PCB multilayer board slitting method based on machine vision
Through machine vision technology, the PCB multi-layer boards are automatically identified and cut, which solves the problems of low efficiency and low accuracy of manual board segmentation, and realizes an efficient and lossless automatic slitting process to meet the needs of full-line automation and intelligence.
Patent Information
- Application Number
- CN202411265549.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-10
- Publication Date
- 2024-12-17
- Estimated Expiration
- 2044-09-10
AI Technical Summary
In the existing PCB pressing process, the disassembly process mainly relies on manual partitioning, which has problems such as low efficiency, low accuracy and component damage, especially when partitioning on circuit boards with components.
Using the PCB multi-layer board slitting method based on machine vision, the first-piece formula parameters are set, and the image processing is performed to obtain the cropping parameters, and whether it is within the tolerance range. If so, it will be performed. Automatically cut, if not, adjust the parameters and try again until the conditions are met.
It realizes efficient and lossless automatic slitting of multi-layer PCB boards, meets the requirements of whole-line automation, intelligence and unmanned, and improves the efficiency and accuracy of board splitting.
Smart Images

Figure CN119155902A_ABST
Abstract
Description
Technical Field
[0001] The invention belongs to the technical field of machine vision detection, and in particular relates to a PCB multilayer board slitting method based on machine vision. Background Art
[0002] In recent years, as the trend of electronic equipment and electronic terminal products towards thinness and miniaturization has become increasingly clear, the demand for high density and high performance of PCBs has become increasingly prominent. Improving utilization, reducing the distance between boards, and increasing production have become the general trend of the PCB industry.
[0003] However, in the PCB lamination process, the disassembly process after lamination still basically adopts the method of manual board separation, and the excess copper foil is recycled by manual work, and the board separation of multiple panels is even not cut at all in some production process lines. There are disadvantages such as long mold opening cycle, slow efficiency, and low precision. Especially when separating boards on circuit boards with components soldered, the vibration will cause certain damage to the components themselves. Therefore, automatic slitting of PCB board lamination is a key core technology in an important part of PCB manufacturing, and it is also a pain point that the industry urgently needs to solve.
[0004] Therefore, the present invention provides a PCB multilayer board slitting method based on machine vision to solve the above technical problems. Summary of the invention
[0005] In view of the above problems, the object of the present invention is to provide a PCB multilayer board slitting method based on machine vision, which has high board slitting efficiency and will not cause damage during the board slitting process.
[0006] The present invention provides a PCB multilayer board cutting method based on machine vision, comprising the following steps:
[0007] Step S1, setting the first-piece formula parameters, wherein the first-piece formula parameters include the standard values of the length and width of the core of the PCB multilayer board, the deviation values of the cutting edges around the core of the PCB multilayer board, the number of cores of the PCB multilayer board, and the thickness of the PCB multilayer board;
[0008] Step S2, acquiring an image of a PCB multilayer board to be identified through a camera, and processing the image of the PCB multilayer board to be identified through an image processing algorithm to obtain cutting parameters of the PCB multilayer board to be identified, and comparing the cutting parameters with the first-piece formula parameters to determine whether the cutting parameters are within the tolerance range of the first-piece formula parameters;
[0009] Step S3, if the cutting parameters are within the tolerance range of the first-piece recipe parameters, the PCB multilayer board to be identified is transferred to a cutting mechanism by a robot, and the cutting mechanism cuts the PCB multilayer board to be identified according to the cutting parameters;
[0010] Step S4, if the cutting parameters are not within the tolerance range of the first-article formula parameters, return to step S1 to readjust the first-article formula parameters, and after readjusting the first-article formula parameters, enter step S2 to continue to perform image processing and parameter comparison operations on the PCB multilayer board to be identified, and cycle in sequence until the cutting parameters of the PCB multilayer board to be identified are within the tolerance range of the adjusted first-article formula parameters, and then enter step S3 to perform cutting operations;
[0011] Step S5, if the cutting mechanism successfully cuts the PCB multilayer board to be identified according to the cutting parameters, the cutting mechanism can batch cut PCB multilayer boards of the same specification as the PCB multilayer board to be identified according to the first piece recipe parameters.
