A precision control system for screen printing

Abstract

The present invention provides a precision control system for screen printing, which relates to the field of printing technology, and includes: a pattern matching module: determining a first placement mode; a printing positioning module: placing a target substrate in a fixed area of ​​a printing table in response to the first placement mode, and then performing position detection and adjustment; a template pressing module: placing a key printing template in a specific area of ​​the target substrate for pressing and gluing; a curing module: based on a mechanical arm, quickly transferring the target substrate after gluing to a set imprinting machine for curing. By placing the target substrate in a fixed area of ​​the printing table, performing position detection and adjustment on the target substrate; after determining that the positioning of the target substrate is accurate, placing the key printing template in a specific area of ​​the target substrate for pressing and gluing, and after gluing the target substrate, quickly transferring it to a set imprinting machine for curing based on a mechanical arm, the precision of screen printing can be effectively improved and the printing effect can be guaranteed.

Description

Technical Field

[0001] The invention relates to the technical field of printing, and in particular to a precision control system for screen printing. Background Art

[0002] The traditional screen printing process often relies on manual operation and visual positioning during the preparation process, which makes it difficult to achieve micron-level precision requirements. Especially in the process of multi-layer template printing and lamination, due to the differences in the material, thickness and pattern of each layer of the template, it is easy to cause cumulative errors, affecting the quality and performance of the final product. Therefore, how to achieve automatic and precise control of printing accuracy has become one of the current research centers.

[0003] Therefore, the present invention provides a precision control system for screen printing. Summary of the invention

[0004] The present invention provides a precision control system for screen printing, which is used for detecting and adjusting the position of a target substrate after placing it in a fixed area of ​​a printing table; after determining that the positioning of the target substrate is accurate, a key printing template is placed in a specific area of ​​the target substrate for pressing and gluing; after gluing the target substrate, the target substrate is quickly transferred to a set imprinting machine for curing based on a mechanical arm, which can effectively improve the precision of screen printing and ensure the printing effect.

[0005] The present invention provides a precision control system for screen printing, comprising: Mode matching module: used to determine the current first placement mode according to printing requirements; Printing substrate positioning module: used to respond to the first placement mode, place the target printing substrate in a fixed area of ​​the printing table, and then perform position detection and adjustment; Template pressing module: used to place the key printing template in a specific area of ​​the target substrate for pressing and gluing after confirming the accurate positioning of the target substrate; Curing module: used to quickly transfer the target substrate after glue application to the set imprinting machine for curing based on the robot arm.

[0006] Preferably, the first printing mode includes an automatic placement mode and a non-automatic placement mode.

[0007] Preferably, the printing positioning module comprises: Placement unit: used for workers to manually place the target substrate in the substrate fixing area when the first placement mode is the non-automatic placement mode; When the first placement mode is the automatic mode, the target substrate is conveyed to the substrate fixing area by the first conveyor belt; Detection unit: used for detecting that the target substrate is placed in the fixed printing area, and then using a CCD detector to perform position detection to obtain a first position image; after performing denoising and image enhancement processing on the first position image, a first key image is obtained; Using a set similarity algorithm, similarity matching is performed between the feature points of the printed object extracted from the first key image and the reference feature points of the reference image to obtain a matching pair; According to the obtained matching pair, the first pixel coordinate of the substrate feature point of the target substrate is obtained; Inputting the first pixel coordinate into a pre-established coordinate output model to obtain position detection information; An adjustment unit: used for comparing the position detection information with a preset position of a substrate to obtain a first position difference; If there is a first position difference greater than a set position difference threshold, it is determined that the current target substrate position is inaccurate; based on the first position difference, a position fine-tuning amount and a position adjustment direction are determined; Using the first robot arm to move the target substrate to a preset substrate position according to the position fine-tuning amount and the position adjustment direction, and then sending a substrate position accuracy signal; If there is no first position difference greater than the set position difference threshold, it is determined that the current target printing object is in an accurate position, and a printing position accurate signal is issued.

[0008] Preferably, the template pressing module comprises: Template positioning unit: used to place the current key printing template in the upper area of ​​the target substrate after detecting the accurate signal of the substrate position; use the initial positioning block and the re-positioning block to perform two template positioning analyses to determine the template positioning situation; Initial positioning block: used to capture the image of the key printing template using a CCD detector to obtain the first template image; Performing data preprocessing on the first template image to obtain a template analysis image; Extracting locator features from the template analysis image to obtain template locating feature points; Mapping the template positioning feature points to the currently acquired first key image using a preset change matrix to obtain first feature coordinates of the template positioning feature points; Extracting locator features from the first key image to obtain key locating feature points; Based on the matching locator number combination, the positioning feature points expected to match the current key printing template are screened out from the acquired key positioning feature points, and marked as expected positioning feature points; Determine a second feature coordinate of the desired positioning feature point in the first key image; Compare the first characteristic coordinates of the template positioning feature point with the second characteristic coordinates of each expected positioning feature point to obtain a first positioning difference evaluation coefficient; The desired positioning feature point with the smallest first positioning difference evaluation coefficient is regarded as the first matching point of the current template positioning feature point; If the first positioning difference evaluation coefficients of all template positioning feature points and the corresponding first matching points are not greater than the set evaluation threshold, it is determined that the current key printing template does not need positioning adjustment; Otherwise, it is determined that the current key printing template needs to be positioned and adjusted, and the template positioning deviation analysis is performed using the repositioning block; Repositioning block: used to extract pattern identification features from the template analysis image using an edge detection algorithm to obtain a first identification feature point; Extracting pattern identification features from the currently acquired first key image using an edge detection algorithm to obtain second identification feature points; Using a feature matching algorithm, feature matching is performed on the first identification feature point and the second identification feature point to obtain a feature matching pair; Input the feature matching pairs whose matching coefficients are greater than the set matching threshold into the pre-established deviation output model to obtain the deviation results; According to the deviation result, obtaining the alignment fine-tuning amount and the alignment adjustment direction; Template adjustment unit: used to determine that the current key printing template does not need positioning adjustment, and send a template positioning accurate signal; When it is determined that the current key printing template needs to be positioned and adjusted, the second robot arm is used to fine-tune the position of the key printing template according to the currently acquired alignment fine-tuning amount and alignment adjustment direction, and then a template accurate positioning signal is issued; Lamination and gluing unit: It is used to laminarize the target substrate with the current key printing template after detecting the accurate signal of template positioning, and then start the gluing system to work and evenly apply glue that matches the current key printing template on the key printing template.

