A method and system for monitoring automatic alignment printing effect of a digital printer

Abstract

The present invention discloses a method and system for monitoring the automatic alignment printing effect of a digital printer, and relates to the technical field of digital printers. The system comprises an image acquisition subsystem, a visual AI recognition subsystem and a printing monitoring subsystem; wherein the image acquisition subsystem has a built-in image acquisition module for acquiring the target workpiece image on the printer table; the technical key points are as follows: by configuring the visual AI recognition subsystem, automatic alignment printing of the workpiece is realized, which saves the time of workers in arranging materials and drawing, reduces production costs, improves production efficiency, and enhances the quality of product printing, and is particularly suitable for the printing of small and special-shaped products, thereby improving the intelligence of the digital printer; finally, through the comprehensive optimization of the printing monitoring subsystem, not only the printing quality and efficiency are improved, but also the production cost and maintenance cost are reduced, providing strong technical support for the wide application of printing technology.

Description

Technical Field

[0001] The invention relates to the technical field of digital printers, and in particular to a method and system for automatically monitoring the printing effect of a digital printer. Background Art

[0002] Digital printers are also known as universal flatbed printers. By inputting patterns into a computer, they can print on the surfaces of soft or hard objects of any material. According to the process, they can be divided into UV flatbed printers and digital direct-injection printers. UV printers use UV hard ink and are generally printed on products with hard surfaces, such as metal, ceramics, crystal, glass, acrylic, stone, PVC, plastic, toys, U disks, cloth, wood, silicone, leather, etc. Digital direct-injection printers use water-based ink and are generally printed on soft products, such as clothes and cloth. Digital printers can reduce costs and labor for product production and improve efficiency, because digital printers do not require film and plate making, full-color one-time imaging, and zero scrap rate. Digital printer high-tech products completely replace traditional processes such as silk screen printing, pad printing, and transfer printing, and are environmentally friendly products.

[0003] Digital printers need to print patterns at the specified position of the product. In the traditional method, the product is placed at the specified coordinate position on the table through the jig. At the same time, the image file to be printed is typeset into a print map according to the corresponding coordinate position to achieve positioning printing. Due to the manual material placement method through the jig, it takes a long time to place the material and make the map, and the effective printing time is relatively low, resulting in high production costs. On the other hand, the production of jigs requires additional costs, and in order to facilitate loading and unloading, the jigs have a certain gap, and the product position accuracy is not high, resulting in high product printing costs and low printing quality.

[0004] With the development of visual AI technology, by configuring a visual AI recognition subsystem on a digital printer, products can be placed arbitrarily, the software automatically identifies and locates, and automatically generates the corresponding print map, achieving precise positioning and printing, and achieving efficient, low-cost, and accurate printing. It has great advantages in printing special-shaped small-sized workpieces; although visual AI positioning is used in alignment printing to solve some problems caused by printing positioning, in the subsequent printing process, the printing effect of the actual product still needs further testing or evaluation. Conventionally, when testing the printing effect, a comprehensive evaluation of the printing effect is usually performed after printing, whether before or after printing. It is impossible to conduct more detailed inspections during printing. In order to obtain more accurate and comprehensive evaluation results and avoid poor evaluation results as much as possible, a more detailed monitoring system needs to be designed to deal with concrete scenarios; for example: after printing a pattern on the surface of product A, due to insufficient spray thickness at a certain position or point, the printed material cannot adhere or becomes rough due to insufficient adhesion. At this time, secondary processing is required for this position or point. Usually, the secondary processing is performed on product A after a complete set of printing operations. If it is not handled properly at this time, it will greatly affect the printing quality, and it is also not conducive to the subsequent printing effect evaluation operation. Summary of the invention

[0005] 1. Technical issues to be resolved

[0006] In view of the shortcomings of the prior art, the present invention provides a method and system for automatically monitoring the printing effect of a digital printer. Through the comprehensive optimization of the printing monitoring subsystem, not only the printing quality and efficiency are improved, but also the production cost and maintenance cost are reduced, which provides strong technical support for the widespread application of printing technology and solves the problems raised in the background technology.

[0007] (II) Technical solution

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0009] A digital printer automatic alignment printing effect monitoring system, the system includes an image acquisition subsystem, a visual AI recognition subsystem and a printing monitoring subsystem;

[0010] Among them, the image acquisition subsystem has a built-in image acquisition module to obtain the target workpiece image on the printer table;

[0011] The visual AI recognition subsystem processes the target workpiece image and then packages and outputs the image data to be printed. The visual AI recognition subsystem has built-in image stitching module, product modeling module, image recognition module, image rendering module and image output module which operate in sequence. The features are:

[0012] A printing monitoring subsystem, which has a built-in printing monitoring module, and the printing monitoring module includes a primary monitoring unit, a secondary monitoring unit and a final monitoring unit that operate in sequence;

[0013] Among them, the primary supervision unit uses machine vision technology to perform random identification before printing, and selects the selected area of ​​the test workpiece on the table for proofing confirmation. After the selected area is printed in the proofing pattern, the image processing software is used to analyze the photos of the selected area;

[0014] If the analysis results show no abnormality, the secondary supervision unit is operated;

[0015] If the analysis results are abnormal, the adjustment strategy is implemented;

[0016] The secondary supervision unit determines whether the size of the packaged image data exceeds a set value;

[0017] If it exceeds, the group export strategy is executed during the printing process, and the supervision adjustment mechanism is executed on the area after each group printing, and whether to trigger the correction action is determined based on the supervision result; if it does not exceed, the established printing strategy is executed during the printing process;

[0018] The ultimate supervision unit, after the registration printing is completed, builds an evaluation calculation model based on the evaluation parameters of the printing pattern to generate an overall effect evaluation value. The overall effect evaluation value is positively correlated with the frequency value of the maintenance and adjustment of the corresponding printing equipment.

[0019] Furthermore, in the visual AI recognition subsystem, the process of processing the target workpiece image is as follows:

[0020] The image stitching module converts the target workpiece image through calibration to obtain an image of the actual size relative to the printer table, and stitches it into an image of the complete printing table;

[0021] The product modeling module selects any product image and selects the characteristic contour line of the product image for product identification and positioning; the image file to be printed is placed on the current product image to determine the position information of the image file printed on the target workpiece, and the product template is generated after saving;

[0022] The image recognition module uses visual AI features to identify matching products based on product templates and obtain product type and location data of the target workpiece;

[0023] The image rendering module renders the image file to be printed at the position of each target workpiece by identifying the product type and position data, and generates the image data to be printed on the entire work surface;

[0024] The image output module packages the rendered image data and outputs it.

[0025] Further, the process of analyzing the photos of the selected area using image processing software is as follows:

[0026] Import the photos of the selected area into the image processing software for standard parameter analysis. The standard parameters include pixel value, contrast and brightness. When any standard parameter exceeds the corresponding standard value, it means that the analysis result is abnormal. When none of the standard parameters exceeds the corresponding standard value, it means that the analysis result is normal.

[0027] Furthermore, the content of executing the adjustment strategy is: replacing the same type of printing equipment and re-operating the visual AI recognition subsystem.

