A cutting optimization method and system for EVA lining of tool box

Abstract

The present invention discloses a cutting optimization method and system for EVA linings for tool boxes, which relates to the field of cutting optimization technology. The method comprises: performing reverse dimensional compensation on the tool box lining based on the nonlinear shrinkage of the thermally cut material to obtain a pre-expansion compensation model; constructing a dynamic nesting boundary based on raw material design information, performing periodic nested splicing fitting of the pre-expansion compensation model to obtain multiple candidate cyclic splicing structures; outputting multiple candidate cutting paths for the multiple candidate cyclic splicing structures based on curve path planning fitting; calculating multiple material utilization rates for the multiple candidate cyclic splicing structures; performing cutting characteristic analysis based on the multiple material utilization rates and the multiple candidate cutting paths, screening out target nested segmentation structures, and executing cyclic segmentation of the EVA lining for the tool box. The present invention solves the technical problems of extensive typesetting layout and low material utilization in the prior art, achieving the technical effect of improving material utilization and reducing scrap rate.

Description

Technical Field

[0001] The present invention relates to the technical field of cutting optimization, and in particular to a cutting optimization method and system for an EVA liner for a tool box. Background Art

[0002] In the manufacturing process of EVA linings for tool boxes, cutting is typically performed on EVA sheets to create customizable storage. However, in existing processing procedures, such as the EVA material cutting device provided in CN219114126U, layout is often performed manually or using simple two-dimensional layout software. This lacks in-depth optimization based on the geometric characteristics of the lining structure and the actual dimensions of the raw sheet material. This results in a crude layout of the lining pattern on the sheet material, preventing the formation of an efficient spatial nesting pattern. This results in a large amount of unusable scrap material and low material utilization. Summary of the Invention

[0003] The present application provides a cutting optimization method and system for EVA linings for tool boxes, which are used to solve the technical problems of rough layout and low material utilization in the prior art.

[0004] In view of the above problems, the present application provides a cutting optimization method and system for EVA linings for tool boxes.

[0005] A first aspect of the present application provides a cutting optimization method for an EVA liner for a tool box, the method comprising:

[0006] Based on the nonlinear shrinkage of the thermally cut material, the tool box lining is reversely compensated for its size to obtain a pre-expansion compensation model; the raw material design information of the raw material plate is interactively obtained, and a dynamic nesting boundary is constructed according to the raw material design information; within the dynamic nesting boundary, periodic nested splicing fitting of the pre-expansion compensation model is performed to obtain a plurality of candidate cyclic splicing structures; based on the curve path planning fitting, a plurality of candidate cutting paths of the plurality of candidate cyclic splicing structures are output; based on the dynamic nesting boundary and the plurality of candidate cutting paths, a plurality of material utilization rates of the plurality of candidate cyclic splicing structures are calculated; based on the plurality of material utilization rates and the plurality of candidate cutting paths, a cutting characteristic analysis is performed to decide and screen out a target nested segmentation structure from the plurality of candidate cyclic splicing structures; and the target nested segmentation structure is used to perform cyclic segmentation of the EVA lining for the tool box.

[0007] A second aspect of the present application provides a cutting optimization system for an EVA liner for a tool box, the system comprising:

[0008] An inverse size compensation module is used to perform inverse size compensation on the tool box lining based on the nonlinear shrinkage of the thermal cutting material to obtain a pre-expansion compensation model; a nesting boundary construction module is used to interactively obtain the raw material design information of the raw material plate and construct a dynamic nesting boundary based on the raw material design information; a splicing fitting module is used to perform periodic nested splicing fitting of the pre-expansion compensation model within the dynamic nesting boundary to obtain multiple candidate cyclic splicing structures; a cutting path determination module is used to output multiple candidate cutting paths for the multiple candidate cyclic splicing structures based on curve path planning fitting; a utilization calculation module is used to calculate multiple material utilizations of the multiple candidate cyclic splicing structures based on the dynamic nesting boundary and the multiple candidate cutting paths; a cutting characteristic analysis module is used to perform cutting characteristic analysis based on the multiple material utilizations and the multiple candidate cutting paths to decide and screen out a target nested segmentation structure from the multiple candidate cyclic splicing structures; a loop segmentation module is used to use the target nested segmentation structure to perform loop segmentation of the EVA lining for the tool box.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] The present invention performs inverse dimensional compensation on a toolbox liner based on the nonlinear shrinkage of the thermally cut material to obtain a pre-expansion compensation model; interactively obtains raw material design information of the raw material sheet and constructs a dynamic nesting boundary based on the raw material design information; performs periodic nesting and splicing fitting of the pre-expansion compensation model within the dynamic nesting boundary to obtain multiple candidate cyclic splicing structures; outputs multiple candidate cutting paths for the multiple candidate cyclic splicing structures based on curve path planning fitting; calculates multiple material utilization rates for the multiple candidate cyclic splicing structures based on the dynamic nesting boundary and the multiple candidate cutting paths; performs cutting characteristic analysis based on the multiple material utilization rates and the multiple candidate cutting paths to determine a target nested segmentation structure from the multiple candidate cyclic splicing structures; and performs cyclic segmentation of the EVA liner for the toolbox using the target nested segmentation structure. The present invention solves the technical problems of crude layout and low material utilization in the prior art. By importing liner shape data and raw material size data, combining an optimization algorithm to perform periodic nesting arrangement and cutting path fitting, and dynamically adjusting cutting process parameters, the present invention achieves the technical effect of improving material utilization and reducing scrap rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0012] Figure 1 A schematic diagram of a process flow for optimizing a cutting method for an EVA liner for a tool box provided in an embodiment of the present application;

[0013] Figure 2 A schematic diagram of the structure of a cutting optimization system for an EVA liner for a tool box provided in an embodiment of the present application.

[0014] Explanation of the reference numerals: reverse size compensation module 11 , nested boundary construction module 12 , splicing and fitting module 13 , cutting path determination module 14 , utilization calculation module 15 , cutting characteristic analysis module 16 , loop segmentation module 17 . DETAILED DESCRIPTION

[0015] This application provides a cutting optimization method and system for EVA linings for tool boxes, aiming to solve the technical problems of rough layout and low material utilization in the existing technology. By importing lining shape data and raw material size data, combining optimization algorithms for periodic nested arrangement and cutting path fitting, and dynamically adjusting cutting process parameters, the technical effect of improving material utilization and reducing scrap rate is achieved.

[0016] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only some of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0017] It should be noted that any variations of the terms "include" and "have" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products or devices.

[0018] Example 1, as Figure 1 As shown, the present application provides a cutting optimization method for an EVA liner for a tool box, the method comprising:

[0019] Step S100: performing reverse dimension compensation on the tool box liner based on the nonlinear shrinkage of the thermally cut material to obtain a pre-expansion compensation model.

