A printing quality monitoring intelligent processing system

Abstract

The present invention belongs to the technical field of printing production, and provides an intelligent processing system for monitoring printing quality, including: traversing each layer of coating after printing, dividing the coating area according to the dot setting radius to obtain coating sub-areas, obtaining the actual dot radius of the coating sub-area at several collection points, and comparing and analyzing with the corresponding dot setting radius to judge the coating quality after single-layer printing, obtaining the paper thickness values ​​at all collection points and processing and analyzing them to obtain the thickness influence value, judging whether the uneven paper thickness has an impact on the unqualified coating quality based on the thickness influence value, if it has an impact, obtaining the roller pad thickness adjustment value in the abnormal unit sub-area, re-printing the abnormal sub-unit area according to the roller pad adjustment value in the abnormal unit sub-area, realizing traversal monitoring of the printed coating, facilitating timely discovery of printing quality problems, and improving printing efficiency.

Description

Technical Field

[0001] The invention belongs to the technical field of printing production, in particular to an intelligent processing system for monitoring printing quality. Background Art

[0002] In the printing industry, the quality of printed products is directly related to the market competitiveness of products. Traditional manual inspection methods are not only inefficient, but also easily affected by subjective factors, making it difficult to ensure the accuracy and consistency of inspection results.

[0003] A Chinese patent application with publication number CN106485435A discloses a printing quality monitoring system, including: an acquisition unit, used to acquire and store orders, the order including the name, quantity and unit price of raw materials and / or the name, quantity and unit price of printed products; an extraction unit, connected to the acquisition unit, used to extract the name, quantity and unit price of the raw materials and / or the name, quantity and unit price of the printed products in the order; a monitoring unit, connected to the extraction unit, used to monitor the incoming quantity of qualified raw materials and / or the incoming quantity of printed products, integrate them into corresponding incoming information and output it; a recording unit, respectively connected to the monitoring unit and the extraction unit, used to record the incoming information and the unit price corresponding to the incoming information and output it.

[0004] In the prior art, during the printing process, there is a lack of multi-layer analysis of the printing, and it is impossible to ensure that when a problem occurs in a single-layer printing, the printing can be stopped in time to prevent further serious printing damage. In addition, more printing monitoring relies on manual subjective judgment, and it is impossible to accurately monitor the tiny details of the printing. Secondly, there is a lack of analysis of the factors affecting the printing quality when multi-layer printing is performed, which is not conducive to the continuous optimization of printing production.

[0005] To this end, the present invention provides a printing quality monitoring intelligent processing system. Summary of the invention

[0006] In order to make up for the deficiencies of the prior art, at least one technical problem raised in the background technology is solved.

[0007] The technical solution adopted by the present invention to solve the technical problem is: a printing quality monitoring intelligent processing system, comprising:

[0008] Printing data acquisition module: pre-process the original image of the design to be printed using Adobe Photoshop to obtain the pre-processed original image of the design and the number of printing layers, receive the pre-processed original image of the design using the Raster Image Processor, and perform screening processing to obtain the dot setting radius of different printing areas when printing each layer;

[0009] Printing monitoring module: traverse each layer of the coating after printing, divide the coating area according to the dot setting radius, obtain the coating sub-area, obtain the actual dot radius of the coating sub-area at several collection points, and mark the coating sub-area by comparing it with the corresponding dot setting radius, obtain the dot abnormal sub-area, and obtain the regional performance value by performing quantitative analysis and abnormal analysis on the dot abnormal sub-area in the coating. The quality of the coating after a single layer of printing is judged by the regional performance value, and a quality monitoring signal is generated, wherein the quality monitoring signal includes a quality qualified signal and a quality unqualified signal;

[0010] Influencing data acquisition module: Based on the quality failure signal, the paper thickness values ​​at all collection points are obtained and processed and analyzed to obtain the thickness impact value. Based on the thickness impact value, it is determined whether the uneven paper thickness has an impact on the coating quality failure. If so, an impact signal is generated;

[0011] Intelligent processing module: Based on the impact signal, the paper thickness in the abnormal sub-area is obtained, and the abnormal sub-area is divided into several abnormal unit sub-areas according to its paper thickness, and the roller pad thickness adjustment value in the abnormal unit sub-area is analyzed according to the thickness deviation value in the abnormal unit sub-area. The abnormal sub-unit area is reprinted according to the roller pad adjustment value in the abnormal unit sub-area. After all abnormal sub-unit areas are reprinted, the next layer of coating printing is continued until all layers of coating are traversed.

