Digital automatic matching method for skirt pile sleeve prefabricated component layout scheme

Abstract

The application relates to the matching technical field, in particular to a skirt pile sleeve prefabricated component layout scheme digital automatic matching method, which comprises the following steps: obtaining a component three-dimensional model, projecting and discretizing a component base plate contour according to internal lap steel bar anchoring point distribution, adding discrete points in the anchoring point dense area to obtain a boundary segmentation set, constructing an initial coupling matrix, combining geometric compactness, steel bar continuity and demolding feasibility to calculate a coupling degree vector, weighting to obtain a scalar coupling degree, and then selecting an optimal component and a pose by using a greedy algorithm to generate an initial layout, constructing a system energy function integrating multiple indexes, iteratively adjusting the component pose by using a heuristic global optimization algorithm, and outputting an optimized layout scheme after energy convergence.

Description

Technical Field

[0001] This application relates to the field of matching technology. More specifically, this application relates to a digital automatic matching method for the assembly scheme of precast skirt pile sleeve components. Background Technology

[0002] In the large-scale prefabrication and processing of skirted pile sleeve components, the layout of the components is a crucial step affecting material utilization, mold arrangement efficiency, and the subsequent component forming quality. This step requires the rational mapping and arrangement of a large number of three-dimensional components with irregular outer contours on a base plate plane of limited size, providing a basis for subsequent material cutting, mold assembly, and precast component casting. Currently, the engineering field often relies on trial-and-error layout based on manual experience, or directly applies conventional two-dimensional sheet metal part layout algorithms to complete the layout. Such methods can play a certain role when dealing with parts with simple structures and single properties, but they often fail to meet actual production needs when facing large-scale special engineering components with complex internal spatial structures and multiple process constraints. In the prefabrication production scenario, skirted pile sleeve components not only have varied geometric boundary shapes, but also typically have densely distributed pre-reserved lapped steel bar anchoring points for subsequent splicing and assembly.

[0003] Chinese patent document CN111488686B discloses a method for matching and arranging the position of horizontal striped fabric based on a genetic algorithm. The method includes: performing regularization preprocessing on the fabric master pattern and garment pieces participating in the simulated arranging, simulating arranging, setting the number of garment sets participating in the arranging, initializing the original population, and performing genetic algorithm arranging; finally, performing master pattern arranging in actual production: calculating the usable area of ​​the actual master pattern, calculating local coordinates and world coordinates, and converting the data points from the simulated arranging system to the actual production coordinate system to obtain the final arranging diagram.

[0004] The aforementioned methods are designed for two-dimensional planar cut pieces with uniform material properties. Their fitness evaluation system only considers the geometric compactness of the projected outline of the cut pieces, lacking a comprehensive consideration of the three-dimensional process properties and assembly constraints of the components. If the relationship between geometric layout and spatial process constraints is severed during the pattern assembly process, and only the optimal result in terms of planar arrangement is pursued, the generated layout scheme may lead to problems such as discontinuity of reserved reinforcement in adjacent components, difficulty in aligning nodes, and mutual interference in demolding space during actual casting, assembly, or demolding, thus causing rework or even component scrapping. Therefore, in the field of skirt pile sleeve component production scheduling, there is an urgent need for a comprehensive pattern matching method that can coordinate the optimization of geometric shape layout, the guarantee of internal spatial structure continuity, and the feasibility of demolding process, so as to achieve a synergistic improvement in material utilization, component assembly accuracy, and actual manufacturing feasibility at the global level. Summary of the Invention

[0005] This application provides a digital automatic matching method for the assembly scheme of precast skirt pile sleeve components, which aims to solve the problem that existing assembly methods ignore the three-dimensional process attributes and assembly constraints of components, resulting in insufficient feasibility of the layout scheme in actual production.

[0006] This application provides a digital automatic matching method for the assembly scheme of precast skirted pile sleeve components. The matching method includes: S1, acquiring all three-dimensional models of the skirted pile sleeve components, discretizing the projection contour of the components on the base plate plane according to the distribution of anchor points of the reserved lapped steel bars inside the three-dimensional models of each component, adding discrete points in the dense anchor point area to obtain a set of boundary segments; S2, constructing an initial coupling matrix with component pairs and boundary segment pairs as spatial indices, calculating the coupling degree vector composed of geometric compactness, steel bar continuity, and demolding feasibility for all pairings in the initial coupling matrix, and weighting it to obtain a scalar coupling degree, wherein the coupling degree is calculated based on the local surplus area and the area of ​​the circumscribed convex hull of the pairing. Geometric compactness is calculated based on the spatial alignment and proximity of the reserved lapped steel bars to determine the continuity of the steel bars. Demolding feasibility is calculated based on the overlapping volume of the demolding interference zone between one component and another. Based on scalar coupling, a greedy algorithm is used to iteratively select the component and pose with the optimal scalar coupling with the already laid-out components to generate the initial panel layout. S3, with the initial panel layout as the starting state, a system energy function is constructed, which is a weighted combination of the sum of the scalar coupling of adjacent components, the ratio of the panel layout envelope area, and the component overlap penalty term. A heuristic global optimization algorithm is used to perform global spatial optimization iterative processing on the poses of all components until the energy convergence state is reached, and the optimized target skirt pile sleeve component panel layout is output.

[0007] Based on the distribution of anchor points for pre-reserved lapped rebars within the components, the projected contours of the components are refined and discretized to improve the accuracy of component boundary feature extraction. By comprehensively introducing geometric compactness, rebar continuity, and demolding feasibility to form a scalar coupling degree, the matching relationship between components is more comprehensively characterized. This improves the utilization rate of substrate materials while considering the continuity of rebar laps and the operability of component demolding during subsequent construction. An initial panel layout is generated based on a greedy algorithm. Global spatial optimization iteration is performed using a system energy function that integrates the coupling degree of adjacent components, the envelope area ratio, and the overlap penalty term to improve the compactness and rationality of the overall panel layout.

[0008] Furthermore, the discretization of the projected contours of the components on the substrate plane, and the addition of discrete points in the dense anchoring point area to obtain the boundary segment set includes: obtaining the orthogonal projection closed polygons of the three-dimensional models of each component on a two-dimensional plane parallel to the substrate as the projection contours; sampling along the projection contours at fixed intervals with a first step length to obtain initial discrete points; obtaining the number of steel bar anchoring points in the local area between adjacent initial discrete points, and when the number is not less than a preset number threshold, inserting supplementary discrete points in the boundary segment between adjacent initial discrete points with a second step length less than the first step length; and connecting all discrete points sequentially in a clockwise direction to generate a line segment composed of adjacent discrete points, which is set as the boundary segment set.

