the slicing file. If the intelligent exposure mode is not selected during slicing, step S120 is entered; if the intelligent exposure mode is selected, the intelligent exposure printing mode is entered.

[0026] Step S120: If not, the to-be-printed model is divided into multiple segments according to the slicing file, and each segment model contains multiple layer models.

[0027] Enter the intelligent mode recommendation, and the 3D printer will analyze the features of the to-be-printed model to obtain a suitable printing mode. Specifically, the to-be-printed model is divided into "segments", and the total number of layers of the to-be-printed model is divided into td small segments, each of which is recorded as a segment model. Each segment model contains multiple layers, which are recorded as layer models. The total number of layer models in each segment model is i. In the following processing, the processed segment model is recorded as the current segment cd, and the processed layer model is recorded as the current layer j.

[0028] Step S130: According to the similarity between each segment model and / or each layer model, determine that the recommended printing mode is any one of the normal printing mode, the high-speed printing mode and the super high-speed printing mode.

[0029] Then, the printing mode is recommended based on the similarity between each segment model and / or each layer model. Simply put, the higher the similarity, the more likely it is to be a printing mode with a higher speed.

[0030] Step S140: Print the model to be printed according to the determined recommended printing mode.

[0031] Finally, print the model to be printed according to the determined recommended printing mode.

[0032] like Figure 1 As shown, this application reads the slice file of the model to be printed, determines whether it specifies a smart exposure mode, and if not, divides the model into multiple segments, each segment into multiple layers containing the same number of layers. Then, based on the similarity between layers of a segment and / or the similarity between segments of different segments, it intelligently recommends a suitable printing mode for the model to be printed, such as normal printing mode, high-speed printing mode, and ultra-high-speed printing mode. Finally, it executes the printing of the model according to the determined recommended printing mode. This application can intelligently recommend a suitable printing mode for different models, and can switch between modes at the start of printing for each model, achieving the effect of one printer indirectly having the functions of multiple printers, and the printer mode switching is convenient; it greatly saves the time cost of 3D printing, meets energy-saving requirements, and has a wide range of applications.

[0033] In some embodiments of this application, determining the recommended printing mode as any one of normal printing mode, high-speed printing mode, and ultra-high-speed printing mode based on the similarity between each segment model and / or each layer model includes: determining the first layer similarity between adjacent layer models of each segment model based on the layer data comparison method; determining the intra-segment similarity value of each segment model based on the first layer similarity; if it is determined that the intra-segment similarity value of a certain segment model is greater than a first preset threshold, then determining that the recommended printing mode of the model to be printed is normal printing mode.

[0034] The layer data comparison method can be simply understood as processing the relevant data between each layer model and the adjacent layer model. In the embodiment, taking a segment model as an example, the segment model includes a plurality of layer models, and the intra-segment similarity value represents the similarity between the plurality of layer models of the segment model. If the similarity between the layer models is relatively small, a relatively slow printing mode, i.e., the normal printing mode, needs to be used. In some embodiments, the first layer similarity between the adjacent layer models of a segment model can be determined in sequence based on the layer data comparison method, and then the intra-segment similarity value of the segment model is determined according to the plurality of first layer similarities. The obtained intra-segment similarity value is compared with the first preset threshold value. If the intra-segment similarity value is greater than the first preset threshold value, it is determined that the recommended printing mode of the to-be-printed model is the normal printing mode. That is, when the intra-segment similarity value meets a certain preset condition, it is determined to enter the normal printing mode.

[0035] As can be seen, the calculation of the intra-segment similarity can quickly determine whether the printing model is suitable for the normal printing mode, thereby saving the calculation amount and improving the printing efficiency.

[0036] Specifically, in some embodiments, the layer data comparison method is used to determine the first layer similarity between the adjacent layer models of each segment model, including: traversing each layer model of a segment model in a preset order, calculating the similarity of the image data between the traversed layer model and the adjacent next layer model as the first layer similarity, and the image data includes one or more of the image size, the image boundary, and the boundary coordinates. The intra-segment similarity value of each segment model is determined according to the first layer similarity, including: if the first layer similarity between a layer model and its adjacent next layer model is greater than the first preset threshold value and less than the second preset threshold value, the intra-segment similarity value is added by one, wherein the first preset threshold value is less than the second preset threshold value; when it is determined that the next layer model of the current layer model is the last layer model of the segment model, the reciprocal of the layer model of the segment model is accumulated on the basis of the intra-segment similarity value to obtain the intra-segment similarity value of the segment model.