[0012] As a further technical solution of the present invention, the specific process of the processing of the Adobe Photoshop and the Raster Image Processor raster image processor is as follows:

[0013] S1, start Adobe Photoshop software and import the original image of the design to be printed, and pre-process the image, wherein the pre-processing includes: cropping, rotating, adjusting color balance, defect repairing, and image sharpening, and the pre-processing is selected according to actual needs;

[0014] S2, in Adobe Photoshop, use layers to manage different parts of an image. Each layer contains different colors, textures, or image elements. The layers will be treated as different printing layers when printing;

[0015] S3, determining the number of printed layers according to the number of layers analyzed by the layer management, that is, the number of layers is equal to the number of printed layers;

[0016] S4, importing the pre-processed original image of the design draft into the Raster Image Processor, and further processing the pre-processed original image of the design draft, including: color correction, color conversion (such as from RGB to CMYK), denoising, and enhancement, to ensure that the image quality meets the printing requirements;

[0017] S5, Raster Image Processor determines the dot setting radius of different areas when printing each layer according to the printing requirements and equipment characteristics and the screening algorithm.

[0018] As a further technical solution of the present invention, the regional performance value is obtained by summing the abnormal region quantity value and the abnormal region area value.

[0019] The method for obtaining the number of abnormal areas is as follows:

[0020] A plurality of acquisition points are set in different coating sub-areas in the coating image, and the actual dot radius at the acquisition points is measured;

[0021] Performing difference processing on the actual dot radius in the coating sub-area and the dot set radius corresponding to the coating sub-area to obtain a dot radius difference, and comparing the dot radius difference with a dot radius error standard range;

[0022] If the dot radius difference is not within the dot radius error standard range, the collection point is marked as an abnormal collection point;

[0023] Based on the analysis of abnormal collection points in the coating sub-area, the abnormal network point performance value YW of the coating sub-area is obtained;

[0024] comparing the abnormal point performance value with an abnormal point performance threshold;

[0025] If the abnormal dot performance value is greater than or equal to the abnormal dot performance threshold, the coating sub-region corresponding to the abnormal dot performance value is marked as an abnormal sub-region;

[0026] Counting the number of abnormal sub-regions and the total number of coating sub-regions, performing ratio processing on the number of abnormal sub-regions and the number of coating sub-regions, and obtaining a value of the number of abnormal regions;

[0027] The method for obtaining the area value of the abnormal region is:

[0028] The total area of ​​the abnormal sub-region and the total area of ​​the coating region are measured, and the total area of ​​the abnormal sub-region is ratio-processed to the total area of ​​the coating region to obtain the area value of the abnormal region.

[0029] As a further technical solution of the present invention, the abnormal network point performance value YW is obtained in the following manner:

[0030] Count the number of abnormal collection points and the total number of collection points in the coating sub-area, perform ratio processing on the number of abnormal collection points and the total number of collection points to obtain the abnormal number value, and mark it as SL;

[0031] Obtain the dot radius difference at the abnormal collection point, and perform difference processing on it with the endpoint value of the adjacent and nearest dot radius error standard range to obtain the dot radius out-of-bounds difference, and perform ratio processing on the dot radius out-of-bounds difference with the endpoint value of the adjacent and nearest dot radius error standard range to obtain the radius out-of-bounds ratio, sum and average the radius out-of-bounds ratios at all abnormal collection points to obtain the abnormality degree value, and mark it as CD;

[0032] The abnormal quantity value SL and the abnormal degree value CD are processed by the formula: The abnormal dot performance value YW of the coating sub-area is obtained, wherein s1 and s2 are both preset proportional coefficients.

[0033] As a further technical solution of the present invention, the quality monitoring signal is generated in the following manner:

[0034] comparing the regional performance value to a regional performance threshold;

[0035] If the regional performance value is greater than or equal to the regional performance threshold, it means that there are many coating sub-regions with serious abnormalities in the coating area and the area of ​​the coating sub-regions accounts for a large area of ​​the coating area, which means that the coating printing quality is low and a quality failure signal is generated;

[0036] If the regional performance value is less than the regional performance threshold, it means that there are fewer coating sub-regions with serious dot abnormalities in the coating area and the area of ​​the coating sub-regions accounts for a smaller area of ​​the coating area, which means that the coating printing quality is high and a quality qualified signal is generated.

[0037] As a further technical solution of the present invention, the thickness influence value is obtained by:

[0038] The suspected influence value YG, the second suspected influence value YR and the variance value FC of the change ratio value group are processed by the formula: The thickness influence value YX is obtained, wherein a1 and a2 are both preset proportional coefficients.

