Automatic checking method and system for silk breathable hole structure

Abstract

The invention relates to the technical field of silk detection, in particular to an automatic checking method and system for a silk breathable hole structure. According to the invention, by acquiring the basic parameters and environmental conditions of the silk and setting the test conditions, accurate test can be carried out in a specific environment, and by analyzing the spatio-temporal evolution data of the silk surface temperature field and the water vapor concentration field, the dynamic change of heat and humidity of the fabric in actual wearing can be comprehensively known, and the real-time performance of the fabric is improved. And three-dimensional component information of a transient airflow velocity field is combined to provide a solid data basis for collaborative analysis of air permeability and moisture permeability, so that a local transient collaborative coefficient related to the air permeability and the moisture permeability can be extracted through automatic verification of the silk air-permeable pore structure, an air-permeable-moisture-permeable efficiency spectrum can be generated, and the air-permeable-moisture-permeable performance of the silk is improved. And comparison with a preset comfort performance evaluation standard can be carried out, so that more comprehensive and reliable comfort performance evaluation is provided.

Description

Technical Field

[0001] This invention relates to the field of silk testing technology, and in particular to an automatic verification method and system for the breathable pore structure of silk. Background Technology

[0002] Silk breathable grooving structure refers to the structure system of regular / irregular micropores and pore channels formed on or inside the surface of silk fabrics through weaving design, fiber modification or physical opening during the weaving or finishing process. Its core function is to enhance the gas flow and moisture permeability of the fabric, while retaining the luster, softness and other properties of silk itself. It mainly includes woven grooving structure and finishing grooving structure.

[0003] Currently, existing technologies primarily use fabric air permeability testers to inspect the air permeability of silk pore structures. The principle is that the airflow control system of the tester creates a constant gas pressure difference between the upper and lower sides of the air chamber. Driven by this pressure difference, gas flows from the high-pressure side to the low-pressure side through the pore channels of the silk pore structure. The instrument's flowmeter measures the gas flow rate through the sample per unit time in real time to obtain the fabric's air permeability and evaluate the pore structure's air permeability performance. However, since the core function of the silk pore structure is to balance air permeability and moisture permeability, fabric air permeability testers can only test air permeability separately and cannot simultaneously measure moisture permeability, nor can they characterize the synergistic relationship between air permeability and moisture permeability, thus failing to comprehensively evaluate the fabric's comfort performance. Summary of the Invention

[0004] The main objective of this invention is to provide an automatic verification method for the breathable perforated structure of silk, aiming to solve the technical problems in the prior art.

[0005] This invention proposes an automatic verification method for the breathable pore structure of silk, comprising: Obtain the basic parameters of the silk and the environmental parameters of the verification environment, and set the test conditions for automatic verification based on the basic parameters and environmental parameters; Acquire the spatiotemporal evolution data of the surface temperature field and water vapor concentration field of the silk in a preset spatial sampling grid under the test conditions; The three-dimensional component information of the transient airflow velocity field inside the breathable pore structure of silk is obtained, and a breathable-moisture-permeable synergistic analysis dataset is constructed based on the three-dimensional component information and spatiotemporal evolution data. Based on the air permeability-moisture permeability synergistic analysis dataset, extract the temperature gradient, water vapor concentration gradient, and three-dimensional airflow velocity component corresponding to each spatiotemporal point in the preset spatial sampling grid to obtain the corresponding local transient synergistic coefficient; The numerical distribution statistical parameters, temporal evolution characteristics, and spatial distribution patterns of multiple local transient synergistic coefficients are obtained to generate the air permeability-moisture permeability synergistic efficiency spectrum of the silk breathable pore structure. The air permeability-moisture permeability synergistic efficiency spectrum is compared with the preset comfort performance evaluation standard to obtain the verification result of the air permeability-moisture permeability synergistic performance of the pore structure, thus completing the automatic verification of the air permeability pore structure of silk.

[0006] This application also provides an automatic verification system for the breathable perforated structure of silk, including: The setting module is used to obtain the basic parameters of the silk and the environmental parameters of the verification environment, and to set the test conditions for automatic verification based on the basic parameters and environmental parameters. The first acquisition module is used to acquire the spatiotemporal evolution data of the surface temperature field and water vapor concentration field of the silk in a preset spatial sampling grid under the test conditions. A construction module is used to obtain the three-dimensional component information of the transient airflow velocity field inside the breathable pore structure of silk, and to construct a breathable-moisture-permeable collaborative analysis dataset based on the three-dimensional component information and spatiotemporal evolution data. The second acquisition module is used to extract the temperature gradient, water vapor concentration gradient and three-dimensional airflow velocity component corresponding to each spatiotemporal point in the preset spatial sampling grid according to the air permeability-moisture permeability synergistic analysis dataset to obtain the corresponding local transient synergistic coefficient. The third acquisition module is used to acquire the numerical distribution statistical parameters, temporal evolution characteristics and spatial distribution laws of multiple local transient synergistic coefficients to generate the air permeability-moisture permeability synergistic efficiency spectrum of the air permeable pore structure of silk. The comparison module is used to compare the synergistic efficiency spectrum with the preset comfort performance evaluation standard to obtain the verification result of the air permeability-moisture permeability synergistic performance of the pore structure, and complete the automatic verification of the air permeability pore structure of silk.

[0007] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described automatic verification method for the breathable pore structure of silk.

[0008] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described automatic verification method for the breathable perforated structure of silk.

[0009] The beneficial effects of this invention are as follows: By acquiring the basic parameters and environmental conditions of silk and setting test conditions, this invention enables precise testing under specific environments. By analyzing the spatiotemporal evolution data of the silk surface temperature field and water vapor concentration field, it is possible to comprehensively understand the dynamic changes of heat and moisture in the fabric during actual wear. Combined with the three-dimensional component information of the transient airflow velocity field, it provides a solid data foundation for the synergistic analysis of breathability and moisture permeability. This allows the automatic verification of the silk breathable pore structure to extract local transient synergistic coefficients related to breathability and moisture permeability. It can not only generate an efficiency spectrum of breathability and moisture permeability, but also compare it with preset comfort performance evaluation standards, providing a more comprehensive and reliable assessment of comfort performance. Attached Figure Description

[0010] Figure 1 This is a schematic diagram of a method flow according to an embodiment of the present invention.

[0011] Figure 2 This is a schematic diagram of the system structure according to an embodiment of the present invention.

[0012] Figure 3 This is a schematic diagram of the internal structure of a computer device according to an embodiment of this application.

