A parting line constraint point interval optimization method

Abstract

The present application relates to the technical field of mold design, and more particularly to a parting line constraint point interval optimization method; a lower limit point sorting sequence is optimized according to a preset convex hull algorithm and a preset intersection condition to obtain an optimized lower limit point sorting sequence; an upper limit point sorting sequence is optimized according to the convex hull algorithm and the intersection condition to obtain an optimized upper limit point sorting sequence; an optimized constraint point interval sequence is generated according to the optimized lower limit point sorting sequence and the optimized upper limit point sorting sequence; the optimized lower limit point sorting sequence and the optimized upper limit point sorting sequence are integrated to generate an optimized constraint point interval sequence with clear boundaries and accurate data, which provides a reliable benchmark for parting line generation, mold processing and other links, improves process efficiency and reduces the risk of rework.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of mold design, and particularly relates to a mold parting line constraint point interval optimization method. BACKGROUND

[0002] In the field of industrial product structure design and precision machining, computer automatic design method has become the core means to improve the research and development efficiency, which usually relies on the technical path of target function iterative optimization to perform multi-round calculation on design parameters to obtain a feasible solution set. However, in the complex scene of mold parting line constraint point interval optimization, due to the coupling of multi-dimensional range conditions, the interweaving of concave-convex boundary shapes and other factors, the traditional iterative optimization method is often difficult to break through the shackles of local optimal solution and cannot accurately converge to the global optimal scheme. At the same time, a large amount of redundant iterative calculation will significantly consume the computing resources, leading to a significant extension of the design cycle, which is difficult to meet the dual requirements of design efficiency and precision of high-precision industrial parts, and therefore an efficient constraint point interval optimization method is needed to make up for the shortcomings of the prior art. SUMMARY

[0003] In order to overcome the shortcomings of the prior art, the purpose of the present application is to provide a mold parting line constraint point interval optimization method.

[0004] The first aspect of the present application provides a mold parting line constraint point interval optimization method, comprising: obtaining a lower limit point ordering sequence from a preset constraint point interval sequence; optimizing the lower limit point ordering sequence according to a preset convex hull algorithm and a preset intersection point condition to obtain an optimized lower limit point ordering sequence; obtaining an upper limit point ordering sequence from the constraint point interval sequence; optimizing the upper limit point ordering sequence according to the convex hull algorithm and the intersection point condition to obtain an optimized upper limit point ordering sequence; and generating an optimized constraint point interval sequence according to the optimized lower limit point ordering sequence and the optimized upper limit point ordering sequence.

[0005] Further, the obtaining of the lower limit point ordering sequence from the preset constraint point interval sequence comprises: obtaining the lower limit points of each constraint point interval in the constraint point interval sequence to obtain a lower limit point sequence; performing shape analysis on the lower limit point sequence to obtain a first shape analysis result; if the first shape analysis result is a convex lower limit point shape set, reordering each lower limit point in the lower limit point sequence according to a preset ordering rule to obtain the lower limit point ordering sequence.

[0006] Further, the optimization of the lower limit point sequence according to the preset convex hull algorithm and the preset intersection condition comprises: analyzing the lower limit point sequence according to the convex hull algorithm to obtain first convex hull contour data; analyzing the lower limit point sequence according to the first convex hull contour data to obtain all non-convex hull points; mapping and analyzing each non-convex hull point and the constraint point interval sequence to obtain a mapping constraint point interval of each non-convex hull point; analyzing the lower limit point sequence according to the first convex hull contour data to obtain a convex hull shape; and optimizing the lower limit point sequence according to the intersection condition, the mapping constraint point interval of each non-convex hull point and the convex hull shape to obtain an optimized lower limit point sequence.

[0007] Further, the analysis of the lower limit point sequence according to the first convex hull contour data to obtain all non-convex hull points comprises: performing feature analysis on the first convex hull contour data to obtain a first convex hull point sequence; performing matching analysis on the first convex hull point sequence and the lower limit point sequence to obtain a matching analysis result; and if the matching analysis result is that there is a non-convex hull point in the lower limit point sequence, obtaining all non-convex hull points from the matching analysis result.

[0008] Further, the optimization of the lower limit point sequence according to the intersection condition, the mapping constraint point interval of each non-convex hull point and the convex hull shape comprises: intersecting the convex hull shape and the mapping constraint point interval of each non-convex hull point to obtain a first intersection result;

[0009] verifying the first intersection result according to the intersection condition to obtain a first verification result; if the first verification result is that the first intersection result does not satisfy the intersection condition, optimizing the lower limit point sequence according to a preset value distance and the first intersection result to obtain an optimized lower limit point sequence; and if the first verification result is that the first intersection result satisfies the intersection condition, optimizing the lower limit point sequence according to the first intersection result to obtain an optimized lower limit point sequence.

[0010] Further, the obtaining of the upper limit point sequence from the constraint point interval sequence comprises:

[0011] obtaining upper limit points of each constraint point interval in the constraint point interval sequence to obtain an upper limit point sequence; performing morphological analysis on the upper limit point sequence to obtain a second morphological analysis result; and if the second morphological analysis result is a convex upper limit point morphological set, reordering each upper limit point in the upper limit point sequence according to a sorting rule to obtain an upper limit point sequence.

[0012] Further, the optimization of the upper limit point sorting sequence according to the convex hull algorithm and the intersection point condition comprises: analyzing the upper limit point sorting sequence according to the convex hull algorithm to obtain second convex hull contour data; detecting the upper limit point sorting sequence according to the second convex hull contour data to obtain a second intersection result; analyzing the upper limit point sorting sequence according to a preset concave direction angle interval and the second intersection result to obtain an angle analysis result; mapping and analyzing the angle analysis result and the upper limit point sorting sequence to obtain a key point sequence; and optimizing the upper limit point sorting sequence according to the intersection point condition and the key point sequence to obtain an optimized upper limit point sorting sequence.

[0013] Further, the detection of the upper limit point sorting sequence according to the second convex hull contour data to obtain a second intersection result comprises: extracting features of the second convex hull contour data to obtain a second convex hull point sequence; obtaining a first upper limit point and a tail upper limit point from the second convex hull point sequence; connecting the first upper limit point and the tail upper limit point to obtain a head-tail connection line; and performing intersection calculation on the head-tail connection line and the upper limit point sorting sequence to obtain the second intersection result.

[0014] Further, the analysis of the upper limit point sorting sequence according to the preset concave direction angle interval and the second intersection result to obtain an angle analysis result comprises: if the second intersection result is that there is no upper limit point of a non-head-tail point on the head-tail connection line, then generating a vector of each pair of adjacent upper limit points in the upper limit point sorting sequence by vector calculation in sequence based on each pair of adjacent upper limit points; forming a vector sequence according to all the vectors; and analyzing the vector sequence according to the concave direction angle interval to obtain the angle analysis result.