[0009] Preferably, using the second robot arm to fine-tune the position of the key printing template according to the currently acquired alignment fine-tune amount and alignment adjustment direction includes: By acquiring the historical adjustment record of the second robot arm and performing error analysis, the currently acquired alignment fine-tuning amount is adjusted to obtain the real-time fine-tuning amount; When the real-time fine-tuning amount is less than the set fine-tuning amount, a first fine-tuning time matching the current real-time fine-tuning amount is obtained from the set alignment time table; The real-time fine-tuning amount is calculated in combination with the first fine-tuning time to obtain a first fine-tuning speed; The second robot arm fine-tunes the position of the key printing template according to the first fine-tuning speed, the real-time fine-tuning amount and the alignment adjustment direction; When the real-time fine adjustment amount is not less than the set fine adjustment amount, the real-time fine adjustment amount is divided by a dynamic division coefficient to obtain a first fine adjustment amount; Subtracting the first fine adjustment amount from the real-time fine adjustment amount to obtain a first coarse adjustment amount; The calculation formula of the dynamic partition coefficient is as follows: ; In the formula, It is represented as the dynamic division coefficient at the current moment; P0 is represented as the preset division coefficient; Indicates the setting of fine adjustment amount; It is expressed as the real-time fine-tuning amount at the current moment; Obtaining a fine adjustment time matching the current first fine adjustment amount from the set alignment time table; The first fine adjustment amount is calculated in combination with the fine adjustment time to obtain the fine adjustment speed; The second robot arm performs a rough adjustment on the key printing template according to the set rough adjustment speed, the first rough adjustment amount and the alignment adjustment direction, and then performs a fine adjustment on the key printing template according to the fine adjustment speed, the first fine adjustment amount and the alignment adjustment direction.

[0010] Preferably, by acquiring the historical adjustment record of the second robot arm and performing error analysis, the currently acquired alignment fine-tuning amount is adjusted to obtain the real-time fine-tuning amount, including: Extracting historical adjustment records within a preset time period of the current second robot arm from the template adjustment database; Obtaining corresponding historical position adjustment amounts and historical position required adjustment amounts of different adjustment types of the second robot arm from the historical adjustment records; Calculate a first adjustment difference between a historical position adjustment amount and a historical position adjustment amount required for the same adjustment type each time the second robot arm is adjusted; Determine a corresponding dynamic adjustment difference threshold for each adjustment type according to all the first adjustment differences obtained; Taking the first adjustment difference as the dependent variable, construct the adjustment difference change curve of each adjustment type according to the time sequence; Obtaining the first adjustment difference that is greater than the dynamic adjustment difference threshold from the adjustment difference variation curve, and marking the corresponding moment as the reference moment; Based on the reference time, segmenting the adjustment difference change curve, marking the curve portion corresponding to the time before the reference time as a first curve, and marking the curve portion corresponding to the time after the reference time as a second curve; Extracting curve features and performing weighted average calculation on the first curve and the second curve respectively, and obtaining a first variation coefficient and a second variation coefficient accordingly; Calculating a key adjustment coefficient based on the first change coefficient and the second change coefficient of each adjustment type; The key adjustment coefficient is used to adjust the currently acquired alignment fine-tuning amount to obtain a real-time fine-tuning amount.

[0011] Preferably, the calculation formula of the key adjustment coefficient is as follows: ; In the formula, Expressed as the key adjustment factor; It is expressed as the area of ​​the first curve corresponding to the i-th adjustment type, where i=1, 2, , n; n represents the total number of adjustment types; It is represented as the area of ​​the second curve corresponding to the i-th adjustment type; It is represented as the second variation coefficient corresponding to the i-th adjustment type; It is represented as the first change coefficient corresponding to the i-th adjustment type; ln represents the natural logarithm sign; e represents a constant with a value of 2.7; It is represented as the absolute time difference between the time period corresponding to the first curve and the time period corresponding to the second curve of the i-th adjustment type; T is represented as a preset time period.

[0012] Preferably, the curing module comprises: Transfer unit: used for transferring the target printing substrate after the gluing to the second conveyor belt by using the first robot arm, and the second conveyor belt transfers the target printing substrate after the gluing to the set imprinting machine; Curing unit: The set stamping machine performs curing treatment on the target printing material after the glue is applied by using a corresponding curing method.

