Special-shaped polygon board splicing method, device, equipment and medium

Abstract

The invention discloses a special-shaped polygon board splicing method, device and equipment and a medium, and the special-shaped polygon board splicing method comprises the steps: obtaining the geometric features of all special-shaped polygons to be spliced, and unifying the geometric features of all the special-shaped polygons to the same coordinate reference to obtain geometric feature coordinate information; the Minkowski sum of any two special-shaped polygons in all the special-shaped polygons at different rotation angles is calculated based on the geometric feature coordinate information, all possible splicing position schemes are obtained, the optimal splicing position scheme of any two special-shaped polygons is selected based on a preset evaluation index, and splicing blocks are generated; performing layout on the splicing blocks on the substrate by using a recursive space segmentation method, and adjusting the positions of the splicing blocks by using an interval approximation algorithm after layout, so that a gap between two adjacent splicing blocks approaches to a preset minimum value; and when the residual space of the substrate cannot accommodate the smallest splicing block, outputting a plate splicing scheme on the current substrate.

Description

Technical Field

[0001] This invention relates to the field of panel technology, and in particular to a method, apparatus, equipment and medium for irregular polygonal panel splicing. Background Technology

[0002] In the PCB (Printed Circuit Board) manufacturing process, the panelization process is a core element affecting material utilization, production costs, and production efficiency. Traditional panelization methods rely on manual layout or simple algorithms, resulting in low space utilization and poor processing efficiency. Especially for irregularly shaped polygons (PCB components), traditional methods cannot accurately calculate the optimal panelization positions, making it difficult to achieve tight panelization. This leads to numerous gaps in the substrate, low space utilization, and a large amount of waste. Furthermore, traditional methods typically use exhaustive methods to calculate all point-pair and edge-pair combinations, resulting in high computational complexity and difficulty in quickly generating feasible panelization solutions. Consequently, this slows down the overall PCB manufacturing process and fails to meet the real-time requirements of large-scale production. Summary of the Invention

[0003] This invention provides a method, apparatus, equipment, and medium for splicing irregular polygons, in order to solve the technical problems that existing PCB splicing methods cannot adapt to the splicing of irregular polygons, resulting in low space utilization, poor processing efficiency, and inability to meet the real-time requirements of large-scale production.

[0004] To address the aforementioned technical problems, in a first aspect, the present invention provides a method for creating irregularly shaped polygonal panels, comprising: Obtain the geometric features of each irregular polygon to be spliced, and unify the geometric features of each irregular polygon to the same coordinate reference to obtain the geometric feature coordinate information; Based on the geometric feature coordinate information, the Minkowski sum of any two irregular polygons in all irregular polygons at different rotation angles is calculated to obtain all possible splicing position schemes. Based on the preset evaluation index, the optimal splicing position scheme of any two irregular polygons is selected to generate a splicing block. The assembly blocks are arranged on the substrate using a recursive spatial partitioning method. After arrangement, the position of the assembly blocks is adjusted using an interval approximation algorithm so that the gap between two adjacent assembly blocks approaches a preset minimum value. When the remaining space on the substrate cannot accommodate the smallest panel, output the panel layout on the current substrate.

[0005] Secondly, an irregular polygonal panel device is provided, comprising: The feature acquisition module is used to acquire the geometric features of each irregular polygon to be spliced, and to unify the geometric features of each irregular polygon to the same coordinate reference to obtain the geometric feature coordinate information. The splicing calculation module is used to calculate the Minkowski sum of any two irregular polygons at different rotation angles based on the geometric feature coordinate information, obtain all possible splicing position schemes, and select the optimal splicing position scheme of any two irregular polygons based on preset evaluation indicators to generate a splicing block. The splicing optimization module is used to arrange the splicing blocks on the substrate using a recursive spatial partitioning method. After the arrangement, the position of the splicing blocks is adjusted using an interval approximation algorithm so that the gap between two adjacent splicing blocks approaches a preset minimum value. The output module is used to output the current panelization scheme on the substrate when the remaining space on the substrate cannot accommodate the smallest panel.

[0006] Thirdly, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the irregular polygon mosaic method.

[0007] Fourthly, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the irregular polygon mosaic method.

