Circuit board blind hole quality detection method and system

Abstract

The embodiment of the application provides a circuit board blind hole quality detection method and system, the method comprises the following steps: taking a target circuit board along an x axis through two cameras to obtain a plurality of first target images, processing the plurality of first target images to obtain a second target image, determining an effective gray image according to the first gray image and the second gray image, obtaining height data and three-dimensional topographic data of a blind hole region of the target circuit board according to the effective gray image, and performing quality evaluation on the blind hole according to the height data and the three-dimensional topographic data of the blind hole region of the target circuit board to obtain a quality evaluation result. By using the foregoing method, the height data and the three-dimensional topographic data of the blind hole on the circuit board can be accurately obtained without damaging the circuit board, and effective quality evaluation can be performed.

Description

Technical Field

[0001] This application relates to the field of general image data processing technology, and in particular to a method and system for detecting the quality of blind vias on circuit boards. Background Technology

[0002] Blind vias on a circuit board are located on the top and bottom surfaces of the board and are used to connect the surface layer circuits to the inner layer circuits below. They are an important component of the circuit board, and the quality of the circuit board mainly includes two aspects: hole morphology and hole depth.

[0003] Currently, in actual production processes, manufacturers primarily use cross-sectional measurement to inspect the quality of blind vias on circuit boards. However, cross-sectional measurement suffers from irreversible damage to the circuit board, significant human error, a lengthy process, and low accuracy, severely hindering circuit board production efficiency. How to accurately, quickly, and effectively evaluate blind via quality without damaging the circuit board is one of the most pressing issues to be addressed in this field. Summary of the Invention

[0004] This application provides a method and system for inspecting the quality of blind vias on a circuit board. The method involves using dual cameras to capture images of the target circuit board, processing the images to determine the height and three-dimensional shape data of the blind vias, and then performing a quality evaluation based on this data. This approach allows for accurate acquisition of the height and three-dimensional shape data of blind vias on the circuit board without damaging the board, and enables effective quality evaluation.

[0005] In a first aspect, embodiments of this application provide a method for detecting the quality of blind vias on a circuit board. The method includes: taking pictures of a target circuit board along the x-axis with two cameras to obtain multiple first target images, wherein at least one blind via exists on the target circuit board, and the target circuit board is irradiated by a laser device. Each first target image includes a first laser stripe image and a second laser stripe image corresponding to the two cameras respectively, and the two cameras are respectively located on both sides of the laser device on the x-axis.

[0006] Multiple second target images are obtained by processing multiple first target images. The second target images include valid first laser stripe images determined based on first laser stripe images and valid second laser stripe images determined based on second laser stripe images.

[0007] A third target image is obtained by processing multiple second target images. The third target image includes a first grayscale image corresponding to multiple valid first laser stripe images and a second grayscale image corresponding to multiple valid second laser stripe images.

[0008] The height and three-dimensional topography data of the blind via region of the target circuit board are obtained from the third target image.

[0009] The quality evaluation results are obtained by evaluating the blind vias based on the height data and three-dimensional topography data of the blind via area on the target circuit board.

[0010] As can be seen, in this embodiment, two cameras are used to capture images of the target circuit board along the x-axis to obtain multiple first target images. These first target images are then processed to obtain second target images. Valid grayscale images are determined based on the first and second grayscale images. Height data and three-dimensional topography data of the blind via region on the target circuit board are obtained from the valid grayscale images. Finally, the quality of the blind vias is evaluated based on these data to obtain a quality evaluation result. Using the aforementioned method, the height data and three-dimensional topography data of the blind vias on the circuit board can be accurately obtained without damaging the circuit board, and their quality can be effectively evaluated.

[0011] Secondly, embodiments of this application provide a circuit board blind via quality inspection system, including a data acquisition device, a processing device, and a detection device. The data acquisition device includes a data acquisition module comprising a laser device and cameras positioned on either side of the laser device along the x-axis. The system is characterized by:

[0012] The acquisition device captures images of the target circuit board to obtain multiple first target images. The target circuit board has at least one blind hole and is illuminated by a laser device. Each first target image includes a first laser stripe image and a second laser stripe image corresponding to two cameras, respectively.

[0013] The processing device processes multiple first target images to obtain multiple second target images, wherein the second target images include a valid first laser stripe image determined based on the first laser stripe image and a valid second laser stripe image determined based on the second laser stripe image;

[0014] The processing device also processes multiple second target images to obtain a third target image, which includes a first grayscale image corresponding to multiple valid first laser stripe images and a second grayscale image corresponding to multiple valid second laser stripe images.

[0015] The processing device also obtains the height data and three-dimensional topography data of the blind via region of the target circuit board based on the third target image;

[0016] The testing device evaluates the quality of blind vias based on the height data and three-dimensional morphology data of the blind via area on the target circuit board, and obtains the quality evaluation results.

[0017] Thirdly, embodiments of this application provide a computer-readable storage medium storing program data. When the program data is executed by a processor, it is used to execute the program data to implement some or all of the steps described in the first aspect of the embodiments of this application. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the structure of a data acquisition device provided in an embodiment of this application;

[0020] Figure 2 A schematic flowchart illustrating a method for inspecting the quality of blind vias on a circuit board, provided in an embodiment of this application;

[0021] Figure 3 This is a schematic diagram of the structure of a laser stripe image provided in an embodiment of this application;

[0022] Figure 4 This is a schematic diagram of the structure of a grayscale image provided in an embodiment of this application;

[0023] Figure 5 This is a schematic diagram of a circuit board blind via quality inspection system provided in an embodiment of this application. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0025] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps is not limited to the steps listed, but may optionally include steps not listed, or may optionally include other steps inherent to these processes, methods, products, or apparatuses.

