A PCB board surface marking printing method and system

Abstract

The invention relates to the technical field of PCB board printing, and specifically discloses a PCB board surface identification printing method and system, comprising: obtaining a substrate identification image of an original PCB board, wherein the substrate identification image includes a reference image and an identification character distribution diagram; segmenting the reference image according to the identification character distribution diagram to obtain a plurality of first substrate segmented images; obtaining deformation values ​​of all pixel blocks in each of the first substrate segmented images; and judging whether the deformation value is in a preset interval. The invention can accurately judge the collapse degree of the deformation area, and can generate a corresponding nozzle adjustment voltage according to the collapse degree. When the nozzle prints the collapse at the location, the nozzle is adjusted according to the adjustment voltage to prevent the ink in the concave part of the PCB surface from being unevenly distributed, so as to realize accurate printing of the PCB board and improve the printing quality and efficiency.

Description

Technical Field

[0001] The invention relates to the technical field of PCB board printing, and in particular to a method and system for printing a surface mark on a PCB board. Background Art

[0002] PCB is a common component in electronic devices, used to support and connect electronic components. It is a plate-like material used for mechanical support and electrical connection, usually made of fiberglass, plastic or metal. The surface of the PCB is generally printed with logos, including component values, circuit icons, production dates, and company logos. PCB character inkjet printer is the application of computer technology in the PCB industry. It can not only produce PCB boards conveniently and quickly, but also be conducive to environmental protection of "reducing pollution and reducing emissions", meet the requirements of "green production", and at the same time enhance the competitiveness of enterprises in the PCB industry, reduce enterprise costs, increase enterprise profits, and thus enhance the core competitiveness of enterprises.

[0003] The existing inkjet printing system is an indispensable and important module in the PCB character inkjet printer. The function of inkjet printing is to print a data matrix of a certain arrangement onto the PCB board through a nozzle. The existing PCB board does not have sufficient support around larger components or connectors, which leads to depression during processing or use. In this way, during the character inkjet printing process, the depression on the PCB surface will cause the ink to be unevenly distributed on the surface, which may make the printed pattern unclear or blurred, thereby affecting the function and reliability of the circuit board. Summary of the invention

[0004] The purpose of the present invention is to provide a PCB board surface marking printing method and system to solve the technical problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method for printing a surface mark of a PCB board, comprising:

[0007] Acquire a substrate identification image of an original PCB board, wherein the substrate identification image includes a reference image and an identification character distribution map;

[0008] Segmenting the reference image according to the identification character distribution map to obtain a plurality of first substrate segmentation images;

[0009] Obtaining deformation values ​​of all pixel blocks in each of the first substrate segmentation images;

[0010] Determine whether the deformation value is within a preset range;

[0011] If yes, it is determined that there is no deformation area in the first substrate segmentation image, and a first logo printing sequence table is generated based on the logo character distribution map, and logo printing is performed in sequence according to the first logo printing sequence table;

[0012] If not, determining that the first substrate segmentation image has a deformed area, taking the first substrate segmentation image with the deformed area as the second substrate segmentation image, and defining the pixel block in the second substrate segmentation image as a deformed pixel block;

[0013] Acquiring position information of each deformed pixel block, and calculating a collapse value of each deformed pixel block according to the position information;

[0014] Calculate the adjustment waveform voltage value of each deformed pixel block in the second substrate segmentation image according to the collapse value and the deformation value;

[0015] Acquire the collapse level value of each deformed pixel block in the second substrate segmentation image according to the collapse value, and sort the multiple collapse level values ​​according to a preset condition to obtain a second mark printing sequence table;

[0016] Sort each adjustment waveform voltage value according to the second identification printing sequence table to obtain a nozzle adjustment sequence table;

[0017] The logo printing is performed according to the second logo printing sequence table and the nozzle adjustment sequence table.

[0018] Preferably, the step of segmenting the reference image according to the identification character distribution map to obtain a plurality of first substrate segmented images includes:

[0019] Obtaining a plurality of character information and position information corresponding to the character information according to the identification character distribution map;

[0020] Establishing a bounding box for the character information to obtain a character bounding box;

[0021] Acquire a to-be-printed area of ​​a character boundary box on a reference image based on the position information;

[0022] The plurality of to-be-printed areas on the reference image are segmented and extracted to obtain a first substrate segmented image.

[0023] Preferably, the step of obtaining deformation values ​​of all pixel blocks in each of the first substrate segmentation images includes:

[0024] Acquire information of a plurality of pixel blocks in the first substrate segmentation image;

[0025] Acquire coordinates of feature points of multiple pixel blocks according to pixel block information;

[0026] Get the gray value corresponding to the coordinates of the feature point of the pixel block;

[0027] Get the grayscale center coordinates of the pixel block information;

[0028] The center distance value of each pixel block feature point is calculated according to the pixel block feature point coordinates, gray center coordinates and gray value. The calculation formula is:

[0029] m pq =∑ p ∑ q (xx 3 ) p (yy 3 ) q I (x，y) ;

[0030] Among them, m pq is the center distance value, x represents the horizontal coordinate of the pixel block feature point, y represents the vertical coordinate of the pixel block feature point, and x 3 Indicates the grayscale center horizontal coordinate, y 3 Indicates the grayscale center ordinate, I (x，y) is the gray value of the pixel block feature point at coordinates (x, y), p is the order in the x direction of the coordinates (x, y), and q is the order in the y direction of the coordinates (x, y);

[0031] The deformation value of each pixel block is calculated according to the center distance value. The calculation formula is:

[0032]

[0033] Among them, S pq is the deformation value of the pixel block, m pq is the center distance value.

[0034] Preferably, the step of obtaining the position information of each deformed pixel block and calculating the collapse value of each deformed pixel block according to the position information comprises:

[0035] Obtain the first centroid coordinates of all deformed pixel blocks according to the position information;

[0036] Acquire the directional features corresponding to each deformed pixel block according to the first centroid coordinates;

[0037] Obtain the deformation area of ​​all deformed pixel block coordinates according to the first centroid coordinates;

[0038] Determine key point pixels within a preset range according to the directional characteristics, and define the key point pixels as a neighborhood;

[0039] Get the coordinates of the second centroid of the neighborhood;

[0040] The collapse value of each deformed pixel block is calculated according to the first centroid coordinates and the second centroid coordinates, wherein the collapse value calculation formula is:

[0041]

[0042] Among them, d is the collapse value of the deformed pixel block, (x 1 ,y 1 ) is the first centroid coordinate, (x 2 ,y 2 ) are the coordinates of the second centroid.

