A method and system for assisting positioning of flip chip mounting of a PCB circuit board
By analyzing the connected components of the image features after the PCB circuit board is flipped, calculating the boundary sparsity and the neighboring space expansion ratio, and constructing the positioning vector, the problem of insufficient positioning accuracy after the PCB circuit board is flipped is solved, and high-precision electronic component mounting is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHENZHEN PENGCHENGTONG ELECTRONIC CO LTD
- Filing Date
- 2026-01-13
- Publication Date
- 2026-05-15
AI Technical Summary
Traditional methods reduce the positioning accuracy of electronic components after the PCB circuit board is flipped, resulting in insufficient mounting accuracy, especially with the decrease in edge extraction accuracy after the miniaturization of components.
By acquiring images of a flipped PCB circuit board, extracting the largest feature connected region, calculating the boundary sparsity and the adjacent space expansion ratio, constructing a positioning vector, and matching it with a standard circuit diagram, the mounting rotation angle is determined, thus achieving high-precision positioning of electronic components.
It improves the mounting accuracy of electronic components after PCB circuit board flipping, reduces positioning errors, and enhances the automation level and stability of the mounting process.
Smart Images
Figure CN121505039B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of PCB board mounting position positioning technology, specifically to an auxiliary positioning method and system for PCB board flip mounting. Background Technology
[0002] A PCB (Printed Circuit Board) is a key component connecting electronic components to electrical systems. During PCB manufacturing, electronic components are soldered onto the PCB. As the functionality of electronic devices increases, the requirements for PCBs become more stringent, leading to the development of double-sided and multi-sided boards. Therefore, when soldering electronic components onto a PCB, it is necessary to flip the PCB to mount the components. However, after flipping the PCB, the positions of each component must be precisely located to ensure accurate mounting and reduce the defect rate.
[0003] Traditional methods for locating component placement on PCBs typically involve extracting the edges of the placement location from a PCB image and matching them with the placement location in a standard image. However, as PCBs become increasingly sophisticated and electronic components become smaller, the accuracy of edge extraction decreases, leading to reduced placement accuracy after the PCB is flipped. Summary of the Invention
[0004] To address the aforementioned technical problems, this application provides an auxiliary positioning method and system for PCB circuit board flip-mounting, the specific technical solution of which is as follows:
[0005] In a first aspect, one embodiment of this application provides an auxiliary positioning method for flip-mounting PCB circuit boards, the method comprising the following steps:
[0006] The PCB image is captured after the PCB is flipped and transported to the placement machine and preprocessed to obtain the placement positioning image and its placement positioning edge image.
[0007] Obtain the largest feature connected region in the mounting positioning edge image; calculate the boundary sparsity of each contour point in the feature connected region by using the distance of each contour point from its minimum bounding rectangle boundary and endpoints, so as to extract the segmentation points in the feature connected region.
[0008] The tortuosity ratio of each segmentation point is determined by the ratio of the contour distance between two adjacent segmentation points to the shortest distance; the neighborhood expansion ratio of each segmentation point is determined by the contour distance between two adjacent segmentation points and their respective distances from the geometric center of the minimum circumscribed rectangle.
[0009] The horizontal and vertical coordinates of the segmentation points, the tortuosity ratio, and the adjacent space expansion ratio are used to form a four-dimensional positioning vector. Based on the positioning vector, the two optimal segmentation points are matched from the mounting positioning image and the standard circuit diagram. The mounting rotation angle is determined according to the angle between the direction vector formed by the two segmentation points and the geometric center point of the smallest circumscribed rectangle of the connected domain in the diagram, and combined with the mounting position to achieve auxiliary positioning of electronic components on the PCB board.
[0010] Preferably, the formula for calculating the boundary alienation is: In the formula, This represents the boundary sparsity of the i-th contour point in the feature connected domain. This represents the circumcircle distance of the i-th contour point in the feature connected domain. , Let $\mathbf{i}$ and $\mathbf{i}$ represent the maximum distance and minimum distance from the $i$-th contour point in the characteristic connected region to the four endpoints of its minimum bounding rectangle, respectively. This represents a preset constant parameter; where the circumscribed distance of the i-th contour point in the feature connected domain is the minimum distance from the i-th contour point to the minimum circumscribed rectangle boundary of the feature connected domain.
