A sock design and weaving integrated system and method

Abstract

The present invention relates to the technical field of sock design and weaving, and specifically to an integrated system and method for sock design and weaving; it includes: adjusting the mouth-binding pressure data to produce test samples; selecting testers to wear the test samples for exercise testing to obtain a test data set and constructing a test database; screening the test database to obtain a reference data set according to the leg shape similarity between the target person's leg shape data and the tester's leg shape data; calculating the mouth-binding pressure label according to the mouth-binding indentation data and the mouth-binding slippage data in the reference data set; training a model based on the exercise process data, the mouth-binding pressure data and the mouth-binding pressure label, and using the corresponding leg shape similarity as the data weight to obtain a mouth-binding pressure prediction model; identifying the optimal mouth-binding pressure data according to the mouth-binding pressure prediction model for the historical exercise data of the target person. The present invention accurately performs differential design and production of sports socks for the target person through the optimal mouth-binding pressure data.

Description

Technical Field

[0001] The present invention relates to the technical field of sock design and weaving, and specifically to an integrated system and method for sock product design and weaving. Background Art

[0002] Sports socks are socks specially designed and woven for sports. Compared with ordinary socks, sports socks pay more attention to breathability, moisture absorption, durability, and support for the feet of athletes; they can enhance the sports performance of athletes, reduce sports injuries, and provide a better sports experience. During sports, due to the intense exercise of athletes, the sports socks may slide down, and it is necessary to fix the sports socks through the cuffs.

[0003] The cuff of a sports sock refers to the part woven with elastic material at the top of the sports sock, which can provide a certain pressure to make the sports sock fit firmly around the ankle or calf, making it not easy to slide off, and is also called the sock mouth. Appropriate cuff pressure is the key to ensuring the functionality and wearing comfort of sports socks. If the cuff pressure is too large, it will affect blood circulation in the legs and cause leg marks; if the cuff pressure is too small, the sports socks cannot be effectively fixed, resulting in the phenomenon of the sports socks falling off.

[0004] Due to the differences in the leg shape data, sports types, and sports habits of athletes, different requirements for the cuff pressure of sports socks are also needed. In order to provide a better sports experience, it is necessary to conduct differential analysis according to the preferences of athletes; however, the existing technology mainly conducts mass production according to fixed parameters without differential consideration, resulting in the cuff pressure data of sports socks not reaching the optimal value and affecting the sports performance of athletes.

[0005] Therefore, an integrated system and method for sock product design and weaving are proposed. Summary of the Invention

[0006] The purpose of the present invention is to provide an integrated system and method for sock product design and weaving. By adjusting the cuff pressure data, test samples are produced; test personnel are selected to wear the test samples for sports tests to obtain a test data set, and a test database is constructed; according to the leg shape similarity between the leg shape data of the target personnel and the leg shape data of the test personnel, the test database is screened to obtain a reference data set; according to the cuff mark data and cuff slip data in the reference data set, the cuff pressure label is calculated; model training is carried out according to the sports process data, cuff pressure data, and cuff pressure label, and the corresponding leg shape similarity is used as the data weight to obtain a cuff pressure prediction model; the historical sports data of the target personnel is identified according to the cuff pressure prediction model to obtain the optimal cuff pressure data; through the optimal cuff pressure data, the differential design and production of socks for the target personnel are accurately carried out.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A sock design and weaving integration system, comprising:

[0009] A database construction module, which obtains parameter information of socks, including sock design data and cuff pressure data; produces test samples by adjusting the cuff pressure data; selects testers to wear the test samples for exercise testing to obtain a test data set; the test data set includes tester leg type data, exercise process data, cuff indentation data, cuff slippage data, and cuff pressure data; the exercise process data includes exercise duration, exercise mileage, exercise temperature, exercise humidity, and exercise intensity; constructs a test database according to the test data set;

[0010] An information matching module, which obtains target person leg type data and historical exercise data; obtains the leg type similarity according to the target person leg type data and the tester leg type data; screens the test database according to the leg type similarity to obtain a reference data set;

[0011] A data processing module, which obtains the cuff indentation data and the cuff slippage data in the reference data set; obtains a first pressure label according to the cuff indentation data, and obtains a second pressure label according to the cuff slippage data; calculates a cuff pressure label according to the first pressure label and the second pressure label;

[0012] A model construction module, which performs model training according to the exercise process data, the cuff pressure data, and the cuff pressure label in the reference data set, and uses the corresponding leg type similarity as a data weight to obtain a cuff pressure prediction model;

[0013] A pressure prediction module, which identifies the historical exercise data of the target person according to the cuff pressure prediction model to obtain the optimal cuff pressure data for differential production.

[0014] Taking the pressure data of the sock cuff when worn as the cuff pressure data, the obtaining process of the cuff pressure data is as follows:

[0015] Determine a standard mold according to the sock design data;

[0016] Wear different test samples on the standard mold, and set pressure sensors on the contact surface between the sock cuff of the test sample and the standard mold; use the pressure data measured by the pressure sensors as the cuff pressure data of the test sample.