[0013] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0014] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0015] like Figure 1 As shown, this application provides an automatic verification method for the breathable perforated structure of silk, including: S1. Obtain the basic parameters of the silk and the environmental parameters of the verification environment, and set the test conditions for automatic verification based on the basic parameters and environmental parameters; S2. Obtain the spatiotemporal evolution data of the silk surface temperature field and water vapor concentration field in the preset spatial sampling grid under the test conditions; S3. Obtain the three-dimensional component information of the transient airflow velocity field inside the breathable pore structure of silk, and construct a breathable-moisture-permeable collaborative analysis dataset based on the three-dimensional component information and spatiotemporal evolution data. S4. Based on the air-permeability-moisture-permeability synergistic analysis dataset, extract the temperature gradient, water vapor concentration gradient, and three-dimensional airflow velocity component corresponding to each spatiotemporal point in the preset spatial sampling grid to obtain the corresponding local transient synergistic coefficient; S5. Obtain the numerical distribution statistical parameters, temporal evolution characteristics and spatial distribution law of multiple local transient synergistic coefficients to generate the air permeability-moisture permeability synergistic efficiency spectrum of the silk breathable pore structure. S6. Compare the air permeability-moisture permeability synergistic efficiency spectrum with the preset comfort performance evaluation standard to obtain the verification result of the air permeability-moisture permeability synergistic performance of the pore structure, and complete the automatic verification of the air permeability pore structure of silk.

[0016] As described in steps S1-S6 above, the step of constructing the air-permeability-humidity co-analysis dataset involves mapping the three-dimensional component information to the corresponding grid nodes through linear interpolation based on the node coordinates of the grid nodes in the preset spatial sampling grid, and extracting the temperature and water vapor concentration at the same time stamp from the temperature spatiotemporal evolution data and water vapor spatiotemporal evolution data and associating them with the three-dimensional component information in the corresponding grid nodes to construct an air-permeability-humidity co-analysis dataset containing spatial coordinates, timestamps, temperature, water vapor concentration, and three-dimensional component information. Through linear interpolation mapping, the problem of spatial coordinate mismatch that may exist between different measurement systems (such as airflow field simulation grid and surface temperature sampling grid) is solved, ensuring that the airflow data can be accurately mapped to each temperature and humidity sampling point. By associating by timestamp, the strict synchronization of airflow state and temperature and humidity state in time is ensured, avoiding misjudgment of co-operation due to data misalignment. The steps for obtaining the local transient coordination coefficient are as follows: Obtain the three-dimensional vectors of the temperature gradient, water vapor concentration gradient, and airflow velocity; multiply the components of the three-dimensional temperature gradient vector and the three-dimensional airflow velocity vector along their corresponding coordinate axes; sum the three products to obtain the temperature-velocity vector dot product, which reflects the basic degree of directional coordination between the two vectors; obtain the temperature gradient magnitude by taking the square root of the sum of the squares of the components of the three-dimensional temperature gradient vector; obtain the velocity magnitude by taking the square root of the sum of the squares of the components of the three-dimensional airflow velocity vector. The magnitude is used to eliminate the interference of the vector's own magnitude on the direction determination; divide the temperature-velocity vector dot product by the product of the temperature gradient magnitude and the velocity magnitude to obtain the temperature-velocity directional fit; the calculation method for the water vapor concentration-velocity directional fit is the same as that for the temperature-velocity directional fit; calculate the local transient coordination coefficient for each spatiotemporal point using the normalized temperature gradient, water vapor concentration gradient, and three-dimensional airflow velocity components, along with their corresponding weighting coefficients and directional fit. The calculation formula is as follows: ;in, Represents the local transient cooperation coefficient. Represents the temperature gradient weights. This represents the normalized temperature gradient. Indicates the degree of fit between temperature and velocity directions. Represents the weights of the water vapor concentration gradient. This represents the normalized water vapor concentration gradient. This indicates the degree of alignment between water vapor concentration and velocity direction. Indicates the weights of the three-dimensional airflow velocity components. It represents the normalized three-dimensional airflow velocity components; by dividing the vector dot product by the modulus product, it reflects the directional synergy, removes the absolute numerical influence of gradient magnitude and airflow velocity magnitude, normalizes the gradient and velocity components, eliminates the influence of different physical dimensions, and allows them to participate in the calculation on the same scale. By introducing a weighting coefficient, it allows for flexible adjustment according to the different emphases on breathability and moisture permeability in actual applications, so that the final synergy coefficient can be customized to reflect the comfort requirements in different scenarios. This invention achieves dynamic adaptive setting of test conditions by introducing basic parameters of silk and environmental parameters of the calibration environment. Compared with existing breathability testers that use fixed pressure difference and single environmental conditions, this invention can accurately simulate real wearing or application scenarios based on actual material properties and usage environment, thus making subsequent measurement data more representative of working conditions and physically realistic. By using a preset spatial sampling grid to monitor the temperature field and water vapor concentration field of the silk surface in a spatiotemporal synchronous manner, dynamic and spatially resolved quantitative acquisition of the moisture permeability process is achieved. By collecting spatiotemporal evolution data, the moisture permeability performance is expanded from a single statistical value to a more comprehensive and accurate measurement. The physical field with temporal and spatial distribution characteristics provides the necessary moisture permeability dataset for subsequent collaborative analysis with the airflow field, making up for the fundamental defect of existing technologies that cannot simultaneously measure moisture permeability. By using the three-dimensional components of the transient airflow velocity field inside the pore structure and spatiotemporally linking and fusing it with the temperature field and water vapor concentration field, a unified collaborative analysis dataset is constructed. By introducing three-dimensional component information, the microscopic motion mode of airflow in the complex pore channel is revealed. The airflow velocity vector field and the temperature and humidity scalar fields are fused in the same spatiotemporal framework, forming the only data basis for subsequent analysis of the collaborative mechanism of air permeability driving moisture permeability. By extracting gradient and airflow velocity vectors from the fused dataset and calculating local transient synergy coefficients, the local transient synergy coefficients essentially characterize the degree of consistency between the airflow direction and the driving direction of heat and moisture diffusion at a microscopic spatiotemporal point. By calculating the dot product relationship between gradient and velocity and performing normalization, the complex synergy effect is quantified into a scalar coefficient, thereby achieving a local and transient quantitative evaluation of the synergy performance of whether air permeability effectively promotes moisture permeability. Through statistical analysis and spatiotemporal evolution analysis, a synergy efficiency spectrum containing statistical distribution, time-varying laws, and spatial laws is generated, which can reflect not only the overall level of synergy efficiency of the perforated structure (such as the mean) but also... Furthermore, it can reveal the uniformity (variance), stability over time, and performance differences in different regions. Through comparison, it can directly output intuitive verification results such as qualified / unqualified or performance level, solving the problem of weak correlation between air permeability index and subjective comfort in existing technologies. This allows the output results of the automatic verification method to directly and scientifically guide product design and quality control. This invention establishes a bridge between the characteristics of the perforation structure and wearing comfort by analyzing the path from local transient synergy coefficient (microscopic mechanism) to the overall synergy efficiency spectrum (macroscopic performance). Through the acquisition and analysis of spatiotemporal evolution data, it can evaluate the performance stability of the fabric during dynamic use.