[0028] Furthermore, the process of executing the group export strategy is as follows:

[0029] Image segmentation: Use image editing software to segment the packaged image data into several small images, and save each segmented small image file;

[0030] Thread processing: Use multi-threading of programming language to process export and printing tasks at the same time; after the export of the current group of small pictures is completed, the printing task of this group is started immediately, and the export of the next group of small pictures is started at the same time.

[0031] Furthermore, the process of implementing the supervision adjustment mechanism for the area after each group printing is as follows:

[0032] Before printing the small image to the corresponding area, a 3D scanner is used to obtain the 3D data of the target workpiece surface, and a 3D software tool is used to analyze the 3D data, identify and calculate the curvature data of the target workpiece surface, and map the curvature data to the corresponding small image according to the correspondence between the several small images divided into the packaged image data and the position of the target workpiece. According to the curvature data of each small image, the printing priority index of the corresponding small image is weightedly calculated. The printing priority index is positively correlated with the printing priority, and the thread processing process in the grouping export strategy is fed back and adjusted according to the printing priority.

[0033] After each small image is printed onto the surface of the target workpiece, a printing area is obtained. The printing data of the corresponding printing area is collected and calculated in sequence. The generated printing effect evaluation value is compared with the preset standard index to obtain the supervision result.

[0034] Furthermore, whether to trigger corrective actions is determined based on the regulatory results:

[0035] If the supervision result is: the printing effect evaluation value of the corresponding printing area exceeds the standard index, no correction action will be triggered;

[0036] If the supervision result is: the printing effect evaluation value of the corresponding printing area does not exceed the standard index, the correction action is triggered;

[0037] The curvature data includes: maximum curvature and curvature quantity;

[0038] The weighted calculation of the printing priority index of the corresponding small image is based on the formula: Lm=A1*Cmax+A2*Sz; where A1 and A2 are weight coefficients, and A1+A2=1, Lm represents the printing priority index, Cmax represents the maximum curvature, and Sz represents the number of curvatures;

[0039] Printing data includes: uniformity index and surface flatness;

[0040] The print quality evaluation value is generated based on the following formula:

[0041] ;

[0042] In the formula, represents the printing effect evaluation value corresponding to the i-th printing area, and i=1, 2, ..., n, n is a positive integer, i represents the number of the corresponding printing area, α and β are adjustment coefficients, and α>0, β>0, U represents the uniformity index, and R represents the surface flatness.

[0043] Furthermore, the triggered correction action is: adding another layer of printing on the basis of the original printing area, and performing the operation of adjusting the extrusion speed on the next printing area; the process of performing the operation of adjusting the extrusion speed is as follows:

[0044] According to the original extrusion speed of the printing device, combined with the difference between the printing effect evaluation value corresponding to the current printing area and the standard index, a function formula is established to calculate the estimated value of the adjusted extrusion speed:

[0045] ;

[0046] In the formula, represents the estimated value of the adjusted extrusion speed, Vr represents the original extrusion speed of the printing device, Ko represents the adjustment index, and λ represents an adjustment coefficient, with a value range of 0< λ <1. , Indicates the difference between the printing effect evaluation value corresponding to the current printing area and the standard index, and Bz represents the standard index; Indicates the threshold parameter, the value range is: 1 < .

[0047] Further, the printed pattern is: a pattern formed after all the small images are printed at corresponding positions of the target workpiece or a pattern obtained on the target workpiece after executing a predetermined printing strategy;

[0048] If the group export strategy is executed to complete printing, the evaluation parameters based on the printed pattern include: the maximum difference of all areas after the triggering correction action, the printing data and the color accuracy;

[0049] The evaluation calculation model is as follows:

[0050] ;

[0051] In the formula, Represents the overall effect evaluation value, C1 represents the adjustment coefficient, and the value range is: , It indicates the maximum difference of all areas after triggering the correction action, F indicates the color accuracy, Uo, Ro and Fo are the reference values ​​of uniformity index, surface flatness and color accuracy respectively;

[0052] If the established printing strategy is executed and printing is completed, the evaluation parameters of the printed pattern include: printing data and color accuracy; the evaluation calculation model is built as follows:

[0053] ;

[0054] In the formula, C2 represents the adjustment parameter, and its value range is: 0< C2<1.

[0055] A method for monitoring the automatic alignment printing effect of a digital printer comprises the following steps:

[0056] S1, obtaining the target workpiece image on the printer table;

[0057] S2, after processing the target workpiece image, the image data to be printed is packaged and output;

[0058] S3. Before printing, use machine vision technology to perform random recognition and select the selected area of ​​the test workpiece on the table for proofing confirmation. After the selected area is printed in the proofing pattern, use image processing software to analyze the photos of the selected area;

[0059] If the analysis result is normal, execute S4;

[0060] If the analysis results are abnormal, the adjustment strategy is implemented;

[0061] S4, judging whether the size of the packaged image data exceeds the set value;

[0062] If it exceeds, the group export strategy is executed during the printing process, and the supervision adjustment mechanism is executed on the area after each group printing, and whether to trigger the correction action is determined based on the supervision result; if it does not exceed, the established printing strategy is executed during the printing process;

[0063] S5. After the registration printing is completed, an evaluation calculation model is built according to the evaluation parameters of the printing pattern to generate an overall effect evaluation value. The overall effect evaluation value is positively correlated with the frequency value of the maintenance and adjustment of the corresponding printing device.

[0064] (III) Beneficial effects

[0065] The present invention provides a method and system for monitoring the automatic alignment printing effect of a digital printer, which has the following beneficial effects:

[0066] (1) This solution realizes automatic alignment printing of workpieces by configuring a visual AI recognition subsystem, avoiding the production of tooling and fixtures, saving workers' time in placing materials and drawing, reducing production costs, improving production efficiency, and improving the quality of product printing. It is particularly suitable for printing small and special-shaped products, thereby improving the intelligence of digital printers;

[0067] (2) This solution achieves dynamic monitoring and optimization of printing quality during the printing process by introducing a supervision and adjustment mechanism. First, through 3D scanning and curvature data analysis, the printing priority is adjusted in advance to ensure that printing on complex curved surfaces can give priority to areas with large curvatures and many changes, thereby improving the accuracy and adaptability of printing. Second, after printing, the printing effect is evaluated in real time by calculating printing data such as uniformity index and surface flatness. After comparing with the preset standards, it is decided whether to trigger correction actions. This feedback mechanism effectively reduces printing defects and improves printing quality. Overall, this technical solution not only improves printing efficiency and accuracy, but also significantly enhances the overall quality and consistency of printed products.

[0068] (3) This solution operates in stages when testing the printing effect;

[0069] Before printing, machine vision technology and image processing software are used to accurately identify and analyze the selected areas of the test workpiece before printing, effectively preventing printing quality problems caused by improper printing parameters, and being able to promptly discover and correct potential problems to ensure that the preparation state before printing is optimal;

[0070] When printing, the printing strategy is adjusted dynamically by judging the size of the packaged image data. When the data is too large, a group export strategy is adopted, combined with multi-threaded processing technology, to achieve an efficient working mode of exporting and printing at the same time, significantly improving the printing efficiency. At the same time, by implementing a supervision and adjustment mechanism for the area after each group printing, the printing priority and extrusion speed are flexibly adjusted according to the curvature data of the target workpiece surface and the printing effect evaluation value, ensuring the stability and consistency of the printing quality and reducing the printing defects caused by parameter fluctuations during the printing process.

