Functional area segmentation method for special clothing based on topological data analysis

Abstract

The invention discloses a method for segmenting and dividing functional areas of special clothing based on topological data analysis, S1. Preprocessing three-dimensional point cloud data and dynamic pressure distribution data; S2. Calculating a preliminary functional area division scheme based on the importance of nodes in a topological network model; S3. Forming a preliminary division framework of functional areas based on geometric characteristics; S4. Matching the preliminary functional area division scheme with the preliminary division framework to form a functional requirement optimization scheme; S5. Obtaining a special clothing functional area division scheme that adapts to functional requirements through multiple iterations of optimization; S6. Simulating and testing the optimized special clothing functional area division scheme, and adjusting the special clothing functional area division scheme based on the simulation results to obtain the final special clothing functional area division scheme. The invention jointly optimizes the boundaries of functional areas by topological entropy and fractal dimension so that the division results can better reflect the dynamic pressure distribution and geometric complexity characteristics under the actual use environment.

Description

Technical Field

[0001] The invention relates to the technical field of special clothing, and in particular to a method for segmenting and dividing functional areas of special clothing based on topological data analysis. Background Art

[0002] With the growing demand for special clothing, the functional area division technology of special clothing has become an important basis for ensuring its performance. Special clothing usually needs to have protection, comfort and durability. The reasonable division of different functional areas directly affects the use effect and user experience of the clothing. However, under the existing technical conditions, the division of functional areas of special clothing still faces many challenges.

[0003] At present, the functional area division of special clothing is mostly based on experience or macro models. Designers usually make preliminary division of functional areas through manual methods according to the usage scenarios and material properties of the clothing. Although this method has certain practicality, it lacks scientific analysis of data and structure.

[0004] In recent years, with the development of point cloud data processing and topological network analysis technology, some methods based on three-dimensional modeling and data analysis have begun to be applied to the functional area division of special clothing. The three-dimensional modeling technology of point cloud data can provide the spatial feature information of clothing, and the topological network analysis can reveal the correlation between different areas. However, there are still the following problems in practical applications: on the one hand, point cloud modeling is easily affected by data noise and uneven sampling, resulting in loss of model details and large modeling errors; on the other hand, the existing topological network analysis is mostly limited to simple node and edge relationships, and it is difficult to fully combine complex mechanical performance data and geometric characteristics for optimization. In addition, the existing methods lack specificity in the division of multi-functional areas, and are still insufficient for the accurate division of high-wear areas, high-pressure areas and flexible demand areas in dynamic environments.

[0005] To sum up, the existing technology has significant deficiencies in the accuracy, dynamic adaptability and functional diversity of the functional area division of special clothing. The defects of the existing technology directly affect the performance optimization and use effect of special clothing. There is an urgent need for a scientific and efficient functional area division method to solve the problems existing in the existing technology and provide strong technical support for the design of special clothing. Summary of the invention

[0006] One purpose of the present invention is to propose a method for segmenting and dividing functional areas of special clothing based on topological data analysis. The present invention jointly optimizes the boundaries of functional areas by topological entropy and fractal dimension so that the division results can better reflect the dynamic pressure distribution and geometric complexity characteristics in the actual use environment.

[0007] A method for segmenting and dividing functional areas of special clothing based on topological data analysis according to an embodiment of the present invention comprises the following steps:

[0008] S1. Acquire three-dimensional point cloud data of special clothing and dynamic pressure distribution data in the use environment, and pre-process the three-dimensional point cloud data and dynamic pressure distribution data;

[0009] S2. Use the preprocessed dynamic pressure distribution data to build a topological network model, and calculate the preliminary functional area division scheme based on the node importance of the topological network model;

[0010] S3. Input the pre-processed three-dimensional point cloud data of special clothing into the fractal network generation system, extract the fractal dimension and geometric characteristics of the three-dimensional point cloud data through the fractal network, generate a fractal network model, and form a preliminary division framework of functional areas based on the geometric characteristics;

[0011] S4. Match the preliminary functional area division scheme with the preliminary division framework, identify the high wear areas, high pressure areas and flexible demand areas in the functional areas of special clothing by integrating the functional demand distribution and geometric characteristics, and form a functional demand optimization plan;

[0012] S5. Based on the functional requirement optimization scheme, the node complexity characteristics in the topological network model are combined with the fractal dimension in the fractal network model to adjust the boundaries of the functional areas of special clothing. Through multiple iterative optimizations, the functional area division scheme of special clothing that meets the functional requirements is obtained;

[0013] S6. Conduct simulation tests on the optimized special clothing functional area division scheme, and adjust the special clothing functional area division scheme based on the simulation results to obtain the final special clothing functional area division scheme.

[0014] Optionally, S1 includes the following specific operations:

[0015] S11. Obtaining 3D point cloud data of special clothing , 3D point cloud data Contains n discrete points in the three-dimensional space of special clothing ;

[0016] Collect dynamic pressure distribution data D in the use environment, which contains m stress points on the clothing surface ;

[0017] S12. 3D point cloud data Perform denoising to remove isolated points using a density-based point filtering method;

[0018] S13. Using Gaussian filtering method to smooth the three-dimensional point cloud data P and dynamic pressure distribution data D;

[0019] S14. Normalize the smoothed 3D point cloud data and dynamic pressure distribution data, and output the denoised, smoothed, and normalized 3D point cloud data and dynamic pressure distribution data .