[0017] In one embodiment, step S1, which sets the test conditions for automatic verification based on the basic parameters and environmental parameters, includes: S11. Obtain the silk thickness, pore size and pore distribution density from the basic parameters to obtain the pore size fit coefficient and density distribution uniformity. S12. Obtain the ambient temperature, ambient humidity and atmospheric pressure from the environmental parameters to obtain the allowable range of temperature and humidity fluctuations and the atmospheric pressure reference value, and determine the initial pressure gradient of the test airflow based on the aperture adaptation coefficient and the atmospheric pressure reference value. S13. Obtain the pressure compensation coefficient based on the roughness of the bore wall in the basic parameters and the atmospheric pressure change rate in the environmental parameters, and obtain the stable test pressure difference based on the pressure compensation coefficient and the initial pressure difference gradient. S14. Determine the minimum threshold for test duration based on the density distribution uniformity and the allowable range of temperature and humidity fluctuations, and integrate the minimum threshold, stable test pressure difference, and allowable range of temperature and humidity fluctuations to obtain test conditions for automatic verification that are adapted to the breathable pore structure of silk.

[0018] As described in steps S11-S14 above, the step of obtaining the aperture adaptation coefficient is to calculate the equivalent aperture of the screw holes based on the actual aperture of multiple screw holes within a unit area, by statistically analyzing the percentage of screw holes in each aperture interval and the average aperture of the screw holes, and then calculating the equivalent aperture of the screw holes based on the average aperture and percentage of each interval. The calculation formula is as follows: ;in, Indicates the equivalent aperture of the screw thread. Indicates the first The average diameter of the orifice in each interval Indicates the first The percentage of the number of screw holes in each interval Indicates the interval index. The number of intervals is indicated; then, the aperture fit coefficient is calculated based on the silk thickness, the equivalent aperture of the pores, and the pore distribution density. The aperture fit coefficient reflects the airflow compatibility between the aperture and the thickness, and the calculation formula is: ;in, Indicates the aperture fit factor. Indicates the equivalent aperture of the screw thread. Indicates the thickness of the silk. Indicates the density of the pore distribution; Density distribution uniformity refers to the degree of spatial equilibrium of the density of pores per unit area on the silk surface. Its core function is to quantify the regularity of the spatial distribution of pores on the silk surface, providing a structural basis for subsequent test condition setting and collaborative performance verification. The initial pressure gradient of the test airflow is obtained by correcting the product of the aperture adaptation coefficient and the atmospheric pressure reference value by the gas viscosity correction coefficient (based on the temperature dependence of the air viscosity coefficient and the airflow characteristics of the pore channel). The aperture adaptation coefficient characterizes the adaptability of the silk structure to the airflow, and the atmospheric pressure reference value eliminates the influence of environmental pressure fluctuations. The coupling calculation of the two can ensure that the initial pressure gradient matches the pore structure and environmental conditions. The formula for calculating the pressure compensation coefficient is: ;in, Indicates the pressure compensation coefficient. Indicates the roughness of the bore wall. Indicates the thickness of the silk. This represents the rate of change of atmospheric pressure. This represents the atmospheric pressure baseline value; the stable test pressure difference is obtained by correcting the product of the pressure compensation coefficient and the initial pressure difference gradient using an environmental adaptation correction coefficient. The steps to determine the minimum threshold for test duration are as follows: First, obtain the upper limits of temperature and humidity standard fluctuations for comfort performance testing. Then, based on density distribution uniformity, obtain the baseline value of the density influence coefficient on duration. Next, obtain the basic duration coefficient. Finally, based on the basic duration coefficient, the baseline value of the influence coefficient, the upper limits of temperature and humidity standard fluctuations, the allowable range of temperature and humidity fluctuations, and density distribution uniformity, calculate the minimum threshold for test duration using the following formula: ;in, This indicates the minimum threshold for test duration. Indicates the uniformity of density distribution. This represents the baseline value of the influence coefficient. Indicates the upper limit of temperature standard fluctuation. Indicates the allowable range of temperature fluctuations. This indicates the upper limit of humidity standard fluctuation. Indicates the allowable range of humidity fluctuations. Indicates the base duration coefficient; This invention calculates the pore size fit coefficient and density distribution uniformity by considering thickness, pore size, and distribution density. This ensures that the subsequently set test conditions match the physical characteristics of the specific pore structure, avoiding excessive turbulence caused by excessive pressure difference in large pores, which would distort the simulation of a light breeze in actual wear, or insufficient pressure difference to effectively drive airflow through the high-density small-pore structure. By determining the allowable range of temperature and humidity fluctuations and the atmospheric pressure benchmark value through ambient temperature, humidity, and atmospheric pressure, the test environment is moved from an ideal laboratory to a simulated real-world scenario. Through dynamic calculation of the initial test driving force based on both structural and environmental factors, the test can be conducted in a more realistic environment from the outset, paving the way for subsequent observations of breathability and moisture permeability under near-realistic conditions. Co-evolution creates the preconditions. Orifice wall roughness affects the airflow boundary layer and frictional resistance, and is a key microstructural factor determining the efficiency of heat and moisture exchange between the airflow and the orifice wall. High-roughness orifice walls increase flow resistance and may enhance turbulence, affecting permeability. The atmospheric pressure change rate reflects the dynamic trend of environmental pressure during the test, directly affecting the stability of the pressure difference. Pressure compensation coefficients are calculated using these two parameters, and the initial pressure difference gradient is corrected in real-time or predictively to obtain a dynamically stable or adaptively adjustable test pressure difference. This allows the test pressure difference to be more stable under different environmental conditions. Dynamic adjustment of airflow and pressure significantly improves the repeatability and reliability of the test. This is achieved through structural characteristics (density distribution uniformity). By linking the environmental simulation requirements (allowable temperature and humidity fluctuation range) to determine the minimum threshold for test duration, the reliability of test results is avoided from being affected by excessively long or short test times. By integrating the minimum threshold (ensuring test sufficiency), stable test pressure difference (ensuring the accuracy of driving conditions), and allowable temperature and humidity fluctuation range (ensuring the realism of environmental simulation), a set of customized automatic verification test conditions that are fully adapted to specific silk breathable pore structures and oriented towards actual application scenarios is output. This ensures that the entire subsequent verification process is carried out under optimized settings with sufficient time, stable conditions, and realistic environmental simulation. This guarantees that the final generated air permeability-moisture permeability synergistic efficiency spectrum can comprehensively and reliably characterize the comprehensive performance of the pore structure under complex working conditions that may be encountered in actual use. This fundamentally overcomes the shortcomings of traditional methods, such as single test conditions, detachment from reality, and inability to support synergistic relationship analysis.