[0012] Preferably, the PCB multilayer board to be identified is a PCB multilayer board with four board cores.
[0013] Preferably, in step S2, the image of the PCB multilayer board to be identified is processed by an image processing algorithm to obtain the cutting parameters of the PCB multilayer board to be identified, which specifically includes:
[0014] Step S21, performing a smoothing preprocessing operation on the PCB multilayer board image to be identified, so as to remove noise points on the PCB multilayer board image to be identified;
[0015] Step S22, using an adaptive segmentation algorithm to segment the PCB multilayer board image to be identified after the smoothing preprocessing operation, so as to segment the board core on the PCB multilayer board image to be identified and perform binarization processing on the PCB multilayer board image to be identified with the board core segmented, so as to form a segmented image;
[0016] Step S23, making a minimum circumscribed rectangle for the board core on the segmented image, and finding the center point of the minimum circumscribed rectangle of the board core and the angle of the board core, and performing overall correction on the segmented image according to the angle of the board core to obtain a cropped image;
[0017] Step S24, compare the minimum circumscribed rectangles of the left and right cores on the cut image to obtain the left and right sidelines of the middle cut area in the vertical direction. Then calculate the position of the middle cut line in the vertical direction based on the left and right sidelines; make another minimum circumscribed rectangle based on the minimum circumscribed rectangles of the left and right cores on the cut image to obtain the first circumscribed rectangles of the left and right cores; compare the four vertex coordinates of the first circumscribed rectangle to obtain the sidelines of the cut areas on the left and right sides; move the sidelines of the cut areas on the left and right sides to the left and right sides by a fixed distance respectively to obtain the left cut line and the right cut line;
[0018] Step S25, compare the minimum circumscribed rectangles of the upper and lower board cores on the cutting image to obtain the upper and lower side lines of the middle cutting area in the horizontal direction; then calculate the position of the middle cutting line in the horizontal direction according to the upper and lower side lines; make another minimum circumscribed rectangle based on the minimum circumscribed rectangles of the upper and lower board cores on the cutting image to obtain the second circumscribed rectangles of the upper and lower board cores; compare the four vertex coordinates of the second circumscribed rectangle to obtain the side lines of the cutting areas on the upper and lower sides; move the side lines of the cutting areas on the upper and lower sides to the upper and lower sides by a fixed distance respectively to obtain the upper cutting line and the lower cutting line
[0019] Step S26, perform nine-point calibration on the cutting image through a manipulator and a camera to obtain the cutting parameters of the PCB multilayer board to be identified, wherein the cutting parameters include the length and width values of the board core on the cutting image, the number of board cores on the cutting image, the thickness of the board core on the cutting image, the coordinate value of the center point of the board core on the cutting image, and the coordinate values of the vertical middle cutting line, the horizontal middle cutting line, the upper cutting line, the lower cutting line, the left cutting line and the right cutting line on the cutting image.
[0020] Preferably, the cutting mechanism is composed of a rolling cutter and / or a rolling cutter.
[0021] Compared with the related art, the present invention provides a PCB multilayer board cutting method based on machine vision, including: setting the first-piece formula parameters; obtaining the image of the PCB multilayer board to be identified through a camera, processing the image of the PCB multilayer board to be identified through an image processing algorithm, obtaining the cutting parameters of the PCB multilayer board to be identified, comparing the cutting parameters with the first-piece formula parameters, and judging whether the cutting parameters are within the tolerance range of the first-piece formula parameters; if the cutting parameters are within the tolerance range of the first-piece formula parameters, the PCB multilayer board to be identified is transported to the cutting mechanism by a manipulator, and the cutting mechanism cuts the PCB multilayer board to be identified according to the cutting parameters; if the cutting is successful, the cutting mechanism can batch cut the PCB multilayer board of the same specification as the PCB multilayer board to be identified according to the first-piece formula parameters. The present invention accurately finds the edge position of the PCB multilayer board and automatically cuts it to form a board-cutting action through visual operation analysis and mechanism cutting principles, which can realize automatic board-cutting without manual board-cutting, and its board-cutting efficiency is high, and the board-cutting process will not cause damage. In addition, the use of the present invention can meet the beat requirements of the entire line and realize the automation, intelligence, unmanned and online operation of the panel separation action. BRIEF DESCRIPTION OF THE DRAWINGS
[0022] Figure 1 A schematic diagram of a process of cutting a PCB multilayer board based on machine vision according to the present invention;
[0023] Figure 2A schematic diagram of a process for obtaining cutting parameters of the present invention;