[0026] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0027] Please see Figure 1 , Figure 1 This is a schematic diagram of the structure of a data acquisition device provided in an embodiment of this application, as shown below. Figure 1 As shown, the acquisition device includes a laser device 101, a first camera 102, and a second camera 103. The laser device 101 is perpendicular to the irradiated plane, and the first camera 102 and the second camera 103 are parallel to each other on both sides of the laser device 101. The shooting angles of the two cameras can be freely adjusted, but this adjustment is done before the detection process begins; during the detection process, the angles between the three cameras remain fixed. When the laser device 101 illuminates the blind hole 104, the first camera 102 will have a blind spot, meaning it cannot capture the shape of the blind hole 104 near the left side. At this time, the second camera 103 can capture the shape of the blind hole 104 near the left side. Similarly, the second camera 103 may also fail to capture the shape of the blind hole 104 near the right side, in which case the first camera 102 is needed to capture the shape of the blind hole 104 near the right side.

[0028] Based on this, the present application provides a method for detecting the quality of blind vias on circuit boards. The embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0029] Please see Figure 2 , Figure 2 This is a flowchart illustrating a method for inspecting the quality of blind vias on a circuit board, as provided in an embodiment of this application. Figure 2 As shown, the method includes the following steps:

[0030] Step 201: Take pictures of the target circuit board along the x-axis using two cameras to obtain multiple first target images.

[0031] The target circuit board has at least one blind via and is illuminated by a laser device. Each first target image includes a first laser stripe image and a second laser stripe image corresponding to two cameras, respectively. The two cameras are located on opposite sides of the laser device along the x-axis. The target circuit board can be a High Density Interconnect (HDI) board, a type of printed circuit board that uses micro-blind via technology to achieve a high line density. The laser device can be a line laser device.

[0032] During filming, the two cameras and the laser device were fixed together, as shown in the image. Figure 1 The acquisition device shown in the diagram maintains relative movement with the target circuit board along the x-axis. Alternatively, the target circuit board can be fixed while the acquisition device moves along the x-axis; or the acquisition device can be fixed while the target circuit board moves along the x-axis. During this relative movement between the target circuit board and the acquisition device, the two cameras simultaneously capture multiple laser stripe images.

[0033] In one feasible embodiment, in the captured laser stripe image, since the laser beam illuminating the object has a certain width (i.e., the corresponding length on the x-axis), it is difficult to determine the precise pixel position. The laser brightness on the object follows a Gaussian distribution on the x-axis. Therefore, the center of the laser stripe on the x-axis can be determined using the gray-scale centroid method to obtain the corresponding pixel position. For more precise calculations, a sub-pixel algorithm can be used to determine the sub-pixel center position of the laser stripe.

[0034] However, before capturing multiple laser stripe images, it is necessary to complete the height calibration of the acquisition device and the image registration between the two cameras to facilitate subsequent image processing. The height calibration of the acquisition device and the image registration between the two cameras are explained below:

[0035] In a feasible embodiment, before obtaining multiple first target images by photographing the target circuit board along the x-axis with two cameras, the method further includes: simultaneously adjusting the heights of the two cameras and the laser device to photograph the target circuit board and obtain third target images corresponding to different heights, the third target images including third laser stripe images and fourth laser stripe images corresponding to the two cameras respectively; generating a first height mapping table and a second height mapping table corresponding to the two cameras respectively based on the distances on the x-axis between the third laser stripe images and the fourth laser stripe images corresponding to different heights, the height mapping tables including the mapping relationship between the actual height change value and the laser image distance change value.

[0036] For the height calibration of the acquisition device, it is necessary to move the height of the acquisition device along the z-axis. Simultaneously, based on the changes in the position of the laser stripes on the camera image at different heights (i.e., the changes in distance along the x-axis of the image), the mapping relationship between the actual height change value and the laser image distance change value is determined. Specifically, when the acquisition device moves a distance a1 along the z-axis, the distance A1 between the corresponding positions of the laser stripes in the laser stripe image captured before and after the movement is determined. By moving the acquisition device multiple times along the z-axis at different distances, the distance changes of the laser stripes in the image are obtained, generating a height mapping table, as shown in Table 1.

[0037] Table 1 Height Mapping Table

[0038] Serial Number Altitude variation value Laser image distance change value 1 a1 A1 …… …… …… n an An

[0039] In this embodiment, the camera height is calibrated by moving the height of two cameras and a laser device to photograph the target circuit board. The true height of the blind holes on the target circuit board can be determined during subsequent shooting by imaging them in the camera.

[0040] In a feasible embodiment, before capturing multiple first target images of the target circuit board by two cameras along the x-axis, the method further includes capturing a calibration board by two cameras to obtain a fourth target image. The fourth target image includes a first height image and a second height image corresponding to the two cameras, respectively. The calibration board includes multiple regularly arranged calibration patterns.