[0013] Compared with the prior art, the present invention has the following beneficial effects: After placing the target substrate in a fixed area of ​​the printing table, the position of the target substrate is detected and adjusted; after determining that the target substrate is accurately positioned, the key printing template is placed in a specific area of ​​the target substrate for lamination and gluing; after gluing the target substrate, the robot arm quickly transfers it to the set imprinting machine for curing, which can effectively improve the accuracy of screen printing and ensure the printing effect.

[0014] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0015] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 The structure diagram of a precision control system for screen printing in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0018] The embodiment of the present invention provides a precision control system for screen printing, such as Figure 1 As shown, including: Mode matching module: used to determine the current first placement mode according to printing requirements; Printing substrate positioning module: used to respond to the first placement mode, place the target printing substrate in a fixed area of ​​the printing table, and then perform position detection and adjustment; Template pressing module: used to place the key printing template in a specific area of ​​the target substrate for pressing and gluing after confirming the accurate positioning of the target substrate; Curing module: used to quickly transfer the target substrate after glue application to the set imprinting machine for curing based on the robot arm.

[0019] In this embodiment, the printing requirement refers to the size, type and printing process of the target substrate; the first printing mode includes an automatic placement mode and a non-automatic placement mode, wherein the automatic placement mode refers to using a first conveyor belt to convey the target substrate to a fixed printing area; the non-automatic placement mode refers to a worker manually placing the target substrate in the fixed printing area; the fixed printing area refers to a pre-set area for placing the target substrate, wherein the target substrate refers to an object used for printing, such as mobile phone keys, keyboards, and film, microcircuits, etc. of display screens, buttons, lights, etc. in cars; the key printing template refers to the corresponding printing template of the current printing process, and the corresponding templates of different printing processes may be different; the set stamping machine refers to a machine used to solidify the target substrate after brushing glue.

[0020] The beneficial effects of the above technical solution are: after placing the target substrate in a fixed area of ​​the printing table, the position of the target substrate is detected and adjusted; after determining that the positioning of the target substrate is accurate, the key printing template is placed in a specific area of ​​the target substrate for pressing and gluing; after gluing the target substrate, it is quickly transferred to the set imprinting machine for curing based on a robotic arm, which can effectively improve the accuracy of screen printing and ensure the printing effect.

[0021] An embodiment of the present invention provides a precision control system for screen printing, wherein the printing positioning module comprises: Placement unit: used for workers to manually place the target substrate in the substrate fixing area when the first placement mode is the non-automatic placement mode; When the first placement mode is the automatic mode, the target substrate is conveyed to the substrate fixing area by the first conveyor belt; Detection unit: used for detecting that the target substrate is placed in the fixed printing area, and then using a CCD detector to perform position detection to obtain a first position image; after performing denoising and image enhancement processing on the first position image, a first key image is obtained; Using a set similarity algorithm, similarity matching is performed between the feature points of the printed object extracted from the first key image and the reference feature points of the reference image to obtain a matching pair; According to the obtained matching pair, the first pixel coordinate of the substrate feature point of the target substrate is obtained; Inputting the first pixel coordinate into a pre-established coordinate output model to obtain position detection information; An adjustment unit: used for comparing the position detection information with a preset position of a substrate to obtain a first position difference; If there is a first position difference greater than a set position difference threshold, it is determined that the current target substrate position is inaccurate; based on the first position difference, a position fine-tuning amount and a position adjustment direction are determined; Using the first robot arm to move the target substrate to a preset substrate position according to the position fine-tuning amount and the position adjustment direction, and then sending a substrate position accuracy signal; If there is no first position difference greater than the set position difference threshold, it is determined that the current target printing object is in an accurate position, and a printing position accurate signal is issued.

[0022] In this embodiment, the first conveyor belt refers to a conveying device used to convey the target substrate to the fixed printing area; the CCD detector refers to a device that can convert an optical image into a digital signal; the first position image refers to an image obtained by scanning the fixed printing area where the target substrate is placed using the CCD detector; the first key image refers to an image obtained after denoising and image enhancement processing of the first position image.

[0023] In this embodiment, the reference image refers to a template image obtained by scanning a fixed printing area where a substrate is accurately placed at a preset position of the substrate using a CCD detector in advance; a matching pair refers to a feature pair consisting of a corresponding substrate feature point with a maximum feature similarity value and a reference feature point, wherein the feature similarity value is a feature descriptor similarity value between the substrate feature point and the reference feature point calculated using a set similarity algorithm, which is used to characterize the degree of similarity between the feature points; a feature descriptor refers to a mathematical representation of a feature point, such as a gradient direction histogram; the set similarity algorithm is a predetermined cosine similarity algorithm; the substrate feature point is a feature point extracted from the first key image using the SIFT algorithm, such as a corner point or an edge point; the first pixel coordinates refer to the coordinates of a key point obtained by calculating the average coordinate value of the matching feature pair, wherein the key point refers to the center of mass or a center point.

[0024] In this embodiment, the steps for establishing the coordinate output model are as follows: 1. Use the SIFT algorithm to extract substrate feature points from pre-established training data, where the training data refers to images of different substrates at different positions, angles and lighting conditions, as well as the real physical positions of the corresponding substrate feature points; substrate feature points refer to stable points in the image, such as corner points of the substrate; 2. Match the feature points of the substrate with the feature points in the reference image to obtain training matching pairs; 3. Use the training matching pairs to train the perspective transformation model and obtain the coordinate output model, where the perspective transformation model is represented by a 3x3 matrix, which contains the perspective transformation parameters and can be calculated by combining the image coordinates and physical coordinates in the training matching pairs through the least squares algorithm.

