Sanitary napkin comfort optimization system based on AI intelligent analysis

Abstract

The invention discloses a sanitary napkin comfort optimization system based on AI intelligent analysis, and relates to the technical field of quality detection, the system is used for setting a plurality of groups of detection points on a sanitary napkin area, and recording first air permeability data of each detection point; the air permeability coefficient # imgabs0 # of each group of sanitary napkins is constructed; the air permeability coefficient # imgabs 1 # of each group of sanitary towels is classified through a classifier; the sanitary napkin is subjected to cyclic alternation absorbency detection, secondary air permeability detection and fitness test at the multiple sets of detection points; and dynamically analyzing and acquiring the absorptivity coefficient # imgabs2 #, the wet air permeability coefficient # imgabs3 # and the fitness coefficient # imgabs4 # of each group of sanitary napkins, evaluating the absorptivity coefficient # imgabs2 #, the wet air permeability coefficient # imgabs3 # and the fitness coefficient # imgabs4 # so as to judge whether each performance is qualified or not, inputting a corresponding classification result, and generating a corresponding strategy according to the corresponding classification result.

Description

Technical Field

[0001] The present invention relates to the technical field of quality inspection, and in particular to a sanitary napkin comfort optimization system based on AI intelligent analysis. Background Art

[0002] In the research and development process of sanitary napkin products, breathability, absorbency and fit are the key factors that determine the comfort of use. Traditional sanitary napkin testing methods mainly rely on laboratory manual testing and subjective evaluation, such as breathability tests, liquid absorption tests and manual wearing tests. However, these traditional methods have many limitations and cannot meet the needs of modern consumers for highly comfortable, personalized and intelligent products.

[0003] Traditional breathability testing methods mainly use static experiments, such as using a permeability meter to measure the rate at which air flows through sanitary napkin materials. However, static testing cannot fully simulate the air flow in the actual wearing environment, especially in high humidity or after long-term wear, the breathability may change significantly. In addition, traditional breathability testing is often limited to single-point measurement, and it is difficult to fully obtain the breathability data of various areas of the sanitary napkin, resulting in a lack of globality in the test results and failure to truly reflect the actual experience of users.

[0004] The secondary rewet phenomenon is often not fully considered in traditional absorbency testing methods, resulting in deviations in dryness tests of sanitary napkins after long-term use. In actual use by users, the fit of sanitary napkins will be affected by factors such as body skin friction and range of motion, and traditional methods are difficult to provide comprehensive and quantitative data. In addition, existing fit tests fail to fully consider the deformation of sanitary napkins during long-term use, such as curling, displacement, wrinkles, etc., which will affect the comfort of use. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a sanitary napkin comfort optimization system based on AI intelligent analysis to solve the problems mentioned in the background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a sanitary napkin comfort optimization system based on AI intelligent analysis, comprising: A static test module, used to set a plurality of groups of detection points on the sanitary napkin area, perform air permeability detection on the sanitary napkin at the plurality of detection points, record first air permeability data of each detection point, and establish a first air permeability data set; The static analysis module is used to build a sanitary napkin AI analysis model using a convolutional neural network, and input the first breathable data set into the sanitary napkin AI analysis model to analyze the air permeability coefficient of each group of sanitary napkins in static state. ; And use the classifier to calculate the air permeability coefficient of each group of sanitary napkins Perform classification and output the first classification result; A dynamic test module is used to perform cyclic alternating absorbency test, secondary air permeability test and fit test on sanitary napkins at several groups of test points, and obtain absorbency data set, dynamic air permeability data set and friction data set respectively; The dynamic analysis module is used to use the sanitary napkin AI analysis model to train the sanitary napkin AI analysis model based on the absorbency data set, dynamic breathability data set, and friction data set, and then deeply analyze and obtain the absorbency coefficient of each group of sanitary napkins. , wet air permeability coefficient and fit coefficient And evaluate to determine whether each performance is qualified, input the corresponding classification results, and generate corresponding strategies based on the corresponding classification results.

[0007] Preferably, the static test module includes a first test unit and a first recording unit; The first testing unit is used to simulate the actual use environment by using the wind tunnel test to test the air permeability of each group of sanitary napkins. The specific method is as follows: S11, select each group of sanitary napkin samples, and take the sanitary napkins with the same specifications as one group, and cut each group of sanitary napkins into N test areas so that each sample has the same size; S12, dividing a plurality of groups of detection points on the surface of each group of sanitary napkins, and marking the plurality of groups of detection points, wherein the plurality of groups of detection points include: a central area, an edge area, and an absorption core area; S13. Before opening the wind tunnel, check and calibrate the gas flow meter and partial pressure sensor, and set the first environmental parameters: the temperature is maintained at 25°C and the humidity is maintained at 50%; S14, fix the sanitary napkin sample in the wind tunnel test area using a sanitary napkin clamp so that it completely covers the test port, and adjust the wind speed to a preset test value, the test value includes a first test interval of 2m / s-4m / s, a second test interval of 5m / s-6m / s, and a third test interval of 7m / s-10m / s; S15, start the wind tunnel, so that the wind flow acts vertically on the surface of the sanitary napkin and passes through the first recording unit to record the initial wind speed at the xth detection point and wind speed through sanitary napkin , and calculate the initial permeability coefficient of the xth detection point by the following formula : S16, repeatedly testing the air permeability under different wind speed conditions, using a first test interval of 2m / s-4m / s, a second test interval of 5m / s-6m / s, and a third test interval of 7m / s-10m / s to establish a first air permeability data set; The first air permeability data set includes: air permeability data at different wind speeds, specifically: wind pressure difference at the xth detection point and initial air permeability ; S17, and drawing a permeability distribution heat map based on the first permeability data set.

[0008] Preferably, the static analysis module includes a model training unit and a static quality assessment unit; The model training unit is used to use the convolutional neural network to construct an initial model of the convolutional neural network, and train and test the initial model of the convolutional neural network with the first permeability data, and use the trained initial model of the convolutional neural network as the sanitary napkin AI analysis model, and use the intermediate layer output of the sanitary napkin AI analysis model as a feature vector to identify the partial pressure difference characteristics in the first permeability data, and train and test the sanitary napkin AI analysis model through the obtained information characteristics, and use the trained sanitary napkin AI analysis model as data to run prediction to construct and obtain the air permeability coefficient of each group of sanitary napkins. : Air permeability coefficient of each set of sanitary napkins The specific way to obtain it is: S21. Extract the initial permeability coefficient of the xth detection point , and conduct a continuous 60-minute test, recording the partial pressure difference every 5 minutes: The air permeability attenuation coefficient of each group of sanitary napkins is calculated by the following formula: : In the formula, It represents the wind pressure difference at the xth test point measured after 60 minutes; n represents the total number of test points of each group of sanitary napkins; S22, adjusting the temperature and humidity of the wind tunnel for testing, setting the second environmental parameters of high temperature and high humidity to: temperature 40°C and humidity 80%, and setting the third environmental parameters of low temperature and low humidity to: temperature 10°C and humidity 20%; The temperature, humidity and air permeability index of each set of sanitary napkins is calculated using the following formula: : In the formula, It represents the wind pressure difference of the xth test point under the second environmental parameter of high temperature and high humidity. represents the wind pressure difference of the third environmental parameter of low temperature and low humidity at the xth detection point; n represents the total number of detection points of each group of sanitary napkins; S23, extracting the wind pressure difference at the xth detection point in each group of sanitary napkins , the air permeability uniformity index of each group of sanitary napkins is calculated by the following formula : in, represents the wind pressure difference at the xth detection point, represents the standard deviation of the wind pressure difference at the xth detection point, It represents the average value of wind pressure difference of several groups of test points; n represents the total number of test points of each group of sanitary napkins; S24, combining the air permeability attenuation coefficient of each group of sanitary napkins obtained by calculation in S21-S23 , Temperature, humidity and air permeability index and air permeability uniformity index , after dimensionless processing, the air permeability coefficient of each group of sanitary napkins is calculated by the following formula : In the formula, , and Denote the air permeability attenuation coefficient , Temperature, humidity and air permeability index and air permeability uniformity index The weight coefficient of , and the weight sum is 1; It represents the inverse term, which indicates the effect of air permeability decay over time. The more stable, the better the air permeability. It represents a correction term, which is used to reflect the impact of temperature and humidity changes on air permeability. The more stable the air permeability is, the less it is affected by temperature and humidity changes, and the better it is.