[0011] Preferably, the method for extracting the segmentation points includes:
[0012] Obtain the segmentation threshold of the boundary alienation of all contour points, mark contour points with boundary alienation greater than or equal to the segmentation threshold as 1, and mark contour points with boundary alienation less than the segmentation threshold as 0;
[0013] Arrange the label value of the contour point corresponding to the maximum boundary separation degree first, and arrange the label values of the remaining contour points in a clockwise direction to obtain the label sequence;
[0014] Perform first-order differencing on the labeled sequence and calculate the absolute value of the difference to obtain the labeled boundary sequence;
[0015] Extract the contour points with a value of 1 from the marker boundary sequence as the segmentation points.
[0016] Preferably, the formula for calculating the adjacent space expansion ratio is: In the formula, This represents the neighborhood expansion ratio of the j-th segment point. This represents the contour distance between the j-th segment and the next segment. , Let represent the center distances of the j-th and (j+1)-th dividing points, respectively; where the center distance of a dividing point is the distance between the dividing point and the geometric center of the smallest circumscribed rectangle.
[0017] Preferably, the contour distance is the sum of the Euclidean distances between all adjacent contour points between the preceding and following two adjacent segmentation points; wherein, the division of the preceding and following segmentation points between the two segmentation points is carried out according to the number in the marked boundary sequence from smallest to largest.
[0018] Preferably, the horizontal coordinates, vertical coordinates, tortuosity ratios, and adjacent space expansion ratios of the segmentation points included in the positioning vector need to be normalized to their maximum values before forming the positioning vector.
[0019] Preferably, the method for matching the two best segmentation points is as follows: calculate the similarity between the positioning vector of each segmentation point in the largest connected region in the standard circuit diagram of the PCB circuit board and the positioning vector of each segmentation point in the feature connected region in the mounting positioning image, and extract the segmentation point corresponding to the maximum similarity in the two images as the two best segmentation points.
[0020] Preferably, when performing auxiliary positioning for PCB board mounting, the mounting rotation angle is used as the rotation angle for the robotic arm to grasp the corresponding electronic components.
[0021] Preferably, when mounting the PCB circuit board, the center position of the electronic component mounting location is the geometric center coordinate of the corresponding connected region in the mounting positioning image.
[0022] Secondly, another embodiment of this application also provides an auxiliary positioning system for PCB circuit board flip-mounting, the system comprising:
[0023] Circuit board flipping module: The PCB circuit board is flipped 180 degrees by a transfer flipping machine to facilitate the subsequent mounting of electronic components on both sides of the PCB circuit board;
[0024] Circuit board transport module: The flipped PCB circuit board is transported to the pick and place machine via a conveyor belt for subsequent placement of electronic components;
[0025] Data acquisition module: used to capture PCB images after the PCB circuit board has been flipped and transported to the mounting machine;
[0026] Positioning module: By executing the auxiliary positioning method for PCB circuit board flipping and mounting described above, the mounting position and mounting rotation angle of electronic components are calculated to achieve auxiliary positioning of the mounting position after the PCB circuit board is flipped.
[0027] This application has at least the following beneficial effects:
[0028] 1. This application analyzes the spatial distribution of segmentation points in the largest connected region of a PCB circuit board image to obtain the prominence of segmentation points in the local distribution area, effectively characterizing the geometric features and spatial position differences of segmentation points in the local area.
[0029] 2. This application introduces boundary sparsity to screen segmentation points and analyzes multi-dimensional features such as the tortuosity ratio and the expansion ratio of the adjacent space of the segmentation points to construct positioning vectors and perform template matching with standard circuit diagrams. This can effectively improve the matching accuracy between the flipped PCB circuit board image and the standard circuit diagram, effectively overcome the reduced accuracy of traditional edge recognition in the positioning of small components, and enhance the accuracy of electronic component placement.