[0025] In this embodiment, the position detection information refers to the physical position coordinates of the center of mass and the center point of the current target substrate; the preset position of the substrate refers to the predetermined physical center of mass position coordinates and physical center point position coordinates of the target substrate; the first position difference is obtained by comparing the position detection information with the preset position of the substrate, including a translation difference and an angle difference; the set position difference threshold is predetermined, including a translation-set position difference threshold and an angle-set position difference threshold, wherein the translation-set position difference threshold is generally 15 microns, and the angle-set position difference threshold is generally 0.00025 degrees; the first robot arm refers to the executing mechanical structure for adjusting the position of the target substrate; the substrate position accuracy signal is used to indicate that the current target substrate is accurately placed.

[0026] In this embodiment, the position fine-tuning amount is determined by comparing the coordinate difference between the position detection information and the preset position of the substrate (i.e., the first position difference), including three types: up and down fine-tuning amount, left and right fine-tuning amount, and rotational fine-tuning amount; the position adjustment direction is determined according to the sign and size of the first position difference, including three types: up / down adjustment, left / right adjustment, and clockwise / counterclockwise rotation adjustment. For example, if the first position difference is positive on the x-axis, it needs to be adjusted to the right; if it is negative, it needs to be adjusted to the left.

[0027] The beneficial effect of the above technical solution is that by selecting different placement methods according to different printing requirements, placing the target substrate in a fixed area of ​​the printing table, and detecting and adjusting the position of the target substrate, the printing efficiency and the degree of automation can be improved.

[0028] An embodiment of the present invention provides a precision control system for screen printing, wherein the template pressing module comprises: Template positioning unit: used to place the current key printing template in the upper area of ​​the target substrate after detecting the accurate signal of the substrate position; use the initial positioning block and the re-positioning block to perform two template positioning analyses to determine the template positioning situation; Initial positioning block: used to capture the image of the key printing template using a CCD detector to obtain the first template image; Performing data preprocessing on the first template image to obtain a template analysis image; Extracting locator features from the template analysis image to obtain template locating feature points; Mapping the template positioning feature points to the currently acquired first key image using a preset change matrix to obtain first feature coordinates of the template positioning feature points; Extracting locator features from the first key image to obtain key locating feature points; Based on the matching locator number combination, the positioning feature points expected to match the current key printing template are screened out from the acquired key positioning feature points, and marked as expected positioning feature points; Determine a second feature coordinate of the desired positioning feature point in the first key image; Compare the first characteristic coordinates of the template positioning feature point with the second characteristic coordinates of each expected positioning feature point to obtain a first positioning difference evaluation coefficient; The desired positioning feature point with the smallest first positioning difference evaluation coefficient is regarded as the first matching point of the current template positioning feature point; If the first positioning difference evaluation coefficients of all template positioning feature points and the corresponding first matching points are not greater than the set evaluation threshold, it is determined that the current key printing template does not need positioning adjustment; Otherwise, it is determined that the current key printing template needs to be positioned and adjusted, and the template positioning deviation analysis is performed using the repositioning block; Repositioning block: used to extract pattern identification features from the template analysis image using an edge detection algorithm to obtain a first identification feature point; Extracting pattern identification features from the currently acquired first key image using an edge detection algorithm to obtain second identification feature points; Using a feature matching algorithm, feature matching is performed on the first identification feature point and the second identification feature point to obtain a feature matching pair; Input the feature matching pairs whose matching coefficients are greater than the set matching threshold into the pre-established deviation output model to obtain the deviation results; According to the deviation result, obtaining the alignment fine-tuning amount and the alignment adjustment direction; Template adjustment unit: used to determine that the current key printing template does not need positioning adjustment, and send a template positioning accurate signal; When it is determined that the current key printing template needs to be positioned and adjusted, the second robot arm is used to fine-tune the position of the key printing template according to the currently acquired alignment fine-tuning amount and alignment adjustment direction, and then a template accurate positioning signal is issued; Lamination and gluing unit: It is used to laminarize the target substrate with the current key printing template after detecting the accurate signal of template positioning, and then start the gluing system to work and evenly apply glue that matches the current key printing template on the key printing template.

[0029] In this embodiment, the first template image is obtained by using a CCD detector to capture an image of a key printing template placed above the target substrate; the template analysis image is obtained by performing data preprocessing on the first template image, namely, denoising and binarization processing; the key positioning feature points are obtained by extracting the locator features from the first key image; the template positioning feature points refer to those obtained after extracting the locator features from the key printing template, and the corresponding locator numbers of each key printing template are different, namely, the corresponding locator features are different; the preset change matrix refers to a matrix obtained by using the coordinates of the predetermined analysis matching feature point pairs in the first template image and the first key image, combined with iterative calculation of the RANSAC algorithm, wherein the analysis matching feature points refer to preselected easily identifiable point pairs, such as edge intersections; the matching locator number combination refers to the locator number combination of the template that is expected to match the target substrate under the current printing process, wherein the locator number combination is composed of the arrangement and combination of the locator in the upper left corner of the template + the locator in the lower right corner of the template.