[0017] The exercise duration represents the duration of the tester wearing the test sample for exercise testing;

[0018] The exercise mileage represents the total moving mileage of the tester within the exercise duration;

[0019] The exercise temperature is the temperature data of the area where the tester wears socks during the exercise test;

[0020] The exercise humidity is the humidity data of the area where the tester wears socks during the exercise test;

[0021] The exercise intensity is used to reflect the intensity of the tester's exercise during the exercise test, and is calculated based on the tester's heart rate data, vibration frequency data, and electromyogram signal data; the calculation formula is:

[0022] ;

[0023] Where, represents the exercise intensity; represents the heart rate weight; represents the average heart rate data, represents the heart rate threshold; represents the vibration frequency weight; represents the average vibration frequency data; represents the vibration frequency threshold; represents the electromyogram weight; represents the average electromyogram data; represents the electromyogram threshold.

[0024] The process of obtaining and comparing the leg shape data of the tester and the target person is as follows:

[0025] Scan the legs of the tester wearing the test sample in the standing state to obtain the three-dimensional leg data within the range wrapped by the test sample, which is used as the leg shape data of the tester;

[0026] Obtain the height of the tester's leg shape data, and identify the legs of the target person based on the height of the tester's leg shape data to obtain the leg shape data of the target person; the height of the tester's leg shape data is the same as the height of the socks;

[0027] Obtain the leg shape similarity based on the data similarity between the target person's leg shape data and the tester's leg shape data;

[0028] Obtain the similarity threshold. When the leg shape similarity is greater than the similarity threshold, select the test data of the tester as the reference data.

[0029] The process of obtaining the first pressure label is as follows:

[0030] Obtain the drawstring indentation data, which includes the drawstring indentation volume and the drawstring contact area;

[0031] The drawstring indentation volume is the skin depression volume of the tester at the drawstring of the test sample after the exercise test; the drawstring contact area is the contact area between the drawstring of the test sample and the tester's skin;

[0032] The average indentation depth is measured based on the drawstring indentation volume and the drawstring contact area, and the first pressure label is measured based on the average indentation depth; the calculation formula for the first pressure label is:

[0033] ;

[0034] wherein, represents the first pressure label; represents the drawstring indentation volume; represents the drawstring contact area; represents the indentation threshold.

[0035] The process of obtaining the second pressure label is as follows:

[0036] Obtain the position of the drawstring of the test sample on the leg of the tester at the start of the movement test as the initial drawstring position; obtain the position of the drawstring of the test sample on the leg of the tester at the end of the movement test as the slipped drawstring position.

[0037] Take the horizontal plane where the initial drawstring position is located as the initial drawstring position horizontal plane, and take the horizontal plane where the slipped drawstring position is located as the slipped drawstring position horizontal plane; obtain the drawstring slip data according to the leg shape data of the tester between the initial drawstring position horizontal plane and the slipped drawstring position horizontal plane.

[0038] Take the horizontal plane of the slipped drawstring position as the xy plane, and take the perpendicular line between the initial drawstring position horizontal plane and the slipped drawstring position horizontal plane as the z axis, construct a three-dimensional coordinate system for the drawstring slip data, and obtain the corresponding relationship between the height of the drawstring slip data and the leg circumference data; the leg circumference data is the cross-sectional circumference data of the drawstring slip data in the horizontal planes at different heights.

[0039] Determine the leg circumference extreme horizontal plane and its corresponding height data according to the extreme points of the leg circumference data to obtain the height division points.

[0040] Obtain the first height division point according to the height of the initial drawstring position, obtain the last height division point according to the height of the slipped drawstring position, and number the intermediate height division points along the z axis.

[0041] Weight the slip height according to the leg circumference data corresponding to the height division points to obtain the second pressure label; the calculation formula for the second pressure label is:

[0042] ;

[0043] wherein, represents the second pressure label; represents the number of height division points; represents the height division point The leg circumference data; Indicating the height division point The height data; Indicating the height threshold.

[0044] In the data processing module, the calculation formula for the drawstring pressure label is:

[0045] ;

[0046] Among them, Indicates the drawstring pressure label; Indicates the first pressure label; Indicates the first pressure weight; Indicates the second pressure label; Indicates the second pressure weight.

[0047] The process of identifying the historical motion data of the target person according to the drawstring pressure prediction model is:

[0048] Obtain the historical motion data of the target person, identify the historical motion data, and obtain the historical motion process data;

[0049] The historical motion process data includes historical motion duration, historical motion mileage, historical motion temperature, historical motion humidity, and historical motion intensity;

[0050] Identify the historical motion process data according to the drawstring pressure prediction model to obtain the optimal drawstring pressure data.