[0020] Optionally, S2 includes the following specific operations:

[0021] S21. Dynamic pressure distribution data Each stress point in Defines the global node set of the global topology network model , where the node Corresponding to the jth force point , define the global edge set in the global topology network model , Represents the global node With Node The association relationship between , through the global node set With the global edge set Constructing a global topology network model ;

[0022] S22. Global topology network model Each global node in Calculate global importance index , which is used to characterize the influence of global nodes in the overall functional area of ​​special clothing:

[0023] ;

[0024] in, For global nodes The importance index in the global topological network model indicates the global influence of the node in the functional area distribution of the entire special clothing;

[0025] S23. Based on the global importance index The calculation results of the global nodes are selected, and a group of global nodes whose importance is higher than the preset value is selected. , Corresponding to the global nodes with significant force characteristics in the special clothing, determine the local focus area;

[0026] S24. For global nodes with significant force characteristics Corresponding dynamic pressure distribution data subset , define the local topology network model , where the local node set correspond The global nodes and local edge sets in Each local edge in The edge weight is ;

[0027] S25. Local topology network model Each local node in Calculate local importance index ;

[0028] S26. Global topology network model The overall functional regional association characteristics and local topological network model reflected Comprehensively analyze the characteristics of the key stress areas reflected and make a plan for the functional area division To evaluate and optimize:

[0029] ;

[0030] in, is a weight parameter used to balance the influence of various indicators on the functional area division results. To prevent small positive numbers with zero denominators, For two sets in the same region The internal nodes correspond to the pressure difference between the stress points. The smaller the pressure difference, the more uniform the pressure distribution in the area. and are the maximum and minimum normalized pressure values ​​of the dynamic pressure distribution data, and They represent the sizes of the intersection and union of node neighborhoods in the local and global topological networks, respectively, and are used to characterize the overlap and complementarity of local and global structural features.

[0031] Optionally, S3 includes the following specific operations:

[0032] S31. 3D point cloud data Input fractal network generation system to build fractal network model , where the node set U represents each point in the three-dimensional point cloud data , edge set Represents the spatial association relationship between nodes and obtains the node With Node The edge weight between ;

[0033] S32. In the fractal network model Extract fractal dimensions that reflect the geometric complexity of local areas ;

[0034] S33. Based on fractal dimension and edge weight Extract each node Geometric characteristics of , which is used to measure the distribution of geometric characteristics of the local area where the node is located:

[0035] ;

[0036] in, For Node The set of neighbor nodes of Comprehensively reflect the superposition effect of fractal dimension distribution and weight allocation;

[0037] S34. Geometric property index based on each node Form a preliminary framework for functional area division ,in Represents a preliminary functional area cluster consisting of several nodes;

[0038] Evaluate and optimize the preliminary functional area division framework to make it meet the design requirements of special clothing in terms of geometric characteristics:

[0039] ;

[0040] in, , , is the weight parameter, Indicates area The average value of all the node geometric characteristic indicators, For Region The average coordinates of the corresponding points of all nodes in the region are used to maintain the compact distribution of the region in three-dimensional space. Indicates area The closer the average value of the fractal dimension of the internal nodes is, the more balanced the point cloud complexity in the region is. and are the maximum and minimum values ​​of the geometric characteristic index of the overall fractal network node, and is the maximum and minimum value of the fractal dimension of the overall fractal network node, It is the maximum Euclidean distance between any two nodes in the three-dimensional point cloud data, which is used to normalize the spatial distribution characteristics and maintain the rationality of the regional spatial configuration.

[0041] Optionally, S4 includes the following specific operations:

[0042] S41. Match the preliminary functional area division scheme F with the preliminary functional area division framework H to establish each functional area and partition framework The similarity matrix :

[0043] ;

[0044] in, and Represents functional areas and partition framework The nodes in represents the Euclidean distance between two nodes, For Node The geometric characteristic index, is the maximum value of all node geometric characteristic indices, is a smoothing parameter to control the matching sensitivity;

[0045] S42. Based on the similarity matrix For functional areas and partition framework Perform joint clustering to form a matched functional area set M. Each matching area in the functional area set It is composed of multiple functional areas and divided framework areas;

[0046] S43. For each matching area , combined with dynamic pressure distribution data and geometric characteristic index Identify high wear areas, high pressure areas and flexibility demand areas, and calculate comprehensive functional demand indicators :

[0047] ;

[0048] in, , , Weight parameters are used to balance the effects of geometric characteristics, pressure distribution and flexibility requirements on comprehensive functional requirements. is the normalized pressure value of the corresponding node in the dynamic pressure distribution data, is the geometric center of the nodes in the matching area;

[0049] S44. Based on comprehensive functional requirements indicators Will match the area The nodes in the , high pressure areas and flexible demand areas , the division rules are as follows:

[0050] like ,node It is a high wear area;

[0051] like ,node It belongs to the high pressure area;

[0052] like ,node Belongs to the flexible demand area;

[0053] in, and The threshold of comprehensive functional requirement index is set to meet ;

[0054] S45. Summarize the high wear area, high pressure area and flexibility requirement area of ​​each matching area to form a functional requirement optimization plan:

[0055] ;

[0056] in, Indicates high wear areas of the specialty garment as a whole, Indicates the high pressure area of ​​the special clothing as a whole, Represents the overall flexible demand area for special clothing.