[0030] In this embodiment, the first feature coordinates refer to the feature coordinates determined after mapping the template positioning feature points to the first key image; the expected positioning feature points refer to the feature points obtained by filtering out from the key positioning feature points with the matching positioning symbol number combination as the filtering condition. For example, there are matching positioning symbol numbers L1, L2 and R3, where L1 is represented as upper left 1, L2 is represented as upper left 2, and R3 is represented as lower right 3. Then, the feature points representing upper left 1, upper left 2 and lower right 3 are filtered out from the key positioning feature points as the current expected positioning feature points; the second feature coordinates refer to the coordinates of the expected positioning feature points in the first key image.

[0031] In this embodiment, the first positioning difference evaluation coefficient is a coefficient obtained by analyzing the coordinate difference between the first feature coordinates of the template positioning feature point and the second feature coordinates of the expected positioning feature point using the cosine similarity algorithm; the setting of the evaluation threshold is predetermined, generally 0.3.

[0032] In this embodiment, for example, there are expected positioning feature points a1, a2, a3, and the first positioning difference evaluation coefficients with the current template positioning feature point b1 are x1, x2, x3, respectively, where: 3. At this time, the expected positioning feature point a1 is regarded as the first matching point of the template positioning feature point b1.

[0033] In this embodiment, the pattern identification feature refers to the edge feature of the specified identification pattern; the first identification feature point is obtained by extracting the edge feature of the specified identification pattern from the template analysis image using an edge detection algorithm, wherein the specified identification pattern is predetermined, such as a goldfish or a butterfly; the second identification feature point is obtained by extracting the edge feature of the specified identification pattern from the first key image currently acquired using an edge detection algorithm; the feature matching pair refers to a feature pair consisting of the first identification feature point and the second identification feature point with the largest matching coefficient determined by the feature matching algorithm, wherein the feature matching algorithm is an algorithm for extracting feature points and their feature vectors from an image in a predetermined manner, such as the SIFI algorithm; the matching coefficient is obtained by calculating the similarity between the feature vectors of the first identification feature point and the second identification feature point using a cosine similarity algorithm; the matching threshold is set in advance, generally at 0.7.

[0034] In this embodiment, the deviation output model refers to a model obtained by preprocessing the collected feature matching pairs between the template and the target substrate and the corresponding deviation data and selecting features related to the deviation prediction to obtain the first training data, and training the neural network with the obtained first training data, which is used to determine the deviation between the current template and the target substrate using the feature matching pairs as input.

[0035] In this embodiment, the deviation result refers to the pattern alignment deviation between the template analysis image and the first key image, including up and down translation deviation, left and right translation deviation and rotation angle deviation; the alignment fine-tuning amount refers to the distance or angle that needs to be moved or rotated to correct the deviation, including up and down fine-tuning amount, left and right fine-tuning amount and rotation fine-tuning amount, which are determined according to the translation deviation amount or angle deviation amount in the deviation result; the alignment adjustment direction refers to the direction in which the template needs to move or rotate, including up / down adjustment, left / right adjustment and clockwise / counterclockwise rotation adjustment; the template positioning accuracy signal is used to express the accurate positioning of the current key printing template.

[0036] In this embodiment, for example, there is a deviation result 1: Up and down translation deviation: +16 microns (indicates that the pattern in the first template image is shifted upward by 16 microns relative to the pattern in the first key image) Left-right translation deviation: -18 microns (indicates that the pattern in the first template image is shifted 18 microns to the left relative to the pattern in the first key image) Rotation angle deviation: -0.005 degrees (indicates that the pattern in the first template image is rotated 0.005 degrees counterclockwise relative to the pattern in the first key image) At this time, the up and down fine-tuning amount is 16 microns, and the up and down adjustment direction is downward adjustment; the left and right fine-tuning amount is 18 microns, and the up and down adjustment direction is right adjustment; the rotation fine-tuning amount is 0.005 degrees, and the rotation adjustment direction is clockwise rotation adjustment.

[0037] The beneficial effect of the above technical solution is that by performing alignment detection and adjustment on the key printing template, automatic pressing and gluing can help improve the accuracy of screen printing, thereby ensuring product quality and printing efficiency.

[0038] An embodiment of the present invention provides a precision control system for screen printing, which uses a second robot arm to fine-tune the position of a key printing template according to a currently acquired alignment fine-tune amount and alignment adjustment direction, including: By acquiring the historical adjustment record of the second robot arm and performing error analysis, the currently acquired alignment fine-tuning amount is adjusted to obtain the real-time fine-tuning amount; When the real-time fine-tuning amount is less than the set fine-tuning amount, a first fine-tuning time matching the current real-time fine-tuning amount is obtained from the set alignment time table; The real-time fine-tuning amount is calculated in combination with the first fine-tuning time to obtain a first fine-tuning speed; The second robot arm fine-tunes the position of the key printing template according to the first fine-tuning speed, the real-time fine-tuning amount and the alignment adjustment direction; When the real-time fine adjustment amount is not less than the set fine adjustment amount, the real-time fine adjustment amount is divided by a dynamic division coefficient to obtain a first fine adjustment amount; Subtracting the first fine adjustment amount from the real-time fine adjustment amount to obtain a first coarse adjustment amount; The calculation formula of the dynamic partition coefficient is as follows: ; In the formula, It is represented as the dynamic division coefficient at the current moment; P0 is represented as the preset division coefficient; Indicates the setting of fine adjustment amount; It is expressed as the real-time fine-tuning amount at the current moment; Obtaining a fine adjustment time matching the current first fine adjustment amount from the set alignment time table; The first fine adjustment amount is calculated in combination with the fine adjustment time to obtain the fine adjustment speed; The second robot arm performs a rough adjustment on the key printing template according to the set rough adjustment speed, the first rough adjustment amount and the alignment adjustment direction, and then performs a fine adjustment on the key printing template according to the fine adjustment speed, the first fine adjustment amount and the alignment adjustment direction.

