PCB board production automatic exposure system and method

Abstract

The present application relates to the technical field of PCB, and particularly relates to a PCB production automatic exposure system and method. Through real-time acquisition and analysis of the alignment offset information of the PCB substrate, the substrate position tilt information and the pattern alignment precision, the present application can more accurately monitor the possible error sources in the exposure process, dynamically adjust the initial parameters of the exposure system through the overall exposure deviation, alignment error and tilt error, effectively balance the exposure intensity of the whole exposure area, compensate for different areas according to the real-time light intensity of each area, dynamically adjust the exposure time according to the real-time light intensity of each area, ensure that each line is formed under appropriate exposure intensity through real-time acquisition of the exposure image and adjustment of the light intensity, and analyze the exposure quality of each area through real-time acquisition of the edge information of the image.

Description

Technical Field

[0001] This invention relates to the field of PCB technology, and in particular to an automated exposure system and method for PCB production. Background Technology

[0002] A PCB, also known as a printed circuit board or printed circuit board, is a board made of insulating board as a substrate, cut to a certain size, with at least one conductive pattern on it, and holes (such as component holes, mounting holes, metallized holes, etc.) to enable interconnection between electronic components. Because this type of board is made using electronic printing technology, it is called a "printed" circuit board.

[0003] Exposure is a crucial step in PCB manufacturing. It involves exposing the circuit diagram portion of the PCB to the film substrate, causing a polymerization reaction. During development, unexposed areas are cleaned away, while the polymerized areas remain. This process forms the initial circuitry on the PCB. However, current PCB manufacturing processes often suffer from uneven exposure due to inaccuracies in parameters such as the light source and exposure time. This uneven exposure affects the PCB's conductivity and aesthetics, ultimately impacting product quality. Summary of the Invention

[0004] The main objective of this invention is to provide an automated exposure method for PCB board production, aiming to solve the technical problems in the prior art.

[0005] This invention proposes an automated exposure method for PCB board production, comprising:

[0006] The initial alignment feature information of the PCB substrate is obtained, wherein the initial alignment feature information includes alignment mark offset information, substrate position tilt information and pattern alignment accuracy information;

[0007] The alignment error and tilt error are obtained based on the alignment offset information and the substrate position tilt information;

[0008] The overall exposure deviation is obtained based on the pattern alignment accuracy information, and the initial parameters of the exposure system are adjusted based on the overall exposure deviation, alignment error, and tilt error.

[0009] The system acquires the illumination intensity and real-time exposure images of multiple areas of the adjusted exposure system in real time, and obtains the exposure compensation time based on the illumination of the multiple areas.

[0010] The key features of the real-time exposure image are obtained, wherein the key features include image edge information and image spatial features;

[0011] Structural similarity is obtained based on the image edge information;

[0012] The matching degree is obtained based on the image spatial features, and the exposure compensation brightness is obtained based on the matching degree and structural similarity.

[0013] The brightness and duration of the exposure system are adjusted according to the exposure compensation brightness and exposure compensation time, respectively.

[0014] Preferably, the step of obtaining the alignment error and tilt error based on the alignment offset information and the substrate position tilt information includes:

[0015] The horizontal offset, vertical offset, and rotation angle offset of the marker are obtained based on the alignment offset information.

[0016] The substrate tilt angle, horizontal offset, and vertical offset are obtained based on the substrate position tilt information.

[0017] The alignment error is obtained based on the horizontal offset of the mark, the vertical offset of the mark, the horizontal offset of the substrate, and the vertical offset of the substrate;

[0018] The tilt error is obtained based on the substrate tilt angle and the mark rotation angle offset.

[0019] Preferably, the step of obtaining the overall exposure deviation based on the pattern alignment accuracy information, and adjusting the parameters of the exposure system based on the overall exposure deviation, alignment error, and tilt error, includes:

[0020] The pattern scaling size deviation and pattern contrast deviation are obtained based on the pattern alignment accuracy information;

[0021] The overall exposure deviation is obtained based on the pattern scaling size deviation and the pattern contrast deviation, and it is determined whether the overall exposure deviation is greater than the preset exposure deviation.

[0022] If the overall exposure deviation is greater than the preset exposure deviation, the initial exposure compensation of the exposure system will be reduced.

[0023] If the overall exposure deviation is not greater than the preset exposure deviation, then the initial exposure compensation of the exposure system is increased.

[0024] Get the offset direction;

[0025] The position calibration accuracy is obtained based on the offset error and offset direction, and the initial exposure area of ​​the exposure system is adjusted based on the position calibration accuracy.

[0026] The focal length error is obtained based on the tilt error, and the initial exposure focal length of the exposure system is adjusted based on the focal length error.

[0027] Preferably, the step of obtaining the exposure compensation time based on the illumination of the multiple regions includes:

[0028] The total exposure brightness is obtained based on the illumination of the multiple regions described;

[0029] Obtain the camera parameters of the exposure system, including aperture value, ISO, and shutter speed;

[0030] The aperture area is obtained based on the aperture value, and the exposure is obtained based on the aperture area, ISO, shutter speed, and total exposure brightness.

[0031] The exposure duration is obtained based on the exposure amount and total exposure brightness.

[0032] Obtain the preset exposure duration, and obtain the exposure compensation time based on the exposure duration and the preset exposure duration.

[0033] Preferably, the step of obtaining structural similarity based on the image edge information includes:

[0034] Multiple first edge pixels are obtained based on the image edge information, and a first red pixel channel value, a first green pixel channel value, and a first blue pixel channel value are obtained based on each first edge pixel.

[0035] The average value and variance value of the first edge pixels are obtained based on multiple first red pixel channel values, multiple first green pixel channel values ​​and multiple first blue pixel channel values;

[0036] Obtain standard edge information of a preset exposure image, and obtain multiple second edge pixels based on the standard edge information;

[0037] Obtain the second red pixel channel value, the second green pixel channel value, and the second blue pixel channel value for each second edge pixel;

[0038] The average value of the second edge pixels and the variance value of the second edge pixels are obtained based on multiple second red pixel channel values, multiple second green pixel channel values ​​and multiple second blue pixel channel values.