[0039] As a further technical solution of the present invention, the suspected influence value YG is obtained in the following manner:

[0040] Obtain the paper thickness at the normal collection points among all the collection points, and take the maximum thickness value and the minimum thickness value as the endpoint values ​​to construct the normal paper thickness range;

[0041] Obtain the paper thickness value at the abnormal collection point in the abnormal sub-area, and compare it with the normal paper thickness range;

[0042] If the paper thickness value at the abnormal collection point is within the normal paper thickness range, it will be marked as a suspected affected collection point;

[0043] The number of suspected impact collection points is counted and compared with the number of abnormal collection points to obtain the suspected impact value, which is marked as YG.

[0044] As a further technical solution of the present invention, the second suspected influence value YR is obtained in the following manner:

[0045] Among all the suspected affected collection points, the paper thickness deviation and the dot radius out-of-bounds error at the suspected affected collection points are obtained and compared, wherein the paper thickness deviation is obtained by performing difference processing between the paper thickness at the suspected abnormal collection point and the endpoint value of the adjacent normal paper thickness range;

[0046] If the paper thickness deviation and the dot radius out-of-bounds error have the same positive and negative values, the suspected influencing collection points are marked as same-direction influencing collection points, the number of same-direction influencing collection points is obtained, and the ratio is processed with the number of suspected influencing collection points to obtain the second suspected influencing value, which is marked as YR.

[0047] As a further technical solution of the present invention, the variance value FC of the change ratio value group is obtained as follows:

[0048] Among all the same-direction influence collection points, the dot radius over-limit error corresponding to the same-direction influence collection point and the paper thickness deviation are processed by ratio, so as to obtain the change ratio at the same-direction influence collection point;

[0049] The value of the change ratio at each unidirectional impact collection point is taken respectively, and they are integrated to obtain a change ratio value group, and the variance value of the change ratio value group is obtained and marked as FC.

[0050] As a further technical solution of the present invention, the roller pad thickness adjustment value is obtained by:

[0051] Perform difference processing on the paper thickness in the abnormal unit sub-region and the endpoint value Dd of the adjacent normal paper range to obtain the thickness deviation value in the abnormal unit sub-region and mark it as HP;

[0052] By formula: The roller pad thickness adjustment value CT is obtained, wherein CG represents the initial pad thickness of the printing press.

[0053] The beneficial effects of the present invention are as follows:

[0054] 1. The dot setting radius and the number of printed coatings are obtained through Adobe Photoshop and Raster Image Processor, and each layer of the printed coating is traversed, and the coating area is divided according to the dot setting radius to obtain the coating sub-area, and the actual dot radius of the coating sub-area at several acquisition points is obtained. The actual dot radius is compared and analyzed with the corresponding dot setting radius to judge the coating quality after single-layer printing, and generate a quality monitoring signal, wherein the quality monitoring signal includes a qualified quality signal and an unqualified quality signal. The present invention realizes the traversal monitoring of the printed coating, which is conducive to timely discovering printing quality problems, improving printing efficiency, and preventing the problem of continuing printing after printing quality problems occur, thereby causing waste of printing resources.

[0055] 2. Obtain the paper thickness values ​​at all collection points and process and analyze them to obtain the thickness influence value. Based on the thickness influence value, determine whether the uneven paper thickness has an impact on the unqualified coating quality. If it does, generate an influence signal. Based on the influence signal, obtain the paper thickness in the abnormal sub-area. Divide the abnormal sub-area into several abnormal unit sub-areas according to its paper thickness. Analyze and obtain the roller pad thickness adjustment value in the abnormal unit sub-area according to the thickness deviation value in the abnormal unit sub-area. Reprint the abnormal sub-unit area according to the roller pad adjustment value in the abnormal unit sub-area, and reprint in all abnormal sub-unit areas. After that, the next layer of coating is printed until all layers of coating are traversed. In the case of unqualified coating quality, the present invention conducts a combined analysis of the thickness of the paper and the radius of the dots to obtain the thickness influence value, and judges whether the uniformity of the paper will affect the coating quality. If so, the roller pad thickness value corresponding to the abnormal paper thickness area during printing is adjusted according to the thickness of the paper, so as to make the printing pressure uniform. The present invention analyzes the thickness of the paper to achieve effective analysis of the causes of abnormal coating quality, improves printing quality, analyzes and processes the factors affecting printing, and optimizes printing production. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The present invention will be further described below in conjunction with the accompanying drawings.