[0030] 3. This application calculates the angle and position by using the spatial distribution characteristics of the dividing points, thereby achieving high-precision identification of the mounting position and mounting rotation angle of electronic components, reducing positioning errors caused by image blurring or small components, and improving the automation level and stability of the mounting process. Attached Figure Description
[0031] To more clearly illustrate the technical solutions and advantages 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.
[0032] Figure 1 This is a flowchart illustrating an auxiliary positioning method for flip-mounting a PCB circuit board, as provided in one embodiment of this application. Detailed Implementation
[0033] Example 1
[0034] One embodiment of this application provides an auxiliary positioning method for PCB circuit board flip-mounting, see details below. Figure 1 The method includes the following steps:
[0035] Step 1: Acquire images of the PCB after it has been flipped and transported to the placement machine, and perform preprocessing to obtain placement positioning images and placement positioning edge images.
[0036] After the PCB circuit board is flipped by the transfer flipping machine, it is transported to the placement machine by the transfer machine. The placement machine is equipped with a monitoring camera at the top to identify the image position of the PCB circuit board, so as to assist in the positioning of electronic components.
[0037] Therefore, images of the flipped PCB circuit board are acquired using a monitoring camera, and the images are converted into grayscale images using a weighted average method. To prevent noise during acquisition from affecting the positioning, NLM filtering is used to denoise the grayscale image in this implementation, and the denoised image is recorded as the mounting positioning image. The calculation of the weighted average method and NLM filtering are well-known techniques, and the specific calculation steps will not be described in detail here.
[0038] For mounting positioning images, since PCB circuit boards generally use dark colors as the background color, there is a clear separation between the background color of the PCB circuit board and the color of the position where electronic components need to be mounted, and there is a clear dividing line between the two.
[0039] Therefore, the mounting positioning image is used as the input to the Canny edge detection algorithm, and the output is the edge image of the mounting positioning image, denoted as the mounting edge image. Note: This image is a binarized image.
[0040] Furthermore, since the image of the flipped PCB circuit board may be affected by the lighting, the edges of a certain mounting area may be blurred, resulting in incomplete mounting areas in the detected mounting edge image. Therefore, a morphological operation of dilation followed by erosion is performed on the mounting edge image. In this embodiment, the size of the morphological kernel is set to 3×3, and the processed image is recorded as the mounting positioning edge image.
[0041] The Canny edge detection algorithm and morphological calculations are well-known techniques, and the specific calculation steps will not be described in detail here.
[0042] Step 2: Obtain the largest feature connected region in the mounting positioning edge image; calculate the boundary sparsity of each contour point in the feature connected region by using the distance of each contour point from its minimum bounding rectangle boundary and endpoints, so as to extract the segmentation points in the feature connected region.
[0043] Different electronic components are positioned differently, and to prevent interference, they are mounted at certain distances. Therefore, the edges of different component mounting positions are not connected. Thus, each connected component in the mounting positioning edge image represents the mounting position of one electronic component. To obtain the mounting position of each component, the mounting positioning edge image is used as input to a two-pass scanning method to obtain all connected components in the image, which represent the position of each electronic component. The calculation of the two-pass scanning method is a well-known technique, and the specific calculation steps will not be elaborated here.
[0044] Furthermore, the connected component with the largest area in the mounting positioning edge image is obtained, which is used to characterize the feature connected component of the positioning.
[0045] Next, in order to characterize the region where the electronic components are located, the minimum bounding rectangle of the characteristic connected region is obtained. The method for obtaining the minimum bounding rectangle is a well-known technique and will not be described in detail here.
[0046] Furthermore, by using the formula for the distance from a point to a line, the distance from each contour point in the feature connected region to each boundary in its smallest bounding rectangle is obtained. The smallest distance is denoted as the bounding distance of the contour point, which is used to characterize the feature distribution of the contour points.
[0047] Since the mounting areas for electronic components are typically circular, rectangular, or rounded rectangular, a higher degree of fit between the mounting area and the external matrix indicates a higher degree of parallelism between the PCB board's position on the mounting machine and the camera boundary after flipping. This also means that the rotation angle of the electronic components during mounting is smaller.
[0048] Therefore, the boundary sparsity of each contour point in the feature connected domain is calculated.