[0039] The pixel covariance is obtained based on the average value of the first edge pixel and the average value of the second edge pixel.

[0040] Structural similarity is calculated based on the average value of the first edge pixels, the variance of the first edge pixels, the average value of the second edge pixels, the variance of the second edge pixels, and the pixel covariance, wherein the calculation formula is:

[0041]

[0042] Where J(XD) represents structural similarity, X(P1) represents the average value of the first edge pixels, X(P2) represents the average value of the second edge pixels, X(XF) represents pixel covariance, F(C1) represents the variance of the first edge pixels, and F(C2) represents the variance of the second edge pixels.

[0043] Preferably, the step of obtaining the matching degree based on the image spatial features and obtaining the exposure compensation brightness based on the matching degree and structural similarity includes:

[0044] The pattern intersection area, pattern union area, and pattern spacing are obtained based on the image spatial features.

[0045] The pattern overlap rate is obtained based on the pattern intersection area and the pattern union area;

[0046] The matching degree is calculated based on the pattern overlap rate and pattern spacing, wherein the calculation formula is:

[0047] P(D) = [1 - T(C)] * T(J);

[0048] Where P(D) represents the matching degree, T(C) represents the pattern overlap rate, and T(J) represents the pattern spacing;

[0049] The exposure amount is obtained based on the matching degree, and the exposure deviation is obtained based on the exposure amount;

[0050] The average local brightness is obtained based on the structural similarity, and the brightness difference value is obtained based on the average local brightness.

[0051] The exposure compensation brightness is obtained based on the brightness difference value and the exposure deviation.

[0052] This application also provides an automated exposure system for PCB board production, including:

[0053] The first acquisition module is used to acquire the initial alignment feature information of the PCB substrate, wherein the initial alignment feature information includes alignment mark offset information, substrate position tilt information and pattern alignment accuracy information;

[0054] The second acquisition module is used to acquire the alignment error and tilt error based on the alignment offset information and the substrate position tilt information.

[0055] The first adjustment module is used to obtain the overall exposure deviation based on the pattern alignment accuracy information, and to adjust the initial parameters of the exposure system based on the overall exposure deviation, alignment error and tilt error;

[0056] The third acquisition module is used to acquire the light intensity of multiple areas of the adjusted exposure system and the real-time exposure image in real time, and to acquire the exposure compensation time based on the light intensity of the multiple areas.

[0057] The fourth acquisition module is used to acquire key features of the real-time exposure image, wherein the key features include image edge information and image spatial features;

[0058] The fifth acquisition module is used to acquire structural similarity based on the image edge information;

[0059] The sixth acquisition module is used to acquire the matching degree based on the image spatial features, and to acquire the exposure compensation brightness based on the matching degree and structural similarity.

[0060] The second adjustment module is used to adjust the brightness and duration of the exposure system according to the exposure compensation brightness and exposure compensation time, respectively.

[0061] Preferably, the second acquisition module includes:

[0062] The first acquisition unit is used to acquire the horizontal offset of the marker, the vertical offset of the marker, and the rotation angle offset of the marker based on the alignment offset information;

[0063] The second acquisition unit is used to acquire the substrate tilt angle, substrate horizontal offset and substrate vertical offset based on the substrate position tilt information.

[0064] The third acquisition unit is used to acquire the alignment error based on the mark horizontal offset, mark vertical offset, substrate horizontal offset, and substrate vertical offset.

[0065] The fourth acquisition unit is used to acquire the tilt error based on the substrate tilt angle and the mark rotation angle offset.

[0066] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described automated exposure method for PCB board production.

[0067] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described automated exposure method for PCB board production.

[0068] The beneficial effects of this invention are as follows: By acquiring and analyzing the alignment offset information, substrate tilt information, and pattern alignment accuracy of the PCB substrate in real time, this invention can more accurately monitor possible error sources during the exposure process. By dynamically adjusting the initial parameters of the exposure system through overall exposure deviation, alignment error, and tilt error, the exposure intensity of the entire exposure area can be effectively balanced. By monitoring and adjusting the light intensity of multiple areas in real time, compensation can be performed for different areas. The exposure time can be dynamically adjusted according to the real-time light intensity of each area. By acquiring the exposure image in real time and adjusting the light intensity, it can be ensured that each line is formed under appropriate exposure intensity. By monitoring the light intensity of each area in real time, unevenness of illumination can be detected and compensated in real time. By acquiring the edge information of the image in real time, the exposure quality of each area can be analyzed. By calculating structural similarity, the local feature differences of the image can be evaluated. By monitoring the edge, structural similarity, and spatial features of the exposure image in real time, not only is manual intervention reduced, but the stability and accuracy of the exposure process are also greatly improved. By automatically analyzing the edge and spatial features in the exposure image, the exposure compensation brightness and exposure time can be intelligently adjusted. Attached Figure Description

[0069] Figure 1 This is a schematic diagram of a method flow according to an embodiment of the present invention.

[0070] Figure 2 This is a schematic diagram of the device structure according to an embodiment of the present invention.

[0071] Figure 3 This is a schematic diagram of the internal structure of a computer device according to an embodiment of this application.