[0037] For details, refer to Figure 2 , Figure 2 FIG. 1 shows a flowchart of determining the recommended printing mode according to an embodiment of the present application, from Figure 2It can be seen that when the intelligent recommendation printing mode is performed, each layer model of the cd segment model is traversed from bottom to top in the current segment cd, the traversed layer model is recorded as the jth layer model, the next layer model of the jth layer model is recorded as the (j+1)th layer model, the similarity between the two is calculated, and the specific calculation method of the similarity can be based on the layer data comparison method. Specifically, the first image data of the jth layer model and the second image data of the (j+1)th layer model are read from the slice file, and the similarity of the first layer is obtained by comparing one or more of the image size, image boundary, and boundary coordinates of the two.

[0038] It should be noted that there can be different standards for the first layer similarity, which can be set by a preset threshold value, such as setting a first preset threshold value and a second preset threshold value, the first preset threshold value being less than the second preset threshold value, and the similarity being distinguished according to the relative size of the similarity and the first preset threshold value and the second preset threshold value. In actual scenarios, the similarity percentage of the image is calculated, and there is usually a distinction between 85% similarity and 95% similarity, that is, if the layer similarity of the jth layer model and the (j+1)th layer model is greater than 85% and less than 95%, it is recorded as 85% similarity; if the layer similarity of the jth layer model and the (j+1)th layer model is greater than 95%, it is recorded as 95% similarity. 85% can be understood as the first preset threshold value, and 95% can be understood as the second preset threshold value. Since the similarity is not required to be high when determining whether the to-be-printed model adopts the normal mode, 85% similarity (i.e., the first layer similarity) is used here. Of course, the specific values of the first preset threshold value and the second preset threshold value can be adjusted in other embodiments.

[0039] The layer similarity can be accumulated to obtain the intra-segment similarity value of the segment model, that is, if the first layer similarity between the jth layer model and its adjacent (j+1)th layer model is greater than 85% and less than 95%, the intra-segment similarity value (which is usually 0 initially) is incremented by one, and then it is determined whether the (j+1)th layer model is the last layer of the current end cd segment. If not, the number of traversed layers j is incremented by 1, and the calculation of the next layer model is entered; if so, the reciprocal of the layer model of the segment model is accumulated on the basis of the intra-segment similarity value, that is, 1 / cd is added to the currently accumulated intra-segment similarity value to obtain the intra-segment similarity value of the cd segment model.

[0040] A preset threshold value can be set to determine the relative size of the intra-segment similarity value of the segment model, which is usually set to be consistent with the first preset threshold value, i.e. 85% in this embodiment. That is, it is determined whether the intra-segment similarity value is greater than 85%. If it is determined that the layer similarity between most layer models is between the first preset threshold value and the second preset threshold value, the similarity between layers does not reach a high level. In this case, it is determined that the recommended printing mode of the to-be-printed model is the normal printing mode, and the step S140 is entered, i.e. the printing of the to-be-printed model is performed according to the determined recommended printing mode.

[0041] In some embodiments of the present application, in the above method, the determining of the recommended printing mode as any one of the normal printing mode, the high-speed printing mode and the super high-speed printing mode according to the similarity between the segment models and / or the layer models further comprises: if it is determined that the intra-segment similarity value of each segment model is less than or equal to the first preset threshold value, then a second layer similarity between a plurality of corresponding layer models between each two adjacent segment models is determined based on the layer data comparison method in sequence; a first inter-segment similarity value of each adjacent segment model is determined according to the obtained plurality of second layer similarities; if it is determined that the first inter-segment similarity value of a certain adjacent segment model is greater than a second preset threshold value, then it is determined that the recommended printing mode of the printing model is the high-speed printing mode; wherein the first preset threshold value is less than the second preset threshold value; if it is determined that the first inter-segment similarity value of each adjacent segment model is less than or equal to the second preset threshold value, then a second inter-segment similarity value of each adjacent segment model is determined according to the first inter-segment similarity value; it is determined whether the second inter-segment similarity value of each adjacent segment model is greater than the second preset threshold value, if yes, then it is determined that the recommended printing mode of the to-be-printed model is the super high-speed printing mode; otherwise, it is determined that the recommended printing mode of the to-be-printed model is the high-speed printing mode.