[0071] After printing, through a comprehensive evaluation of the printed pattern, including multiple dimensions such as the maximum regional difference after the correction action, printing data, and color accuracy, a targeted and scientific evaluation calculation model is constructed under the execution of different strategies. This model can specifically and accurately reflect the overall quality of the printing effect, and provides an objective basis for the inspection and adjustment of the printing equipment. By setting a positive correlation between the overall effect evaluation value and the inspection and adjustment frequency, the present invention realizes the intelligent management of the printing equipment, extends the equipment service life, and reduces the maintenance cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 It is a modular schematic diagram of the image acquisition subsystem and the visual AI recognition subsystem in the present invention;

[0073] Figure 2 It is a modular schematic diagram of the printing monitoring subsystem in the present invention;

[0074] Figure 3 A flowchart for creating a product template in the present invention;

[0075] Figure 4 This is a flow chart of the image acquisition subsystem and the visual AI recognition subsystem in the present invention in operation;

[0076] Figure 5 This is a schematic diagram of the installation of a high-definition camera in the present invention. DETAILED DESCRIPTION

[0077] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0078] Research and development concept:

[0079] When using a digital printer, the pattern needs to be printed at the specified position of the product. The traditional method is:

[0080] The product is placed at the coordinate position specified on the table through the jig, and the image file to be printed is typeset into a print map according to the corresponding coordinate position to achieve positioning printing; due to the manual material placement through the jig, it takes a long time to place the material and make the map, and the effective printing time is relatively low, resulting in high production costs; on the other hand, the production of jigs requires additional costs, and in order to facilitate loading and unloading, the jigs have a certain gap, and the position accuracy of the product is not high, resulting in high printing costs and low printing quality; but with the development of visual AI technology, by configuring the visual AI recognition subsystem on the digital printer, the product can be placed arbitrarily, the software automatically identifies and locates, and automatically generates the corresponding print map, to achieve precise positioning printing, and achieve efficient, low-cost, and accurate printing, which has great advantages in printing special-shaped small-sized workpieces;

[0081] Although visual AI positioning is used during registration printing to solve some problems caused by printing positioning, the printing effect of the actual product still needs further testing or evaluation in the subsequent printing process. Conventionally, when testing the printing effect, a comprehensive evaluation is usually carried out after printing. No more detailed testing can be performed before or during printing. In order to obtain more accurate and comprehensive evaluation results and avoid poor evaluation results as much as possible, a more detailed monitoring system needs to be designed to deal with concrete scenarios.

[0082] Example 1

[0083] See also Figures 1 to 5 , this embodiment provides a digital printer automatic alignment printing effect monitoring system, the system is composed of an image acquisition subsystem, a visual AI recognition subsystem and a printing monitoring subsystem; wherein the image acquisition subsystem belongs to the hardware composition of the whole system, and the visual AI recognition subsystem and the printing monitoring subsystem belong to the software composition of the whole system;

[0084] Image acquisition subsystem:

[0085] It has a built-in image acquisition module to obtain the target workpiece image on the printer table;

[0086] Among them, the image acquisition module includes a high-definition camera, a lens, an LED light source, and a camera mounting bracket;

[0087] High-definition camera and lens: The high-definition camera scans and photographs the workpiece on the printer table through the lens to obtain high-definition photos;

[0088] LED light source: used to fill in the light of the target workpiece on the table during high-speed scanning. Through the fill in light, a bright enough picture and a clear enough outline of the target workpiece can be obtained;

[0089] The functional design of the entire image acquisition module is as follows: responsible for fast and high-quality image acquisition of the target workpiece before printing, providing basic data for subsequent image processing and analysis;

[0090] It should be noted that a high-definition camera for photographing and scanning is installed on the digital printer to realize photographing and scanning of the workpiece (i.e., the target workpiece) on the printing table. The scanning camera can be of various types;

[0091] Method 1 is the high-speed shooting method, that is, a high-definition industrial area array camera is installed on the top of the table to capture the image of the entire table at one time; Method 2 is the beam scanning method, a CIS scanning camera is installed under the X beam of the digital printer, and the image of the entire table is captured through motion scanning in the Y direction; Method 3 is the head scanning method, a high-definition industrial linear array camera is installed on the head of the printing carriage, and the image of the entire table is captured through multiple motion scanning in the X direction.

[0092] Visual AI recognition subsystem:

[0093] It has built-in image stitching module, product modeling module, image recognition module, image rendering module and image output module which operate in sequence;

[0094] Among them, the image stitching module converts the target workpiece image through calibration to obtain an image of the actual size relative to the printer table, and stitches it into an image of the complete printing table;

[0095] The contents of the calibration conversion are as follows:

[0096] ① Use a digital printer to print the X and Y scales on the table according to the maximum working range of the printer. The camera scans the table according to the maximum scanning range to obtain the printed scale image. Observe the range of the X and Y scales in the image to confirm the common working range of the printer and camera scanning.

[0097] ②Within the common working range of the printer and the high-definition camera scanning, the visual AI software is used to automatically generate a calibration plate pattern. The calibration plate pattern is a pattern of small dots with equal spacing in the X and Y directions, and the printer prints the calibration plate pattern;

[0098] ③ The high-definition camera scans and prints the calibration plate pattern. The visual AI software reads the scanned calibration plate pattern, identifies the center coordinates of each small dot, and performs corresponding processing with the theoretical coordinates generated by the visual AI software to generate calibration data; the calibration data is the correspondence between the visual coordinates and the printer coordinates;

[0099] The product modeling module selects any product image and selects the characteristic contour line of the product image for product identification and positioning; the image file to be printed is placed on the current product image to determine the position information of the image file to be printed on the target workpiece, and the product template is generated after saving;

[0100] Among them, each product needs to establish a product template when it is produced;

[0101] When modeling, enter the template name, scan the product photo first, then select some characteristic contour lines on the product photo for visual AI recognition and positioning, then put the pattern to be printed on the product photo, save it, and generate the template data;

[0102] It should be noted that to obtain the characteristic contour line of the product image, the following steps can be taken:

[0103] Image preprocessing: Use Gaussian filtering and other methods to remove noise and improve image quality; Edge detection: Apply edge detection algorithms such as Canny and Sobel to identify intensity changes or color changes in the image and obtain edge pixels; Edge connection and closure: Connect edge pixels to form a continuous boundary line, and perform a closing operation to repair broken or missing edges; Contour extraction: Extract the contour of the object from the connected edge lines to obtain the characteristic contour line of the product; These steps can be implemented based on image processing libraries such as OpenCV;

[0104] The image recognition module uses visual AI (i.e., visual AI software, which should use visual AI technology) feature recognition to match products based on product templates and obtain product type and location data of the target workpiece;