[0043] Preferably, the step of calculating the adjustment waveform voltage value of each deformed pixel block in the second substrate segmentation image according to the collapse value and the deformation value comprises:

[0044] Obtaining a preset voltage waveform value of each pixel block;

[0045] Obtaining the collapse value of each pixel block;

[0046] Obtain the weight coefficient of the collapse value of each pixel block;

[0047] Obtaining a deformation value of a pixel block of each pixel block;

[0048] Obtaining a weight coefficient of a pixel block deformation value of each pixel block;

[0049] The voltage value of the regulated waveform of each pixel block is calculated according to the collapse value and the bending energy of the pixel block. The calculation formula is:

[0050] V a =V b |(E*W E +d*W d -1)|;

[0051] Among them, V a To adjust the waveform voltage value, V b is the preset voltage waveform value, E is the pixel block deformation value, W E is the weight coefficient of the pixel block deformation value, d is the collapse value, W d is the weight coefficient of the collapse value.

[0052] Preferably, the step of obtaining the collapse level value of each deformed pixel block in the second substrate segmentation image according to the collapse value comprises:

[0053] Obtaining a collapse value of each pixel block in the second substrate segmentation image;

[0054] Get the collapse coefficient of the collapse value;

[0055] Calculate the collapse level value of each pixel block according to the collapse value:

[0056] L = d * c;

[0057] Among them, L is the collapse level value, d is the collapse value of the pixel block, and c is the collapse coefficient;

[0058] The present invention also provides a PCB board surface marking printing system, comprising:

[0059] A first acquisition module is used to acquire a substrate identification image of an original PCB board, wherein the substrate identification image includes a reference image and an identification character distribution map;

[0060] An image segmentation module, used for segmenting the reference image according to the identification character distribution map to obtain a plurality of first substrate segmentation images;

[0061] A second acquisition module, used for acquiring deformation values ​​of all pixel blocks in each of the first substrate segmentation images;

[0062] A judgment module, used to judge whether the deformation value is within a preset range;

[0063] If yes, it is determined that there is no deformation area in the first substrate segmentation image, and a first logo printing sequence table is generated based on the logo character distribution map, and logo printing is performed in sequence according to the first logo printing sequence table;

[0064] If not, determining that the first substrate segmentation image has a deformed area, taking the first substrate segmentation image with the deformed area as the second substrate segmentation image, and defining the pixel block in the second substrate segmentation image as a deformed pixel block;

[0065] A third acquisition module, used to acquire position information of each deformed pixel block, and calculate a collapse value of each deformed pixel block according to the position information;

[0066] A first calculation module, used for calculating the adjustment waveform voltage value of each deformed pixel block in the second substrate segmentation image according to the collapse value and the deformation value;

[0067] A fourth acquisition module, configured to acquire a collapse level value of each deformed pixel block in the second substrate segmentation image according to the collapse value, and sort the multiple collapse level values ​​according to a preset condition to obtain a second mark printing sequence table;

[0068] A sorting module, used for sorting each adjustment waveform voltage value according to the second identification printing sequence table to obtain a nozzle adjustment sequence table;

[0069] The printing module is used to perform identification printing according to the second identification printing sequence table and the nozzle adjustment sequence table.

[0070] Preferably, the second acquisition module includes:

[0071] A first acquisition unit, used to acquire information of a plurality of pixel blocks in the substrate segmentation image;

[0072] A second acquisition unit, used for acquiring coordinates of feature points of a plurality of pixel blocks according to the pixel block information;

[0073] A third acquisition unit is used to acquire the grayscale value corresponding to the coordinates of the feature point of the pixel block;

[0074] A fourth acquisition unit, used to acquire the grayscale center coordinates of the pixel block information;

[0075] The first calculation unit is used to calculate the center distance value of each pixel block feature point according to the pixel block feature point coordinates, gray center coordinates and gray value, and the calculation formula is:

[0076] m pq =∑ p ∑ q (xx 3 ) p (yy 3 ) q I (x，y) ;

[0077] Among them, m pq is the center distance value, x represents the horizontal coordinate of the pixel block feature point, y represents the vertical coordinate of the pixel block feature point, and x 3 Indicates the grayscale center horizontal coordinate, y 3 Indicates the grayscale center ordinate, I (x，y) is the gray value of the pixel block feature point at coordinates (x, y), p is the order in the x direction of the coordinates (x, y), and q is the order in the y direction of the coordinates (x, y);

[0078] The second calculation unit is used to calculate the deformation value of each pixel block according to the center distance value, and the calculation formula is:

[0079]

[0080] Among them, S pq is the deformation value of the pixel block, m pq is the center distance value.

[0081] Preferably, the third acquisition module includes:

[0082] A fifth acquisition unit, used for acquiring first centroid coordinates of all deformed pixel block coordinates according to the position information;

[0083] The sixth acquisition unit is used to acquire the directional features corresponding to each deformed pixel block according to the first centroid coordinates.

[0084] A seventh acquisition unit, configured to acquire the deformation area of ​​all deformed pixel block coordinates according to the first centroid coordinates;

[0085] An eighth acquisition unit, used to determine key point pixels within a preset range according to the directional features, and define the key point pixels as a neighborhood;

[0086] A ninth acquisition unit, used for acquiring the coordinates of the second centroid of the neighborhood;

[0087] The second calculation unit is used to calculate the collapse value of the deformed pixel block according to the first centroid coordinates and the second centroid coordinates, wherein the collapse value calculation formula is:

[0088]

[0089] Among them, d is the collapse value of the deformed pixel block, (x 1 ,y 1 ) is the first centroid coordinate, (x 2 ,y 2 ) are the coordinates of the second centroid.