[0057] Optionally, S5 includes the following specific operations:

[0058] S51. Map each area set in the functional requirement optimization solution O to the node set N in the topological network model and the node set U in the fractal network model, and establish the optimization objective function Used to measure the rationality of regional division boundaries:

[0059] ;

[0060] in, Represents each area in the functional requirements optimization solution, For topological network model nodes The complexity characteristics of For fractal network model nodes fractal dimension;

[0061] S52. Based on the optimization objective function , for each region The boundary of the node is adjusted. The adjustment rule is as follows: or The comprehensive boundary contribution value or If it exceeds the preset threshold, it will be assigned to the adjacent functional area;

[0062] S53. updating the edge weights and fractal dimensions of neighboring nodes of newly added or removed nodes during the boundary adjustment process;

[0063] S54. Recalculate the functional area division plan based on the adjusted boundaries , compare the objective function values ​​before and after optimization change:

[0064] If the optimized objective function value after optimization Less than the optimization objective function value before optimization , then accept the optimization result;

[0065] If the optimization objective function value If there is no improvement, stop iterating;

[0066] S55. Repeat the iterative process from S51 to S54 until the objective function value is optimized. Converge or reach the preset optimization times threshold, and output the optimized functional area division plan of special clothing .

[0067] Optionally, S6 includes the following specific operations:

[0068] S61. Establish a simulation environment, set simulation conditions corresponding to the use scenario of special clothing, including dynamic pressure distribution, friction coefficient, material properties and environmental variables, and generate a mechanical model for simulation by combining normalized dynamic pressure distribution data with material characteristic parameters;

[0069] S62. The optimized functional area division scheme of special clothing is input into the mechanical model for simulation test. By analyzing the shear resistance of high wear areas, the load-bearing performance of high pressure areas, and the deformation capacity of flexible demand areas, the performance indicators of each functional area are calculated respectively:

[0070] The performance index of the high wear area is comprehensively evaluated by the shear strength of the nodes in the area and the distance distribution between the nodes;

[0071] The performance index of the high pressure area is calculated based on the distribution relationship between the dynamic pressure value of the nodes in the area and the elastic modulus of the material;

[0072] The performance index of the flexible demand area is obtained by comprehensive analysis of the inverse value of the elastic modulus of the material in the area and the spatial distribution characteristics of the node position;

[0073] S63. Adjust the functional area division plan according to the simulation results. The adjustment rules are as follows:

[0074] When the performance index of a functional area does not meet the preset requirements, increase the node density of the functional area or adjust the material characteristic parameters of the nodes in the functional area;

[0075] The adjusted functional area boundaries are redefined based on the spatial distribution characteristics between nodes, and the neighborhood relationships and distribution characteristic values ​​of the nodes in the functional area are updated at the same time;

[0076] S64. Re-simulate the adjusted functional area division scheme to verify whether the adjusted performance indicators meet the preset requirements:

[0077] If the performance index of the adjusted functional area reaches the set threshold, the adjusted functional area division plan shall be recorded;

[0078] If the performance index does not meet the requirements, readjust the node density or material properties based on the updated characteristics of the nodes in the functional area and repeat the simulation test;

[0079] S65. Repeat steps S61-S64 until the performance indicators of each functional area meet the preset requirements, and finally output a verified special clothing functional area division plan .

[0080] The beneficial effects of the present invention are:

[0081] The present invention combines topological network data analysis with point cloud fractal network and applies it to the functional area division of special clothing. By utilizing the node complexity characteristics in the topological network and the geometric characteristic indicators in the fractal network to form a multi-level optimization strategy, the problem that the functional area division in the prior art relies on experience and subjective judgment is effectively solved. The boundaries of the functional areas are jointly optimized by topological entropy and fractal dimension, so that the division results can better reflect the dynamic pressure distribution and geometric complexity characteristics under the actual use environment.

[0082] The dynamic matching algorithm proposed in the present invention calculates the similarity matrix between the functional area division scheme and the preliminary division framework, and dynamically adjusts the boundary and node density of the area division in combination with the functional requirement optimization scheme, thereby ensuring that the division result can adapt to different usage environments. Through multiple iterative optimizations using dynamic pressure distribution and material performance data for adjustment, the convergence of the optimization objective function value is significantly improved.

[0083] The present invention evaluates the shear resistance of high-wear areas, the bearing capacity of high-pressure areas, and the deformation capacity of flexible demand areas of special clothing by performing multi-dimensional performance tests on the functional area division scheme in a simulation environment, and makes dynamic adjustments based on the simulation results to ensure the practical feasibility of the final scheme. The division scheme after simulation verification significantly improves the adaptability of material properties in key functional areas. The durability index of high-wear areas is improved by 12%, the bearing capacity of high-pressure areas is improved by 16%, and the deformation capacity of flexible demand areas is increased by 10%. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0085] Figure 1 A flowchart of a method for segmenting and dividing functional areas of special clothing based on topological data analysis proposed by the present invention;

[0086] Figure 2 A schematic diagram of the dynamic adjustment of the functional requirement optimization scheme in the process of optimizing the functional area division of a special clothing functional area segmentation method based on topological data analysis proposed by the present invention. DETAILED DESCRIPTION

[0087] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, and therefore only show the components related to the present invention.

[0088] refer to Figure 1-Figure 2 , a method for segmenting functional areas of special clothing based on topological data analysis, comprising the following steps:

[0089] S1. Acquire three-dimensional point cloud data of special clothing and dynamic pressure distribution data in the use environment, and pre-process the three-dimensional point cloud data and dynamic pressure distribution data;

[0090] S2. Use the preprocessed dynamic pressure distribution data to build a topological network model, and calculate the preliminary functional area division scheme based on the node importance of the topological network model;

[0091] S3. Input the pre-processed three-dimensional point cloud data of special clothing into the fractal network generation system, extract the fractal dimension and geometric characteristics of the three-dimensional point cloud data through the fractal network, generate a fractal network model, and form a preliminary division framework of functional areas based on the geometric characteristics;

[0092] S4. Match the preliminary functional area division scheme with the preliminary division framework, identify the high wear areas, high pressure areas and flexible demand areas in the functional areas of special clothing by integrating the functional demand distribution and geometric characteristics, and form a functional demand optimization plan;

[0093] S5. Based on the functional requirement optimization scheme, the node complexity characteristics in the topological network model are combined with the fractal dimension in the fractal network model to adjust the boundaries of the functional areas of special clothing. Through multiple iterative optimizations, the functional area division scheme of special clothing that meets the functional requirements is obtained;

[0094] S6. Conduct simulation tests on the optimized special clothing functional area division scheme, and adjust the special clothing functional area division scheme based on the simulation results to obtain the final special clothing functional area division scheme.