[0020] In an embodiment of the present application, by constructing a lining design model of the tool box EVA lining, combining the local cutting temperature field distribution and the thermal expansion coefficient of the EVA material, a nonlinear shrinkage model is established to characterize the dimensional change law during the thermal cutting process, and based on this model, the lining design model is reversely dimensional compensated, thereby generating a pre-expansion compensation model with the ability to correct thermal shrinkage errors.

[0021] Furthermore, in the method provided in the embodiment of the application, the tool box liner is subjected to reverse dimensional compensation based on the nonlinear shrinkage of the thermally cut material to obtain a pre-expansion compensation model, which also includes:

[0022] According to the lining structure design parameters of the tool box EVA lining, a lining design model is constructed; the cutting temperature field distribution is locally called, and a nonlinear shrinkage model is established according to the thermal expansion coefficient of the EVA material to be cut and the cutting temperature field distribution; the nonlinear shrinkage model is used to perform reverse dimensional compensation on the lining design model to generate the pre-expansion compensation model.

[0023] In an embodiment of the present application, first, based on the product design drawings of the EVA lining, the lining structure design parameters including the boundary contour, groove structure, slot position and depth are extracted, and a digital lining design model is established using a CAD modeling tool (such as SolidWorks or AutoCAD).

[0024] The cutting temperature field distribution is then called locally. To obtain the temperature distribution of the EVA material during the thermal cutting process, a finite element heat conduction simulation method is used. Through thermal simulation platforms such as ANSYS, cutting path data and process parameters (such as cutting speed, heat source diameter, and power density) are imported to perform two-dimensional planar thermal field modeling of the EVA sheet. During the simulation process, the material thermophysical properties (thermal conductivity, specific heat capacity, density) as well as convection and radiation boundary conditions are set, and a time-stepping simulation is performed. The output reflects the temperature changes on the surface and inside of the EVA sheet at each moment as the heat source moves along the cutting path. The final cutting temperature data is based on spatial coordinates and output as a heat distribution array with a time dimension, namely the cutting temperature field distribution.

[0025] Then, a nonlinear shrinkage model is established based on the thermal expansion coefficient of the EVA material to be cut and the cutting temperature field distribution. In this step, first, the thermal expansion coefficient α (e.g. 2×10⁻) is obtained by consulting the EVA material data sheet. 4 / °C), representing the expansion rate per unit length per 1°C increase. Then, using a point-by-point temperature mapping method, the temperature T(x,y) is extracted for each coordinate point (x,y) in the cutting temperature field distribution. The linear shrinkage rate at that location is calculated using the formula ε(x,y)=α×T(x,y). The shrinkage rate at each location is then decomposed along the x- and y-axes using the vector projection method. Specifically, the angle θ(x,y) between each point and the x-axis along the normal is set. Trigonometric functions are used to calculate the shrinkage offsets in the x- and y-directions: Δx(x,y)=ε(x,y)×L0×cosθ(x,y) and Δy(x,y)=ε(x,y)×L0×sinθ(x,y), respectively, where L0 is the reference unit length. By constructing Δx and Δy into vector form, a complete set of two-dimensional shrinkage vectors is constructed according to the coordinate system of the original design model, resulting in a nonlinear shrinkage model.

[0026] Finally, the nonlinear shrinkage model is used to perform inverse dimensional compensation on the lining design model. Using a coordinate offset method, all heat-affected contour points in the lining design model are translated inversely according to the offset vectors provided by the nonlinear shrinkage model. For example, if a point is expected to shrink by 0.5 mm, it is translated outward by 0.5 mm during modeling. The contour is geometrically expanded using a point-by-point correction method to complete the compensation operation and generate the final pre-expansion compensation model.

[0027] Step S200: interactively obtaining raw material design information of a raw material plate, and constructing a dynamic nesting boundary according to the raw material design information.

[0028] In the embodiment of the present application, the raw material design information of the raw material plate is first obtained interactively. The operator enters the basic parameters of the raw material plate, including length, width, thickness, edge treatment method, etc. through the human-computer interaction interface. At the same time, historical storage data can be automatically obtained through docking with the ERP or MES system, or standard plate information can be quickly imported through barcode scanning to form standardized raw material design information.

[0029] The system then locally calls edge tolerance correlation indicators, including cutting equipment accuracy and clamping mechanism errors. A material design model is then constructed based on the material design information. A rectangular effective processing area is then delineated from the material design model using the edge tolerance correlation indicators. Cutting edge boundary features are then interactively derived, and a thermal deformation buffer zone is constructed based on these features. Finally, the thermal deformation buffer zone is superimposed on the rectangular effective processing area to form a dynamically nested boundary.

[0030] Furthermore, in the method provided in the embodiment of the application, the raw material design information of the raw material plate is interactively obtained, and a dynamic nesting boundary is constructed based on the raw material design information, further comprising:

[0031] Locally call edge tolerance association indicators, wherein the edge tolerance association indicators include cutting equipment accuracy and clamping mechanism error; after constructing a raw material design model according to the raw material design information, delineate a rectangular effective processing area from the raw material design model according to the edge tolerance association indicators; interactively obtain cutting edge boundary features, and construct a thermal deformation buffer zone based on the cutting edge boundary features; superimpose the thermal deformation buffer zone on the rectangular effective processing area to obtain the dynamic nested boundary.

[0032] In this embodiment, edge tolerance-related indicators are first locally retrieved. Using a parameter table reading method, the system database's preset equipment error parameter table is used to retrieve the current cutting equipment's machining accuracy (e.g., positioning accuracy ±0.5mm) and clamping mechanism error (e.g., clamp edge obstruction 8mm). These indicators are measured during equipment commissioning or provided by the manufacturer, stored in a standard table format, and retrieved through the rule engine.

[0033] Then, a raw material design model is constructed based on the raw material design information. This modeling step adopts the CAD geometric modeling method, obtains key parameters such as the length, width, and thickness of the plate through the human-computer interaction interface, or calls the raw material information table through the ERP / MES system to generate standard plate specifications, and draws a two-dimensional rectangular boundary in the CAD modeling software (such as AutoCAD or SolidWorks) to form the raw material design model.

[0034] After modeling is complete, a rectangular effective processing area is delineated from the raw material design model based on edge tolerance-related indicators. This delineation utilizes an inward boundary offset method. Specifically, each boundary line representing the plate edge in the raw material design model is offset by a minimum safety margin calculated based on the accuracy of the used cutting equipment and the clamping mechanism error. For example, when the cutting accuracy is ±0.5mm and the clamping error is 8mm, an inward offset of ≥8.5mm is automatically applied, eliminating high-error risk areas and retaining the controllable central area, ultimately resulting in a rectangular effective processing area.