[0090] Preferably, the first calculation module includes:

[0091] a tenth acquiring unit, configured to acquire a preset voltage waveform value of each pixel block;

[0092] an eleventh obtaining unit, configured to obtain a collapse value of each pixel block;

[0093] A twelfth obtaining unit, used to obtain a weight coefficient of a collapse value of each pixel block;

[0094] A thirteenth obtaining unit, configured to obtain a deformation value of a pixel block of each pixel block;

[0095] A fourteenth obtaining unit, used to obtain a weight coefficient of a pixel block deformation value of each pixel block;

[0096] The fourth calculation unit is used to calculate the adjustment waveform voltage value of each pixel block according to the collapse value and the pixel block bending energy, and the calculation formula is:

[0097] V a =V b |(E*W E +d*W d -1)|;

[0098] Among them, V a To adjust the waveform voltage value, V b is the preset voltage waveform value, E is the pixel block deformation value, W E is the weight coefficient of the pixel block deformation value, d is the collapse value, W d is the weight coefficient of the collapse value.

[0099] The beneficial effects of the present application are as follows: the present invention can improve printing quality and efficiency: by acquiring image information of a PCB board to be printed, and acquiring a substrate identification image according to the image information, and then segmenting the reference image according to the identification character distribution map, a plurality of first substrate segmented images are obtained, and the first substrate segmented images can be classified, and the deformation value of each first substrate segmented image is calculated to determine whether the first substrate segmented image is deformed, and a second substrate segmented image is obtained, and by quantifying the degree of collapse of the deformation area of ​​the second substrate segmented image, the degree of collapse of the deformation area can be accurately determined, and a corresponding nozzle adjustment voltage can be generated according to the degree of collapse, and when the nozzle prints the collapse at that location, it is adjusted according to the adjustment voltage to prevent uneven distribution of ink in the recessed part of the PCB surface, so as to achieve accurate printing of the PCB board and improve printing quality and efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0100] Figure 1 The figure is a schematic diagram of a method flow of an embodiment of the present application.

[0101] Figure 2 A schematic diagram of the system structure of an embodiment of the present application.

[0102] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0103] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0104] like Figure 1 As shown, the present application provides a method for printing a surface mark on a PCB board, comprising:

[0105] S1. Acquire a substrate identification image of an original PCB board, wherein the substrate identification image includes a reference image and an identification character distribution map;

[0106] S2, segmenting the reference image according to the identification character distribution map to obtain a plurality of first substrate segmentation images;

[0107] S3, obtaining deformation values ​​of all pixel blocks in each of the first substrate segmentation images;

[0108] S4, determining whether the deformation value is within a preset range;

[0109] If yes, it is determined that there is no deformation area in the first substrate segmentation image, and a first logo printing sequence table is generated based on the logo character distribution map, and logo printing is performed in sequence according to the first logo printing sequence table;

[0110] If not, determining that the first substrate segmentation image has a deformed area, taking the first substrate segmentation image with the deformed area as the second substrate segmentation image, and defining the pixel block in the second substrate segmentation image as a deformed pixel block;

[0111] S5, obtaining the position information of each deformed pixel block, and calculating the collapse value of each deformed pixel block according to the position information;

[0112] S6, calculating the adjustment waveform voltage value of each deformed pixel block in the second substrate segmentation image according to the collapse value and the deformation value;

[0113] S7, obtaining a collapse level value of each deformed pixel block in the second substrate segmentation image according to the collapse value, and sorting the multiple collapse level values ​​according to a preset condition to obtain a second mark printing sequence table;

[0114] S8, sorting each adjustment waveform voltage value according to the second identification printing sequence table to obtain a nozzle adjustment sequence table;

[0115] S9, performing logo printing according to the second logo printing sequence table and the nozzle adjustment sequence table.

[0116] As described in the above steps S1-S9, when inkjet printing is performed on the concave parts on the surface of the PCB board, uneven ink distribution may occur. The concave part of the PCB board surface will cause the ink to accumulate at the midpoint of the concave part, and be thin at the edge of the concave part and the convex part, which will cause the ink distribution of the printed pattern to be uneven, and some areas may have too much or too little ink, thereby affecting the printing quality; and the concave part of the PCB board will cause the distribution of the ink on the surface to be unstable, which may make the printed pattern blurred. The ink will accumulate in the concave part, which may blur the edge and details of the pattern, affecting the clarity of the pattern, and the components on the PCB board need to be marked. Only by identifying the components can the user understand and confirm the components. For example, the length of the resistor component is only 1 cm, and its surface will be marked with multiple different colors. In the prior art, the resistance value represented by the multiple colors is generally calculated. However, usually, a plurality of resistor components are distributed on a PCB board. If the identification is unclear and only relies on color to distinguish, the user needs to calculate the resistance value of each resistor component. When it is necessary to quickly find a resistor component with a certain resistance value, it will undoubtedly be time-consuming and labor-intensive, and the work efficiency is extremely low. Therefore, it is particularly important to print the PCB surface clearly and accurately. Based on this, the present invention first obtains the image information of the original PCB board, and according to The image information obtains the substrate identification image, which is composed of a reference image and an identification character distribution map. The reference image is an unprinted image of the original PCB board, and the identification character distribution map contains the position information of the identification characters in the reference image; according to the identification character distribution map, the reference image is segmented to obtain multiple first substrate segmentation images, so that the reference image can be segmented into multiple small blocks, each small block corresponds to a first substrate segmentation image, such segmentation can achieve accurate printing of different areas, and can obtain the deformation values ​​of all pixel blocks in each first substrate segmentation image, the deformation value represents the deformation degree of the pixel block, and the deformation value can be accurately calculated by calculating the deformation value. Deformation of each pixel block is determined, and by judging whether the deformation value of each pixel block is within a preset interval, it can be judged whether each first substrate segmentation image has a deformation area; if the deformation value is within the preset interval, it is determined that the first substrate segmentation image does not have a deformation area, and a first identification printing sequence table is generated based on the identification character distribution diagram, and the nozzle prints the identification in sequence according to the first identification printing sequence table; if not, it is determined that the first substrate segmentation image has a deformation area, and the first substrate segmentation image is output to obtain a second substrate segmentation image, and the image that meets the requirements and the image that does not meet the requirements are distinguished by the above method, so as to be printed and processed separately;The collapse value of each deformed pixel block is calculated according to the position information of the deformed pixel block, and the collapsed part of the second substrate segmentation image is quantified by the collapse value. At the same time, the collapse degree of the concave part is determined by calculating the collapse value of each deformed pixel block, and the intensity of the inkjet is readjusted according to the collapse degree. Specifically, the corresponding collapse level value is obtained according to the collapse value of the deformed pixel block, and the collapse level values ​​corresponding to the deformed pixel blocks are sorted from large to small to obtain the second logo printing sequence table. According to the sorting result of the collapse level value, the printing order is determined so that orderly printing is performed according to the priority. By sorting in order, the deformed pixel block with a larger degree of collapse can be printed first. When the nozzle moves to a deformed pixel block, the adjustment waveform voltage value corresponding to the deformed pixel block being printed is obtained according to the nozzle adjustment sequence table, and the inkjet intensity of the nozzle is adjusted according to the adjustment waveform voltage value. The nozzle can accurately adjust the inkjet intensity according to the depression depth of the PCB surface, thereby avoiding the formation of different pixel blocks in the depression of the PCB surface with the same intensity of ink, and preventing the ink from being unevenly distributed on the depression surface of the PCB surface, thereby improving the clarity and accuracy of the printed pattern. ;