[0015] Further, the analysis of the vector sequence according to the concave direction angle interval to obtain an angle analysis result comprises: generating an angle of each pair of adjacent vectors in the vector sequence by angle calculation in sequence based on each pair of adjacent vectors; forming an angle sequence according to all the angles; and analyzing the angle sequence according to the concave direction angle interval to obtain the angle analysis result.

[0016] Further, the mapping and analyzing of the angle analysis result and the upper limit point sorting sequence to obtain a key point sequence comprises: when the angle analysis result is that there is a concave direction angle, obtaining all the concave direction angles from the angle analysis result; mapping and analyzing all the concave direction angles and the upper limit point sorting sequence to obtain upper limit points corresponding to each concave direction angle; taking the upper limit points corresponding to each concave direction angle as key points; and forming a key point sequence according to all the key points, the first upper limit point and the tail upper limit point.

[0017] Further, the upper limit point sequence is optimized according to the intersection condition and the key point sequence to obtain an optimized upper limit point sequence, including: taking the key point sequence as a new upper limit point sequence, and returning to perform vector calculation for each pair of adjacent upper limit points in the upper limit point sequence in turn to generate a vector of each pair of adjacent upper limit points until the included angle analysis result is that there is no concave direction included angle; if the included angle analysis result is that there is no concave direction included angle, then the upper limit point sequence and each constraint point interval are intersected to obtain a third intersection result; the third intersection result is verified according to the intersection condition to obtain a verification result; if the verification result is that the third intersection result does not satisfy the intersection condition, then the upper limit point sequence is optimized according to the value distance and the third intersection result to obtain an optimized upper limit point sequence;

[0018] If the verification result is that the third intersection result satisfies the intersection condition, then the upper limit point sequence is optimized according to the third intersection result to obtain an optimized upper limit point sequence.

[0019] In the technical scheme of the present application, the optimized constraint point interval sequence is generated relying on the optimized lower limit point sequence and the optimized upper limit point sequence, the upper and lower limit boundary data with the shape smoothing and constraint compliance can be integrated, the redundant point positions and shape deviations of the original constraint point interval are eliminated, the generated optimized interval sequence has clear boundaries and accurate data, and a unified and reliable constraint reference is provided for subsequent parting line generation, industrial design, mold processing and the like, the connection efficiency of the overall process is effectively improved, and the production rework risk caused by interval data defects is reduced. BRIEF DESCRIPTION OF DRAWINGS

[0020] The above and / or additional aspects and advantages of the present application will become apparent and more readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:

[0021] Figure 1 A first flowchart of a parting line constraint point interval optimization method provided for an embodiment of the present application;

[0022] Figure 2 A second flowchart of a parting line constraint point interval optimization method provided for an embodiment of the present application;

[0023] Figure 3 A third flowchart of a parting line constraint point interval optimization method provided for an embodiment of the present application;

[0024] Figure 4 A fourth flowchart of a parting line constraint point interval optimization method provided for an embodiment of the present application;

[0025] Figure 5 A fifth flowchart of a parting line constraint point interval optimization method provided for an embodiment of the present application;

[0026] Figure 6 The sixth flow chart of the mold line constraint point interval optimization method provided by the embodiment of the present application;

[0027] Figure 7 The seventh flow chart of the mold line constraint point interval optimization method provided by the embodiment of the present application;

[0028] Figure 8 The eighth flow chart of the mold line constraint point interval optimization method provided by the embodiment of the present application;

[0029] Figure 9 The ninth flow chart of the mold line constraint point interval optimization method provided by the embodiment of the present application;

[0030] Figure 10 The tenth flow chart of the mold line constraint point interval optimization method provided by the embodiment of the present application;

[0031] Figure 11 The eleventh flow chart of the mold line constraint point interval optimization method provided by the embodiment of the present application;

[0032] Figure 12 The twelfth flow chart of the mold line constraint point interval optimization method provided by the embodiment of the present application. DETAILED DESCRIPTION

[0033] The terms "first", "second", "third", "fourth" and the like in the description and claims of the present application, and above drawings (if there is) are used to distinguish similar objects, and do not necessarily have to be used to describe a particular order or sequence. It should be understood that the data used in this way can be exchanged under appropriate circumstances, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the term "comprising" or "having" and any variation thereof is intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0034] For the sake of understanding, the specific flow of the embodiment of the present application is described below. Please refer to Figure 1 An embodiment of the mold line constraint point interval optimization method in the embodiment of the present application includes:

[0035] 101, obtaining a lower limit point ordering sequence from a preset constraint point interval sequence;

[0036] In the embodiment, the lower limit point sequence is extracted from the preset constraint point interval sequence, the basic ordered point set meeting the design constraint can be directly obtained, the boundary reference of the lower limit shape is anchored, compliant and regular data support is provided for subsequent lower limit point sequence optimization, shape analysis and other processes, and the accuracy and efficiency of the overall processing are improved;

[0037] 102. The lower limit point sequence is optimized according to the preset convex hull algorithm and the preset intersection point condition, to obtain an optimized lower limit point sequence;

[0038] In the embodiment, the convex hull algorithm can accurately fit the convexity profile of the lower limit point sequence, and the preset intersection point condition checks the whole optimization process to ensure that the lower limit point sequence meets the design constraint requirement, and the accuracy and efficiency of the overall process are improved;

[0039] 103. The upper limit point sequence is obtained from the constraint point interval sequence;

[0040] In the embodiment, the upper limit point sequence is extracted from the constraint point interval sequence, which provides compliant and regular data support for subsequent convex hull detection, angle analysis, key point screening and other processes, and improves the accuracy and efficiency of the overall processing;

[0041] 104. The upper limit point sequence is optimized according to the convex hull algorithm and the intersection point condition, to obtain an optimized upper limit point sequence;

[0042] In the embodiment, the convex hull algorithm can accurately fit the convexity profile of the upper limit point sequence, and the preset intersection point condition checks the whole optimization process to ensure that the upper limit point sequence strictly meets the design constraint;

[0043] 105. The optimized constraint point interval sequence is generated according to the optimized lower limit point sequence and the optimized upper limit point sequence;

[0044] In the embodiment, the optimized constraint point interval sequence is generated based on the optimized lower limit point sequence and the optimized upper limit point sequence, which can integrate the upper and lower limit boundary data with shape smoothing and constraint compliance, eliminate the redundant points and shape deviations of the original constraint point interval, and generate the optimized interval sequence with clear boundary and accurate data, providing unified and reliable constraint reference for subsequent parting line generation, industrial design, mold processing and other links, effectively improving the connection efficiency of the overall process and reducing the risk of production rework caused by interval data defects.