[0041] Obtain the pattern shooting parameters of the calibration pattern, including the shape parameters, pixel size and gray value of the calibration pattern; set the matching model according to the pattern shooting parameters, match the pattern shooting parameters in the fourth target image according to the matching model to determine the calibration pattern in the fourth target image, and calculate the center coordinates of multiple calibration patterns;

[0042] The center coordinates of multiple calibration patterns are fitted using the least squares method to determine the straight line where the center coordinates of multiple calibration patterns are located. Based on the slope of the straight line, the fourth target image is rotated with the center point of the fourth target image as the origin until the straight line is parallel to the x-axis. The gray value corresponding to the coordinates in the rotated fourth target image is determined using the bicubic interpolation algorithm to obtain the fifth target image. The fifth target image includes the third height image corresponding to the first height image and the fourth height image corresponding to the second height image.

[0043] The image center distance between multiple calibration patterns in the fifth target image is determined based on the distance between their center coordinates, and the actual center distance between the calibration patterns is determined based on the prior parameters of the calibration plate. The image resolution corresponding to each of the two cameras is determined based on the image center distance between multiple calibration patterns in the fifth target image and the actual center distance between the calibration patterns.

[0044] The offset between the two cameras is determined based on the center coordinates of the calibration pattern corresponding to the third altitude image and the center coordinates of the calibration pattern corresponding to the second altitude image.

[0045] Image coordinate registration is performed between the two cameras based on their respective image resolutions and the offset between them.

[0046] Image registration between the two cameras is primarily achieved through calibration using a calibration board. The calibration patterns on this board can be regular patterns, such as cones, cylinders, or polygonal prisms, or other irregular patterns suitable for identification. Specifically, the calibration board is photographed by both cameras, resulting in third and fourth height images corresponding to each camera. These height images are two-dimensional grayscale images, where the grayscale values ​​correspond to different displacement values ​​along the x-axis obtained during camera capture. The pattern capture parameters of the calibration patterns on the calibration board are obtained, including shape parameters, pixel size, and grayscale values. A matching model is set based on these parameters, and the model is matched against the third and fourth height images in the fourth target image to determine the calibration patterns within these images. The center coordinates of the determined calibration patterns are then determined based on their image positions. The matching model performs grayscale value similarity matching.

[0047] After determining the center coordinates of the calibration patterns in the third and fourth altitude images, to avoid inaccuracies in obtaining the center coordinates leading to them not being on a straight line, the center coordinates of multiple calibration patterns are fitted using the least squares method to determine the straight line containing their center coordinates. For example, the equation of the straight line is y = ax + b, where the tilt angle is arctanb. Based on this tilt angle, the image is rotated with the center point of the fourth target image as the origin. Since the image coordinates before and after rotation do not correspond, some coordinate points in the rotated image lack grayscale values. Therefore, a bicubic interpolation algorithm is used to determine the grayscale values ​​corresponding to the coordinates of the fourth target image after rotation, thus determining the fifth target image. This ensures that both the calibration patterns and the acquisition device are parallel to the x-axis. The calibration patterns are then calibrated... After calibration, the image center distance Δxr between adjacent calibration patterns is calculated based on the center coordinates of multiple calibration patterns. The actual center distance in the calibration plate is determined as xr based on prior parameters, which determines the image resolution of the camera along the x-axis. This image resolution can also be called the lateral resolution of the image, expressed as Fx = xr / Δxr. The lateral resolutions of the two cameras are determined as FxL and FxR respectively, using the aforementioned method. This image resolution (lateral resolution) represents the relationship between the lateral displacement in the image captured by the camera and the actual displacement. Since the two cameras are parallel to the x-axis, it can be determined that there is no offset between the two cameras along the y-axis. The offset Δx between the left and right cameras is determined based on the center coordinates of the calibration patterns in the first and second height images corresponding to the left and right cameras. An affine matrix is ​​established based on the offset Δx between the left and right cameras and the resolutions FxL and FxR of the two cameras along the x-axis. The coordinate parameters of the images captured by the left and right cameras are registered using an affine matrix.

[0048] In this embodiment, two cameras are used to capture images of a calibration board to obtain corresponding third and fourth height images. A matching model is generated using the pattern capture parameters of the calibration pattern on the calibration board and matched with the third and fourth height images to determine the center coordinates of the calibration pattern in the images. The straight lines determined by multiple center coordinates are corrected to be parallel to the x-axis. Finally, the images between the two cameras are registered based on the average spacing between the multiple calibration patterns. Using the aforementioned method, image registration between the left and right cameras can be completed with relatively high accuracy.

[0049] Step 202: Process multiple first target images to obtain a second target image.

[0050] The second target image includes a first height image corresponding to multiple first laser stripe images and a second height image corresponding to multiple second laser stripe images. The height information of the first and second height images is reflected by the grayscale values ​​of the image pixels.

[0051] In one feasible embodiment, processing multiple first target images to obtain a second target image includes: determining the correspondence between laser image distance change values ​​and grayscale change values;

[0052] Based on the mapping relationship between the actual height change value and the laser image distance change value in the first height mapping table and the second height mapping table, the correspondence between the grayscale change value and the actual height change value is determined;

[0053] The second target image is obtained by processing multiple first target images based on the correspondence between the distance change value and the grayscale change value of the laser image, and the height data corresponding to the grayscale value of each pixel in the second target image is determined based on the correspondence between the grayscale change value and the height change value of the actual object.