[0019] In one embodiment, step S2, which involves acquiring the spatiotemporal evolution data of the silk surface temperature field and water vapor concentration field in a preset spatial sampling grid under the test conditions, includes: S21. Obtain the division parameters based on the size parameters and orifice distribution range in the basic parameters, and construct a preset spatial sampling grid based on the division parameters; S22. Obtain the sampling frequency parameter according to the allowable range of temperature and humidity fluctuations in the test conditions, and synchronously collect the instantaneous temperature value and instantaneous water vapor concentration value of each grid node in the preset spatial sampling grid in real time according to the sampling frequency parameter. S23. Record the acquisition time corresponding to each instantaneous temperature value and instantaneous water vapor concentration value according to the timestamp to obtain the original spatiotemporal dataset of temperature and the original spatiotemporal dataset of water vapor; S24. Based on the spatial coordinates of multiple grid nodes, the original spatiotemporal dataset of temperature, and the original spatiotemporal dataset of water vapor, construct the spatiotemporal matrix of temperature field and water vapor concentration field of silk surface temperature field, and integrate the temperature spatiotemporal matrix and water vapor spatiotemporal matrix to obtain continuously distributed spatiotemporal evolution data, wherein the spatiotemporal evolution data includes temperature spatiotemporal evolution data and water vapor spatiotemporal evolution data.

[0020] As described in steps S21-S24 above, when obtaining the division parameters, the grid spacing can be set to 1 / 3 of the maximum aperture of the orifice to ensure that each orifice and its surrounding area are covered by at least 3 grid nodes. The division parameters are obtained by converting the pixel resolution of the two-dimensional scan image of the sample. After constructing a preset spatial sampling grid, a dual detection component consisting of a miniature infrared temperature sensor and a fiber optic water vapor sensor is arranged at each grid node. The sensor placement position is determined by the spatial coordinates of the grid node to ensure seamless contact with the sample surface. The sampling frequency can be set to 5 times the rate of change of temperature and humidity in the test environment and dynamically adjusted based on real-time monitoring data of environmental parameters. The instantaneous temperature value and instantaneous water vapor concentration value of each grid node are collected synchronously through the dual detection component. After obtaining the original spatiotemporal datasets of temperature and water vapor, it is necessary to obtain the outlier judgment threshold (set according to the data mean ± 3 times the standard deviation) based on the numerical distribution in the original spatiotemporal datasets of temperature and water vapor, remove outlier data that exceed the threshold, and use linear interpolation based on the spatiotemporal correlation of adjacent nodes to complete the missing data. This invention generates partitioning parameters and constructs a preset spatial sampling grid by using the size parameters and the distribution range of the pores in the basic parameters. This achieves refined and structured spatial discretization of the silk surface, ensuring that the sampling points can effectively cover and capture the spatial heterogeneity of the temperature and humidity field directly caused by the pore structure. By extracting the allowable range of temperature and humidity fluctuations from the test conditions and intelligently back-deriving the required sampling frequency parameters, it ensures the time resolution for distortion-free or low-distortion sampling of the dynamic process. By accurately timestamping each collected instantaneous value and organizing them into raw temperature spatiotemporal datasets and raw water vapor spatiotemporal datasets, it enables any data point to be accurately traced back to its collected grid node and time. Organizing discrete sampling points according to the structure of space, time, and physical quantities provides an efficient and standardized data foundation for subsequent data processing and analysis. By reconstructing the raw datasets with spatial coordinates and timestamps into temperature spatiotemporal matrices and water vapor spatiotemporal matrices respectively, the matrix data can be reconstructed in space and time using interpolation and other methods to obtain continuously distributed temperature and water vapor concentration fields. Integrating the two spatiotemporal matrices forms a unified spatiotemporal evolution data containing temperature and water vapor concentration information. This ensures that the temperature and humidity data are fully aligned and correlated in time and space at every step of the subsequent analysis, providing an accurate data foundation for precise analysis of the interaction between the two.

[0021] In one embodiment, step S3, which involves obtaining the three-dimensional component information of the transient airflow velocity field inside the breathable pore structure of silk, includes: S31. Obtain the orifice distribution density and the equivalent orifice diameter, and determine the measurement section of the airflow velocity field based on the orifice distribution density and the equivalent orifice diameter; S32. Determine the maximum estimated velocity of the airflow based on the initial pressure gradient in the test conditions, and determine the tracer particles based on the maximum estimated velocity of the airflow; S33. According to the spatial position of the measurement section, laser emitters and high-speed cameras are symmetrically arranged on the upper and lower sides of the silk. The laser emitters illuminate the tracer particles and the high-speed cameras are activated to synchronously acquire particle motion sequence images. S34. Obtain the spatial coordinates of the particles at each moment based on the particle motion sequence image, and obtain the spatial displacement based on the spatial coordinates of the particles at adjacent moments. S35. Decompose each of the spatial displacements to obtain the instantaneous velocity components of the X-axis, Y-axis, and Z-axis, and integrate them to form the three-dimensional component information of the transient airflow velocity field.