[0049] 〖Bhv〗_i=d_i / (〖dl〗_(i,max)-〖dl〗_(i,min)+ )
[0050] In the formula, 〖Bhv〗_i represents the boundary sparsity of the i-th contour point in the feature connected domain, d_i represents the circumscribed distance of the i-th contour point in the feature connected domain, and 〖dl〗_(i,max) and 〖dl〗_(i,min) represent the maximum and minimum distances from the i-th contour point in the feature connected domain to the four endpoints of the minimum circumscribed rectangle, respectively. This represents a preset constant parameter to prevent the denominator from being 0. The default value range is [0.001, 1], and in this implementation, the value is 0.1.
[0051] Calculation logic: 〖Bhv〗_i characterizes the fit between the contour point and the minimum bounding rectangle by measuring the distances from the contour point to the boundaries and endpoints of the minimum bounding rectangle. Specifically, the minimum distance from the contour point to each boundary of the minimum bounding rectangle characterizes the degree of non-overlap between the contour point and the minimum bounding rectangle. The difference between the maximum and minimum distances from the contour point to each endpoint characterizes the fit between the contour point and the minimum bounding rectangle; therefore, the ratio of these two parameters characterizes the boundary separation of the contour point.
[0052] The greater the distance from the contour point to the boundary of the minimum bounding rectangle, the more prominent the feature of the contour point is within the minimum bounding rectangle. As a result, the circumscribed distance of the contour point is greater, and the difference between the maximum distance and the minimum distance from the contour point to the four endpoints of the minimum bounding rectangle is smaller, thus making the boundary separation of the contour point greater.
[0053] Adjacent contour points are relatively close in distance, thus exhibiting similar characteristics. Furthermore, the closer the points are to the boundary of the smallest bounding rectangle, the more similar their boundary separation. When segmenting a connected feature region, the segmentation points should be chosen at locations where the boundary separation of the contour points differs to effectively segment the contours of the connected feature region.
[0054] Therefore, the boundary sparsity of all contour points in the feature connected region is used as the input of the Otsu's method, and the output is the segmentation threshold for all contour points. Contour points with a boundary sparsity greater than or equal to the segmentation threshold are marked as 1, and contour points with a boundary sparsity less than the segmentation threshold are marked as 0.
[0055] The label value of the contour point corresponding to the maximum boundary alienation is placed first, and the label values of the remaining contour points are arranged clockwise to obtain a label sequence, which is used to characterize the feature distribution of contour points in the feature connected region. The calculation of the maximum class variance method is a well-known technique, and the specific calculation steps will not be described here.
[0056] Furthermore, the labeled sequence is used as input to the first-order difference algorithm, and the output is a labeled difference sequence of the labeled sequence. Note: The difference value of the first element is obtained by subtracting the last element in the labeled sequence from the first element. The absolute values of all elements in the labeled difference sequence are then calculated to obtain the labeled boundary sequence, which is used to characterize different boundary values of the feature connected components. An element that is 1 in the labeled decomposition sequence indicates that the element is the optimal boundary line of the contour.
[0057] Accordingly, the contour points corresponding to all values of 1 in the marked boundary sequence are obtained and recorded as the split points. Note: If the boundary sparsity of all contour points is 0, it means that the feature connected region and the minimum bounding rectangle are in a state of overlap. Therefore, the four endpoints of the minimum bounding rectangle are used as split points.
[0058] Step 3: Determine the tortuosity ratio of each segmentation point by using the ratio of the contour distance between two adjacent segmentation points to the shortest distance; determine the neighborhood expansion ratio of each segmentation point by using the contour distance between two adjacent segmentation points and their respective distances from the geometric center of the smallest circumscribed rectangle.
[0059] The length of the connected component determines the size of the mounting area for electronic components; the larger the value, the larger the mounting area. The distance between each dividing point is the distance between feature segments of the connected component; the closer the distance is to the length of the connected component, the closer the segment's outline is to a straight line.
[0060] Therefore, the contour distance between two segmentation points is calculated by summing the Euclidean distances between all adjacent contour points between the current segmentation point and the next segmentation point, which is used to characterize the contour length between the current segmentation points.