[0024] Figure 3 It is a schematic diagram of cutting the multi-layer PCB to be identified according to the present invention. DETAILED DESCRIPTION
[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0026] Please also refer to the attached Figure 1-2 The present invention provides a PCB multilayer board cutting method based on machine vision, comprising the following steps:
[0027] Step S1, setting the first-piece formula parameters, wherein the first-piece formula parameters include the standard values of the length and width of the core of the PCB multilayer board, the deviation values of the cutting edges around the core of the PCB multilayer board, the number of cores of the PCB multilayer board, and the thickness of the PCB multilayer board;
[0028] Step S2, acquiring an image of a PCB multilayer board to be identified through a camera, and processing the image of the PCB multilayer board to be identified through an image processing algorithm to obtain cutting parameters of the PCB multilayer board to be identified, and comparing the cutting parameters with the first-piece formula parameters to determine whether the cutting parameters are within the tolerance range of the first-piece formula parameters;
[0029] Step S3, if the cutting parameters are within the tolerance range of the first-piece recipe parameters, the PCB multilayer board to be identified is transferred to a cutting mechanism by a robot, and the cutting mechanism cuts the PCB multilayer board to be identified according to the cutting parameters;
[0030] Step S4, if the cutting parameters are not within the tolerance range of the first-article formula parameters, return to step S1 to readjust the first-article formula parameters, and after readjusting the first-article formula parameters, enter step S2 to continue to perform image processing and parameter comparison operations on the PCB multilayer board to be identified, and cycle in sequence until the cutting parameters of the PCB multilayer board to be identified are within the tolerance range of the adjusted first-article formula parameters, and then enter step S3 to perform cutting operations;
[0031] Step S5, if the cutting mechanism successfully cuts the PCB multilayer board to be identified according to the cutting parameters, the cutting mechanism can batch cut PCB multilayer boards of the same specification as the PCB multilayer board to be identified according to the first piece recipe parameters.
[0032] In this embodiment, the PCB multilayer board to be identified is a PCB multilayer board with four board cores, but is certainly not limited to this. The PCB multilayer board to be identified can also be a PCB multilayer board with 2 board cores, or a PCB multilayer board with 6 board cores, or a PCB multilayer board with 8 board cores, etc. The board separation principle is consistent with the principle of this method and is within the protection scope of the present invention.
[0033] Specifically, in step S2, the image of the PCB multilayer board to be identified is processed by an image processing algorithm to obtain the cutting parameters of the PCB multilayer board to be identified, which specifically includes:
[0034] Step S21, performing a smoothing preprocessing operation on the PCB multilayer board image to be identified, so as to remove noise points on the PCB multilayer board image to be identified;
[0035] Step S22, using an adaptive segmentation algorithm to segment the PCB multilayer board image to be identified after the smoothing preprocessing operation, so as to segment the board core on the PCB multilayer board image to be identified and perform binarization processing on the PCB multilayer board image to be identified with the board core segmented, so as to form a segmented image;
[0036] Step S23, making a minimum circumscribed rectangle for the board core on the segmented image, and finding the center point of the minimum circumscribed rectangle of the board core and the angle of the board core, and performing overall correction on the segmented image according to the angle of the board core to obtain a cropped image;
[0037] Step S24, compare the minimum circumscribed rectangles of the left and right cores on the cut image to obtain the left and right sidelines of the middle cut area in the vertical direction. Then calculate the position of the middle cut line 1 in the vertical direction based on the left and right sidelines; make another minimum circumscribed rectangle based on the minimum circumscribed rectangles of the left and right cores on the cut image to obtain the first circumscribed rectangles of the left and right cores; compare the four vertex coordinates of the first circumscribed rectangle to obtain the sidelines of the cut areas on the left and right sides; move the sidelines of the cut areas on the left and right sides to the left and right sides by a fixed distance respectively to obtain the left cut line 2 and the right cut line 3;
[0038] Step S25, compare the minimum circumscribed rectangles of the upper and lower board cores on the cutting image to obtain the upper and lower side lines of the middle cutting area in the horizontal direction; then calculate the position of the middle cutting line 4 in the horizontal direction based on the upper and lower side lines; make another minimum circumscribed rectangle based on the minimum circumscribed rectangles of the upper and lower board cores on the cutting image to obtain the second circumscribed rectangle of the upper and lower board cores; compare the four vertex coordinates of the second circumscribed rectangle to obtain the side lines of the cutting areas on the upper and lower sides; move the side lines of the cutting areas on the upper and lower sides by a fixed distance to the upper and lower sides respectively to obtain the upper cutting line 5 and the lower cutting line 6.