[0057] Figure 1 is a flowchart of the steps of a printing quality monitoring intelligent processing system according to an embodiment of the present invention;

[0058] Figure 2 1 is a flow chart of the steps for monitoring the coating printing quality in an embodiment of the present invention. DETAILED DESCRIPTION

[0059] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods. Example 1

[0060] like Figure 1 As shown, a printing quality monitoring intelligent processing system according to an embodiment of the present invention includes:

[0061] Printing data acquisition module: pre-process the original image of the design to be printed using Adobe Photoshop to obtain the pre-processed original image of the design and the number of printing layers, receive the pre-processed original image of the design using the Raster Image Processor, and perform screening to obtain the dot setting radius of different printing areas when printing each layer;

[0062] Exemplarily, the specific process of processing by Adobe Photoshop and Raster Image Processor is as follows:

[0063] S1, start Adobe Photoshop software and import the original image of the design to be printed, and pre-process the image, wherein the pre-processing includes: cropping, rotating, adjusting color balance, defect repair, image sharpening, etc. The pre-processing is selected according to actual needs;

[0064] S2, in Adobe Photoshop, use layers to manage different parts of an image. Each layer contains different colors, textures, or image elements. The layers will be treated as different printing layers when printing;

[0065] S3, determining the number of printed layers according to the number of layers analyzed by the layer management, that is, the number of layers is equal to the number of printed layers;

[0066] S4, importing the pre-processed original image of the design draft into the Raster Image Processor, and further processing the pre-processed original image of the design draft, including: color correction, color conversion (such as from RGB to CMYK), denoising, enhancement, etc., to ensure that the image quality meets the printing requirements;

[0067] S5, Raster Image Processor determines the dot setting radius of different areas when printing each layer according to the printing requirements and equipment characteristics based on the screening algorithm;

[0068] Printing monitoring module: traverse each layer of the coating after printing, divide the coating area according to the dot setting radius, obtain the coating sub-area, obtain the actual dot radius of the coating sub-area at several collection points, and mark the coating sub-area by comparing it with the corresponding dot setting radius, obtain the dot abnormal sub-area, and obtain the regional performance value by performing quantitative analysis and abnormal analysis on the dot abnormal sub-area in the coating. The quality of the coating after a single layer of printing is judged by the regional performance value, and a quality monitoring signal is generated, wherein the quality monitoring signal includes a quality qualified signal and a quality unqualified signal;

[0069] The conditions satisfied by dividing the coating area according to the dot setting radius are: the dot setting radius corresponding to the divided coating sub-areas is the same and the divided coating sub-areas are continuous. Specifically, within the coating sub-area, the dot setting radius required to be printed is the same, and the area is continuous and uninterrupted;

[0070] In some embodiments, a high-precision camera or other image acquisition device is used to acquire a coating image after single-layer printing, and the image is imported into Adobe Photoshop. Using the measurement tool of Adobe Photoshop, a number of acquisition points are set in different coating sub-areas in the coating image, and the actual dot radius at the acquisition points is measured. The actual dot radius at the acquisition point is measured by:

[0071] Use the measurement tool of Adobe Photoshop to measure the area of ​​the dots at the collection point, and use the area formula of the circle: Converted to radius calculation formula: Get the actual dot radius r;

[0072] It should be noted that the purpose of using the circle formula to convert and calculate the actual dot radius is that the actual dot pattern may be a non-standard circle. In printing, the dot shape on the coating surface is irregular. Therefore, by using the equivalent circle calculation method to calculate the dot radius, it is sufficient to realize the printing monitoring of the coating dots.

[0073] In some embodiments, Figure 2 As shown, the actual dot radius in the coating sub-area is subjected to difference processing with the dot set radius corresponding to the coating sub-area to obtain the dot radius difference, and the dot radius difference is compared with the dot radius error standard range;

[0074] If the dot radius difference is within the dot radius error standard range, the collection point is marked as a normal collection point;

[0075] If the dot radius difference is not within the dot radius error standard range, the collection point is marked as an abnormal collection point;

[0076] It should be noted that the standard range of dot radius error indicates the dot printing error allowed by the printing equipment during printing, and the error is obtained through the printing parameters and operating instructions of the printing equipment;

[0077] Count the number of abnormal collection points and the total number of collection points in the coating sub-area, perform ratio processing on the number of abnormal collection points and the total number of collection points to obtain the abnormal number value, and mark it as SL;

[0078] Obtain the dot radius difference at the abnormal collection point, and perform difference processing on it with the endpoint value of the adjacent and nearest dot radius error standard range to obtain the dot radius out-of-bounds difference, and perform ratio processing on the dot radius out-of-bounds difference with the endpoint value of the adjacent and nearest dot radius error standard range to obtain the radius out-of-bounds ratio, sum and average the radius out-of-bounds ratios at all abnormal collection points to obtain the abnormality degree value, and mark it as CD;