[0008] In the above-mentioned method for splicing irregular polygons, the geometric features of the obtained irregular polygons to be spliced ​​are unified to the same coordinate reference. Based on the geometric feature coordinate information, the Minkowski sum of any two irregular polygons at different rotation angles is calculated to obtain all possible splicing position schemes. The optimal splicing position scheme for any two irregular polygons is selected based on a preset evaluation index, generating multiple splicing blocks. The splicing blocks are then arranged on a substrate using a recursive spatial partitioning method. After arrangement, the positions of the splicing blocks are adjusted using an interval approximation algorithm to make the gap between adjacent splicing blocks approach a preset minimum value. Therefore, this invention... By using Minkowski algorithm and preset evaluation indicators, the optimal splicing position scheme for the local part of the irregular polygon is selected. Then, based on the recursive spatial segmentation method and the interval approximation algorithm, the optimal splicing position of the local part is globally optimized. That is, the splicing blocks are arranged on the substrate by recursive spatial segmentation method, and the position of the splicing blocks is adjusted by interval approximation algorithm. This can maximize space utilization, reduce material waste, computational delay and redundancy caused by unreasonable splicing, and improve material utilization and processing efficiency. Moreover, the interval approximation algorithm can filter out most invalid calculation points by step size design, reducing computational complexity and meeting the real-time requirements of large-scale production. Attached Figure Description

[0009] Figure 1 This is a flowchart illustrating an embodiment of the irregular polygon panel method of the present invention.

[0010] Figure 2 yes Figure 1 The diagram shows the specific process flow of S20 in the irregular polygon panel method.

[0011] Figure 3 yes Figure 1 The diagram shows the specific process flow of S30 in the irregular polygon panel method.

[0012] Figure 4 yes Figure 3 The diagram shows the specific process flow of S31 in the irregular polygon panel method.

[0013] Figure 5 yes Figure 3 The diagram shows the specific process flow of S32 in the irregular polygon panel method.

[0014] Figure 6 yes Figure 5 The diagram shows the specific process flow of S322 in the irregular polygon panel method.

[0015] Figure 7 The irregular polygon panel method provided by this invention is a panelization scheme for outputting irregular polygon panels.

[0016] Figure 8 It uses existing panelization methods for Figure 7 A panelization scheme for outputting irregularly shaped polygons.

[0017] Figure 9 The irregular polygon panel method provided by this invention is a panelization scheme output for another irregular polygon panel.

[0018] Figure 10 It uses existing panelization methods for Figure 9 A panelization scheme for outputting irregularly shaped polygons.

[0019] Figure 11 This is a schematic diagram of the structure of the irregular polygonal panel device provided in an embodiment of the present invention.

[0020] Figure 12 This is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0021] To better understand the technical content of this invention, the technical solution of this invention will be further introduced and explained below with reference to the schematic diagram, but it is not limited thereto.

[0022] This invention's irregular polygon panelization method is applicable to industrial scenarios requiring efficient graphic layout, such as PCB manufacturing, sheet metal processing (irregular metal parts layout), laser cutting (irregular sheet metal cutting and layout), and furniture manufacturing (irregular wood panel splicing and layout). It utilizes a single-panel stacking compression method based on Minkowski algorithm combined with recursive spatial segmentation and interval approximation algorithms to achieve substrate layout and adjustment. This method quickly completes the optimal splicing and spatial compression of irregular polygons, reducing material waste and computational delays caused by unreasonable panelization, improving material utilization and processing efficiency, reducing computational complexity, supporting multiple splicing modes, and suitable for production needs of different scales.

[0023] Reference Figure 1 , Figure 1 This is a flowchart illustrating a specific embodiment of the irregular polygon mosaic method of the present invention. In the embodiment shown in the figure, the irregular polygon mosaic method includes the following steps S10-S40: S10. Obtain the geometric features of each irregular polygon to be spliced, and unify the geometric features of each irregular polygon to the same coordinate reference to obtain the geometric feature coordinate information.

[0024] In this invention, irregular polygons are polygons with irregular shapes (not rectangular, circular, or other standard shapes), and their vertex convexity and side length distribution differ. Panelization refers to the process of arranging multiple components (including irregular polygons) on the same substrate.

[0025] In this step, the convexity of the vertices of each irregular polygon to be spliced ​​is detected to obtain the concave and convex points. Specifically, based on the vertex sequence direction, the concave and convex points are calculated using the vector cross product method, and the corresponding points are marked and recorded in the point data object. Furthermore, the bounding box algorithm is used to identify the longest side of the irregular polygon to obtain the geometric features containing the concave and convex points and the longest side. All irregular polygons are then translated to the lower left corner of the same coordinate system (with the smallest x and y coordinates of the polygon as the origin) to ensure that the splicing calculation benchmark of all irregular polygons is consistent, so as to avoid splicing errors caused by coordinate offset.

[0026] Furthermore, in this embodiment, the geometric feature coordinate information can also be standardized in terms of data format, that is, the attribute information such as vertex coordinates, side lengths, and areas of the irregular polygons in the geometric feature coordinate information can be generated into standardized data files.

[0027] S20. Based on the geometric feature coordinate information, calculate the Minkowski sum of any two irregular polygons at different rotation angles to obtain all possible splicing position schemes, and select the optimal splicing position scheme of any two irregular polygons based on the preset evaluation index to generate a splicing block.