[0042] Please refer to Figure 2When the last segment model is traversed, and it is determined that the intra-segment similarity values of all segment models are less than or equal to the first preset threshold value 85%, the next stage, i.e., the judgment of the high-speed printing mode, is entered. That is, on the basis of determining that the inter-layer models in the segment model are relatively similar, the similarity between the segment models can be further judged. Specifically, based on the layer data comparison method, the second layer similarity between the corresponding layers of each two adjacent segment models is determined, and according to the second layer similarity, the first inter-segment similarity value of each adjacent segment model is determined. Specifically, the second layer similarity between the corresponding layer models of each two adjacent segment models is determined based on the layer data comparison method, including: traversing each segment model of the to-be-printed model in a preset order, for a segment model traversed, the second layer similarity between the first image data of the multiple layer models of the segment model and the second image data of the corresponding layer models of the next segment model of the segment model is calculated; and according to the obtained multiple second layer similarities, the first inter-segment similarity value of each adjacent segment model is determined, including: if the second layer similarity of a group of corresponding layer models of one segment model and the next segment model is greater than the second preset threshold value, the first inter-segment similarity value is added by one.

[0043] In the order from bottom to top, each segment model of the to-be-printed model is traversed, for a segment model cd, k (k≥2) layer models in the segment model are read, for one layer, the first image data in the cd segment model and the second image data in the cd+1 segment model are read, the similarity between the first image data and the second image data is calculated, and is recorded as the second layer similarity, if the second layer similarity of a group of corresponding layer models of one segment model and the next segment model is greater than the second preset threshold value, such as 95%, the first inter-segment similarity (which can be understood as 95% similarity, and the initial value is usually 0) value is added by one, and by processing the k layer models respectively, the first inter-segment similarity value can be obtained.

[0044] Then, if it is determined that the first inter-segment similarity value of at least one adjacent segment model is greater than the second preset threshold value, it is determined that the recommended printing mode of the printing model is the high-speed printing mode; wherein the first preset threshold value is less than the second preset threshold value.

[0045] When the first inter-segment similarity value of one adjacent segment model is obtained, it is judged whether the first inter-segment similarity value is greater than a preset threshold value, which is usually set to be consistent with the second preset threshold value, if yes, it is determined that the recommended printing mode of the printing model is the high-speed printing mode.

[0046] If it is determined that the first inter-segment similarity values of the adjacent segment models are all less than or equal to the second preset threshold, the next mode is determined. In some embodiments of the present application, the recommended printing mode of the to-be-printed model is determined according to the similarity between the segment models and / or the layer models, and further comprises: if it is determined that the first inter-segment similarity values of the adjacent segment models are all less than or equal to the second preset threshold, the second inter-segment similarity values of the adjacent segment models are determined according to the first inter-segment similarity values; it is determined whether the second inter-segment similarity values of the adjacent segment models are all greater than the second preset threshold, if yes, it is determined that the recommended printing mode of the to-be-printed model is the super-high-speed printing mode; otherwise, it is determined that the recommended printing mode of the to-be-printed model is the high-speed printing mode.

[0047] If it is determined that the first inter-segment similarity values of the adjacent segment models are all less than or equal to the second preset threshold, the first inter-segment similarity values are further processed to obtain the second inter-segment similarity values. Specifically, the reciprocal of the number of the segment models is added to the first inter-segment similarity values to obtain the second inter-segment similarity values, that is, the second inter-segment similarity values are obtained by adding 1 / cd to the cumulative first inter-segment similarity values, and a plurality of second inter-segment similarity values are obtained.

[0048] Then, it is determined whether the plurality of second inter-segment similarity values are all greater than 95% of the second preset threshold, if yes, it is determined that the recommended printing mode of the to-be-printed model is the super-high-speed printing mode, and if one or several of the plurality of second inter-segment similarity values are less than or equal to the second preset threshold, it is determined that the recommended printing mode of the to-be-printed model is the high-speed printing mode.

[0049] When the 3D printer performs printing on the to-be-printed model, if the recommended printing mode is the ordinary printing mode, the 3D printer runs according to the general running effect and performs printing according to the following process: reading file information in a slice file, specifically, reading and analyzing image data of the file information, then reading exposure parameters, and then starting to perform exposure printing layer by layer, after each layer of the model is printed, it is determined whether the printing is completed, if not, it returns to the step of reading and analyzing the image data of the file information, and then reads the image data of the next layer of the model, and then the above process is repeated until the printing is completed. It should be noted that the ordinary printing model is the same as the ordinary printer in the prior art, and each time the exposure is completed, the lifting is required to be lifted off the type for the next exposure.