[0095] In this implementation, S1 includes the following specific operations:

[0096] S11. Obtaining 3D point cloud data of special clothing , 3D point cloud data Contains n discrete points in the three-dimensional space of special clothing ;

[0097] Collect dynamic pressure distribution data D in the use environment, which contains m stress points on the clothing surface ;

[0098] S12. 3D point cloud data Perform denoising to remove isolated points using a density-based point filtering method;

[0099] S13. Using Gaussian filtering method to smooth the three-dimensional point cloud data P and dynamic pressure distribution data D;

[0100] S14. Normalize the smoothed 3D point cloud data and dynamic pressure distribution data, and output the denoised, smoothed, and normalized 3D point cloud data and dynamic pressure distribution data .

[0101] In this implementation, S2 includes the following specific operations:

[0102] S21. Dynamic pressure distribution data Each stress point in Defines the global node set of the global topology network model , where the node Corresponding to the jth force point , define the global edge set in the global topology network model , Represents the global node With Node The association relationship between , through the global node set With the global edge set Constructing a global topology network model ;

[0103] S22. Global topology network model Each global node in Calculate global importance index , which is used to characterize the influence of global nodes in the overall functional area of ​​special clothing:

[0104] ;

[0105] in, For global nodes The importance index in the global topological network model indicates the global influence of the node in the functional area distribution of the entire special clothing;

[0106] S23. Based on the global importance index The calculation results of the global nodes are selected, and a group of global nodes whose importance is higher than the preset value is selected. , Corresponding to the global nodes with significant force characteristics in the special clothing, determine the local focus area;

[0107] S24. For global nodes with significant force characteristics Corresponding dynamic pressure distribution data subset , define the local topology network model , where the local node set correspond The global nodes and local edge sets in Each local edge in The edge weight is ;

[0108] S25. Local topology network model Each local node in Calculate local importance index ;

[0109] S26. Global topology network model The overall functional regional association characteristics and local topological network model reflected Comprehensively analyze the characteristics of the key stress areas reflected and make a plan for the functional area division To evaluate and optimize:

[0110] ;

[0111] in, is the objective function, is a weight parameter used to balance the influence of various indicators on the functional area division results. To prevent small positive numbers with zero denominators, For two sets in the same region The internal nodes correspond to the pressure difference between the stress points. The smaller the pressure difference, the more uniform the pressure distribution in the area. and are the maximum and minimum normalized pressure values ​​of the dynamic pressure distribution data, and They represent the sizes of the intersection and union of node neighborhoods in the local and global topological networks, respectively, and are used to characterize the overlap and complementarity of local and global structural features.

[0112] The goal is to integrate multiple key indicators by weighting, build an optimization objective function, and guide the dynamic adjustment and iterative optimization of regional division.

[0113] The first one ensures that the importance of local key nodes matches their global roles by proportionality, thus avoiding the situation where important nodes are ignored in local area partitioning.

[0114] The second item optimizes the pressure uniformity within the area by reducing the difference in pressure values, ensuring that the area division results are more adaptable in actual use.

[0115] The third item optimizes the overall coordination of regional division by improving the similarity between local and global neighborhoods, avoiding local regions from splitting the global network structure.

[0116] In this implementation, S3 includes the following specific operations:

[0117] S31. Input 3D point cloud data into the fractal network generation system to build a fractal network model , where the node set U represents each point in the three-dimensional point cloud data , edge set Represents the spatial association relationship between nodes and obtains the node With Node The edge weight between ;

[0118] S32. In the fractal network model Extract fractal dimensions that reflect the geometric complexity of local areas ;

[0119] S33. Based on fractal dimension and edge weight Extract each node Geometric characteristics of , which is used to measure the distribution of geometric characteristics of the local area where the node is located:

[0120] ;

[0121] in, For Node The set of neighbor nodes of Comprehensively reflect the superposition effect of fractal dimension distribution and weight allocation;

[0122] S34. Geometric property index based on each node Form a preliminary framework for functional area division ,in Represents a preliminary functional area cluster consisting of several nodes;

[0123] Evaluate and optimize the preliminary functional area division framework to make it meet the design requirements of special clothing in terms of geometric characteristics:

[0124] ;

[0125] in, , , is the weight parameter, Indicates area The average value of all the node geometric characteristic indicators, For Region The average coordinates of the corresponding points of all nodes in the region are used to maintain the compact distribution of the region in three-dimensional space. Indicates area The closer the average value of the fractal dimension of the internal nodes is, the more balanced the point cloud complexity in the region is. and are the maximum and minimum values ​​of the geometric characteristic index of the overall fractal network node, and is the maximum and minimum value of the fractal dimension of the overall fractal network node, It is the maximum Euclidean distance between any two nodes in the three-dimensional point cloud data, which is used to normalize the spatial distribution characteristics and maintain the rationality of the regional spatial configuration.