[0028] In this step, the optimal splicing position scheme for the local part of the irregular polygon is selected by Minkowski and preset evaluation indicators.

[0029] Specifically, such as Figure 2 As shown, this step includes the following steps S21-S22: S21. Perform multi-angle rotations on each of the irregular polygons to be spliced ​​within the range of 0-360°, calculate the Minkowski sum of any two irregular polygons at different rotation angles based on the geometric feature coordinate information, and generate all possible splicing position schemes.

[0030] In this step, when performing multi-angle rotation, the rotation step can be 90°, or it can be adjusted according to actual needs, thereby generating multiple rotation instances. In this embodiment, Minkowski sums are calculated for any two irregular polygons and their respective rotation instances, generating all possible splicing position schemes.

[0031] In this embodiment, if the Minkowski sum of the two irregular polygons A and B is calculated, then the graphic scheme composed of all rotation angles a+b (a∈A, b∈B) is obtained. That is, the Minkowski sum of the two irregular polygons A and B is the graphic composed of all rotation angles a+b (a∈A, b∈B).

[0032] S22. Traverse all possible splicing position schemes, calculate the comprehensive fitness rate of each splicing position scheme based on the preset evaluation index, select the scheme with the highest comprehensive fitness rate as the optimal splicing position scheme, and generate the splicing block.

[0033] In this invention, the preset evaluation index may include at least one of the following: the area of ​​the circumscribed rectangle of the assembled block, the effective space utilization rate, and the compactness of the assembly.

[0034] Preferably, in this embodiment, the preset evaluation indicators include the area of ​​the circumscribed rectangle of the splicing block, the effective space utilization rate, and the splicing compactness. The calculation of the overall adaptability of each splicing position scheme based on the preset evaluation indicators specifically includes: calculating the area of ​​the minimum circumscribed rectangle after splicing the two irregular polygons in each splicing position scheme using an outer bounding box algorithm; that is, obtaining the minimum circumscribed rectangle by completely enclosing the irregular polygons with an outer bounding box, and then calculating the area. The minimum circumscribed rectangle can be used for rapid positioning and geometric transformation calculations; calculating the effective space utilization rate and splicing compactness after splicing the two irregular polygons in each splicing position scheme based on the area of ​​the minimum circumscribed rectangle and the substrate area; and calculating the overall adaptability of the splicing position scheme based on the minimum circumscribed rectangle, the effective space utilization rate, and the splicing compactness.

[0035] Preferably, in this embodiment, the overall adaptability rate = effective space utilization rate * weight 1 + assembly compactness * weight 2 - gap redundancy coefficient * weight 3, wherein the effective space utilization rate can be used to measure the degree of matching between the actual area occupied by the assembled block and the available area of ​​the substrate, and is related to the material waste rate. Preferably, the effective space utilization rate = the sum of the current areas of the two irregular polygons assembled / (substrate area - total area of ​​trimmed edges - total area of ​​forced gaps), and the total area of ​​trimmed edges = 2 × (substrate length + substrate width) × single-sided trimming width (fixed process value, e.g., 5mm), total forced gap area = minimum process gap (e.g., 0.2mm) × minimum perimeter of the circumscribed rectangle of the assembly block; assembly compactness can be used to measure the degree of fit after two irregular polygons are assembled, avoiding excessive size leading to wasted space. Assembly compactness = sum of the current areas of the two irregular polygons / area of ​​the minimum circumscribed rectangle; gap redundancy coefficient is used to penalize excess gaps exceeding the minimum process gap, ensuring that the assembly is compliant and compact. Gap redundancy coefficient = actual redundant gap area / area of ​​the minimum circumscribed rectangle of the assembly block, actual redundant gap area = total actual gap area - total forced gap area (if the actual gap ≤ minimum process gap, then the value is 0). For example, if the total substrate area = 1000mm² 2 Total trimmed area = 100mm 2 Minimum process clearance = 0.5mm; Area of ​​irregular polygon A in one splicing position scheme = 150mm² 2 The area of ​​the other irregular polygon B is 100 mm². 2 The area of ​​the smallest bounding rectangle after assembly is 280 mm². 2 The actual total area of ​​the gap is 30mm. 2 The total area of ​​the forced gap is 20mm. 2 Therefore, the effective space utilization rate = (150+100)÷(1000-100-20) = 250÷880≈0.284, the compactness of the assembly = (150+100)÷280 = 250÷280≈0.893, the gap redundancy coefficient = (30-20)÷280 = 10÷280≈0.036, the weights 1, 2 and 3 are 0.5, 0.3 and 0.2 respectively, and the overall adaptability rate = 0.5×0.284 + 0.3×0.893 - 0.2×0.036≈0.142+0.268-0.007≈0.403.