[0050] If the recommended printing mode is the high-speed printing mode, the printing of the to-be-printed model according to the determined recommended printing mode comprises: reading file information of the slice file, the file information comprising model parameters, image data and exposure parameters of the to-be-printed model; setting an automatic lifting parameter according to the model parameters; parsing the image data, and performing layer-by-layer exposure printing on the to-be-printed model according to the exposure parameters; after printing a layer of model, lifting the print head of the 3D printer by a thickness indicated by the automatic lifting parameter, and continuing printing of the next layer of model until printing of the to-be-printed model is completed.

[0051] The high-speed printing mode is different from the ordinary printing mode in that, in the high-speed printing mode, the 3D printer automatically sets a continuous lifting parameter. When the continuous lifting parameter is set, the 3D printer does not need to lift off the type after exposure and then perform the next exposure, but only needs to lift by a layer thickness after exposure of a layer of model, and then directly perform exposure of the next layer of model.

[0052] Specifically, refer to Figure 3 , Figure 3 Fig. 2 shows a flowchart of the high-speed printing mode according to an embodiment of the present application, from Figure 3 It can be seen that, when the high-speed printing mode is entered, file information in the slice file is read, an automatic lifting parameter is set according to model parameters (such as a height of a layer of model) in the file information, image data in the file information is read and parsed, then exposure parameters are read, and then exposure printing is started. After printing a layer of model, it is determined whether printing is completed. If not, the print head is lifted by a certain height (different from lifting off the type) according to the automatic lifting parameter, and printing of the next layer of model is directly performed until printing of the to-be-printed model is completed. The 3D printer according to the present application can automatically set a lifting parameter in the high-speed printing mode, and realize high-speed printing without lifting off the type.

[0053] In some embodiments of the present application, the recommended printing mode is a high-speed printing model; and the printing of the to-be-printed model according to the determined recommended printing mode comprises: parsing file information of the slice file, the file information comprising image data and exposure parameters of the to-be-printed model; setting an automatic lifting parameter according to the file information; parsing the image data, and performing layer-by-layer exposure printing on the to-be-printed model according to the exposure parameters and the image similarity between adjacent layer models; after printing any layer model, lifting the printing head of the 3D printer by a thickness indicated by the automatic lifting parameter, and continuing to print the next layer model until the printing of the to-be-printed model is completed; for a target layer model, if the image similarity between the target layer model and the last layer model is greater than a third preset threshold, the image data of the last layer model is used to perform exposure printing on the target layer model; otherwise, the image data of the target layer model is used to perform exposure printing on the target layer model.

[0054] That is, the super high-speed printing not only introduces the automatic lifting parameter, but also introduces the "brushing image mode". Please refer to Figure 4 , Figure 4 The flowchart of the super high-speed printing mode according to an embodiment of the present application is shown in FIG. 2. Please refer to Figure 3 and Figure 4 The difference between the two is that, for the target layer model to be printed, after reading the exposure parameters, the first image data of the target layer model is compared with the second image data of the last layer model which has been printed, which is referred to as image similarity. If the image similarity of the two is greater than a third preset threshold, such as 95%, the image data of the last layer model can be used to perform exposure printing on the current target layer model; otherwise, the image data of the current target layer model is parsed and exposed. In this way, when the first image data of the target layer model has high similarity with the second image data of the last layer model which has been printed, part of the image data parsing computing power and time can be saved, thereby realizing super high-speed printing.

[0055] In some embodiments of the present application, the method further comprises: if the specified printing mode of the to-be-printed model determined according to the slice file is an intelligent exposure mode, reading the current exposure image data layer by layer, the exposure image data comprising a plurality of image blocks; determining whether the exposure image data is a solid image, if yes, determining the exposure parameters of each image block based on the light uniformity algorithm; if no, performing a completion processing on the exposure image, and determining the exposure parameters of each image block after completion based on the light uniformity algorithm; and performing layer-by-layer exposure printing on the to-be-printed model according to the exposure parameters.