[0009] Compared to the conventional approach of uniformly discretizing the contour with a fixed step size, this application first obtains initial discrete points by sampling at equal intervals with a first step size. Then, based on whether the number of rebar anchor points in the local area between adjacent discrete points reaches a threshold, it adaptively inserts supplementary discrete points in dense areas with a smaller second step size. This concentrates the limited discrete point resources on the key sections that truly affect the subsequent rebar hole mapping and pairing accuracy. This avoids the surge in computational load caused by global subdivision and prevents pairing distortion caused by loss of boundary features due to excessively coarse discretization near anchor points. The resulting boundary segment set has higher geometric fidelity in dense areas, providing a more reliable geometric basis for subsequent coupling degree calculation and splicing alignment. In practical applications, this directly reduces the risk of rebar hole misalignment and interference during the assembly process.

[0010] Further, the calculation of geometric compactness based on the paired local surplus area and the circumscribed convex hull area includes: obtaining the non-overlapping closed internal two-dimensional region formed by the pairing of two boundary segments, and extracting the area of ​​the region as the local surplus area; extracting the two-dimensional coordinates of all discrete vertices on the projected contours of the two components after pairing, calculating the minimum area closed convex polygon covering all coordinates, and extracting the area of ​​the polygon as the circumscribed convex hull area; dividing the local surplus area by the sum of the circumscribed convex hull area and the minimum value to obtain the area ratio; and calculating the difference between 1 and the area ratio as the geometric compactness.

[0011] Compared to the traditional method of roughly estimating excess material by the difference between the area of ​​the circumscribed convex hull and the area of ​​the union, this application identifies the non-overlapping closed internal gap area formed by the paired projection contours of two components and not covered by either component. The area of ​​this gap is used as the local excess material area and normalized dimensionlessly using the area of ​​the circumscribed convex hull. This allows the geometric compactness to truly reflect the seamless fit at the seam rather than the overall shape difference, thus more accurately depicting the tightness of the local splicing of the two components. During layout optimization, the algorithm is guided to prioritize the pairing scheme with small gaps and good fit, effectively improving the actual material utilization rate of the substrate and reducing invalid excess material.

[0012] Further, the calculation of rebar continuity based on the spatial alignment and proximity of the reserved lapped rebars includes: extracting the first three-dimensional relative coordinates of the center of the end face of the reserved lapped rebar extending outward from the first component after pairing in the pairing local coordinate system; extracting the second three-dimensional relative coordinates of the center of the preset insertion sleeve hole inside the second component after pairing in the pairing local coordinate system; mapping and pairing the first three-dimensional relative coordinates and the second three-dimensional relative coordinates one by one based on the principle of shortest spatial distance, calculating the sum of the squares of the coordinate differences of each pairing node in the three-axis direction to obtain the squared value of the Euclidean distance; summing the squared values ​​of the Euclidean distances of all pairing nodes to obtain the total sum of squared distances, dividing the preset reference sum of squared distances by the sum of the preset reference sum of squared distances, the total sum of squared distances, and the minimum value to obtain the rebar continuity with a value in the range of 0 to 1.

[0013] Compared to the simple approach of directly matching the anchor points of the reinforcing bars of two components as the reinforcing bars, this application uses the center of the end face of the protruding reinforcing bar of the first component and the center of the sleeve opening of the second component as the actual matching objects in the local coordinate system of the pairing. Based on the principle of the shortest spatial distance, a one-to-one mapping is established, and the continuity index in the interval of 0 to 1 is obtained by normalizing the sum of the squares of the total distances through the reference distance. This allows the spatial alignment and proximity of the reinforcing bar laps to be accurately quantified and kept in the same dimension as other indicators. As a result, it is possible to quantitatively predict whether the subsequent grouting sleeve and the protruding reinforcing bar can be successfully inserted during the assembly stage. This significantly reduces the probability of rework caused by difficulty in aligning nodes and discontinuity of reinforcing bars, and improves the assembly accuracy of components and the success rate of construction on the first attempt.

[0014] Furthermore, the calculation process of the enveloping area ratio of the layout scheme includes: calculating the area of ​​the smallest bounding rectangle that covers the orthogonal projections of all components in the current layout, and dividing the area of ​​the rectangle by the sum of the orthogonal projection areas of all components as the enveloping area ratio of the layout scheme.

[0015] Compared to the approach of evaluating the footprint solely based on the sum of the projected areas of the components, this application uses the area of ​​the smallest bounding rectangle covering the orthogonal projections of all components to divide the sum of the projected areas of the components to obtain a dimensionless envelope area ratio. This allows the overall layout's spaciousness and compactness to be uniformly characterized as a ratio independent of the component size. This facilitates horizontal comparisons between different batches and different numbers of components in the layout task and can be directly used as a target component for global optimization. As a result, it guides the multi-component layout to evolve towards a smaller footprint and higher utilization rate, effectively improving the overall space utilization efficiency of the substrate.

[0016] Further, the calculation process of demolding feasibility includes: selecting a three-dimensional normal direction perpendicular to the substrate plane and upward as the demolding stretching path; translating the first component solid model upward along the stretching path by the maximum solid envelope height, and combining the space occupied by the entire translation process into an extended polyhedron as the demolding interference zone; obtaining the adjacent second component solid model, performing a three-dimensional Boolean intersection operation, obtaining the common intersection part between the second component solid model and the demolding interference zone, and calculating the volume of the intersection part as the overlap volume; when the overlap volume value is 0, the demolding feasibility is assigned a value of 1; when the overlap volume is greater than 0, the demolding feasibility is assigned a value of 0.

[0017] Compared to existing methods that only determine whether components overlap in a two-dimensional plane while ignoring the demolding process, this application sweeps the component entities along the demolding direction perpendicular to the substrate to form a three-dimensional demolding interference zone. Then, it calculates the overlap volume between adjacent component entities and the interference zone through three-dimensional Boolean intersection operation, and assigns a binary value to the demolding feasibility accordingly. This allows the layout scheme to identify and filter out infeasible poses that would cause mutual interference in the demolding space of adjacent components in the early stages of generation. This embeds the key manufacturing process constraint of whether demolding can be successful into the matching decision in advance, avoiding the problem that the layout may seem optimal on the plane but will cause mutual jamming and damage to components during actual demolding, thus improving the actual manufacturability of the panelization scheme.

[0018] Further, generating the initial panel layout includes: selecting the component with the largest base area from the unpaneled set and placing it at the preset origin of the substrate as the reference component, adding it to the set of already laid-out components and removing it from the unpaneled set; establishing a loop iteration: traversing all components in the unpaneled set, querying the initial coupling matrix, and obtaining the scalar coupling degree when each unpaneled component is connected to each component in the set of already laid-out components through different boundary segment pairs; selecting the unpaneled component with the largest scalar coupling degree and its relative pose, which includes two-dimensional translation and rotation dimensions, determined by the alignment relationship of the corresponding boundary segment pairs, as the optimal component and optimal pose; arranging the optimal component according to the optimal pose, adding it to the set of already laid-out components and removing it from the unpaneled set; repeating the loop iteration until the unpaneled set is empty, and outputting the initial panel layout composed of the set of already laid-out components.