[0126] In special clothing, the geometric characteristics of functional areas need to be consistent, and the high-wear areas need uniform material distribution characteristics to avoid local weak points. The first item guides the optimization of functional areas by measuring the discreteness of geometric characteristics in the area to ensure the consistency of material performance.

[0127] For high-pressure areas of special clothing, it is necessary to ensure that the spatial distribution of nodes is concentrated to avoid waste of resources or insufficient performance due to excessive functional areas. The second item ensures that the design meets the material distribution and actual usage requirements by optimizing the spatial distribution of functional areas.

[0128] In areas where flexibility is required, the uniformity of the fractal dimension can reflect whether the complex geometric characteristics of the area meet the requirements. The flexible area requires a smooth distribution of fractal dimensions to avoid excessive local rigidity of the material affecting the wearing experience. The third item improves the adaptability of the functional area by optimizing the fractal complexity of the area.

[0129] In this implementation, S4 includes the following specific operations:

[0130] S41. Match the preliminary functional area division scheme F with the preliminary functional area division framework H to establish each functional area and partition framework The similarity matrix :

[0131] ;

[0132] in, and Represents functional areas and partition framework The nodes in represents the Euclidean distance between two nodes, For Node The geometric characteristic index, is the maximum value of all node geometric characteristic indices, is a smoothing parameter to control the matching sensitivity;

[0133] S42. Based on the similarity matrix For functional areas and partition framework Perform joint clustering to form a matched functional area set M. Each matching area in the functional area set It is composed of multiple functional areas and divided framework areas;

[0134] S43. For each matching area , combined with dynamic pressure distribution data and geometric characteristic index Identify high wear areas, high pressure areas and flexibility demand areas, and calculate comprehensive functional demand indicators :

[0135] ;

[0136] in, , , Weight parameters are used to balance the effects of geometric characteristics, pressure distribution and flexibility requirements on comprehensive functional requirements. is the normalized pressure value of the corresponding node in the dynamic pressure distribution data, is the geometric center of the nodes in the matching area;

[0137] S44. Based on comprehensive functional requirements indicators Will match the area The nodes in the , high pressure areas and flexible demand areas , the division rules are as follows:

[0138] like ,node It is a high wear area;

[0139] like ,node It belongs to the high pressure area;

[0140] like ,node Belongs to the flexible demand area;

[0141] in, and The threshold of comprehensive functional requirement index is set to meet ;

[0142] S45. Summarize the high wear area, high pressure area and flexibility requirement area of ​​each matching area to form a functional requirement optimization plan:

[0143] ;

[0144] in, Indicates high wear areas of the specialty garment as a whole, Indicates the high pressure area of ​​the special clothing as a whole, Represents the overall flexible demand area for special clothing.

[0145] In this implementation, S5 includes the following specific operations:

[0146] S51. Map each area set in the functional requirement optimization solution O to the node set N in the topological network model and the node set U in the fractal network model, and establish the optimization objective function Used to measure the rationality of regional division boundaries:

[0147] ];

[0148] in, Represents each area in the functional requirements optimization solution, For topological network model nodes The complexity characteristics of For fractal network model nodes fractal dimension;

[0149] S52. Based on the optimization objective function , for each region The boundary of the node is adjusted. The adjustment rule is as follows: or The comprehensive boundary contribution value or If it exceeds the preset threshold, it will be assigned to the adjacent functional area;

[0150] S53. updating the edge weights and fractal dimensions of neighboring nodes of newly added or removed nodes during the boundary adjustment process;

[0151] S54. Recalculate the functional area division plan based on the adjusted boundaries , compare the objective function values ​​before and after optimization change:

[0152] If the optimized objective function value after optimization Less than the optimization objective function value before optimization , then accept the optimization result;

[0153] If the optimization objective function value If there is no improvement, stop iterating;

[0154] S55. Repeat the iterative process from S51 to S54 until the objective function value is optimized. Converge or reach the preset optimization times threshold, and output the optimized functional area division plan of special clothing .

[0155] In this implementation, S6 includes the following specific operations:

[0156] S61. Establish a simulation environment, set simulation conditions corresponding to the use scenario of special clothing, including dynamic pressure distribution, friction coefficient, material properties and environmental variables, and generate a mechanical model for simulation by combining normalized dynamic pressure distribution data with material characteristic parameters;

[0157] S62. The optimized functional area division scheme of special clothing is input into the mechanical model for simulation test. By analyzing the shear resistance of high wear areas, the load-bearing performance of high pressure areas, and the deformation capacity of flexible demand areas, the performance indicators of each functional area are calculated respectively:

[0158] The performance index of the high wear area is comprehensively evaluated by the shear strength of the nodes in the area and the distance distribution between the nodes;

[0159] The performance index of the high pressure area is calculated based on the distribution relationship between the dynamic pressure value of the nodes in the area and the elastic modulus of the material;

[0160] The performance index of the flexible demand area is obtained by comprehensive analysis of the inverse value of the elastic modulus of the material in the area and the spatial distribution characteristics of the node position;

[0161] S63. Adjust the functional area division plan according to the simulation results. The adjustment rules are as follows:

[0162] When the performance index of a functional area does not meet the preset requirements, increase the node density of the functional area or adjust the material characteristic parameters of the nodes in the functional area;

[0163] The adjusted functional area boundaries are redefined based on the spatial distribution characteristics between nodes, and the neighborhood relationships and distribution characteristic values ​​of the nodes in the functional area are updated at the same time;

[0164] S64. Re-simulate the adjusted functional area division scheme to verify whether the adjusted performance indicators meet the preset requirements:

[0165] If the performance index of the adjusted functional area reaches the set threshold, the adjusted functional area division plan shall be recorded;