[0009] Preferably, the static quality assessment unit is used to preset a permeability threshold value X and calculate the permeability coefficient of each group of sanitary napkins. The air permeability threshold X is compared to determine whether the air permeability of the group of sanitary napkins is qualified under the static test. The static test refers to measuring and classifying the air permeability of the sanitary napkins under the fixed environmental conditions of the first environmental parameter, the second environmental parameter and the third environmental parameter to obtain the first classification result, including: If the air permeability coefficient of each set of sanitary napkins ≥ breathability threshold value X, indicating that the breathability of the sanitary napkins in this group is qualified, and the first qualified classification label is generated; If the air permeability coefficient of each set of sanitary napkins < breathability threshold value X, indicating that the breathability of the sanitary napkins in this group is unqualified, triggering the first warning instruction.

[0010] Preferably, the dynamic test module includes an immersion test unit, an alternating test unit and a comfort test unit; The immersion test unit is used to perform multiple liquid immersion tests at the detection points of each group of sanitary napkin samples, record the absorbency data of each detection point, and establish a first absorbency data set; and after the absorbency test, the alternating test unit is used to perform a secondary air permeability test on the detection points of each group of sanitary napkin samples, record the dynamic air permeability data of each detection point, and establish a dynamic air permeability data set; after the secondary air permeability test, the comfort test unit is used to perform a fit test on the detection points of each group of sanitary napkin samples, use a pressure sensor to simulate the contact pressure between the sanitary napkin and the skin, simulate different body positions, record the pressure change data under different test conditions and the friction data of the contact point, and establish a friction data set; Multiple liquid immersion tests include: Select each group of sanitary napkin samples, prepare standard test liquid, set the liquid temperature to 37°C, simulate the composition of human excrement, use a titration device, and perform multiple immersion tests at each test point according to the preset liquid volume, including 1ml, 3ml and 5ml. Record the time required for complete absorption of the liquid, and use an extrusion device to measure the residual humidity after each liquid penetration and the volume of liquid that seeps back under a certain pressure; Perform multiple immersion tests, accumulate absorption data of different liquid volumes and different time intervals, and establish a first absorbency data set; Secondary air permeability tests include: After completing multiple liquid immersion tests, immediately conduct a secondary air permeability test on each group of sanitary napkin samples, conduct an inspection before opening the wind tunnel, calibrate the gas flow meter and partial pressure sensor, and set the fourth environmental parameters: the temperature is maintained at 37°C and the humidity is maintained at 60% to simulate a wet environment; the sanitary napkin samples are fixed in the wind tunnel test area using a sanitary napkin clamp so that they completely cover the test port, and the wind speed is adjusted to the preset test value, which includes the first test interval of 2m / s-4m / s, the second test interval of 5m / s-6m / s and the third test interval of 7m / s-10m / s; collect dynamic air permeability data after multiple liquid immersion tests, repeat the dynamic air permeability test under different wind speed conditions, and establish a dynamic air permeability data set; Fit testing includes: After completing the dynamic air permeability test, each group of sanitary napkin samples is tested for fit. The sanitary napkin samples are fixed on the human body simulation device to fit the simulated skin area, and the contact pressure is measured in real time using a high-precision pressure sensor. Different body positions are simulated, including standing, walking, sitting and lying. Different pressures are applied in each position, and the pressure distribution data of the contact area is recorded. The friction coefficient under different test conditions is measured by a friction sensor, the friction changes at the contact points are recorded, and the displacement, curling and wrinkling of the sanitary napkins in different body positions are analyzed, and a friction data set is established.

[0011] Preferably, the first absorbency data set includes: the liquid absorption saturation time of each detection point , Maximum absorption and re-infiltration ; The dynamic permeability data set includes: the residual permeability volume in the wet state at each detection point And the partial pressure difference of each detection point in the wet state ; The friction data set includes: displacement S, curling rate E and wrinkle area W of each detection point.

[0012] Preferably, the dynamic analysis module includes an absorption analysis unit, an alternating air permeability analysis unit and a comfort analysis unit; The absorption analysis unit is used to use the sanitary napkin AI analysis model to divide the absorbency data set into 80% training set, 10% test set and 10% validation set. After training and validating the sanitary napkin AI analysis model, the absorbency coefficient of each group of sanitary napkins is calculated using the following formula: : In the formula, represents the maximum absorption at the xth detection point, represents the absorption saturation time of the xth detection point, represents the back-infiltration amount at the xth detection point; and represents the weight coefficient; The alternating air permeability analysis unit is used to use the sanitary napkin AI analysis model to divide the dynamic air permeability data set into 80% training set, 10% test set and 10% validation set. After training and validating the sanitary napkin AI analysis model, the wet air permeability coefficient of each group of sanitary napkins is calculated using the following formula: : In the formula, represents the maximum absorption at the xth detection point, represents the residual permeability volume of the xth test point in the wet state, It represents the partial pressure difference of the xth detection point in the wet state; and represents the weight coefficient; The comfort analysis unit is used to use the sanitary napkin AI analysis model to divide the friction data set into 80% training set, 10% test set and 10% validation set. After training and validating the sanitary napkin AI analysis model, the fit coefficient of each set of sanitary napkins is calculated using the following formula: : In the formula, represents the displacement of the xth detection point, represents the curling rate of the xth detection point, represents the wrinkle area at the xth detection point; represents the friction coefficient of the xth detection point, The value of is set based on experimental data. , , and Represents the weight coefficient.

[0013] Preferably, the dynamic analysis module further includes a first evaluation unit, a second evaluation unit and a third evaluation unit; The first evaluation unit is used to preset a first absorption threshold value Y1 and calculate the absorption coefficient of each group of sanitary napkins. Compare with the first absorption threshold value Y1 to determine whether the absorbency of the sanitary napkin is qualified, and generate a second classification result, including: If the absorbency coefficient of each set of sanitary napkins ≥ the first absorption threshold Y1, indicating that the absorbency of the group of sanitary napkins is qualified, and a second qualified classification label is generated; If the absorbency coefficient of each set of sanitary napkins < the first absorption threshold value Y1, indicating that the absorbency of the group of sanitary napkins is unqualified, triggering the second warning instruction; The second evaluation unit is used to preset a second air permeability threshold value Y2 and calculate the wet air permeability coefficient of each group of sanitary napkins. The result is compared with the second air permeability threshold value Y2 to determine whether the air permeability of the sanitary napkin during the dynamic liquid immersion process is qualified, and a third classification result is generated, including: If the wet air permeability coefficient of each group of sanitary napkins is ≥ the second air permeability threshold value Y2, indicating that the air permeability of the sanitary napkins in the dynamic liquid immersion process is qualified, and a third qualified classification label is generated; If the wet air permeability coefficient of each group of sanitary napkins is < the second air permeability threshold value Y2, indicating that the air permeability of the sanitary napkins in the dynamic liquid immersion process is unqualified, triggering the third warning instruction; The third evaluation unit is used to preset a third comfort threshold Y3 and calculate the fit coefficient of each set of sanitary napkins. The third comfort threshold Y3 is compared to determine whether the comfort level of the sanitary napkin during wearing is qualified, and a fourth classification result is generated, including: If the fit coefficient of each set of sanitary napkins ≥ the third comfort threshold Y3, indicating that the wearing comfort of the group of sanitary napkins is qualified, and the third qualified classification label is generated; If the fit coefficient of each set of sanitary napkins <The third comfort threshold Y3, indicating that the wearing comfort of the group of sanitary napkins is unqualified, triggering the fourth warning instruction.

[0014] Preferably, the dynamic analysis module further includes a first strategy unit and a second strategy unit; The first strategy unit is used to generate a first strategy after receiving the first warning instruction in the first classification result, including: marking unqualified test points, increasing the porosity of the absorbent core by 5%-15%, increasing the air layer fiber content by 5%-15%, increasing the central zone air permeability distribution area by 10%-12%, or adjusting the air permeable membrane opening rate by 5%-8%.

[0015] Preferably, the second strategy unit is used to generate a second strategy after receiving the second warning instruction in the second classification result, including: increasing the current absorption core proportion to 3%-5%, thickening the current guide layer by 0.2mm-0.3mm, and increasing the pore density of the bottom anti-leakage film by 20-30 / cm²; After receiving the third warning instruction in the third classification result, a third strategy is generated, including: increasing the air permeability of the current original film by 15%-20%, optimizing the diameter of the surface micropores by 0.2mm, and increasing the original embossing depth to 0.4mm; After receiving the fourth warning instruction in the fourth classification result, a fourth strategy is generated, including: increasing the width value of the side wing size by 10%-15%, reducing the wing sticking angle by 10%-12% and increasing the viscosity of the original tape by 15%-20%.