[0105] When performing template matching, the extracted features are compared with the features in the pre-stored product template (which can be a template library), and the most matching product type is determined by calculating the similarity or distance measurement; the product template should contain standard images of various products and their corresponding feature descriptions; after a successful match, the precise position of the target workpiece in the image (such as coordinates, angle, etc.) is further obtained to provide accurate position information for subsequent image rendering;

[0106] The image rendering module renders the image file to be printed at the position of each target workpiece by identifying the product type and position data, and generates the image data to be printed on the entire work surface;

[0107] The rendering process is as follows:

[0108] Image file preparation: According to the identified product type, the corresponding image files are selected from the database. These files may include images of different resolutions and formats; Position mapping: Using the identified position data, the image file is mapped to the corresponding position of the work surface, which involves image scaling, rotation and perspective transformation operations to ensure that the image fits the workpiece perfectly; Synthetic rendering: All image files are synthesized into a large image according to the mapping relationship. This image represents the image to be printed on the entire work surface. When synthesizing, the overlap and occlusion between images must be considered to ensure the visual effect of the final image;

[0109] The image output module packages the rendered image data and outputs it to the printing device;

[0110] The image data is packaged into a tif or pdf file format for output, saved to a local file, or directly sent to a printer for printing; the printing device in this embodiment refers to a digital printer;

[0111] To summarize, during production, select the corresponding product template and enter production; first scan the countertop photo. After the scan is completed, the visual AI software automatically identifies and matches the product based on the characteristic contour of the template, locates the precise position of the product, and then automatically generates a printing pattern for the entire countertop based on the position in the template. The visual AI software sends the generated printing pattern to the digital printer for printing, so that each product can be accurately printed with the pattern that needs to be printed.

[0112] Specifically, this system uses visual AI recognition and positioning technology to achieve accurate positioning and printing of products placed arbitrarily on the work surface, replacing the fixed coordinate printing method of tooling fixtures. The visual AI positioning software supports a variety of photo scanning methods, including high-angle scanning, beam scanning, and head scanning. This system can support multiple workpieces and joint production, that is, it can simultaneously identify and locate multiple workpieces on the table to achieve accurate printing. The image formats supported by the system include: TIF images and PDF vector images. This system uses the method of printing and scanning X, Y scales to determine the common working range of the printer and camera, and automatically generates calibration plate patterns. After printing and scanning the calibration plate patterns, the software realizes automatic calibration.

[0113] This system integrates the mainstream digital printers on the market to realize communication control and printing control of the printers;

[0114] This system can have various functions that facilitate production; template list function, according to template information, search and find templates, so that users can find previously produced templates and produce them again; production counting function, so that users can count the production quantity of each product; area scanning function, when users only need to produce a small number of products, they only need to quickly take pictures and scan part of the table area to achieve rapid generation; automatic cropping function, when a small number of products are produced, when the software exports the print image, the blank image behind the table can be not exported, so as to achieve rapid export of the print image; frame selection printing function, when users print and produce new products, they can frame some workpieces on the table for proofing confirmation first; group export function, for large models, the pictures that need to be exported are large and the export is slow, the software can export pictures in groups, realize the function of printing while exporting, realize rapid start of printing, and improve production efficiency;

[0115] Specifically, the digital printer, by configuring a visual AI recognition subsystem, achieves automatic alignment printing of workpieces, avoids the production of tooling and fixtures, saves workers' time in arranging materials and drawing, reduces production costs, improves production efficiency, and enhances the quality of product printing. It is particularly suitable for printing small and special-shaped products, thereby improving the intelligence of digital printers.

[0116] Print monitoring subsystem:

[0117] It has a built-in printing monitoring module, and the printing monitoring module includes a primary monitoring unit, a secondary monitoring unit and a final monitoring unit that operate in sequence; wherein the primary monitoring unit is applied to the period before printing, the secondary monitoring unit is applied to the period during printing, and the final monitoring unit is applied to the period after printing;

[0118] The primary supervision unit uses machine vision technology to perform random identification before printing, and selects the selected area of ​​the test workpiece on the table for proofing confirmation. After the selected area is printed in the proofing pattern, the image processing software is used to analyze the photos of the selected area;

[0119] If the analysis results show no abnormality, the secondary supervision unit is operated;

[0120] If there are any abnormalities in the analysis results, an adjustment strategy will be implemented, the same type of printing equipment will be replaced, and the visual AI recognition subsystem will be re-operated. The reason for re-operating the visual AI recognition subsystem is to ensure that after replacing the printing equipment, the machine vision system can accurately identify and select the new test workpiece selected area to avoid recognition errors caused by equipment replacement, thereby ensuring the accuracy of subsequent proofing confirmation and image analysis.

[0121] The process of analyzing the photos of the selected area using image processing software is as follows:

[0122] Import the photos of the selected area into the image processing software for standard parameter analysis. The standard parameters include pixel value, contrast and brightness. When any standard parameter exceeds the corresponding standard value, it means that the analysis result is abnormal. When none of the standard parameters exceeds the corresponding standard value, it means that the analysis result is normal.

[0123] It should be noted that the pixel value corresponds to the setting of the standard value:

[0124] Set to 240 DPI (dots per inch); this value is determined based on the sophistication of the product design and the required printing resolution. For products that require high-definition details, such as patterns and text on mobile phone cases, a higher DPI value can ensure the clarity and accuracy of the printing effect; comparison process: compare the pixel value of the photo of the selected area with the DPI value of the actual printing effect. If the pixel value of the photo is lower than 240 DPI, it may mean that the printing resolution is insufficient, resulting in blurred or lost details, so there is an abnormality.

[0125] Contrast setting corresponding to standard value:

[0126] Set to 50% (the range can be adjusted according to actual conditions). Contrast is a parameter that measures the difference between light and dark areas in an image, which is crucial to ensuring the clarity and readability of the print. Comparison process: compare the contrast value of the selected area photo with the standard value. If the contrast is lower than 50%, it may mean that the difference between light and dark areas in the image is not obvious, resulting in unclear or difficult to recognize print effects, so there is an abnormality.

[0127] Brightness corresponding to standard value setting:

[0128] Set to 60% (the range can be adjusted according to the actual light source and environmental conditions). Brightness is a parameter that measures the overall brightness of the image, which is essential to ensure the uniformity of the printing effect and the accuracy of the color. Comparison process: compare the brightness value of the photo in the selected area with the standard value. If the brightness is lower than 60%, it may mean that the image is dark as a whole, resulting in the printing effect not being bright enough or the color being distorted, so there is an abnormality.

[0129] Standard value setting basis:

[0130] Product design requirements: The setting of standard values ​​should be based on the sophistication of product design and the required printing effect; for example, for products that require high-definition details, a higher DPI value should be set; Printing equipment performance: The performance of the printing equipment will also affect the setting of standard values. Different models of printing equipment may differ in resolution, contrast, and brightness. Therefore, the standard value needs to be adjusted according to the actual printing equipment used; Actual production environment: Factors such as light source and background in the actual production environment may also affect the setting of standard values. For example, in a darker environment, the standard value of brightness may need to be increased to ensure the clarity and readability of the printing effect.