[0051] A sock design and weaving integration method includes:

[0052] S10. Obtain the parameter information of the socks, including sock design data and drawstring pressure data; adjust the drawstring pressure data to produce test samples; select test personnel to wear the test samples for motion testing to obtain a test data set; the test data set includes test personnel leg shape data, motion process data, drawstring indentation data, drawstring slippage data, and drawstring pressure data; the motion process data includes motion duration, motion mileage, motion temperature, motion humidity, and motion intensity; construct a test database according to the test data set;

[0053] S20. Obtain the target person's leg shape data and historical motion data; obtain the leg shape similarity according to the target person's leg shape data and the test personnel's leg shape data; screen the test database according to the leg shape similarity to obtain a reference data set;

[0054] S30. Obtain the drawstring indentation data and drawstring slippage data in the reference dataset; obtain the first pressure label according to the drawstring indentation data, and obtain the second pressure label according to the drawstring slippage data; calculate the drawstring pressure label based on the first pressure label and the second pressure label;

[0055] S40. Perform model training based on the motion process data, drawstring pressure data, and drawstring pressure label in the reference dataset, and use the corresponding leg shape similarity as the data weight to obtain the drawstring pressure prediction model;

[0056] S50. Identify the historical motion data of the target person according to the drawstring pressure prediction model to obtain the optimal drawstring pressure data for differential production.

[0057] The calculation formula for calculating the drawstring pressure label based on the first pressure label and the second pressure label is:

[0058] ;

[0059] where, represents the drawstring pressure label; represents the first pressure label; represents the first pressure weight; represents the second pressure label; represents the second pressure weight.

[0060] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0061] 1. The present invention identifies the motion process data of the test person to obtain the motion duration, motion mileage, motion temperature, motion humidity, and motion intensity; among them, the motion intensity is measured according to the heart rate data, vibration frequency data, and electromyogram signal data of the test person during the motion test; through the motion duration, motion mileage, motion temperature, motion humidity, and motion intensity, the motion process of the test person can be accurately identified.

[0062] 2. The present invention obtains the drawstring indentation volume and drawstring contact area of the test person during the motion test, and then calculates the average indentation depth according to the drawstring indentation volume and drawstring contact area; according to the average indentation depth and the indentation threshold, it can accurately measure whether the drawstring pressure of the test sample is too large.

[0063] 3. The present invention obtains the drawstring slippage data according to the horizontal plane where the initial drawstring position and the slipped drawstring position are located, constructs a three-dimensional coordinate system for the drawstring slippage data, and obtains the corresponding relationship between the height of the drawstring slippage data and the leg circumference data; then, according to the extreme points of the leg circumference data, the initial drawstring position, and the slipped drawstring position, the height division points are obtained; the slipped height is weighted according to the leg circumference data corresponding to the height division points, and it can accurately measure whether the drawstring pressure of the test sample is too small.

[0064] 4. The present invention obtains a drawstring pressure label based on the first pressure label and the second pressure label, trains a model according to the motion process data, the drawstring pressure data and the drawstring pressure label, and uses the corresponding leg shape similarity as a data weight to obtain a drawstring pressure prediction model; then, the historical motion data of the target person is identified through the drawstring pressure prediction model, and the optimal drawstring pressure data can be accurately obtained according to the foot shape data and the historical motion data of the target person. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 It is a schematic structural diagram of an integrated sock design and weaving system of the present invention;

[0066] Figure 2 It is a schematic flow diagram of an integrated sock design and weaving method of the present invention;

[0067] Figure 3 It is a schematic diagram of a scenario for height division of the drawstring slippage data of the present invention.

[0068] In the figure: 11, the horizontal plane of the initial drawstring position; 12, the horizontal plane of the extreme leg circumference; 13, the horizontal plane of the slipped drawstring position; a, the first height division point; b, the second height division point; c, the third height division point. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0069] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0070] Embodiment 1

[0071] The present invention proposes an integrated sock design and weaving system, the structure of which is as Figure 1 shown, including: a database construction module, an information matching module, a data processing module, a model construction module, and a pressure prediction module.

[0072] The database construction module obtains the parameter information of the socks, including sock design data and drawstring pressure data; produces test samples by adjusting the drawstring pressure data; selects test personnel to wear the test samples for motion tests to obtain a test data set; the test data set includes test personnel leg shape data, motion process data, drawstring mark data, drawstring slippage data, and drawstring pressure data; the motion process data includes motion duration, motion mileage, motion temperature, motion humidity, and motion intensity; a test database is constructed according to the test data set.

[0073] The sock design data includes three - dimensional structure data, material composition data, and knitting data. The three - dimensional structure data includes the foot length data, foot circumference data, sock height, etc. of the sock; the material composition data includes the fiber materials used in each part of the sock; the knitting data includes the knitting method and knitting density of each part of the sock, and the knitting density refers to the number of yarns per unit area.

[0074] Take the pressure data at the sock cuff when worn as the cuff pressure data. The acquisition process of the cuff pressure data is as follows:

[0075] Determine a standard mold according to the sock design data; wear different test samples on the standard mold, and set pressure sensors on the contact surface between the sock cuff of the test sample and the standard mold; take the pressure data measured by the pressure sensor as the cuff pressure data of the test sample.