[0054] In the previous embodiment, the mapping relationship between the actual height change value of the two cameras and the distance change of the laser image was determined by moving the acquisition device along the z-axis. In this embodiment, the correspondence between the distance change value and the grayscale change value of the laser image is first determined, and then the correspondence between the grayscale change value of the image and the actual height change value is determined according to the aforementioned correspondence. In this way, the laser stripe image in the first target image can be converted into a height image, i.e., the second target image, and the height value reflected by the height image is obtained by the grayscale value of each pixel.

[0055] For example, please refer to Figure 3 , Figure 3 This is a schematic diagram of the structure of a laser stripe image provided in an embodiment of this application, as shown below. Figure 3 As shown, Figure 3This includes capturing a laser stripe pattern of the blind vias on the target circuit board. The laser stripe pattern has a displacement portion 301 on the x-axis. In this embodiment, the laser stripe pattern is converted into a height image, which means that the displacement amount of the displacement portion 301 on the x-axis is mapped to the change in grayscale value, and the laser stripe image is converted into a straight line parallel to the y-axis, i.e., a height image. Each pixel in the height image has a corresponding grayscale value, and the grayscale value of the pixel corresponds to the displacement amount of the pixel on the x-axis in the original laser stripe pattern.

[0056] In this embodiment, the correspondence between the laser image distance change value and the grayscale change value is determined to establish the correspondence between the grayscale change value and the actual height change value. Based on this correspondence, the first target image is converted into a second target image. Using the aforementioned method, the image of a three-dimensional object can be rendered in two dimensions.

[0057] Step 203: Determine the effective height image based on the second target image, and obtain the height data and three-dimensional topography data of the blind hole area of ​​the target circuit board based on the effective height image.

[0058] Before determining the height and 3D topography data of the blind vias on the target circuit board based on the height image, it is also necessary to determine the validity of each pixel in the height image, removing invalid pixels and retaining valid ones. This is mainly because during the shooting process of the two cameras, there may be... Figure 1 As shown in the image, there is an occlusion problem. Therefore, the pixels in the occluded parts are inaccurate. If these pixels are retained, it will be detrimental to the calculation of blind hole height data.

[0059] In one feasible embodiment, an effective height image is determined based on the second target image, and height data and three-dimensional topographic data of the blind via region of the target circuit board are obtained based on the effective height image, including:

[0060] Obtain prior information about the target circuit board, including the maximum diameter of the blind vias in the target circuit board; determine the maximum diameter of the blind vias in the second target image based on the image resolution corresponding to each of the two cameras according to the prior information; determine multiple height images on the first height image and the second height image respectively, with the maximum diameter of the blind vias in the target circuit board as the span on the x-axis;

[0061] The validity of each pixel in multiple height images is determined by the continuity of the grayscale value of each pixel in the corresponding height image.

[0062] Among the valid pixels, the first pixel corresponding to the first height image and the second pixel corresponding to the second height image are identified; the height data and three-dimensional topography data of the blind hole region of the target circuit board are obtained by spatial matching of the first pixel and the second pixel according to the iterative nearest point algorithm.

[0063] The prior information of the target circuit board includes the maximum diameter of the blind hole in the target circuit board. However, this diameter is the actual diameter. What needs to be determined in this embodiment is the maximum diameter of the blind hole displayed on the second target image. In the above embodiment, the image resolution of the two cameras was calculated. Therefore, this embodiment can determine the maximum diameter of the blind hole in the second target image by using the prior information of the target circuit board and the image resolution of the two cameras. On the x-axis, with the maximum diameter as the span, a height image is cropped from the first height image and the second height image in the second target image, respectively. The cropped height image covers a complete blind hole. Then, multiple height images are determined based on this height image.

[0064] For example, please refer to Figure 4 , Figure 4 This is a schematic diagram of the structure of a grayscale image provided in an embodiment of this application, such as... Figure 4 As shown, Figure 4 This includes a height image composed of multiple height maps 401. The maximum diameter of the blind hole in this height image is determined to be 6 using the method described above. Since the blind hole is located within the interval 2-8 on the x-axis, a height image within this interval is extracted on the x-axis with a span of 6 (the maximum diameter of the blind hole). Seven height maps 401 are then determined based on the height images within this interval. Figure 4 The height map 401 in the image is only used to represent the selection process of the span; the grayscale values ​​of each pixel in it are not actually processed. Figure 4 To express it.

[0065] Each heightmap contains multiple pixels. Validity is determined for each pixel individually, based on the continuity of its grayscale value within the corresponding heightmap. This continuity can be determined by either the difference in grayscale value between each pixel and its adjacent pixels, or by comparing each pixel's grayscale value with the average grayscale value in the corresponding heightmap. After validating each pixel using these methods, invalid pixels are removed, and valid pixels are retained.

[0066] Among the valid pixels, the first and second pixels corresponding to the first and second height maps of the two cameras are determined respectively. The first and second pixels are then spatially matched according to the iterative nearest point algorithm to obtain a complete image. The height data and three-dimensional topography data of the complete blind hole region obtained by the two cameras are determined based on the gray values ​​of the pixels in the complete image.