[0072] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0073] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0074] like Figure 1 - Figure 3 As shown, this application provides an automated exposure method for PCB board production, including:

[0075] S1. Obtain the initial alignment feature information of the PCB substrate, wherein the initial alignment feature information includes alignment mark offset information, substrate position tilt information and pattern alignment accuracy information;

[0076] S2. Obtain the alignment error and tilt error based on the alignment offset information and substrate tilt information;

[0077] S3. Obtain the overall exposure deviation based on the pattern alignment accuracy information, and adjust the initial parameters of the exposure system based on the overall exposure deviation, alignment error, and tilt error;

[0078] S4. Real-time acquisition of illumination intensity and real-time exposure images of multiple areas of the adjusted exposure system, and acquisition of exposure compensation time based on the illumination of the multiple areas;

[0079] S5. Obtain the key features of the real-time exposure image, wherein the key features include image edge information and image spatial features;

[0080] S6. Obtain structural similarity based on the image edge information;

[0081] S7. Obtain the matching degree based on the image spatial features, and obtain the exposure compensation brightness based on the matching degree and structural similarity.

[0082] S8. Adjust the brightness and duration of the exposure system according to the exposure compensation brightness and exposure compensation time.

[0083] As described in steps S1-S8 above, a PCB board, also known as a printed circuit board or simply a printed circuit board, uses an insulating board as a substrate, cut to a certain size, and has at least one conductive pattern attached to it, along with holes (such as component holes, mounting holes, metallized holes, etc.) to enable interconnection between electronic components. Because this type of board is manufactured using electronic printing techniques, it is called a "printed" circuit board. Exposure is a crucial step in the PCB board manufacturing process. Exposure involves exposing the circuit diagram portion of the PCB board to the film substrate. After exposure, this portion undergoes a polymerization reaction. During the development process, unexposed areas can be cleaned away with developer, while the areas that underwent polymerization cannot be cleaned. This process initially forms the circuitry on the PCB board. However, in current PCB board manufacturing processes, inaccurate parameters such as the exposure light source and exposure time often lead to uneven exposure intensity, affecting the conductivity and aesthetics of the PCB board, thus impacting product quality. This invention obtains alignment error and tilt error by using the alignment offset information and substrate tilt information of the PCB substrate. Then, it obtains the overall exposure deviation based on the pattern alignment accuracy information of the PCB substrate. Finally, it adjusts the initial parameters of the exposure system based on the overall exposure deviation, alignment error, and tilt error. The alignment mark offset information refers to the deviation between the actual alignment mark position on the substrate and the predetermined position during exposure. The substrate tilt refers to the tilt angle of the PCB substrate relative to the ideal plane of the photolithography equipment during exposure. The pattern alignment accuracy refers to the alignment accuracy between the exposed pattern and the existing pattern or graphic on the substrate during exposure. By acquiring and analyzing the PCB substrate alignment offset information, substrate tilt information, and pattern alignment accuracy in real time, possible error sources during exposure can be monitored more accurately. Alignment error and tilt error can be corrected through a feedback mechanism, thereby effectively... Reducing exposure errors caused by substrate misalignment or tilt during exposure is crucial, as uneven exposure intensity is a major factor leading to PCB quality issues. By dynamically adjusting the initial parameters of the exposure system based on overall exposure deviation, alignment error, and tilt error, the exposure intensity of the entire exposure area can be effectively balanced, reducing local overexposure or underexposure and ensuring the uniformity of exposure across the entire PCB. This allows the exposure system to make more intelligent adaptive adjustments, reducing the complexity and errors of manual operation, improving the automation level of the production line, and increasing production efficiency and consistency. By acquiring the light intensity and real-time exposure images of multiple areas of the adjusted exposure system in real time, and obtaining exposure compensation time based on the light intensity of multiple areas, the problem of uneven exposure intensity caused by inaccurate parameters such as exposure light source and exposure time in existing technologies can be effectively solved, thereby significantly improving the conductivity and aesthetics of the PCB.Specifically, the intensity of the exposure light source may vary across the entire exposure area, leading to overexposure or underexposure in some areas, thus affecting the quality of the PCB pattern. Therefore, by monitoring and adjusting the light intensity of multiple areas in real time, compensation can be applied to different areas, ensuring that each area receives relatively uniform illumination. Dynamically adjusting the exposure time based on the real-time light intensity of each area effectively avoids localized overexposure or underexposure caused by uneven exposure time. This ensures consistent overall exposure and avoids the negative impact of light intensity differences on PCB quality. Uneven exposure can lead to overexposed areas on the circuit board, where the pattern may be incomplete or inaccurate, causing short circuits or open circuits. By acquiring exposure images in real time and adjusting the light intensity, this defect can be reduced, ensuring that each circuit is formed under appropriate exposure intensity. During the exposure process, real-time monitoring of the light intensity of each area allows for the detection and real-time compensation of uneven illumination.For example, if the light intensity in a certain area is low, the exposure time in that area can be increased, or the light source intensity can be adjusted to compensate, thus avoiding local underexposure caused by uneven light intensity. Based on real-time light intensity feedback, the required exposure compensation time can be automatically calculated. This compensation mechanism ensures that the exposure of all areas is relatively consistent throughout the exposure process, avoiding uneven exposure caused by human error or equipment error. Furthermore, structural similarity is obtained based on image edge information in the key features of the real-time exposed image, and matching degree is obtained based on image spatial features. Exposure compensation brightness is then obtained based on the matching degree and structural similarity. The brightness and duration of the exposure system are adjusted according to the exposure compensation brightness and exposure compensation time, respectively. By acquiring image edge information in real time, the exposure quality of each area can be analyzed, identifying areas with uneven exposure or uneven light intensity distribution. Calculating structural similarity can assess local feature differences in the image, identifying which areas do not meet the expected exposure. Further calculations of spatial feature matching degree can be used to... Understanding the exposure conditions in different areas, especially complex patterns or detailed areas, ensures precise adjustment of exposure levels in these areas, avoiding local overexposure or underexposure. Based on matching degree and structural similarity, the system automatically calculates and adjusts the compensation brightness and exposure time of the exposure system, making the exposure more balanced across all areas and avoiding exposure intensity deviations. This improves the overall exposure uniformity of the PCB board. Traditional PCB exposure processes often rely on manual or preset parameter adjustments to exposure time and light source intensity, but these methods cannot handle complex situations. By monitoring the edge characteristics, structural similarity, and spatial features of the exposed image in real time, the system automatically calculates and adjusts exposure parameters, reducing manual intervention and significantly improving the stability and accuracy of the exposure process. By automatically analyzing the edge and spatial features in the exposed image, the system can intelligently adjust the exposure compensation brightness and exposure time. This adaptive adjustment mechanism allows the exposure system to respond based on real-time image features and matching degree, improving the system's intelligence level and reducing human error.