[0117] In one embodiment, the step of segmenting the reference image according to the identification character distribution map to obtain a plurality of substrate segmentation images includes:

[0118] S201, obtaining a plurality of character information and position information corresponding to the character information according to a distribution map of identification characters;

[0119] S202, establishing a bounding box for the character information to obtain a character bounding box;

[0120] S203, acquiring a to-be-printed area of ​​a character boundary box on the reference image based on the position information;

[0121] S204 , segmenting and extracting the plurality of to-be-printed areas on the reference image to obtain a first substrate segmented image.

[0122] As described in the above steps S201-S204, the present invention accurately extracts multiple character information and obtains their position information in the image by analyzing the identification character distribution map, which can ensure that the subsequent processing steps are based on accurate data to avoid errors and inaccuracies. At the same time, a boundary box is established for the character information. The advantage of obtaining the character boundary box is that the character information can be effectively surrounded to form a boundary box. In this way, it can be ensured that the subsequent processing steps are only operated on the character information, avoiding the processing of other irrelevant areas, improving the processing efficiency and accuracy, and obtaining the to-be-printed area of ​​the character boundary box on the reference image based on the position information, and the to-be-printed area can be accurately determined according to the position information of the character boundary box. The advantages of segmenting and extracting multiple to-be-printed areas on the reference image and obtaining the first substrate segmented image are that the to-be-printed area can be segmented and extracted, and the first substrate segmented image can be obtained. Each to-be-printed area can be processed separately to ensure the printing quality and accuracy of each area, and the reference image can be segmented to reduce the detection of a large range of reference images, reduce data redundancy, and improve processing efficiency.

[0123] In one embodiment, the step of obtaining deformation values ​​of all pixel blocks in each of the first substrate segmentation images includes:

[0124] S301, obtaining information of a plurality of pixel blocks in a substrate segmentation image;

[0125] S302, obtaining coordinates of feature points of multiple pixel blocks according to pixel block information;

[0126] S303, obtaining the grayscale value corresponding to the coordinates of the feature point of the pixel block;

[0127] S304, obtaining the grayscale center coordinates of the pixel block information;

[0128] S305, calculating the center distance value of the pixel block feature point according to the pixel block feature point coordinates and grayscale values, the calculation formula is:

[0129] m pq =∑ p ∑ q (xx 3 ) p (yy 3 ) q I (x，y) ;

[0130] Among them, m pq is the center distance value, x represents the horizontal coordinate of the pixel block feature point, y represents the vertical coordinate of the pixel block feature point, and x 3 Indicates the grayscale center horizontal coordinate, y 3 Indicates the grayscale center ordinate, I (x，y)is the gray value of the pixel block feature point at coordinates (x, y), p is the order in the x direction of the coordinates (x, y), and q is the order in the y direction of the coordinates (x, y);

[0131] S306, calculating the deformation value of each pixel block according to the center distance value, and the calculation formula is:

[0132]

[0133] Among them, S pq is the deformation value of the pixel block, m pq is the center distance value.

[0134] As described in the above steps S301-S306, the present invention analyzes multiple pixel block information in the substrate segmentation image, and multiple pixel blocks can be combined into a line in the substrate segmentation image. By obtaining multiple pixel block information, the position and shape information of the line can be understood, and accurate line information can be provided for subsequent processing steps to ensure the accuracy and reliability of printing. For example, the position and shape of the line (multiple pixel block information) can be determined by detecting features such as the width, spacing and direction of the line, thereby accurately segmenting the substrate image; at the same time, the coordinates of multiple pixel feature points in each pixel block information are determined, and the pixel feature points are used to represent the composition of each pixel block. The pixel feature point coordinates represent the position of the pixel block in the image. The feature points of each pixel block can be extracted separately to provide accurate data for subsequent calculations. By sampling the pixel blocks around the feature points in each pixel block, the grayscale value of the feature point can be obtained, thereby understanding information such as the brightness and contrast of the feature point, and improving the pixel The extraction accuracy of the block is determined by the grayscale center coordinates (the grayscale center coordinates represent the center position of the grayscale distribution in the pixel block feature point) to determine the grayscale center of the pixel block feature point (if the first substrate segmentation image is deformed, the floating-point value of the statistic of the grayscale distribution in the image will also change, and the grayscale center of the pixel block in the first substrate segmentation image will change). The center distance value of each pixel block feature point is determined by calculating the Euclidean distance between the coordinates of each pixel block feature point and the grayscale center coordinates. The center distance value is a measure that describes the distribution of the pixel block feature point relative to its grayscale center, reflecting the distribution of the feature point around the grayscale center, including the shape, size and direction of the distribution. When (p) and (q) are 0 (i.e. (m_{00})), it is actually the sum of the grayscale values ​​of all pixels in the image or pixel block, reflecting the overall brightness level. When (p) or (q) is not 0, the center distance provides more information about the shape and direction of the image or pixel block. For example, (m_{10}) and (m_{01}) are related to the position of the center of gravity of the image or pixel block on the x-axis and y-axis respectively, while (m_{11}) contains information about the shape direction and inclination. Suppose there is a pixel block containing 4 feature points. The coordinates and grayscale values ​​of each feature point are shown in the following table:

[0135] Feature point number (x) (y) (I(x,y)) 1 1 2 100 2 2 3 150 3 3 2 200 4 4 3 250