[0079] The abnormal quantity value SL and the abnormal degree value CD are processed by the formula: Obtain the abnormal dot performance value YW of the coating sub-area, where s1 and s2 are both preset proportional coefficients;

[0080] comparing the abnormal point performance value with an abnormal point performance threshold;

[0081] If the abnormal dot performance value is greater than or equal to the abnormal dot performance threshold, the coating sub-region corresponding to the abnormal dot performance value is marked as an abnormal sub-region;

[0082] If the abnormal dot performance value is less than the abnormal dot performance threshold, the coating sub-region corresponding to the abnormal dot performance value is marked as a normal sub-region;

[0083] Counting the number of abnormal sub-regions and the total number of coating sub-regions, performing ratio processing on the number of abnormal sub-regions and the number of coating sub-regions, and obtaining a value of the number of abnormal regions;

[0084] Measuring the total area of ​​the abnormal sub-region and the total area of ​​the coating region, performing ratio processing on the total area of ​​the abnormal sub-region and the total area of ​​the coating region to obtain the area value of the abnormal region;

[0085] The number of abnormal regions and the area of ​​abnormal regions are summed to obtain the regional performance value;

[0086] In some embodiments, the region performance value is compared to a region performance threshold;

[0087] If the regional performance value is greater than or equal to the regional performance threshold, it means that there are many coating sub-regions with serious abnormalities in the coating area and the area of ​​the coating sub-regions accounts for a large area of ​​the coating area, which means that the coating printing quality is low and a quality failure signal is generated;

[0088] If the regional performance value is less than the regional performance threshold, it means that there are fewer coating sub-regions with serious dot abnormalities in the coating area and the area of ​​the coating sub-regions accounts for a smaller area of ​​the coating area, which means that the coating printing quality is high and a quality qualified signal is generated. Based on the quality qualified signal, the next layer printing is continued.

[0089] The technical solution of the embodiment of the present invention is: obtaining the dot setting radius and the number of printed coatings through Adobe Photoshop and Raster Image Processor, traversing each layer of printed coating, dividing the coating area according to the dot setting radius to obtain coating sub-areas, obtaining the actual dot radius of the coating sub-area at several acquisition points, and comparing and analyzing with the corresponding dot setting radius to judge the coating quality after single-layer printing, and generating a quality monitoring signal, wherein the quality monitoring signal includes a quality qualified signal and a quality unqualified signal. The present invention realizes traversal monitoring of the printed coating, which is conducive to timely discovering printing quality problems, improving printing efficiency, and preventing the problem of continuing printing after printing quality problems occur, thereby causing waste of printing resources. Example 2

[0090] like Figure 1 As shown, based on Example 1, when a single-layer printing is unqualified, a printing abnormality analysis is required, wherein the unevenness of the paper thickness may cause an abnormal radius of the coating dots. For example, when the paper is thin, the contact pressure between the paper and the roller is small, resulting in the ink being unable to diffuse to the surroundings, thereby causing the radius of the dots to decrease and the dot shape to be smaller. On the contrary, when the paper is thick, the contact pressure between the paper and the roller is large, resulting in the ink being excessively diffused to the surroundings, thereby causing the radius of the dots to increase and the dot shape to be larger. In the embodiment of the present application, the uniformity of the paper thickness is analyzed to determine whether the paper thickness is the cause of the unqualified coating quality, including:

[0091] Influencing data acquisition module: Based on the quality failure signal, the paper thickness values ​​at all collection points are obtained and processed and analyzed to obtain the thickness impact value. Based on the thickness impact value, it is determined whether the uneven paper thickness has an impact on the coating quality failure. If so, an impact signal is generated;

[0092] In some embodiments, the paper thickness at the normal collection point among all the collection points is obtained, and the maximum thickness value and the minimum thickness value are taken as the endpoint values ​​to construct the normal paper thickness range;

[0093] Obtain the paper thickness value at the abnormal collection point in the abnormal sub-area, and compare it with the normal paper thickness range;

[0094] If the paper thickness value at the abnormal collection point is within the normal paper thickness range, the abnormal collection point is marked as a non-influencing collection point;

[0095] If the paper thickness value at the abnormal collection point is within the normal paper thickness range, it will be marked as a suspected affected collection point;

[0096] It should be noted that the meaning of the suspected affected collection point is: among the abnormal collection points, if the paper thickness affects its coating quality (dot radius), the paper thickness at the abnormal collection point should be different from the paper thickness of all normal collection points;