[0016] The present invention provides a sanitary napkin comfort optimization system based on AI intelligent analysis. It has the following beneficial effects: (1) Traditional breathability testing methods usually rely on static experiments and single-point measurements, which makes it difficult to truly simulate the breathability performance of sanitary napkins under high humidity or long-term use. The dynamic breathability test based on the wind tunnel test simulates the variability of air flow during actual wearing and can comprehensively measure the breathability of different areas. Through the precise measurement of the gas flow meter, the breathability data of each test point is obtained, and the data is optimized and processed through the AI ​​analysis model to output a practical permeability coefficient. This not only avoids the limitations of traditional methods, but also can evaluate the breathability performance of sanitary napkins under different environmental conditions.

[0017] (2) Traditional absorbency testing methods often ignore the secondary rewet phenomenon that may occur after long-term use of sanitary napkins, which may lead to inaccurate dryness tests and affect user comfort. This system comprehensively evaluates the performance of sanitary napkins in a wet state through dynamic absorbency tests and secondary air permeability tests. The combination of wet air permeability and absorbency ensures the absorption performance and comfort of sanitary napkins in actual use. Through AI analysis, the system can comprehensively evaluate the dynamic absorption performance of sanitary napkins in use and determine whether they meet the user's high standards for absorbency.

[0018] (3) Traditional fit testing methods mostly rely on manual wearing tests and lack objective, quantitative data. By introducing friction data sets and quantitative evaluation of the fit coefficient, the system can effectively evaluate the changes in comfort of sanitary napkins in different body positions. The recording and analysis of the friction coefficient helps identify changes in friction during long-term use of sanitary napkins, and further reflects the fit problems of sanitary napkins, such as displacement, curling and wrinkling. Using AI analysis models, the fit coefficient can be automatically calculated, and a more accurate comfort analysis can be made based on a large amount of test data, eliminating the subjective bias in traditional tests.

[0019] (4) Through the training of AI analysis models, the system can conduct in-depth analysis of data in multiple dimensions such as breathability, absorbency and fit, and formulate personalized comfort optimization strategies for each sanitary napkin. Based on the test results, the system can generate corresponding adjustment suggestions, such as adjusting the breathability of the material, optimizing the absorption design, improving the fit, etc., to meet the needs of different consumers. In particular, for the needs in specific environments such as high humidity, high temperature and high exercise intensity, the system can adjust the design of the sanitary napkin in real time to ensure a balance between comfort and performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 The present invention is a flowchart of a sanitary napkin comfort optimization system based on AI intelligent analysis. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] Example 1 See also Figure 1 The present invention provides a sanitary napkin comfort optimization system based on AI intelligent analysis, comprising: A static test module, used to set a plurality of groups of detection points on the sanitary napkin area, perform air permeability detection on the sanitary napkin at the plurality of detection points, record first air permeability data of each detection point, and establish a first air permeability data set; The static analysis module is used to build a sanitary napkin AI analysis model using a convolutional neural network, and input the first breathable data set into the sanitary napkin AI analysis model to analyze the air permeability coefficient of each group of sanitary napkins in static state. ; And use the classifier to calculate the air permeability coefficient of each group of sanitary napkins Perform classification and output the first classification result; A dynamic test module is used to perform cyclic alternating absorbency test, secondary air permeability test and fit test on sanitary napkins at several groups of test points, and obtain absorbency data set, dynamic air permeability data set and friction data set respectively; The dynamic analysis module is used to use the sanitary napkin AI analysis model to train the sanitary napkin AI analysis model based on the absorbency data set, dynamic breathability data set, and friction data set, and then deeply analyze and obtain the absorbency coefficient of each group of sanitary napkins. , wet air permeability coefficient and fit coefficient And evaluate to determine whether each performance is qualified, input the corresponding classification results, and generate corresponding strategies based on the corresponding classification results.

[0023] In this embodiment, the traditional air permeability test method usually relies on static experiments and single-point measurements, which makes it difficult to truly simulate the air permeability performance of sanitary napkins under high humidity or long-term use. The dynamic air permeability test based on the wind tunnel test simulates the variability of air flow during actual wearing, and can comprehensively measure the air permeability of different areas. Through the precise measurement of the gas flow meter, the air permeability data of each detection point is obtained, and the data is optimized and processed through the AI ​​analysis model to output a practical air permeability coefficient. This not only avoids the limitations of traditional methods, but also can evaluate the air permeability performance of sanitary napkins under different environmental conditions.

[0024] Traditional absorbency testing methods often ignore the secondary rewet phenomenon that may occur after long-term use of sanitary napkins, which may lead to inaccurate dryness tests and affect user comfort. The system comprehensively evaluates the performance of sanitary napkins in a wet state through dynamic absorbency tests and secondary air permeability tests. The combination of wet air permeability and absorbency ensures the absorption performance and comfort of sanitary napkins in actual use. Through AI analysis, the system can comprehensively evaluate the dynamic absorption performance of sanitary napkins in use and determine whether they meet the user's high standards for absorbency.

[0025] Traditional fit testing methods mostly rely on manual wearing tests and lack objective, quantitative data. By introducing friction data sets and quantitative evaluation of the fit coefficient, the system can effectively evaluate the changes in comfort of sanitary napkins in different body positions. The recording and analysis of the friction coefficient helps identify changes in friction during long-term use of sanitary napkins, and further reflects the fit problems of sanitary napkins, such as displacement, curling and wrinkling. Using the AI ​​analysis model, the fit coefficient can be automatically calculated, and a more accurate comfort analysis can be made based on a large amount of test data, eliminating the subjective bias in traditional testing.

[0026] Through the training of AI analysis models, the system can conduct in-depth analysis of data in multiple dimensions such as breathability, absorbency and fit, and formulate personalized comfort optimization strategies for each sanitary napkin. Based on the test results, the system can generate corresponding adjustment suggestions, such as adjusting the breathability of the material, optimizing the absorption design, improving the fit, etc., to meet the needs of different consumers. In particular, for the needs in specific environments such as high humidity, high temperature and high exercise intensity, the system can adjust the design of the sanitary napkin in real time to ensure a balance between comfort and performance.

[0027] Example 2 This embodiment is explained and illustrated in Example 1. Please refer to Figure 1 ,Specifically, the static test module includes a first test unit and a first recording unit; The first testing unit is used to simulate the actual use environment by using the wind tunnel test to test the air permeability of each group of sanitary napkins. The specific method is as follows: S11, select each group of sanitary napkin samples, and take the sanitary napkins with the same specifications as one group, and cut each group of sanitary napkins into N test areas so that each sample has the same size; S12, dividing a plurality of groups of detection points on the surface of each group of sanitary napkins, and marking the plurality of groups of detection points, wherein the plurality of groups of detection points include: a central area, an edge area, and an absorption core area; S13. Before opening the wind tunnel, check and calibrate the gas flow meter and partial pressure sensor, and set the first environmental parameters: the temperature is maintained at 25°C and the humidity is maintained at 50%; S14, fix the sanitary napkin sample in the wind tunnel test area using a sanitary napkin clamp so that it completely covers the test port, and adjust the wind speed to a preset test value, the test value includes a first test interval of 2m / s-4m / s, a second test interval of 5m / s-6m / s, and a third test interval of 7m / s-10m / s; S15, start the wind tunnel, so that the wind flow acts vertically on the surface of the sanitary napkin and passes through the first recording unit to record the initial wind speed at the xth detection point and wind speed through sanitary napkin , and calculate the initial permeability coefficient of the xth detection point by the following formula : S16, repeatedly testing the air permeability under different wind speed conditions, using a first test interval of 2m / s-4m / s, a second test interval of 5m / s-6m / s, and a third test interval of 7m / s-10m / s to establish a first air permeability data set; The first air permeability data set includes: air permeability data at different wind speeds, specifically: wind pressure difference at the xth detection point and initial air permeability ; S17, and drawing a permeability distribution heat map based on the first permeability data set.