[0076] The present invention determines a standard mold through the sock design data, and then measures the pressure on the contact surface of the sock cuff of the sock test sample when worn through the standard mold to obtain the pressure data of the cuff, and takes the pressure data as the cuff pressure data of the test sample, which can accurately measure the cuff pressure of the test sample.

[0077] The sports process data includes exercise duration, exercise mileage, exercise temperature, exercise humidity, and exercise intensity;

[0078] Among them, the exercise duration represents the duration of the test person wearing the test sample for exercise testing; the exercise mileage represents the total moving mileage of the test person during the exercise duration; the exercise temperature is the temperature data of the area where the sock is worn by the test person during the exercise test; the exercise humidity is the humidity data of the area where the sock is worn by the test person during the exercise test; during the strenuous exercise of the exercise person, due to the increase in body temperature and the discharge of sweat, the temperature and humidity of the sock will change. On the one hand, the changes in temperature and humidity will affect the properties such as the softness of the material at the sock cuff, affecting the cuff pressure; on the other hand, the changes in the temperature and humidity of the sock will cause changes in the overall weight of the sock.

[0079] The exercise intensity is used to reflect the intensity of the test person's exercise during the exercise test, and is calculated based on the heart rate data, vibration frequency data, and electromyogram signal data of the test person; the vibration frequency data refers to the body vibration frequency data of the exercise person during exercise, which is monitored by a vibration frequency sensor; the electromyogram signal data refers to the electromyogram signal generated by the muscle contraction and relaxation work of the exercise person during exercise, which is identified by an electromyogram signal detection device;

[0080] The calculation formula for exercise intensity is:

[0081] ;

[0082] Among them, represents the exercise intensity; represents the heart rate weight; represents the average heart rate data, represents the heart rate threshold; represents the vibration frequency weight; represents the average vibration frequency data; represents the vibration frequency threshold; represents the electromyogram weight; represents the average electromyogram data; represents the electromyogram threshold.

[0083] Among them, the heart rate threshold, the vibration frequency threshold, and the electromyogram threshold are obtained by taking the average value according to the data of the tester; the heart rate weight, the vibration frequency weight, and the electromyogram weight are obtained according to the importance of the average heart rate data, the average vibration frequency data, and the average electromyogram data.

[0084] The present invention identifies the exercise process data of the tester to obtain the exercise duration, exercise mileage, exercise temperature, exercise humidity, and exercise intensity; among them, the exercise intensity is measured according to the heart rate data, vibration frequency data, and electromyogram signal data of the tester during the exercise test; through the exercise duration, exercise mileage, exercise temperature, exercise humidity, and exercise intensity, the exercise process of the tester can be accurately identified.

[0085] The information matching module obtains the leg type data and historical exercise data of the target person; obtains the leg type similarity according to the leg type data of the target person and the leg type data of the tester; screens the test database according to the leg type similarity to obtain the reference data set.

[0086] The process of obtaining and comparing the leg type data of the tester and the target person is as follows: scan the legs of the tester wearing the test sample in the standing state to obtain the three-dimensional data of the legs within the range wrapped by the test sample as the leg type data of the tester; obtain the height of the leg type data of the tester, and identify the legs of the target person according to the height of the leg type data of the tester to obtain the leg type data of the target person; the height of the leg type data of the tester is the same as the height of the socks; obtain the leg type similarity according to the data similarity between the leg type data of the target person and the leg type data of the tester; obtain the similarity threshold, and when the leg type similarity is greater than the similarity threshold, select the test data of the tester as the reference data.

[0087] The present invention scans the three-dimensional data of the legs within the range of the test sample wrapping to obtain the leg shape data of the tester; then, based on the height of the leg shape data of the tester, the legs of the target person are identified to obtain the leg shape data of the target person; the leg shape similarity is obtained according to the data similarity between the leg shape data of the target person and the leg shape data of the tester; accurately screening the testers with leg shapes similar to those of the target person ensures the accuracy of the reference data set.

[0088] The data processing module acquires the drawstring indentation data and drawstring slippage data in the reference data set; obtains the first pressure label according to the drawstring indentation data and the second pressure label according to the drawstring slippage data; calculates and obtains the drawstring pressure label according to the first pressure label and the second pressure label.

[0089] The process of obtaining the first pressure label is as follows:

[0090] Acquire the drawstring indentation data, where the drawstring indentation data includes the drawstring indentation volume and the drawstring contact area;

[0091] The drawstring indentation volume is the volume of the skin depression of the tester at the drawstring of the test sample after the movement test; the drawstring contact area is the contact area between the drawstring of the test sample and the skin of the tester;

[0092] Calculate the average indentation depth according to the drawstring indentation volume and the drawstring contact area, and calculate the first pressure label according to the average indentation depth; the calculation formula for the first pressure label is:

[0093] ;

[0094] Among them, represents the first pressure label; represents the drawstring indentation volume; represents the drawstring contact area; represents the indentation threshold. The indentation threshold is obtained according to the average indentation depth of the tester.