[0036] Understandably, this invention can generate a combined block of any two irregular polygons based on the optimal splicing position scheme, and the combined blocks generated by combining all irregular polygons can constitute a combined block library.

[0037] S30. The assembly blocks are arranged on the substrate using a recursive spatial partitioning method. After arrangement, the position of the assembly blocks is adjusted using an interval approximation algorithm so that the gap between two adjacent assembly blocks approaches the preset minimum value.

[0038] Specifically, such as Figure 3 As shown, this step includes the following steps S31-S32: S31. Recursively divide the remaining space of the substrate to obtain multiple subspaces to be filled. For each subspace to be filled, traverse all the splicing blocks and determine whether there is a splicing block that can be placed in the subspace.

[0039] Specifically, such as Figure 4 As shown, this step includes the following steps S311-S312: S311. Using the dynamically selected assembly block size as the dividing benchmark, the remaining space of the substrate is recursively divided to obtain multiple subspaces to be filled.

[0040] S312. For each subspace to be filled, traverse all the blocks to be placed, determine whether the smallest bounding rectangle of the block can be contained in the subspace, and use a geometric collision detection method to detect whether the block contained in the subspace can be rotated at multiple angles within the subspace.

[0041] For steps S311-S312 above, a dynamic recursive segmentation and adaptive filling method is adopted to determine whether the assemblies can be filled in the subspaces to be filled by the substrate. Specifically, the segmentation reference size can be intelligently selected based on the characteristics of the current remaining space and the size distribution of the assemblies in the assemblies library. For example, a recursive strategy based on the size of the assemblies with the highest frequency in the assemblies library is adopted to divide the unfilled remaining space in the substrate into multiple subspaces to be filled, so as to transform the irregular large space into a series of regular and more manageable small spaces. For each subspace to be filled, the assemblies library is traversed to determine whether the minimum bounding rectangle of its assemblies can be accommodated by the subspace. Furthermore, geometric collision detection is used to verify whether the assemblies (including multi-angle rotation states) can be embedded without conflicting with the assemblies that have already been placed.

[0042] S32. If so, fill the subspace with the piecing block, and adjust the position of the currently filled piecing block in the subspace according to the gap between the currently filled piecing block and the adjacent placed piecing blocks using the gap approximation algorithm, so that the gap between the currently filled piecing block and the adjacent piecing blocks approaches the preset minimum value.

[0043] In this embodiment, if a subspace has multiple placeable blocks, the block with the highest matching degree index (area fit, etc.) is selected for filling, and after filling, the gap between adjacent blocks is optimized using an interval approximation algorithm.

[0044] Specifically, such as Figure 5 As shown, step S32 includes the following steps S321-S323: S321. Calculate the gap values ​​between the points / edges of the currently filled block and the points / edges of the adjacent placed blocks in the X-axis and Y-axis directions, respectively.

[0045] In this embodiment, the distances between points, points, and / or edges of the outer contours of the two assembled blocks are calculated. Since most of the assembled blocks are also irregular polygons, due to the tortuousness of the boundaries of irregular polygons and the density of the points forming the polygons, the present invention performs further sampling calculations near this distance, i.e. the gap value, during the assembly process, so that the gap between the two assembled blocks after final placement approaches the preset minimum value (i.e., the minimum process gap).

[0046] S322. Compare the calculated gap value with the preset minimum value. If the calculated gap value is greater than the preset minimum value, use the interval approximation algorithm to calculate the shortest distance between the currently filled block and the adjacent placed blocks in the X-axis and Y-axis directions respectively.

[0047] In this step, when the calculated gap value is greater than the preset minimum value, it can be determined that the currently filled block is far from the adjacent placed block, and the gap can be adjusted to optimize the layout.

[0048] For steps S321-S322 above, by detecting the actual gap between the current assembly block and the adjacent already placed assembly blocks, the interval approximation algorithm is used to calculate the optimal adjustment position in the X-axis and Y-axis directions respectively. Under the premise of ensuring that it is not less than the minimum process gap (i.e. the preset minimum value), the layout of the assembly blocks is made more compact, and the current local space utilization is optimized.

[0049] Specifically, such as Figure 6 As shown, step S322 includes the following steps S3221-S3223: S3221. Calculate the relative position search range between the currently filled block and the adjacent placed block based on the points / edges of the outer contour of the currently filled block and the points / edges of the outer contour of the adjacent placed block; wherein, the relative position search range includes the relative movable distance range in the X-axis direction and the Y-axis direction.

[0050] In this step, a search space is established based on the outer contour boundary of the irregular polygon.

[0051] S3222. According to the preset movement step size, move the currently filled piece in the X-axis / Y-axis direction with the movement step size being less than the relative position search range as a constraint. After moving, check whether the currently filled piece is connected to the outline of the adjacent placed piece.