[0028] In this embodiment, the wind tunnel test is used to simulate the actual wearing environment, and the effect of air flow on the air permeability of the sanitary napkin can be accurately simulated. Compared with the traditional static air permeability test, the wind tunnel test can more realistically reflect the air permeability performance of the sanitary napkin under different environmental conditions, especially when the user is in different activity states, the effect of air flow rate changes on the air permeability. Therefore, the test results are more in line with the actual use situation, and provide scientific and objective data support for the air permeability of sanitary napkin products. By dividing multiple detection points (such as the central area, the edge area and the absorption core area) on the surface of the sanitary napkin and recording the air permeability data of these detection points respectively, the air permeability performance of different areas of the sanitary napkin can be fully understood. In particular, the air permeability analysis of different parts is helpful to make improvements according to the local air permeability differences in the design stage, and optimize the comfort and hygroscopicity of the sanitary napkin. In addition, through the multi-level setting of wind speed (2m / s-4m / s, 5m / s-6m / s, 7m / s-10m / s), the air permeability data under different wind speed conditions can be obtained, and the performance of the sanitary napkin in different environments can be further analyzed to ensure its adaptability. By establishing the first breathability data set and drawing a permeability distribution heat map, the difference in breathability performance at different test points can be intuitively displayed. This provides an accurate basis for subsequent optimization, and can promptly identify deficiencies in the design based on the permeability distribution heat map. For example, poor air permeability in certain areas may lead to local moisture accumulation. Based on this data, the R&D team can adjust material selection, structural design or production process to improve the overall breathability of sanitary napkins and enhance product comfort and user experience.

[0029] Example 3 This embodiment is explained and illustrated in Example 1. Please refer to Figure 1 ,Specifically, the static analysis module includes a model training unit and a static ,quality assessment unit; The model training unit is used to use the convolutional neural network to construct an initial model of the convolutional neural network, and train and test the initial model of the convolutional neural network with the first permeability data, and use the trained initial model of the convolutional neural network as the sanitary napkin AI analysis model, and use the intermediate layer output of the sanitary napkin AI analysis model as a feature vector to identify the partial pressure difference characteristics in the first permeability data, and train and test the sanitary napkin AI analysis model through the obtained information characteristics, and use the trained sanitary napkin AI analysis model as data to run prediction to construct and obtain the air permeability coefficient of each group of sanitary napkins. : Air permeability coefficient of each set of sanitary napkins The specific way to obtain it is: S21. Extract the initial permeability coefficient of the xth detection point , and conduct a continuous 60-minute test, recording the partial pressure difference every 5 minutes: The air permeability attenuation coefficient of each group of sanitary napkins is calculated by the following formula: : In the formula, It represents the wind pressure difference at the xth test point measured after 60 minutes; n represents the total number of test points of each group of sanitary napkins; S22. Adjust the temperature and humidity of the wind tunnel for testing. Set the second environmental parameters of high temperature and high humidity to 40°C and 80% humidity, and set the third environmental parameters of low temperature and low humidity to 10°C and 20% humidity. Test for 60 minutes continuously, record the partial pressure difference every 5 minutes, and calculate the air permeability attenuation coefficient of each group of sanitary napkins. This method can truly reflect the attenuation trend of the air permeability of sanitary napkins during long-term use, which is helpful to evaluate the durability and comfort of sanitary napkins. The air permeability attenuation coefficient provides a scientific basis for product quality control and continuous optimization, and is particularly suitable for tracking and analyzing air permeability performance during long-term use.

[0030] The temperature, humidity and air permeability index of each set of sanitary napkins is calculated using the following formula: : In the formula, It represents the wind pressure difference of the xth test point under the second environmental parameter of high temperature and high humidity. It represents the wind pressure difference of the third environmental parameter of low temperature and low humidity at the xth test point; n represents the total number of test points of each group of sanitary napkins; by setting different temperature and humidity environments (such as high temperature and high humidity and low temperature and low humidity), the breathability of sanitary napkins under different environmental conditions can be fully tested. This process helps to identify the changes in the breathability of sanitary napkins in extreme environments and reveals the adaptability of their materials and structures. For brands, this analysis helps ensure that the product can still maintain good comfort under different climate and environmental conditions. The introduction of the temperature and humidity breathability index helps to finely evaluate the stability of the product in different external environments.

[0031] , indicating that the current group of sanitary napkin materials has decreased air permeability and increased material resistance in high temperature and high humidity environments; , indicating that the breathability of the sanitary napkin materials in this group is not affected by environmental changes; , indicating that the current group of sanitary napkin materials has undergone microstructural changes, resulting in improved air permeability in high temperature and high humidity environments; S23, extracting the wind pressure difference at the xth detection point in each group of sanitary napkins , the air permeability uniformity index of each group of sanitary napkins is calculated by the following formula : in, represents the wind pressure difference at the xth detection point, represents the standard deviation of the wind pressure difference at the xth detection point, It represents the average value of the wind pressure difference of several groups of test points; n represents the total number of test points of each group of sanitary napkins; the air permeability uniformity index can reflect the uniformity of the air permeability of sanitary napkins by measuring the wind pressure difference of different test points and calculating the standard deviation. This index can help find the phenomenon of insufficient or excessive local air permeability in the design of sanitary napkins. Ensuring the uniformity of air permeability is crucial to improving the comfort of the product, especially in occasions where it needs to be worn for a long time. Uniform air permeability can effectively improve the wearer's experience.

[0032] S24, combining the air permeability attenuation coefficient of each group of sanitary napkins obtained by calculation in S21-S23 , Temperature, humidity and air permeability index and air permeability uniformity index , after dimensionless processing, the air permeability coefficient of each group of sanitary napkins is calculated by the following formula : In the formula, , and Denote the air permeability attenuation coefficient , Temperature, humidity and air permeability index and air permeability uniformity index The weight coefficient of , and the weight sum is 1; It represents the inverse term, which indicates the effect of air permeability decay over time. The more stable, the better the air permeability. It represents the correction term, which is used to reflect the influence of temperature and humidity changes on air permeability. The more stable the air permeability is, the less affected it is by temperature and humidity changes, and the better it is. e represents an exponential function with 1 as the base; In this embodiment, the sanitary napkin AI analysis model constructed using a convolutional neural network (CNN) can extract implicit features from complex breathability data, and train through the feature vector output by the intermediate layer, thereby improving the accuracy of the model. Through the trained model, not only can the air permeability coefficient of each group of sanitary napkins be accurately predicted, but also the air permeability changes under different conditions can be refined. This can greatly improve the recognition accuracy of the air permeability performance of sanitary napkins and optimize product design and improvement. In the process of systematic and standardized testing of each group of sanitary napkins, the performance consistency of different batches of products can be ensured by accurately calculating the air permeability coefficient, attenuation coefficient and uniformity index of each group of sanitary napkins. The static analysis module combines deep learning, environmental adaptability testing and refined data analysis to provide a scientific and accurate multi-dimensional analysis method for the air permeability evaluation of sanitary napkins. Through this module, the air permeability performance of sanitary napkins under different environmental conditions can be quantified and predicted, helping companies make more informed decisions in product design, production and quality control, and improving product performance and user experience. At the same time, this method has wide adaptability and can be applied to the breathability evaluation of different types of sanitary napkins, promoting the improvement of industry standards and technological innovation.

[0033] Example 4 This embodiment is explained and illustrated in Example 3. Please refer to Figure 1 Specifically, the static quality evaluation unit is used to preset the air permeability threshold X and calculate the air permeability coefficient of each group of sanitary napkins. The air permeability threshold X is compared to determine whether the air permeability of the group of sanitary napkins is qualified under the static test. The static test refers to measuring and classifying the air permeability of the sanitary napkins under the fixed environmental conditions of the first environmental parameter, the second environmental parameter and the third environmental parameter to obtain the first classification result, including: If the air permeability coefficient of each set of sanitary napkins ≥ breathability threshold value X, indicating that the breathability of the sanitary napkins in this group is qualified, and the first qualified classification label is generated; If the air permeability coefficient of each set of sanitary napkins < breathability threshold value X, indicating that the breathability of the sanitary napkins in this group is unqualified, triggering the first warning instruction.

[0034] Here is a chart of the first breathable dataset and an example of the entire first classification results: In this embodiment, by presetting the air permeability threshold value X and comparing the air permeability coefficient of each group of sanitary napkins with it, it is possible to clearly determine whether the air permeability of the sanitary napkins in the static test is qualified. The fixed environmental conditions (the first, second, and third environmental parameters) provide a stable test platform for the test, ensuring that the results of each air permeability test are consistent and comparable. This method can avoid the influence of external environmental changes on the test results, thereby ensuring the accuracy of the evaluation process.