[0039] In this embodiment, the second robot arm refers to an executive mechanical structure that controls the key printing template to perform position fine-tuning and pressing; the set fine-tuning amount is predetermined; the set alignment schedule is composed of the fine-tuning amount and the corresponding set fine-tuning time, wherein the set fine-tuning time refers to the preset execution adjustment duration of the second robot arm; the first fine-tuning time refers to the set fine-tuning time selected from the set alignment schedule with the real-time fine-tuning amount as the screening condition.

[0040] In this embodiment, the first fine-tuning speed is obtained by dividing the real-time fine-tuning amount by the first fine-tuning time; the fine-tuning time refers to the set fine-tuning time in the set alignment time table that matches the current first fine-tuning amount; the fine-tuning speed is obtained by dividing the first fine-tuning amount by the fine-tuning time.

[0041] The beneficial effect of the above technical solution is: by using the second robot arm to fine-tune the position of the key printing template according to the currently acquired alignment fine-tuning amount and alignment adjustment direction, it can help improve the accuracy of screen printing and ensure the printing effect.

[0042] The embodiment of the present invention provides a precision control system for screen printing, which obtains the historical adjustment record of the second robot arm and performs error analysis, adjusts the currently obtained alignment fine-tuning amount, and obtains the real-time fine-tuning amount, including: Extracting historical adjustment records within a preset time period of the current second robot arm from the template adjustment database; Obtaining corresponding historical position adjustment amounts and historical position required adjustment amounts of different adjustment types of the second robot arm from the historical adjustment records; Calculate a first adjustment difference between a historical position adjustment amount and a historical position adjustment amount required for the same adjustment type each time the second robot arm is adjusted; Determine a corresponding dynamic adjustment difference threshold for each adjustment type according to all the first adjustment differences obtained; Taking the first adjustment difference as the dependent variable, construct the adjustment difference change curve of each adjustment type according to the time sequence; Obtaining the first adjustment difference that is greater than the dynamic adjustment difference threshold from the adjustment difference variation curve, and marking the corresponding moment as the reference moment; Based on the reference time, segmenting the adjustment difference change curve, marking the curve portion corresponding to the time before the reference time as a first curve, and marking the curve portion corresponding to the time after the reference time as a second curve; Extracting curve features and performing weighted average calculation on the first curve and the second curve respectively, and obtaining a first variation coefficient and a second variation coefficient accordingly; Calculating a key adjustment coefficient based on the first change coefficient and the second change coefficient of each adjustment type; The key adjustment coefficient is used to adjust the currently acquired alignment fine-tuning amount to obtain a real-time fine-tuning amount.

[0043] In this embodiment, the template adjustment database is composed of the historical position adjustment records of the key printing template and the historical position adjustment records of the second robot arm; the preset time period is predetermined; the historical position adjustment amount refers to the actual amount of the historical adjustment of the substrate by the second robot arm; the historical position adjustment amount refers to the expected historical position adjustment amount of the substrate; the first adjustment difference refers to the position adjustment difference between the historical position adjustment amount and the corresponding historical position adjustment amount; the adjustment types include clockwise rotation angle adjustment, counterclockwise rotation angle adjustment, up and down translation, and left and right translation; the dynamic adjustment difference threshold is obtained by adding the calculated first adjustment difference average value and the maximum value of the first adjustment difference and then averaging them.

[0044] In this embodiment, the adjustment difference change curve is a curve constructed in time series with the first adjustment difference as the dependent variable; the reference moment refers to the corresponding historical moment in the adjustment difference change curve when the first first adjustment difference greater than the dynamic adjustment difference threshold is obtained; the first curve refers to the curve portion corresponding to the moment before the reference moment in the adjustment difference change curve; the second curve refers to the curve portion corresponding to the moment after the reference moment in the adjustment difference change curve; the first change coefficient is obtained by extracting the curve features of the first curve and calculating the weighted average; the second change coefficient is obtained by extracting the curve features of the second curve and calculating the weighted average; the key adjustment coefficient is used to adjust the obtained alignment fine-tuning amount to obtain the real-time fine-tuning amount.

[0045] The beneficial effect of the above technical solution is: by obtaining the historical adjustment records of the second robot arm and performing error analysis, the currently obtained alignment fine-tuning amount is adjusted, which can effectively ensure the accuracy of the template alignment, thereby improving the accuracy of screen printing and ensuring the printing effect.

[0046] An embodiment of the present invention provides a precision control system for screen printing, and the calculation formula of the key adjustment coefficient is as follows: ; In the formula, Expressed as the key adjustment factor; It is expressed as the area of ​​the first curve corresponding to the i-th adjustment type, where i=1, 2, , n; n represents the total number of adjustment types; It is represented as the area of ​​the second curve corresponding to the i-th adjustment type; It is represented as the second variation coefficient corresponding to the i-th adjustment type; It is represented as the first change coefficient corresponding to the i-th adjustment type; ln represents the natural logarithm sign; e represents a constant with a value of 2.7; It is represented as the absolute time difference between the time period corresponding to the first curve and the time period corresponding to the second curve of the i-th adjustment type; T is represented as a preset time period.