[0067] In this embodiment, multiple height images are determined on the x-axis, using the maximum diameter of the blind vias in the target circuit board as the span, on the first grayscale image and the second grayscale image respectively. The validity of each pixel in the height image is determined based on the residual between the grayscale value of each pixel and the average grayscale value in the corresponding height image, and / or the difference between each pixel and its adjacent pixel on the corresponding height image. An iterative nearest-neighbor algorithm is then used to spatially match the first pixel corresponding to the first grayscale image and the second pixel corresponding to the second grayscale image among the valid pixels to obtain the height data and three-dimensional topographic data of the blind via region of the target circuit board. Using the aforementioned method to determine the validity of each pixel avoids inaccurate blind via height data caused by occlusion issues between the two cameras during the shooting process.

[0068] Step 204: Evaluate the quality of the blind vias based on the height data and three-dimensional topography data of the blind via area on the target circuit board to obtain the quality evaluation results.

[0069] The quality evaluation of blind holes mainly includes two aspects: hole depth and hole morphology.

[0070] In one feasible embodiment, the blind via region of the target circuit board includes the region inside the blind via and the region outside the blind via. The quality evaluation result is obtained by evaluating the blind via based on the height data and three-dimensional topography data of the blind via region of the target circuit board, including: obtaining the plane equation of the region outside the blind via by performing plane fitting based on the least squares method and the height data of the region outside the blind via; and obtaining the via depth data based on the plane equation of the region outside the blind via and the height data of the region inside the blind via.

[0071] The radius of curvature of each pixel in the blind via region of the target circuit board is calculated in the x-axis and y-axis directions based on the three-dimensional topographic data of the blind via region. The quality evaluation result is obtained by evaluating the quality of the blind via based on the depth data of the blind via and the radius of curvature of each point in the x-axis and y-axis directions.

[0072] After obtaining the height data of the blind hole region through the above embodiments, it is necessary to calculate the depth of the blind hole. Since the target circuit board may not be perfectly horizontal when photographed, there may be a tilt problem. Therefore, directly obtaining the hole depth from the height data of the area inside the blind hole is inaccurate. At this time, it is necessary to perform plane fitting on the height data of the area outside the blind hole using the least squares method to obtain the height data of multiple pixels of a complete plane. The coordinates of these multiple pixels can be determined based on their height data, and the plane equation of the plane is determined based on the coordinates as Ax + By + Cz + D = 0. Then, based on the height data of the area inside the blind hole, the height data of the deepest point of the blind hole can be determined. This is then determined as the coordinates (x1, y1, z1), and the hole depth of the blind hole can be determined based on its coordinates and the plane equation. After determining the depth of the blind hole, its quality is evaluated according to the quality control standards for blind hole depth, i.e., whether it meets the depth requirements.

[0073] After obtaining the three-dimensional topography data of the blind hole through the above embodiments, it is necessary to determine the radius of curvature of each point in the x-axis and y-axis directions, i.e., the radius of curvature on the horizontal plane, based on the three-dimensional topography data of the blind hole. The logical judgment of each point is realized by comparing the size of the radius of curvature of each point with the size of the radius of curvature of each point corresponding to the quality control standard. That is, the judgment of 0 and 1. Based on the distribution of logical 0 points in the entire blind hole, the quality evaluation of the three-dimensional topography of the blind hole is carried out, such as judging the size of the number of logical 0 points or whether the distribution is concentrated.

[0074] In this embodiment, the plane equation of the region outside the blind hole is determined by using the least squares method and the height data of the blind hole region. The depth of the blind hole is then determined based on the height data and plane equation within the blind hole. Finally, the radius of curvature of each pixel within the blind hole in the x-axis and y-axis directions is determined using the three-dimensional topography data of the blind hole region to evaluate the quality of the blind hole and obtain a quality evaluation result. Using the aforementioned method, the depth of the blind hole can be accurately obtained, and a highly accurate quality evaluation of the three-dimensional topography within the blind hole can be performed.

[0075] As can be seen, in this embodiment, two cameras are used to capture images of the target circuit board along the x-axis to obtain multiple first target images. These first target images are then processed to obtain second target images. Valid grayscale images are determined based on the first and second grayscale images. Height data and three-dimensional topography data of the blind via region on the target circuit board are obtained from the valid grayscale images. Finally, the quality of the blind vias is evaluated based on these data to obtain a quality evaluation result. Using this method, the height data and three-dimensional topography data of the blind vias on the circuit board can be accurately obtained without damaging the circuit board, and their quality can be effectively evaluated.

[0076] For embodiments consistent with those shown above, please refer to... Figure 5 , Figure 5 This is a schematic diagram of a circuit board blind via quality inspection system provided in an embodiment of this application. The circuit board blind via quality inspection system 50 includes a data acquisition device 501, a processing device 502, and a detection device 503. The data acquisition device 501 includes a data acquisition module comprising a laser device and cameras located on both sides of the laser device on the x-axis, wherein:

[0077] The acquisition device 501 is used to capture images of the target circuit board, obtain multiple first target images, and send the multiple first target images to the processing device. The target circuit board has at least one blind hole and is illuminated by a laser device. Each first target image includes a first laser stripe image and a second laser stripe image corresponding to two cameras, respectively.

[0078] Processing device 502 is used to process multiple first target images to obtain a second target image, the second target image including a first height image corresponding to multiple first laser stripe images and a second height image corresponding to multiple second laser stripe images;

[0079] The processing device 502 is also used to determine an effective height image based on the second target image, and to obtain height data and three-dimensional topography data of the blind hole area of ​​the target circuit board based on the effective height image;

[0080] The testing device 503 is used to evaluate the quality of blind holes based on the height data and three-dimensional topographic data of the blind hole area of ​​the target circuit board and obtain the quality evaluation result.