[0166] If the performance index does not meet the requirements, readjust the node density or material properties based on the updated characteristics of the nodes in the functional area and repeat the simulation test;

[0167] S65. Repeat steps S61-S64 until the performance indicators of each functional area meet the preset requirements, and finally output a verified special clothing functional area division plan . Example

[0168] Application of embodiment In June 2024, a high-end protective clothing manufacturer in an industrial manufacturing park designed a multifunctional industrial protective clothing for front-line high-risk operators. The company's R&D team found that the existing protective clothing had significant problems in uneven shoulder pressure distribution, severe wear in the knee area, and insufficient flexibility in the joints, resulting in reduced work efficiency of workers and even the risk of strain injuries. In order to improve the design, the team decided to apply the functional area segmentation method based on topological network data analysis and point cloud fractal network proposed in the present invention to comprehensively optimize the protective clothing.

[0169] On June 15, the team used 3D scanning equipment to conduct dynamic scans of 50 front-line workers in a real working environment, and collected 3D point cloud data of each worker in five typical movements (standing, bending, squatting, raising arms and rotating). Each set of point clouds contained approximately 120,000 coordinate points. In addition, the dynamic pressure distribution data on the surface of the clothing was collected in real time through implanted dynamic sensors, and the pressure change curves of the shoulders, elbows, knees and waist were recorded. The samples were sampled 50 times per second, and a total of 240 million pressure data were obtained.

[0170] On June 18, the R&D team denoised and normalized the collected data. During the processing, it was found that the dynamic pressure value in the knee area of ​​a worker during squatting was much higher than the average level (the peak value of dynamic pressure reached 120N / cm², while the average value was 80N / cm²). At the same time, through point cloud data analysis, it was identified that the point cloud distribution density in the worker's knee area was uneven, and the local point cloud noise accounted for 15%. In order to ensure data quality, the team smoothed this part of the point cloud data.

[0171] On June 20, the team used the pre-processed dynamic pressure distribution data to construct a topological network model, defining areas with pressure peaks higher than the threshold of 90N / cm² as high-pressure nodes, and calculated the pressure correlation between nodes. The results showed that the nodes in the shoulder and elbow areas had a high correlation, forming an obvious high-pressure area. At the same time, the three-dimensional point cloud data was analyzed through a fractal network, and the fractal dimension of each node was extracted. The fractal dimension data showed that the geometric complexity of the knee and waist areas was significantly higher than that of other areas, with an average fractal dimension of 2.35 (1.92 for other areas), indicating that these areas are at high risk of wear.

[0172] On June 22, the team matched the results of the topological network and the fractal network and found that the high-pressure areas of the shoulders and elbows covered fewer nodes, accounting for only 12% of the total number of nodes, and the boundaries needed to be further optimized. The team adjusted the node distribution and edge weights through a dynamic matching algorithm, and the density of high-wear nodes in the knee area increased by 20%, eventually forming an optimized functional area division plan.

[0173] On June 25, the optimization scheme was simulated and tested in a high-intensity work scenario. The dynamic pressure distribution results in the shoulder area showed that the peak pressure value was reduced from 120N / cm² to 95N / cm², and the distribution uniformity was improved by 18%. The shear resistance of the knee area was enhanced. After simulating the squatting action 1,000 times, the intact rate of the knee node material reached 98% (85% before optimization), the bending angle of the joint flexible area increased by 12%, and the dynamic response time was shortened by 8%.

[0174] On July 1, the team distributed the optimized protective clothing to 10 front-line workers for a week-long actual test. Workers reported that the comfort in the shoulder area was significantly improved during 8 consecutive hours of high-weight lifting work, and there was no obvious wear in the knee area after frequent squatting and kneeling movements. The improved flexibility in the joint area enabled the workers to move more smoothly and their work efficiency was improved by 15%.

[0175] In order to verify the effectiveness of the method of the present invention, the team selected protective clothing designed by traditional methods as the control group and conducted a performance comparison test under the same environment. The following Table 1 shows the test data:

[0176] Table 1 Performance comparison test data of the method of the present invention and the traditional method under the same environment

[0177] Functional Area Test indicators Method of the present invention Traditional methods Improvement High-stress areas in the shoulders Peak pressure (N / cm²) 95 120 -20.8% High wear area at the knee Material integrity rate (%) 98 85 +15.3% Joint flexibility area Bending angle (°) 55 49 +12.2% Working comfort Worker Feedback Rating 9.1 7.6 +19.7%

[0178] This embodiment has been verified in actual scenarios, fully demonstrating the significant advantages of the method of the present invention in the division of functional areas of special clothing. The optimized protective clothing performs well in adaptability to high-wear, high-pressure and flexible demand areas, and can effectively improve the workers' usage experience and work efficiency, providing scientific and efficient technical support for the design of special clothing.

[0179] The present invention combines topological network data analysis with point cloud fractal network and applies it to the functional area division of special clothing. By utilizing the node complexity characteristics in the topological network and the geometric characteristic indicators in the fractal network to form a multi-level optimization strategy, the problem that the functional area division in the prior art relies on experience and subjective judgment is effectively solved. The boundaries of the functional areas are jointly optimized by topological entropy and fractal dimension, so that the division results can better reflect the dynamic pressure distribution and geometric complexity characteristics under the actual use environment.

[0180] The dynamic matching algorithm proposed in the present invention calculates the similarity matrix between the functional area division scheme and the preliminary division framework, and dynamically adjusts the boundary and node density of the area division in combination with the functional requirement optimization scheme, thereby ensuring that the division result can adapt to different usage environments. Through multiple iterative optimizations using dynamic pressure distribution and material performance data for adjustment, the convergence of the optimization objective function value is significantly improved.