[0056] Due to the large difference in energy of different image blocks on the exposure screen, it leads to a large difference in exposure effect of different image blocks in the 3D printing process with the same layer and exposure time, which affects the printing quality. If it is known through analysis that the smart exposure mode is specified in the slice file, the smart exposure mode is directly entered, and for details, please refer to Figure 5 , Figure 5 The flowchart of the smart exposure mode according to an embodiment of the present application is shown from Figure 5 As can be seen, after entering the smart exposure mode, for a target layer model, the image data in the slice file is read and parsed, denoted as exposure image data, which includes multiple image blocks (similar to a nine-square grid), which is parsed and analyzed, such as calculating the effective pixels of the exposure image data and calculating the maximum image coordinate system of the exposure image data, and then determining whether the exposure image data is a solid image (it can be understood that whether the center position of the image contains a certain number of effective pixels), if so, the exposure data of each image block can be calculated based on the light uniformity algorithm, which can be UV (Ultra-Violet Ray, ultraviolet) lamp exposure data, the UV lamp at the corresponding position should be turned on through each coordinate data, and the light uniformity relationship between the UV lamps is calculated to obtain the light uniformity data of each image block. The next step is to calculate the energy relationship between the UV lamps according to the relationship between the light uniformity values of each image block to obtain the final UV lamp exposure data, and then the current target layer model is exposed and printed according to the calculated UV lamp exposure data. If the exposure image data is not a solid image, N neat image blocks are arranged, such as the boundaries and sizes of each image, if there is no effective pixel in an image block, each pixel i in the image block is assigned a value of 0, and whether the image block is coupled with its adjacent image block is calculated, if so, the two image blocks are integrated into one image block; until all image blocks are processed, the exposure data of each image block is calculated based on the light uniformity algorithm, and then the current target layer model is exposed and printed according to the calculated exposure data. Through the above process, the energy of each image block can meet the set conditions, which can effectively reduce the influence of the energy difference between different image blocks on the printing quality.

[0057] As can be seen, the smart exposure mode of the present application can automatically calculate the exposure data of the model, realize the rapid and efficient printing of the model, greatly save the time cost of printing, and significantly improve the printing efficiency.

[0058] Figure 6 The structural diagram of a 3D printing device according to an embodiment of the present application is shown, which can be deployed in a 3D printer, and the 3D printing device 600 includes:

[0059] The first mode determining unit 610 is configured to determine, according to the slice file, whether the specified printing mode of the to-be-printed model is an intelligent exposure mode.

[0060] The slicing unit 620 is configured to slice the to-be-printed model into multiple segments according to the slice file, each segment containing multiple layers of the model, if the specified printing mode of the to-be-printed model is not the non-intelligent exposure mode.

[0061] The second mode determining unit 630 is configured to determine, according to the similarity between each segment of the model and / or each layer of the model, the recommended printing mode as any one of a normal printing mode, a high-speed printing mode, and an ultra-high-speed printing mode.

[0062] The printing executing unit 640 is configured to execute printing of the to-be-printed model according to the determined recommended printing mode.

[0063] In some embodiments of the present application, in the above device, the second mode determining unit 630 is configured to determine, based on a layer data comparison method, a first layer similarity between adjacent layers of each segment of the model in sequence, and determine an intra-segment similarity value of each segment of the model according to the first layer similarity, and if the intra-segment similarity value of a certain segment of the model is greater than a first preset threshold, determine the recommended printing mode of the to-be-printed model as the normal printing mode.

[0064] In some embodiments of the present application, in the above device, the second mode determining unit 630 is configured to traverse each layer of a segment of the model in a preset order, calculate a similarity of image data between a layer model and its adjacent next layer model as a first layer similarity, the image data including one or more of image size, image boundary, and boundary coordinates, if the first layer similarity between a layer model and its adjacent next layer model is greater than the first preset threshold and less than the second preset threshold, add one to the intra-segment similarity value, wherein the first preset threshold is less than the second preset threshold, and when it is determined that the next layer model of the current layer model is the last layer model of the segment of the model, accumulate the reciprocal of the layer models of the segment of the model on the basis of the intra-segment similarity value to obtain the intra-segment similarity value of the segment of the model.

[0065] In some embodiments of the present application, in the above device, the second mode determining unit 630 is further configured to: if it is determined that the intra-segment similarity values of the segment models are all less than or equal to the first preset threshold, determine, in sequence, second layer similarities between a plurality of groups of corresponding layer models between each two adjacent segment models based on a layer data comparison method; determine first inter-segment similarity values of each of the adjacent segment models according to the obtained second layer similarities; if it is determined that the first inter-segment similarity value of a certain adjacent segment model is greater than a second preset threshold, determine that the recommended printing mode of the printing model is a high-speed printing mode; wherein the first preset threshold is less than the second preset threshold; if it is determined that the first inter-segment similarity values of each of the adjacent segment models are all less than or equal to the second preset threshold, determine second inter-segment similarity values of each of the adjacent segment models according to the first inter-segment similarity values; and determine whether the second inter-segment similarity values of each of the adjacent segment models are all greater than the second preset threshold, if yes, determine that the recommended printing mode of the printing model is an ultra-high-speed printing mode; otherwise, determine that the recommended printing mode of the printing model is the high-speed printing mode.