[0022] As described in steps S31-S35 above, the measurement section is divided according to the principle of every 5 consecutive orifices covering one section, and is obtained by statistical analysis of the orifice coordinates of the sample micro-scanning image; hollow glass microspheres with a particle size of 1-5 micrometers are selected as tracer particles according to the maximum predicted velocity of the airflow, and the particle size is determined by the matching test between the airflow viscosity coefficient and the predicted velocity. The steps for obtaining the spatial coordinates of particles at each moment from particle motion sequence images are as follows: Based on the material characteristics of the tracer particles (high reflectivity of hollow glass microspheres), obtain the particle grayscale feature threshold (this can be determined by adding three times the standard deviation to the grayscale mean of a particle-free background image, ensuring accurate differentiation between particles and background); after grayscale enhancement and median filtering of the particle motion sequence images, an adaptive threshold segmentation algorithm can be used to extract particle regions that meet the grayscale feature threshold, obtaining the two-dimensional pixel coordinates of each particle; based on the installation parameters (spacing, pitch angle) of the laser emitter and high-speed camera, obtain the spatial calibration matrix (this can be obtained through calibration experiments using a calibration plate, converting the two-dimensional pixel coordinates into three-dimensional physical coordinates); for overlapping particle regions, morphological operations can be used to separate the particle contours and combine them with particle size. The parameters are used to filter valid particles and remove interference. Finally, the same particle in each frame of the image is associated according to the timestamp order. The consistency of the gray-scale distribution and the continuity of the spatial position of the particles are verified to ensure the accuracy of the matching of the spatial coordinates of the particles at each moment. By combining adaptive threshold segmentation with morphological processing, the interference caused by silk background texture and laser speckle can be effectively dealt with, and the tracer particles can be accurately separated. The noise resistance is strong. The two-dimensional pixel coordinates in the image are accurately converted into three-dimensional physical coordinates in the real world through the spatial calibration matrix, eliminating the errors caused by lens distortion and perspective. The particle cross-frame matching is performed by using the consistency of gray-scale distribution and the continuity of spatial position, which greatly improves the tracking accuracy in the case of dense particles or complex motion, and ensures the reliability and accuracy of the finally obtained particle coordinates and subsequent velocity information. The steps to decompose the spatial displacement to obtain the instantaneous velocity components along the X, Y, and Z axes are as follows: First, establish a three-dimensional orthogonal coordinate system adapted to the silk. This system is determined through physical dimension calibration of the sample, ensuring that the coordinate axes accurately correspond to the actual spatial dimensions of the airflow. The X-axis runs along the silk length, the Y-axis along the silk width, and the Z-axis along the silk thickness. The spatial displacement of the tracer particles is the change in their three-dimensional spatial position between adjacent moments. Essentially, it is the composite vector of the particle's displacement in the three orthogonal directions (X, Y, Z). According to the principle of vector orthogonal decomposition, the composite displacement can be decomposed into component displacements along the three coordinate axes. The physical definition of instantaneous velocity is the change in displacement per unit time. Since the sampling frequency of the high-speed camera is fixed, the time interval between adjacent moments (1 / sampling frequency) is a known constant. Therefore, the instantaneous velocity components in the three directions can be calculated by the ratio of the corresponding component displacement to the time interval. It can be calculated that, combined with the tracking design of tracer particles and airflow (hollow glass microspheres with a particle size of 1-5 micrometers, verified by airflow viscosity matching test, can completely follow the airflow), the three-dimensional velocity component of the particles is equivalent to the instantaneous velocity component of the airflow at that point in space. Thus, the three-dimensional information of the airflow velocity is indirectly obtained through particle displacement decomposition. By clearly defining a three-dimensional orthogonal coordinate system fixed to the silk sample, a unified and clear reference benchmark is provided for the description of all spatial vectors. By explaining the principle of conversion from displacement to velocity, the basic physical law basis of data processing is clarified. By explaining the tracking design of tracer particles (hollow glass microspheres with a particle size of 1-5 micrometers and verified by viscosity matching), the validity of the core premise that particle velocity is airflow velocity is demonstrated from the principle of fluid mechanics, eliminating potential doubts and making the entire conversion process from image to three-dimensional velocity field logically rigorous and well-founded. This invention, by introducing pore distribution density and equivalent pore size, can intelligently identify and locate the most complex and representative regions of airflow motion (such as pore density abrupt change regions and maximum / minimum pore size regions) as measurement sections. This ensures that the collected three-dimensional velocity information can most effectively reflect the true behavior of airflow passing through pore channels with structural features, avoiding invalid measurements in non-porous or low-permeability regions. It significantly improves the relevance and representativeness of subsequent collaborative analysis datasets, enabling accurate correlation between microscopic airflow information and macroscopic pore structure features. Pre-calculation of the maximum predicted airflow velocity based on the initial pressure gradient under test conditions provides a quantitative basis for the scientific selection of tracer particles. This ensures that the selected tracer particles have a Stokes number matching the predicted flow velocity, accurately following the low-speed, transient airflow motion within the silk pores, thus guaranteeing the physical authenticity of the subsequent inversion of airflow velocity from particle motion. Compared to traditional methods, this method overcomes measurement distortion caused by particle response lag and improves measurement accuracy. By acquiring the spatial displacement of each particle within an extremely short time interval, it directly measures the trajectory of particles carried by airflow micro-clusters at the microscale. Through statistical measurements based on a large number of discrete point displacements, it can reveal local transient phenomena such as vortices, stagnation, and acceleration that may exist in complex perforated channels. This provides direct observational data for understanding the microscopic mechanism of the air permeability process. By orthogonally decomposing the spatial displacement vector of each particle, the instantaneous velocity components of each spatial point in the three coordinate axes are obtained. Integrating these component information on a spatial grid forms a three-dimensional vector field of transient airflow velocity field. This provides an indispensable vector input for subsequent analysis of the synergistic relationship between airflow direction and humidity / temperature gradient direction, and is a decisive data element for constructing an air permeability-moisture permeability synergistic analysis model.

[0023] In one embodiment, step S5, which involves obtaining the numerical distribution statistical parameters, temporal evolution characteristics, and spatial distribution patterns of multiple local transient synergistic coefficients to generate the air permeability-moisture permeability synergistic efficiency spectrum of the silk breathable pore structure, includes: S51. Determine the core dimensions of the preset efficiency spectrum based on the test conditions of automatic verification, wherein the core dimensions include the time dimension, the space dimension, and the synergy strength dimension. S52. Map the multiple numerical distribution statistical parameters, temporal evolution characteristics, and spatial distribution patterns to the corresponding cooperative intensity dimension, time dimension, and spatial dimension in the same three-dimensional coordinate system to construct a three-dimensional basic spectrum. S53. Obtain the time dimension weight, the space dimension weight, and the collaboration strength dimension weight. S54. Based on the time dimension weight, spatial dimension weight, and synergy strength dimension weight, the numerical distribution statistical parameters, temporal evolution characteristics, and spatial distribution patterns of each spatial point in the same three-dimensional coordinate system in the three-dimensional basic spectrum are weighted, fused, and normalized to generate the air permeability-moisture permeability synergy efficiency spectrum.