[0097] Count the number of suspected impact collection points, and compare it with the number of abnormal collection points to obtain the suspected impact value, which is marked as YG;

[0098] Among all the suspected affected collection points, the paper thickness deviation and the dot radius out-of-bounds error at the suspected affected collection points are obtained and compared, wherein the paper thickness deviation is obtained by performing difference processing between the paper thickness at the suspected abnormal collection point and the endpoint value of the adjacent normal paper thickness range;

[0099] If the paper thickness deviation and the dot radius out-of-bounds error have the same positive and negative values, the suspected affected collection points are marked as the same-direction affected collection points;

[0100] If the paper thickness deviation and the dot radius out-of-bounds error are different in positive and negative, the suspected affected collection point is marked as a non-affected collection point;

[0101] The number of the same-direction impact collection points is obtained, and the ratio is processed with the number of the suspected impact collection points to obtain the second suspected impact value, which is marked as YR;

[0102] It should be noted that the meaning of the same-direction impact collection point is: among the suspected impact collection points, if the paper thickness affects its coating quality (dot radius), and its paper thickness is thin (less than the minimum value of the normal paper thickness range), then the dot radius at the collection point should be less than the dot setting radius, and the positive and negative signs of its paper thickness deviation and dot radius out-of-bounds error should be the same;

[0103] Among all the same-direction influence collection points, the dot radius over-limit error corresponding to the same-direction influence collection point and the paper thickness deviation are processed by ratio, so as to obtain the change ratio at the same-direction influence collection point;

[0104] Take the value of the change ratio at each unidirectional impact collection point respectively, and integrate them to obtain a change ratio value group, obtain the variance value of the change ratio value group, and mark it as FC;

[0105] It should be noted that the variance value of the change ratio value group means that, in the abnormal collection point, if the paper thickness affects its coating quality (dot radius), the paper thickness change and the dot radius not only have the same positive and negative changes, but also have the same degree of change. For example, if the paper thickness changes by 1mm, the dot radius changes by 2mm, if the paper thickness changes by 2mm, the dot radius changes by 4mm, if the paper thickness changes by 3mm, the dot radius changes by 6mm. Its variance value reflects the degree of deviation fluctuation between the paper thickness change and the dot radius change.

[0106] The above-obtained suspected influence value YG, the second suspected influence value YR and the variance value FC of the change ratio value group are processed by the formula: Obtain thickness influence value YX, where a1 and a2 are both preset proportional coefficients;

[0107] In some embodiments, the thickness impact value is compared to a thickness impact threshold;

[0108] If the thickness impact value is greater than or equal to the thickness impact threshold, it means that the uneven paper thickness has an impact on the coating quality, and an impact signal is generated;

[0109] If the thickness impact value is less than the thickness impact threshold, it means that the uneven paper thickness has no impact on the coating quality failure;

[0110] Intelligent processing module: Based on the impact signal, the paper thickness in the abnormal sub-area is obtained, and the abnormal sub-area is divided into several abnormal unit sub-areas according to its paper thickness. According to the thickness deviation value in the abnormal unit sub-area, the roller pad thickness adjustment value in the abnormal unit sub-area is analyzed and obtained. According to the roller pad adjustment value in the abnormal unit sub-area, the abnormal sub-unit area is reprinted. After all abnormal sub-unit areas are reprinted, the next layer of coating is printed until all layers of coating are traversed;

[0111] Among them, the paper thickness in the sub-area of ​​the abnormal unit is equal;

[0112] In some embodiments, the thickness of the paper in the abnormal unit sub-region is processed by difference with the nearest normal paper range endpoint value Dd to obtain the thickness deviation value in the abnormal unit sub-region, and it is marked as HP;

[0113] By formula: Obtaining a roller pad thickness adjustment value CT, wherein CG represents the initial pad thickness of the printing press;

[0114] The technical solution of the embodiment of the present invention is as follows: the paper thickness values ​​at all the collection points are obtained and processed and analyzed to obtain the thickness influence value, based on the thickness influence value, it is judged whether the uneven paper thickness has an impact on the unqualified coating quality, if it does, an influence signal is generated, based on the influence signal, the paper thickness in the abnormal sub-region is obtained, the abnormal sub-region is divided into a plurality of abnormal unit sub-regions according to its paper thickness, and according to the thickness deviation value in the abnormal unit sub-region, the roller pad thickness adjustment value in the abnormal unit sub-region is analyzed, the abnormal sub-unit region is reprinted according to the roller pad adjustment value in the abnormal unit sub-region, and in all abnormal sub-units, the roller pad thickness adjustment value in the abnormal unit sub-region is adjusted. After the area is reprinted, the next layer of coating is printed until all layers of coating are traversed. In the case of unqualified coating quality, the present invention conducts a combined analysis of the thickness of the paper and the radius of the dots to obtain the thickness influence value, and judges whether the uniformity of the paper will affect the coating quality. If so, the roller pad thickness value corresponding to the abnormal paper thickness area is adjusted according to the thickness of the paper during printing, so as to make the printing pressure uniform. The present invention analyzes the thickness of the paper to achieve effective analysis of the causes of abnormal coating quality, improves printing quality, analyzes and processes the factors affecting printing, and optimizes printing production.