[0035] Example 5 This embodiment is explained and illustrated in Example 1. Please refer to Figure 1 ,Specifically, the dynamic test module includes an immersion test unit, an alternating test unit and a comfort test unit; The immersion test unit is used to perform multiple liquid immersion tests at the detection points of each group of sanitary napkin samples, record the absorbency data of each detection point, and establish a first absorbency data set; and after the absorbency test, the alternating test unit is used to perform a secondary air permeability test on the detection points of each group of sanitary napkin samples, record the dynamic air permeability data of each detection point, and establish a dynamic air permeability data set; after the secondary air permeability test, the comfort test unit is used to perform a fit test on the detection points of each group of sanitary napkin samples, use a pressure sensor to simulate the contact pressure between the sanitary napkin and the skin, simulate different body positions, record the pressure change data under different test conditions and the friction data of the contact point, and establish a friction data set; Multiple liquid immersion tests include: Select each group of sanitary napkin samples, prepare standard test liquid, set the liquid temperature to 37°C, simulate the composition of human excrement, use a titration device, and perform multiple immersion tests at each test point according to the preset liquid volume, including 1ml, 3ml and 5ml. Record the time required for complete absorption of the liquid, and use an extrusion device to measure the residual humidity after each liquid penetration and the volume of liquid that seeps back under a certain pressure; Perform multiple immersion tests, accumulate absorption data of different liquid volumes and different time intervals, and establish a first absorbency data set; Secondary air permeability tests include: After completing multiple liquid immersion tests, immediately conduct a secondary air permeability test on each group of sanitary napkin samples, conduct an inspection before opening the wind tunnel, calibrate the gas flow meter and partial pressure sensor, and set the fourth environmental parameters: the temperature is maintained at 37°C and the humidity is maintained at 60% to simulate a wet environment; the sanitary napkin samples are fixed in the wind tunnel test area using a sanitary napkin clamp so that they completely cover the test port, and the wind speed is adjusted to the preset test value, which includes the first test interval of 2m / s-4m / s, the second test interval of 5m / s-6m / s and the third test interval of 7m / s-10m / s; collect dynamic air permeability data after multiple liquid immersion tests, repeat the dynamic air permeability test under different wind speed conditions, and establish a dynamic air permeability data set; Fit testing includes: After completing the dynamic air permeability test, each group of sanitary napkin samples is tested for fit. The sanitary napkin samples are fixed on the human body simulation device to fit the simulated skin area, and the contact pressure is measured in real time using a high-precision pressure sensor. Different body positions are simulated, including standing, walking, sitting and lying. Different pressures are applied in each position, and the pressure distribution data of the contact area is recorded. The friction coefficient under different test conditions is measured by a friction sensor, the friction changes at the contact points are recorded, and the displacement, curling and wrinkling of the sanitary napkins in different body positions are analyzed, and a friction data set is established.

[0036] In this embodiment, the absorption performance of the sanitary napkin in actual use can be accurately simulated through multiple liquid immersion tests, including absorption data at different liquid volumes and different time intervals, so as to obtain the absorption efficiency and liquid retention capacity of the sanitary napkin in actual use. This process provides detailed measurement data for the hygroscopic performance of the sanitary napkin and provides a scientific basis for improving the absorption capacity of the sanitary napkin and liquid penetration management.

[0037] The secondary air permeability test further analyzes the air permeability of sanitary napkins in different wet environments, especially how to maintain air permeability after being soaked in liquid. By simulating different environmental conditions such as wind speed, temperature, and humidity, the air permeability of sanitary napkins in wet conditions can be accurately evaluated, which helps ensure that sanitary napkins remain dry and comfortable during use.

[0038] The comfort test unit can simulate the fit of sanitary napkins in different human body positions (such as standing, walking, sitting, and lying). It measures the pressure of the sanitary napkin in contact with the skin through high-precision pressure sensors, truly reflects the adaptability of the sanitary napkin in various activities, helps optimize product design, and improves the user's comfort.

[0039] The friction sensor measures the friction coefficient of sanitary napkins in different body positions and analyzes the displacement, curling and wrinkling of sanitary napkins. This provides a basis for optimizing the comfort of sanitary napkins, reduces the discomfort of products in different body positions, and improves the user experience.

[0040] Example 6 This embodiment is explained and illustrated in Example 1. Please refer to Figure 1 Specifically, the first absorbency data set includes: the liquid absorption saturation time of each detection point , Maximum absorption and re-infiltration ; The dynamic permeability data set includes: the residual permeability volume in the wet state at each detection point And the partial pressure difference of each detection point in the wet state ; The friction data set includes: displacement S, curling rate E and wrinkle area W of each detection point.

[0041] The dynamic analysis module includes an absorption analysis unit, an alternating air permeability analysis unit and a comfort analysis unit; The absorption analysis unit is used to use the sanitary napkin AI analysis model to divide the absorbency data set into 80% training set, 10% test set and 10% validation set. After training and validating the sanitary napkin AI analysis model, the absorbency coefficient of each group of sanitary napkins is calculated using the following formula: : In the formula, represents the maximum absorption at the xth detection point, represents the absorption saturation time of the xth detection point, represents the back-infiltration amount at the xth detection point; and represents the weight coefficient; and the sum of the weights is 1; The alternating air permeability analysis unit is used to use the sanitary napkin AI analysis model to divide the dynamic air permeability data set into 80% training set, 10% test set and 10% validation set. After training and validating the sanitary napkin AI analysis model, the wet air permeability coefficient of each group of sanitary napkins is calculated using the following formula: : In the formula, represents the maximum absorption at the xth detection point, represents the residual permeability volume of the xth test point in the wet state, It represents the partial pressure difference of the xth detection point in the wet state; and represents the weight coefficient; and the sum of the weights is 1; The comfort analysis unit is used to use the sanitary napkin AI analysis model to divide the friction data set into 80% training set, 10% test set and 10% validation set. After training and validating the sanitary napkin AI analysis model, the fit coefficient of each set of sanitary napkins is calculated using the following formula: : In the formula, represents the displacement of the xth detection point, represents the curling rate of the xth detection point, represents the wrinkle area at the xth detection point; represents the friction coefficient of the xth detection point, The value of is set based on experimental data. , , and Represents the weight coefficient, and the sum of the weights is 1.

[0042] In the calculation process of the present invention, all formulas involved are dimensionless to ensure that different physical quantities are calculated and compared in the same dimension. The main purpose of dimensionless is to eliminate the unit effect, improve the versatility and adaptability of the calculation, and enable sanitary napkin products of different batches and specifications to be scientifically evaluated under the same evaluation system.

[0043] Humidity has a great influence on friction and comfort. When the humidity is high, the skin is prone to sweating, the friction coefficient β increases, and the sanitary napkin may shift. Therefore, when the humidity is high, β will increase accordingly.

[0044] Below is an example graph of the coefficient of friction, β, as a function of humidity: Temperature has a great impact on the skin. In a high temperature environment, sweat secretion increases, humidity also increases, friction increases, and fit may decrease. In a low temperature environment, the skin is dry and the friction coefficient β is low; Below is an example graph of the coefficient of friction, β, as a function of humidity: When the intensity of exercise is high, the human body generates a lot of heat, sweat increases, friction increases, and the fit may also decrease. Therefore, under different exercise intensities, the friction coefficient β also needs to be adjusted.

[0045] Here is an example graph of the coefficient of friction, β, affected by motion: Based on the above conditions, the friction coefficient β can be calculated by combining humidity, temperature and exercise intensity. For example, assuming a light walking activity in an environment with a temperature of 25°C and a humidity of 60%: Temperature 25° → β = 1.2; Humidity 60% → friction coefficient β = 1.2; Light walking activity → β = 1.2; The final β value is (1.2+1.2+1.2)2 / 3=1.2, which reflects the effects of humidity and temperature on friction in this environment, as well as the changes in friction caused by light walking activities.

[0046] In this embodiment, the absorbency coefficient calculation can accurately quantify the absorption capacity of the sanitary napkin through the comprehensive calculation of the maximum absorption amount, absorption saturation time and re-seepage amount. The absorption saturation time is used to make the products with fast absorption speed score higher, avoid the limitation of measuring performance only by the maximum absorption amount, consider the re-seepage amount, ensure that it can still remain dry after absorption, and improve the user comfort. The wet permeability coefficient calculation uses the wet residual permeable volume to measure the breathability of the sanitary napkin after absorbing the liquid, which helps to reduce the stuffiness. Combined with the partial pressure difference, the difficulty of wet air exchange is reflected to ensure that the calculated air permeability conforms to the actual use. The quantification of the wet permeability coefficient is convenient for improving the air permeability, which can reduce skin discomfort and improve the comfort of long-term wearing. The fit coefficient calculation is combined with the friction coefficient, and pays attention to parameters such as displacement, curling rate, and wrinkling area to comprehensively measure the fit of the sanitary napkin to ensure that the comfort is not affected by displacement and deformation. Ensure that the sanitary napkin can fit stably in various environments without affecting the user experience.