[0131] The secondary supervision unit determines whether the size of the packaged image data exceeds a set value;

[0132] If it exceeds, it means that the packaged image data is large, and the group export strategy is executed during the printing process, and the supervision adjustment mechanism is executed on the area after each group printing, and whether to trigger the correction action is determined based on the supervision result; if it does not exceed, it means that the packaged image data is normal, and the established printing strategy is executed during the printing process, that is, normal printing operation, and the group export strategy is not executed;

[0133] The set value is set according to the actual situation. When the size of the packaged image data exceeds the set value, the export efficiency will be slow. Usually, the corresponding printing device is tested, the size of the packaged image data is continuously increased, and then the export efficiency is observed to obtain the corresponding curve graph. If the export efficiency is suddenly observed to be significantly reduced under a certain image data size, it means that the image data size is the set value.

[0134] The process of executing the group export policy is as follows:

[0135] Image segmentation: Use image editing software (such as Photoshop, GIMP, Preview (included in macOS)) to segment the packaged image data into several small images. This usually involves selecting an appropriate segmentation method (such as by grid, by specific area, etc.) and saving each segmented small image file;

[0136] Thread processing: Use the multi-threading or asynchronous function of the programming language to process export and print tasks at the same time; when a group of small pictures is exported, start the printing task of the group immediately, and start the export of the next group of small pictures at the same time;

[0137] Some examples of functions when executing group export strategies (Python pseudo code):

[0138] Suppose we have a list of images and use Python's threading library to implement multithreaded processing;

[0139] import threading

[0140] import time

[0141] # Assume this is our image list

[0142] images = ['image1.jpg', 'image2.jpg', ..., 'imageN.jpg']

[0143] # Export function, simulate the image export process

[0144] def export_images(image_group):

[0145] for image in image_group:

[0146] print(f"Exporting {image}...")

[0147] time.sleep(1) #Simulation export time

[0148] print(f"Exported {len(image_group)} images.")

[0149] # Print function, simulate the image printing process

[0150] def print_images(image_group):

[0151] for image in image_group:

[0152] print(f"Printing {image}...")

[0153] time.sleep(2) # simulate printing time

[0154] print(f"Printed {len(image_group)} images.")

[0155] # Group size can be adjusted according to actual situation

[0156] group_size = 5

[0157] # Grouping

[0158] image_groups = group_images(images, group_size)

[0159] # Thread list

[0160] threads = []

[0161] # Traverse each group of pictures, create and start export and print threads

[0162] for group in image_groups:

[0163] # Create export thread

[0164] export_thread = threading.Thread(target=export_images, args=(group,))

[0165] export_thread.start()

[0166] threads.append(export_thread)

[0167] #Wait for the export thread to complete before creating the print thread

[0168] export_thread.join()

[0169] # Create a printing thread

[0170] print_thread = threading.Thread(target=print_images, args=(group,))

[0171] print_thread.start()

[0172] threads.append(print_thread)

[0173] # Wait for all threads to complete

[0174] for thread in threads:

[0175] thread.join()

[0176] print("All images have been exported and printed.");

[0177] Notes: Thread safety: In a multi-threaded environment, ensure that access to shared resources is thread-safe; Performance optimization: According to the actual export and printing speed, adjust the group size and number of threads to achieve optimal performance; Resource release: Ensure that occupied resources such as file handles and memory are released in a timely manner after the task is completed; Through the above method, the function of exporting pictures in groups and printing while exporting can be realized, thereby improving production efficiency.

[0178] The process of implementing the supervision adjustment mechanism for the area after each group printing is as follows:

[0179] Before printing the small image to the corresponding area, a 3D scanner is used to obtain the 3D data of the target workpiece surface, and a 3D software tool is used to analyze the 3D data, identify and calculate the curvature data of the target workpiece surface, and map the curvature data to the corresponding small image according to the correspondence between the several small images divided into the packaged image data and the position of the target workpiece. According to the curvature data of each small image, the printing priority index of the corresponding small image is weightedly calculated. The printing priority index is positively correlated with the printing priority, and the thread processing process in the grouping export strategy is fed back and adjusted according to the printing priority.

[0180] After each small image is printed on the surface of the target workpiece, a printing area is obtained, and the printing data of the corresponding printing area is collected and calculated in sequence. The generated printing effect evaluation value is compared with the preset standard index to obtain the supervision result;

[0181] Determine whether to trigger corrective actions based on the supervision results:

[0182] If the supervision result is: the evaluation value of the printing effect of the corresponding printing area exceeds the standard index, the correction action is not triggered; if the supervision result is: the evaluation value of the printing effect of the corresponding printing area does not exceed the standard index, the correction action is triggered;

[0183] The curvature data includes: maximum curvature and curvature quantity;

[0184] The maximum curvature represents the maximum curvature of the area to which the small image belongs at the corresponding position of the target workpiece. The curvature quantity is the number of times the curvature changes or the number of extreme points of curvature in the area to which it belongs. In this embodiment, the number of times the curvature changes is used as the curvature quantity.

[0185] The printing priority index of the corresponding small picture is calculated by weighting;

[0186] The formula is: Lm=A1*Cmax+A2*Sz; where A1 and A2 are weight coefficients, and A1+A2=1, Lm represents the printing priority index, Cmax represents the maximum curvature, and Sz represents the number of curvatures;

[0187] The print priority index is positively correlated with the print priority, which means that the larger the print priority index is, the higher the print priority is, and the higher the priority of the print operation is. The thread processing process in the group export strategy is adjusted based on the print priority, so as to obtain the printing order for different small image files during thread processing;

[0188] It should be noted that the standard index is also set according to the actual situation in the same way as the above-mentioned set value, and serves as an indicator data to determine whether a corrective action needs to be triggered;

[0189] Print data includes uniformity index and surface flatness;

[0190] Among them, the uniformity index is obtained by calculating the brightness difference of a set number of areas (usually 4) in the printed area image, using image processing software to analyze the printed area image, divide the area and calculate the difference value between each area (that is, the difference between the brightness of different areas), and then extract the maximum value of the difference value as the uniformity index; surface flatness is measured by surface roughness (Ra), which is obtained by a 3D scanner or a special surface measurement tool;

[0191] The formula used to generate the print quality evaluation value is as follows:

[0192] ;

[0193] In the formula, represents the printing effect evaluation value corresponding to the i-th printing area, and i=1, 2, ..., n, n is a positive integer, i represents the number of the corresponding printing area, α and β are adjustment coefficients, and α>0, β>0, U represents the uniformity index, and R represents the surface flatness;

[0194] Logic description:

[0195] Keep the uniformity index as a positive indicator and consider its square or square root form to change its sensitivity to the final result; perform mathematical processing on the surface roughness, such as taking the reciprocal of its logarithm (1 / log(R)) or using other nonlinear functions to transform it to more accurately reflect its impact on the printing effect, and introduce one or more adjustment coefficients to adjust the relative weights of the uniformity index and surface roughness in the formula so as to make fine adjustments according to actual needs;

[0196] Specifically, the above technical solution realizes dynamic monitoring and optimization of printing quality during the printing process by introducing a supervision and adjustment mechanism; first, through three-dimensional scanning and curvature data analysis, the printing priority is adjusted in advance to ensure that printing on complex surfaces can give priority to areas with large curvatures and many changes, thereby improving the accuracy and adaptability of printing; secondly, after printing, the printing effect is evaluated in real time by calculating printing data such as uniformity index and surface flatness, and after comparing with the preset standards, it decides whether to trigger correction actions. This feedback mechanism effectively reduces printing defects and improves printing quality; in addition, the solution comprehensively considers a variety of influencing factors, such as curvature, brightness differences, surface roughness, etc., and makes the printing process more scientific and controllable through weighted calculation and formulaic evaluation; overall, the technical solution not only improves printing efficiency and accuracy, but also significantly enhances the overall quality and consistency of printed products, providing an innovative solution for the application of printing technology on complex curved workpieces.