[0019] Furthermore, reaching the energy convergence state includes: after sampling multiple times according to the Markov chain length, updating the system temperature using a cooling function until the current system temperature is lower than a set minimum temperature threshold, or the variance of the system energy function is less than the convergence tolerance threshold within multiple consecutive cooling cycles, and then determining that the energy convergence state has been reached.

[0020] Furthermore, the calculation process of the component overlap penalty term includes: calculating the total spatial overlap volume between all pairs of entities of all components in the current layout, and dividing the total spatial overlap volume by the sum of the total volume of all entity components and the minimum value of zero, to obtain the dimensionless component overlap penalty term.

[0021] Furthermore, the process of constructing the system energy function includes: traversing the current panel layout, extracting and accumulating the scalar coupling degree between all adjacent paired components to obtain the overall coupling degree sum; multiplying the overall coupling degree sum by a preset negative first weight coefficient to obtain a first weighting term; multiplying the panel scheme envelope area ratio by a preset positive second weight coefficient to obtain a second weighting term; multiplying the component overlap penalty term by a preset positive third weight coefficient to obtain a third weighting term; and adding the first weighting term, the second weighting term, and the third weighting term to obtain the system energy function.

[0022] Compared to existing methods that drive layout with only a single objective, this application multiplies the overall coupling degree by a negative weight, and multiplies the envelope area ratio and overlap penalty term by positive weights respectively, and then superimposes them algebraically to form a system energy function. This allows the three mutually restrictive objectives of improving adjacent matching quality, reducing floor space, and suppressing entity overlap to be uniformly expressed as an optimal scalar evaluation index. The relative priority of each objective can be flexibly adjusted through weight calibration, thereby achieving a synergistic trade-off between material utilization, assembly continuity, and manufacturing feasibility in global optimization. This provides a clear and adjustable optimization objective basis for outputting a high-quality layout scheme that takes into account multiple engineering constraints.

[0023] This application has the following technical advantages:

[0024] Based on the distribution of anchor points for pre-reserved lapped rebars within the component, the projected contour of the component is refined and discretized, with the number of discretized points increased in densely populated anchor point areas to improve the accuracy of component boundary feature extraction. By comprehensively introducing geometric compactness, rebar continuity, and demolding feasibility to form a scalar coupling degree, the matching relationship between components can be more comprehensively characterized. This improves the utilization rate of substrate materials while considering the continuity of rebar laps and the operability of component demolding during subsequent construction. Furthermore, an initial panel layout is generated based on a greedy algorithm, and global spatial optimization iteration is performed using a system energy function that integrates the coupling degree of adjacent components, the envelope area ratio, and the overlap penalty term, which improves the compactness and rationality of the overall panel layout. Thus, this application achieves automated and high-quality generation of panel layout schemes for skirt pile sleeve components, reducing manual layout trial and error time and material waste, and improving the production efficiency of prefabrication of engineering components. Attached Figure Description

[0025] Figure 1This is a flowchart of a digital automatic matching method for the assembly scheme of precast skirt pile sleeve components according to an embodiment of this application; Figure 2 This is a schematic diagram of the demolding interference overlap area of ​​the digital automatic matching method for the assembly scheme of precast skirt sleeve components according to an embodiment of this application; Figure 3 This is a schematic diagram comparing the average deviation of rebar alignment in the digital automatic matching method for the assembly scheme of precast skirt pile sleeve components according to an embodiment of this application. Detailed Implementation

[0026] Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] This application provides a method for automatically matching digital assembly schemes of precast skirted pile sleeve components. Figure 1 This is a flowchart of a digital automatic matching method for the assembly scheme of precast skirt pile sleeve components according to an embodiment of this application. The specific implementation process of this method will be described in detail below.

[0028] S1: Adaptive discretization of anchor points.

[0029] Obtain the three-dimensional models of all skirt pile sleeve components. Based on the distribution of anchor points of the reserved lapped steel bars inside the three-dimensional models of each component, discretize the projection contour of the component on the base plate plane, add discrete points in the dense anchor point area, and obtain the boundary segment set.

[0030] The 3D model files of all skirt pile sleeve components were imported using a 3D geometric modeling and analysis tool. The 3D spatial coordinates of the ends of the reserved lapped steel bars were extracted as the anchorage point set by traversing topological surfaces and edge features. A 3D model projection algorithm was used to project each 3D model vertically onto the 2D plane containing the horizontal base plate. The outermost edge closed loop was extracted to construct a 2D projection contour. A kernel density estimation algorithm was used, with the 2D projection coordinates of all anchorage points as input, to calculate the kernel density distribution value at each position on the projection contour. A sampling algorithm was used to divide the step size along the parameterized curve of the projection contour. When traversing a curve region where the kernel density distribution value is greater than the density threshold, the step size parameter was reduced, increasing the number of generated discrete points on the contour. The curve segments between adjacent discrete points were sequentially connected to construct polyline objects, and a set of boundary segments with topological predecessor-follower relationships was formed through 2D geometric processing methods.

[0031] In some embodiments, discretizing the projected profile of the component on the substrate plane and adding discrete points in the dense anchor point region to obtain a boundary segment set includes: Obtain the orthogonal projection closed polygons of the 3D models of each component onto a 2D plane parallel to the substrate as the projection outline; Sample along the projected contour at fixed intervals using the first step length to obtain initial discrete points; Obtain the number of steel bar anchorage points in the local area between adjacent initial discrete points. When the number is not less than the preset number threshold, insert supplementary discrete points in the boundary segment between adjacent initial discrete points with a second step length less than the first step length. Connect all discrete points sequentially in a clockwise direction to generate line segments composed of adjacent discrete points, which are then set as the boundary segment set.

[0032] The orthogonal projection of the component onto the XY substrate plane is extracted using a 3D geometry engine. Polygon Boolean operations are used to repair self-intersection lines, and internal holes in the projected contour are identified, generating closed outer envelope polygons and corresponding internal constraint loops. For actual internal holes affecting panel occupancy or surplus material area calculations, they are not directly deleted but marked as internal constraint loops of the projected contour and participate in subsequent geometric calculations. A length parameter, i.e., the first step length, is set, preferably within the range of 50mm to 100mm, with an example value of 100mm. Starting from the starting point of the projected contour, the arc length is calculated along the contour boundary and equidistant sampling is performed to obtain a series of initial discrete points and a 2D coordinate sequence. After obtaining the initial discrete points, a local rectangular search area is constructed for every two adjacent initial discrete points, with the line segment as the central axis and a width half the first step length, such as 50mm. The number of steel reinforcement anchor points projected onto the substrate plane within this area is found using a spatial indexing method.