[0095] The present invention acquires the drawstring indentation volume and the drawstring contact area of the tester during the movement test, and then calculates the average indentation depth according to the drawstring indentation volume and the drawstring contact area; accurately measures whether the drawstring pressure of the test sample is too large according to the average indentation depth and the indentation threshold.

[0096] The process of obtaining the second pressure label is as follows:

[0097] Acquire the position of the drawstring of the test sample on the leg of the tester at the start of the movement test as the initial drawstring position; acquire the position of the drawstring of the test sample on the leg of the tester at the end of the movement test as the slipped drawstring position;

[0098] Take the horizontal plane where the initial drawstring position is located as the initial drawstring position horizontal plane, and take the horizontal plane where the slipping drawstring position is located as the slipping drawstring position horizontal plane; obtain the drawstring slipping data according to the tester's leg shape data between the initial drawstring position horizontal plane and the slipping drawstring position horizontal plane;

[0099] Take the slipping drawstring position horizontal plane as the xy plane, and take the perpendicular line between the initial drawstring position horizontal plane and the slipping drawstring position horizontal plane as the z axis, construct a three-dimensional coordinate system for the drawstring slipping data, and obtain the corresponding relationship between the height of the drawstring slipping data and the leg circumference data; the leg circumference data is the cross-sectional circumference data of the drawstring slipping data in the horizontal planes at different heights;

[0100] According to the extreme points of the leg circumference data, determine the leg circumference extreme horizontal plane and its corresponding height data, and obtain the height division points;

[0101] Obtain the first height division point according to the height of the initial drawstring position, obtain the last height division point according to the height of the slipping drawstring position, and number the intermediate height division points along the z axis;

[0102] Weight the slipping height according to the leg circumference data corresponding to the height division points to obtain the second pressure label; the calculation formula of the second pressure label is:

[0103] ;

[0104] Wherein, represents the second pressure label; represents the number of height division points; represents the height division point of the leg circumference data; represents the height division point of the height data; represents the height threshold. The height threshold is obtained according to the average value of the sock slipping height of the tester.

[0105] The present invention obtains the drawstring slipping data according to the horizontal planes where the initial drawstring position and the slipping drawstring position are located, constructs a three-dimensional coordinate system for the drawstring slipping data, and obtains the corresponding relationship between the height of the drawstring slipping data and the leg circumference data; then obtains the height division points according to the extreme points of the leg circumference data, the initial drawstring position and the slipping drawstring position; weights the slipping height according to the leg circumference data corresponding to the height division points, and accurately measures whether the drawstring pressure of the test sample is too small.

[0106] In the data processing module, the formula for calculating the drawstring pressure label is:

[0107] ;

[0108] Wherein, Indicates the drawstring pressure label; Indicates the first pressure label; Indicates the first pressure weight; Indicates the second pressure label; Indicates the second pressure weight; the first pressure weight and the second pressure weight are determined according to the severity of the negative impacts of excessive and insufficient drawstring pressures.

[0109] In the present invention, the first pressure label and the second pressure label are subtracted in terms of weights to obtain the drawstring pressure label; when the drawstring pressure label is greater than 0, it indicates that the drawstring pressure of the test sample is relatively large, and when the drawstring pressure label is less than 0, it indicates that the drawstring pressure of the test sample is relatively small; accurately measure the drawstring pressure of the test sample.

[0110] The model construction module trains a model based on the motion process data, drawstring pressure data, and drawstring pressure label in the reference dataset, and uses the corresponding leg shape similarity as the data weight to obtain the drawstring pressure prediction model.

[0111] The drawstring pressure prediction model is constructed based on a deep neural network, and its training process is as follows:

[0112] Obtain an initialized drawstring pressure prediction model;

[0113] Obtain the motion process data, drawstring pressure data, leg shape similarity in the reference dataset, and the drawstring pressure label calculated based on the drawstring mark data and drawstring slippage data;

[0114] Use the drawstring pressure label as the data label to train the motion process data and drawstring pressure data, and use the corresponding leg shape similarity as the data weight to optimize the parameters of the model to obtain the drawstring pressure prediction model. The higher the leg shape similarity, the higher the importance of the test data, and the greater its impact on the parameters and recognition results.

[0115] The pressure prediction module identifies the historical motion data of the target person according to the drawstring pressure prediction model to obtain the optimal drawstring pressure data for differential production.

[0116] The process of identifying the historical motion data of the target person according to the drawstring pressure prediction model is as follows: Obtain the historical motion data of the target person, identify the historical motion data to obtain the historical motion process data; the historical motion process data includes historical motion duration, historical motion mileage, historical motion temperature, historical motion humidity, and historical motion intensity;

[0117] Identify the historical motion process data according to the drawstring pressure prediction model to obtain the optimal drawstring pressure data.