[0136] At the same time, assuming that the grayscale center coordinates of the pixel block are ((x_3, y_3) = (2.5, 2.5)),

[0137] According to the above formula:

[0138] 0th order moment ((p=0,q=0)), m_{00}=700, where ((x-2.5)0) and ((y-2.5)0) of each feature point are equal to 1, because they are both 0th power;

[0139] 1st order x moment ((p=1,q=0)), m_{10}=250;

[0140] 1st order y moment ((p=0,q=1)), m_{01}=75;

[0141] By calculating the center distances of different orders, various features of the image can be extracted, such as size, direction, shape, etc. In deformation detection, by comparing the center distance values ​​of different images or pixel blocks, the similarities and differences between them can be evaluated, which serves as the basis for judging whether there is deformation;

[0142] Deformation value (S pq ) is calculated based on the center distance value, which quantifies the degree of deformation of the pixel block in a specific direction. In image analysis, the deformation value can be used to detect small deformations or displacements in the image, such as small ridges, depressions or distortions on the surface of the material. For example, in the process of printing the logo on the surface of the PCB board, by calculating the deformation value of each pixel block, the small deformation or unevenness of the surface of the PCB board can be detected. This helps to ensure the manufacturing quality of the PCB board and avoid poor welding and signal transmission problems in subsequent processes; when calculating the deformation value of each pixel block, the center distance value (m pq ) plays a key role. The center distance value is calculated based on the coordinates of the pixel block feature points, grayscale value and grayscale center coordinates, which reflects the geometric characteristics of the grayscale distribution within the pixel block. pq ) is further calculated based on the center distance value and the grayscale value of each point in the pixel block. It is used to quantify the degree of deformation of the pixel block due to some external factors (such as pressure, temperature, etc.). Suppose there is a pixel block whose feature point coordinates and grayscale values ​​on the grayscale image are known. The grayscale center coordinates (x_3, y_3) are obtained by weighted averaging the grayscale values ​​of all feature points. First, we need to calculate the grayscale center coordinates (x_3, y_3). Suppose in this example, the grayscale center coordinates are (1.5, 1.5) (this is calculated by weighted averaging, which may be different in actual calculations. Then, select a combination of (p) and (q), such as (p=1, q=0), to calculate the first-order center distance (m_{10}), and then according to A deformation value (S_{10}) is obtained, and a deformation value of the pixel block is calculated according to the center distance values ​​of all pixel block feature points. The deformation of the pixel block is evaluated by the deformation value. The present invention analyzes the information of each pixel block in the substrate segmentation image, and can obtain multiple pixel block feature point coordinates according to the information of each pixel block. The center distance value from each pixel block feature point to the grayscale center coordinate is calculated according to the multiple pixel block feature point coordinates and the grayscale center coordinate. Because the grayscale center coordinate changes due to image deformation, the center distance value from each pixel block feature point coordinate to the grayscale center coordinate will also change. The deformation value is calculated according to the center distance value of each pixel block feature point. Whether the pixel block in the first substrate segmentation image is deformed can be accurately judged by the deformation value, thereby improving the accuracy of the first substrate segmentation image judgment, and improving the accuracy of the judgment. At the same time, the deformation is determined by considering the feature points and grayscale information of the pixel block, which has high accuracy and calculation efficiency.

[0143] In one embodiment, the step of obtaining the position information of each deformed pixel block and calculating the collapse value of each deformed pixel block according to the position information includes:

[0144] S501, obtaining first centroid coordinates of all deformed pixel blocks according to position information;

[0145] S502: Obtaining the directional features corresponding to each deformed pixel block according to the first centroid coordinates

[0146] S503, acquiring the deformation area of ​​all deformed pixel block coordinates according to the first centroid coordinates;

[0147] S504, determining key point pixels within a preset range according to the directional features, and defining the key point pixels as a neighborhood;

[0148] S505, obtaining the coordinates of the second centroid of the neighborhood;

[0149] S506: Calculate the collapse value of the deformed pixel block according to the first centroid coordinates and the second centroid coordinates, wherein the collapse value calculation formula is:

[0150]

[0151] Among them, d is the collapse value of the deformed pixel block, (x 1 ,y 1 ) is the first centroid coordinate, (x 2 ,y 2 ) are the coordinates of the second centroid.

[0152] As described in the above steps S501-S506, the present invention determines the first centroid coordinates of each deformed pixel block by calculating the average coordinates of the deformed pixel blocks, thereby accurately locating the center position of the deformed pixel block, and determines the directional characteristics of the deformed pixel block by calculating the line connecting the first centroid coordinates and the boundary points of the pixel block, thereby accurately describing the direction and shape of the pixel block; and determines the area range of the deformed pixel block by calculating the maximum distance between the first centroid coordinates and the deformed pixel block, thereby accurately limiting the position of the deformed pixel block, and determining the next deformed pixel block according to the directional characteristics of the deformed pixel block. By obtaining the key point pixels of the next deformed pixel block and defining them as a neighborhood, and obtaining the second centroid coordinates of the next deformed pixel block, the Euclidean distance between the first centroid coordinates and the second centroid coordinates of the neighborhood is calculated to determine the collapse value of the deformed pixel block corresponding to the first centroid coordinate, thereby accurately evaluating the collapse of the deformed pixel block corresponding to the first centroid coordinate. By calculating the collapse value of each deformed pixel block, the collapse degree of the PCB board depression can be accurately determined, the accuracy of PCB board depression recognition is improved, and the problem that the depth of the PCB board depression cannot be accurately judged in the prior art can be solved.

[0153] In one embodiment, the step of calculating the adjustment waveform voltage value of each deformed pixel block in the second substrate segmentation image according to the collapse value and the deformation value includes:

[0154] S601, obtaining a preset voltage waveform value of each pixel block;

[0155] S602, obtaining the collapse value of each pixel block;

[0156] S603, obtaining a weight coefficient of the collapse value of each pixel block;

[0157] S604, obtaining a deformation value of each pixel block;

[0158] S605, obtaining a weight coefficient of a pixel block deformation value of each pixel block;

[0159] S606, calculating the adjustment waveform voltage value of each pixel block according to the collapse value and the pixel block bending energy, the calculation formula is:

[0160] V a =V b |(E*W E +d*W d -1)|;

[0161] Among them, V a To adjust the waveform voltage value, V b is the preset voltage waveform value, E is the pixel block deformation value, W Eis the weight coefficient of the pixel block deformation value, d is the collapse value, W d is the weight coefficient of the collapse value.