[0035] The cut edge boundary features are then interactively acquired through visual inspection or manual input. Specific methods include scanning the plate edge with a linear CCD camera to identify defects such as cracks, warping, and burning, or having an operator manually mark boundary defects within a visual interface. These features are recorded as coordinate points or bounding boxes and used as spatial interference sources for boundary safety correction.

[0036] Based on feature recognition, a thermal deformation buffer zone is constructed based on the cutting edge boundary features. This construction method uses a fixed expansion radius method, performing a geometric expansion operation on each identified defect area. For example, a rounded closed polygon is formed within a 10mm radius around the defect. This creates a thermal deformation buffer zone with thermal deformation isolation function, which is used to eliminate thermally unstable areas during layout.

[0037] Finally, the thermal deformation buffer zone is superimposed on the rectangular effective processing area. The superposition method uses Boolean set operations (such as difference operations) to eliminate the thermal deformation buffer zone from the rectangular effective processing area. This results in a spatial area that can be arranged after comprehensively considering the influence of equipment accuracy, clamping interference, and edge thermal deformation. The final output is a dynamic nesting boundary.

[0038] Furthermore, the method provided in the application embodiment also includes:

[0039] A linear array CCD camera is used to scan the surface of the raw material plate to locate multiple surface defect distributions; a circular forbidden grid is matched according to the size characteristics of the multiple surface defect distributions; the circular forbidden grid is used to cover the center of the circle with the multiple surface defect distributions as the center, and a global calibration of the forbidden grid is performed on the dynamic nesting boundary.

[0040] In the present embodiment, a linear array CCD camera is first used to scan the surface of the raw sheet material. This step involves setting the linear array CCD camera along a linear scanning trajectory, working with a mobile platform or synchronously following the motion path of a cutting machine, to capture high-resolution images of the entire sheet material surface. After image acquisition, image processing methods (such as edge detection, morphological analysis, and connected domain labeling) are used to analyze abnormal areas in the image and locate the distribution of multiple surface defects, including localized flaws such as indentations, bubbles, pits, and scratches. This defect information is output as a set of two-dimensional coordinate points, with each defect point corresponding to a set of location information and area dimensions.

[0041] Next, circular forbidden grids are matched based on the size characteristics of multiple surface defect distributions. To facilitate subsequent grid layout calculations, multiple standard circular grid units are pre-set (for example, three sizes with diameters of 5mm, 10mm, and 15mm). By comparing the maximum circumscribed diameter of each surface defect distribution, the smallest circular forbidden grid that is sufficient to completely cover the defect area is selected as the occlusion unit for the defect.

[0042] Then, with the distribution of multiple surface defects as the center of the circle, a circular forbidden grid is used to cover the center of the circle. That is, in the two-dimensional coordinate system of the raw material plate, with the center point of each defect as the center of the circle, a circular forbidden grid of the corresponding diameter is drawn, which is covered on the surface layer of the plate and forms a geometric occlusion relationship with the arrangement pattern. Finally, all the forbidden grids generated in this operation are summarized and globally calibrated at the dynamic nesting boundary. The calibration process traverses the two-dimensional coordinate system of the entire dynamic nesting boundary, records the position, coverage radius, center coordinates and number of each circular forbidden grid, and forms a unified spatial grid forbidden mapping table. The mapping result serves as the input hard constraint of the nested optimization algorithm and path planning engine to complete the global calibration of the forbidden grid.

[0043] Step S300: performing periodic nested splicing fitting of the pre-expansion compensation model within the dynamic nesting boundary to obtain a plurality of candidate cyclic splicing structures.

[0044] In an embodiment of the present application, when performing periodic nested splicing fitting on the pre-expansion compensation model within a dynamic nesting boundary, the basic geometric units and transition connection structures are first extracted through topological analysis; then, a nested repetition rule consisting of a translation repetition restriction and a rotation repetition restriction is predefined; under the constraints of this rule, the basic geometric units are first equidistantly replicated in the biaxial direction to generate M translational cyclic splicing structures; then, based on the rotational repetition restriction, the transition connection structure is rotated and replicated within the dislocated area to form M groups of rotational cyclic splicing structures; finally, the translation and rotation structures are mapped and combined to output multiple candidate cyclic splicing structures.

[0045] Furthermore, in the method provided in the embodiment of the application, performing periodic nested splicing fitting of the pre-expansion compensation model within the dynamic nesting boundary to obtain multiple candidate cyclic splicing structures further includes:

[0046] A topological analysis is performed on the pre-expansion compensation model to extract basic geometric units and transition connection structures; a nested repetition rule is predefined, wherein the nested repetition rule is composed of a translation repetition restriction and a rotation repetition restriction; based on the translation repetition restriction, bidirectional equidistant replication of the basic geometric units is performed along the Y-axis and the X-axis at the dynamic nesting boundary until a nested loop occurs, and M translational cyclic splicing structures are output; based on the rotation repetition restriction, staggered replication of the transition connection structure is performed at the dynamic nesting boundary and the M staggered spatial distributions of the M translational cyclic splicing structures until a nested loop occurs, and M groups of rotational cyclic splicing structures are output; and the M translational cyclic splicing structures and the M groups of rotational cyclic splicing structures are mapped and combined to obtain the multiple candidate cyclic splicing structures.

[0047] In an embodiment of the present application, a topological analysis is first performed on the pre-expansion compensation model to extract basic geometric units and transition connection structures. This step adopts a boundary contour decomposition method. By calling the boundary recognition tool in the CAD modeling software, the two-dimensional contour of the pre-expansion compensation model is split, and the closed and repeatable main graphics are identified as basic geometric units, and the auxiliary bridging structure connecting the two units is identified as a transition connection structure.

[0048] The nested replication rules are then predefined, consisting of translational and rotational replication limits. This process uses a parameter-based approach, with the user setting the parameters controlling the nested replication behavior within the interface. Translational replication limits ensure that elements do not overlap by setting the minimum repetition spacing along the X and Y axes. Rotational replication limits control the rotational adaptation of transitional structures within boundary gaps by limiting the permissible rotation angles (e.g., 90° and 180°).

[0049] Then, based on the translation repetition limit, the basic geometric units are bidirectionally and equidistantly replicated along the Y and X directions at the dynamic nesting boundary until the nesting loop is reached, outputting M translational and cyclic splicing structures. This operation uses the equidistant array replication method, calling the 2D graphic replication command in the layout module to arrange the basic geometric units along the X and Y axes based on the set step size until the dynamic nesting boundary is filled. The replication endpoint is automatically identified and M translational and cyclic splicing structures with uniform direction and compact structure are output.