[0033] When the system detects that the number of anchor points within a local rectangular search area is greater than or equal to a set density threshold, preferably 2 to 5 (e.g., 3), it determines that the boundary segment belongs to a densely anchored reinforcement zone. On the boundary segment between adjacent initial discrete points, a smaller second step size, preferably 10mm to 30mm (exemplarily 20mm), is used for resampling, inserting supplementary discrete points to improve the geometric fidelity of the dense area and the accuracy of subsequent pairing. Based on the direction attribute of the clockwise traversal of the projected contour, the initial discrete points and the newly inserted supplementary discrete points are sequentially reassembled and connected, transforming them into several end-to-end line segments, forming a complete set of boundary segments and storing it in the database.

[0034] S2: Scalar coupling degree calculation and initial layout generation.

[0035] An initial coupling matrix is ​​constructed using component pairs and boundary segment pairs as spatial indices. For all pairings in the initial coupling matrix, a coupling degree vector consisting of geometric compactness, reinforcement continuity, and demolding feasibility is calculated and weighted to obtain a scalar coupling degree. Geometric compactness is calculated based on the area of ​​the local surplus material and the area of ​​the circumscribed convex hull of the pairing. Reinforcement continuity is calculated based on the spatial alignment and proximity of the reserved lapped reinforcement. Demolding feasibility is calculated based on the overlapping volume of the demolding interference zone between one component entity and another component. Based on the scalar coupling degree, a greedy algorithm is used to iteratively select the component and pose with the optimal scalar coupling degree with the already laid-out components to generate the initial panel layout.

[0036] A four-dimensional tensor is initialized using a multidimensional array as the initial coupling matrix, with the four dimensions mapping to the first component number, the first boundary segment number, the second component number, and the second boundary segment number, respectively. For each combined element in the tensor, a boundary segment fitting algorithm is used to translate and rotate the target boundary segment of the second component to the source boundary segment of the first component for geometric fitting. When determining the relative pose, the boundary segment fitting algorithm ensures that the tangential directions of the two boundary segments involved in the fitting are opposite, their outward normal directions are opposite, and that the two component entities are located on opposite sides of the seam. When the lengths of the two boundary segments are inconsistent, the translation along the boundary direction is determined according to the principle of maximizing the overlap length. After geometric fitting, the difference between the circumscribed convex hull area and the union area is no longer used as the local excess area. Instead, a non-overlapping closed internal two-dimensional region, enclosed by the projected contours of the two components and not covered by the projected area of ​​either component, is identified when the two boundary segments are paired and placed. The area of ​​this internal gap or hole region is used as the local excess area. When the non-overlapping closed internal two-dimensional region does not exist, the local excess area is assigned a value of 0. The circumscribed convex hull area is only used to proportionally normalize the local excess area. The two-dimensional coordinates of all discrete vertices on the projected contours of the two components after pairing are extracted. The minimum area closed convex polygon covering all coordinates is calculated and its area is extracted as the circumscribed convex hull area. Then, the geometric compactness is calculated based on the local excess area and the circumscribed convex hull area.

[0037] The rebar anchorage points are used to characterize the spatial arrangement of reserved lapped rebars or sleeve openings within the component model. During the rebar continuity calculation stage, the center of the outward-extending rebar end face in the direction to be connected and the center of the corresponding sleeve opening are used as the actual matching nodes. When calculating rebar continuity, the center of the reserved lapped rebar end face extending outward from the first component and the center of the preset insertion sleeve opening inside the second component are uniformly used as the matching objects; the rebar anchorage points of the two components are no longer directly used as the matching objects between rebars. A one-to-one mapping relationship between the reserved lapped rebar end face center and the sleeve opening center is established based on the principle of shortest spatial distance. The squared Euclidean distance of each paired node is calculated and accumulated to form the total squared distance. When the number of reserved lapped rebar end face centers is inconsistent with the number of sleeve opening centers, candidate nodes are first screened according to the direction to be connected and the preset connection range, and then the candidate nodes are matched one-to-one. For unmatched end face centers or opening centers, a preset missing penalty distance is included in the total squared distance. The reinforcement continuity is obtained by dividing the sum of the squares of the preset reference distances by the sum of the squares of the preset reference distances, the sum of the squares of the total distances, and the sum of the minimum values ​​to prevent zero. The reinforcement continuity is made closer to 1 when the alignment is better and closer to 0 when the deviation is greater, and the index is avoided from exceeding 1.

[0038] When calculating demolding feasibility, the first component is uniformly used as the currently demolded component. The first component is swept along the preset demolding direction to form a demolding interference zone. Then, the overlap volume between the adjacent second component solid model and the demolding interference zone is calculated. When reverse demolding needs to be evaluated, the roles of the first and second components are swapped and the calculation is repeated. If the overlap volume is not greater than the preset interference tolerance, the demolding feasibility is assigned a value of 1; if the overlap volume is greater than the preset interference tolerance, the demolding feasibility is assigned a value of 0. The overlap volume value of 0 means that the discrimination volume after the preset interference tolerance is zeroed is not greater than the preset interference tolerance. In the candidate pose screening stage, if the demolding feasibility of any paired pose is 0, the paired pose is removed from the candidate pose set, or the scalar coupling degree corresponding to the paired pose is directly assigned a value of 0, so that poses that do not meet the demolding conditions do not participate in the subsequent greedy selection. The geometric compactness, reinforcement continuity, and demolding feasibility are combined into a coupling degree vector, and the inner product with the preset three-dimensional weight vector is obtained to obtain the scalar coupling degree. Each weight in the three-dimensional weight vector is non-negative and the sum of the weights is 1, ensuring that the scalar coupling degree remains within the range of 0 to 1. A greedy search algorithm is used to place the component with the largest area at the origin. In each iteration, the algorithm iterates through the initial coupling matrix to find the unplaced component with the maximum scalar coupling degree to the placed components. Based on the 2D affine transformation relationship of the boundary segment pairs that trigger this maximum scalar coupling degree, the rotation angle and planar coordinates of the unplaced component are determined. This search and pose update process is iterated until all components are placed, forming an initial mosaic layout containing the spatial pose information of each component.

[0039] In some embodiments, calculating the geometric compactness based on the paired local surplus area and the circumscribed convex hull area includes: Obtain the non-overlapping closed internal two-dimensional region formed when two boundary segments are paired and placed, and extract the area of ​​the region as the local surplus area. Extract the two-dimensional coordinates of all discrete vertices on the projected contours of the two components after pairing, calculate the minimum area closed convex polygon that covers all coordinates, and extract the area of ​​the polygon as the circumscribed convex hull area. The area ratio is obtained by dividing the area of ​​the local surplus material by the sum of the area of ​​the circumscribed convex hull and the minimum value of the zero-prevention area; The difference between 1 and the area ratio is calculated as the geometric compactness.