[0084] In one embodiment, step S2, which involves obtaining the alignment error and tilt error based on the alignment offset information and the substrate position tilt information, includes:

[0085] S21. Obtain the horizontal offset of the marker, the vertical offset of the marker, and the rotation angle offset of the marker based on the alignment offset information;

[0086] S22. Obtain the substrate tilt angle, substrate horizontal offset, and substrate vertical offset based on the substrate position tilt information;

[0087] S23. Obtain the alignment error based on the mark horizontal offset, mark vertical offset, substrate horizontal offset, and substrate vertical offset;

[0088] S24. Obtain the tilt error based on the substrate tilt angle and the mark rotation angle offset.

[0089] As described in steps S21-S24 above, this invention obtains the horizontal offset, vertical offset, and rotation angle offset of the mark through alignment offset information, and obtains the substrate tilt angle, horizontal offset, and vertical offset of the substrate through substrate position tilt information. Then, it obtains the alignment error based on the horizontal and vertical offsets of the mark, and the tilt error based on the substrate tilt angle and the mark rotation angle offset. By obtaining the horizontal and vertical offsets of the mark and the substrate, the alignment error can be accurately calculated. This allows for accurate alignment of the photolithography pattern and substrate position during exposure, ensuring that the light source illuminates the correct area, reducing photolithography defects caused by exposure alignment errors, and thus improving the accuracy of the PCB circuit pattern. It compensates for the rotation offset between the substrate and the mark (calculated through the mark rotation angle offset), thereby avoiding exposure errors caused by substrate rotation or tilt. Since the substrate tilt angle has a significant impact on exposure quality, if the substrate tilts during exposure, the illumination angle of the light source will change, resulting in uneven exposure intensity and affecting the quality and appearance of the circuit. By measuring and compensating for the substrate tilt angle, uneven exposure caused by tilt can be effectively avoided, ensuring uniform exposure intensity across the entire PCB surface. Compensation for alignment and tilt errors makes the light source illumination more consistent during exposure, preventing local underexposure or overexposure and ensuring uniform PCB exposure quality, further improving circuit reliability. Uneven exposure often leads to color difference, blurring, or pattern distortion, affecting the PCB's appearance. By precisely controlling alignment and tilt compensation during exposure, the clarity, sharpness, and symmetry of the lithography pattern can be ensured, avoiding aesthetic problems caused by uneven exposure. This method can monitor and adjust alignment, tilt, and rotation errors in real time through an automated system, reducing human error and improving the system's intelligence and adaptability. The system can automatically adjust based on real-time data, reducing human interference during production. Real-time feedback and adjustment allow the system to automatically optimize exposure conditions based on the actual conditions of each production batch, ensuring that the exposure quality of each PCB meets standards and improving production flexibility and intelligence.

[0090] In one embodiment, step S3, which involves obtaining the overall exposure deviation based on the pattern alignment accuracy information and adjusting the parameters of the exposure system based on the overall exposure deviation, alignment error, and tilt error, includes:

[0091] S31. Obtain the pattern scaling size deviation and pattern contrast deviation based on the pattern alignment accuracy information;

[0092] S32. Obtain the overall exposure deviation based on the pattern scaling size deviation and the pattern contrast deviation, and determine whether the overall exposure deviation is greater than the preset exposure deviation;

[0093] If the overall exposure deviation is greater than the preset exposure deviation, the initial exposure compensation of the exposure system will be reduced.

[0094] If the overall exposure deviation is not greater than the preset exposure deviation, then the initial exposure compensation of the exposure system is increased.

[0095] S33, Obtain the offset direction;

[0096] S34. Obtain the position calibration accuracy based on the offset error and offset direction, and adjust the initial exposure area of ​​the exposure system based on the position calibration accuracy;

[0097] S35. Obtain the focal length error based on the tilt error, and adjust the initial exposure focal length of the exposure system based on the focal length error.

[0098] As described in steps S31-S35 above, this invention obtains the pattern scaling size deviation and pattern contrast deviation through pattern alignment accuracy information, and obtains the overall exposure deviation based on the pattern scaling size deviation and pattern contrast deviation. By determining whether the overall exposure deviation is greater than a preset exposure deviation, if it is greater, the initial exposure compensation of the exposure system is reduced; otherwise, the initial exposure compensation of the exposure system is increased. By obtaining the pattern scaling size deviation and pattern contrast deviation, the deviation of the pattern during the exposure process can be accurately evaluated, thereby optimizing the compensation of the exposure system. If uneven exposure intensity is found, the exposure compensation is automatically adjusted to improve the exposure uniformity. This avoids PCB conductivity differences or aesthetic problems caused by uneven exposure, ensuring the quality of the entire circuit board. By determining whether the overall exposure deviation exceeds the preset exposure deviation threshold, the compensation of the exposure system is automatically adjusted. The automated compensation process reduces manual intervention. This reduces the problems of inaccurate or missed adjustments by human operation, thereby improving the stability and consistency of the production process. By monitoring and adjusting exposure compensation in real time, the exposure system can be continuously optimized in each production process, reducing the impact of factors such as fluctuations in exposure light source intensity and inaccurate exposure time on image quality. The position calibration accuracy is obtained through offset error and offset direction, and the initial exposure area of ​​the exposure system is adjusted according to the position calibration accuracy. The focal length error is obtained through tilt error, and the initial exposure focal length of the exposure system is adjusted according to the focal length error. By adjusting the initial exposure area of ​​the exposure system according to offset error and offset direction, the uniformity of exposure intensity throughout the exposure area can be effectively guaranteed, avoiding overexposure or underexposure. This makes the final circuit pattern more accurate and has consistent conductivity. However, focal length error may lead to a decrease in the resolution of the photolithography pattern, or even a blurry focus or pattern misalignment. By obtaining the focal length error based on the tilt error and adjusting the initial exposure focal length of the exposure system, it is possible to effectively ensure that the focus during photolithography is always kept in the optimal position. This not only improves the fineness of the pattern but also prevents pattern blurring or error accumulation caused by inaccurate focal length, thereby improving the reliability and quality of the PCB. This allows for precise control of various parameters of the exposure system, ensuring uniform light intensity and accurate focal length during the exposure process, thus improving the quality and production efficiency of the PCB board and reducing conductivity and aesthetic issues caused by inaccurate exposure. This optimization method not only improves the stability and consistency of the product but also helps to reduce production costs and enhance the automation and intelligence level of the production line.