[0197] The corrective actions triggered are:

[0198] Add another layer of printing on the basis of the original printing area, and adjust the extrusion speed on the next printing area; Add another layer of printing on the basis of the original printing settings, which can be achieved by adjusting the slice settings in the 3D printing software, such as increasing the number of layers from 20 to 21; This helps to fill in the uneven parts of the surface and improve the flatness of the surface; When adding the number of layers, it is necessary to ensure that each layer is evenly and firmly attached to the previous layer to avoid delamination or peeling;

[0199] The process of adjusting the extrusion speed is as follows:

[0200] According to the original extrusion speed of the printing device, combined with the difference between the printing effect evaluation value corresponding to the current printing area and the standard index, a function formula is established to calculate the estimated value of the adjusted extrusion speed:

[0201] ;

[0202] In the formula, It indicates the estimated value of the extrusion speed after adjustment, Vr indicates the original extrusion speed of the printing device, Ko indicates the adjustment index, and λ indicates an adjustment coefficient used to control the adjustment range. The value range is: 0< λ <1. , Indicates the difference between the printing effect evaluation value corresponding to the current printing area and the standard index, and Bz represents the standard index; Represents the threshold parameter, which is used to control the rate of change of the adjustment coefficient. The value range is: 1 < ;

[0203] Logic description:

[0204] First, the difference between the printing effect evaluation value and the standard index is calculated; then, an adjustment index is determined based on the difference, and the index can be a linear function, a nonlinear function, or a piecewise function of the difference, and the specific form depends on the relationship between the difference and the extrusion speed adjustment; finally, the adjusted extrusion speed is calculated using the adjustment index and the extrusion speed of the original printing device; in this formula, the adjustment index increases as the difference increases, but the rate of increase gradually slows down (due to the nature of the exponential function), which means that when the difference between the printing effect evaluation value and the standard index is large, the adjustment range of the extrusion speed will be larger, but as the difference decreases, the adjustment range will gradually decrease;

[0205] For example: assuming that the original extrusion speed is 60mm / s, in order to improve the surface flatness and appropriately thicken the corresponding printing area, the extrusion speed can be adjusted to 50mm / s. This can ensure that the material is more evenly distributed on the surface, while increasing a certain thickness to achieve the effect of enhancing the printing effect.

[0206] Specifically, the above technical solution realizes fine adjustment and optimization of the printing process by triggering correction actions; when it is found that the printing effect does not meet the standard, the number of printing layers is automatically increased to fill the unevenness, which significantly improves the surface flatness of the printed product; at the same time, the extrusion speed is dynamically adjusted by establishing a function formula, and the adjustment range is accurately controlled according to the difference between the printing effect evaluation value and the standard index, which not only ensures the real-time printing quality, but also avoids the waste of resources caused by excessive adjustment; this intelligent adjustment mechanism based on real-time feedback makes the printing process more flexible and controllable, and can respond quickly to changes in printing effects, effectively reducing the printing defect rate; in addition, the scheme also takes into account the nonlinear relationship of extrusion speed adjustment to ensure the accuracy and effectiveness of the adjustment strategy; overall, this technical solution not only improves the quality of printed products, but also enhances the intelligence and automation level of the printing process, providing strong support for the widespread application of printing technology.

[0207] The ultimate supervision unit, after the registration printing is completed, builds an evaluation calculation model based on the evaluation parameters of the printed pattern to generate an overall effect evaluation value;

[0208] Among them, the printing pattern is:

[0209] The pattern formed after all the small pictures are printed to the corresponding positions of the target workpiece or the pattern obtained on the target workpiece after executing the established printing strategy;

[0210] If the group export strategy is executed to complete printing, the evaluation parameters based on the printed pattern include: the maximum difference of all areas after the triggering correction action, the printing data and the color accuracy; the evaluation calculation model is built as follows:

[0211] ;

[0212] In the formula, Represents the overall effect evaluation value, C1 represents the adjustment coefficient, which is used to control the influence of the maximum difference on the overall effect. The value range is: , It indicates the maximum difference of all regions after triggering the correction action, F indicates the color accuracy, Uo, Ro and Fo are the ideal values ​​or benchmark values ​​of uniformity index, surface flatness and color accuracy respectively, which can be obtained according to the actual situation;

[0213] Logic description:

[0214] In the group export strategy, we need to pay special attention to the regional differences after the correction action, and hope that the difference is as small as possible; at the same time, we also hope that the image uniformity index, color accuracy and the inverse of surface flatness are as high as possible. In order to reflect the nonlinear relationship and mutual influence between these parameters, we can construct a composite function containing these parameters, and control the influence of all evaluation parameters on the overall effect through a unique adjustment coefficient;

[0215] It should be noted that obtaining the maximum difference usually involves two steps: first, use a 3D scanner or high-precision measuring tool to scan the pattern nodes formed after several small pictures are printed to the corresponding positions of the target workpiece, and obtain the surface data, such as roughness; then, compare the surface data with each other, and calculate the difference between any two surface data to find the maximum value, which is the maximum difference; this process requires the use of professional software tools for data analysis and processing to ensure the accuracy and reliability of the results.

[0216] If the established printing strategy is executed and printing is completed, the evaluation parameters of the printed pattern include: printing data and color accuracy; the evaluation calculation model is built as follows:

[0217] ;

[0218] In the formula, C2 represents the adjustment parameter, which is used to control the influence of surface flatness on the overall effect;

[0219] Logic description:

[0220] In the established printing strategy, we only need to focus on the uniformity index and color accuracy of the image as well as the surface flatness, introduce adjustment parameters to control the impact of surface flatness on the overall effect, and combine other evaluation parameters through a multiplication relationship;

[0221] Reasons for selecting the corresponding evaluation parameters:

[0222] For the group export strategy: the maximum difference of the area after the correction action is a unique evaluation parameter of the group export strategy, which directly reflects the effect of the correction action; by introducing a unique adjustment parameter, we can control the influence of the maximum difference on the overall effect; the uniformity index, color accuracy and surface flatness are common print quality evaluation parameters, which are incorporated into the formula through a product relationship to comprehensively evaluate the printing effect;

[0223] For the established printing strategy: In the established printing strategy, we assume that the printing process is relatively stable, so there is no need to pay special attention to the regional differences after the correction action; by introducing a unique adjustment parameter, we can control the degree of influence of surface flatness on the overall effect and reflect the interaction between surface flatness and other indicators; uniformity index and color accuracy are important evaluation indicators, which are included in the formula through a product relationship and together with surface flatness, constitute the evaluation criteria for the overall effect;

[0224] The overall effect evaluation value is positively correlated with the frequency of overhauling and adjusting the corresponding printing equipment;

[0225] For example: set the overall effect evaluation value to 10, and the frequency of maintenance and adjustment of the corresponding printing equipment to once every 2 days; then when the overall effect evaluation value is 20, the frequency of maintenance and adjustment of the corresponding printing equipment is once every 4 days, and when the overall effect evaluation value is 5, the frequency of maintenance and adjustment of the corresponding printing equipment is once every 1 day.