[0039] Step S26, perform nine-point calibration on the cutting image through a manipulator and a camera to obtain the cutting parameters of the PCB multilayer board to be identified, wherein the cutting parameters include the length and width values of the board core on the cutting image, the number of board cores on the cutting image, the thickness of the board core on the cutting image, the coordinate value of the center point of the board core on the cutting image, and the coordinate values of the vertical middle cutting line 1, the horizontal middle cutting line 4, the upper cutting line 5, the lower cutting line 6, the left cutting line 2 and the right cutting line 3 on the cutting image.
[0040] In addition, it should be noted that the cut image is calibrated at nine points by the manipulator and the camera to obtain the conversion relationship between the pixel coordinates of the cut image and the manipulator coordinates. According to the results of the nine-point calibration, the length and width of the core board on the cut image, the number of core boards on the cut image, the thickness of the core board on the cut image, the coordinate value of the center point of the core board on the cut image, and the coordinate values of the vertical middle cutting line 1, the horizontal middle cutting line 4, the upper cutting line 5, the lower cutting line 6, the left cutting line 2 and the right cutting line 3 on the cut image are obtained, and finally the above parameters are sent to the manipulator and the cutting mechanism for grasping and cutting.
[0041] In this embodiment, the cutting mechanism is composed of a rolling cutter and / or a rolling cutter.
[0042] Compared with the related art, the present invention provides a PCB multilayer board cutting method based on machine vision, including: setting the first-piece formula parameters; obtaining the image of the PCB multilayer board to be identified through a camera, processing the image of the PCB multilayer board to be identified through an image processing algorithm, obtaining the cutting parameters of the PCB multilayer board to be identified, comparing the cutting parameters with the first-piece formula parameters, and judging whether the cutting parameters are within the tolerance range of the first-piece formula parameters; if the cutting parameters are within the tolerance range of the first-piece formula parameters, the PCB multilayer board to be identified is transported to the cutting mechanism by a manipulator, and the cutting mechanism cuts the PCB multilayer board to be identified according to the cutting parameters; if the cutting is successful, the cutting mechanism can batch cut the PCB multilayer board of the same specification as the PCB multilayer board to be identified according to the first-piece formula parameters. The present invention accurately finds the edge position of the PCB multilayer board and automatically cuts it to form a board-cutting action through visual operation analysis and mechanism cutting principles, which can realize automatic board-cutting without manual board-cutting, and its board-cutting efficiency is high, and the board-cutting process will not cause damage. In addition, the use of the present invention can meet the beat requirements of the entire line and realize the automation, intelligence, unmanned and online operation of the panel separation action.
[0043] It should be noted that the above-described embodiments should be understood as illustrative rather than limiting the scope of protection of the present invention, and the scope of protection of the present invention shall be subject to the claims. For those skilled in the art, some non-essential improvements and adjustments made to the present invention still fall within the scope of protection of the present invention without departing from the essence and scope of the present invention.