[0050] On this basis, to fill the local misalignment gaps between the M translational cyclic splicing structures, the transitional connection structure is replicated based on rotational repetition constraints within the dynamic nesting boundary and the M misaligned spaces of the M translational cyclic splicing structures, until the nesting loop is complete. This process uses an angular rotation matching method to rotate the transitional connection structure by a limited angle (e.g., ±90°) according to the rotational repetition constraints and attempt to embed it into corners or diagonal areas not covered by the translational structure until all matching positions within the dynamic nesting boundary are filled, outputting M sets of rotated cyclic splicing structures.

[0051] Finally, M translational cyclic splicing structures and M groups of rotational cyclic splicing structures are mapped and combined. In this process, the basic geometric units and transition connection structures are restored to the standard structural proportional characteristics used for calculation in the pre-expansion compensation model, which are used as the nested structure evaluation benchmark. After mapping and combining M translational cyclic splicing structures and M groups of rotational cyclic splicing structures, the real-time structural proportional characteristics of each group of combined structures are calculated. Each group of real-time structural proportional characteristics is then compared with the standard structural proportional characteristics to screen out structural combinations that meet the set proportional accuracy requirements, ultimately obtaining multiple candidate cyclic splicing structures.

[0052] Furthermore, in the method provided in the embodiment of the application, mapping and combining the M translation cyclic splicing structures and the M groups of rotation cyclic splicing structures to obtain the multiple candidate cyclic splicing structures further includes:

[0053] The basic geometric unit and the transition connection structure are restored to the pre-expansion compensation model to calculate the standard structural proportional characteristics; after mapping and combining the M translational cyclic splicing structures and the M groups of rotational cyclic splicing structures, M groups of real-time structural proportional characteristics are calculated and output; and the multiple candidate cyclic splicing structures are screened based on whether the M groups of real-time structural proportional characteristics meet the standard structural proportional characteristics, wherein each candidate cyclic splicing structure consists of a translational cyclic splicing structure and a rotational cyclic splicing structure.

[0054] In this embodiment, the basic geometric units and transitional connection structures are first restored to a pre-expansion compensation model to calculate the standard structural proportional characteristics. This step utilizes a graphical configuration restoration method. The pre-expansion compensation model's initial design state is retrieved within the modeling software. Using the primitive grouping function, the basic geometric units and transitional connection structures are extracted as two component sets. The two-dimensional geometric properties of the two types of structures are then calculated, including area, boundary length, principal axis length, and relative connection boundary length between structures. The proportion of each type of structure within the original model is then calculated, normalized using the total structural area as the basis, and the output is the standard structural proportional characteristics.

[0055] After mapping and combining M translational cyclic splicing structures and M groups of rotational cyclic splicing structures, M sets of real-time structural proportional features are calculated and output. This step uses a structural splicing analysis method to sequentially merge the M translational cyclic splicing structures with the M groups of rotational cyclic splicing structures to form M sets of nested combined structures. Using the geometric measurement tools in the CAD platform, the basic geometric units and transitional connecting structures in each structural combination are graphically identified, and their areas, side lengths, and joint boundary lengths are measured. A normalization method is then used to convert the measured values ​​of each structural category into their relative proportions within the combined structure, thereby calculating M sets of real-time structural proportional features.

[0056] Finally, multiple candidate cyclic splicing structures are screened based on whether the M sets of real-time structural ratio characteristics meet the standard structural ratio characteristics. This step uses a quantitative ratio consistency determination method to simplify the ratios of the M sets of real-time structural ratios and the standard structural ratios to determine whether they form the same proportional relationship as the standard ratio. For example, if the standard structural ratio is 2:3 and the quantitative ratio of a splicing structure group is 4:6, it is considered to meet the standard ratio; if it is 5:8, it is not met. To account for possible differences in the number of structures in the residual space of actual splicing edges or corners, a limited integer difference tolerance range is set. That is, if the quantitative ratio error between the basic geometric unit and the transition connection structure is within ±1 structural unit (for example, the ratio should be 4:6, but it is actually 4:5 or 4:7), it can also be considered to approximately meet the standard ratio. Here, ±1 unit means that the number of any type of structure differs from its expected ratio by at most 1 in the integer dimension. Splicing structures outside this range are eliminated. Finally, multiple candidate cyclic splicing structures are screened and output, each of which consists of a set of translational cyclic splicing structures and a set of rotational cyclic splicing structures.

[0057] Step S400: outputting a plurality of candidate cutting paths of the plurality of candidate cyclic splicing structures based on curve path planning and fitting.

[0058] In an embodiment of the present application, in order to convert multiple candidate cyclic splicing structures into path data that can be used for actual thermal cutting, a continuous and feasible curve trajectory is generated according to the structural boundary characteristics, which is specifically achieved by outputting multiple candidate cutting paths of the multiple candidate cyclic splicing structures based on curve path planning fitting.

[0059] Specifically, a boundary contour extraction method is first used to perform two-dimensional contour recognition on each candidate circular splicing structure. Graphics processing tools are then used to perform line segment recognition on its outer contour and internal hole contours, obtaining a continuous sequence of boundary points that constitute the basic geometric units and transition connection structures. A curve fitting method is then used to fit the extracted boundary point sequence, converting it from a multi-segment broken line into a continuous smooth curve. B-spline fitting or least squares fitting is primarily used to ensure good continuity and smoothness during the machining process. Cutting path data is then generated for each fitted curve, which is output as a candidate path for the splicing structure. Finally, path generation is completed for each candidate circular splicing structure, resulting in multiple candidate cutting paths that correspond to it.

[0060] Step S500: Calculating multiple material utilization rates of the multiple candidate cyclic splicing structures based on the dynamic nesting boundary and multiple candidate cutting paths.

[0061] In an embodiment of the present application, when calculating multiple material utilization rates for multiple candidate loop splicing structures based on a dynamic nesting boundary and multiple candidate cutting paths, the dynamic nesting boundary is first gridded according to a preset scale to construct a standard grid matrix. The multiple candidate loop splicing structures are then projected onto this grid matrix to identify the first-level abandoned grids not covered by valid structures. Subsequently, multiple candidate cutting paths are introduced, and the path gap areas in the first-level abandoned grids are deducted to obtain the second-level abandoned grid distribution. Finally, the material utilization rate corresponding to each group of candidate loop splicing structures is calculated and output based on the ratio of the total number of grids in the dynamic nesting boundary to the number of valid retained grids. Through this process, multiple material utilization rates for multiple candidate loop splicing structures are obtained.