[0226] By adopting the above technical solution, the present invention realizes the comprehensive optimization of the printing monitoring subsystem, significantly improves the controllability, accuracy and efficiency of the printing process, and the specific technical effects are as follows:

[0227] Enhanced prediction and adjustment capabilities before printing:

[0228] The primary monitoring unit uses machine vision technology and image processing software to accurately identify and analyze the selected area of ​​the test workpiece before printing, effectively preventing printing quality problems caused by improper printing parameters. By setting and comparing standard parameters such as pixel value, contrast and brightness, the present invention can timely discover and correct potential problems, ensuring that the preparation state before printing is optimal, thereby reducing the risk of printing failure and improving the printing success rate;

[0229] Optimize the supervision and adjustment mechanism during the printing process:

[0230] The secondary supervision unit dynamically adjusts the printing strategy by judging the size of the packaged image data. When the data is too large, a group export strategy is adopted, combined with multi-threaded processing technology, to achieve an efficient working mode of exporting and printing at the same time, significantly improving the printing efficiency. At the same time, by executing the supervision adjustment mechanism on the area after each group printing, the printing priority and extrusion speed are flexibly adjusted according to the curvature data of the target workpiece surface and the printing effect evaluation value, ensuring the stability and consistency of the printing quality and reducing the printing defects caused by parameter fluctuations during the printing process.

[0231] Improve the overall effect evaluation and feedback mechanism after printing:

[0232] The ultimate supervision unit conducts a comprehensive evaluation of the printed pattern, including multiple dimensions such as the maximum regional difference after the correction action, printing data, and color accuracy, and constructs a targeted and scientific evaluation calculation model under the execution of different strategies. This model can reflect the overall quality of the printing effect in a targeted and accurate manner, and provides an objective basis for the inspection and adjustment of the printing equipment. By setting a positive correlation between the overall effect evaluation value and the inspection and adjustment frequency, the present invention realizes the intelligent management of the printing equipment, extends the equipment service life, and reduces maintenance costs.

[0233] In summary, the present invention not only improves printing quality and efficiency but also reduces production and maintenance costs through comprehensive optimization of the printing monitoring subsystem, thus providing strong technical support for the widespread application of printing technology.

[0234] Example 2

[0235] Based on Example 1, this embodiment also provides a method for monitoring the automatic alignment printing effect of a digital printer, comprising the following specific steps:

[0236] S1, obtaining the target workpiece image on the printer table;

[0237] S2, after processing the target workpiece image, the image data to be printed is packaged and output;

[0238] S3. Before printing, use machine vision technology to perform random recognition and select the selected area of ​​the test workpiece on the table for proofing confirmation. After the selected area is printed in the proofing pattern, use image processing software to analyze the photos of the selected area;

[0239] If the analysis result is normal, execute S4;

[0240] If the analysis results are abnormal, the adjustment strategy is implemented;

[0241] S4, judging whether the size of the packaged image data exceeds the set value;

[0242] If it exceeds, the group export strategy is executed during the printing process, and the supervision adjustment mechanism is executed on the area after each group printing, and whether to trigger the correction action is determined based on the supervision result; if it does not exceed, the established printing strategy is executed during the printing process;

[0243] S5. After the registration printing is completed, an evaluation calculation model is built according to the evaluation parameters of the printing pattern to generate an overall effect evaluation value. The overall effect evaluation value is positively correlated with the frequency value of the maintenance and adjustment of the corresponding printing device.

[0244] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0245] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0246] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A digital printer automatic alignment printing effect monitoring system, the system includes an image acquisition subsystem, a visual AI recognition subsystem and a printing monitoring subsystem; in, An image acquisition subsystem, which has a built-in image acquisition module to acquire the image of the target workpiece on the printer table; The visual AI recognition subsystem processes the target workpiece image and then packages and outputs the image data to be printed. The visual AI recognition subsystem has built-in image stitching module, product modeling module, image recognition module, image rendering module and image output module which operate in sequence. The features are: A printing monitoring subsystem, which has a built-in printing monitoring module, and the printing monitoring module includes a primary monitoring unit, a secondary monitoring unit and a final monitoring unit that operate in sequence; Among them, the primary supervision unit uses machine vision technology to perform random identification before printing, and selects the selected area of ​​the test workpiece on the table for proofing confirmation. After the selected area is printed in the proofing pattern, the image processing software is used to analyze the photos of the selected area; If the analysis results show no abnormality, the secondary supervision unit is operated; If the analysis results are abnormal, the adjustment strategy is implemented; The secondary supervision unit determines whether the size of the packaged image data exceeds a set value; If it exceeds, the group export strategy is executed during the printing process, and the supervision adjustment mechanism is executed on the area after each group printing, and whether to trigger the correction action is determined based on the supervision result; if it does not exceed, the established printing strategy is executed during the printing process; The triggered correction action is: add another layer of printing on the basis of the original printing area, and perform the operation of adjusting the extrusion speed on the next printing area; the process of performing the operation of adjusting the extrusion speed is as follows: According to the original extrusion speed of the printing device, combined with the difference between the printing effect evaluation value corresponding to the current printing area and the standard index, a function formula is established to calculate the estimated value of the adjusted extrusion speed: ； In the formula, It indicates the estimated value of the extrusion speed after adjustment, Vr indicates the original extrusion speed of the printing device, Ko indicates the adjustment index, and λ indicates an adjustment coefficient, with a value range of 0 < λ < 1. =Bz- , Indicates the difference between the print effect evaluation value corresponding to the current print area and the standard index, and Bz represents the standard index; Indicates the threshold parameter, the value range is: 1< ; represents the printing effect evaluation value corresponding to the i-th printing area, and i=1, 2, ..., n, n is a positive integer, and i represents the number of the corresponding printing area; The ultimate supervision unit, after the registration printing is completed, builds an evaluation calculation model based on the evaluation parameters of the printing pattern to generate an overall effect evaluation value, which is positively correlated with the frequency value of the corresponding printing equipment for maintenance and adjustment; The printed pattern is: a pattern formed after all the small images are printed at the corresponding positions of the target workpiece or a pattern obtained on the target workpiece after executing a predetermined printing strategy; If the group export strategy is executed to complete printing, the evaluation parameters based on the printed pattern include: the maximum difference of all areas after the triggering correction action, the printing data and the color accuracy; The evaluation calculation model is as follows: ； In the formula, Represents the overall effect evaluation value, C1 represents the adjustment coefficient, and the value range is: 0 < < 1, It indicates the maximum difference of all areas after triggering correction actions, F indicates color accuracy, Uo, Ro and Fo are the reference values ​​of uniformity index, surface flatness and color accuracy respectively; U indicates uniformity index, R indicates surface flatness; If the established printing strategy is executed and printing is completed, the evaluation parameters of the printed pattern include: printing data and color accuracy; the evaluation calculation model is built as follows: ； Wherein, C2 represents the adjustment parameter, and its value range is: 0 < C2 < 1.