[0047] The beneficial effect of the above technical solution is that the alignment fine-tuning amount can be accurately adjusted by calculating the key adjustment coefficient, which is beneficial to ensure the accurate alignment of the template, improve the accuracy of screen printing, and ensure the printing effect.

[0048] An embodiment of the present invention provides a precision control system for screen printing, wherein the curing module comprises: Transfer unit: used for transferring the target printing substrate after the gluing to the second conveyor belt by using the first robot arm, and the second conveyor belt transfers the target printing substrate after the gluing to the set imprinting machine; Curing unit: The set stamping machine performs curing treatment on the target printing material after the glue is applied by using a corresponding curing method.

[0049] In this embodiment, the first robot arm is used to adjust the position and transfer the target substrate; the second conveyor belt refers to a conveying device that transfers the target substrate after brushing with glue to a set imprinting machine; the set imprinting machine refers to a machine used to cure the target substrate after brushing with glue; there are several curing methods, and different types of glue may correspond to different curing methods.

[0050] The beneficial effect of the above technical solution is that through the cooperation of the first robot arm and the second conveyor belt, the target substrate after brushing glue is quickly and accurately transferred to the set imprinting machine for curing treatment, which can ensure that the glue of the target substrate is fully cured, thereby improving the firmness and durability of the product.

[0051] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A precision control system for screen printing, characterized in that: include: Mode matching module: used to determine the current first placement mode according to printing requirements; Printing substrate positioning module: used to respond to the first placement mode, place the target printing substrate in a fixed area of ​​the printing table, and then perform position detection and adjustment; Template pressing module: used to place the key printing template in a specific area of ​​the target substrate for pressing and gluing after confirming the accurate positioning of the target substrate; Curing module: used to quickly transfer the target substrate after glue application to the set imprinting machine for curing based on the robot arm.

2. A precision control system for screen printing according to claim 1, characterized in that: The first printing mode includes an automatic placement mode and a non-automatic placement mode.

3. The precision control system for screen printing according to claim 1, characterized in that: The printing positioning module comprises: Placement unit: used for workers to manually place the target substrate in the substrate fixing area when the first placement mode is the non-automatic placement mode; When the first placement mode is the automatic mode, the target substrate is conveyed to the substrate fixing area by the first conveyor belt; Detection unit: used for detecting that the target substrate is placed in the fixed printing area, performing position detection using a CCD detector to obtain a first position image; performing denoising and image enhancement processing on the first position image to obtain a first key image; Using a set similarity algorithm, similarity matching is performed between the feature points of the printed object extracted from the first key image and the reference feature points of the reference image to obtain a matching pair; According to the obtained matching pair, the first pixel coordinate of the substrate feature point of the target substrate is obtained; Inputting the first pixel coordinate into a pre-established coordinate output model to obtain position detection information; An adjustment unit: used for comparing the position detection information with a preset position of a substrate to obtain a first position difference; If there is a first position difference greater than a set position difference threshold, it is determined that the current target substrate position is inaccurate; based on the first position difference, a position fine-tuning amount and a position adjustment direction are determined; Using the first robot arm to move the target substrate to a preset substrate position according to the position fine-tuning amount and the position adjustment direction, and then sending a substrate position accuracy signal; If there is no first position difference greater than the set position difference threshold, it is determined that the current target printing object is in an accurate position, and a printing position accurate signal is issued.

4. The precision control system for screen printing according to claim 1, characterized in that: The template pressing module comprises: Template positioning unit: used to place the current key printing template in the upper area of ​​the target substrate after detecting the accurate signal of the substrate position; use the initial positioning block and the re-positioning block to perform two template positioning analyses to determine the template positioning situation; Initial positioning block: used to capture the image of the key printing template using a CCD detector to obtain the first template image; Performing data preprocessing on the first template image to obtain a template analysis image; Extracting locator features from the template analysis image to obtain template locating feature points; Mapping the template positioning feature points to the currently acquired first key image using a preset change matrix to obtain first feature coordinates of the template positioning feature points; Extracting locator features from the first key image to obtain key locating feature points; Based on the matching locator number combination, the positioning feature points expected to match the current key printing template are screened out from the acquired key positioning feature points, and marked as expected positioning feature points; Determine a second feature coordinate of the desired positioning feature point in the first key image; Compare the first characteristic coordinates of the template positioning feature point with the second characteristic coordinates of each expected positioning feature point to obtain a first positioning difference evaluation coefficient; The desired positioning feature point with the smallest first positioning difference evaluation coefficient is regarded as the first matching point of the current template positioning feature point; If the first positioning difference evaluation coefficients of all template positioning feature points and the corresponding first matching points are not greater than the set evaluation threshold, it is determined that the current key printing template does not need positioning adjustment; Otherwise, it is determined that the current key printing template needs to be positioned and adjusted, and the template positioning deviation analysis is performed using the repositioning block; Repositioning block: used to extract pattern identification features from the template analysis image using an edge detection algorithm to obtain a first identification feature point; Extracting pattern identification features from the currently acquired first key image using an edge detection algorithm to obtain second identification feature points; Using a feature matching algorithm, feature matching is performed on the first identification feature point and the second identification feature point to obtain a feature matching pair; Input the feature matching pairs whose matching coefficients are greater than the set matching threshold into the pre-established deviation output model to obtain the deviation results; According to the deviation result, obtaining the alignment fine-tuning amount and the alignment adjustment direction; Template adjustment unit: used to determine that the current key printing template does not need positioning adjustment, and send a template positioning accurate signal; When it is determined that the current key printing template needs to be positioned and adjusted, the second robot arm is used to fine-tune the position of the key printing template according to the currently acquired alignment fine-tuning amount and alignment adjustment direction, and then a template accurate positioning signal is issued; Lamination and gluing unit: It is used to laminarize the target substrate with the current key printing template after detecting the accurate signal of template positioning, and then start the gluing system to work and evenly apply glue that matches the current key printing template on the key printing template.