[0115] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A printing quality monitoring intelligent processing system, characterized in that: include: Printing data acquisition module: pre-process the original image of the design to be printed using Adobe Photoshop to obtain the pre-processed original image of the design and the number of printing layers, receive the pre-processed original image of the design using the Raster Image Processor, and perform screening to obtain the dot setting radius of different printing areas when printing each layer; Printing monitoring module: traverse each layer of the coating after printing, divide the coating area according to the dot setting radius, obtain the coating sub-area, obtain the actual dot radius of the coating sub-area at several collection points, and mark the coating sub-area by comparing it with the corresponding dot setting radius, obtain the dot abnormal sub-area, and obtain the regional performance value by performing quantitative analysis and abnormal analysis on the dot abnormal sub-area in the coating. The quality of the coating after a single layer of printing is judged by the regional performance value, and a quality monitoring signal is generated, wherein the quality monitoring signal includes a quality qualified signal and a quality unqualified signal; Influencing data acquisition module: Based on the quality failure signal, the paper thickness values ​​at all collection points are obtained and processed and analyzed to obtain the thickness impact value. Based on the thickness impact value, it is determined whether the uneven paper thickness has an impact on the coating quality failure. If so, an impact signal is generated; Intelligent processing module: Based on the impact signal, the paper thickness in the abnormal sub-area is obtained, and the abnormal sub-area is divided into several abnormal unit sub-areas according to its paper thickness, and the roller pad thickness adjustment value in the abnormal unit sub-area is analyzed according to the thickness deviation value in the abnormal unit sub-area. The abnormal sub-unit area is reprinted according to the roller pad adjustment value in the abnormal unit sub-area. After all abnormal sub-unit areas are reprinted, the next layer of coating printing is continued until all layers of coating are traversed.

2. The printing quality monitoring intelligent processing system according to claim 1, characterized in that: The specific process of the processing of the Adobe Photoshop and the Raster Image Processor is as follows: S1, start Adobe Photoshop software and import the original image of the design to be printed, and pre-process the image, wherein the pre-processing includes: cropping, rotating, adjusting color balance, defect repairing, and image sharpening, and the pre-processing is selected according to actual needs; S2, in Adobe Photoshop, use layers to manage different parts of an image. Each layer contains different colors, textures, or image elements. The layers will be treated as different printing layers when printing; S3, determining the number of printed layers according to the number of layers analyzed by the layer management, that is, the number of layers is equal to the number of printed layers; S4, importing the pre-processed original image of the design draft into the Raster Image Processor, and further processing the pre-processed original image of the design draft, including: color correction, color conversion, denoising, and enhancement, to ensure that the image quality meets the printing requirements; S5, Raster Image Processor determines the dot setting radius of different areas when printing each layer according to the printing requirements and equipment characteristics and the screening algorithm.

3. The printing quality monitoring intelligent processing system according to claim 1 is characterized in that: The regional performance value is obtained by summing the number of abnormal regions and the area of ​​abnormal regions; The method for obtaining the number of abnormal areas is as follows: A plurality of acquisition points are set in different coating sub-areas in the coating image, and the actual dot radius at the acquisition points is measured; Performing difference processing on the actual dot radius in the coating sub-area and the dot set radius corresponding to the coating sub-area to obtain a dot radius difference, and comparing the dot radius difference with a dot radius error standard range; If the dot radius difference is not within the dot radius error standard range, the collection point is marked as an abnormal collection point; Based on the analysis of abnormal collection points in the coating sub-area, the abnormal network point performance value YW of the coating sub-area is obtained; comparing the abnormal point performance value with an abnormal point performance threshold; If the abnormal dot performance value is greater than or equal to the abnormal dot performance threshold, the coating sub-region corresponding to the abnormal dot performance value is marked as an abnormal sub-region; Counting the number of abnormal sub-regions and the total number of coating sub-regions, performing ratio processing on the number of abnormal sub-regions and the number of coating sub-regions, and obtaining a value of the number of abnormal regions; The method for obtaining the area value of the abnormal region is: The total area of ​​the abnormal sub-region and the total area of ​​the coating region are measured, and the total area of ​​the abnormal sub-region is ratio-processed to the total area of ​​the coating region to obtain the area value of the abnormal region.