[0045] The following steps 201-503 are applicable to the optimization of the lower limit point sequence with convex lower limit point shape set, and can be directly applied to the optimization process of the upper limit point sequence with concave upper limit point shape set;

[0046] Please refer to Figure 2The second embodiment of the mold parting line constraint point interval optimization method in the embodiment of the application specifically comprises the following steps.

[0047] 201. Obtain lower limit points in each constraint point interval in the constraint point interval sequence to obtain a lower limit point sequence.

[0048] In this embodiment, the preset constraint point interval sequence is traversed, and the boundary point (i.e., the lower limit point) close to the part side is extracted from each independent constraint point interval. All extracted lower limit points are integrated to form an initial lower limit point sequence, which lays a foundation for subsequent convex hull algorithm optimization and elimination of inferior solutions.

[0049] 202. Perform morphological analysis on the lower limit point sequence to obtain a first morphological analysis result.

[0050] In this embodiment, the overall morphological characteristics of the lower limit point sequence can be determined by a geometric morphological recognition algorithm (such as point set convexity detection, boundary curvature analysis, etc.). The first morphological analysis result (whether it is a convex lower limit point set) is output, which indicates that the overall distribution of the lower limit points is convex to the part and has no obvious concave or irregular convexity.

[0051] 203. If the first morphological analysis result is a convex lower limit point set, reorder each lower limit point in the lower limit point sequence according to a preset sorting rule to obtain a lower limit point sorting sequence.

[0052] In this embodiment, the non-convex hull points in the convex lower limit point set are the core inferior solution source that causes the mold parting line to be not smooth. Morphological analysis provides a basis for subsequent elimination of inferior solutions and narrowing of the effective constraint range. If the first morphological analysis result is a convex lower limit point set, the initial lower limit point sequence is reordered according to a preset sorting rule (such as the mold parting line extension direction, the clockwise / counterclockwise direction around the part, the point set coordinate progressive direction, etc.) to form an ordered lower limit point sorting sequence. The mold parting line is a continuous boundary line, and the ordered arrangement of the lower limit points can ensure that the point set after subsequent optimization can be connected in the mold parting line extension direction, avoiding the mold parting line from being broken or wrinkled due to the disorder of the point sequence, and laying a foundation for smoothness from the data level.

[0053] In the embodiment, by separately extracting the lower limit points close to the part side, focusing on the parting line core constraint, laying a data foundation for accurate optimization; with the help of geometric shape identification algorithm to screen the convex lower limit point shape set, accurately match the scene optimization demand, reduce the redundant algorithm consumption; according to the preset rule, the convex lower limit scene is reordered, which not only adapts to the requirement of the convex hull algorithm for the ordered point set, guarantees the accuracy of the subsequent poor solution elimination and convex hull optimization, but also ensures that each lower limit point is connected according to the extension direction of the parting line, avoids the problem of parting line fracture and wrinkle caused by point sequence disorder, and synchronously improves the pertinence of optimization strategy, the adaptability of algorithm and the smoothness of parting line, effectively shortens the design cycle, and meets the processing quality and efficiency demand of high-precision industrial parts.

[0054] Referring to Figure 3 , the third embodiment of the parting line constraint point interval optimization method in the embodiment of the application, step 102, specifically comprises:

[0055] 301, analyzing the lower limit point sorting sequence according to the convex hull algorithm to obtain first convex hull contour data;

[0056] 302, analyzing the lower limit point sorting sequence according to the first convex hull contour data to obtain all non-convex hull points;

[0057] In the embodiment, the ordered lower limit point sorting sequence is input into the convex hull algorithm (such as Graham scanning method, Andrew algorithm, etc.), the convex hull boundary of the point set is calculated through the algorithm, and the points not falling on the convex hull boundary are screened out, that is, the non-convex hull points;

[0058] 303, mapping analysis is performed on each non-convex hull point and the constraint point interval sequence to obtain the mapping constraint point interval of each non-convex hull point;

[0059] In the embodiment, the initial independent constraint point interval (i.e. the “mapping constraint point interval”) of each non-convex hull point is determined through index matching, coordinate tracing and other methods, which guarantees that the optimization does not deviate from the original constraint and ensures the compliance of the optimization result;

[0060] 304, analyzing the lower limit point sorting sequence according to the first convex hull contour data to obtain the convex hull shape;

[0061] In the embodiment, the convex hull algorithm outputs the convex hull boundary contour of the point set while identifying the non-convex hull points, that is, the “convex hull shape”, which is the ideal boundary shape of the most smooth and most suitable part side of the lower limit point sequence, and can ensure that the point set after subsequent adjustment can fit the optimal boundary, laying a foundation for the smoothness of the parting line from the shape;

[0062] 305, optimizing the lower limit point sorting sequence according to the intersection condition, the mapping constraint point interval of each non-convex hull point and the convex hull shape to obtain an optimized lower limit point sorting sequence;

[0063] In the embodiment, the light smoothing reference is provided by the convex hull shape, the legal boundary is delimited by mapping the constraint point interval, the compliance is verified by the intersection condition, the lower limit point invalid adjustment is avoided, the optimization accuracy and result reliability are improved, the process is simplified, the computing power consumption is reduced, the design cycle is effectively shortened, and the actual industrial needs are adapted;

[0064] In the embodiment, the non-convex point is accurately identified by the convex hull algorithm, the core suboptimal solution source of the mold parting line smoothing is locked, and the blindness of optimization is avoided; the constraint point interval to which the non-convex point belongs is traced back by mapping analysis, the optimization compliance bottom line is consolidated, and the problem of deviating from the original constraint is avoided; the convex hull shape provides an ideal smoothing boundary that best fits the part, lays a foundation for the adjustment direction, verifies the optimization rationality in combination with the intersection condition, improves the optimization accuracy and result reliability, simplifies the process, reduces redundant computing power consumption, effectively shortens the design cycle, and adapts to the multiple needs of the industrial scene for the mold parting line smoothing, compliance and design efficiency.