[0052] In this step, under the constraint that the movement step size is less than the relative position search range, the currently filled piece is moved individually in the X-axis or Y-axis direction with a preset movement step size d. That is, while fixing one axial position, the piece is moved to the position of the other axial position. After the shortest distance is estimated for that axial position, the piece is moved to the position of the other axial position. After moving with the preset movement step size d, a connection detection is performed. If the piece does not connect after moving in the X-axis direction, it is moved again with the preset movement step size d. If the piece connects, the preset movement step size d is reduced (e.g., d = d / 2), and the connection detection is performed again. The interval is gradually reduced, and the piece is iteratively approximated. It is understandable that the preset movement step size d in the X-axis and Y-axis directions can be different or the same.

[0053] S3223. If so, gradually reduce the preset movement step size and move with the reduced preset movement step size. Continuously adjust the preset movement step size and perform contact detection until the outline of the currently filled block is connected to the outline of the adjacent placed block. Obtain the final preset movement step size in the X-axis direction and Y-axis direction respectively, thereby obtaining the shortest distance between the currently filled block and the adjacent placed block in the X-axis direction and Y-axis direction respectively.

[0054] In this step, a multi-level interval search strategy is adopted, which gradually reduces the step size from the initial preset movement step size, thereby reducing the interval between two adjacent pieces. Invalid positions are quickly filtered out by step size design and contour connection detection, and the search range is dynamically refined. The optimal position of the other axis is calculated with one axis coordinate fixed. The shortest distance in the X-axis direction and the shortest distance in the Y-axis direction are calculated respectively. By calculating the axial distance, it can be ensured that the process clearance requirements are met during the assembly process, thereby improving product quality.

[0055] S323. Move the position of the currently filled tile in the subspace according to the shortest distance, so that the gap between it and the adjacent placed tile approaches the preset minimum value.

[0056] For the above steps, the gap approximation algorithm can quickly and accurately calculate the shortest distance and horizontal / vertical distance between any irregular polygons, and quickly determine whether the polygons are separated, intersecting, or connected. The time consumption can be reduced by more than 20% compared with traditional algorithms. It can quickly process complex irregular graphics, provide positioning and balancing gap benchmarks for splicing, stacking, and nesting, and support operations such as rotation (0-360°) and translation (arbitrary coordinate offset) of irregular polygons through Minkowski and recursive filling.

[0057] Understandably, when adding new tiling blocks, the above-mentioned recursive filling judgment and gap optimization adjustment operations can be performed to achieve matching tiling with other filled tiling blocks. This invention, through this "incremental update strategy", only updates the vertex coordinates, circumscribed rectangle and other related attributes of the irregular polygon during transformation, which can avoid overall data recalculation and improve transformation efficiency.

[0058] Furthermore, in some embodiments, after selecting the optimal splicing position scheme of any two irregular polygons based on preset evaluation indicators and generating a spliced ​​block, the process may further include: adjusting the positions of the two irregular polygons in each spliced ​​block using an interval approximation algorithm, so that the gap between the irregular polygons in the spliced ​​block approaches a preset minimum value. That is, before substrate layout, the gap between the two irregular polygons in the spliced ​​block generated by the optimal splicing position scheme is adjusted. The adjustment of the gap between the two irregular polygons is also performed using the above-mentioned interval approximation algorithm, so that the gap between the irregular polygons in the spliced ​​block approaches a preset minimum value, further optimizing the layout and improving space utilization.

[0059] In this invention, before performing the above-mentioned steps of assembly block layout and gap optimization, initialization is performed. That is, a single-assembly algorithm can be used to package the class, input the assembly block and substrate parameters (size, material limitations, etc.) in the optimal splicing position scheme, initialize the spatial result set (record the filled area) and the width and height number array (record the width and height of each subspace and the number of assemblies that can be accommodated), and can update the spatial result set and the width and height number array in real time after each assembly block layout, accurately record the splicing board filling status of each subspace, and avoid duplicate filling or space waste.

[0060] S40. When the remaining space on the substrate cannot accommodate the smallest panel, output the panelization scheme on the current substrate.

[0061] In this invention, the generated splicing boards are arranged one by one on the substrate through the above step S30. When the remaining space on the substrate cannot accommodate the smallest splicing block, the splicing scheme on the current substrate is output, and information such as the position and angle of the splicing block, substrate utilization rate, and waste rate can also be output simultaneously.