[0047] Example 7 This embodiment is explained and illustrated in Example 6. Please refer to Figure 1 ,Specifically, the dynamic analysis module also includes a first evaluation unit, a second evaluation unit, and a third evaluation unit; The first evaluation unit is used to preset a first absorption threshold value Y1 and calculate the absorption coefficient of each group of sanitary napkins. Compare with the first absorption threshold value Y1 to determine whether the absorbency of the sanitary napkin is qualified, and generate a second classification result, including: If the absorbency coefficient of each set of sanitary napkins ≥ the first absorption threshold Y1, indicating that the absorbency of the group of sanitary napkins is qualified, and a second qualified classification label is generated; If the absorbency coefficient of each set of sanitary napkins < the first absorption threshold value Y1, indicating that the absorbency of the group of sanitary napkins is unqualified, triggering the second warning instruction; The second evaluation unit is used to preset a second air permeability threshold value Y2 and calculate the wet air permeability coefficient of each group of sanitary napkins. The result is compared with the second air permeability threshold value Y2 to determine whether the air permeability of the sanitary napkin during the dynamic liquid immersion process is qualified, and a third classification result is generated, including: If the wet air permeability coefficient of each group of sanitary napkins is ≥ the second air permeability threshold value Y2, indicating that the air permeability of the sanitary napkins in the dynamic liquid immersion process is qualified, and a third qualified classification label is generated; If the wet air permeability coefficient of each group of sanitary napkins is < the second air permeability threshold value Y2, indicating that the air permeability of the sanitary napkins in the dynamic liquid immersion process is unqualified, triggering the third warning instruction; The third evaluation unit is used to preset a third comfort threshold Y3 and calculate the fit coefficient of each set of sanitary napkins. The third comfort threshold Y3 is compared to determine whether the comfort level of the sanitary napkin during wearing is qualified, and a fourth classification result is generated, including: If the fit coefficient of each set of sanitary napkins ≥ the third comfort threshold Y3, indicating that the wearing comfort of the group of sanitary napkins is qualified, and the third qualified classification label is generated; If the fit coefficient of each set of sanitary napkins <The third comfort threshold Y3, indicating that the wearing comfort of the group of sanitary napkins is unqualified, triggering the fourth warning instruction.

[0048] In this embodiment, a quantitative calculation formula + threshold comparison + early warning mechanism is used to realize intelligent monitoring of sanitary napkin product quality, reduce manual intervention, and improve detection efficiency. Combined with absorbency, breathability, and comfort, it ensures that sanitary napkins perform well under different conditions of use. Multi-level early warning (second early warning instruction, third early warning instruction, fourth early warning instruction) can detect abnormalities in time and improve the quality management level of the production line. The dynamic analysis module combines the three core indicators of absorption, breathability, and comfort, and adopts intelligent calculation + automatic threshold evaluation + early warning feedback mechanism to provide an accurate and automated quality evaluation system. Compared with traditional manual detection or single standard evaluation methods, this solution is smarter, more accurate, and more efficient, which can effectively improve product quality, optimize user experience, and reduce losses caused by quality problems.

[0049] Example 8 This embodiment is explained and illustrated in Example 1. Please refer to Figure 1 ,Specifically, the dynamic analysis module also includes a first strategy unit and a second strategy unit; The first strategy unit is used to generate a first strategy after receiving the first warning instruction in the first classification result, including: marking unqualified test points, increasing the porosity of the absorbent core by 5%-15%, increasing the air layer fiber content by 5%-15%, increasing the central zone air permeability distribution area by 10%-12%, or adjusting the air permeable membrane opening rate by 5%-8%.

[0050] In this embodiment, the first strategy unit is used to accurately mark products with unqualified air permeability, rather than blindly adjusting the overall production parameters, thereby avoiding material waste or unnecessary additional costs caused by overall adjustment and improving production efficiency.

[0051] By appropriately increasing the porosity of the absorbent core, the liquid absorption rate and capacity are optimized and the risk of back seepage is reduced.

[0052] Increasing the porosity by 5%-15% can improve the uniformity of liquid diffusion, avoid local saturation, and improve overall absorption efficiency.

[0053] Example 9 This embodiment is explained and illustrated in Example 7. Please refer to Figure 1 Specifically, the second strategy unit is used to generate a second strategy after receiving the second warning instruction in the second classification result, including: increasing the current absorption core ratio to 3%-5%, thickening the current guide layer by 0.2mm-0.3mm, and increasing the pore density of the bottom anti-leakage film by 20-30 / cm²; After receiving the third warning instruction in the third classification result, a third strategy is generated, including: increasing the air permeability of the current original film by 15%-20%, optimizing the diameter of the surface micropores by 0.2mm, and increasing the original embossing depth to 0.4mm; After receiving the fourth warning instruction in the fourth classification result, a fourth strategy is generated, including: increasing the width value of the side wing size by 10%-15%, reducing the wing sticking angle by 10%-12% and increasing the viscosity of the original tape by 15%-20%.

[0054] Corresponding strategy actual example: Second strategy (absorption optimization strategy) Trigger condition: Absorbency coefficient of each set of sanitary napkins <The first absorption threshold Y1 (e.g. Y1=15g / g, indicating that each gram of sanitary napkin can absorb 15g of liquid); Optimization direction: enhance liquid absorption capacity, reduce back permeation, and improve liquid locking capacity; Optimization strategy refinement: (1) Optimization of polymer absorbent material (SAP): Original SAP share: 25%-30%; Adjustment plan: Increase the proportion of SAP by 3%-5% (i.e., increase it to 28%-35%) to enhance the water absorption rate and liquid storage capacity; Target improvement value: Increase the absorbency coefficient A by 8%-12% and reduce the re-seepage by 5%-7%; (2) Optimization of the flow guide layer: Original guide layer thickness: 1.0mm; Adjustment plan: increase the thickness by 0.2mm-0.3mm to increase the liquid diffusion rate; Target improvement value: absorption speed increased by 10%-15%, absorption unevenness reduced by 6%-8%; (3) Optimization of bottom anti-leakage membrane: Original air hole density: 150 / cm²; Adjustment plan: increase 20-30 / cm² to improve moisture volatilization capacity; Target improvement value: Humidity reduction of 12%-18%, reducing the feeling of fluid accumulation; (4) Key test optimization: Back permeability test pressure: 5kPa: Adjustment plan: Increase to 7kPa to simulate a higher pressure environment; Target value: Re-seepage volume reduced by 5%-8%, water-locking capacity increased by 9%-12%; The third strategy (breathability optimization strategy): Trigger condition: wet air permeability coefficient of each set of sanitary napkins <The second air permeability threshold Y2 (e.g. Y2=1200mL / (m²·s)); Optimization direction: improve air permeability in humid environments and reduce stuffiness; Optimization strategy refinement: (1) Breathable membrane optimization: Original film air permeability: 1100mL / (m²·s); Adjustment plan: increase by 15%-20%, optimized to 1265-1320mL / (m²·s); Target improvement: air permeability increased by 14%-18%, surface dryness increased by 10%-12%; (2) Optimization of surface micropore structure: Original micropore diameter: 0.5mm; Adjustment plan: Increase to 0.7mm to improve air circulation; Target improvement value: Moisture diffusion rate increased by 12%-16%; (3) Hot air embossing treatment: Original embossing depth: 0.2mm; Adjustment plan: Increase the depth to 0.4mm to increase the air gap between the skin and the surface; Target improvement value: Skin contact humidity is reduced by 8%-10%, and breathability and comfort are improved by 15%-18%; (4) Key test optimization: High humidity environment test: the original set humidity is 60%; Adjustment plan: Increase to 75% to simulate extreme hot and humid conditions; Target value: Maintaining more than 85% ventilation efficiency in high humidity environment; The fourth strategy (fitness optimization strategy): Trigger condition: The fit coefficient of each set of sanitary napkins <The third comfort threshold Y3 (e.g. Y3=0.85, indicating that the fit must reach 85%); Optimization direction: Improve fit, reduce displacement, curling and wrinkling; Optimization strategy refinement: (1) Flank size optimization: Original wing width: 25mm; Adjustment plan: increase by 10%-15% (adjust to 27.5-28.75mm) to increase the contact area; Target improvement value: Improve the wing fixing capacity by 15%-20% and reduce the side leakage by 8%-10%; (2) Optimization of the wing attachment angle: Original pasting angle: 45°; Adjustment plan: Lower to 30°-35° to accommodate changes in fit during leg movement; Target improvement value: Stability in motion is increased by 10%-12%; (3) Optimization of tape adhesion: Original tape viscosity: 200N / m; Adjustment plan: Increase by 15%-20%, adjust to 230-240N / m; Target improvement value: Improve the fit by 12%-15% and reduce the displacement rate by 10% during exercise; (4) Key test optimization: Dynamic body position test (imitating walking, running, squatting movements); Original moving displacement deviation: 5mm Adjustment plan: The target is reduced to 3mm to reduce the failure rate of fitting; Target value: The fit remains above 90% after long-term exercise; Example chart of the final optimization target: In this embodiment, the present invention uses the second strategy unit to perform intelligent optimization for different warning situations to improve the overall performance of the sanitary napkin. The corresponding strategy combines multi-dimensional optimization to accurately improve the absorption, breathability and comfort performance. Compared with traditional adjustment methods, it can more intelligently improve product quality and optimize user experience.