[0065] Referring to Figure 4 , the fourth embodiment of the mold parting line constraint point interval optimization method in the embodiment of the application specifically comprises the following steps:

[0066] 401, performing feature analysis on the first convex hull contour data to obtain a first convex hull point sequence;

[0067] In the embodiment, the lower limit point sorting sequence sorted according to the preset rule is input into the convex hull algorithm (such as Graham scanning method, Andrew algorithm, etc.), the algorithm filters out the “smallest convex polygon boundary (first convex hull contour data)” through geometric calculation, and then performs feature extraction on the “smallest convex polygon boundary (first convex hull contour data)” to obtain the point set of the “smallest convex polygon boundary (first convex hull contour data)”, that is, the “first convex hull point sequence”. These points are the core points that best fit the part and are most regular in distribution in the lower limit point sequence, and naturally have the smoothing characteristics of no concave and no wrinkle, thereby providing an objective reference standard for judging which points are suboptimal points deviating from the optimal boundary in the subsequent step;

[0068] 402, performing matching analysis on the first convex hull point sequence and the lower limit point sorting sequence to obtain a matching analysis result;

[0069] In the embodiment, whether each point in the lower limit point sorting sequence exists in the first convex hull point sequence is verified one by one by means of accurate comparison of coordinates, point index association and the like, and the matching analysis result of “whether there is a non-convex point” and specific difference point information is output, so as to clearly determine the key object of subsequent optimization;

[0070] 403, if the matching analysis result is that there is a non-convex point in the lower limit point sorting sequence, all non-convex points are obtained from the matching analysis result.

[0071] In the embodiment, when the matching analysis confirms that there are points not included in the first convex hull point sequence, these difference points are uniformly extracted to form a complete non-convex hull point set as the object of subsequent optimization adjustment. Non-convex hull points are the core of the solution that causes the parting line to produce wrinkles and waves. This step avoids invalid processing of convex hull points that do not need to be optimized by explicitly extracting all non-convex hull points, so that the subsequent optimization focuses on the problem points, improving the optimization efficiency.

[0072] In the embodiment, the first convex hull point sequence constituting the minimum convex polygon boundary is screened from the ordered lower limit point sequence by means of the convex hull algorithm. This sequence naturally has the smoothing characteristics of no concave and no wrinkles, providing an objective and part demand reference for solution identification. Through coordinate accurate comparison, matching analysis of point index correlation, one-to-one verification of convex hull points and original points is realized to ensure the accuracy of non-convex hull point identification. All non-convex hull points are extracted according to the matching result to clearly define the object of subsequent optimization, avoiding invalid processing of qualified convex hull points, improving optimization pertinence, and overall process through algorithmic and standardized operation, locking the core solution of parting line wrinkles and waves, reducing redundant algorithm consumption, shortening the design cycle, and providing clear targets and basis for subsequent optimization, ensuring the smoothness of the parting line and the standardization of industrial design.

[0073] Referring to Figure 5 , the fifth embodiment of the parting line constraint point interval optimization method in the embodiment of the application, step 305, specifically includes:

[0074] 501. Intersect the mapping constraint point interval of the convex hull shape and each non-convex hull point to obtain a first intersection result.

[0075] In the embodiment, for each non-convex hull point, the convex hull shape (ideal smoothing boundary) and the mapping constraint point interval (original legal constraint range) corresponding to the point are subjected to geometric intersection operation to generate a possible new intersection point set, i.e., the first intersection result. Through vector operation, straight line equation, and plane equation solving geometric algorithms, the intersection of the convex hull shape and the mapping constraint point interval of each non-convex hull point is calculated: the common intersection point (i.e., the new intersection point) of the convex hull shape and the mapping constraint point interval of each non-convex hull point is included in the "first intersection result"; if the mapping constraint point interval of a non-convex hull point has no common intersection point with the convex hull shape, the single-point intersection result is recorded as empty in the first intersection result, and no intersection point is included, providing a judgment basis for subsequent "adjustment according to a preset distance";

[0076] 502. Verify the first intersection result according to the intersection point condition to obtain a first verification result.

[0077] In the embodiment, the preset intersection condition (all new intersection points need to intersect with any constraint point interval in the constraint point interval sequence) is taken as the judgment standard to carry out global constraint compliance verification on the first intersection result, and the verification logic is divided into two categories:

[0078] For the effective common intersection points in the first intersection result: the intersection point coordinates are compared with all intervals of the constraint point interval sequence one by one, it is judged whether the intersection point falls within any interval, the effective intersection points meeting the global constraint are screened out, and if all new intersection points intersect with any constraint point interval in the constraint point interval sequence, it is judged that the intersection condition is met;

[0079] For the single-point intersection item recorded as empty in the first intersection result: no additional verification is needed, and it is directly judged as “not meeting the intersection condition”; through the explicit global constraint verification rule, the first intersection result is accurately verified in two categories, the globally compliant intersection points are effectively screened out, the empty result item is directly judged, the subsequent optimization direction is clear, and the optimization accuracy and efficiency are improved;

[0080] 503、If the first verification result is that the first intersection result does not meet the intersection condition, the lower limit point ordering sequence is optimized according to the preset value distance and the first intersection result to obtain an optimized lower limit point ordering sequence;

[0081] In the embodiment, when it is verified and judged that the intersection condition is not met and it is clear that “no new intersection point is generated” (that is, the intersection item corresponding to the non-convex point in the first intersection result is empty), targeted adjustment is performed; taking the non-convex point (old lower limit point) to be optimized in the original lower limit point ordering sequence which does not generate a new intersection point as the only adjustment reference; the coordinates are accurately adjusted according to the preset rule (the new lower limit point is taken at a distance of 1 mm from the old lower limit point), the adjustment range is controllable, the new lower limit point after adjustment is replaced with the old lower limit point in the original sequence, the entire lower limit point ordering sequence is updated and integrated, and finally an optimized lower limit point ordering sequence is formed, which is suitable for industrial operation and efficiently solves the optimization problem in special scenarios;

[0082] 504、If the first verification result is that the first intersection result meets the intersection condition, the lower limit point ordering sequence is optimized according to the first intersection result to obtain an optimized lower limit point ordering sequence;

[0083] In the embodiment, the effective common intersection points in the first intersection result are matched one by one with the corresponding non-convex points in the original lower limit point ordering sequence, the replacement object of each effective intersection point is clear, and the original sequence is directly replaced with the corresponding non-convex point by using the effective common intersection point; for the convex points in the sequence that do not need to be optimized, the coordinates and positions thereof are kept unchanged, the replaced convex points and the effective common intersection points are re-integrated in the order of the original lower limit point ordering sequence, and finally an optimized lower limit point ordering sequence is generated;

[0084] In the embodiment, by calculating the intersection of the convex hull shape and the mapping constraint point interval of each non-convex point, the effective intersection point that meets the ideal fairing boundary (convex hull shape) and local constraint is accurately generated, and the special scene without intersection point is clearly marked, laying a solid foundation for subsequent differentiated processing. Differentiated optimization paths are designed for different verification results. When the conditions are met, the valid intersection point is reused. When the conditions are not met and there is no new intersection point, the old point is replaced by 1mm fine tuning, realizes the optimization process, avoids subjective error, improves the consistency of the results, and efficiently adapts to the industrial operation needs.

[0085] The steps 601 to 1205 described below are applicable to the optimization of the upper limit point sequence of the convex upper limit point morphology set, and can be directly applied to the optimization process of the lower limit point sequence of the concave lower limit point morphology set.