[0118] The present invention trains a model based on the motion process data, the mouth-binding pressure data, and the mouth-binding pressure label in the obtained reference data, and uses the corresponding leg type similarity as the data weight to obtain a mouth-binding pressure prediction model; then, the historical motion data of the target person is identified through the mouth-binding pressure prediction model, and the optimal mouth-binding pressure data can be accurately obtained.

[0119] The present invention also proposes a method for integrated sock design and weaving, and its process is as Figure 2 shown, including:

[0120] S10. Obtain the parameter information of the socks, including the sock design data and the mouth-binding pressure data; adjust the mouth-binding pressure data to produce test samples; select test personnel to wear the test samples for motion tests to obtain a test data set; the test data set includes the leg type data, motion process data, mouth-binding mark data, mouth-binding slipping data, and mouth-binding pressure data of the test personnel; the motion process data includes the motion duration, motion mileage, motion temperature, motion humidity, and motion intensity; construct a test database according to the test data set;

[0121] S20. Obtain the leg type data and historical motion data of the target person; obtain the leg type similarity according to the leg type data of the target person and the leg type data of the test personnel; screen the test database according to the leg type similarity to obtain a reference data set;

[0122] S30. Obtain the mouth-binding mark data and mouth-binding slipping data in the reference data set; obtain the first pressure label according to the mouth-binding mark data, and obtain the second pressure label according to the mouth-binding slipping data; calculate the mouth-binding pressure label according to the first pressure label and the second pressure label;

[0123] S40. Train a model according to the motion process data, the mouth-binding pressure data, and the mouth-binding pressure label in the reference data set, and use the corresponding leg type similarity as the data weight to obtain a mouth-binding pressure prediction model;

[0124] S50. Identify the historical motion data of the target person through the mouth-binding pressure prediction model to obtain the optimal mouth-binding pressure data for differential production.

[0125] The present invention produces test samples by adjusting the pressure data of the sock mouth; selects testers to wear the test samples for sports tests to obtain a test data set, and constructs a test database; screens the test database to obtain a reference data set according to the leg shape similarity between the leg shape data of the target person and the leg shape data of the tester; calculates the sock mouth pressure label according to the sock mouth indentation data and the sock mouth slippage data in the reference data set; performs model training according to the motion process data, the sock mouth pressure data, and the sock mouth pressure label, and uses the corresponding leg shape similarity as the data weight to obtain a sock mouth pressure prediction model; identifies the historical motion data of the target person according to the sock mouth pressure prediction model to obtain the optimal sock mouth pressure data; and accurately designs and produces the difference in the sock mouth pressure of the target person through the foot shape data and the motion process data.

[0126] Embodiment 2

[0127] Sock manufacturing factory F mainly engages in the design and production of football sports socks. Football socks are a type of sports socks specially designed for football sports, with functions such as support, protection, comfort, and anti-slip, which can effectively reduce sports injuries during football sports and enhance the sports performance of athletes. Due to the long sports time and intense sports in football, the sports socks often slip, affecting the sports experience of athletes. It is necessary to adjust the sock mouth of the football sports socks to ensure that the sock mouth can provide appropriate pressure and make the football sports socks fit firmly on the ankles and calves.

[0128] In order to improve the production service level of football sports socks, sock manufacturing factory F adopts a sock product design and weaving integration system described in the present invention to provide customers with differentiated sock mouth design and production services for football sports socks;

[0129] The structure of the sock product design and weaving integration system is as Figure 1 shown, including: a database construction module, an information matching module, a data processing module, a model construction module, and a pressure prediction module.

[0130] The database construction module obtains the parameter information of the socks, including sock design data and sock mouth pressure data; produces test samples by adjusting the sock mouth pressure data; selects testers to wear the test samples for sports tests to obtain a test data set; the test data set includes tester leg shape data, motion process data, sock mouth indentation data, sock mouth slippage data, and sock mouth pressure data; the motion process data includes motion duration, motion mileage, motion temperature, motion humidity, and motion intensity; a test database is constructed according to the test data set.

[0131] Taking the pressure data of the sock mouth when wearing as the sock mouth pressure data, the acquisition process of the sock mouth pressure data is:

[0132] Determine the standard mold according to the sock design data; wear test samples with different cuff pressure data on the standard mold, and set pressure sensors on the contact surface between the cuff of the test sample and the standard mold; use the pressure data measured by the pressure sensor as the cuff pressure data of the test sample.

[0133] The pressure of the sports sock cuff on the leg generally varies with the design, material, and tightness of the sock, and is usually described using the pressure unit of millimeters of mercury (mmHg); the pressure of the sports sock cuff is usually between 10-30 mmHg.

[0134] Sock manufacturer F selects its best-selling football sports sock product P as the test object to construct a test database; adjusts the production of the cuff pressure data of product P to obtain test samples, and measures the cuff pressure of the test samples according to the standard mold. The cuff pressure data of some test samples are shown in Table 1.