[0099] In one embodiment, step S4, which involves obtaining the exposure compensation time based on the illumination of the plurality of said regions, includes:

[0100] S41. Obtain the total exposure brightness based on the illumination of the multiple regions;

[0101] S42. Obtain the camera parameters of the exposure system, including aperture value, ISO and shutter speed;

[0102] S43. Obtain the aperture area based on the aperture value, and calculate the exposure based on the aperture area, ISO, shutter speed, and total exposure brightness. The calculation formula is as follows: Where B(GL) represents exposure, B(ZL) represents total exposure brightness, G(GD) represents sensitivity, G(QM) represents aperture area, and K(MS) represents shutter speed;

[0103] S44. Calculate the exposure time based on the exposure amount and total exposure brightness, wherein the calculation formula is: Where B(SC) represents the exposure time, B(GL) represents the exposure amount, and B(ZL) represents the total exposure brightness;

[0104] S45. Obtain the preset exposure duration, and calculate the exposure compensation time based on the sum of the exposure duration and the preset exposure duration.

[0105] As described in steps S41-S45 above, this invention obtains the total exposure brightness through multiple areas of illumination, then obtains the aperture area based on the aperture value in the camera parameters of the exposure system, and obtains the exposure amount based on the aperture area, ISO, shutter speed, and total exposure brightness. The exposure duration is then obtained based on the exposure amount and total exposure brightness. A preset exposure duration is obtained, and an exposure compensation time is calculated based on the exposure duration and the preset exposure duration. By obtaining illumination from multiple areas and calculating the total exposure brightness, the light intensity of the entire exposure area can be measured in detail. This allows the exposure system to better control the light distribution, thereby avoiding problems such as uneven light source, local overexposure, or underexposure that may occur in traditional exposure processes. This precise exposure intensity control helps ensure the clarity and uniformity of the PCB pattern, guaranteeing the conductivity and overall integrity of the circuit. To improve aesthetics, this invention calculates the exposure amount by taking into account factors such as aperture area, ISO, shutter speed, and total exposure brightness. Based on this, the exposure time is calculated, and then calibrated according to the preset exposure time to obtain the exposure compensation time. This allows the exposure system to automatically adjust the exposure time and compensation time, eliminating deviations caused by fluctuations in the exposure light source and changes in equipment performance. Automated adjustment reduces manual intervention, minimizes human error, and improves the consistency and reliability of the exposure process. By precisely controlling the exposure time and light intensity, it ensures that every area on the PCB receives proper exposure, effectively avoiding electrical defects caused by uneven light sources or inaccurate exposure times. Traditional exposure techniques may result in overexposure or underexposure in certain areas due to unstable light sources or inaccurate focusing. This invention, by calculating parameters such as total exposure brightness and aperture area, allows the system to dynamically adjust the exposure amount and exposure time before each exposure, ensuring a more uniform distribution of light across different areas and avoiding localized overexposure or underexposure.

[0106] In one embodiment, step S6, which involves obtaining structural similarity based on the image edge information, includes:

[0107] S61. Obtain multiple first edge pixels based on the image edge information, and obtain the first red pixel channel value, the first green pixel channel value, and the first blue pixel channel value based on each first edge pixel.

[0108] S62. Obtain the average value of the first edge pixels and the variance value of the first edge pixels based on the multiple first red pixel channel values, the multiple first green pixel channel values ​​and the multiple first blue pixel channel values;

[0109] S63. Obtain standard edge information of the preset exposure image, and obtain multiple second edge pixels based on the standard edge information;

[0110] S64. Obtain the second red pixel channel value, the second green pixel channel value, and the second blue pixel channel value based on each second edge pixel.

[0111] S65. Obtain the average value of the second edge pixels and the variance value of the second edge pixels based on the multiple second red pixel channel values, the multiple second green pixel channel values ​​and the multiple second blue pixel channel values;

[0112] S66. Obtain the pixel covariance based on the average value of the first edge pixel and the average value of the second edge pixel;

[0113] S67. Calculate the structural similarity based on the average value of the first edge pixels, the variance of the first edge pixels, the average value of the second edge pixels, the variance of the second edge pixels, and the pixel covariance, wherein the calculation formula is:

[0114]

[0115] Where J(XD) represents structural similarity, X(P1) represents the average value of the first edge pixels, X(P2) represents the average value of the second edge pixels, X(XF) represents pixel covariance, F(C1) represents the variance of the first edge pixels, and F(C2) represents the variance of the second edge pixels.

