IC board warping degree and curved surface groove detection method based on three-dimensional point cloud

Abstract

The invention discloses an IC board warping degree and curved surface groove detection method based on a three-dimensional point cloud, and the method comprises the following steps: S1, collecting the point cloud data of the surface of an IC board through a three-dimensional imaging device, and carrying out the noise filtering, resampling and attitude normalization preprocessing; s2, nine key points distributed on the surface of the IC board are automatically extracted, a reference surface is generated through a curved surface fitting algorithm based on coordinates of the key points, and the height deviation value of each key point relative to the reference surface is calculated; according to the method, nine key points are selected on the surface of the IC Board, the global reference curved surface is generated by combining the curved surface fitting technology of the three-dimensional point cloud, and errors caused by local height anomaly or measurement noise are effectively avoided. Through the multi-dimensional analysis of the height difference between the central point and the edge point, the quantification of the warping degree is more comprehensive, the measurement result is more stable and reliable, and compared with a traditional single-point or linear measurement method, the method has higher precision and robustness.

Description

Technical Field

[0001] This invention relates to the field of circuit board visual inspection technology, and in particular to a method for detecting the warpage and surface grooves of IC boards based on three-dimensional point clouds. Background Technology

[0002] In integrated circuit board (IC) manufacturing processes, warpage directly affects the yield of soldering and assembly. Warpage exceeding ±0.1mm can lead to defects such as poor soldering and broken leads. Furthermore, the surface area of ​​the curved groove structure is crucial for heat dissipation efficiency and structural strength; an area deviation greater than 5% can cause localized overheating or mechanical failure. Therefore, warpage and the geometric accuracy of the curved groove structure are directly related to the reliability and performance of the product.

[0003] However, traditional contact-based equipment (such as coordinate measuring machines) requires point-by-point scanning, which is inefficient. While laser ranging is non-contact, it only supports single-point positioning measurement and cannot simultaneously acquire the warp distribution across the entire area, making it difficult to meet the cycle time requirements of high-speed production lines.

[0004] When inspecting curved grooves, the traditional two-dimensional projection method compresses the three-dimensional curved surface into a two-dimensional plane, resulting in the loss of information about the sidewall area of ​​the groove. On the other hand, the probe inspection method cannot penetrate into narrow grooves due to physical size limitations and is prone to scratching the delicate groove wall surface.

[0005] To address the aforementioned issues, we have developed a method for detecting IC board warpage and surface grooves based on 3D point clouds. Summary of the Invention

[0006] This invention discloses a method for detecting the warpage and surface grooves of an IC board based on three-dimensional point clouds, aiming to solve the technical problems in the background art.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: A method for detecting the warpage and surface grooves of an IC board based on 3D point clouds includes the following steps: S1. Acquire point cloud data of the IC board surface using a 3D imaging device, and perform noise filtering, resampling, and attitude normalization preprocessing. S2. Automatically extract 9 key points distributed on the surface of the IC board, generate a reference surface based on the coordinates of the key points using a surface fitting algorithm, and calculate the height offset value of each key point relative to the reference surface. S3. Calculate the height deviation between the 8 edge points and the center point, and use the height deviation range as the warping amplitude index and the average height deviation to determine the warping direction. S4. Extract the 3D boundary curve of the groove structure and orthogonally project it onto the reference plane. Perform binarization and morphological optimization on the projected contour. Calculate the average area of ​​multiple sub-regions using the pixel integration method and output the final result.

[0008] In a preferred embodiment, in step S2: The nine key points include four corner points, four midpoints of the sides, and one center point; The surface fitting employs multi-scale grid interpolation optimization, including iteratively eliminating outliers with abnormal normal vector distributions.

[0009] In a preferred embodiment, the rule for determining the warping direction in step S3 is as follows: Based on the comparison between the average height deviation and a preset threshold, the direction of positive warping, negative warping, or no significant warping is determined. In a preferred embodiment, in step S4: Orthogonal projection employs a normal adaptive segmentation technique to segment boundary curves based on curvature variations; The number of the multiple sub-regions is 10.

[0010] In a preferred embodiment, the pixel integration method in step S4 includes: The number of pixels in the target region of the masked image is counted, and the area is calculated based on the physical size of a single pixel. The calculation formula is as follows:

[0011] The number of pixels is set to ; Single pixel physical size set .