[0061] It is worth noting that the method for dividing the two split points into the preceding and following split points in the entire paper is to divide them by marking the corresponding numbers in the boundary sequence from small to large.
[0062] Next, the shortest distance between the two segmentation points is calculated and denoted as the segmentation distance of the current segmentation point, which is used to characterize the local flatness of the feature connected region. Note: The contour distance of the last segmentation point is calculated with respect to the first segmentation point.
[0063] Therefore, the zigzag prominence ratio of each segmentation point within the characteristic connected domain is calculated to characterize the prominence of the curve between adjacent segmentation points.
[0064] 〖rt〗_j=〖SL〗_j / 〖SD〗_j
[0065] In the formula, 〖rt〗_j represents the tortuosity ratio of the j-th segmentation point, and 〖SL〗_j and 〖SD〗_j represent the contour distance and segmentation phase distance between the j-th segmentation point and the next segmentation point, respectively.
[0066] Calculation logic: The `rt` function uses two features—the contour length and the shortest distance between segmentation points—to characterize the relative tortuosity of the neighborhood curves of each segmentation point. Specifically, the contour distance of a segmentation point represents the length of its connection to the next segmentation point, indicating the change in length between segmentation points. The segmentation distance represents the shortest distance between segmentation points. The ratio of these two features effectively characterizes the shape of the contours connecting the segmentation points.
[0067] The closer the contour shape between the dividing point and the next dividing point is to a straight line, the closer the contour distance between the dividing point and the next dividing point is to the dividing distance, the smaller the ratio of the two parameters, the smaller the tortuosity of the dividing point, and the smaller the prominence of the contour.
[0068] The distance from different split points to the geometric center of the minimum bounding rectangle can characterize the spatial distribution of the split points within the characteristic connected domain. Furthermore, the differences in the spatial distribution of adjacent split points can characterize the salience of the neighborhood distribution features of the split points.
[0069] Therefore, the distance between each dividing point and the geometric center of the minimum bounding rectangle is calculated and denoted as the center distance of each dividing point, which is used to characterize the spatial distribution characteristics of the dividing points in the minimum bounding rectangle.
[0070] Therefore, the neighborhood expansion ratio of each segmentation point within the characteristic connected domain is calculated to characterize the degree of non-flattening between the current segmentation point and the next segmentation point.
[0071] 〖tk〗_j=(〖SL〗_j+〖Ds〗_(j+1)) / 〖Ds〗_j
[0072] In the formula, 〖tk〗_j represents the neighborhood expansion ratio of the j-th segmentation point, and 〖Ds〗_j and 〖Ds〗_(j+1) represent the center distances of the j-th and j+1-th segmentation points, respectively.
[0073] Calculation logic: 〖tk〗_j represents the non-flattening characteristics of the neighborhood space of a segmentation point by using the contour distance between the segmentation point and the next segmentation point, as well as the center distance. Specifically, the contour distance between two segmentation points represents the degree of separation between them, the center distance represents the spatial distribution distance between the segmentation point and the center point, and the ratio of the sum of these two distances to the center distance represents the degree of flattening between the three neighboring segmentation points and the center point.
[0074] The higher the degree of flattening between two dividing points and the center point, the more it indicates that the dividing points and their neighboring dividing points have the same spatial distribution characteristics, making the center distance between the two dividing points similar and the outline distance between the dividing points small. This results in a smaller value for the neighboring spatial expansion ratio of the dividing points and a smaller protruding feature of the dividing points.
[0075] Step 4: Construct a four-dimensional positioning vector from the x-coordinate, y-coordinate, tortuosity ratio, and adjacent space expansion ratio of the segmentation point; based on the positioning vector, match the two optimal segmentation points from the mounting positioning image and the standard circuit diagram; determine the mounting rotation angle based on the angle between the direction vector formed by the two segmentation points and the geometric center point of the smallest circumscribed rectangle of the connected domain in their respective diagrams, and combine this with the mounting position to achieve auxiliary positioning of electronic components on the PCB board.