[0162] As described in the above steps S601-S606, the present invention can solve the problem in the prior art that the regulating voltage of the nozzle cannot be accurately adjusted according to the depression range and depth of the PCB board, resulting in different deformations of the ink when the ejected ink adheres to the depressions of different depths during the subsequent inkjet printing process due to the obstruction of the ink by the different depressions of the PCB board. The present invention can determine the initial value of the regulating waveform voltage for each pixel block according to a preset voltage waveform value (the preset voltage waveform value is applicable to the nozzle printing data of the first substrate segmentation image), thereby accurately controlling the voltage regulation during the printing process, and determining the initial value of the regulating waveform voltage by calculating the collapse degree of the pixel block. According to the deformation in the printing process, different weights are assigned to the collapse values ​​of each pixel block, so as to accurately adjust the influence of each pixel block in the calculation of the regulating waveform voltage. The deformation in the printing process can be determined by calculating the deformation degree of the pixel block. The step of calculating the regulating waveform voltage value of each pixel block in the second substrate segmentation image according to the collapse value and the deformation value realizes the accurate calculation of the regulating waveform voltage by obtaining the preset voltage waveform value, the collapse value, the collapse value weight coefficient, the deformation value and the deformation value weight coefficient. The waveform voltage of the nozzle can be adjusted according to the depression depth and range of the PCB board, thereby improving the control effect of the nozzle.

[0163] In one embodiment, the step of obtaining the collapse level value of each deformed pixel block in the second substrate segmentation image according to the collapse value comprises:

[0164] S701, obtaining a collapse value of each pixel block in the second substrate segmentation image;

[0165] S702, obtaining a collapse coefficient of the collapse value;

[0166] S703, calculating the collapse level value of each pixel block according to the collapse value:

[0167] L = d * c;

[0168] Among them, L is the collapse level value, d is the collapse value of the pixel block, and c is the collapse coefficient;

[0169] As described in the above steps S601-S603, the specific advantage of the present invention in calculating the collapse level value of each pixel block according to the collapse value is that it can be obtained through a calculation formula, wherein the collapse coefficient is a preset parameter for adjusting the influence of the collapse value in the final collapse level value calculation, and the collapse level of each pixel block can be determined according to the collapse value of the pixel block, and the collapse depth of each pixel block in the recessed area of ​​the PCB board can be determined, so as to solve the problem that the collapse level evaluation of the pixel block in the recessed area of ​​the PCB board in the prior art may not be accurate enough, resulting in the inability to accurately control in the subsequent printing or processing process. By introducing the collapse coefficient and combining the collapse value to calculate the collapse level value, the collapse degree of each pixel block can be more accurately reflected, and the accuracy of the evaluation can be improved. In the inkjet printing process, if the printing order of the pixel blocks is unreasonable, it may cause problems such as ink flowing mutually or uneven coverage. By calculating the collapse level value of each pixel block and sorting them, the darker or more critical pixel blocks can be printed first, ensuring that they solidify first, providing stable support for subsequent printing, thereby avoiding problems caused by disordered printing.

[0170] like Figure 2 As shown, the present invention also provides a PCB board surface marking printing system, comprising:

[0171] A first acquisition module 1 is used to acquire a substrate identification image of an original PCB board, wherein the substrate identification image includes a reference image and an identification character distribution map;

[0172] An image segmentation module 2, used for segmenting the reference image according to the identification character distribution map to obtain a plurality of first substrate segmentation images;

[0173] A second acquisition module 3, used to acquire deformation values ​​of all pixel blocks in each of the first substrate segmentation images;

[0174] A judging module 4 is used to judge whether the deformation value is within a preset range;

[0175] If yes, it is determined that there is no deformation area in the first substrate segmentation image, and a first logo printing sequence table is generated based on the logo character distribution map, and logo printing is performed in sequence according to the first logo printing sequence table;

[0176] If not, determining that the first substrate segmentation image has a deformed area, taking the first substrate segmentation image with the deformed area as the second substrate segmentation image, and defining the pixel block in the second substrate segmentation image as a deformed pixel block;

[0177] A third acquisition module 5 is used to acquire the position information of each deformed pixel block, and calculate the collapse value of each deformed pixel block according to the position information;

[0178] A first calculation module 6, used for calculating the adjustment waveform voltage value of each deformed pixel block in the second substrate segmentation image according to the collapse value and the deformation value;

[0179] The fourth acquisition module 7 is used to acquire the collapse level value of each deformed pixel block in the second substrate segmentation image according to the collapse value, and sort the multiple collapse level values ​​according to a preset condition to obtain a second mark printing sequence table;

[0180] A sorting module 8, used for sorting each adjustment waveform voltage value according to the second identification printing sequence table to obtain a nozzle adjustment sequence table;

[0181] The printing module 9 is used to perform logo printing according to the second logo printing sequence table and the nozzle adjustment sequence table.

[0182] In one embodiment, the second acquisition module includes:

[0183] A first acquisition unit, used to acquire information of a plurality of pixel blocks in the substrate segmentation image;

[0184] A second acquisition unit, used for acquiring coordinates of feature points of a plurality of pixel blocks according to the pixel block information;

[0185] A third acquisition unit is used to acquire the grayscale value corresponding to the coordinates of the feature point of the pixel block;

[0186] A fourth acquisition unit, used to acquire the grayscale center coordinates of the pixel block information;

[0187] The first calculation unit is used to calculate the center distance value of each pixel block feature point according to the pixel block feature point coordinates, gray center coordinates and gray value, and the calculation formula is:

[0188] m pq =∑ p ∑ q (xx 3 ) p (yy 3 ) q I (x，y) ;

[0189] Among them, m pq is the center distance value, x represents the horizontal coordinate of the pixel block feature point, y represents the vertical coordinate of the pixel block feature point, and x 3 Indicates the grayscale center horizontal coordinate, y 3 Indicates the grayscale center ordinate, I (x，y) is the gray value of the pixel block feature point at coordinates (x, y), p is the order in the x direction of the coordinates (x, y), and q is the order in the y direction of the coordinates (x, y);

[0190] The second calculation unit is used to calculate the deformation value of each pixel block according to the center distance value, and the calculation formula is:

[0191]

[0192] Among them, S pq is the deformation value of the pixel block, m pq is the center distance value.