[0012] The IC board warpage and surface groove detection method based on three-dimensional point cloud provided by this invention has the following advantages: 1. This invention generates a global reference surface by selecting nine key points on the IC Board surface and combining them with surface fitting technology based on three-dimensional point clouds, effectively avoiding errors caused by local height anomalies or measurement noise. Through multi-dimensional analysis of the height difference between the center point and the edge points, the quantification of warpage is more comprehensive, and the measurement results are more stable and reliable, exhibiting higher accuracy and robustness compared to traditional single-point or linear measurement methods.

[0013] 2. This invention uses a method of projecting the boundary curve of a three-dimensional surface onto a reference plane, transforming a complex spatial geometry problem into a two-dimensional image processing problem. By extracting and binarizing the image edge, combined with a pixel integration algorithm, the area of ​​the closed region is calculated, avoiding problems such as unclear boundaries and insufficient accuracy in traditional projection area estimation.

[0014] 3. This invention relies on a point cloud data-driven algorithm framework, which does not depend on specific process models or templates, and has good platform versatility. It is applicable to IC board inspection under different packaging structures and manufacturing precision, and does not require manual parameter calibration, possessing a high degree of automation capability, making it suitable for deployment and promotion in complex production lines. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating a method for detecting IC board warpage and surface grooves based on three-dimensional point clouds, as proposed in this invention.

[0016] Figure 2 This diagram illustrates the extraction of nine key points in an IC board warpage and surface groove detection method based on three-dimensional point clouds proposed in this invention.

[0017] Figure 3 This image shows the front warpage measurement results of an IC board warpage and surface groove detection method based on three-dimensional point cloud proposed in this invention.

[0018] Figure 4 This is a schematic diagram of 10 sampling areas of the back surface groove in an IC board warpage and surface groove detection method based on three-dimensional point cloud proposed in this invention.

[0019] Figure 5 This is a back surface groove contour diagram of the IC board warpage and surface groove detection method based on three-dimensional point cloud proposed in this invention.

[0020] Figure 6 This is a projection image of the back surface groove of an IC board warpage and surface groove detection method based on three-dimensional point cloud proposed in this invention.

[0021] Figure 7 This image shows the average area of ​​10 regions of the back surface groove in an IC board warpage and surface groove detection method based on three-dimensional point cloud proposed in this invention. Detailed Implementation

[0022] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and marked in the accompanying drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0023] This invention discloses a method for detecting the warpage and surface grooves of an IC board based on three-dimensional point clouds.

[0024] Reference Figures 1 to 7 As shown, a method for detecting the warpage and surface grooves of an IC board based on three-dimensional point clouds includes the following steps: S1. Acquire point cloud data of the IC board surface using a 3D imaging device, and perform noise filtering, resampling, and attitude normalization preprocessing. A structured light 3D imaging system or lidar device is used to collect high-density point cloud data on the IC Board surface to obtain complete 3D geometric information. Outlier points are removed and noise points are eliminated using density-based or statistical distance-based filtering methods. Voxel grid filtering is used to uniformly sample the point cloud to ensure consistent point density in key areas. The overall pose of the IC Board is normalized so that its long side is parallel to the coordinate axis, which is conducive to standardized measurement.

[0025] S2. Automatically extract 9 key points distributed on the surface of the IC board, generate a reference surface based on the coordinates of the key points using a surface fitting algorithm, and calculate the height offset value of each key point relative to the reference surface. In step S2: The nine key points include four corner points, four midpoints of the sides, and one center point; The surface fitting employs multi-scale grid interpolation optimization, including iteratively eliminating outliers with abnormal normal vector distributions.

[0026] The four corner points are the top left, top right, bottom left, and bottom right, respectively, and the four edge midpoints are the centers of the top, bottom, left, and right boundaries, respectively. The center point is the overall centroid or geometric center. The three-dimensional coordinates (X, Y, Z) of these nine key points are processed, and a reference plane is generated using a least-squares plane fitting algorithm. This plane represents the ideal surface morphology of the plate. The height offset of the nine key points relative to this fitted plane is further calculated. ), used for subsequent warp quantification analysis.

[0027] S3. Calculate the height deviation between the 8 edge points and the center point, and use the height deviation range as the warping amplitude index and the average height deviation to determine the warping direction. The height difference between the edge point and the center point is calculated as follows: Calculate the values ​​of each of the eight edge key points (corner points and edge midpoints). value minus the center point The value is used to determine the height deviation of each edge point relative to the center, and the calculation formula is as follows:

[0028] The rule for determining the warping direction in step S3 is as follows: Based on the comparison between the average height deviation and the preset threshold, the direction of positive warping, negative warping, or no significant warping is determined.