[0081] In a feasible embodiment, before acquiring multiple first target images by photographing the target circuit board along the x-axis, the acquisition device 501 is further configured to: simultaneously adjust the height of the acquisition device to photograph the target circuit board to obtain third target images corresponding to different heights, the third target images including third laser stripe images and fourth laser stripe images corresponding to the two cameras respectively; and generate a first height mapping table and a second height mapping table corresponding to the two cameras respectively based on the distance on the x-axis between the third laser stripe images and the fourth laser stripe images corresponding to different heights, the height mapping table including the mapping relationship between the change value of the actual height and the change value of the laser image distance.

[0082] In one feasible embodiment, before the acquisition device 501 captures images of the target circuit board along the x-axis to obtain multiple first target images, the system further includes: capturing images of a calibration board through the acquisition device 501 to obtain a fourth target image, the fourth target image including first height images and second height images corresponding to the two cameras respectively, and the calibration board including multiple regularly arranged calibration patterns.

[0083] The processing device 502 acquires the pattern shooting parameters of the calibration pattern, including the shape parameters, pixel size, and grayscale value of the calibration pattern; sets a matching model based on the pattern shooting parameters, matches the pattern shooting parameters in the fourth target image according to the matching model to determine the calibration pattern in the fourth target image, and calculates the center coordinates of multiple calibration patterns; fits the center coordinates of multiple calibration patterns according to the least squares method to determine the straight line where the center coordinates of multiple calibration patterns are located; rotates the fourth target image with the center point of the fourth target image as the origin according to the slope of the straight line until the straight line is parallel to the x-axis, and determines the grayscale value corresponding to the coordinates in the rotated fourth target image according to the bicubic interpolation algorithm to obtain the fifth target image, which includes the third height image corresponding to the first height image and the fourth height image corresponding to the second height image;

[0084] The image center distance between multiple calibration patterns in the fifth target image is determined based on the distance between their center coordinates, and the actual center distance between the calibration patterns is determined based on the prior parameters of the calibration plate. The image resolution corresponding to each of the two cameras is determined based on the image center distance between multiple calibration patterns in the fifth target image and the actual center distance between the calibration patterns. The offset between the two cameras is determined based on the center coordinates of the calibration patterns corresponding to the third altitude image and the center coordinates of the calibration patterns corresponding to the second altitude image. Image coordinate registration is performed on the two cameras based on their respective resolutions and the offset between them.

[0085] In one feasible embodiment, the processing device 502 processes multiple first target images to obtain a second target image, including: determining the correspondence between laser image distance change values ​​and grayscale change values; determining the correspondence between grayscale change values ​​and actual object height change values ​​based on the mapping relationship between actual object height change values ​​and laser image distance change values ​​in a first height mapping table and a second height mapping table; processing the multiple first target images to obtain the second target image based on the correspondence between laser image distance change values ​​and grayscale change values, and determining the height data corresponding to the grayscale value of each pixel in the second target image based on the correspondence between grayscale change values ​​and actual object height change values.

[0086] In a feasible embodiment, the processing device 502 determines an effective height image based on the second target image, and obtains height data and three-dimensional topographic data of the blind hole region of the target circuit board based on the effective height image, including: acquiring prior information of the target circuit board, the prior information including the maximum diameter of the blind hole in the target circuit board; determining the maximum diameter of the blind hole in the second target image based on the image resolution corresponding to each of the two cameras based on the prior information; determining multiple height images on the first height image and the second height image respectively, with the maximum diameter of the blind hole in the target circuit board as the span on the x-axis; determining the validity of each pixel in the multiple height images, wherein the validity of each pixel includes: the residual between the gray value of each pixel and the average gray value in the height image corresponding to the pixel satisfies a preset condition, and / or the difference between each pixel and its adjacent pixels in the corresponding height image satisfies a preset condition;

[0087] Among the valid pixels, the first pixel corresponding to the first height image and the second pixel corresponding to the second height image are identified; the height data and three-dimensional topography data of the blind hole region of the target circuit board are obtained by spatial matching of the first pixel and the second pixel according to the iterative nearest point algorithm.

[0088] In one feasible embodiment, the blind via region of the target circuit board includes the region inside the blind via and the region outside the blind via. The detection device 503 performs a quality evaluation of the blind via based on the height data and three-dimensional topography data of the blind via region of the target circuit board to obtain a quality evaluation result. This includes: performing plane fitting based on the least squares method and the height data of the region outside the blind via to obtain the plane equation of the region outside the blind via; obtaining the via depth data based on the plane equation of the region outside the blind via and the height data of the region inside the blind via; calculating the radius of curvature of each point in the blind via in the x-axis and y-axis directions based on the three-dimensional topography data of the blind via region of the target circuit board; and performing a quality evaluation of the blind via based on the via depth data and the radius of curvature of each pixel in the blind via in the x-axis and y-axis directions to obtain a quality evaluation result.

[0089] This application provides a computer-readable storage medium storing program data, which, when executed by a processor, is used to perform some or all of the steps of any of the circuit board blind via quality inspection methods described in the above method embodiments.

[0090] It should be noted that, for the sake of simplicity, all of the aforementioned embodiments of the circuit board blind via quality inspection method are described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to this application.