[0076] Furthermore, the x-coordinate, y-coordinate, tortuosity ratio, and adjacent space expansion ratio of all segmentation points are normalized to their maximum values to eliminate the dimensions between data. The normalized values are then used to form a four-dimensional vector for each segmentation point, which is denoted as the positioning vector of each segmentation point.
[0077] Next, similarly, by following the steps above, the location vector of each dividing point in the largest connected domain in the standard circuit diagram of the PCB circuit board is calculated.
[0078] Using the localization vectors of the segmentation points, the optimal two segmentation points are matched between the mounting positioning image and the standard circuit diagram. Specifically, the similarity between the localization vector of each segmentation point in the largest connected region in the standard circuit diagram of the PCB board and the localization vector of each segmentation point in the characteristic connected region in the mounting positioning image is calculated. The segmentation points corresponding to the maximum similarity in the two images are extracted as the optimal two segmentation points.
[0079] Similarity includes, but is not limited to, cosine similarity, the reciprocal of DTW distance, and the reciprocal of Euclidean distance. In this implementation, cosine similarity is used for calculation. The calculation of cosine similarity is a well-known technique, and the specific calculation steps will not be described here.
[0080] The geometric center point of the smallest bounding rectangle and the position of the extracted segmentation point are combined to form a direction vector, and the angle between the direction vector of the circuit diagram and the mounting positioning image is calculated as the mounting rotation angle.
[0081] The geometric center coordinates of each connected region in the mounting positioning image are used as the center position of the corresponding electronic component mounting location, and the mounting rotation angle is used as the rotation angle of the robot arm grasping the electronic component. The calculation of the angle between vectors is a well-known technique, and the specific calculation steps will not be elaborated here.
[0082] Thus, an auxiliary positioning method for flip-mounting PCB circuit boards has been realized.
[0083] Example 2
[0084] Another embodiment of this application provides an auxiliary positioning system for PCB circuit board flip-mounting, the system comprising:
[0085] Circuit board flipping module: The PCB circuit board is flipped 180 degrees by a transfer flipping machine to facilitate the subsequent mounting of electronic components on both sides of the PCB circuit board.
[0086] Circuit board transport module: The flipped PCB circuit board is transported to the pick-and-place machine via a conveyor belt for subsequent placement of electronic components.
[0087] Data acquisition module: Used to capture PCB images after the PCB circuit board has been flipped and transported to the mounting machine.
[0088] Positioning module: By executing the auxiliary positioning method for PCB circuit board flipping and mounting described above, the mounting position and mounting rotation angle of electronic components are calculated to achieve auxiliary positioning of the mounting position after the PCB circuit board is flipped.
[0089] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not invented in this application.
[0090] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope.
Claims
1. An auxiliary positioning method for flip-mounting PCB circuit boards, characterized in that, The method includes the following steps: The PCB image is captured after the PCB is flipped and transported to the placement machine and preprocessed to obtain the placement positioning image and its placement positioning edge image. Obtain the largest feature connected region in the mounting positioning edge image; calculate the boundary sparsity of each contour point in the feature connected region by using the distance of each contour point from its minimum bounding rectangle boundary and endpoints, so as to extract the segmentation points in the feature connected region. The tortuosity ratio of each segmentation point is determined by the ratio of the contour distance between two adjacent segmentation points to the shortest distance; the neighborhood expansion ratio of each segmentation point is determined by the contour distance between two adjacent segmentation points and their respective distances from the geometric center of the minimum circumscribed rectangle. The horizontal and vertical coordinates of the segmentation points, the tortuosity ratio, and the adjacent space expansion ratio are used to form a four-dimensional positioning vector. Based on the positioning vector, the two optimal segmentation points are matched from the mounting positioning image and the standard circuit diagram. The mounting rotation angle is determined according to the angle between the direction vector formed by the two segmentation points and the geometric center point of the smallest circumscribed rectangle of the connected domain in the diagram, and combined with the mounting position to achieve auxiliary positioning of electronic components on the PCB board.