[0040] When evaluating the geometric compactness of two components after segmental alignment and bonding along specific boundaries, a local coordinate system is established based on their relative poses on the substrate plane. A polygon detection algorithm is then used to scan the gaps and holes formed between the projected contours of the two components, areas not covered by either component entity. The closed internal two-dimensional region is extracted, and its area is calculated using a shoelace formula; for example, the extracted area of ​​the excess material is 0.45. This is set as the local surplus area. Obtain the two-dimensional coordinate set of all discrete points outside the projected contour of the paired component, and use the fast convex hull algorithm to generate a closed convex polygon with the minimum area covering all vertices. Calculate the area of ​​this polygon as the circumscribed convex hull area; for example, the circumscribed convex hull area is 12.5. .

[0041] To ensure computational stability, a preset zero-protection minimum value is input, preferably on the order of magnitude of [value missing]. to Example value Dividing the area of ​​the local excess material by the sum of the area of ​​the circumscribed convex hull and the minimum value of the zero point yields a dimensionless area ratio, which is approximately 0.036. Subtracting this area ratio from 1 gives the geometric compactness normalized to the interval between 0 and 1, resulting in 0.964. This index represents the seamlessness of the splicing, thus numerically expressing the nonlinear relationship between excess material and compactness.

[0042] In some embodiments, calculating the continuity of the reinforcing bars based on the spatial alignment and proximity of the reserved lapped reinforcing bars includes: Extract the first three-dimensional relative coordinates of the center of the reserved lapped steel bar end face extending outward from the first component after pairing in the local coordinate system of pairing; Extract the second three-dimensional relative coordinates of the center of the pre-set insertion sleeve orifice inside the second component after pairing, under the local coordinate system of the pairing; Based on the principle of shortest spatial distance, the first three-dimensional relative coordinates and the second three-dimensional relative coordinates are mapped and paired one by one, and the sum of the squares of the coordinate differences of each paired node in the three-axis direction is calculated to obtain the squared value of the Euclidean distance. The total squared distance is obtained by summing the squared Euclidean distances of all paired nodes. The reinforcement continuity is obtained by dividing the preset reference squared distance by the sum of the preset reference squared distance, the total squared distance, and the minimum value to prevent zero. The value is in the range of 0 to 1.

[0043] Based on the transformation matrix, the two components involved in the matching are transformed to the same paired local coordinate system. By extracting all the protruding reserved lapped steel bars in the 3D model of the first component, for example, setting the center of the end face of the steel bar with a diameter of 32mm, a first set of 3D relative coordinates is obtained. The corresponding sleeve grouting hole or anchor hole position in the second component model is scanned, and the coordinates of the center point of the hole are extracted to generate a second set of 3D relative coordinates. Based on the principle of minimizing the straight-line distance in space, the two sets of coordinates are matched so that each protruding steel bar corresponds to the corresponding sleeve hole.

[0044] After establishing the mapping relationship, the coordinate differences of each paired node in the X, Y, and Z dimensions are calculated, squared, and then summed to obtain the squared Euclidean distance of each single-point pair. The squared values ​​of all paired nodes are then accumulated to generate the total sum of squared distances representing the degree of spatial deviation. To establish a continuity evaluation index, a preset reference sum of squared distances representing the allowable alignment tolerance is used. Preferably, this is set to the square of the allowable deviation radius of a single node multiplied by the total number of reinforcing bars. For example, if the allowable tolerance for a single point is set to 5mm, and there are a total of 10 paired reinforcing bars, the reference sum of squared distances is calibrated to 250. And the minimum value to prevent zero is preferably set to The rebar continuity score is calculated by dividing the sum of the squared reference distances by the sum of the squared reference distances, the total sum of squared distances, and the minimum value to prevent zero. The smaller the total sum of squared distances, the closer the rebar continuity is to 1; the larger the total sum of squared distances, the closer the rebar continuity is to 0, thus ensuring that this index is consistent with the scalar coupling degree in the subsequent range of 0 to 1.

[0045] In some embodiments, calculating demolding feasibility based on the overlap volume of the demolding interference zone between one component and another component includes: The three-dimensional normal direction perpendicular to the plane of the substrate and pointing upwards is selected as the demolding stretching path; The first component solid model is translated upward along the stretching path to the maximum solid envelope height, and the space occupied by the entire translation process is combined into an extended polyhedron as the demolding interference zone. Obtain the second component solid model placed adjacent to it, perform a three-dimensional Boolean intersection operation, obtain the common intersection part between the second component solid model and the demolding interference zone, and calculate the volume of the intersection part as the overlap volume; When the overlap volume value is 0, the demolding feasibility value is assigned to 1; When the overlapping volume is greater than 0, the demolding feasibility is assigned a value of 0.

[0046] When evaluating the feasibility of demolding after component assembly, the positive Z-axis of the substrate plane is selected as the preset vertical demolding stretching path. The first component is used as the currently demolded component, and the second component is used as the adjacent interference judgment object. By analyzing the 3D solid bounding box of the first component, the spatial difference between the highest and lowest points in the Z-axis direction is calculated as the maximum solid envelope height parameter, preferably ranging from 500mm to 2000mm; for example, a value of 1200mm is used for typical engineering prefabricated parts. The 3D solid model of the first component is controlled to linearly translate upwards along the set vertical stretching path by this envelope height distance, and the voxel trajectory swept by the model's outer contour in space during the entire translation process is recorded. The trajectory is then fused into an extended polyhedral solid to construct the demolding interference zone.

[0047] After the interference zone is constructed, the solid model of the adjacent second component is obtained, and a 3D Boolean intersection operation is performed using a spatial interference check or Boolean operation library. The volume of the common intersection region formed by the mutual penetration of the two geometric entities is calculated as the overlap volume parameter. For example, the result is 0 when there is no interference, or the extracted intersection volume is 14.5 when interference exists. .like Figure 2 As shown, the spatial structure of the demolding interference zone of the component and the adjacent component entities is drawn. The intersecting areas in the figure correspond to the overlapping volume solved in this operation. During the discrimination, the numerical error of the three-dimensional Boolean operation is considered. When the overlapping volume is not greater than the preset interference tolerance, it is considered that there is no substantial demolding interference, and the demolding feasibility is assigned a value of 1; when the overlapping volume is greater than the preset interference tolerance, it is considered that there is demolding interference, and the demolding feasibility is assigned a value of 0. The preset interference tolerance can be set according to the modeling accuracy, for example, 0.01. When the overlapping volume is not greater than 0.01 When the overlap volume is greater than 0.01, it is considered that there is no substantial demolding interference; when the overlap volume is greater than 0.01 If demolding interference is detected, the demolding feasibility is assigned a value of 0. When it is necessary to determine the reverse demolding feasibility of the second component relative to the first component, the roles of the first and second components are swapped and the above calculation is repeated to avoid inconsistencies in the generation of the main body before and after the demolding interference zone. This discrimination mechanism, as a constraint condition, can identify and filter out panel poses that do not have demolding feasibility in the early stage of coupling degree calculation.