[0055] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0056] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula that is close to the actual value. The coefficients in the formula are set by technical personnel in this field according to actual conditions. The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited to this. Any technical personnel familiar with the technical field within the technical scope disclosed by the present invention, according to the technical solution and the inventive concept of the present invention, make equivalent replacement or change, which should be covered within the protection scope of the present invention.

Claims

1. A sanitary napkin comfort optimization system based on AI intelligent analysis, characterized in that: include: A static test module, used to set a plurality of groups of detection points on the sanitary napkin area, perform air permeability detection on the sanitary napkin at the plurality of detection points, record first air permeability data of each detection point, and establish a first air permeability data set; The static analysis module is used to build a sanitary napkin AI analysis model using a convolutional neural network, and input the first breathable data set into the sanitary napkin AI analysis model to analyze the air permeability coefficient of each group of sanitary napkins in static state. ; And use the classifier to calculate the air permeability coefficient of each group of sanitary napkins Perform classification and output the first classification result; A dynamic test module is used to perform cyclic alternating absorbency test, secondary air permeability test and fit test on sanitary napkins at several groups of test points, and obtain absorbency data set, dynamic air permeability data set and friction data set respectively; The dynamic analysis module is used to use the sanitary napkin AI analysis model to train the sanitary napkin AI analysis model based on the absorbency data set, dynamic breathability data set, and friction data set, and then deeply analyze and obtain the absorbency coefficient of each group of sanitary napkins. , wet air permeability coefficient and fit coefficient And evaluate to determine whether each performance is qualified, input the corresponding classification results, and generate corresponding strategies based on the corresponding classification results.

2. A sanitary napkin comfort optimization system based on AI intelligent analysis according to claim 1, characterized in that: The static test module includes a first test unit and a first recording unit; The first detection unit is used to simulate the actual use environment by using a wind tunnel test to perform air permeability test on each group of sanitary napkins. The specific method is as follows: S11, select each group of sanitary napkin samples, and take the sanitary napkins with the same specifications as one group, and cut each group of sanitary napkins into N test areas so that each sample has the same size; S12, dividing a plurality of groups of detection points on the surface of each group of sanitary napkins, and marking the plurality of groups of detection points, wherein the plurality of groups of detection points include: a central area, an edge area, and an absorption core area; S13. Before opening the wind tunnel, check and calibrate the gas flow meter and partial pressure sensor, and set the first environmental parameters: the temperature is maintained at 25°C and the humidity is maintained at 50%; S14, fix the sanitary napkin sample in the wind tunnel test area using a sanitary napkin clamp so that it completely covers the test port, and adjust the wind speed to a preset test value, the test value includes a first test interval of 2m / s-4m / s, a second test interval of 5m / s-6m / s, and a third test interval of 7m / s-10m / s; S15, start the wind tunnel, so that the wind flow acts vertically on the surface of the sanitary napkin and passes through the first recording unit to record the initial wind speed at the xth detection point and wind speed through sanitary napkin , and calculate the initial permeability coefficient of the xth detection point by the following formula : S16, repeatedly testing the air permeability under different wind speed conditions, using a first test interval of 2m / s-4m / s, a second test interval of 5m / s-6m / s, and a third test interval of 7m / s-10m / s to establish a first air permeability data set; The first air permeability data set includes: air permeability data at different wind speeds, specifically: wind pressure difference at the xth detection point and initial air permeability ; S17, and drawing a permeability distribution heat map based on the first permeability data set.

3. The sanitary napkin comfort optimization system based on AI intelligent analysis according to claim 1, characterized in that: The static analysis module includes a model training unit and a static quality assessment unit; The model training unit is used to use a convolutional neural network to construct an initial model of the convolutional neural network, and train and test the initial model of the convolutional neural network with the first permeability data, and use the trained initial model of the convolutional neural network as the sanitary napkin AI analysis model, and use the intermediate layer output of the sanitary napkin AI analysis model as a feature vector to identify the partial pressure difference feature in the first permeability data, and train and test the sanitary napkin AI analysis model through the obtained information features, and use the trained sanitary napkin AI analysis model as data to run prediction, so as to construct and obtain the air permeability coefficient of each group of sanitary napkins. : The air permeability coefficient of each group of sanitary napkins The specific way to obtain it is: S21. Extract the initial permeability coefficient of the xth detection point , and conduct a continuous 60-minute test, recording the partial pressure difference every 5 minutes: The air permeability attenuation coefficient of each group of sanitary napkins is calculated by the following formula: : In the formula, It represents the wind pressure difference at the xth test point measured after 60 minutes; n represents the total number of test points of each group of sanitary napkins; S22, adjusting the temperature and humidity of the wind tunnel for testing, setting the second environmental parameters of high temperature and high humidity to: temperature 40°C and humidity 80%, and setting the third environmental parameters of low temperature and low humidity to: temperature 10°C and humidity 20%; The temperature, humidity and air permeability index of each set of sanitary napkins is calculated using the following formula: : In the formula, It represents the wind pressure difference of the xth test point under the second environmental parameter of high temperature and high humidity. represents the wind pressure difference of the third environmental parameter of low temperature and low humidity at the xth detection point; n represents the total number of detection points of each group of sanitary napkins; S23, extracting the wind pressure difference at the xth detection point in each group of sanitary napkins , the air permeability uniformity index of each group of sanitary napkins is calculated by the following formula : in, represents the wind pressure difference at the xth detection point, represents the standard deviation of the wind pressure difference at the xth detection point, It represents the average value of wind pressure difference of several groups of test points; n represents the total number of test points of each group of sanitary napkins; S24, the air permeability attenuation coefficient of each group of sanitary napkins obtained by calculation in S21-S23 , Temperature, humidity and air permeability index and air permeability uniformity index , after dimensionless processing, the air permeability coefficient of each group of sanitary napkins is calculated by the following formula : In the formula, , and Denote the air permeability attenuation coefficient , Temperature, humidity and air permeability index and air permeability uniformity index The weight coefficient of , and the weight sum is 1; It represents the inverse term, which indicates the effect of air permeability decay over time. The more stable, the better the air permeability. It represents a correction term, which is used to reflect the impact of temperature and humidity changes on air permeability. The more stable the air permeability is, the less it is affected by temperature and humidity changes, and the better it is.

4. A sanitary napkin comfort optimization system based on AI intelligent analysis according to claim 3, characterized in that: The static quality evaluation unit is used to preset a permeability threshold value X and calculate the permeability coefficient of each group of sanitary napkins. The air permeability threshold X is compared to determine whether the air permeability of the group of sanitary napkins is qualified under the static test. The static test refers to measuring and classifying the air permeability of the sanitary napkins under the fixed environmental conditions of the first environmental parameter, the second environmental parameter and the third environmental parameter to obtain the first classification result, including: If the air permeability coefficient of each set of sanitary napkins ≥ breathability threshold value X, indicating that the breathability of the sanitary napkins in this group is qualified, and the first qualified classification label is generated; If the air permeability coefficient of each set of sanitary napkins < breathability threshold value X, indicating that the breathability of the sanitary napkins in this group is unqualified, triggering the first warning instruction.