[0024] As described in steps S51-S54 above, the steps for obtaining numerical distribution statistical parameters, temporal evolution characteristics, and spatial distribution patterns are as follows: Numerical distribution statistical parameters are obtained based on the local transient synergy coefficients of all spatiotemporal points. These parameters include the mean, standard deviation, peak value, and distribution interval. The numerical distribution statistical parameters can be obtained by statistical fitting analysis of multiple local transient synergy coefficient samples. The fitting model can be selected based on the degree of dispersion of the coefficient values. Temporal evolution characteristics are obtained by arranging the synergy coefficients of each spatiotemporal point in chronological order. These characteristics include the slope of the change trend, the fluctuation amplitude, and the stable duration. The slope of the change trend is calculated through linear regression. The fluctuation amplitude is the difference between the extreme values ​​of the coefficients within the same time period. The stable duration is calculated based on the duration during which the coefficient fluctuation is less than a preset threshold. Spatial distribution patterns are obtained by combining the node coordinates of a preset spatial sampling grid. The parameters of the spatial distribution patterns include the proportion of high-synergy regions, spatial clustering density, and the coefficient difference between porous and non-porous regions. The proportion of high-synergy regions is the ratio of the number of grid nodes with coefficients greater than the critical value corresponding to comfort performance to the total number of nodes. The critical value is obtained through synergy coefficient calibration of a large number of qualified samples. The core dimensions of the preset efficiency spectrum can be determined based on the evaluation focus of air permeability and moisture permeability. The mapping rules for constructing the three-dimensional basic spectrum are determined through correlation analysis of numerical distribution statistical parameters, temporal evolution characteristics, spatial distribution patterns, and corresponding dimensions. A three-dimensional coordinate system is set with the synergistic strength dimension as the X-axis, the time dimension as the Y-axis, and the spatial dimension as the Z-axis. The three-dimensional coordinate system is calibrated by the performance evaluation priority in the verification requirements to ensure that the physical meaning of each dimension and parameter is accurately corresponding. The numerical range of the numerical distribution statistical parameters is mapped to the X-axis coordinate values ​​through linear scaling. The scaling factor can be obtained by using the synergistic strength threshold of qualified samples. The values ​​are obtained by reverse calculation; the total test duration is used as the Y-axis range, and the time nodes corresponding to the time evolution characteristic parameters are mapped to Y-axis coordinates according to the timestamp order. The time nodes are set by the time segmentation results during parameter statistics; the Z-axis range is determined according to the coordinate range of the preset spatial sampling grid, and the spatial region corresponding to the parameter is mapped to Z-axis coordinates through spatial interpolation. The interpolation rules are set by the spatial correlation analysis of the grid nodes; during the mapping process, each parameter corresponds to a spatial point in the three-dimensional coordinate system, and the set of spatial points corresponding to all parameters constitutes the core data of the three-dimensional basic spectrum, ensuring that the characteristics of the three types of parameters are fully presented in the same spectrum; The weight of the time dimension is set according to the test stability requirements, the weight of the spatial dimension is adjusted according to the priority of densely distributed areas of the orifice, and the weight of the synergy strength dimension is determined with reference to the weight of the comfort performance. The weight coefficients can be calculated by the analytic hierarchy process. The steps for generating the air permeability-moisture permeability synergistic efficiency spectrum are as follows: extract the original values ​​of the X-axis, Y-axis, and Z-axis parameters of each spatial point in the three-dimensional basic spectrum; multiply the original values ​​of the three types of parameters by the corresponding dimension weight coefficients to obtain the weighted contribution values ​​of each dimension; sum the three weighted contribution values ​​of each spatial point to obtain the comprehensive synergistic score of that spatial point; normalize all comprehensive synergistic scores by linear scaling to eliminate dimensional differences, and finally form an air permeability-moisture permeability synergistic efficiency spectrum of a unified scale. This invention provides a clear index framework for subsequent analysis by defining the core dimensions (time, space, and synergistic strength) of the air permeability-moisture permeability efficiency spectrum. It can deeply explore the performance of the pore structure of silk, not only examining air permeability but also effectively evaluating the synergistic relationship between moisture permeability and the two. This ensures the multidimensionality and systematic nature of the data. By mapping multiple numerical distribution statistical parameters, temporal evolution characteristics, and spatial distribution patterns to the same three-dimensional coordinate system, it can achieve intuitive comparison and correlation of parameters in different dimensions. This allows for the rapid identification of key factors affecting the performance of the air permeability pore structure of silk, especially in the interaction between air permeability and moisture permeability. By weighted fusion and normalization of the parameters in the three-dimensional basic spectrum, a comprehensive air permeability-moisture permeability synergistic efficiency spectrum can be generated, reflecting the comprehensive performance of materials under different conditions.

[0025] In one embodiment, step S6, which compares the air permeability-moisture permeability synergistic efficiency spectrum with a preset comfort performance evaluation standard to obtain the verification result of the air permeability-moisture permeability synergistic performance of the perforated structure, includes: S61. Extract core comparison indicators from the air permeability-moisture permeability synergistic efficiency spectrum, wherein the core comparison indicators include the spectrum mean, time fluctuation coefficient and spatial variation coefficient; S62. The mean value of the spectrum, the time fluctuation coefficient, and the spatial variation coefficient are compared one by one with the corresponding qualified intervals in the preset comfort performance evaluation standard, and the mean value deviation rate, time fluctuation deviation rate, and spatial variation deviation rate of the mean value of the spectrum, the time fluctuation coefficient, and the spatial variation coefficient are obtained from the median value of the corresponding qualified interval. S63. The comprehensive deviation rate is obtained by weighting the mean deviation rate, time fluctuation deviation rate and spatial variation deviation rate of the spectrum, and it is determined whether the comprehensive deviation rate is greater than the qualified judgment threshold. If the overall deviation rate is greater than the pass / fail threshold, the air permeability-moisture permeability synergistic performance of the pore structure is deemed unqualified. If the overall deviation rate is not greater than the pass / fail threshold, the air permeability-moisture permeability synergistic performance of the pore structure is deemed to be qualified, and the verification result is obtained.

[0026] As described in steps S61-S63 above, the spectral mean deviation rate is obtained by the ratio of the difference between the spectral mean and the median of the corresponding qualified interval to the median of the corresponding qualified interval. The time fluctuation deviation rate and the spatial variation deviation rate are obtained in the same way as the spectral mean deviation rate. This invention provides a quantitative basis for performance evaluation by comparing the extracted core comparison indicators with the qualified intervals in the preset comfort performance evaluation standards one by one. This allows the breathability and moisture permeability of materials to be directly compared with industry standards, transforming them into operable evaluation results. By obtaining the deviation rate of the three indicators, the relative performance of each performance indicator can be clearly understood. This process significantly improves the transparency and reliability of performance evaluation. By weighting the deviation rate of the spectral mean, the deviation rate of time fluctuation, and the deviation rate of spatial variation to obtain the comprehensive deviation rate, the breathability and moisture permeability of materials can be evaluated more comprehensively. By setting the qualified judgment threshold, the evaluation results have quantitative standards and repeatability.