[0091] Although this application has been described herein in conjunction with various embodiments, those skilled in the art, by reviewing the accompanying drawings, disclosure, and appended claims, will understand and implement other variations of the disclosed embodiments in carrying out the claimed application. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude multiple instances. While different dependent claims may recite certain measures, this does not mean that these measures cannot be combined to produce a good effect.

[0092] Those skilled in the art will understand that all or part of the steps in the various methods of any of the above-described embodiments of the circuit board blind via quality inspection method can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage device, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a disk, or an optical disk, etc.

[0093] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principle and implementation of a method and system for detecting blind vias on a circuit board. The description of the embodiments above is only for the purpose of helping to understand the method and its core ideas. At the same time, for those skilled in the art, there will be changes in the specific implementation and application scope based on the idea of ​​the method and system for detecting blind vias on a circuit board. Therefore, the content of this specification should not be construed as a limitation of this application.

[0094] This application is described with reference to flowchart illustrations and / or block diagrams of methods, hardware products, and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0095] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0096] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0097] It is understood that any product that is controlled or configured to perform the processing method described in the flowchart of the method embodiment of the circuit board blind via quality inspection method of this application, such as the terminal and computer program product of the above flowchart, falls within the scope of the related products described in this application.

[0098] Obviously, those skilled in the art can make various modifications and variations to the circuit board blind via quality inspection method and system provided in this application without departing from the spirit and scope of this application. Therefore, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application also intends to include these modifications and variations.

Claims

1. A method for inspecting the quality of blind vias on a circuit board, characterized in that, The method includes: Multiple first target images are obtained by taking pictures of the target circuit board along the x-axis using two cameras. The target circuit board has at least one blind hole and is illuminated by a laser device. Each first target image includes a first laser stripe image and a second laser stripe image corresponding to the two cameras respectively. The two cameras are located on both sides of the laser device along the x-axis. A second target image is obtained by processing multiple first target images, and the second target image includes multiple first height images corresponding to multiple first laser stripe images and multiple second height images corresponding to multiple second laser stripe images. An effective height image is determined based on the second target image, and height data and three-dimensional topography data of the blind hole region of the target circuit board are obtained based on the effective height image. The quality evaluation results are obtained by evaluating the blind vias based on the height data and three-dimensional topography data of the blind via area of ​​the target circuit board. Before obtaining multiple first target images by photographing the target circuit board along the x-axis using two cameras, the method further includes: Simultaneously, the heights of the two cameras and the laser device are adjusted to capture images of the target circuit board at different heights, resulting in third target images corresponding to different heights. The third target images include third laser stripe images and fourth laser stripe images corresponding to the two cameras, respectively. Based on the distances on the x-axis between the third and fourth laser stripe images corresponding to different heights, a first height mapping table and a second height mapping table are generated for the two cameras respectively. The height mapping table includes the mapping relationship between the change value of the actual height and the change value of the distance in the laser image.

2. The method according to claim 1, characterized in that, Before obtaining multiple first target images by photographing the target circuit board along the x-axis using two cameras, the method further includes: The calibration board is photographed by the two cameras to obtain a fourth target image. The fourth target image includes the third height image and the fourth height image corresponding to the two cameras respectively. The calibration board includes multiple regularly arranged calibration patterns. Obtain the pattern shooting parameters of the calibration pattern, the pattern shooting parameters including the shape parameters, pixel size and grayscale value of the calibration pattern; A matching model is set according to the pattern shooting parameters. The pattern shooting parameters in the fourth target image are matched according to the matching model to determine the calibration pattern in the fourth target image, and the center coordinates of multiple calibration patterns are calculated. The center coordinates of the multiple calibration patterns are fitted using the least squares method to determine the straight line where the center coordinates of the multiple calibration patterns lie; Based on the inclination of the straight line, the fourth target image is rotated with the center point of the fourth target image as the origin until the straight line is parallel to the x-axis. The gray values ​​corresponding to the coordinates in the rotated fourth target image are determined according to the bicubic interpolation algorithm to obtain the fifth target image. The fifth target image includes the fifth height image corresponding to the third height image and the sixth height image corresponding to the fourth height image. The image center distance between the multiple calibration patterns in the fifth target image is determined based on the distance between the center coordinates of the multiple calibration patterns in the fifth target image, and the actual center distance between the calibration patterns is determined based on the prior parameters of the calibration plate. The image resolution of each of the two cameras is determined based on the image center distance between multiple calibration patterns in the fifth target image and the actual center distance between the calibration patterns. The offset between the two cameras is determined based on the center coordinates of the calibration pattern corresponding to the fifth altitude image and the center coordinates of the calibration pattern corresponding to the sixth altitude image; Image coordinate registration is performed between the two cameras based on their respective resolutions and the offset between them.

3. The method according to claim 2, characterized in that, The process of processing multiple first target images to obtain a second target image includes: Determine the correspondence between the distance change value and the grayscale change value in the laser image; Based on the mapping relationship between the actual height change value and the laser image distance change value in the first height mapping table and the second height mapping table, the correspondence between the grayscale change value and the actual height change value is determined; The second target image is obtained by processing the plurality of first target images according to the correspondence between the laser image distance change value and the grayscale change value, and the height data corresponding to the grayscale value of each pixel in the second target image is determined according to the correspondence between the grayscale change value and the object height change value.