[0086] Referring to Figure 6 In the sixth embodiment of the mold parting line constraint point interval optimization method in the embodiment, step 103 specifically includes:

[0087] 601. Obtain the upper limit points of each constraint point interval in the constraint point interval sequence to obtain an upper limit point sequence.

[0088] In the embodiment, the "upper limit points" (i.e., the boundary maximum value points of each interval) of each constraint point interval are extracted one by one from the constraint point interval sequence, and the extracted upper limit points are integrated to form an upper limit point sequence.

[0089] 602. Perform morphology analysis on the upper limit point sequence to obtain a second morphology analysis result.

[0090] In the embodiment, the overall morphology characteristics of the upper limit point sequence can be determined by a geometric morphology recognition algorithm (such as point set convexity detection, boundary curvature analysis, etc.), and the core output is the second morphology analysis result "whether it is a convex upper limit point morphology set" (the convex upper limit point morphology set refers to the distribution characteristic that the upper limit points are convex to the part as a whole, without obvious concave or irregular protrusions).

[0091] 603. If the second morphology analysis result is a convex upper limit point morphology set, reorder each upper limit point in the upper limit point sequence according to the sorting rule to obtain an upper limit point sorting sequence.

[0092] In the embodiment, if the second shape analysis result is a convex upper limit point shape set, the initial upper limit point sequence is reordered according to a preset sorting rule (such as the extension direction of the parting line, the clockwise / counterclockwise surrounding direction of the part, the coordinate progressive direction of the point set, etc.), to form an ordered upper limit point sorting sequence. The parting line is a continuous boundary line, and the ordered arrangement of the upper limit points can ensure that the subsequent optimized point set can be connected in the extension direction of the parting line, avoiding the parting line from being broken or wrinkled due to disorderly point sequence, and laying a smoothness foundation from the data level;

[0093] In the embodiment, the upper limit points in each constraint interval are extracted, and the core boundary data is focused, to lay a simple and reliable foundation for subsequent analysis. The convex upper limit point shape set is screened through shape analysis, to avoid invalid sorting operation. The convex shape sequence is reordered, to construct a regular and ordered upper limit point sorting sequence, to improve the adaptability and accuracy of subsequent optimization and intersection calculation, to have strong pertinence for the overall process, to reduce the consumption of computing power, to ensure the stability of the sequence, and to efficiently support the subsequent processing requirements related to the upper limit points in industrial design.

[0094] Please refer to Figure 7 In the seventh embodiment of the parting line constraint point interval optimization method in the embodiment, step 104 specifically includes:

[0095] 701. Analyze the upper limit point sorting sequence according to the convex hull algorithm, to obtain second convex hull contour data;

[0096] 702. Detect the upper limit point sorting sequence according to the second convex hull contour data, to obtain a second intersection result;

[0097] In the embodiment, the ordered upper limit point sorting sequence is detected in geometry shape by using the convex hull algorithm, to fit the convex hull boundary of the point set, to calculate the intersection of the convex hull boundary and the original upper limit point sorting sequence, and to output the second intersection result. The core function of the result is to distinguish two types of points: one is the convex hull point (constituting the convexity contour of the sequence) falling on the convex hull boundary, and the other is the non-convex hull point (potential concave feature point) located in the convex hull.

[0098] 703. Analyze the upper limit point sorting sequence according to the preset concave direction angle interval and the second intersection result, to obtain an angle analysis result;

[0099] In the embodiment, the upper limit point sorting sequence is accurately analyzed to obtain the angle analysis result by combining the preset concave direction angle interval and the second intersection result, to accurately locate the concave shape feature in the sequence, to improve the analysis pertinence, and to provide accurate basis for subsequent key point screening and upper limit point sorting sequence optimization;

[0100] 704. Perform mapping analysis on the angle analysis result and the upper limit point sorting sequence, to obtain a key point sequence;

[0101] In the embodiment, the key point sequence is generated by mapping analysis of the included angle analysis result and the upper limit point sequence, the concave direction features can be accurately associated with the corresponding upper limit points, the core point positions affecting the shape are screened out, the redundant non-feature points are effectively removed, high-quality data support is provided for subsequent upper limit point sequence optimization, subjective point selection errors are avoided, and the pertinence and efficiency of the overall process are improved;

[0102] 705. optimizing the upper limit point sequence according to the intersection condition and the key point sequence to obtain an optimized upper limit point sequence;

[0103] In the embodiment, the convex hull algorithm is used to accurately distinguish the convex points and the potential inner concave points, to lay a reliable foundation for shape analysis; the concave shape features are accurately positioned by combining the preset concave direction included angle interval and the detection result, the analysis pertinence is improved, the concave direction features are associated with the corresponding upper limit points through mapping analysis, the core point positions are screened out and the redundant points are removed, the subjective point selection errors are avoided, and finally the optimized upper limit point sequence is generated according to the intersection condition, the whole process is accurate and efficient, high-quality data support is provided for subsequent industrial design links, the overall processing efficiency and optimization precision are improved, and the reliability of design landing is ensured.

[0104] Please refer to Figure 8 , the eighth embodiment of the mold parting line constraint point interval optimization method in the embodiment of the application, step 702, specifically comprising:

[0105] 801. feature extraction is performed on the second convex hull contour data to obtain a second convex point sequence;

[0106] In the embodiment, the convex hull algorithm is used to perform geometric shape fitting on the upper limit point sequence, to screen out the core points constituting the convexity contour of the sequence, and to integrate to form a second convex point sequence, which reflects the overall convexity boundary features of the upper limit point sequence, and provides a reliable basis for subsequent extraction of the first and last boundary points;

[0107] 802. the first upper limit point and the last upper limit point are obtained from the second convex point sequence;

[0108] 803. the first upper limit point and the last upper limit point are connected to obtain a first-last connection line;

[0109] In the embodiment, the first upper limit point and the last upper limit point (i.e. the starting boundary convex point and the terminal boundary convex point of the sequence) are accurately extracted from the second convex point sequence, the two points are connected through a geometric connection algorithm to generate a first-last connection line, and the connection line is a core reference point for determining whether the original upper limit point sequence has linear segmentation;

[0110] 804. the first-last connection line and the upper limit point sequence are intersected to obtain a second intersection result;

[0111] In the embodiment, the first-end-to-last line is subjected to a geometric intersection operation with the original upper limit point sequence, and a second intersection result is output. The core of the result is to determine whether there is an upper limit point other than the first-end and last points on the first-end-to-last line. If the second intersection result shows that there is an upper limit point other than the first-end and last points on the first-end-to-last line, it indicates that these upper limit points need to be taken as division nodes to cut the original upper limit point sequence into multiple independent new upper limit point sequences. Then, the reordering operation is performed on each new sequence to optimize the operation. The "segmented ordering" is realized for the sub-sequences with different morphological characteristics. The linear sub-sequences are independently sorted to avoid the interference of nonlinear characteristics and to ensure the regularity of the sorting result. Meanwhile, the distortion problem of linear segments caused by overall sorting is solved.