[0062] Furthermore, in the method provided in the embodiment of the application, the material utilization rates of the plurality of candidate cyclic splicing structures are calculated based on the dynamic nesting boundary and the plurality of candidate cutting paths, and further includes:

[0063] The dynamic nesting boundary is discretized into a grid matrix of a preset scale; the multiple candidate cyclic splicing structures are projected onto the grid matrix to locate multiple first-level abandoned grid distributions; the multiple candidate cutting paths are projected onto the multiple first-level abandoned grid distributions to perform path gap deduction to obtain multiple second-level abandoned grid distributions; the volume ratio of the dynamic nesting boundary to the multiple second-level abandoned grid distributions is calculated, and the multiple material utilization rates are output.

[0064] In an embodiment of the present application, the dynamic nesting boundary is first discretized into a grid matrix of a preset scale, and a regular grid division method is used to perform planar segmentation of the dynamic nesting boundary in two-dimensional space with squares of fixed side length (for example, 1 mm) as units to construct a grid matrix covering the entire nesting area.

[0065] After rasterization is complete, multiple candidate cyclic splicing structures are projected onto a grid matrix to locate multiple first-level abandoned grid distributions. This step uses a structural graph projection method to project the two-dimensional boundary information of each candidate cyclic splicing structure onto the grid matrix. The occupancy status of the grid is determined by determining whether the grid center falls within the structure outline. Grids not covered by any candidate cyclic splicing structures are uniformly marked as first-level abandoned grid distributions, representing areas that are not actually used in the structural arrangement.

[0066] The multiple candidate cutting paths are then projected onto multiple first-level discarded grid distributions for path gap subtraction, resulting in multiple second-level discarded grid distributions. This step utilizes a path buffer zone subtraction method. Based on the centerline of each candidate cutting path, the kerf width (e.g., 0.8 mm) is expanded outward to form a thermal cutting impact range, which is then projected onto the first-level discarded grid distribution. If the path buffer range overlaps with a first-level discarded grid, that grid is marked as a second-level discarded grid distribution, indicating material waste due to thermal impact from the cutting path or path gaps.

[0067] Finally, the volume ratio of the dynamic nesting boundary to the distribution of multiple secondary abandoned grids is calculated. This step uses a grid volume ratio calculation method, using the total number of grids in the dynamic nesting boundary as the total area benchmark. The number of secondary abandoned grids corresponding to each group is deducted to obtain the number of effectively used grids. This ratio is then calculated with the total number of grids to determine the material utilization rate for each candidate circular splicing structure. This process outputs multiple material utilization rates.

[0068] Furthermore, in the method provided in the embodiment of the application, the volume ratio of the dynamic nesting boundary to the distribution of multiple secondary abandoned grids is calculated, and the multiple material utilization rates are output, further comprising:

[0069] Interactively obtain an EVA pad design; use the EVA pad design to reuse the multiple secondary abandoned grid distributions to obtain multiple tertiary abandoned grid distributions; calculate the volume ratio of the dynamic nesting boundary to the multiple tertiary abandoned grid distributions, and output multiple updated material utilization rates; use the multiple updated material utilization rates to replace the material utilization rate for cutting characteristic analysis.

[0070] In this embodiment, an EVA pad design is first interactively obtained. Using a graphical template call method, a preset library of standard pad templates is retrieved through a human-computer interface, or an operator manually imports dimensioned padding graphic files. These graphics include commonly used circles, anti-slip sheets, and rectangular filler blocks, which are then reused as layout objects. The imported EVA pad design is then converted into a nestable 2D outline set, and attributes such as size parameters, rotatability, and edge spacing constraints are bound to facilitate layout.

[0071] The EVA padding design is then used to recalculate the distribution of multiple secondary abandoned grids. Using a spatial nesting arrangement method, EVA padding patterns are individually placed in the corresponding free areas of the secondary abandoned grids. Based on the spatial topology data of the secondary abandoned grids, the boundaries of the continuous available areas are identified. Heuristic nesting algorithms (such as the maximum empty rectangle method) are then used to fill and arrange the patterns according to the pattern size, rotation angle, and minimum margin rules. Areas where padding patterns are successfully placed are marked as utilized, and the remaining free grids that failed to be nested are retained as the third-level abandoned grid distribution. This process results in multiple third-level abandoned grid distributions.

[0072] Next, the volume ratio of the dynamic nesting boundary to the distribution of multiple third-level abandoned grids is calculated, outputting multiple updated material utilization rates. This process uses the discrete area difference ratio method. First, the total number of grids divided by the dynamic nesting boundary is counted as the base area unit, and then the number of third-level abandoned grids in each group is counted. The updated material utilization rate is calculated and output using the formula: Updated Material Utilization Rate = 1 - Number of Third-Level Abandoned Grids / Total Number of Grids. This ratio reflects the overall panel utilization efficiency after reuse, including the main structure and EVA padding.

[0073] Finally, multiple updated material utilization rates are used to replace the material utilization rates for cutting characteristic analysis. The utilization-driven characteristic reanalysis method is used to update the indicator fields in the raw material utilization data table to the corresponding updated material utilization rates, and the cutting performance analysis associated with the candidate circular splicing structure is re-performed.

[0074] Step S600: performing cutting characteristic analysis based on the multiple material utilization rates and the multiple candidate cutting paths to select a target nested segmentation structure from the multiple candidate cyclic splicing structures.

[0075] In an embodiment of the present application, in order to select a target nested segmentation structure from multiple candidate loop splicing structure decisions, each group of candidate cutting paths is first run, the EVA lining cutting process is fitted, and the path corner radius sequence, cutting load sequence and cutting breakpoint sequence that form the structural path characteristics are extracted to comprehensively characterize the path smoothness, energy consumption fluctuation and cutting continuity; then, the proportion of continuous cutting segments is statistically analyzed based on the cutting breakpoint sequence, the path corner radius discreteness is calculated through the corner data, and the load fluctuation coefficient is obtained for the load sequence, which respectively reflect the path interruption frequency, trajectory complexity and cutting stability; then, the above three path characteristic indicators are fused and mapped with the corresponding material utilization rate of each group to form a unified evaluation basis, namely the candidate cutting availability coefficient; finally, according to the serialized sorting result of the availability coefficient, the optimal target nested segmentation structure is selected from all candidate loop splicing structures.

[0076] Furthermore, in the method provided in the embodiment of the application, cutting characteristics analysis is performed based on the multiple material utilization rates and the multiple candidate cutting paths to select a target nested segmentation structure from the multiple candidate cyclic splicing structures, and further includes:

[0077] Run the multiple candidate cutting paths to perform EVA lining cutting fitting, and output multiple path corner radius sequences, multiple cutting load sequences, and multiple cutting breakpoint sequences; calculate and output multiple continuous cutting segment proportions based on the multiple cutting breakpoint sequences; calculate and output multiple path corner radius discreteness based on the multiple path corner radius sequences; calculate multiple load fluctuation coefficients of the multiple cutting load sequences; obtain multiple candidate cutting availability coefficients by mapping and weighted fusion of the multiple material utilization rates, the multiple continuous cutting segment proportions, the multiple path corner radius discreteness, and the multiple load fluctuation coefficients; and call the target nested segmentation structure from the multiple candidate cyclic splicing structure mapping according to the serialized results of the multiple candidate cutting availability coefficients.