[0181] The present invention evaluates the shear resistance of high-wear areas, the bearing capacity of high-pressure areas, and the deformation capacity of flexible demand areas of special clothing by performing multi-dimensional performance tests on the functional area division scheme in a simulation environment, and makes dynamic adjustments based on the simulation results to ensure the practical feasibility of the final scheme. The division scheme after simulation verification significantly improves the adaptability of material properties in key functional areas. The durability index of high-wear areas is improved by 12%, the bearing capacity of high-pressure areas is improved by 16%, and the deformation capacity of flexible demand areas is increased by 10%.

[0182] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for segmenting functional areas of special clothing based on topological data analysis, characterized in that: The steps include: S1. Acquire three-dimensional point cloud data of special clothing and dynamic pressure distribution data in the use environment, and pre-process the three-dimensional point cloud data and dynamic pressure distribution data; S2. Use the preprocessed dynamic pressure distribution data to build a topological network model, and calculate the preliminary functional area division scheme based on the node importance of the topological network model; S3. Input the pre-processed three-dimensional point cloud data of special clothing into the fractal network generation system, extract the fractal dimension and geometric characteristics of the three-dimensional point cloud data through the fractal network, generate a fractal network model, and form a preliminary division framework of functional areas based on the geometric characteristics; S4. Match the preliminary functional area division scheme with the preliminary division framework, identify the high wear areas, high pressure areas and flexible demand areas in the functional areas of special clothing by integrating the functional demand distribution and geometric characteristics, and form a functional demand optimization plan; S5. Based on the functional requirement optimization scheme, the node complexity characteristics in the topological network model are combined with the fractal dimension in the fractal network model to adjust the boundaries of the functional areas of special clothing. Through multiple iterative optimizations, the functional area division scheme of special clothing that meets the functional requirements is obtained; S6. Conduct simulation tests on the optimized special clothing functional area division scheme, and adjust the special clothing functional area division scheme based on the simulation results to obtain the final special clothing functional area division scheme.

2. According to claim 1, a method for segmenting functional areas of special clothing based on topological data analysis is characterized in that: The S1 includes the following specific operations: S11. Obtaining 3D point cloud data of special clothing , 3D point cloud data Contains n discrete points in the three-dimensional space of special clothing ; Collect dynamic pressure distribution data D in the use environment, which contains m stress points on the clothing surface ; S12. 3D point cloud data Perform denoising to remove isolated points using a density-based point filtering method; S13. Using Gaussian filtering method to smooth the three-dimensional point cloud data P and dynamic pressure distribution data D; S14. Normalize the smoothed 3D point cloud data and dynamic pressure distribution data, and output the denoised, smoothed, and normalized 3D point cloud data and dynamic pressure distribution data .

3. According to claim 2, a method for segmenting and dividing functional areas of special clothing based on topological data analysis is characterized in that: The S2 includes the following specific operations: S21. Dynamic pressure distribution data Each stress point in Defines the global node set of the global topology network model , where the node Corresponding to the jth force point , define the global edge set in the global topology network model , Represents the global node With Node The association relationship between , through the global node set With the global edge set Constructing a global topology network model ; S22. Global topology network model Each global node in Calculate global importance index , which is used to characterize the influence of global nodes in the overall functional area of ​​special clothing: ； in, For global nodes The importance index in the global topological network model indicates the global influence of the node in the functional area distribution of the entire special clothing; S23. Based on the global importance index The calculation results of the global nodes are selected, and a group of global nodes whose importance is higher than the preset value is selected. , Corresponding to the global nodes with significant force characteristics in the special clothing, determine the local focus area; S24. For global nodes with significant force characteristics Corresponding dynamic pressure distribution data subset , define the local topology network model , where the local node set correspond The global nodes and local edge sets in Each local edge in The edge weight is ; S25. Local topology network model Each local node in Calculate local importance index ; S26. Global topology network model The overall functional regional association characteristics and local topological network model reflected Comprehensively analyze the characteristics of the key stress areas reflected and make a plan for the functional area division To evaluate and optimize: ； in, is the objective function, is a weight parameter used to balance the influence of various indicators on the functional area division results. To prevent small positive numbers with zero denominators, For two sets in the same region The internal nodes correspond to the pressure difference between the stress points. The smaller the pressure difference, the more uniform the pressure distribution in the area. and are the maximum and minimum normalized pressure values ​​of the dynamic pressure distribution data, and They represent the sizes of the intersection and union of node neighborhoods in the local and global topological networks, respectively, and are used to characterize the overlap and complementarity of local and global structural features.

4. According to claim 3, a method for segmenting and dividing functional areas of special clothing based on topological data analysis is characterized in that: The S3 includes the following specific operations: S31. 3D point cloud data Input fractal network generation system to build fractal network model , where the node set U represents each point in the three-dimensional point cloud data , edge set Represents the spatial association relationship between nodes and obtains the node With Node The edge weight between ; S32. In the fractal network model For each node Extract fractal dimensions that reflect the geometric complexity of local areas ; S33. Based on fractal dimension and edge weight Extract each node Geometric characteristics of , which is used to measure the distribution of geometric characteristics of the local area where the node is located: ； in, For Node The set of neighbor nodes of Comprehensively reflect the superposition effect of fractal dimension distribution and weight allocation; S34. Geometric property index based on each node Form a preliminary framework for functional area division ,in Represents a preliminary functional area cluster consisting of several nodes; Evaluate and optimize the preliminary functional area division framework to make it meet the design requirements of special clothing in terms of geometric characteristics: ； in, , , is the weight parameter, Indicates area The average value of all the node geometric characteristic indicators, For Region The average coordinates of the corresponding points of all nodes in the region are used to maintain the compact distribution of the region in three-dimensional space. Indicates area The closer the average value of the fractal dimension of the internal nodes is, the more balanced the point cloud complexity in the region is. and are the maximum and minimum values ​​of the geometric characteristic index of the overall fractal network node, and is the maximum and minimum value of the fractal dimension of the overall fractal network node, It is the maximum Euclidean distance between any two nodes in the three-dimensional point cloud data, which is used to normalize the spatial distribution characteristics and maintain the rationality of the regional spatial configuration.