[0027] like Figure 2 As shown, this application also provides an automatic verification system for the breathable perforated structure of silk, comprising: The setting module is used to obtain the basic parameters of the silk and the environmental parameters of the verification environment, and to set the test conditions for automatic verification based on the basic parameters and environmental parameters. The first acquisition module is used to acquire the spatiotemporal evolution data of the surface temperature field and water vapor concentration field of the silk in a preset spatial sampling grid under the test conditions. A construction module is used to obtain the three-dimensional component information of the transient airflow velocity field inside the breathable pore structure of silk, and to construct a breathable-moisture-permeable collaborative analysis dataset based on the three-dimensional component information and spatiotemporal evolution data. The second acquisition module is used to extract the temperature gradient, water vapor concentration gradient and three-dimensional airflow velocity component corresponding to each spatiotemporal point in the preset spatial sampling grid according to the air permeability-moisture permeability synergistic analysis dataset to obtain the corresponding local transient synergistic coefficient. The third acquisition module is used to acquire the numerical distribution statistical parameters, temporal evolution characteristics and spatial distribution laws of multiple local transient synergistic coefficients to generate the air permeability-moisture permeability synergistic efficiency spectrum of the air permeable pore structure of silk. The comparison module is used to compare the synergistic efficiency spectrum with the preset comfort performance evaluation standard to obtain the verification result of the air permeability-moisture permeability synergistic performance of the pore structure, and complete the automatic verification of the air permeability pore structure of silk.

[0028] In one embodiment, the setting module includes: The first acquisition unit is used to acquire the silk thickness, pore size and pore distribution density in the basic parameters to obtain the pore size adaptation coefficient and density distribution uniformity. The determining unit is used to acquire the ambient temperature, ambient humidity and atmospheric pressure in the environmental parameters to obtain the allowable range of temperature and humidity fluctuations and the atmospheric pressure reference value, and to determine the initial pressure gradient of the test airflow based on the aperture adaptation coefficient and the atmospheric pressure reference value. The second acquisition unit is used to obtain the pressure compensation coefficient based on the roughness of the orifice wall in the basic parameters and the atmospheric pressure change rate in the environmental parameters, and to obtain the stable test pressure difference based on the pressure compensation coefficient and the initial pressure difference gradient. An integration unit is used to determine the minimum threshold for test duration based on the density distribution uniformity and the allowable range of temperature and humidity fluctuations, and to integrate the minimum threshold, stable test pressure difference, and allowable range of temperature and humidity fluctuations to obtain test conditions for automatic calibration that are adapted to the breathable pore structure of silk.

[0029] It should be noted that each module and unit in the automatic verification system for the breathable pore structure of silk corresponds one-to-one with the steps in the automatic verification method for the breathable pore structure of silk.

[0030] like Figure 3 As shown, this application also provides a computer device, which can be a server, and its internal structure can be as follows: Figure 3 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores all data required for the automatic verification method of the silk breathable pore structure. The network interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements the automatic verification method of the silk breathable pore structure.

[0031] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer equipment on which the present application is applied.

[0032] An embodiment of this application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements any of the above-described automatic verification methods for the breathable pore structure of silk.

[0033] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in this application and in the embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual-speed SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0034] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0035] The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. An automatic verification method for the breathable perforated structure of silk, characterized in that, include: Obtain the basic parameters of the silk and the environmental parameters of the verification environment, and set the test conditions for automatic verification based on the basic parameters and environmental parameters; Acquire the spatiotemporal evolution data of the surface temperature field and water vapor concentration field of the silk in a preset spatial sampling grid under the test conditions; The three-dimensional component information of the transient airflow velocity field inside the breathable pore structure of silk is obtained, and a breathable-moisture-permeable synergistic analysis dataset is constructed based on the three-dimensional component information and spatiotemporal evolution data. Based on the air permeability-moisture permeability synergistic analysis dataset, extract the temperature gradient, water vapor concentration gradient, and three-dimensional airflow velocity component corresponding to each spatiotemporal point in the preset spatial sampling grid to obtain the corresponding local transient synergistic coefficient; The numerical distribution statistical parameters, temporal evolution characteristics, and spatial distribution laws of multiple local transient synergistic coefficients are obtained to generate the air permeability-moisture permeability synergistic efficiency spectrum of the silk breathable pore structure. The air permeability-moisture permeability synergistic efficiency spectrum is compared with the preset comfort performance evaluation standard to obtain the verification result of the air permeability-moisture permeability synergistic performance of the pore structure, thus completing the automatic verification of the air permeability pore structure of silk.

2. The automatic verification method for the breathable perforated structure of silk according to claim 1, characterized in that, The step of setting the test conditions for automatic verification based on the basic parameters and environmental parameters includes: The silk thickness, pore size, and pore distribution density in the basic parameters are obtained to obtain the pore size fit coefficient and density distribution uniformity. The ambient temperature, ambient humidity, and atmospheric pressure in the environmental parameters are obtained to obtain the allowable range of temperature and humidity fluctuations and the atmospheric pressure reference value. The initial pressure gradient of the test airflow is determined according to the aperture adaptation coefficient and the atmospheric pressure reference value. The pressure compensation coefficient is obtained based on the roughness of the orifice wall in the basic parameters and the rate of change of atmospheric pressure in the environmental parameters, and the stable test pressure difference is obtained based on the pressure compensation coefficient and the initial pressure difference gradient. The minimum threshold for test duration is determined based on the density distribution uniformity and the allowable range of temperature and humidity fluctuations. The minimum threshold, stable test pressure difference, and allowable range of temperature and humidity fluctuations are then integrated to obtain test conditions for automatic calibration that are adapted to the breathable pore structure of silk.

3. The automatic verification method for the breathable perforated structure of silk according to claim 1, characterized in that, The step of acquiring the spatiotemporal evolution data of the silk surface temperature field and water vapor concentration field in a preset spatial sampling grid under the test conditions includes: The division parameters are obtained based on the size parameters and orifice distribution range in the basic parameters, and a preset spatial sampling grid is constructed based on the division parameters; The sampling frequency parameter is obtained according to the allowable range of temperature and humidity fluctuations in the test conditions, and the instantaneous temperature value and instantaneous water vapor concentration value of each grid node in the preset spatial sampling grid are synchronously and in real time collected according to the sampling frequency parameter. Record the acquisition time corresponding to each instantaneous temperature value and instantaneous water vapor concentration value according to the timestamp to obtain the original spatiotemporal dataset of temperature and the original spatiotemporal dataset of water vapor; Based on the spatial coordinates of multiple grid nodes, the original spatiotemporal dataset of temperature, and the original spatiotemporal dataset of water vapor, a temperature spatiotemporal matrix and a water vapor spatiotemporal matrix of water vapor concentration field are constructed for the silk surface temperature field, respectively. The temperature spatiotemporal matrix and the water vapor spatiotemporal matrix are then integrated to obtain continuously distributed spatiotemporal evolution data, wherein the spatiotemporal evolution data includes temperature spatiotemporal evolution data and water vapor spatiotemporal evolution data.