5. The sanitary napkin comfort optimization system based on AI intelligent analysis according to claim 1, characterized in that: The dynamic test module includes an immersion test unit, an alternating test unit and a comfort test unit; The immersion test unit is used to perform multiple liquid immersion tests at the detection points of each group of sanitary napkin samples, record the absorbency data of each detection point, and establish a first absorbency data set; After the absorbency test, the alternating test unit is used to perform a secondary air permeability test on the test points of each group of sanitary napkin samples, and the dynamic air permeability data of each test point is recorded to establish a dynamic air permeability data set; After the second air permeability test, the comfort test unit is used to perform fit tests on the test points of each group of sanitary napkin samples. The pressure sensor is used to simulate the contact pressure between the sanitary napkin and the skin, and different body positions are simulated to record the pressure change data under different test conditions and the friction data of the contact points to establish a friction data set. Multiple liquid immersion tests include: Select each group of sanitary napkin samples, prepare standard test liquid, set the liquid temperature to 37°C, simulate the composition of human excrement, use a titration device, and perform multiple immersion tests at each test point according to the preset liquid volume, including 1ml, 3ml and 5ml. Record the time required for complete absorption of the liquid, and use an extrusion device to measure the residual humidity after each liquid penetration and the volume of liquid that seeps back under a certain pressure; Perform multiple immersion tests, accumulate absorption data of different liquid volumes and different time intervals, and establish a first absorbency data set; Secondary air permeability tests include: After completing multiple liquid immersion tests, immediately conduct a secondary air permeability test on each group of sanitary napkin samples, conduct an inspection before opening the wind tunnel, calibrate the gas flow meter and partial pressure sensor, and set the fourth environmental parameters: the temperature is maintained at 37°C and the humidity is maintained at 60% to simulate a wet environment; the sanitary napkin samples are fixed in the wind tunnel test area using a sanitary napkin clamp so that they completely cover the test port, and the wind speed is adjusted to the preset test value, which includes the first test interval of 2m / s-4m / s, the second test interval of 5m / s-6m / s and the third test interval of 7m / s-10m / s; collect dynamic air permeability data after multiple liquid immersion tests, repeat the dynamic air permeability test under different wind speed conditions, and establish a dynamic air permeability data set; Fit testing includes: After completing the dynamic air permeability test, each group of sanitary napkin samples is tested for fit. The sanitary napkin samples are fixed on the human body simulation device to fit the simulated skin area, and the contact pressure is measured in real time using a high-precision pressure sensor. Different body positions are simulated, including standing, walking, sitting and lying. Different pressures are applied in each position, and the pressure distribution data of the contact area is recorded. The friction coefficient under different test conditions is measured by a friction sensor, the friction changes at the contact points are recorded, and the displacement, curling and wrinkling of the sanitary napkins in different body positions are analyzed, and a friction data set is established.

6. A sanitary napkin comfort optimization system based on AI intelligent analysis according to claim 5, characterized in that: The first absorbency data set includes: the liquid absorption saturation time of each detection point , Maximum absorption and re-infiltration ; The dynamic air permeability data set includes: the residual air permeability volume of each detection point in the wet state And the partial pressure difference of each detection point in the wet state ; The friction data set includes: the displacement S, the curling rate E and the wrinkling area W of each detection point.

7. A sanitary napkin comfort optimization system based on AI intelligent analysis according to claim 6, characterized in that: The dynamic analysis module includes an absorption analysis unit, an alternating air permeability analysis unit and a comfort analysis unit; The absorption analysis unit is used to use the sanitary napkin AI analysis model to divide the absorbency data set into 80% training set, 10% test set and 10% validation set. After training and validating the sanitary napkin AI analysis model, the absorbency coefficient of each group of sanitary napkins is calculated by the following formula: : In the formula, represents the maximum absorption at the xth detection point, represents the absorption saturation time of the xth detection point, represents the back-infiltration amount at the xth detection point; and represents the weight coefficient; The alternating air permeability analysis unit is used to use the sanitary napkin AI analysis model to divide the dynamic air permeability data set into 80% training set, 10% test set and 10% validation set. After training and validating the sanitary napkin AI analysis model, the wet air permeability coefficient of each group of sanitary napkins is calculated by the following formula: : In the formula, represents the maximum absorption at the xth detection point, represents the residual permeability volume of the xth test point in the wet state, It represents the partial pressure difference of the xth detection point in the wet state; and represents the weight coefficient; The comfort analysis unit is used to use the sanitary napkin AI analysis model to divide the friction data set into 80% training set, 10% test set and 10% validation set. After training and validating the sanitary napkin AI analysis model, the fit coefficient of each group of sanitary napkins is calculated by the following formula: : In the formula, represents the displacement of the xth detection point, represents the curling rate of the xth detection point, represents the wrinkle area at the xth detection point; represents the friction coefficient of the xth detection point, The value of is set based on experimental data. , , and Represents the weight coefficient.

8. A sanitary napkin comfort optimization system based on AI intelligent analysis according to claim 7, characterized in that: The dynamic analysis module also includes a first evaluation unit, a second evaluation unit and a third evaluation unit; The first evaluation unit is used to preset a first absorption threshold value Y1 and calculate the absorption coefficient of each group of sanitary napkins. Compare with the first absorption threshold value Y1 to determine whether the absorbency of the sanitary napkin is qualified, and generate a second classification result, including: If the absorbency coefficient of each set of sanitary napkins ≥ the first absorption threshold Y1, indicating that the absorbency of the group of sanitary napkins is qualified, and a second qualified classification label is generated; If the absorbency coefficient of each set of sanitary napkins < the first absorption threshold value Y1, indicating that the absorbency of the group of sanitary napkins is unqualified, triggering the second warning instruction; The second evaluation unit is used to preset a second air permeability threshold value Y2 and calculate the wet air permeability coefficient of each group of sanitary napkins. The third classification result is generated by comparing the second air permeability threshold value Y2 to determine whether the air permeability of the sanitary napkin during the dynamic liquid immersion process is qualified, including: If the wet air permeability coefficient of each set of sanitary napkins is ≥ the second air permeability threshold value Y2, indicating that the air permeability of the sanitary napkins in the dynamic liquid immersion process is qualified, and a third qualified classification label is generated; If the wet air permeability coefficient of each set of sanitary napkins is < the second air permeability threshold value Y2, indicating that the air permeability of the sanitary napkins in the dynamic liquid immersion process is unqualified, triggering the third warning instruction; The third evaluation unit is used to preset a third comfort threshold Y3 and calculate the fit coefficient of each set of sanitary napkins. The third comfort threshold Y3 is compared to determine whether the comfort level of the sanitary napkin during wearing is qualified, and a fourth classification result is generated, including: If the fit coefficient of each set of sanitary napkins ≥ the third comfort threshold Y3, indicating that the wearing comfort of the group of sanitary napkins is qualified, and the third qualified classification label is generated; If the fit coefficient of each set of sanitary napkins <The third comfort threshold Y3, indicating that the wearing comfort of the group of sanitary napkins is unqualified, triggering the fourth warning instruction.

9. A sanitary napkin comfort optimization system based on AI intelligent analysis according to claim 8, characterized in that: The dynamic analysis module also includes a first strategy unit and a second strategy unit; The first strategy unit is used to generate a first strategy after receiving the first warning instruction in the first classification result, including: marking unqualified inspection points, and increasing the porosity of the absorbent core by 5%-15%, increasing the air layer fiber content by 5%-15%, increasing the central zone air permeability distribution area by 10%-12%, or adjusting the air permeable membrane opening rate by 5%-8%.

10. A sanitary napkin comfort optimization system based on AI intelligent analysis according to claim 9, characterized in that: The second strategy unit is used to generate a second strategy after receiving the second warning instruction in the second classification result, including: increasing the current absorption core proportion to 3%-5%, thickening the current guide layer by 0.2mm-0.3mm, and increasing the pore density of the bottom anti-leakage film by 20-30 / cm²; After receiving the third warning instruction in the third classification result, a third strategy is generated, including: increasing the air permeability of the current original film by 15%-20%, optimizing the diameter of the surface micropores by 0.2mm, and increasing the original embossing depth to 0.4mm; After receiving the fourth warning instruction in the fourth classification result, a fourth strategy is generated, including: increasing the width value of the side wing size by 10%-15%, reducing the wing sticking angle by 10%-12% and increasing the viscosity of the original tape by 15%-20%.

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