4. The method according to claim 3, characterized in that, The step of determining an effective height image based on the second target image, and obtaining height data and three-dimensional topography data of the blind via region of the target circuit board based on the effective height image, includes: Obtain prior information of the target circuit board, including the maximum diameter of blind vias in the target circuit board; Based on the prior information, the maximum diameter of the blind hole in the second target image is determined by determining the image resolution corresponding to each of the two cameras. On the x-axis, with the maximum diameter of the blind via in the target circuit board as the span, multiple height images are determined on the first height image and the second height image, respectively. The validity of each pixel in the multiple height images is determined based on the continuity of the grayscale value of each pixel in the corresponding height image. Among the valid pixels, the first pixel corresponding to the first height image and the second pixel corresponding to the second height image are identified. The height data and three-dimensional shape data of the blind hole region of the target circuit board are obtained by spatial matching of the first pixel and the second pixel using the iterative nearest point algorithm.

5. The method according to claim 4, characterized in that, The target circuit board blind via region includes the area within the blind via and the area outside the blind via. The quality evaluation result obtained by evaluating the blind via based on the height data and three-dimensional topographic data of the target circuit board blind via region includes: The plane equation of the area outside the blind holes of the target circuit board is obtained by plane fitting based on the least squares method and the height data of the area outside the blind holes of the target circuit board. The hole depth data of the blind hole is obtained based on the plane equation of the area outside the blind hole of the target circuit board and the height data of the area inside the blind hole of the target circuit board. The radius of curvature of each point in the blind hole in the x-axis and y-axis directions is calculated based on the three-dimensional topographic data of the blind hole region of the target circuit board. The quality evaluation result is obtained by evaluating the blind hole based on the hole depth data and the curvature radius of each pixel in the blind hole in the x-axis and y-axis directions.

6. A circuit board blind via quality inspection system, comprising a data acquisition device, a processing device, and a detection device, wherein the data acquisition device includes a data acquisition module comprising a laser device and cameras positioned on either side of the laser device along the x-axis, characterized in that: The acquisition device captures images of the target circuit board to obtain multiple first target images, and sends the multiple first target images to the processing device. The target circuit board has at least one blind hole, and the target circuit board is illuminated by the laser device. Each first target image includes a first laser stripe image and a second laser stripe image corresponding to two cameras, respectively. The processing device is used to process multiple first target images to obtain a second target image, wherein the second target image includes multiple first height images corresponding to the first laser stripe images and multiple second height images corresponding to the second laser stripe images; The processing device is further configured to determine an effective height image based on the second target image, and obtain height data and three-dimensional topography data of the blind hole region of the target circuit board based on the effective height image; The detection device is used to evaluate the quality of the blind hole based on the height data and three-dimensional morphology data of the blind hole area of ​​the target circuit board and obtain the quality evaluation result. Before the acquisition device captures images of the target circuit board and obtains multiple first target images, the system further includes: Simultaneously, the height of the acquisition device is adjusted to capture images of the target circuit board at different heights, resulting in third target images corresponding to different heights. The third target images include third laser stripe images and fourth laser stripe images corresponding to the two cameras, respectively. Based on the distances on the x-axis between the third and fourth laser stripe images corresponding to different heights, a first height mapping table and a second height mapping table are generated for the two cameras respectively. The height mapping table includes the mapping relationship between the change value of the actual height and the change value of the distance in the laser image.

7. The system according to claim 6, characterized in that, Before the acquisition device captures images of the target circuit board and obtains multiple first target images, the system further includes: The calibration board is photographed by the acquisition device to obtain a fourth target image. The fourth target image includes a first height image and a second height image corresponding to the two cameras respectively. The calibration board includes multiple regularly arranged calibration patterns. The processing device acquires the pattern shooting parameters of the calibration pattern, the pattern shooting parameters including the shape parameters, pixel size and grayscale value of the calibration pattern; A matching model is set according to the pattern shooting parameters, and the pattern shooting parameters in the fourth target image are matched according to the matching model to determine the calibration pattern in the fourth target image, and the center coordinates of multiple calibration patterns are calculated. The center coordinates of the multiple calibration patterns are fitted using the least squares method to determine the straight line where the center coordinates of the multiple calibration patterns lie; Based on the inclination of the straight line, the fourth target image is rotated with the center point of the fourth target image as the origin until the straight line is parallel to the x-axis. The gray value corresponding to the coordinates in the rotated fourth target image is determined according to the bicubic interpolation algorithm to obtain the fifth target image. The fifth target image includes the third height image corresponding to the first height image and the fourth height image corresponding to the second height image. The image center distance between the multiple calibration patterns in the fifth target image is determined based on the distance between the center coordinates of the multiple calibration patterns in the fifth target image, and the actual center distance between the calibration patterns is determined based on the prior parameters of the calibration plate. The image resolution of each of the two cameras is determined based on the image center distance between multiple calibration patterns in the fifth target image and the actual center distance between the calibration patterns. The offset between the two cameras is determined based on the center coordinates of the calibration pattern corresponding to the third altitude image and the center coordinates of the calibration pattern corresponding to the second altitude image; Image coordinate registration is performed between the two cameras based on their respective resolutions and the offset between them.

8. A computer-readable storage medium, characterized in that, A computer program for storing electronic data interchange is provided, wherein the computer program causes a computer to perform the method as described in any one of claims 1-5.

Images