[0112] In the embodiment, the core convex hull points are screened by relying on the convex hull algorithm to generate a second convex hull point sequence. The first-end and last boundary points are accurately extracted and connected to provide a reliable reference for linear segment determination. The intersection of the first-end-to-last line and the original upper limit point sequence is calculated to accurately identify the linear segment nodes. For the case where there are upper limit points other than the first-end and last points, the original upper limit point sequence is divided into multiple sub-sequences and independently reordered. The segmented processing adapts to the characteristics of different sub-sequences to ensure the regularity of the sorting result. Meanwhile, the redundant calculation is reduced to improve the preprocessing efficiency. The ordered sub-sequences output provide high-quality data support for subsequent morphological analysis, key point screening, and other links to adapt to the industrial design operation needs of the range optimization of the parting line.

[0113] Referring to Figure 9 , the ninth embodiment of the method for optimizing the parting line constraint point interval in the embodiment of the application specifically comprises the following steps:

[0114] 901. If the second intersection result is that there is no upper limit point other than the first-end and last points on the first-end-to-last line, the vector of each pair of adjacent upper limit points in the upper limit point sequence is calculated in sequence based on each pair of adjacent upper limit points in the upper limit point sequence.

[0115] 902. The vector sequence is formed according to all the vectors.

[0116] In the embodiment, based on the upper limit point sequence, each pair of adjacent upper limit points (the first and the second, the second and the third,..., the n-1th and the nth) is extracted in sequence. The vector calculation formula , is used to calculate the vector of each pair of adjacent upper limit points in sequence. is the first upper limit point in the upper limit point sequence, is the i-th upper limit point in the upper limit point sequence, The direction of the vector is from the previous upper limit point to the next upper limit point, and the size of the vector is the distance between the two points. Finally, the vector of the i-th upper limit point in the upper limit point sequence is obtained. An ordered vector is used to convert the discrete upper limit point sequence into a vector set describing the position change trend, and a calculable geometric carrier is provided for subsequent recognition of the concave direction feature through the angle analysis;

[0117] 903. Analyzing the vector sequence according to the concave direction angle interval to obtain an angle analysis result;

[0118] In this embodiment, the vector sequence is quantitatively analyzed based on the concave direction angle interval, the concave direction feature angle is accurately screened and the corresponding position is located, the morphological feature of the vector sequence is converted into a traceable quantitative result, and the consistency of the concave direction feature recognition is improved, thereby providing a precise targeting basis for subsequent key point screening and upper limit point sequence optimization;

[0119] In this embodiment, by virtue of the scenario that the front and rear connecting lines of the pre-checking do not have other upper limit points, invalid processing of linear sequences is avoided, and the consumption of redundant computing power is greatly reduced, indicating that the point set does not need to be segmented and optimized, an ordered vector is generated based on adjacent upper limit points, a discrete point set is converted into a calculable geometric carrier describing the position change trend, and quantitative conversion of the morphological feature is realized; the vector sequence is analyzed based on the concave direction angle interval, the concave direction feature angle is accurately screened and the corresponding position is located, the morphological feature is converted into a traceable quantitative result, and the consistency and accuracy of the concave direction feature recognition are improved, the overall process is highly targeted, and explicit basis is provided for subsequent key point screening and upper limit point sequence optimization, which is suitable for the practical operation needs of morphological analysis in industrial design and improves the overall processing efficiency.

[0120] Please refer to Figure 10 The tenth embodiment of the method for optimizing the parting line constraint point interval in the embodiment of the application comprises the following steps:

[0121] 1001. Based on each pair of adjacent vectors in the vector sequence, the angle between each pair of adjacent vectors is calculated in sequence to generate the angle between each pair of adjacent vectors;

[0122] In this embodiment, each pair of adjacent vectors (i.e., the first and second vectors, the second and third vectors,..., the n-1th and n vectors) is extracted from the vector sequence in sequence, a vector angle calculation algorithm (such as based on the dot product formula: ,

[0123] In the formula, is the first adjacent vector, is the second adjacent vector), the angle θ is solved by the inverse trigonometric function, and the angle between each pair of adjacent vectors is calculated in sequence (the unit is degree or radian, which needs to be unified with the subsequent interval standard), so that all pairs of adjacent vectors are covered without omission;

[0124] 1002. Form an angle sequence according to all the angles;

[0125] In this embodiment, all calculated adjacent vector angles are integrated and arranged in sequence according to the order of the corresponding adjacent vector pairs in the original vector sequence to form an angle sequence (i.e., the first angle corresponds to the first-2 vectors in the original sequence, the second angle corresponds to the second-3 vectors in the original sequence, and so on, to ensure that the angle sequence is completely matched with the position of the original vector sequence), which facilitates subsequent batch and regular interval comparison analysis, and improves analysis efficiency;

[0126] 1003. Analyzing the angle sequence according to the concave direction angle interval to obtain an angle analysis result;

[0127] In this embodiment, the pre-set concave direction angle interval (180°~360°, or a customized interval according to the actual position of the part and design requirements) is first determined, and then each angle in the angle sequence is compared with the interval to determine whether each angle falls within the concave direction angle interval: if the angle falls within the concave direction angle interval, it is marked as a "concave feature angle" and its position in the angle sequence (corresponding to the position of the adjacent vector pair in the original vector sequence) is recorded; if the angle does not fall within the interval, it is marked as a "non-concave feature angle", and the final output includes the complete angle analysis result containing "whether each angle is a concave feature" and "the position distribution of the concave feature angle";

[0128] In this embodiment, the dot product formula algorithm is used to calculate the angle between adjacent vectors pair by pair, and the geometric shape is converted into a measurable numerical value; the angles are integrated in sequence according to the original vector sequence to ensure that the feature corresponds accurately to the position of the original vector, making the analysis results traceable. By using a customized concave direction angle interval (180°~360° or adjusted as needed) to filter the feature angles and accurately mark the positions of the concave features, the method not only adapts to diversified design requirements, but also eliminates redundant data, reduces the subsequent processing load, and provides reliable data support for upper limit point sorting sequence, constraint point interval and part shape design, etc., improving the accuracy and efficiency of industrial design.