[0116] As described in steps S61-S67 above, the present invention obtains multiple first edge pixels through image edge information, and obtains first red pixel channel value, first green pixel channel value and first blue pixel channel value according to each first edge pixel. The first edge pixel average value and first edge pixel variance value are obtained through multiple first red pixel channel values, multiple first green pixel channel values ​​and multiple first blue pixel channel values. The standard edge information of the preset exposure image is obtained, and multiple second edge pixels are obtained according to the standard edge information. The second red pixel channel value, second green pixel channel value and second blue pixel channel value are obtained through each second edge pixel. The second edge pixel average value and second edge pixel variance value are obtained through multiple second red pixel channel values, multiple second green pixel channel values ​​and multiple second blue pixel channel values. In PCB manufacturing, the uniformity of the exposure light source is crucial. If the light source is not uniform, the exposure intensity in some areas may be too strong or too weak, resulting in blurry or distorted patterns, which in turn affects conductivity and aesthetics. By analyzing image edge information, the lighting conditions of edge pixels can be accurately located. Then, based on the color values ​​of the red, green, and blue channels, the uniformity of exposure can be analyzed. The mean and variance values ​​provide a precise measure of the regional exposure intensity distribution, helping to identify uneven areas in the exposure process. By calculating the RGB channel values ​​of each edge pixel and obtaining the mean and variance values ​​of these pixels, color changes in the exposed area can be quantified, thus revealing deviations in the exposure process. For example, if an area is overexposed, the RGB channel color values ​​may be abnormally high; if underexposed, the RGB values ​​may be too low.Edge pixel variance effectively reflects the fluctuations in exposure intensity across different areas, helping to accurately identify and adjust uneven exposure. Detailed analysis of pixels at image edges allows for rapid identification of light source instability (such as brightness variations). The variance of edge pixels reflects local exposure changes; a larger variance indicates higher light source instability, potentially leading to uneven exposure. Analyzing edge pixels in the exposure area ensures smooth and clear transitions at each edge, which is particularly important for high-precision circuit boards. By calculating the average and variance of edge pixels, blurring or errors in pattern details during exposure can be detected, allowing for adjustments to exposure parameters to ensure the accuracy of circuit patterns on the circuit board and reduce electrical defects (such as short circuits or open circuits). Pixel covariance is obtained through the average value of the first edge pixel and the average value of the second edge pixel. The variance of the first edge pixel, the first edge pixel variance, and the first edge pixel variance are used to determine the pixel covariance. Structural similarity is calculated using the average value of two edge pixels, the variance of the second edge pixels, and the pixel covariance. Pixel covariance is an important indicator for measuring the relationship between two sets of pixels (such as the first and second edge pixels). It can help identify the correlation between different parts of an exposed image. By calculating the covariance of the exposed area, the similarity and consistency of exposure intensity in different areas can be determined, thereby revealing areas of uneven exposure. The calculation of structural similarity is based on the average value and variance of edge pixels. It can effectively assess the illumination differences in different areas of an exposed image. This assessment method can not only help identify uneven intensity problems that occur during exposure, but also accurately locate the specific areas of uneven exposure. Then, by adjusting exposure parameters (such as exposure time and light source intensity), the overall exposure uniformity can be optimized. During the exposure process, changes in light source intensity and exposure time may cause some areas to be overexposed or underexposed, resulting in pattern distortion and differences in conductivity. By calculating structural similarity and pixel covariance, exposure deviations during the exposure process can be monitored in real time, promptly identifying issues such as uneven light source and improper exposure time. Compensation can be achieved by adjusting exposure parameters (such as light source brightness and exposure time) to ensure clear patterns and uniform illumination on the PCB board, thereby avoiding circuit performance fluctuations caused by uneven exposure. Based on image analysis, the average value, variance, and covariance of edge pixels can be automatically calculated, automating the quality control process. This helps optimize the exposure process, improve exposure uniformity, and ensure the conductivity, appearance quality, and electrical performance of the PCB. It also reduces deviations during production, lowers scrap rates, improves production efficiency, and ensures the consistency and high quality of the final product.

[0117] In one embodiment, step S7, which involves obtaining a matching degree based on the image spatial features and obtaining exposure compensation brightness based on the matching degree and structural similarity, includes:

[0118] S71. Obtain the pattern intersection area, pattern union area, and pattern spacing based on the image spatial features;

[0119] S72. Obtain the pattern overlap rate based on the pattern intersection area and the pattern union area;

[0120] S73. Calculate the matching degree based on the pattern overlap rate and pattern spacing, wherein the calculation formula is:

[0121] P(D) = [1 - T(C)] * T(J);

[0122] Where P(D) represents the matching degree, T(C) represents the pattern overlap rate, and T(J) represents the pattern spacing;

[0123] S74. Obtain the exposure amount based on the matching degree, and obtain the exposure deviation based on the exposure amount;

[0124] S75. Obtain the local average brightness value based on the structural similarity, and obtain the brightness difference value based on the local average brightness value;

[0125] S76. Obtain the exposure compensation brightness based on the brightness difference value and exposure deviation.