Claims
1. A PCB multilayer cutting method based on machine vision, It is characterized in that The method comprises the following steps: Step S1, setting the first-piece formula parameters, wherein the first-piece formula parameters include the standard values of the length and width of the core of the PCB multilayer board, the deviation values of the cutting edges around the core of the PCB multilayer board, the number of cores of the PCB multilayer board, and the thickness of the PCB multilayer board; Step S2, acquiring an image of a PCB multilayer board to be identified through a camera, and processing the image of the PCB multilayer board to be identified through an image processing algorithm to obtain cutting parameters of the PCB multilayer board to be identified, and comparing the cutting parameters with the first-piece formula parameters to determine whether the cutting parameters are within the tolerance range of the first-piece formula parameters; Step S3, if the cutting parameters are within the tolerance range of the first-piece recipe parameters, the PCB multilayer board to be identified is transferred to a cutting mechanism by a robot, and the cutting mechanism cuts the PCB multilayer board to be identified according to the cutting parameters; Step S4, if the cutting parameters are not within the tolerance range of the first-article formula parameters, return to step S1 to readjust the first-article formula parameters, and after readjusting the first-article formula parameters, enter step S2 to continue to perform image processing and parameter comparison operations on the PCB multilayer board to be identified, and cycle in sequence until the cutting parameters of the PCB multilayer board to be identified are within the tolerance range of the adjusted first-article formula parameters, and then enter step S3 to perform cutting operations; Step S5, if the cutting mechanism successfully cuts the PCB multilayer board to be identified according to the cutting parameters, the cutting mechanism can batch cut PCB multilayer boards of the same specification as the PCB multilayer board to be identified according to the first piece recipe parameters.
2. According to the machine vision-based PCB multilayer cutting method of claim 1, It is characterized in that The PCB multilayer board to be identified is a PCB multilayer board with four board cores.
3. According to the machine vision-based PCB multilayer cutting method of claim 2, It is characterized in that In the step S2, the image of the PCB multilayer board to be identified is processed by an image processing algorithm to obtain the cutting parameters of the PCB multilayer board to be identified, which specifically includes: Step S21, performing a smoothing preprocessing operation on the PCB multilayer board image to be identified, so as to remove noise points on the PCB multilayer board image to be identified; Step S22, using an adaptive segmentation algorithm to segment the PCB multilayer board image to be identified after the smoothing preprocessing operation, so as to segment the board core on the PCB multilayer board image to be identified and perform binarization processing on the PCB multilayer board image to be identified with the board core segmented, so as to form a segmented image; Step S23, making a minimum circumscribed rectangle for the board core on the segmented image, and finding the center point of the minimum circumscribed rectangle of the board core and the angle of the board core, and performing overall correction on the segmented image according to the angle of the board core to obtain a cropped image; Step S24, compare the minimum circumscribed rectangles of the left and right board cores on the cut image to obtain the left and right sidelines of the middle cut area in the vertical direction, and then find the position of the middle cut line in the vertical direction according to the left and right sidelines; make another minimum circumscribed rectangle based on the minimum circumscribed rectangles of the left and right board cores on the cut image to obtain the first circumscribed rectangles of the left and right board cores; compare the four vertex coordinates of the first circumscribed rectangle to obtain the sidelines of the cut areas on the left and right sides; move the sidelines of the cut areas on the left and right sides to the left and right sides by a fixed distance respectively to obtain the left cut line and the right cut line; Step S25, compare the minimum circumscribed rectangles of the upper and lower board cores on the cutting image to obtain the upper and lower side lines of the middle cutting area in the horizontal direction; then calculate the position of the middle cutting line in the horizontal direction according to the upper and lower side lines; make another minimum circumscribed rectangle based on the minimum circumscribed rectangles of the upper and lower board cores on the cutting image to obtain the second circumscribed rectangles of the upper and lower board cores; compare the four vertex coordinates of the second circumscribed rectangle to obtain the side lines of the cutting areas on the upper and lower sides; move the side lines of the cutting areas on the upper and lower sides to the upper and lower sides by a fixed distance respectively to obtain the upper cutting line and the lower cutting line; Step S26, perform nine-point calibration on the cutting image through a manipulator and a camera to obtain the cutting parameters of the PCB multilayer board to be identified, wherein the cutting parameters include the length and width values of the board core on the cutting image, the number of board cores on the cutting image, the thickness of the board core on the cutting image, the coordinate value of the center point of the board core on the cutting image, and the coordinate values of the vertical middle cutting line, the horizontal middle cutting line, the upper cutting line, the lower cutting line, the left cutting line and the right cutting line on the cutting image.
4. According to the machine vision-based PCB multilayer cutting method of claim 1, It is characterized in that The cutting mechanism is composed of a rolling cutter and / or a rolling cutter.
Citation Information
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