[0029] Warp amplitude set to The range of the above 8 relative height deviations is calculated as follows:

[0030] This value represents the maximum range of warpage fluctuations on the IC Board surface and is a key indicator of warpage.

[0031] To further determine the directionality of the warping, the average relative height deviation of all edge points is calculated using the following formula:

[0032] Determine the warping trend based on this mean: like >0 indicates that the board is positively warped, meaning that the center part is bulging. like <0 indicates that the board has negative warping, that is, the center part is concave; like ≈0, which can be considered as the warping direction being insignificant. Here, the threshold is taken to be within 10μm.

[0033] S4. Extract the three-dimensional boundary curve of the groove structure and orthogonally project it onto the reference plane. Perform binarization and morphological optimization on the projected contour. Calculate the average area of ​​multiple sub-regions using the pixel integration method and output the final result. In step S4: Orthogonal projection employs a normal adaptive segmentation technique to segment boundary curves based on curvature variations; The number of the multiple sub-regions is 10. The pixel integration method in step S4 includes: The spatial curves of the groove structure edge are extracted from the 3D point cloud. Boundary tracking is completed by normal consistency detection and curvature change analysis. Then, the boundary curves are orthogonally projected onto the XY reference plane along the Z-axis (or groove surface normal) to avoid area distortion caused by spatial curvature.

[0034] The projected 2D boundary points are transformed into closed polygon regions to construct a contour map. Image processing algorithms are then used to generate a binary mask image, where: The slot area is marked as 1 (white); The background is marked as 0 (black).

[0035] The number of pixels in the target region of the masked image is counted, and the area is calculated based on the physical size of a single pixel. The calculation formula is as follows:

[0036] The number of pixels is set to ; Single pixel physical size set .

[0037] To improve the stability and resistance to local errors in area calculations for large-sized structures, the groove structure can be divided into multiple independent sub-regions (e.g., 10), and the area of ​​each region can be estimated separately. Finally, the average value is taken as the final result. .

[0038] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. The substitutions may be replacements of some structures, devices, or method steps, or they may be complete technical solutions. Equivalent substitutions or modifications made to the technical solutions and inventive concepts of the present invention should all be covered within the scope of protection of the present invention.

Claims

1. A method for detecting the warpage and surface grooves of an IC board based on three-dimensional point clouds, characterized in that, Includes the following steps: S1. Acquire point cloud data of the IC board surface using a 3D imaging device, and perform noise filtering, resampling, and attitude normalization preprocessing. S2. Automatically extract 9 key points distributed on the surface of the IC board, generate a reference surface based on the coordinates of the key points using a surface fitting algorithm, and calculate the height offset value of each key point relative to the reference surface. S3. Calculate the height deviation between the 8 edge points and the center point, and use the height deviation range as the warping amplitude index and the average height deviation to determine the warping direction. S4. Extract the 3D boundary curve of the groove structure and orthogonally project it onto the reference plane. Perform binarization and morphological optimization on the projected contour. Calculate the average area of ​​multiple sub-regions using the pixel integration method and output the final result.

2. The method for detecting IC board warpage and surface grooves based on three-dimensional point clouds according to claim 1, characterized in that, In step S2: The nine key points include four corner points, four midpoints of the sides, and one center point; The surface fitting employs multi-scale grid interpolation optimization, including iteratively eliminating outliers with abnormal normal vector distributions.

3. The method for detecting IC board warpage and surface grooves based on three-dimensional point clouds according to claim 1, characterized in that, The rule for determining the warping direction in step S3 is as follows: Based on the comparison between the average height deviation and the preset threshold, the direction of positive warping, negative warping, or no significant warping is determined.

4. The method for detecting IC board warpage and surface grooves based on three-dimensional point clouds according to claim 1, characterized in that, In step S4: Orthogonal projection employs a normal adaptive segmentation technique to segment boundary curves based on curvature variations; The number of the multiple sub-regions is 10.

5. The method for detecting IC board warpage and surface grooves based on three-dimensional point clouds according to claim 1, characterized in that, The pixel integration method in step S4 includes: The number of pixels in the target region of the masked image is counted, and the area is calculated based on the physical size of a single pixel. The calculation formula is as follows:

6. Among them, Pixel count set to ; Single pixel physical size set .

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