[0048] In some embodiments, the step of using a greedy algorithm to iteratively select the component and pose with the optimal scalar coupling degree to the already laid-out components, based on the scalar coupling degree, to generate an initial panel layout includes: Select the component with the largest base area from the un-paneled set and place it at the preset origin of the base plate as the reference component. Add it to the set of already laid-out components and remove it from the un-paneled set. Establish a loop iteration: traverse all components in the unassembled set, query the initial coupling matrix, and obtain the scalar coupling degree when each unassembled component is connected to each component in the laid-out component set through different boundary segment pairs; The unassembled component with the highest scalar coupling degree and the relative pose containing two-dimensional translation and rotation dimensions determined by the alignment relationship of the corresponding boundary segments are selected as the optimal component and the optimal pose. Arrange the optimal components according to their optimal poses, add them to the set of already laid-out components, and remove them from the set of unlaid-out components. Repeat the loop iteratively until the un-laid-out set is empty, and output the initial layout consisting of the set of laid-out components.

[0049] The polygonal base area of ​​all components in the input data is calculated and sorted. The component with the largest orthogonal projected area of ​​its base surface is selected as the reference component for the initial layout. The centroid or bounding box center point of the component is then translated and aligned to the preset origin of the substrate. The parameters are set as follows: , The reference orientation is set to 0 degrees. At this point, the reference component is added to the set of already laid-out components, and the corresponding component is removed from the set of unlaid-out components. The process then enters an iterative progression phase, traversing the remaining unlaid-out components in the queue and querying the calculated initial coupling matrix database.

[0050] During the retrieval phase, the boundary segment pairings between each component to be arranged and all already arranged components are extracted, and the scalar coupling degree of their combination is parsed, with a value ranging from 0 to 1. By comparison, the unassembled component that causes the scalar coupling degree to reach its maximum value, such as the highest score of 0.89, is located. Simultaneously, based on the geometric boundary segment alignment mapping relationship that triggers this optimal solution, the relative pose including translation and rotation dimensions is calculated using inverse solving; for example, the translation correction vector is parsed as follows. , The yaw rotation parameter is 45.5 degrees clockwise. Before arranging this optimal component according to the extracted relative pose parameters, the overlap volume between the optimal component and all components in the already laid-out component set is checked. If the overlap volume exceeds the preset overlap tolerance, the candidate pose is removed, and the next candidate pose is selected according to the scalar coupling degree. If the overlap volume does not exceed the preset overlap tolerance, the optimal component is arranged according to the extracted relative pose parameters, added to the already laid-out component set, and removed from the un-laid-out set. The above retrieval, transformation, and set update process continues to loop until the un-laid-out set is empty, at which point the loop ends, and the initial layout containing node connection relationships and geometric pose coordinates is output.

[0051] S3: Construct the system energy function and output the optimized puzzle scheme.

[0052] A system energy function is constructed by weighting the sum of the scalar coupling degrees of adjacent components, the ratio of the envelope area of ​​the panel scheme, and the component overlap penalty term. A heuristic global optimization algorithm is used to perform global spatial optimization iteration on the poses of all the components until the energy convergence state is reached, and the optimized target skirt sleeve component panel scheme is output.

[0053] A system energy function is constructed. Each evaluation term in the system energy function uses dimensionless indices in a weighted combination to avoid imbalances in the optimization objective due to differences in dimensions and orders of magnitude between the spatial overlap area or volume and the scalar coupling degree and envelope area ratio. Specifically, the system energy function includes adjacent component coupling terms, envelope area terms, and overlap penalty terms. In application scenarios with fixed substrate size constraints, the substrate boundary is used as a pose feasibility constraint in the global optimization process. When the projected contour of any component exceeds the substrate boundary, the pose update is rejected, or the pose is marked as an infeasible candidate pose, without changing the composition of the system energy function consisting of adjacent component coupling terms, envelope area terms, and overlap penalty terms. The adjacent component coupling term is the sum of the scalar coupling degrees of all adjacent component pairs in the current layout, used to characterize the overall matching degree between adjacent components in the current layout; the envelope area term is the envelope area ratio of the panel layout; the overlap penalty term is the dimensionless ratio obtained by dividing the sum of the spatial overlap volumes between all pairs of components by the sum of the sum of the volumes of all components and the minimum value of zero, rather than the intersection area of ​​two-dimensional polygons. To avoid the scale shift of the coupling term caused by changes in the number of adjacent component pairs, the first weighting coefficient can be preset and calibrated according to the number of adjacent component pairs, so that the overall coupling degree remains comparable under different component scales. The system energy function is equal to the adjacent component coupling term multiplied by the negative first weighting coefficient, plus the envelope area term multiplied by the positive second weighting coefficient, plus the overlap penalty term multiplied by the positive third weighting coefficient.

[0054] Simulated annealing is employed as a heuristic global optimization algorithm. The two-dimensional coordinates and rotation / yaw angles of each component in the initial panel layout are unfolded and concatenated into continuous state-space variables. The system energy function value is used as the target evaluation value for global space optimization iteration. The initial coupling matrix is ​​only used in the greedy phase to generate the initial panel layout and provide candidate boundary segmentation relationships. After the simulated annealing algorithm generates arbitrary continuous pose perturbations, the old scalar coupling degree in the initial coupling matrix is ​​no longer directly read. Instead, based on the current absolute coordinates and angles after the perturbation, the adjacency relationships of components are re-determined, the nearest or actually contacting boundary segmentation pairs between current adjacent components are re-established, and the scalar coupling degree under the current pose is dynamically updated according to the unified geometric compactness, reinforcement continuity, and demolding feasibility calculation rules in S2. Thus, the current pose, adjacency relationships, scalar coupling degree, and system energy function form a closed-loop update process.

[0055] At the current system temperature, a new pose is generated by randomly perturbing the state-space variables of a component. The adjacency relationships, current scalar coupling degree, panel layout envelope area ratio, and dimensionless component overlap penalty term are recalculated under the new pose, resulting in a new system energy function value. The energy difference is obtained by subtracting the new system energy function value from the energy function value before perturbation. If the energy difference is less than or equal to 0, the new pose is accepted; if the energy difference is greater than 0, the pose is determined according to probability. Accept the new position, among which For energy difference, The current system temperature is used. After multiple samplings based on the Markov chain length, the system temperature is updated using a cooling function until the current system temperature falls below a set minimum temperature threshold, or the system energy function variance is less than the convergence tolerance threshold for multiple consecutive cooling cycles, reaching an energy convergence state. The state-space variable matrix in the convergence state is extracted, and the optimized projected contour geometric data with absolute coordinates and angles are converted into two-dimensional engineering drawing format and saved. The optimized target skirted pile sleeve component assembly scheme is then output.