4. The automatic verification method for the breathable perforated structure of silk according to claim 1, characterized in that, The step of obtaining the three-dimensional component information of the transient airflow velocity field inside the breathable pore structure of silk includes: Obtain the orifice distribution density and the equivalent orifice diameter, and determine the measurement section of the airflow velocity field based on the orifice distribution density and the equivalent orifice diameter; The maximum predicted airflow velocity is determined based on the initial pressure gradient in the test conditions, and the tracer particles are determined based on the maximum predicted airflow velocity. Laser emitters and high-speed cameras are symmetrically arranged on the upper and lower sides of the silk according to the spatial position of the measurement section. The laser emitters illuminate the tracer particles and the high-speed cameras are activated to synchronously acquire the particle motion sequence images. The spatial coordinates of the particles at each moment are obtained from the particle motion sequence image, and the spatial displacement is obtained from the spatial coordinates of the particles at adjacent moments. Each of the spatial displacements is decomposed to obtain the instantaneous velocity components of the X-axis, Y-axis, and Z-axis, which are then integrated to form the three-dimensional component information of the transient airflow velocity field.

5. The automatic verification method for the breathable perforated structure of silk according to claim 1, characterized in that, The step of obtaining the numerical distribution statistical parameters, temporal evolution characteristics, and spatial distribution patterns of multiple local transient synergistic coefficients to generate the air permeability-moisture permeability synergistic efficiency spectrum of the silk breathable pore structure includes: The core dimensions of the preset efficiency spectrum are determined based on the test conditions of automatic verification, wherein the core dimensions include the time dimension, the space dimension, and the synergy strength dimension. Multiple numerical distribution statistical parameters, temporal evolution characteristics, and spatial distribution patterns are mapped to the corresponding cooperative intensity dimension, temporal dimension, and spatial dimension in the same three-dimensional coordinate system to construct a three-dimensional basic spectrum. Obtain the time dimension weight, the space dimension weight, and the collaboration strength dimension weight; Based on the weights of the time dimension, spatial dimension, and synergy strength dimension, the numerical distribution statistical parameters, temporal evolution characteristics, and spatial distribution patterns of each spatial point in the same three-dimensional coordinate system in the three-dimensional basic spectrum are weighted, fused, and normalized to generate an air permeability-moisture permeability synergy efficiency spectrum.

6. The automatic verification method for the breathable perforated structure of silk according to claim 1, characterized in that, The step of comparing the air permeability-moisture permeability synergistic efficiency spectrum with a preset comfort performance evaluation standard to obtain the verification result of the air permeability-moisture permeability synergistic performance of the perforated structure includes: Core comparison indicators are extracted from the air permeability-moisture permeability synergistic efficiency spectrum, wherein the core comparison indicators include the spectrum mean, time fluctuation coefficient and spatial variation coefficient; The mean value of the spectrum, the time fluctuation coefficient, and the spatial variation coefficient are compared one by one with the corresponding qualified intervals in the preset comfort performance evaluation standard, and the deviation rate of the mean value of the spectrum, the time fluctuation coefficient, and the spatial variation coefficient from the median of the corresponding qualified interval are obtained. The comprehensive deviation rate is obtained by weighting the mean deviation rate, time fluctuation deviation rate and spatial variation deviation rate of the spectrum, and it is then determined whether the comprehensive deviation rate is greater than the pass / fail threshold. If the overall deviation rate is greater than the pass / fail threshold, the air permeability-moisture permeability synergistic performance of the pore structure is deemed unqualified. If the overall deviation rate is not greater than the pass / fail threshold, the air permeability-moisture permeability synergistic performance of the pore structure is deemed to be qualified, and the verification result is obtained.

7. An automatic verification system for the breathable perforated structure of silk, characterized in that, include: The setting module is used to obtain the basic parameters of the silk and the environmental parameters of the verification environment, and to set the test conditions for automatic verification based on the basic parameters and environmental parameters. The first acquisition module is used to acquire the spatiotemporal evolution data of the surface temperature field and water vapor concentration field of the silk in a preset spatial sampling grid under the test conditions. A construction module is used to obtain the three-dimensional component information of the transient airflow velocity field inside the breathable pore structure of silk, and to construct a breathable-moisture-permeable collaborative analysis dataset based on the three-dimensional component information and spatiotemporal evolution data. The second acquisition module is used to extract the temperature gradient, water vapor concentration gradient and three-dimensional airflow velocity component corresponding to each spatiotemporal point in the preset spatial sampling grid according to the air permeability-moisture permeability synergistic analysis dataset to obtain the corresponding local transient synergistic coefficient. The third acquisition module is used to acquire the numerical distribution statistical parameters, temporal evolution characteristics and spatial distribution laws of multiple local transient synergistic coefficients to generate the air permeability-moisture permeability synergistic efficiency spectrum of the air permeable pore structure of silk. The comparison module is used to compare the synergistic efficiency spectrum with the preset comfort performance evaluation standard to obtain the verification result of the air permeability-moisture permeability synergistic performance of the pore structure, and complete the automatic verification of the air permeability pore structure of silk.

8. The automatic verification system for the breathable perforated structure of silk according to claim 7, characterized in that, The setting module includes: The first acquisition unit is used to acquire the silk thickness, pore size and pore distribution density in the basic parameters to obtain the pore size adaptation coefficient and density distribution uniformity. The determining unit is used to acquire the ambient temperature, ambient humidity and atmospheric pressure in the environmental parameters to obtain the allowable range of temperature and humidity fluctuations and the atmospheric pressure reference value, and to determine the initial pressure gradient of the test airflow based on the aperture adaptation coefficient and the atmospheric pressure reference value. The second acquisition unit is used to obtain the pressure compensation coefficient based on the roughness of the orifice wall in the basic parameters and the atmospheric pressure change rate in the environmental parameters, and to obtain the stable test pressure difference based on the pressure compensation coefficient and the initial pressure difference gradient. An integration unit is used to determine the minimum threshold for test duration based on the density distribution uniformity and the allowable range of temperature and humidity fluctuations, and to integrate the minimum threshold, stable test pressure difference, and allowable range of temperature and humidity fluctuations to obtain test conditions for automatic calibration that are adapted to the breathable pore structure of silk.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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