[0193] In one embodiment, the third acquisition module includes:

[0194] A fifth acquisition unit, used for acquiring first centroid coordinates of all deformed pixel block coordinates according to the position information;

[0195] The sixth acquisition unit is used to acquire the directional features corresponding to each deformed pixel block according to the first centroid coordinates.

[0196] A seventh acquisition unit, configured to acquire the deformation area of ​​all deformed pixel block coordinates according to the first centroid coordinates;

[0197] An eighth acquisition unit, used to determine key point pixels within a preset range according to the directional features, and define the key point pixels as a neighborhood;

[0198] A ninth acquisition unit, used for acquiring the coordinates of the second centroid of the neighborhood;

[0199] The second calculation unit is used to calculate the collapse value of the deformed pixel block according to the first centroid coordinates and the second centroid coordinates, wherein the collapse value calculation formula is:

[0200]

[0201] Among them, d is the collapse value of the deformed pixel block, (x 1 ,y 1 ) is the first centroid coordinate, (x 2 ,y 2 ) are the coordinates of the second centroid.

[0202] In one embodiment, the first computing module includes:

[0203] a tenth acquiring unit, configured to acquire a preset voltage waveform value of each pixel block;

[0204] an eleventh obtaining unit, configured to obtain a collapse value of each pixel block;

[0205] A twelfth obtaining unit, used to obtain a weight coefficient of a collapse value of each pixel block;

[0206] A thirteenth obtaining unit, configured to obtain a deformation value of a pixel block of each pixel block;

[0207] A fourteenth obtaining unit, used to obtain a weight coefficient of a pixel block deformation value of each pixel block;

[0208] The fourth calculation unit is used to calculate the adjustment waveform voltage value of each pixel block according to the collapse value and the pixel block bending energy, and the calculation formula is:

[0209] V a =V b |(E*W E +d*W d -1)|;

[0210] Among them, V a To adjust the waveform voltage value, V b is the preset voltage waveform value, E is the pixel block deformation value, W E is the weight coefficient of the pixel block deformation value, d is the collapse value, W d is the weight coefficient of the collapse value.

[0211] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided in this application and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0212] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0213] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent results or equivalent process changes made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for printing a mark on a PCB surface, characterized in that: include: Acquire a substrate identification image of an original PCB board, wherein the substrate identification image includes a reference image and an identification character distribution map, the reference image is an unprinted image of the original PCB board, and the identification character distribution map includes position information of identification characters in the reference image; Segmenting the reference image according to the identification character distribution map to obtain a plurality of first substrate segmentation images; Obtaining deformation values ​​of all pixel blocks in each of the first substrate segmentation images; Determine whether the deformation value is within a preset range; If yes, it is determined that there is no deformation area in the first substrate segmentation image, and a first logo printing sequence table is generated based on the logo character distribution map, and logo printing is performed in sequence according to the first logo printing sequence table; If not, determining that the first substrate segmentation image has a deformed area, taking the first substrate segmentation image with the deformed area as the second substrate segmentation image, and defining the pixel block in the second substrate segmentation image as a deformed pixel block; Acquiring position information of each deformed pixel block, and calculating a collapse value of each deformed pixel block according to the position information; Calculate the adjustment waveform voltage value of each deformed pixel block in the second substrate segmentation image according to the collapse value and the deformation value; Acquire the collapse level value of each deformed pixel block in the second substrate segmentation image according to the collapse value, and sort the multiple collapse level values ​​according to a preset condition to obtain a second mark printing sequence table; Sort each adjustment waveform voltage value according to the second identification printing sequence table to obtain a nozzle adjustment sequence table; The logo printing is performed according to the second logo printing sequence table and the nozzle adjustment sequence table.

2. The PCB board surface marking printing method according to claim 1, characterized in that: The step of segmenting the reference image according to the identification character distribution map to obtain a plurality of first substrate segmented images includes: Obtaining a plurality of character information and position information corresponding to the character information according to the identification character distribution map; Establishing a bounding box for the character information to obtain a character bounding box; Acquire a to-be-printed area of ​​a character boundary box on a reference image based on the position information; The plurality of to-be-printed areas on the reference image are segmented and extracted to obtain a first substrate segmented image.

3. The PCB board surface marking printing method according to claim 1, characterized in that: The step of obtaining deformation values ​​of all pixel blocks in each of the first substrate segmentation images comprises: Acquire information of a plurality of pixel blocks in the first substrate segmentation image; Acquire coordinates of feature points of multiple pixel blocks according to pixel block information; Get the gray value corresponding to the coordinates of the feature point of the pixel block; Get the grayscale center coordinates of the pixel block information; The center distance value of each pixel block feature point is calculated according to the pixel block feature point coordinates, gray center coordinates and gray value. The calculation formula is: ； Among them, m pq is the center distance value, x represents the horizontal coordinate of the pixel block feature point, y represents the vertical coordinate of the pixel block feature point, x3 represents the horizontal coordinate of the grayscale center, y3 represents the vertical coordinate of the grayscale center, I (x, y) is the gray value of the pixel block feature point at coordinates (x, y), p is the order in the x direction in coordinates (x, y), and q is the order in the y direction in coordinates (x, y); The deformation value of each pixel block is calculated according to the center distance value. The calculation formula is: ； Among them, S pq is the deformation value of the pixel block, m pq is the center distance value.

4. The PCB board surface marking printing method according to claim 1, characterized in that: The step of obtaining the position information of each deformed pixel block and calculating the collapse value of each deformed pixel block according to the position information comprises: Obtain the first centroid coordinates of all deformed pixel blocks according to the position information; Acquire the directional features corresponding to each deformed pixel block according to the first centroid coordinates; Obtain the deformation area of ​​all deformed pixel block coordinates according to the first centroid coordinates; Determine key point pixels within a preset range according to the directional characteristics, and define the key point pixels as a neighborhood; Get the coordinates of the second centroid of the neighborhood; The collapse value of each deformed pixel block is calculated according to the first centroid coordinates and the second centroid coordinates, wherein the collapse value calculation formula is: ； Among them, d is the collapse value of the deformed pixel block, (x1, y1) is the first centroid coordinate, and (x2, y2) is the second centroid coordinate.