[0126] As described in steps S71-S76 above, this invention obtains the pattern intersection area, pattern union area, and pattern spacing through image spatial features, and obtains the pattern overlap rate based on the pattern intersection area and pattern union area. The matching degree is calculated using the pattern overlap rate and pattern spacing. Here, the pattern overlap rate refers to the matching situation of identical or similar patterns in two images, and the pattern spacing refers to the spatial distance between adjacent patterns in the image. The calculation of the pattern intersection area and pattern union area can help quantify the overlap and distribution of patterns during PCB exposure and assess the impact of uneven exposure on pattern morphology. When the exposure light source is uneven, some areas may be overexposed or underexposed, causing changes in the intersection or spacing between patterns. By calculating this... These geometric features can accurately identify pattern changes caused by uneven exposure, such as excessive pattern overlap or unnecessary increased spacing. Pattern overlap rate is a key indicator, reflecting whether abnormal overlap has occurred between different patterns. This is usually caused by uneven exposure. If the overlap rate is too high, it may indicate that a certain area is overexposed, resulting in a blurred pattern. If the overlap rate is too low, it may indicate underexposure, and the pattern may not be fully displayed. During the exposure process, by adjusting exposure parameters (such as exposure time, light source intensity, etc.), and based on the calculated overlap rate and matching degree, the shape and size of the circuit pattern can be controlled more precisely to ensure that the conductivity of each area on the PCB meets the design requirements, reduce the generation of defective areas, and the pattern spacing is crucial. The electrical performance of a PCB is crucial. Insufficient pattern spacing can lead to signal interference, electrical short circuits, or poor contact. By calculating pattern spacing and matching degree, the rationality of pattern spacing in different areas can be accurately assessed. Analyzing the relationship between pattern spacing and exposure uniformity helps adjust the light source intensity or exposure time during the exposure process, ensuring uniform pattern spacing across the entire PCB and thus improving electrical performance. Evaluating pattern matching degree allows for better adjustment of exposure parameters, reducing issues such as pattern blurring and unclear outlines caused by uneven exposure, ensuring the aesthetics of the PCB. The matching degree is used to obtain the exposure amount, and the exposure deviation is determined based on the exposure amount. Structural similarity is used to obtain the local average brightness, and based on local... The brightness difference value is obtained by taking the average brightness value, and then the exposure compensation brightness is calculated by summing the brightness difference value and the exposure deviation. The exposure deviation reflects the difference between the exposure value of the image and the ideal exposure value. It is usually used to represent the difference in exposure level in image processing or camera settings. The brightness difference value usually refers to the difference in overall brightness between the current image and the target image (such as the ideal exposure image or reference image). By accurately measuring and compensating for the exposure amount and local brightness difference, the impact of uneven exposure light source or inaccurate exposure time can be effectively reduced, thereby ensuring that the exposure intensity of each area on the PCB board is more uniform. During the exposure process, factors such as the instability of the light source and the fluctuation of the exposure time may cause fluctuations in product quality.By calculating and compensating for exposure deviations, the stability of the photolithography process can be further improved, ensuring that the exposure effect of PCB products remains consistent across different batches of production. This enhances the controllability and reliability of the production process, enabling more precise control of light intensity distribution during PCB exposure and reducing various problems caused by uneven exposure. This not only improves the conductivity and appearance quality of PCBs but also optimizes the production process, increases production efficiency, and enhances product consistency.

[0127] This application also provides an automated exposure system for PCB board production, including:

[0128] The first acquisition module is used to acquire the initial alignment feature information of the PCB substrate, wherein the initial alignment feature information includes alignment mark offset information, substrate position tilt information and pattern alignment accuracy information;

[0129] The second acquisition module is used to acquire the alignment error and tilt error based on the alignment offset information and the substrate position tilt information.

[0130] The first adjustment module is used to obtain the overall exposure deviation based on the pattern alignment accuracy information, and to adjust the initial parameters of the exposure system based on the overall exposure deviation, alignment error and tilt error;

[0131] The third acquisition module is used to acquire the light intensity of multiple areas of the adjusted exposure system and the real-time exposure image in real time, and to acquire the exposure compensation time based on the light intensity of the multiple areas.

[0132] The fourth acquisition module is used to acquire key features of the real-time exposure image, wherein the key features include image edge information and image spatial features;

[0133] The fifth acquisition module is used to acquire structural similarity based on the image edge information;

[0134] The sixth acquisition module is used to acquire the matching degree based on the image spatial features, and to acquire the exposure compensation brightness based on the matching degree and structural similarity.

[0135] The second adjustment module is used to adjust the brightness and duration of the exposure system according to the exposure compensation brightness and exposure compensation time, respectively.

[0136] In one embodiment, the second acquisition module includes:

[0137] The first acquisition unit is used to acquire the horizontal offset of the marker, the vertical offset of the marker, and the rotation angle offset of the marker based on the alignment offset information;

[0138] The second acquisition unit is used to acquire the substrate tilt angle, substrate horizontal offset and substrate vertical offset based on the substrate position tilt information.

[0139] The third acquisition unit is used to acquire the alignment error based on the mark horizontal offset, mark vertical offset, substrate horizontal offset, and substrate vertical offset.

[0140] The fourth acquisition unit is used to acquire the tilt error based on the substrate tilt angle and the mark rotation angle offset.

[0141] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described automated exposure method for PCB board production.

[0142] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described automated exposure method for PCB board production.

[0143] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media provided in this application and 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), dual-speed SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0144] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0145] The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. An automated exposure method for PCB board production, characterized in that, Applied to exposure systems, including: The initial alignment feature information of the PCB substrate is obtained, wherein the initial alignment feature information includes alignment offset information, substrate position tilt information and pattern alignment accuracy information; The alignment error and tilt error are obtained based on the alignment offset information and the substrate position tilt information; The overall exposure deviation is obtained based on the pattern alignment accuracy information, and the initial parameters of the exposure system are adjusted based on the overall exposure deviation, alignment error, and tilt error. The system acquires the illumination intensity and real-time exposure images of multiple areas of the adjusted exposure system in real time, and obtains the exposure compensation time based on the illumination of the multiple areas. The key features of the real-time exposure image are obtained, wherein the key features include image edge information and image spatial features; Structural similarity is obtained based on the image edge information; The matching degree is obtained based on the image spatial features, and the exposure compensation brightness is obtained based on the matching degree and structural similarity. The brightness and duration of the exposure system are adjusted according to the exposure compensation brightness and exposure compensation time, respectively.

2. The automated exposure method for PCB board production according to claim 1, characterized in that, The step of obtaining the alignment error and tilt error based on the alignment offset information and the substrate position tilt information includes: The horizontal offset, vertical offset, and rotation angle offset of the marker are obtained based on the alignment offset information. The substrate tilt angle, horizontal offset, and vertical offset are obtained based on the substrate position tilt information. The alignment error is obtained based on the horizontal offset of the mark, the vertical offset of the mark, the horizontal offset of the substrate, and the vertical offset of the substrate; The tilt error is obtained based on the substrate tilt angle and the mark rotation angle offset.