5. The precision control system for screen printing according to claim 4, characterized in that: The second robot arm is used to fine-tune the position of the key printing template according to the currently acquired alignment fine-tuning amount and alignment adjustment direction, including: By acquiring the historical adjustment record of the second robot arm and performing error analysis, the currently acquired alignment fine-tuning amount is adjusted to obtain the real-time fine-tuning amount; When the real-time fine-tuning amount is less than the set fine-tuning amount, a first fine-tuning time matching the current real-time fine-tuning amount is obtained from the set alignment time table; The real-time fine-tuning amount is calculated in combination with the first fine-tuning time to obtain a first fine-tuning speed; The second robot arm fine-tunes the position of the key printing template according to the first fine-tuning speed, the real-time fine-tuning amount and the alignment adjustment direction; When the real-time fine adjustment amount is not less than the set fine adjustment amount, the real-time fine adjustment amount is divided by a dynamic division coefficient to obtain a first fine adjustment amount; Subtracting the first fine adjustment amount from the real-time fine adjustment amount to obtain a first coarse adjustment amount; The calculation formula of the dynamic partition coefficient is as follows: ; In the formula, It is represented as the dynamic division coefficient at the current moment; P0 is represented as the preset division coefficient; Indicates the setting of fine adjustment amount; It is expressed as the real-time fine-tuning amount at the current moment; Obtaining a fine adjustment time matching the current first fine adjustment amount from the set alignment time table; The first fine adjustment amount is calculated in combination with the fine adjustment time to obtain the fine adjustment speed; The second robot arm performs a rough adjustment on the key printing template according to the set rough adjustment speed, the first rough adjustment amount and the alignment adjustment direction, and then performs a fine adjustment on the key printing template according to the fine adjustment speed, the first fine adjustment amount and the alignment adjustment direction.

6. The precision control system for screen printing according to claim 5, characterized in that: By acquiring the historical adjustment record of the second robot arm and performing error analysis, the currently acquired alignment fine-tuning amount is adjusted to obtain the real-time fine-tuning amount, including: Extracting historical adjustment records within a preset time period of the current second robot arm from the template adjustment database; Obtaining corresponding historical position adjustment amounts and historical position required adjustment amounts of different adjustment types of the second robot arm from the historical adjustment records; Calculate a first adjustment difference between a historical position adjustment amount and a historical position adjustment amount required for the same adjustment type each time the second robot arm is adjusted; Determine a corresponding dynamic adjustment difference threshold for each adjustment type according to all the first adjustment differences obtained; Taking the first adjustment difference as the dependent variable, construct the adjustment difference change curve of each adjustment type according to the time sequence; Obtaining the first adjustment difference that is greater than the dynamic adjustment difference threshold from the adjustment difference variation curve, and marking the corresponding moment as the reference moment; Based on the reference time, segmenting the adjustment difference change curve, marking the curve portion corresponding to the time before the reference time as a first curve, and marking the curve portion corresponding to the time after the reference time as a second curve; Extracting curve features and performing weighted average calculation on the first curve and the second curve respectively, and obtaining a first variation coefficient and a second variation coefficient accordingly; Calculating a key adjustment coefficient based on the first change coefficient and the second change coefficient of each adjustment type; The key adjustment coefficient is used to adjust the currently acquired alignment fine-tuning amount to obtain a real-time fine-tuning amount.

7. The precision control system for screen printing according to claim 6, characterized in that: The calculation formula of the key adjustment coefficient is as follows: ; In the formula, Expressed as the key adjustment factor; It is expressed as the area of ​​the first curve corresponding to the i-th adjustment type, where i=1, 2, , n; n represents the total number of adjustment types; It is represented as the area of ​​the second curve corresponding to the i-th adjustment type; It is represented as the second variation coefficient corresponding to the i-th adjustment type; It is represented as the first change coefficient corresponding to the i-th adjustment type; ln represents the natural logarithm sign; e represents a constant with a value of 2.7; It is represented as the absolute time difference between the time period corresponding to the first curve and the time period corresponding to the second curve of the i-th adjustment type; T is represented as a preset time period.

8. The precision control system for screen printing according to claim 1, characterized in that: The curing module comprises: Transfer unit: used for transferring the target printing substrate after the gluing to the second conveyor belt by using the first robot arm, and the second conveyor belt transfers the target printing substrate after the gluing to the set imprinting machine; Curing unit: The set stamping machine performs curing treatment on the target printing material after the glue is applied by using a corresponding curing method.

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