[0135] Table 1 Cuff pressure data table of football sports socks

[0136]

[0137] Select test personnel to conduct sports tests on wearing test samples to obtain a test data set; the test data set includes test personnel's leg shape data, exercise process data, cuff indentation data, cuff slippage data, and cuff pressure data; the exercise process data includes exercise duration, exercise mileage, exercise temperature, exercise humidity, and exercise intensity;

[0138] The exercise duration represents the duration of the test personnel wearing the test sample for sports tests; the exercise mileage represents the total moving mileage of the test personnel during the exercise duration; the exercise temperature is the temperature data of the area where the socks are worn during the test personnel's sports tests; the exercise humidity is the humidity data of the area where the socks are worn during the test personnel's sports tests;

[0139] The exercise intensity is used to reflect the intensity of the test personnel's exercise during the sports test, and is calculated based on the test personnel's heart rate data, vibration frequency data, and electromyogram signal data; the calculation formula is:

[0140] ;

[0141] Among them, represents the exercise intensity; represents the heart rate weight; represents the average heart rate data, represents the heart rate threshold; represents the vibration frequency weight; represents the average vibration frequency data; represents the vibration frequency threshold; represents the electromyogram weight; represents the average electromyogram data; represents the electromyogram threshold.

[0142] Collect the test data of the football sports sock product P. Part of the sports process data is shown in Table 2, where the maximum values of the sports temperature and sports humidity are selected.

[0143] Table 2 Sports process data table of the test personnel

[0144]

[0145] The information matching module obtains the leg type data and historical sports data of the target person; obtains the leg type similarity according to the leg type data of the target person and the leg type data of the test personnel; screens the test database according to the leg type similarity to obtain the reference data set.

[0146] The process of obtaining and comparing the leg type data of the test personnel and the target person is as follows:

[0147] Scan the legs of the test personnel wearing the test sample in the standing state to obtain the three-dimensional data of the legs within the range wrapped by the test sample as the leg type data of the test personnel;

[0148] Obtain the height of the leg type data of the test personnel, identify the legs of the target person according to the height of the leg type data of the test personnel to obtain the leg type data of the target person; the height of the leg type data of the test personnel is the same as the height of the socks;

[0149] Obtain the leg type similarity according to the data similarity between the leg type data of the target person and the leg type data of the test personnel;

[0150] Obtain the similarity threshold. When the leg type similarity is greater than the similarity threshold, select the test data of the test personnel as the reference data.

[0151] After receiving the differential order from the customer, the sock weaving factory F takes the customer as the target person and obtains the leg type data and historical sports data of the target person; compares the leg type data of the target person with the leg type data of the test personnel, obtains the leg type similarity according to the data similarity, and judges the test personnel with successful matching according to the leg type similarity.

[0152] The sock weaving factory F sets the leg type similarity threshold to 0.8. When the leg type similarity between the test personnel and the target person is greater than 0.8, it is determined that the test personnel are successfully matched. The leg type similarity data of some test personnel and the target person are shown in Table 3.

[0153] Table 3 Leg type similarity data table of the test personnel and the target person

[0154]

[0155] According to the data in Table 3, it can be obtained that the leg shape similarity between tester C and the target person is not greater than 0.8, and the matching is unsuccessful. The leg shape similarity between the remaining testers and the target person is greater than 0.8, and the matching is successful. The test data of the testers with successful matching is retrieved from the test database to obtain the reference dataset.

[0156] The data processing module obtains the drawstring indentation data and drawstring slippage data in the reference dataset; obtains the first pressure label according to the drawstring indentation data, and obtains the second pressure label according to the drawstring slippage data; calculates and obtains the drawstring pressure label according to the first pressure label and the second pressure label.

[0157] The process of obtaining the first pressure label is as follows:

[0158] Obtain the drawstring indentation data, where the drawstring indentation data includes the drawstring indentation volume and the drawstring contact area;

[0159] The drawstring indentation volume is the volume of the skin depression of the tester at the drawstring of the test sample after the movement test; the drawstring contact area is the contact area between the drawstring of the test sample and the tester's skin;

[0160] Calculate the average indentation depth according to the drawstring indentation volume and the drawstring contact area, and calculate the first pressure label according to the average indentation depth; the calculation formula of the first pressure label is:

[0161] ;

[0162] where represents the first pressure label; represents the drawstring indentation volume; represents the drawstring contact area; represents the indentation threshold.

[0163] After the movement test, obtain the drawstring contact area according to the leg circumference data and the drawstring height of the tester; obtain the drawstring indentation volume through 3D scanning technology; obtain the drawstring indentation volume and the drawstring contact area of all testers of the same test sample to obtain the average drawstring indentation volume and the average drawstring contact area; the drawstring indentation data of the testers is shown in Table 4.

[0164] Table 4 Drawstring Indentation Data Table of Testers

[0165]

[0166] Calculate the average indentation depth according to the average drawstring indentation volume and the average drawstring contact area in Table 4.