[0129] Referring to Figure 11 The eleventh embodiment of the parting line constraint point interval optimization method in the embodiment of the application comprises the following steps:

[0130] 1101. When the angle analysis result is that there is a concave direction angle, all concave direction angles are obtained from the angle analysis result;

[0131] In this embodiment, the angle analysis result is first verified, and only when it is determined that there is a concave direction angle, the subsequent operation is started; if there is no concave direction angle, key point filtering is not needed, ensuring that the process only acts on the upper limit point sorting sequence with concave shape features, reducing redundant computing power consumption and improving the overall analysis specificity;

[0132] 1102. Perform mapping analysis on all the sorted sequences of concave direction angles and upper limit points to obtain the upper limit points corresponding to each concave direction angle;

[0133] 1103. Take the upper limit points corresponding to the included angles of each concave direction as key points;

[0134] In this embodiment, based on the information of adjacent vector pairs corresponding to the concave direction angle, a precise mapping is performed with the upper limit point sorting sequence: clarifying the correspondence between vectors and upper limit points. ,therefore and The included angle directly corresponds to the upper limit point pnt_i+1 in the upper limit point sequence. If the included angle is determined to be concave (for convex upper limit patterns) or convex (for concave lower limit patterns), then... Mark a key point as a core location that causes the sequence to exhibit a concave shape. Traverse all concave angles to complete the filtering and marking of the corresponding key points.

[0135] 1104. Form a keypoint sequence based on all keypoints, the first upper limit point, and the last upper limit point;

[0136] In this embodiment, by pre-checking the existence of the concave angle, operations are only performed on sequences with morphological features to avoid invalid processing and reduce redundant computing power consumption. Based on the correspondence between vectors and upper limit points, the concave angle is accurately mapped to the core points, ensuring that the selected key points are all core elements affecting the concave shape. Redundant non-feature points are eliminated, and the first and last upper limit points are added to form a complete key point sequence. This preserves the core morphological features and ensures the integrity of the sequence boundaries, avoiding omissions in subsequent optimization. The entire process relies on standardized rules, eliminating subjective errors and ensuring stable and consistent results. This provides high-quality data support for subsequent upper limit point sequence optimization and is suitable for the practical needs of industrial design.

[0137] Please see Figure 12 The twelfth embodiment of the parting line constraint point interval optimization method of the present invention, step 705, specifically includes:

[0138] 1201. Take the key point sequence as the new upper limit point sorting sequence, and return to execute the vector calculation based on each pair of adjacent upper limit points in the upper limit point sorting sequence to generate the vector of each pair of adjacent upper limit points, until the angle analysis result shows that there is no concave direction angle.

[0139] In this embodiment, the key point sequence obtained in the previous screening is directly used as the new upper limit point sorting sequence. The process of calculating the vector of adjacent upper limit points and analyzing the angle between the vector sequences is repeated until the angle analysis result determines that there is no concave direction angle. During the loop, each new sequence generated in each round will be optimized based on the key points of the previous round to gradually eliminate concave morphological features.

[0140] 1202、If the included angle analysis result is that there is no concave direction included angle, the intersection of the upper limit point sequence and each constraint point interval is calculated to obtain a third intersection result;

[0141] In this embodiment, when the sequence shape converges to no concave direction included angle, the final upper limit point sequence is geometrically intersected with each constraint point interval, and the common intersection points that fall within the sequence boundary and the constraint interval at the same time are screened out to form the third intersection result;

[0142] 1203, verifying the third intersection result according to the intersection point condition to obtain a verification result;

[0143] In this embodiment, the preset intersection point condition (such as all intersection points need to fall within the constraint point interval, the intersection point distribution meets the design rule, etc.) is taken as the judgment standard, and the global compliance verification of the third intersection result is carried out, and the verification result of “satisfying or not satisfying the intersection point condition” is output;

[0144] 1204, if the verification result is that the third intersection result does not satisfy the intersection point condition, the upper limit point sequence is optimized according to the value distance and the third intersection result to obtain an optimized upper limit point sequence;

[0145] In this embodiment, if the verification result is that the intersection point condition is satisfied: the effective common intersection points in the third intersection result are directly matched and replaced with the corresponding upper limit points in the original sequence, the points that do not need to be optimized are retained, and the optimized upper limit point sequence is integrated and generated;

[0146] 1205, if the verification result is that the third intersection result satisfies the intersection point condition, the upper limit point sequence is optimized according to the third intersection result to obtain an optimized upper limit point sequence;

[0147] In this embodiment, when the third intersection result does not satisfy the intersection point condition, 1mm is taken as the preset value distance reference, and directional fine tuning is performed on the upper limit points in the original upper limit point sequence that do not meet the constraints: the adjusted new upper limit points are set at a position more than 1mm away from the original upper limit points, the adjustment range is strictly controlled to avoid sequence shape distortion due to excessive point displacement; at the same time, the effective common intersection points in the third intersection result are matched and replaced with the corresponding upper limit points in the original sequence, and finally the optimized upper limit point sequence is integrated and generated;

[0148] In the embodiment, by repeating the vector calculation and angle analysis process as a new sequence of key points, iterative convergence is achieved, gradually eliminating concave morphological features, ensuring the final sequence is smooth and regular, and solving the problem of incomplete single morphological processing. After the sequence converges to a non-concave angle, the intersection with the constraint point interval is calculated and global compliance verification is performed. The intersection point is accurately determined to meet the design rules. Different optimization strategies are used for different verification results: if the third intersection result meets the intersection point condition, the effective common intersection point is directly reused to replace the upper limit point to be optimized in the original upper limit point sequence, and the sequence accuracy is preserved with minimal changes; if it does not meet the condition, the upper limit point is adjusted by 1mm, the adjustment range is strictly controlled to avoid morphological distortion, and the compliant intersection point is integrated for optimization. The whole process is automatically executed based on algorithmic rules to improve batch processing consistency. The optimized upper limit point sequence can be directly connected to the design of parting line, mold boundary planning and other industrial processes, effectively reducing the risk of production rework and improving the accuracy and efficiency of design and processing.