[0078] In an embodiment of the present application, a plurality of candidate cutting paths are first run to perform EVA lining cutting fitting. Specifically, the actual sample cutting method is adopted, each set of candidate cutting paths is loaded into the CNC cutting equipment, and the cutting operation is performed directly on the EVA sheet sample, while the control system log and sensor data of the equipment are called. By reading the cutter head motion control instructions and position feedback values, all turning points in the path are extracted, and the arc transition curvature between adjacent path segments is calculated, and the output is a plurality of path corner radius sequences, which are used to characterize the smoothness of the path change. At the same time, the power feedback signal and the running time are read, and the power per unit time is calculated by the path segment and multiplied by the segment length, and the output is a plurality of cutting load sequences, which are used to record the thermal energy input intensity of each path segment in the actual processing. Combined with the cutting head start and stop signal and the position change data, the start point and stop point in the path are detected, the position of the non-continuous segment is identified, and the output is a plurality of cutting breakpoint sequences, which are used to describe the continuity of the path.

[0079] The algorithm then calculates and outputs the proportions of multiple continuous cutting segments based on multiple cutting breakpoint sequences. Using a threshold segmentation method, each path is divided into several segments based on the cutting breakpoints. Valid cutting segments with a continuous length of at least 50 mm are selected, and the ratio of their total length to the entire path length is calculated. This is output as the proportion of multiple continuous cutting segments, reflecting the proportion of sustainable cutting segments in the path. Subsequently, the algorithm calculates and outputs the discreteness of multiple path corner radii based on multiple path corner radius sequences. Using standard deviation statistics, a variance analysis is performed on each set of path corner radius data to calculate the consistency of its variation range. The discreteness of multiple path corner radii is then output, used to assess the smoothness of corner changes in the path.

[0080] Next, multiple load fluctuation coefficients of multiple cutting load sequences are calculated. The mean and standard deviation of each group of cutting load sequences are calculated using the mean-standard deviation ratio method. Multiple load fluctuation coefficients are obtained by dividing the standard deviation by the mean value. These coefficients are used to measure thermal load stability. The lower the value, the more uniform the power output and the more stable the temperature rise control during the processing.

[0081] After completing the above feature extraction, the multiple material utilization rates, multiple continuous cutting segment proportions, multiple path corner radius discreteness and multiple load fluctuation coefficients are mapped and weightedly fused, and the normalized scoring and weighted summation method is adopted to uniformly convert the four indicators into a score value between 0 and 1. Combined with the weight ratio (for example, material utilization rate 30%, continuous cutting segment proportion 30%, path corner radius discreteness 20%, load fluctuation coefficient 20%), the candidate cutting availability coefficient of each group of structures is comprehensively obtained to reflect the overall applicability of the structure in actual processing.

[0082] Finally, according to the serialization results of multiple candidate cutting availability coefficients, the target nested segmentation structure is mapped and called from multiple candidate loop splicing structures. The sorting and screening method is used to arrange all candidate structures from high to low according to the availability coefficient, and the structure with the highest score is selected as the target nested segmentation structure for the final EVA lining cutting execution.

[0083] Step S700: Execute loop segmentation of the EVA lining for the tool box using the target nested segmentation structure.

[0084] In an embodiment of the present application, after determining the target nested segmentation structure, the target nested segmentation structure is used to perform cyclic segmentation of the EVA lining for the tool box. Specifically, the cutting path data corresponding to the basic geometric units and transition connection structures contained in the target nested segmentation structure are sent to the CNC cutting equipment, and the control equipment is controlled to perform processing on the EVA sheet along a preset path trajectory. The cutting equipment executes the path group by group according to the arrangement of the target nested segmentation structure within the dynamic nesting boundary, and repeats the arrangement on the raw material sheet to complete the segmentation of multiple structural units. By continuously executing the target nested segmentation structure, cyclic segmentation processing of the entire EVA raw material area is achieved, and batch molding of the tool box lining structure is completed.

[0085] In the embodiments of the present application, in summary, the embodiments of the present application have at least the following technical effects:

[0086] The present invention performs inverse dimensional compensation on a toolbox liner based on the nonlinear shrinkage of the thermally cut material to obtain a pre-expansion compensation model; interactively obtains raw material design information of the raw material sheet and constructs a dynamic nesting boundary based on the raw material design information; performs periodic nesting and splicing fitting of the pre-expansion compensation model within the dynamic nesting boundary to obtain multiple candidate cyclic splicing structures; outputs multiple candidate cutting paths for the multiple candidate cyclic splicing structures based on curve path planning fitting; calculates multiple material utilization rates for the multiple candidate cyclic splicing structures based on the dynamic nesting boundary and the multiple candidate cutting paths; performs cutting characteristic analysis based on the multiple material utilization rates and the multiple candidate cutting paths to determine a target nested segmentation structure from the multiple candidate cyclic splicing structures; and performs cyclic segmentation of the EVA liner for the toolbox using the target nested segmentation structure. The present invention solves the technical problems of crude layout and low material utilization in the prior art. By importing liner shape data and raw material size data, combining an optimization algorithm to perform periodic nesting arrangement and cutting path fitting, and dynamically adjusting cutting process parameters, the present invention achieves the technical effect of improving material utilization and reducing scrap rate.

[0087] Example 2, based on the same inventive concept as the cutting optimization method for an EVA liner for a tool box in the above embodiment, Figure 2 As shown, the present application provides a cutting optimization system for EVA liners for tool boxes. The system and method embodiments in the present application are based on the same inventive concept. The system includes:

[0088] The inverse size compensation module 11 is used to perform inverse size compensation on the tool box lining based on the nonlinear shrinkage of the thermal cutting material to obtain a pre-expansion compensation model; the nesting boundary construction module 12 is used to interactively obtain the raw material design information of the raw material plate and construct a dynamic nesting boundary based on the raw material design information; the splicing fitting module 13 is used to perform periodic nested splicing fitting of the pre-expansion compensation model within the dynamic nesting boundary to obtain multiple candidate cyclic splicing structures; the cutting path determination module 14 is used to output multiple candidate cutting paths for the multiple candidate cyclic splicing structures based on curve path planning fitting; the utilization calculation module 15 is used to calculate multiple material utilizations of the multiple candidate cyclic splicing structures based on the dynamic nesting boundary and the multiple candidate cutting paths; the cutting characteristic analysis module 16 is used to perform cutting characteristic analysis based on the multiple material utilizations and the multiple candidate cutting paths to decide and screen out the target nested segmentation structure from the multiple candidate cyclic splicing structures; the loop segmentation module 17 is used to use the target nested segmentation structure to perform loop segmentation of the EVA lining for the tool box.