[0066] In some embodiments of the present application, in the above device, the second mode determining unit 630 is configured to: traverse each segment model of the printing model in a preset order, for a segment model traversed, calculate second layer similarities between first image data of a plurality of layer models of the segment model and second image data of corresponding layer models of a next segment model of the segment model; and if the second layer similarity of a group of corresponding layer models between a segment model and a next segment model is greater than the second preset threshold, add one to the first inter-segment similarity value.

[0067] In some embodiments of the present application, in the above device, the second mode determining unit 630 is configured to: add, on the basis of the first inter-segment similarity value, a reciprocal of the number of the segment models to obtain the second inter-segment similarity value.

[0068] In some embodiments of the present application, in the above device, the recommended printing mode is a high-speed printing mode; and the printing executing unit 640 is configured to: parse file information of the slicing file, the file information including image data of a printing model and exposure parameters; set an automatic lifting parameter according to the file information; parse the image data, and perform layer-by-layer exposure printing on the printing model according to the exposure parameters; when printing of any layer model is completed, lift a print head of the 3D printer by a thickness indicated by the automatic lifting parameter, and continue printing of a next layer model until printing of the printing model is completed.

[0069] In some embodiments of the present application, in the above device, the recommended printing mode is a high-speed printing mode; the printing execution unit 640 is configured to parse file information of the slicing file, the file information including image data of a model to be printed and exposure parameters; set automatic lifting parameters according to the file information; parse the image data, and according to the exposure parameters, perform layer-by-layer exposure printing on the model to be printed according to image similarity between adjacent layer models; when printing of any layer model is completed, lift the print head of the 3D printer by a thickness indicated by the automatic lifting parameters, and continue printing of the next layer model until printing of the model to be printed is completed; for a target layer model, if image similarity between the target layer model and a previous layer model is greater than a third preset threshold, use image data of the previous layer model to perform exposure printing on the target layer model; otherwise, use image data of the target layer model to perform exposure printing on the target layer model.

[0070] In some embodiments of the present application, in the above device, the printing execution unit 640 is further configured to, if it is determined according to the slicing file that the specified printing mode of the model to be printed is an intelligent exposure mode, read current exposure image data layer by layer, the exposure image data including a plurality of image blocks; determine whether the exposure image data is a solid image, if yes, determine exposure parameters of each of the image blocks based on a light uniformity algorithm; if no, perform completion processing on the exposure image data, and determine exposure parameters of each of the completed image blocks based on the light uniformity algorithm; and perform layer-by-layer exposure printing on the model to be printed according to the exposure parameters.

[0071] It should be noted that the above 3D printing device can implement the above 3D printing method, which will not be described here.

[0072] Figure 7 FIG. 1 is a structural schematic diagram of a 3D printer according to an embodiment of the present application. Please refer to Figure 7 At the hardware level, the 3D printer includes a processor, and optionally further includes an internal bus, a network interface, and a memory. The memory can include a memory such as a random-access memory (RAM), and can also include a non-volatile memory such as at least one disk memory. Of course, the 3D printer can also include other hardware required by the business.

[0073] The processor, the network interface and the memory can be connected with each other through an internal bus, which can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus or the like. The bus can be divided into an address bus, a data bus, a control bus and the like. For the convenience of representation, Figure 7 Only one bidirectional arrow is used to represent the bus, but it does not mean that there is only one bus or only one type of bus.

[0074] The memory is used to store programs. Specifically, the programs can include program codes including computer operation instructions. The memory can include an internal memory and a non-volatile memory, and provide instructions and data for the processor.

[0075] The processor reads the corresponding computer program from the non-volatile memory into the internal memory and then runs, and forms a 3D printing device at a logical level. The processor executes the programs stored in the memory, and is specifically used for executing the foregoing method.