4. The printing quality monitoring intelligent processing system according to claim 3 is characterized in that: The abnormal network point performance value YW is obtained in the following manner: Count the number of abnormal collection points and the total number of collection points in the coating sub-area, perform ratio processing on the number of abnormal collection points and the total number of collection points to obtain the abnormal number value, and mark it as SL; Obtain the dot radius difference at the abnormal collection point, and perform difference processing on it with the endpoint value of the adjacent and nearest dot radius error standard range to obtain the dot radius out-of-bounds difference, and perform ratio processing on the dot radius out-of-bounds difference with the endpoint value of the adjacent and nearest dot radius error standard range to obtain the radius out-of-bounds ratio, sum and average the radius out-of-bounds ratios at all abnormal collection points to obtain the abnormality degree value, and mark it as CD; The abnormal quantity value SL and the abnormal degree value CD are processed by the formula: The abnormal dot performance value YW of the coating sub-area is obtained, wherein s1 and s2 are both preset proportional coefficients.

5. The printing quality monitoring intelligent processing system according to claim 1 is characterized in that: The quality monitoring signal is generated in the following manner: comparing the regional performance value to a regional performance threshold; If the regional performance value is greater than or equal to the regional performance threshold, it means that there are many coating sub-regions with serious abnormalities in the coating area and the area of ​​the coating sub-regions accounts for a large area of ​​the coating area, which means that the coating printing quality is low and a quality failure signal is generated; If the regional performance value is less than the regional performance threshold, it means that there are fewer coating sub-regions with serious dot abnormalities in the coating area and the area of ​​the coating sub-regions accounts for a smaller area of ​​the coating area, which means that the coating printing quality is high and a quality qualified signal is generated.

6. The printing quality monitoring intelligent processing system according to claim 1 is characterized in that: The thickness influence value is obtained as follows: The suspected influence value YG, the second suspected influence value YR and the variance value FC of the change ratio value group are processed by the formula: The thickness influence value YX is obtained, wherein a1 and a2 are both preset proportional coefficients.

7. The printing quality monitoring intelligent processing system according to claim 6 is characterized by: The suspected impact value YG is obtained as follows: Obtain the paper thickness at the normal collection points among all the collection points, and take the maximum thickness value and the minimum thickness value as the endpoint values ​​to construct the normal paper thickness range; Obtain the paper thickness value at the abnormal collection point in the abnormal sub-area, and compare it with the normal paper thickness range; If the paper thickness value at the abnormal collection point is within the normal paper thickness range, it will be marked as a suspected affected collection point; The number of suspected impact collection points is counted and compared with the number of abnormal collection points to obtain the suspected impact value, which is marked as YG.

8. The printing quality monitoring intelligent processing system according to claim 6 is characterized by: The second suspected impact value YR is obtained as follows: Among all the suspected affected collection points, the paper thickness deviation and the dot radius out-of-bounds error at the suspected affected collection points are obtained and compared, wherein the paper thickness deviation is obtained by performing difference processing between the paper thickness at the suspected abnormal collection point and the endpoint value of the adjacent normal paper thickness range; If the paper thickness deviation and the dot radius out-of-bounds error have the same positive and negative values, the suspected influencing collection points are marked as same-direction influencing collection points, the number of same-direction influencing collection points is obtained, and the ratio is processed with the number of suspected influencing collection points to obtain the second suspected influencing value, which is marked as YR.

9. The printing quality monitoring intelligent processing system according to claim 6, characterized in that: The variance value FC of the change ratio value group is obtained as follows: Among all the same-direction influence collection points, the dot radius over-limit error corresponding to the same-direction influence collection point and the paper thickness deviation are processed by ratio, so as to obtain the change ratio at the same-direction influence collection point; The value of the change ratio at each unidirectional impact collection point is taken respectively, and they are integrated to obtain a change ratio value group, and the variance value of the change ratio value group is obtained and marked as FC.

10. The printing quality monitoring intelligent processing system according to claim 1, characterized in that: The roller pad thickness adjustment value is obtained as follows: Perform difference processing on the paper thickness in the abnormal unit sub-region and the endpoint value Dd of the adjacent normal paper range to obtain the thickness deviation value in the abnormal unit sub-region and mark it as HP; By formula: The roller pad thickness adjustment value CT is obtained, wherein CG represents the initial pad thickness of the printing press.

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