2. The automatic alignment printing effect monitoring system for a digital printer according to claim 1, characterized in that: In the visual AI recognition subsystem, the process of processing the target workpiece image is as follows: The image stitching module converts the target workpiece image through calibration to obtain an image of the actual size relative to the printer table, and stitches it into an image of the complete printing table; The product modeling module selects any product image and selects the characteristic contour line of the product image for product identification and positioning; the image file to be printed is placed on the current product image to determine the position information of the image file to be printed on the target workpiece, and the product template is generated after saving; The image recognition module uses visual AI features to identify matching products based on product templates and obtain product type and location data of the target workpiece; The image rendering module renders the image file to be printed at the position of each target workpiece by identifying the product type and position data, and generates the image data to be printed on the entire work surface; The image output module packages the rendered image data and outputs it.

3. The automatic alignment printing effect monitoring system for a digital printer according to claim 1, characterized in that: The process of analyzing the photos of the selected area using image processing software is as follows: Import the photos of the selected area into the image processing software for standard parameter analysis. The standard parameters include pixel value, contrast and brightness. When any standard parameter exceeds the corresponding standard value, it means that the analysis result is abnormal. When none of the standard parameters exceeds the corresponding standard value, it means that the analysis result is normal.

4. The automatic alignment printing effect monitoring system for a digital printer according to claim 1, characterized in that: The content of the implementation adjustment strategy is: replace the same type of printing equipment and re-operate the visual AI recognition subsystem.

5. The automatic alignment printing effect monitoring system for a digital printer according to claim 1, characterized in that: The process of executing the group export policy is as follows: Image segmentation: Use image editing software to segment the packaged image data into several small images, and save each segmented small image file; Thread processing: Use multi-threading of programming language to process export and printing tasks at the same time; after the export of the current group of small pictures is completed, the printing task of this group is started immediately, and the export of the next group of small pictures is started at the same time.

6. The automatic alignment printing effect monitoring system for a digital printer according to claim 5, characterized in that: The process of implementing the supervision adjustment mechanism for the area after each group printing is as follows: Before printing the small image to the corresponding area, a 3D scanner is used to obtain the 3D data of the target workpiece surface, and a 3D software tool is used to analyze the 3D data, identify and calculate the curvature data of the target workpiece surface, and map the curvature data to the corresponding small image according to the correspondence between the several small images divided into the packaged image data and the position of the target workpiece. According to the curvature data of each small image, the printing priority index of the corresponding small image is weightedly calculated. The printing priority index is positively correlated with the printing priority, and the thread processing process in the grouping export strategy is fed back and adjusted according to the printing priority. After each small image is printed onto the surface of the target workpiece, a printing area is obtained. The printing data of the corresponding printing area is collected and calculated in sequence. The generated printing effect evaluation value is compared with the preset standard index to obtain the supervision result.

7. The automatic alignment printing effect monitoring system for a digital printer according to claim 6, characterized in that: Decide whether to trigger corrective actions based on the supervision results: If the supervision result is: the printing effect evaluation value of the corresponding printing area exceeds the standard index, no correction action will be triggered; If the supervision result is: the printing effect evaluation value of the corresponding printing area does not exceed the standard index, the correction action is triggered; The curvature data includes: maximum curvature and curvature quantity; The weighted calculation of the printing priority index of the corresponding small image is based on the formula: Lm=A1*Cmax+A2*Sz; where A1 and A2 are weight coefficients, and A1+A2=1, Lm represents the printing priority index, Cmax represents the maximum curvature, and Sz represents the number of curvatures; Printing data includes: uniformity index and surface flatness; The print quality evaluation value is generated based on the following formula: ； Where α and β are adjustment coefficients, and α > 0, β > 0.

8. A method for monitoring the printing effect of a digital printer automatically registering the printing, using any system described in any one of claims 1 to 7, characterized in that: The steps include: S1, obtaining the target workpiece image on the printer table; S2, after processing the target workpiece image, the image data to be printed is packaged and output; S3. Before printing, use machine vision technology to perform random recognition and select the selected area of ​​the test workpiece on the table for proofing confirmation. After the selected area is printed in the proofing pattern, use image processing software to analyze the photos of the selected area; If the analysis result is normal, execute S4; If the analysis results are abnormal, the adjustment strategy is implemented; S4, judging whether the size of the packaged image data exceeds the set value; If it exceeds, the group export strategy is executed in the state of the printing process, and the supervision adjustment mechanism is executed on the area after each group printing, and whether to trigger the correction action is determined according to the supervision result; If it is not exceeded, the established printing strategy is executed in the state of the printing process; The triggered correction action is: add another layer of printing on the basis of the original printing area, and perform the operation of adjusting the extrusion speed on the next printing area; the process of performing the operation of adjusting the extrusion speed is as follows: According to the original extrusion speed of the printing device, combined with the difference between the printing effect evaluation value corresponding to the current printing area and the standard index, a function formula is established to calculate the estimated value of the adjusted extrusion speed: ； In the formula, It indicates the estimated value of the extrusion speed after adjustment, Vr indicates the original extrusion speed of the printing device, Ko indicates the adjustment index, and λ indicates an adjustment coefficient, with a value range of 0 < λ < 1. =Bz- , Indicates the difference between the print effect evaluation value corresponding to the current print area and the standard index, and Bz represents the standard index; Indicates the threshold parameter, the value range is: 1< ; S5. After the registration printing is completed, an evaluation calculation model is built according to the evaluation parameters of the printing pattern to generate an overall effect evaluation value, and the overall effect evaluation value is positively correlated with the frequency value of the corresponding printing device for maintenance and adjustment; The printed pattern is: a pattern formed after all the small images are printed at the corresponding positions of the target workpiece or a pattern obtained on the target workpiece after executing a predetermined printing strategy; If the group export strategy is executed to complete printing, the evaluation parameters based on the printed pattern include: the maximum difference of all areas after the triggering correction action, the printing data and the color accuracy; The evaluation calculation model is as follows: ； In the formula, Represents the overall effect evaluation value, C1 represents the adjustment coefficient, and the value range is: 0 < < 1, It indicates the maximum difference of all areas after triggering the correction action, F indicates the color accuracy, Uo, Ro and Fo are the reference values ​​of uniformity index, surface flatness and color accuracy respectively; If the established printing strategy is executed and printing is completed, the evaluation parameters of the printed pattern include: printing data and color accuracy; the evaluation calculation model is built as follows: ； Wherein, C2 represents the adjustment parameter, and its value range is: 0 < C2 < 1.

Images