5. According to claim 4, a method for segmenting and dividing functional areas of special clothing based on topological data analysis is characterized in that: The S4 includes the following specific operations: S41. Match the preliminary functional area division scheme F with the preliminary functional area division framework H to establish each functional area and partition framework The similarity matrix : ； in, and Represents functional areas and partition framework The nodes in represents the Euclidean distance between two nodes, For Node The geometric characteristic index, is the maximum value of all node geometric characteristic indices, is a smoothing parameter to control the matching sensitivity; S42. Based on the similarity matrix For functional areas and partition framework Perform joint clustering to form a matched functional area set M. Each matching area in the functional area set It is composed of multiple functional areas and divided framework areas; S43. For each matching area , combined with dynamic pressure distribution data and geometric characteristic index Identify high wear areas, high pressure areas and flexibility demand areas, and calculate comprehensive functional demand indicators : ； in, , , Weight parameters are used to balance the effects of geometric characteristics, pressure distribution and flexibility requirements on comprehensive functional requirements. is the normalized pressure value of the corresponding node in the dynamic pressure distribution data, is the geometric center of the nodes in the matching area; S44. Based on comprehensive functional requirements indicators Will match the area The nodes in the , high pressure areas and flexible demand areas , the division rules are as follows: like ,node It is a high wear area; like ,node It belongs to the high pressure area; like ,node Belongs to the flexible demand area; in, and The threshold of comprehensive functional requirement index is set to meet ; S45. Summarize the high wear area, high pressure area and flexibility requirement area of ​​each matching area to form a functional requirement optimization plan: ； in, Indicates high wear areas of the specialty garment as a whole, Indicates the high pressure area of ​​the special clothing as a whole, Represents the overall flexible demand area for special clothing.

6. The method for segmenting functional areas of special clothing based on topological data analysis according to claim 5 is characterized in that: The S5 includes the following specific operations: S51. Map each area set in the functional requirement optimization solution O to the node set N in the topological network model and the node set U in the fractal network model, and establish the optimization objective function Used to measure the rationality of regional division boundaries: ]； in, Represents each area in the functional requirements optimization solution, For topological network model nodes The complexity characteristics of For fractal network model nodes fractal dimension; S52. Based on the optimization objective function , for each region The boundary of the node is adjusted. The adjustment rule is as follows: or The comprehensive boundary contribution value or If it exceeds the preset threshold, it will be assigned to the adjacent functional area; S53. updating the edge weights and fractal dimensions of neighboring nodes of newly added or removed nodes during the boundary adjustment process; S54. Recalculate the functional area division plan based on the adjusted boundaries , compare the objective function values ​​before and after optimization change: If the optimized objective function value Less than the optimization objective function value before optimization , then accept the optimization result; If the optimization objective function value If there is no improvement, stop iterating; S55. Repeat the iterative process from S51 to S54 until the objective function value is optimized. Converge or reach the preset optimization times threshold, and output the optimized functional area division plan of special clothing .

7. The method for segmenting functional areas of special clothing based on topological data analysis according to claim 1 is characterized in that: The S6 includes the following specific operations: S61. Establish a simulation environment, set simulation conditions corresponding to the use scenario of special clothing, including dynamic pressure distribution, friction coefficient, material properties and environmental variables, and generate a mechanical model for simulation by combining normalized dynamic pressure distribution data with material characteristic parameters; S62. The optimized functional area division scheme of special clothing is input into the mechanical model for simulation test. By analyzing the shear resistance of high wear areas, the load-bearing performance of high pressure areas, and the deformation capacity of flexible demand areas, the performance indicators of each functional area are calculated respectively: The performance index of the high wear area is comprehensively evaluated by the shear strength of the nodes in the area and the distance distribution between the nodes; The performance index of the high pressure area is calculated based on the distribution relationship between the dynamic pressure value of the nodes in the area and the elastic modulus of the material; The performance index of the flexible demand area is obtained by comprehensive analysis of the inverse value of the elastic modulus of the material in the area and the spatial distribution characteristics of the node position; S63. Adjust the functional area division plan according to the simulation results. The adjustment rules are as follows: When the performance index of a functional area does not meet the preset requirements, increase the node density of the functional area or adjust the material characteristic parameters of the nodes in the functional area; The adjusted functional area boundaries are redefined based on the spatial distribution characteristics between nodes, and the neighborhood relationships and distribution characteristic values ​​of the nodes in the functional area are updated at the same time; S64. Re-simulate the adjusted functional area division scheme to verify whether the adjusted performance indicators meet the preset requirements: If the performance index of the adjusted functional area reaches the set threshold, the adjusted functional area division plan shall be recorded; If the performance index does not meet the requirements, readjust the node density or material properties based on the updated characteristics of the nodes in the functional area and repeat the simulation test; S65. Repeat steps S61-S64 until the performance indicators of each functional area meet the preset requirements, and finally output a verified special clothing functional area division plan .

Images