2. The auxiliary positioning method for PCB circuit board flipping and mounting as described in claim 1, characterized in that, The formula for calculating the boundary alienation is: In the formula, This represents the boundary sparsity of the i-th contour point in the feature connected domain. This represents the circumcircle distance of the i-th contour point in the feature connected domain. , Let $\mathbf{i}$ and $\mathbf{i}$ represent the maximum distance and minimum distance from the $i$-th contour point in the characteristic connected region to the four endpoints of its minimum bounding rectangle, respectively. This represents a preset constant parameter; where the circumscribed distance of the i-th contour point in the feature connected domain is the minimum distance from the i-th contour point to the minimum circumscribed rectangle boundary of the feature connected domain.
3. The auxiliary positioning method for PCB circuit board flipping and mounting as described in claim 1, characterized in that, The method for extracting the segmentation points includes: Obtain the segmentation threshold of the boundary alienation of all contour points, mark contour points with boundary alienation greater than or equal to the segmentation threshold as 1, and mark contour points with boundary alienation less than the segmentation threshold as 0; Arrange the label value of the contour point corresponding to the maximum boundary separation degree first, and arrange the label values of the remaining contour points in a clockwise direction to obtain the label sequence; Perform first-order differencing on the labeled sequence and calculate the absolute value of the difference to obtain the labeled boundary sequence; Extract the contour points with a value of 1 from the marker boundary sequence as the segmentation points.
4. The auxiliary positioning method for PCB circuit board flipping and mounting as described in claim 1, characterized in that, The formula for calculating the adjacent space expansion ratio is as follows: In the formula, This represents the neighborhood expansion ratio of the j-th segment point. This represents the contour distance between the j-th segment and the next segment. , Let represent the center distances of the j-th and (j+1)-th dividing points, respectively; where the center distance of a dividing point is the distance between the dividing point and the geometric center of the smallest circumscribed rectangle.
5. The auxiliary positioning method for PCB circuit board flipping and mounting as described in claim 3 or 4, characterized in that, The contour distance is the sum of the Euclidean distances between all adjacent contour points between the preceding and following segmentation points in two adjacent segmentation points; wherein, the division of the preceding and following segmentation points between two segmentation points is based on the number in the marked boundary sequence from smallest to largest.
6. The auxiliary positioning method for PCB circuit board flip-mounting as described in claim 1, characterized in that, The x-coordinate, y-coordinate, tortuosity ratio, and adjacent space expansion ratio of the segmentation points included in the positioning vector need to be normalized to their maximum values before forming the positioning vector.
7. The auxiliary positioning method for PCB circuit board flipping and mounting as described in claim 1, characterized in that, The method for matching the two best segmentation points is as follows: calculate the similarity between the positioning vector of each segmentation point in the largest connected region in the standard circuit diagram of the PCB circuit board and the positioning vector of each segmentation point in the feature connected region in the mounting positioning image, and extract the segmentation points corresponding to the maximum similarity in the two images as the two best segmentation points.
8. The auxiliary positioning method for PCB circuit board flip-mounting as described in claim 1, characterized in that, When implementing auxiliary positioning for PCB board mounting, the mounting rotation angle is used as the rotation angle for the robot arm to grasp the corresponding electronic components.
9. The auxiliary positioning method for PCB circuit board flip-mounting as described in claim 8, characterized in that, When mounting electronic components on a PCB, the center position of the mounting location is the geometric center coordinate of the corresponding connected region in the mounting positioning image.
10. An auxiliary positioning system for flipping and mounting PCB circuit boards, characterized in that, The system includes: Circuit board flipping module: The PCB circuit board is flipped 180 degrees by a transfer flipping machine to facilitate the subsequent mounting of electronic components on both sides of the PCB circuit board; Circuit board transport module: The flipped PCB circuit board is transported to the pick and place machine via a conveyor belt for subsequent placement of electronic components; Data acquisition module: used to capture PCB images after the PCB circuit board has been flipped and transported to the mounting machine; Positioning module: By executing the auxiliary positioning method for PCB circuit board flipping and mounting as described in any one of claims 1-9, the mounting position and mounting rotation angle of electronic components are calculated to achieve auxiliary positioning of the mounting position after the PCB circuit board is flipped.