[0056] In some embodiments, a system energy function is constructed by weighting the sum of the scalar coupling degrees of adjacent components, the ratio of the panel layout envelope area, and the component overlap penalty term, including: Traverse the current panel layout, extract the scalar coupling degree between all adjacent paired components and sum them up to obtain the overall coupling degree sum; Calculate the area of ​​the minimum bounding rectangle that covers the orthogonal projections of all components in the current layout, and divide the area of ​​the rectangle by the sum of the orthogonal projection areas of all components to obtain the area ratio of the layout scheme. Calculate the total spatial overlap volume between all pairs of entities in the current layout, and divide the total spatial overlap volume by the sum of the total volume of all entity entities and the minimum value to obtain the dimensionless component overlap penalty term; The first weighting term is obtained by multiplying the sum of the overall coupling degree by a preset negative first weighting coefficient; The second weighting term is obtained by multiplying the area ratio of the layout scheme by a preset positive second weighting coefficient; The third weighting term is obtained by multiplying the component overlap penalty term by a preset positive third weighting coefficient; The system energy function is obtained by adding the first weighted term, the second weighted term, and the third weighted term.

[0057] In the subsequent global optimization process, a system energy function is constructed to evaluate the evolution. This function iterates through all component nodes and connecting edges within the current layout. For any pair of adjacent component entities that are geometrically aligned or whose distance is less than a preset adjacency threshold, the corresponding scalar coupling degree is dynamically extracted based on the current pose and accumulated. For example, if there are 10 pairs of seam connections in the layout scene, after the scores of each point are superimposed, the overall coupling degree is generated, for example, a combined output score of 8.5. Based on the coordinates of the limit points of the geometric outer boundary of all placed components in the current layout, the minimum bounding rectangle covering the boundaries of all components is generated. After obtaining the area of ​​this bounding rectangle, it is divided by the sum of the orthogonal projected areas of all components participating in the layout to derive the layout scheme's envelope area ratio. For example, a value of 1.25 represents an overall area utilization rate of 80%. A spatial collision detection algorithm is used to traverse the layout and calculate the sum of the spatial overlap volumes generated when component entities penetrate each other. Then, the sum of the spatial overlap volumes is divided by the sum of the total volume of all component entities and the sum of the minimum value to obtain the dimensionless component overlap penalty term.

[0058] The overall coupling degree is multiplied by a preset negative first weighting coefficient, which is set in the range of -1.0 to -0.5, for example, -0.8, to generate the first weighting term. The envelope area ratio parameter of the panel layout is extracted and multiplied by a preset positive second weighting coefficient, which is set in the range of 0.5 to 2.0, for example, 1.5, to generate the second weighting term. The component overlap penalty term is extracted and multiplied by a preset positive third weighting coefficient, with a magnitude range of 100 to 1000, for example, 500, to generate the third weighting term. Since the component overlap penalty term has already undergone volume normalization, the third weighting coefficient is used to express a strong constraint on entity overlap, and will not be directly used... The numerical value of the volume leads to an imbalance in the magnitude of the energy function. After the above three calculations are completed, the first weighted term, the second weighted term, and the third weighted term are algebraically superimposed and summed. The resulting comprehensive output is the system energy function determination value, which is used as the evaluation index of the objective function for subsequent optimization algorithm iterations.

[0059] The experiment used 50 different types of precast concrete component 3D models provided by a prefabricated building project as the dataset. The experimental conditions were set with a computing platform equipped with a 10-core processor and 32GB of memory; the substrate size was set to 12m × 8m. The first step length parameter was set to 100mm, the anchor point density threshold was set to 3, and the second step length was set to 20mm. In the energy function construction, the first weighting coefficient was set to -0.8, the second weighting coefficient to 1.5, and the third weighting coefficient to 500. The evaluation indicators for the ablation experiment were uniformly selected as substrate space utilization rate, average deviation of rebar alignment, and scheme generation time. The comparison results of the average deviation of rebar alignment are shown below. Figure 3 As shown, each set of values ​​corresponds to the operating status under different module combinations.

[0060] The baseline scheme, without discretization and system energy function optimization, achieves a substrate space utilization rate of 65.4%, an average rebar alignment deviation of 15.2 mm, and a scheme generation time of 18.5 s. Experimental results show that the ablation scheme with only the discretization module increases the substrate space utilization rate to 72.1%, reduces the average rebar alignment deviation to 4.8 mm, and achieves a scheme generation time of 24.3 s. The ablation scheme with only the energy function optimization module achieves a substrate space utilization rate of 81.6%, an average rebar alignment deviation of 12.7 mm, and a generation time of 36.2 s. The specific experimental data for the complete scheme of this application, including all core modules, are: a substrate space utilization rate of 86.9%, an average rebar alignment deviation of 3.1 mm, and a scheme generation time of 41.7 s.

[0061] The complete solution improves substrate space utilization by 21.5 percentage points compared to the baseline solution, and reduces the average rebar alignment deviation by 12.1 mm. The discretization module adds local discrete points to densely anchored areas, improving the geometric fidelity of rebar hole mapping during component splicing and reducing interference risks during assembly. The energy function optimization module uses the envelope area ratio of the panelization scheme and the dimensionless overlap penalty term for global constraints to drive the evolution of multi-component layout poses towards compactness, achieving a high degree of unity between demolding feasibility, panel compactness, and assembly alignment accuracy.

Claims

1. A method for digitally and automatically matching the assembly scheme of precast components for skirted pile sleeves, characterized in that, The matching method includes: S1, obtaining the three-dimensional models of all skirt pile sleeve components, discretizing the projection contour of the component on the base plate plane according to the distribution of the anchor points of the reserved lapped steel bars inside the three-dimensional model of each component, adding discrete points in the dense area of ​​anchor points, and obtaining the boundary segment set. S2. Construct an initial coupling matrix with component pairs and boundary segment pairs as spatial indices. For all pairings in the initial coupling matrix, calculate the coupling degree vector consisting of geometric compactness, reinforcement continuity, and demolding feasibility, and weight it to obtain the scalar coupling degree. Geometric compactness is calculated based on the area of ​​the local surplus material and the area of ​​the circumscribed convex hull of the pairing. Reinforcement continuity is calculated based on the spatial alignment and proximity of the reserved lapped reinforcement. Demolding feasibility is calculated based on the overlapping volume of the demolding interference zone between one component entity and another component. Based on the scalar coupling degree, a greedy algorithm is used to iteratively select the component and pose with the optimal scalar coupling degree with the already laid-out components to generate the initial panel layout. S3, starting from the initial layout, constructs a system energy function composed of the sum of the scalar coupling degree of adjacent components, the ratio of the envelope area of ​​the layout scheme, and the component overlap penalty term. A heuristic global optimization algorithm is used to perform global spatial optimization iteration on the poses of all components until the energy convergence state is reached, and the optimized target skirt sleeve component layout scheme is output.