[0089] Furthermore, the system is also used to implement the following functions:

[0090] According to the lining structure design parameters of the tool box EVA lining, a lining design model is constructed; the cutting temperature field distribution is locally called, and a nonlinear shrinkage model is established according to the thermal expansion coefficient of the EVA material to be cut and the cutting temperature field distribution; the nonlinear shrinkage model is used to perform reverse dimensional compensation on the lining design model to generate the pre-expansion compensation model.

[0091] Furthermore, the system is also used to implement the following functions:

[0092] Locally call edge tolerance association indicators, wherein the edge tolerance association indicators include cutting equipment accuracy and clamping mechanism error; after constructing a raw material design model according to the raw material design information, delineate a rectangular effective processing area from the raw material design model according to the edge tolerance association indicators; interactively obtain cutting edge boundary features, and construct a thermal deformation buffer zone based on the cutting edge boundary features; superimpose the thermal deformation buffer zone on the rectangular effective processing area to obtain the dynamic nested boundary.

[0093] Furthermore, the system is also used to implement the following functions:

[0094] A linear array CCD camera is used to scan the surface of the raw material plate to locate multiple surface defect distributions; a circular forbidden grid is matched according to the size characteristics of the multiple surface defect distributions; the circular forbidden grid is used to cover the center of the circle with the multiple surface defect distributions as the center, and a global calibration of the forbidden grid is performed on the dynamic nesting boundary.

[0095] Furthermore, the system is also used to implement the following functions:

[0096] A topological analysis is performed on the pre-expansion compensation model to extract basic geometric units and transition connection structures; a nested repetition rule is predefined, wherein the nested repetition rule is composed of a translation repetition restriction and a rotation repetition restriction; based on the translation repetition restriction, bidirectional equidistant replication of the basic geometric units is performed along the Y-axis and the X-axis at the dynamic nesting boundary until a nested loop occurs, and M translational cyclic splicing structures are output; based on the rotation repetition restriction, staggered replication of the transition connection structure is performed at the dynamic nesting boundary and the M staggered spatial distributions of the M translational cyclic splicing structures until a nested loop occurs, and M groups of rotational cyclic splicing structures are output; and the M translational cyclic splicing structures and the M groups of rotational cyclic splicing structures are mapped and combined to obtain the multiple candidate cyclic splicing structures.

[0097] Furthermore, the system is also used to implement the following functions:

[0098] The basic geometric unit and the transition connection structure are restored to the pre-expansion compensation model to calculate the standard structural proportional characteristics; after mapping and combining the M translational cyclic splicing structures and the M groups of rotational cyclic splicing structures, M groups of real-time structural proportional characteristics are calculated and output; and the multiple candidate cyclic splicing structures are screened based on whether the M groups of real-time structural proportional characteristics meet the standard structural proportional characteristics, wherein each candidate cyclic splicing structure consists of a translational cyclic splicing structure and a rotational cyclic splicing structure.

[0099] Furthermore, the system is also used to implement the following functions:

[0100] The dynamic nesting boundary is discretized into a grid matrix of a preset scale; the multiple candidate cyclic splicing structures are projected onto the grid matrix to locate multiple first-level abandoned grid distributions; the multiple candidate cutting paths are projected onto the multiple first-level abandoned grid distributions to perform path gap deduction to obtain multiple second-level abandoned grid distributions; the volume ratio of the dynamic nesting boundary to the multiple second-level abandoned grid distributions is calculated, and the multiple material utilization rates are output.

[0101] Furthermore, the system is also used to implement the following functions:

[0102] Interactively obtain an EVA pad design; use the EVA pad design to reuse the multiple secondary abandoned grid distributions to obtain multiple tertiary abandoned grid distributions; calculate the volume ratio of the dynamic nesting boundary to the multiple tertiary abandoned grid distributions, and output multiple updated material utilization rates; use the multiple updated material utilization rates to replace the material utilization rate for cutting characteristic analysis.

[0103] Furthermore, the system is also used to implement the following functions:

[0104] Run the multiple candidate cutting paths to perform EVA lining cutting fitting, and output multiple path corner radius sequences, multiple cutting load sequences, and multiple cutting breakpoint sequences; calculate and output multiple continuous cutting segment proportions based on the multiple cutting breakpoint sequences; calculate and output multiple path corner radius discreteness based on the multiple path corner radius sequences; calculate multiple load fluctuation coefficients of the multiple cutting load sequences; obtain multiple candidate cutting availability coefficients by mapping and weighted fusion of the multiple material utilization rates, the multiple continuous cutting segment proportions, the multiple path corner radius discreteness, and the multiple load fluctuation coefficients; and call the target nested segmentation structure from the multiple candidate cyclic splicing structure mapping according to the serialized results of the multiple candidate cutting availability coefficients.

[0105] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential sequence shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0106] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

[0107] This specification and drawings are merely illustrative of the present application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Obviously, those skilled in the art may make various modifications and variations to this application without departing from the scope of this application. Thus, this application is intended to include such modifications and variations as fall within the scope of this application and its equivalents.

Claims

1. A cutting optimization method for EVA lining for tool boxes, characterized in that: The method comprises: Based on the nonlinear shrinkage of the thermally cut material, the tool box liner is inversely compensated to obtain a pre-expansion compensation model. interactively obtaining raw material design information of the raw material plate, and constructing a dynamic nesting boundary based on the raw material design information; Performing periodic nested splicing fitting of the pre-expansion compensation model within the dynamic nesting boundary to obtain a plurality of candidate cyclic splicing structures; Outputting multiple candidate cutting paths for the multiple candidate cyclic splicing structures based on curve path planning fitting; Calculating multiple material utilization rates of the multiple candidate cyclic splicing structures according to the dynamic nesting boundary and the multiple candidate cutting paths; Performing a cutting characteristic analysis based on the multiple material utilization rates and the multiple candidate cutting paths to select a target nested segmentation structure from the multiple candidate cyclic splicing structures, the method comprising: Running the multiple candidate cutting paths to perform EVA liner cutting fitting, and outputting multiple path corner radius sequences, multiple cutting load sequences, and multiple cutting breakpoint sequences; Calculating and outputting a plurality of continuous cutting segment proportions based on the plurality of cutting breakpoint sequences; Calculate and output a plurality of path corner radius discretenesses based on the plurality of path corner radius sequences; calculating a plurality of load fluctuation coefficients of the plurality of cutting load sequences; Obtaining multiple candidate cutting availability coefficients by mapping and weighting the multiple material utilization rates, the multiple continuous cutting segment proportions, the multiple path corner radius discretenesses, and the multiple load fluctuation coefficients; According to the serialization results of the plurality of candidate cutting availability coefficients, mapping and calling the target nested segmentation structure from the plurality of candidate loop splicing structures; The target nested segmentation structure is used to perform loop segmentation of the EVA lining of the tool box.