[0149] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system or device, unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

[0150] Finally, it should be noted that: the above only for the preferred examples of the present application, and not for the limitation of the present application, although the present application is described in detail with reference to the foregoing embodiments, for those skilled in the art, it still can modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for parting line constraint point interval optimization, characterized in that, The method comprises the following steps: obtaining a lower limit point sequence from a preset constraint point interval sequence; that is, traversing the preset constraint point interval sequence, extracting the boundary point close to the side of the part from each independent constraint point interval, the boundary point being the lower limit point, and integrating all the extracted lower limit points to form an initial lower limit point sequence; optimizing the lower limit point sequence according to a preset convex hull algorithm and a preset intersection point condition to obtain an optimized lower limit point sequence; the optimization of the lower limit point sequence according to the preset convex hull algorithm and the preset intersection point condition to obtain the optimized lower limit point sequence comprises: analyzing the lower limit point sequence according to the convex hull algorithm to obtain first convex hull contour data; analyzing the lower limit point sequence according to the first convex hull contour data to obtain all non-convex hull points; mapping and analyzing each non-convex hull point and the constraint point interval sequence to obtain a mapping constraint point interval of each non-convex hull point; analyzing the lower limit point sequence according to the first convex hull contour data to obtain a convex hull shape; optimizing the lower limit point sequence according to the intersection point condition, the mapping constraint point interval of each non-convex hull point and the convex hull shape to obtain an optimized lower limit point sequence, wherein, for each non-convex hull point, the convex hull shape and the mapping constraint point interval corresponding to the non-convex hull point are subjected to a geometric intersection operation to generate a new intersection point set, and if all the new intersection points intersect with any constraint point interval in the constraint point interval sequence, it is determined that the intersection point condition is satisfied; obtaining an upper limit point sequence from the constraint point interval sequence; optimizing the upper limit point sequence according to the convex hull algorithm and the intersection point condition to obtain an optimized upper limit point sequence; generating an optimized constraint point interval sequence according to the optimized lower limit point sequence and the optimized upper limit point sequence.

2. The method of Claim 1, wherein, the obtaining of the lower limit point sequence from the preset constraint point interval sequence comprises: obtaining the lower limit points of each constraint point interval in the constraint point interval sequence to obtain a lower limit point sequence; morphological analysis is performed on the lower limit point sequence to obtain a first morphological analysis result; if the first morphological analysis result is a convex lower limit point morphology set, the lower limit points in the lower limit point sequence are reordered according to a preset ordering rule to obtain a lower limit point sequence.

3. The method of Claim 1, wherein, the analysis of the lower limit point sequence according to the first convex hull contour data to obtain all non-convex hull points comprises: feature analysis is performed on the first convex hull contour data to obtain a first convex hull point sequence; matching analysis is performed on the first convex hull point sequence and the lower limit point sequence to obtain a matching analysis result; if the matching analysis result is that there is a non-convex hull point in the lower limit point sequence, all the non-convex hull points are obtained from the matching analysis result.

4. The method of Claim 1, wherein, the optimization of the lower limit point sequence according to the intersection point condition, the mapping constraint point interval of each non-convex hull point and the convex hull shape to obtain the optimized lower limit point sequence comprises: intersection is performed on the convex hull shape and the mapping constraint point interval of each non-convex hull point to obtain a first intersection result; the first intersection result is verified according to the intersection point condition to obtain a first verification result; If the first verification result is that the first intersection result does not satisfy the intersection point condition, the lower limit point sequence is optimized according to a preset value distance and the first intersection result to obtain an optimized lower limit point sequence. If the first verification result is that the first intersection result satisfies the intersection point condition, the lower limit point sequence is optimized according to the first intersection result to obtain an optimized lower limit point sequence.

5. The method of Claim 2, wherein, The upper limit point sequence is obtained from the constraint point interval sequence, including: An upper limit point of each constraint point interval in the constraint point interval sequence is obtained to obtain an upper limit point sequence; A morphological analysis is performed on the upper limit point sequence to obtain a second morphological analysis result; If the second morphological analysis result is a convex upper limit point shape set, each upper limit point in the upper limit point sequence is reordered according to a sorting rule to obtain an upper limit point sequence.

6. The method of Claim 4, wherein, The upper limit point sequence is optimized according to the convex hull algorithm and the intersection point condition to obtain an optimized upper limit point sequence, including: The upper limit point sequence is analyzed according to the convex hull algorithm to obtain second convex hull contour data; The upper limit point sequence is detected according to the second convex hull contour data to obtain a second intersection result; The upper limit point sequence is analyzed according to a preset concave direction angle interval and the second intersection result to obtain an angle analysis result; A mapping analysis is performed on the angle analysis result and the upper limit point sequence to obtain a key point sequence; The upper limit point sequence is optimized according to the intersection point condition and the key point sequence to obtain an optimized upper limit point sequence.

7. The method of Claim 6, wherein, The upper limit point sequence is detected according to the second convex hull contour data to obtain a second intersection result, including: Feature extraction is performed on the second convex hull contour data to obtain a second convex hull point sequence; A first upper limit point and a tail upper limit point are obtained from the second convex hull point sequence; The first upper limit point and the tail upper limit point are connected to obtain a head-tail connection line; The head-tail connection line and the upper limit point sequence are intersected to obtain a second intersection result.

8. The method of Claim 7, wherein, The upper limit point sequence is analyzed according to a preset concave direction angle interval and the second intersection result to obtain an angle analysis result, including: If the second intersection result is that there is no upper limit point of a non-head-tail point on the head-tail connection line, a vector of each pair of adjacent upper limit points in the upper limit point sequence is generated by vector calculation; A vector sequence is formed according to all the vectors; The vector sequence is analyzed according to the concave direction angle interval to obtain an angle analysis result.

9. The method of Claim 8, wherein, The vector sequence is analyzed according to the concave direction angle interval to obtain an angle analysis result, including: An angle of each pair of adjacent vectors in the vector sequence is generated by angle calculation; An angle sequence is formed according to all the angles; The angle sequence is analyzed according to the concave direction angle interval to obtain an angle analysis result.

10. The method of Claim 9, wherein, The mapping analysis is performed on the angle analysis result and the upper limit point sequence to obtain a key point sequence, including: When the angle analysis result is that there is a concave direction angle, all the concave direction angles are obtained from the angle analysis result; Mapping analysis is performed on all concave direction angle and upper limit point sorting sequence to obtain upper limit points corresponding to each concave direction angle; The upper limit points corresponding to each concave direction angle are taken as key points; A key point sequence is formed according to all key points, the first upper limit point and the tail upper limit point.

11. The method of Claim 8, wherein the method further comprises: The optimization of the upper limit point sorting sequence according to the intersection condition and the key point sequence to obtain the optimized upper limit point sorting sequence comprises: The key point sequence is taken as a new upper limit point sorting sequence, and the execution is returned to the vector calculation of each pair of adjacent upper limit points in the upper limit point sorting sequence to generate a vector of each pair of adjacent upper limit points in turn until the concave direction angle analysis result is no concave direction angle; If the concave direction angle analysis result is no concave direction angle, the intersection of the upper limit point sorting sequence and each constraint point interval is calculated to obtain a third intersection result; The third intersection result is verified according to the intersection condition to obtain a verification result; If the verification result is that the third intersection result does not satisfy the intersection condition, the upper limit point sorting sequence is optimized according to the value distance and the third intersection result to obtain the optimized upper limit point sorting sequence; If the verification result is that the third intersection result satisfies the intersection condition, the upper limit point sorting sequence is optimized according to the third intersection result to obtain the optimized upper limit point sorting sequence.

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