[0076] The above as described in the present application Figure 6The method performed by the 3D printing device disclosed in the embodiment can be applied in a processor or implemented by the processor. The processor can be an integrated circuit chip with processing capability of signals. In the implementation process, each step of the above method can be completed by integrated logic circuits of hardware in the processor or instructions in the form of software. The processor mentioned above can be a general processor, including a central processing unit (CPU), a network processor (NP), etc.; or a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. Each method, step and logic block diagram disclosed in the embodiment of the present application can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in combination with the embodiment of the present application can be directly embodied as a hardware code processor for execution, or a combination of hardware and software modules in the code processor for execution. The software module can be located in a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register or other mature storage medium in the art. The storage medium is located in the memory, and the processor reads the configuration information in the memory and combines the hardware to complete the steps of the above method.

[0077] The 3D printing machine can also perform the method performed by the 3D printing device in the embodiment. Figure 6 The 3D printing device in the embodiment can also perform the method performed by the 3D printing device in the embodiment, and realize the functions of the 3D printing device in the embodiment. The embodiment of the present application will not be repeated here. Figure 6 The 3D printing device in the embodiment can also perform the method performed by the 3D printing device in the embodiment, and realize the functions of the 3D printing device in the embodiment. The embodiment of the present application will not be repeated here.

[0078] The embodiment of the present application also proposes a computer readable storage medium, which stores one or more programs, the one or more programs including instructions, which when executed by a 3D printing machine including a plurality of application programs, can enable the 3D printing machine to perform the method performed by the 3D printing device in the embodiment. Figure 6 The 3D printing device in the embodiment can also perform the method performed by the 3D printing device in the embodiment, and realize the functions of the 3D printing device in the embodiment. The embodiment of the present application will not be repeated here.

[0079] Those skilled in the art will appreciate that embodiments of the application can be readily used as software, hardware, or a combination of software and hardware. In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0080] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more functions specified in the flowchart block or blocks. Figure 1 means for functionally implementing the one or more functions specified in the flowchart block or blocks.

[0081] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instructions which implement the flowchart block or blocks. Figure 1 one or more functions specified in the flowchart block or blocks. Figure 1 means for functionally implementing the one or more functions specified in the flowchart block or blocks.

[0082] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more functions specified in the flowchart block or blocks. Figure 1 Figure 1 means for functionally implementing the one or more functions specified in the flowchart block or blocks.

[0083] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0084] The memory can include non-persistent memory and / or volatile memory, such as random access memory (RAM) and / or cache memory, non-volatile memory, such as read-only memory (ROM), optical storage, and / or flash memory. The memory is an example of computer readable storage media.

[0085] Computer-readable media includes permanent and non-permanent, movable and non-movable media, which can be implemented by any method or technology to configure information storage. The configuration information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store configuration information that can be accessed by a computing device. According to the definition herein, computer readable media does not include transitory media such as modulated data signals and carriers.

[0086] Those skilled in the art will appreciate that embodiments of the present application can be provided as methods, systems or computer program products. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage etc.) containing computer usable program code.

[0087] The above only describes the embodiments of the present application and is not intended to limit the present application. Those skilled in the art can make various changes and modifications to the present application. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application shall be included in the scope of claims of the present application.

Claims

1. A 3D printing method, characterized in that, The method is applied to a 3D printer, and the method includes: Determine whether the specified printing mode for the model to be printed is the intelligent exposure mode based on the slice file; If not, the model to be printed is divided into multiple segments according to the slice file, and each segment contains multiple layers of the model; The recommended printing pattern is determined based on the similarity between each segment model and / or each layer model; The printing of the model to be printed is performed according to the determined recommended printing mode.

2. The method according to claim 1, characterized in that, The process of determining the recommended printing mode based on the similarity between each segment model and / or each layer model includes: Based on the layer data comparison method, the first layer similarity between adjacent layer models of each segment model is determined sequentially; Based on the first layer of similarity, determine the intra-segment similarity value of each segment model; If it is determined that the intra-segment similarity value of a certain model segment is greater than a first preset threshold, then the recommended printing mode for the model to be printed is determined to be the normal printing mode.

3. The method according to claim 2, characterized in that, The layer-based data comparison method sequentially determines the first-layer similarity between adjacent layers of each model segment, including: According to a preset order, the model of each layer of a segment model is traversed, and the similarity of the image data between the traversed layer model and its adjacent next layer model is calculated as the first layer similarity. The image data includes one or more of the following: image size, image boundary, and boundary coordinates. The step of determining the intra-segment similarity value of each segment model based on the first layer of similarity includes: If the first-layer similarity between a layer model and its adjacent next-layer model is greater than the first preset threshold and less than the second preset threshold, then the intra-segment similarity value is incremented by one, wherein the first preset threshold is less than the second preset threshold. When it is determined that the next layer model of the current layer model is the last layer model of the segment model, the inverse of the layer model of the segment model is added to the intra-segment similarity value to obtain the intra-segment similarity value of the segment model.