[0062] Understandably, the irregular polygon panelization method of this invention can be applied to industrial scenarios such as PCB manufacturing that require efficient layout of planar graphics. For irregular polygons, the Minkowski sum of different rotation angles is calculated based on their geometric feature information, supporting multiple panelization modes, such as... Figures 7-10 As shown, the process involves assembling irregular polygons of a single shape, that is, placing irregular polygons of the same shape on the same substrate for assembly. Figure 7 and Figure 8 This serves as a control group for a specific application. Figure 9 and Figure 10 As a control group for another specific application, Figure 7 and Figure 9 This invention provides a panel layout output method using the irregular polygon panel method. Figure 8 and Figure 10 As shown in the figure, the panelization scheme output by the existing panelization software GENESIS 2000 has a high substrate space utilization rate and a variety of splicing modes, making it suitable for production needs of different scales.

[0063] As can be seen, in the above scheme, the irregular polygon splicing method of the present invention can accurately complete the standardization, optimal splicing and space compression of irregular polygons, and realize the generation of efficient and high-utilization splicing schemes. The optimal splicing position scheme of the irregular polygons is selected by using Minkowski algorithm and preset evaluation index. Then, the gap between the two irregular polygons in the optimal splicing position scheme is adjusted by using interval approximation algorithm. Then, the local optimal splicing position is globally optimized based on recursive space segmentation method and interval approximation algorithm. That is, the splicing blocks generated by the optimal splicing position scheme are arranged on the substrate by recursive space segmentation method, and the position of the splicing blocks is adjusted by interval approximation algorithm. The splicing blocks are filled on the substrate in the optimal arrangement, which can maximize space utilization, reduce material waste, calculation delay and redundancy caused by unreasonable splicing, improve material utilization and processing efficiency. Moreover, the interval approximation algorithm can also filter most invalid calculation points by step size design, reduce calculation complexity, and meet the real-time requirements of large-scale production.

[0064] It should be understood that the above method embodiments are described as a series of actions for the sake of simplicity. However, those skilled in the art should know that the present invention is not limited by the described order of actions. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0065] Reference Figure 11 , Figure 11 This is a schematic diagram of the structural block of the irregular polygonal panel device provided by the present invention. As shown in the figure, the irregular polygonal panel device includes a feature acquisition module 301, a splicing calculation module 302, a splicing optimization module 303, and an output module 304. Detailed descriptions of each functional module are as follows: The feature acquisition module 301 is used to acquire the geometric features of each irregular polygon to be spliced, and to unify the geometric features of each irregular polygon to the same coordinate reference to obtain geometric feature coordinate information. The splicing calculation module 302 is used to calculate the Minkowski sum of any two irregular polygons at different rotation angles based on the geometric feature coordinate information, obtain all possible splicing position schemes, and select the optimal splicing position scheme of any two irregular polygons based on preset evaluation indicators to generate a splicing block. The splicing optimization module 303 is used to arrange the splicing blocks on the substrate using a recursive spatial partitioning method. After the arrangement, the position of the splicing blocks is adjusted using an interval approximation algorithm so that the gap between two adjacent splicing blocks approaches a preset minimum value. Output module 304 is used to output the current panelization scheme on the substrate when the remaining space on the substrate cannot accommodate the smallest panel.

[0066] In some embodiments, the splicing calculation module 302 is specifically used for: Each irregular polygon to be spliced ​​is rotated at multiple angles within the range of 0-360°. Based on the geometric feature coordinate information, the Minkowski sum of any two irregular polygons at different rotation angles is calculated to generate all possible splicing position schemes. Iterate through all possible splicing position schemes, calculate the overall fitness rate of each splicing position scheme based on preset evaluation indicators, and select the scheme with the highest overall fitness rate as the optimal splicing position scheme.

[0067] In some embodiments, the splicing calculation module 302 is further specifically used for: The position of the two irregular polygons in each piece is adjusted by using an interval approximation algorithm so that the gap between the irregular polygons in the piece approaches the preset minimum value.

[0068] In some embodiments, the stitching optimization module 303 is specifically used for: The remaining space of the substrate is recursively divided to obtain multiple subspaces to be filled. For each subspace to be filled, all the splicing blocks are traversed to determine whether there are any splicing blocks that can be placed in the subspace. If so, the piecing block is filled into the subspace, and the position of the currently filled piecing block in the subspace is adjusted using an interval approximation algorithm based on the gap between the currently filled piecing block and the adjacent placed piecing blocks, so that the gap between it and the adjacent piecing blocks approaches the preset minimum value.

[0069] In some embodiments, the splicing optimization module 303 is further specifically used for: Using dynamically selected assembly block sizes as the segmentation benchmark, the remaining space of the substrate is recursively segmented to obtain multiple subspaces to be filled; For each subspace to be filled, traverse all the blocks to be placed, determine whether the smallest bounding rectangle of the block can be contained within the subspace, and use a geometric collision detection method to detect whether the blocks contained within the subspace can be rotated at multiple angles within the subspace.