5. The PCB board surface marking printing method according to claim 1, characterized in that: The step of calculating the adjustment waveform voltage value of each deformed pixel block in the second substrate segmentation image according to the collapse value and the deformation value comprises: Obtaining a preset voltage waveform value of each pixel block; Obtaining the collapse value of each pixel block; Obtain the weight coefficient of the collapse value of each pixel block; Obtaining a deformation value of a pixel block of each pixel block; Obtaining a weight coefficient of a pixel block deformation value of each pixel block; The voltage value of the regulated waveform of each pixel block is calculated according to the collapse value and the bending energy of the pixel block. The calculation formula is: ； Among them, V a To adjust the waveform voltage value, V b is the preset voltage waveform value, E is the pixel block deformation value, W E is the weight coefficient of the pixel block deformation value, d is the collapse value, W d is the weight coefficient of the collapse value.

6. The PCB board surface marking printing method according to claim 1, characterized in that: The step of obtaining the collapse level value of each deformed pixel block in the second substrate segmentation image according to the collapse value comprises: Obtaining a collapse value of each pixel block in the second substrate segmentation image; Get the collapse coefficient of the collapse value; Calculate the collapse level value of each pixel block according to the collapse value: ； Among them, L is the collapse level value, d is the collapse value of the pixel block, and c is the collapse coefficient.

7. A PCB board surface marking printing system, characterized in that: include: A first acquisition module is used to acquire a substrate identification image of an original PCB board, wherein the substrate identification image includes a reference image and an identification character distribution map, the reference image is an unprinted image of the original PCB board, and the identification character distribution map includes position information of identification characters in the reference image; An image segmentation module, used for segmenting the reference image according to the identification character distribution map to obtain a plurality of first substrate segmentation images; A second acquisition module, used for acquiring deformation values ​​of all pixel blocks in each of the first substrate segmentation images; A judgment module, used to judge whether the deformation value is within a preset range; If yes, it is determined that there is no deformation area in the first substrate segmentation image, and a first logo printing sequence table is generated based on the logo character distribution map, and logo printing is performed in sequence according to the first logo printing sequence table; If not, determining that the first substrate segmentation image has a deformed area, and using the first substrate segmentation image with the deformed area as the second substrate segmentation image, and defining the pixel block in the second substrate segmentation image as a deformed pixel block; A third acquisition module, used to acquire the position information of each deformed pixel block, and calculate the collapse value of each deformed pixel block according to the position information; A first calculation module, used for calculating the adjustment waveform voltage value of each deformed pixel block in the second substrate segmentation image according to the collapse value and the deformation value; A fourth acquisition module, configured to acquire a collapse level value of each deformed pixel block in the second substrate segmentation image according to the collapse value, and sort the multiple collapse level values ​​according to a preset condition to obtain a second mark printing sequence table; A sorting module, used for sorting each adjustment waveform voltage value according to the second identification printing sequence table to obtain a nozzle adjustment sequence table; The printing module is used to perform identification printing according to the second identification printing sequence table and the nozzle adjustment sequence table.

8. A PCB board surface marking printing system according to claim 7, characterized in that: The second acquisition module includes: A first acquisition unit, used to acquire information of a plurality of pixel blocks in a substrate segmentation image; A second acquisition unit, used for acquiring coordinates of feature points of a plurality of pixel blocks according to the pixel block information; A third acquisition unit is used to acquire the grayscale value corresponding to the coordinates of the feature point of the pixel block; A fourth acquisition unit, used to acquire the grayscale center coordinates of the pixel block information; The first calculation unit is used to calculate the center distance value of each pixel block feature point according to the pixel block feature point coordinates, gray center coordinates and gray value, and the calculation formula is: ； Among them, m pq is the center distance value, x represents the horizontal coordinate of the pixel block feature point, y represents the vertical coordinate of the pixel block feature point, x3 represents the horizontal coordinate of the grayscale center, y3 represents the vertical coordinate of the grayscale center, I (x, y) is the gray value of the pixel block feature point at coordinates (x, y), p is the order in the x direction in coordinates (x, y), and q is the order in the y direction in coordinates (x, y); The second calculation unit is used to calculate the deformation value of each pixel block according to the center distance value, and the calculation formula is: ； Among them, S pq is the deformation value of the pixel block, m pq is the center distance value.

9. A PCB board surface marking printing system according to claim 7, characterized in that: The third acquisition module includes: A fifth acquisition unit, used for acquiring first centroid coordinates of all deformed pixel block coordinates according to the position information; a sixth acquisition unit, configured to acquire a directional feature corresponding to each deformed pixel block according to the first centroid coordinates; A seventh acquisition unit, configured to acquire the deformation area of ​​all deformed pixel block coordinates according to the first centroid coordinates; An eighth acquisition unit, used to determine key point pixels within a preset range according to the directional features, and define the key point pixels as a neighborhood; A ninth acquisition unit, used for acquiring the coordinates of the second centroid of the neighborhood; The second calculation unit is used to calculate the collapse value of the deformed pixel block according to the first centroid coordinates and the second centroid coordinates, wherein the collapse value calculation formula is: ； Among them, d is the collapse value of the deformed pixel block, (x1, y1) is the first centroid coordinate, and (x2, y2) is the second centroid coordinate.

10. A PCB board surface marking printing system according to claim 7, characterized in that: The first computing module comprises: a tenth acquiring unit, configured to acquire a preset voltage waveform value of each pixel block; an eleventh obtaining unit, configured to obtain a collapse value of each pixel block; A twelfth obtaining unit, used to obtain a weight coefficient of a collapse value of each pixel block; A thirteenth obtaining unit, configured to obtain a deformation value of a pixel block of each pixel block; A fourteenth obtaining unit, used to obtain a weight coefficient of a pixel block deformation value of each pixel block; The fourth calculation unit is used to calculate the adjustment waveform voltage value of each pixel block according to the collapse value and the pixel block bending energy, and the calculation formula is: ； Among them, V a To adjust the waveform voltage value, V b is the preset voltage waveform value, E is the pixel block deformation value, W E is the weight coefficient of the pixel block deformation value, d is the collapse value, W d is the weight coefficient of the collapse value.

Images