3. The automated exposure method for PCB board production according to claim 1, characterized in that, The step of obtaining the overall exposure deviation based on the pattern alignment accuracy information, and adjusting the parameters of the exposure system based on the overall exposure deviation, alignment error, and tilt error, includes: The pattern scaling size deviation and pattern contrast deviation are obtained based on the pattern alignment accuracy information; The overall exposure deviation is obtained based on the pattern scaling size deviation and the pattern contrast deviation, and it is determined whether the overall exposure deviation is greater than the preset exposure deviation. If the overall exposure deviation is greater than the preset exposure deviation, the initial exposure compensation of the exposure system will be reduced. If the overall exposure deviation is not greater than the preset exposure deviation, then the initial exposure compensation of the exposure system is increased. Get the offset direction; The position calibration accuracy is obtained based on the offset error and offset direction, and the initial exposure area of ​​the exposure system is adjusted based on the position calibration accuracy. The focal length error is obtained based on the tilt error, and the initial exposure focal length of the exposure system is adjusted based on the focal length error.

4. The automated exposure method for PCB board production according to claim 1, characterized in that, The step of obtaining the exposure compensation time based on the illumination of the multiple regions includes: The total exposure brightness is obtained based on the illumination of the multiple regions described; Obtain the camera parameters of the exposure system, including aperture value, ISO, and shutter speed; The aperture area is obtained based on the aperture value, and the exposure is obtained based on the aperture area, ISO, shutter speed, and total exposure brightness. The exposure duration is obtained based on the exposure amount and total exposure brightness. Obtain the preset exposure duration, and obtain the exposure compensation time based on the exposure duration and the preset exposure duration.

5. The automated exposure method for PCB board production according to claim 1, characterized in that, The step of obtaining structural similarity based on the image edge information includes: Multiple first edge pixels are obtained based on the image edge information, and a first red pixel channel value, a first green pixel channel value, and a first blue pixel channel value are obtained based on each first edge pixel. The average value and variance value of the first edge pixels are obtained based on multiple first red pixel channel values, multiple first green pixel channel values ​​and multiple first blue pixel channel values; Obtain standard edge information of a preset exposure image, and obtain multiple second edge pixels based on the standard edge information; Obtain the second red pixel channel value, the second green pixel channel value, and the second blue pixel channel value for each second edge pixel; The average value of the second edge pixels and the variance value of the second edge pixels are obtained based on multiple second red pixel channel values, multiple second green pixel channel values ​​and multiple second blue pixel channel values. The pixel covariance is obtained based on the average value of the first edge pixel and the average value of the second edge pixel. Structural similarity is calculated based on the average value of the first edge pixels, the variance of the first edge pixels, the average value of the second edge pixels, the variance of the second edge pixels, and the pixel covariance, wherein the calculation formula is as follows: ； Where J(XD) represents structural similarity, X(P1) represents the average value of the first edge pixels, X(P2) represents the average value of the second edge pixels, X(XF) represents pixel covariance, F(C1) represents the variance of the first edge pixels, and F(C2) represents the variance of the second edge pixels.

6. The automated exposure method for PCB board production according to claim 1, characterized in that, The step of obtaining a matching degree based on the image spatial features and obtaining exposure compensation brightness based on the matching degree and structural similarity includes: The pattern intersection area, pattern union area, and pattern spacing are obtained based on the image spatial features. The pattern overlap rate is obtained based on the pattern intersection area and the pattern union area; The matching degree is calculated based on the pattern overlap rate and pattern spacing, wherein the calculation formula is: P(D) = [1 - T(C)] * T(J); Where P(D) represents the matching degree, T(C) represents the pattern overlap rate, and T(J) represents the pattern spacing; The exposure amount is obtained based on the matching degree, and the exposure deviation is obtained based on the exposure amount; The average local brightness is obtained based on the structural similarity, and the brightness difference value is obtained based on the average local brightness. The exposure compensation brightness is obtained based on the brightness difference value and the exposure deviation.

7. An automated exposure system for PCB board production, characterized in that, include: The first acquisition module is used to acquire the initial alignment feature information of the PCB substrate, wherein the initial alignment feature information includes alignment offset information, substrate position tilt information and pattern alignment accuracy information. The second acquisition module is used to acquire the alignment error and tilt error based on the alignment offset information and the substrate position tilt information. The first adjustment module is used to obtain the overall exposure deviation based on the pattern alignment accuracy information, and to adjust the initial parameters of the exposure system based on the overall exposure deviation, alignment error and tilt error; The third acquisition module is used to acquire the light intensity of multiple areas of the adjusted exposure system and the real-time exposure image in real time, and to acquire the exposure compensation time based on the light intensity of the multiple areas. The fourth acquisition module is used to acquire key features of the real-time exposure image, wherein the key features include image edge information and image spatial features; The fifth acquisition module is used to acquire structural similarity based on the image edge information; The sixth acquisition module is used to acquire the matching degree based on the image spatial features, and to acquire the exposure compensation brightness based on the matching degree and structural similarity. The second adjustment module is used to adjust the brightness and duration of the exposure system according to the exposure compensation brightness and exposure compensation time, respectively.

8. The automated exposure system for PCB board production according to claim 7, characterized in that, The second acquisition module includes: The first acquisition unit is used to acquire the horizontal offset of the marker, the vertical offset of the marker, and the rotation angle offset of the marker based on the alignment offset information; The second acquisition unit is used to acquire the substrate tilt angle, substrate horizontal offset and substrate vertical offset based on the substrate position tilt information. The third acquisition unit is used to acquire the alignment error based on the mark horizontal offset, mark vertical offset, substrate horizontal offset, and substrate vertical offset. The fourth acquisition unit is used to acquire the tilt error based on the substrate tilt angle and the mark rotation angle offset.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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