[0070] In some embodiments, the splicing optimization module 303 is further specifically used for: Calculate the gap values ​​between the points / edges of the currently filled tile and the points / edges of the adjacent placed tiles in the X-axis and Y-axis directions respectively; Compare the calculated gap value with the preset minimum value. If the calculated gap value is greater than the preset minimum value, use the interval approximation algorithm to calculate the shortest distance between the currently filled block and the adjacent placed blocks in the X-axis and Y-axis directions respectively. The position of the currently filled tile in the subspace is moved according to the shortest distance, so that the gap between it and the adjacent placed tile approaches the preset minimum value.

[0071] In some embodiments, the splicing optimization module 303 is further specifically used for: The relative position search range between the currently filled block and the adjacent placed blocks is calculated based on the points / edges of the outer contour of the currently filled block and the points / edges of the outer contour of the adjacent placed blocks; wherein, the relative position search range includes the relative movable distance range in the X-axis direction and the Y-axis direction; According to the preset movement step size, the currently filled piece is moved in the X-axis / Y-axis direction with the movement step size being less than the relative position search range as a constraint. After moving, it is checked whether the currently filled piece is connected to the outline of the adjacent placed piece. If so, the preset movement step size is gradually reduced, and the movement is performed with the reduced preset movement step size. The preset movement step size is continuously adjusted and a connection detection is performed until the outline of the currently filled block is connected to the outline of the adjacent placed block. The final preset movement step size in the X-axis direction and Y-axis direction are obtained respectively, thereby obtaining the shortest distance between the currently filled block and the adjacent placed block in the X-axis direction and Y-axis direction respectively.

[0072] As can be seen from the above, the irregular polygon panelization device of the present invention can be applied to PCB panelization. It can panelize the same irregular polygons and accurately complete the standardization, optimal splicing and space compression of irregular polygons before the copper foil identification, component layout and other pre- and post-processing. This reduces material waste and calculation delay caused by unreasonable panelization, improves the material utilization rate and processing efficiency of PCB manufacturing, and reduces costs and increases efficiency for PCB mass production. At the same time, it can also be applied to other industrial scenarios that require efficient layout of planar graphics, realize the efficient optimization of irregular polygon panelization, support multiple splicing modes, and be suitable for production needs of different scales.

[0073] For specific limitations regarding the irregular polygon mosaic device, please refer to the limitations of the irregular polygon mosaic method mentioned above, which will not be repeated here. Each module in the aforementioned irregular polygon mosaic device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0074] In one embodiment, a computer device is provided, the internal structure of which can be shown as follows: Figure 12 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with external devices via a network connection. Furthermore, the computer device may also include a display screen and input devices (e.g., mouse, keyboard, etc.) for interactive purposes.

[0075] Specifically, when the processor in the computer device executes the computer program, it implements each step of the irregular polygon tile method provided in the above embodiments.

[0076] In one embodiment, the present invention may also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the various steps of the irregular polygon mosaic method provided in the above embodiments.

[0077] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0078] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0079] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for tiling irregularly shaped polygons, characterized in that, The irregular polygon panel method includes: Obtain the geometric features of each irregular polygon to be spliced, and unify the geometric features of each irregular polygon to the same coordinate reference to obtain the geometric feature coordinate information; Based on the geometric feature coordinate information, the Minkowski sum of any two irregular polygons in all irregular polygons at different rotation angles is calculated to obtain all possible splicing position schemes. Based on the preset evaluation index, the optimal splicing position scheme of any two irregular polygons is selected to generate a splicing block. The assembly blocks are arranged on the substrate using a recursive spatial partitioning method. After arrangement, the position of the assembly blocks is adjusted using an interval approximation algorithm so that the gap between two adjacent assembly blocks approaches a preset minimum value. When the remaining space on the substrate cannot accommodate the smallest panel, output the panel layout on the current substrate.

2. The method for assembling irregularly shaped polygonal panels as described in claim 1, characterized in that, Based on the geometric feature coordinate information, the Minkowski sum of any two irregular polygons at different rotation angles is calculated to obtain all possible splicing position schemes. Then, based on a preset evaluation index, the optimal splicing position scheme for any two irregular polygons is selected. Specifically, this includes: Each irregular polygon to be spliced ​​is rotated at multiple angles within the range of 0-360°. Based on the geometric feature coordinate information, the Minkowski sum of any two irregular polygons at different rotation angles is calculated to generate all possible splicing position schemes. Iterate through all possible splicing position schemes, calculate the overall fitness rate of each splicing position scheme based on preset evaluation indicators, and select the scheme with the highest overall fitness rate as the optimal splicing position scheme.