4. The method according to claim 2, characterized in that, The method of determining the recommended printing mode based on the similarity between each segment model and / or each layer model also includes: If it is determined that the intra-segment similarity value of each segment model is less than or equal to the first preset threshold, then the second layer similarity between multiple sets of corresponding layer models between each pair of adjacent segment models is determined sequentially based on the layer data comparison method. Based on the obtained multiple second-layer similarities, the first segment similarity value of each adjacent segment model is determined; If it is determined that the similarity value between the first segments of a certain adjacent segment model is greater than the second preset threshold, then the recommended printing mode for the model to be printed is determined to be the high-speed printing mode. Wherein, the first preset threshold is less than the second preset threshold; If it is determined that the first inter-segment similarity value of each adjacent segment model is less than or equal to the second preset threshold, then the second inter-segment similarity value of each adjacent segment model is determined based on the first inter-segment similarity value. If the similarity value between the second segments of each adjacent segment model is greater than the second preset threshold, then the recommended printing mode for the model to be printed is determined to be the ultra-high-speed printing mode; otherwise, the recommended printing mode for the model to be printed is determined to be the high-speed printing mode.

5. The method according to claim 4, characterized in that, The method of determining the second-layer similarity between multiple sets of corresponding layer models between every two adjacent model segments, based on layer data comparison, includes: According to a preset order, each segment of the model to be printed is traversed. For a segment model that is traversed, the second layer similarity of the first image data of the multiple layer models of the segment model and the second image data of the corresponding layer model of the next segment model is calculated. The step of determining the first segment similarity value of each adjacent segment model based on the obtained multiple second-layer similarities includes: If the second layer similarity between a segment model and a corresponding layer model of the next segment model is greater than the second preset threshold, then the first segment similarity value is incremented by one.

6. The method according to claim 4, characterized in that, The step of determining the second inter-segment similarity value of each adjacent segment model based on the first inter-segment similarity value includes: The second inter-segment similarity value is obtained by summing the reciprocal of the number of segment models to the first inter-segment similarity value.

7. The method according to claim 1, characterized in that, If the recommended printing mode is the high-speed printing mode; The step of printing the model to be printed according to the determined recommended printing mode includes: The file information of the slice file is parsed, including the model parameters, image data, and exposure parameters of the model to be printed; Set the automatic lifting parameters according to the model parameters; The image data is analyzed, and the model to be printed is exposed and printed layer by layer according to the exposure parameters. After any layer of the model is printed, the print head of the 3D printer is raised to the thickness indicated by the automatic lifting parameters, and the printing of the next layer of the model continues until the printing of the model to be printed is completed. If the recommended printing mode is the ultra-high-speed printing mode; the step of printing the model to be printed according to the determined recommended printing mode includes: The file information of the slice file is parsed, including the model parameters, image data, and exposure parameters of the model to be printed; Set the automatic lifting parameters according to the model parameters; The image data is analyzed, and the model to be printed is exposed and printed layer by layer according to the exposure parameters and the image similarity between adjacent layers. After printing any layer, the print head of the 3D printer is raised to the thickness indicated by the automatic lifting parameter, and the printing of the next layer continues until the printing of the model to be printed is completed. For a target layer model, if the image similarity between the target layer model and the previous layer model is greater than a preset third threshold, then the image data of the previous layer model is used to expose and print the target layer model; otherwise, the image data of the target layer model is used to expose and print the target layer model.

8. The method according to claim 1, characterized in that, The method further includes: If the specified printing mode of the model to be printed is determined to be the intelligent exposure mode based on the slice file, then the current exposure image data is read layer by layer, and the exposure image data includes multiple image blocks; Determine whether the exposed image data is a solid image. If so, determine the exposure parameters of each image block based on the light averaging algorithm. If not, perform completion processing on the exposed image data and determine the exposure parameters of each image block after completion based on the light averaging algorithm. Based on the exposure parameters, the model to be printed is exposed and printed layer by layer.

9. A 3D printer, comprising: processor; as well as A memory configured to store computer-executable instructions, characterized in that, when executed, the executable instructions cause the processor to perform the method according to any one of claims 1 to 8.

10. A computer-readable storage medium storing one or more programs, characterized in that, When the one or more programs are executed by a 3D printer that includes multiple applications, the 3D printer performs the method according to any one of claims 1 to 8.

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