2. The method for digital automatic matching of prefabricated skirt pile sleeve component assembly schemes according to claim 1, characterized in that, The discretization of the projected contour of the component on the substrate plane, and the addition of discrete points in the dense anchor point region to obtain the boundary segment set, includes: Obtain the orthogonal projection closed polygon of the 3D model of each component onto a 2D plane parallel to the substrate as the projection contour; sample along the projection contour at a fixed interval with a first step length to obtain initial discrete points; obtain the number of steel bar anchor points in the local area between adjacent initial discrete points; when the number is not less than a preset number threshold, insert supplementary discrete points in the boundary segment between adjacent initial discrete points with a second step length less than the first step length; connect all discrete points sequentially in a clockwise direction to generate a line segment composed of adjacent discrete points, which is set as the boundary segment set.

3. The method for digital automatic matching of prefabricated skirt pile sleeve component assembly schemes according to claim 1, characterized in that, The calculation of geometric compactness based on the paired local surplus area and the area of ​​the circumscribed convex hull includes: Obtain the non-overlapping closed internal two-dimensional region formed by the pairing of two boundary segments, and extract the area of ​​the region as the local surplus area; extract the two-dimensional coordinates of all discrete vertices on the projected contours of the two components after pairing, calculate the minimum area closed convex polygon covering all coordinates, and extract the area of ​​the polygon as the circumscribed convex hull area; divide the local surplus area by the sum of the circumscribed convex hull area and the minimum value to obtain the area ratio; calculate the difference between 1 and the area ratio as the geometric compactness.

4. The method for digital automatic matching of prefabricated skirt pile sleeve component assembly schemes according to claim 1, characterized in that, The calculation of rebar continuity based on the spatial alignment and proximity of reserved lapped rebars includes: Extract the first three-dimensional relative coordinates of the center of the reserved lapped rebar end face extending outward from the first component after pairing in the pairing local coordinate system; extract the second three-dimensional relative coordinates of the center of the preset insertion sleeve hole inside the second component after pairing in the pairing local coordinate system; map the first three-dimensional relative coordinates and the second three-dimensional relative coordinates one by one based on the principle of shortest spatial distance, calculate the sum of squares of the coordinate differences of each pairing node in the three-axis direction to obtain the squared value of Euclidean distance; sum the squared values ​​of Euclidean distance of all pairing nodes to obtain the total sum of squared distances, divide the squared value of the preset reference distance by the sum of the squared value of the preset reference distance, the total sum of squared distances and the minimum value of zero, and obtain the rebar continuity with a value in the range of 0 to 1.

5. The method for digital automatic matching of prefabricated skirt pile sleeve component assembly schemes according to claim 1, characterized in that, The calculation process for the envelope area ratio of the layout scheme includes: Calculate the area of ​​the minimum bounding rectangle that covers the orthogonal projections of all components in the current layout, and divide the area of ​​the rectangle by the sum of the orthogonal projection areas of all components to obtain the enveloping area ratio of the layout scheme.

6. The method for digital automatic matching of prefabricated skirt pile sleeve assembly schemes according to claim 1, characterized in that, The calculation process for demolding feasibility includes: selecting a three-dimensional normal direction perpendicular to the substrate plane and pointing upwards as the demolding stretching path; translating the first component solid model upwards along the stretching path by the maximum solid envelope height, and combining the space occupied by the entire translation process into an extended polyhedron as the demolding interference zone; obtaining the adjacent second component solid model, performing a three-dimensional Boolean intersection operation, obtaining the common intersection part between the second component solid model and the demolding interference zone, and calculating the volume of the intersection part as the overlap volume; when the overlap volume value is 0, the demolding feasibility is assigned a value of 1; when the overlap volume is greater than 0, the demolding feasibility is assigned a value of 0.

7. The method for digital automatic matching of prefabricated skirt pile sleeve component assembly schemes according to claim 1, characterized in that, The generation of the initial layout includes: The component with the largest base area from the un-paneled set is placed at the preset origin of the substrate as the reference component, added to the set of already laid-out components, and removed from the un-paneled set. An iterative loop is established: all components in the un-paneled set are traversed, the initial coupling matrix is ​​queried, and the scalar coupling degree of each un-paneled component when connected to each component in the set of already laid-out components through different boundary segment pairs is obtained. The un-paneled component with the largest scalar coupling degree and its relative pose, which includes two-dimensional translation and rotation dimensions, determined by the alignment relationship of the corresponding boundary segment pairs, are selected as the optimal component and optimal pose. The optimal component is arranged according to its optimal pose, added to the set of already laid-out components, and removed from the un-paneled set. This iterative loop is repeated until the un-paneled set is empty, and the initial panel layout composed of the set of already laid-out components is output.

8. The method for digital automatic matching of prefabricated skirt pile sleeve component assembly schemes according to claim 1, characterized in that, The state of energy convergence includes: After sampling multiple times according to the Markov chain length, the system temperature is updated using a cooling function until the current system temperature is lower than the set minimum temperature threshold, or the variance of the system energy function is less than the convergence tolerance threshold for multiple consecutive cooling cycles, at which point the energy convergence state is determined to be reached.

9. The method for digital automatic matching of prefabricated skirt pile sleeve assembly schemes according to claim 1, characterized in that, The calculation process for the component overlap penalty term includes: Calculate the total spatial overlap volume between all pairs of entities in the current layout, and divide the total spatial overlap volume by the sum of the total volume of all entity entities and the minimum value to obtain the dimensionless component overlap penalty term.

10. The method for digital automatic matching of prefabricated skirt pile sleeve assembly schemes according to claim 1, characterized in that, The process of constructing the system energy function includes: traversing the current panel layout, extracting and accumulating the scalar coupling degree between all adjacent paired components to obtain the overall coupling degree sum; multiplying the overall coupling degree sum by a preset negative first weight coefficient to obtain a first weighted term; multiplying the panel scheme envelope area ratio by a preset positive second weight coefficient to obtain a second weighted term; multiplying the component overlap penalty term by a preset positive third weight coefficient to obtain a third weighted term; and adding the first weighted term, the second weighted term, and the third weighted term to obtain the system energy function.

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