3. The method for assembling irregularly shaped polygonal panels as described in claim 1, characterized in that, After selecting the optimal splicing position scheme for any two irregular polygons based on preset evaluation indicators and generating a spliced ​​block, the process includes: The position of the two irregular polygons in each piece is adjusted by using an interval approximation algorithm so that the gap between the irregular polygons in the piece approaches the preset minimum value.

4. The method for assembling irregularly shaped polygonal panels as described in claim 1, characterized in that, The method of arranging the assembled blocks on the substrate using a recursive spatial partitioning method, followed by adjusting the position of the assembled blocks using an interval approximation algorithm to make the gap between two adjacent assembled blocks approach a preset minimum value, specifically includes: The remaining space of the substrate is recursively divided to obtain multiple subspaces to be filled. For each subspace to be filled, all the splicing blocks are traversed to determine whether there are any splicing blocks that can be placed in the subspace. If so, the piecing block is filled into the subspace, and the position of the currently filled piecing block in the subspace is adjusted using an interval approximation algorithm based on the gap between the currently filled piecing block and the adjacent placed piecing blocks, so that the gap between it and the adjacent piecing blocks approaches the preset minimum value.

5. The method for assembling irregularly shaped polygonal panels as described in claim 4, characterized in that, The recursive division of the remaining space of the substrate yields multiple subspaces to be filled. For each subspace to be filled, all the piecing blocks are traversed to determine if any piecing block can be placed within the subspace. Specifically, this includes: Using dynamically selected assembly block sizes as the segmentation benchmark, the remaining space of the substrate is recursively segmented to obtain multiple subspaces to be filled; For each subspace to be filled, traverse all the blocks to be placed, determine whether the smallest bounding rectangle of the block can be contained within the subspace, and use a geometric collision detection method to detect whether the blocks contained within the subspace can be rotated at multiple angles within the subspace.

6. The method for assembling irregularly shaped polygonal panels as described in claim 4, characterized in that, The step of adjusting the position of the currently filled tile in the subspace using an interval approximation algorithm based on the gap between the currently filled tile and its adjacent placed tiles, so that the gap between it and its adjacent tiles approaches a preset minimum value, specifically includes: Calculate the gap values ​​between the points / edges of the currently filled tile and the points / edges of the adjacent placed tiles in the X-axis and Y-axis directions respectively; Compare the calculated gap value with the preset minimum value. If the calculated gap value is greater than the preset minimum value, use the interval approximation algorithm to calculate the shortest distance between the currently filled block and the adjacent placed blocks in the X-axis and Y-axis directions respectively. The position of the currently filled tile in the subspace is moved according to the shortest distance, so that the gap between it and the adjacent placed tile approaches the preset minimum value.

7. The method for assembling irregularly shaped polygonal panels as described in claim 6, characterized in that, The step of using an interval approximation algorithm to calculate the shortest distance between the currently filled tile and its adjacent placed tiles in the X-axis and Y-axis directions respectively includes: The relative position search range between the currently filled block and the adjacent placed blocks is calculated based on the points / edges of the outer contour of the currently filled block and the points / edges of the outer contour of the adjacent placed blocks; wherein, the relative position search range includes the relative movable distance range in the X-axis direction and the Y-axis direction; According to the preset movement step size, the currently filled piece is moved in the X-axis / Y-axis direction with the movement step size being less than the relative position search range as a constraint. After moving, it is checked whether the currently filled piece is connected to the outline of the adjacent placed piece. If so, the preset movement step size is gradually reduced, and the movement is performed with the reduced preset movement step size. The preset movement step size is continuously adjusted and a connection detection is performed until the outline of the currently filled block is connected to the outline of the adjacent placed block. The final preset movement step size in the X-axis direction and Y-axis direction are obtained respectively, thereby obtaining the shortest distance between the currently filled block and the adjacent placed block in the X-axis direction and Y-axis direction respectively.

8. A device for splicing irregularly shaped polygonal panels, characterized in that, include: The feature acquisition module is used to acquire the geometric features of each irregular polygon to be spliced, and to unify the geometric features of each irregular polygon to the same coordinate reference to obtain the geometric feature coordinate information. The splicing calculation module is used to calculate the Minkowski sum of any two irregular polygons at different rotation angles based on the geometric feature coordinate information, obtain all possible splicing position schemes, and select the optimal splicing position scheme of any two irregular polygons based on preset evaluation indicators to generate a splicing block. The splicing optimization module is used to arrange the splicing blocks on the substrate using a recursive spatial partitioning method. After the arrangement, the position of the splicing blocks is adjusted using an interval approximation algorithm so that the gap between two adjacent splicing blocks approaches a preset minimum value. The output module is used to output the current panelization scheme on the substrate when the remaining space on the substrate cannot accommodate the smallest panel.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the irregular polygon mosaic method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the irregular polygon mosaic method as described in any one of claims 1 to 7.

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