2. The cutting optimization method for an EVA liner for a tool box according to claim 1, characterized in that: Performing reverse dimension compensation on the tool box liner based on the nonlinear shrinkage of the thermally cut material to obtain a pre-expansion compensation model, the method comprising: According to the lining structure design parameters of the tool box EVA lining, the lining design model is constructed; Locally calling the cutting temperature field distribution, and establishing a nonlinear shrinkage model according to the thermal expansion coefficient of the EVA material to be cut and the cutting temperature field distribution; The nonlinear shrinkage model is used to perform inverse size compensation on the lining design model to generate the pre-expansion compensation model.

3. The cutting optimization method for an EVA liner for a tool box according to claim 1, characterized in that: Interactively obtaining raw material design information of a raw material plate and constructing a dynamic nesting boundary based on the raw material design information, the method comprising: Locally calling edge tolerance related indicators, wherein the edge tolerance related indicators include cutting equipment accuracy and clamping mechanism error; After constructing a raw material design model according to the raw material design information, a rectangular effective processing area is delineated from the raw material design model according to the edge tolerance correlation index; interactively obtaining cutting edge boundary features, and constructing a thermal deformation buffer zone according to the cutting edge boundary features; The thermal deformation buffer zone is superimposed on the rectangular effective processing area to obtain the dynamic nesting boundary.

4. The cutting optimization method for an EVA liner for a tool box according to claim 3, characterized in that: The method further comprises: Scanning the surface of the raw material plate using a linear array CCD camera to locate the distribution of multiple surface defects; Matching a circular disabled grid according to size characteristics of the plurality of surface defect distributions; The plurality of surface defect distributions are used as the center of a circle, the circular forbidden grid is used to perform circle center coverage, and a forbidden grid global calibration is performed at the dynamic nesting boundary.

5. The cutting optimization method for an EVA liner for a tool box according to claim 1, characterized in that: Performing periodic nested splicing fitting of the pre-expansion compensation model within the dynamic nesting boundary to obtain a plurality of candidate cyclic splicing structures, the method comprising: performing a topological analysis on the pre-expansion compensation model to extract basic geometric units and transition connection structures; Predefined nested repetition rules, wherein the nested repetition rules are composed of translation repetition restrictions and rotation repetition restrictions; According to the translation repetition limit, performing bidirectional equidistant replication of the basic geometric unit along the Y-axis direction and the X-axis direction at the dynamic nesting boundary until the nesting loop is formed, and outputting M translation loop splicing structures; At the M staggered spatial distributions of the dynamic nesting boundary and the M translational cyclic splicing structures, performing staggered replication of the transition connection structure based on the rotational repetition restriction until the nesting cycle is reached, and outputting M groups of rotational cyclic splicing structures; The M translation cyclic splicing structures and the M groups of rotation cyclic splicing structures are mapped and combined to obtain the multiple candidate cyclic splicing structures.

6. A cutting optimization method for an EVA liner for a tool box according to claim 5, characterized in that: Mapping and combining the M translation cyclic splicing structures and the M groups of rotation cyclic splicing structures to obtain the multiple candidate cyclic splicing structures, the method comprising: Restoring the basic geometric unit and transition connection structure to the standard structural proportion characteristics calculated by the pre-expansion compensation model; After mapping and combining the M translational cyclic splicing structures and the M groups of rotational cyclic splicing structures, M groups of real-time structural proportion features are calculated and output; The plurality of candidate cyclic splicing structures are screened and obtained according to whether the M groups of real-time structural proportion features meet the standard structural proportion features, wherein each candidate cyclic splicing structure consists of a translation cyclic splicing structure and a rotation cyclic splicing structure.

7. The cutting optimization method for an EVA liner for a tool box according to claim 1, characterized in that: Calculating multiple material utilization rates of the multiple candidate cyclic splicing structures based on the dynamic nesting boundary and multiple candidate cutting paths, the method includes: Discretizing the dynamic nesting boundary into a grid matrix of a preset scale; Projecting the plurality of candidate cyclic splicing structures onto the grid matrix to locate a plurality of first-level abandoned grid distributions; Projecting the plurality of candidate cutting paths onto the plurality of first-level abandoned grid distributions to perform path gap deduction to obtain a plurality of second-level abandoned grid distributions; The volume ratio of the dynamic nesting boundary to the distribution of multiple secondary abandoned grids is calculated, and the multiple material utilization rates are output.

8. The cutting optimization method for an EVA liner for a tool box according to claim 7, characterized in that: Calculating a volume ratio of the dynamic nesting boundary to a plurality of secondary abandoned grid distributions and outputting the plurality of material utilization rates, the method comprising: Interactively obtain EVA pad design; The EVA pad design is used to perform multiplexing calculations on the plurality of secondary abandoned grid distributions to obtain a plurality of tertiary abandoned grid distributions; Calculating a volume ratio of the dynamic nesting boundary to a plurality of third-level abandoned grid distributions, and outputting a plurality of updated material utilization rates; The cutting characteristic analysis is performed by using the multiple updated material utilization ratios to replace the material utilization ratio.

9. A cutting optimization system for EVA liners used in tool boxes, characterized in that: The system is used to execute a cutting optimization method for an EVA liner for a tool box according to any one of claims 1 to 8, and the system comprises: The reverse dimension compensation module is used to perform reverse dimension compensation on the tool box lining based on the nonlinear shrinkage of the thermally cut material to obtain a pre-expansion compensation model; A nesting boundary construction module, for interactively obtaining raw material design information of a raw material plate and constructing a dynamic nesting boundary according to the raw material design information; a splicing fitting module, configured to perform periodic nested splicing fitting of the pre-expansion compensation model within the dynamic nesting boundary to obtain a plurality of candidate cyclic splicing structures; a cutting path determining module, configured to output a plurality of candidate cutting paths for the plurality of candidate cyclic splicing structures based on curve path planning and fitting; a utilization rate calculation module, configured to calculate a plurality of material utilization rates of the plurality of candidate cyclic splicing structures according to the dynamic nesting boundary and the plurality of candidate cutting paths; a cutting characteristic analysis module, configured to perform cutting characteristic analysis based on the plurality of material utilization rates and the plurality of candidate cutting paths, so as to select a target nested segmentation structure from the plurality of candidate cyclic splicing structures; A loop segmentation module is used to perform loop segmentation of the EVA lining for the tool box by adopting the target nested segmentation structure.

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