[0167] The process of obtaining the second pressure label is as follows: Obtain the position of the mouth of the test sample on the leg of the tester at the start of the exercise test as the initial mouth position; obtain the position of the mouth of the test sample on the leg of the tester at the end of the exercise test as the slipping mouth position.

[0168] Take the horizontal plane where the initial mouth position is located as the initial mouth position horizontal plane, and take the horizontal plane where the slipping mouth position is located as the slipping mouth position horizontal plane; obtain the mouth slipping data according to the leg shape data of the tester between the initial mouth position horizontal plane and the slipping mouth position horizontal plane.

[0169] Take the slipping mouth position horizontal plane as the xy plane, and take the perpendicular line between the initial mouth position horizontal plane and the slipping mouth position horizontal plane as the z axis, construct a three-dimensional coordinate system for the mouth slipping data, and obtain the corresponding relationship between the height of the mouth slipping data and the leg circumference data; the leg circumference data is the cross-sectional circumference data of the mouth slipping data in horizontal planes at different heights.

[0170] According to the extreme points of the leg circumference data, determine the leg circumference extreme horizontal plane and its corresponding height data to obtain the height division points.

[0171] Obtain the first height division point according to the height of the initial mouth position, obtain the last height division point according to the height of the slipping mouth position, and number the intermediate height division points along the z axis.

[0172] Weight the slipping height according to the leg circumference data corresponding to the height division points to obtain the second pressure label; the calculation formula of the second pressure label is:

[0173] ;

[0174] Among them, represents the second pressure label; represents the number of height division points; represents the height division point 's leg circumference data; represents the height division point 's height data; represents the height threshold.

[0175] The scenario of height division for the mouth slipping data of the tester of the football sports sock product P is as Figure 3 shown; in the figure, 11 represents the initial mouth position horizontal plane; 12 is the leg circumference extreme horizontal plane; 13 represents the slipping mouth position horizontal plane; a is the first height division point; b is the second height division point; c is the third height division point.

[0176] Among them, the horizontal plane of the initial drawstring position, the horizontal plane of the slipping drawstring position, and the horizontal plane of the leg circumference extreme value are parallel to each other; the horizontal plane of the leg circumference extreme value is the horizontal plane of the maximum leg circumference. The leg circumference data between the horizontal plane of the initial drawstring position and the horizontal plane of the leg circumference extreme value gradually increases, and the leg circumference data between the horizontal plane of the leg circumference extreme value and the horizontal plane of the slipping position gradually decreases.

[0177] Determine the first height division point according to the height of the initial drawstring position, and the first height division point is located within the horizontal plane of the initial drawstring position; determine the second height division point according to the height of the horizontal plane of the leg circumference extreme value, and the second height division point is located within the horizontal plane of the leg circumference extreme value; determine the third height division point according to the height of the slipping drawstring position, and the third height division point is located within the horizontal plane of the slipping drawstring position.

[0178] Collect and organize the height data and leg circumference data of the height division points to obtain the distribution data of the height division points as shown in Table 5.

[0179] Table 5 Distribution Data Table of Height Division Points

[0180]

[0181] The process of the football sports sock slipping from the initial drawstring position to the slipping drawstring position includes two stages, namely from the first height division point to the second height division point, and from the second height division point to the third height division point; in the process of slipping from the first height division point to the second height division point, since the leg circumference data gradually increases, the slipping difficulty of the sock drawstring is greater than that in the case of a fixed leg circumference. Therefore, a weight greater than 1 is assigned to the slipping height to increase its influence in the measurement of the second pressure label; in the process from the second height division point to the third height division point, since the leg circumference data gradually decreases, the slipping difficulty of the sock drawstring is smaller than that in the case of a fixed leg circumference. Therefore, a weight less than 1 is assigned to the slipping height to reduce its influence in the measurement of the second pressure label; through the setting of the weight, the second pressure label can be measured more accurately.

[0182] In the data processing module, the formula for measuring the drawstring pressure label is:

[0183] ;

[0184] Among them, represents the drawstring pressure label; represents the first pressure label; represents the first pressure weight; represents the second pressure label; represents the second pressure weight.

[0185] The model construction module trains a model based on the motion process data, drawstring pressure data, and drawstring pressure labels in the reference dataset, and uses the corresponding leg type similarity as the data weight to obtain the drawstring pressure prediction model.

[0186] The drawstring pressure prediction model is constructed based on a deep neural network, and its training process is as follows:

[0187] Obtain an initialized drawstring pressure prediction model;

[0188] Obtain the motion process data, drawstring pressure data, leg type similarity in the reference dataset, and the drawstring pressure labels calculated based on the drawstring mark data and drawstring slipping data;

[0189] Use the drawstring pressure labels as data labels to train the motion process data and drawstring pressure data, and use the corresponding leg type similarity as the data weight to optimize the model parameters to obtain the drawstring pressure prediction model.

[0190] The pressure prediction module identifies the historical motion data of the target person according to the drawstring pressure prediction model to obtain the optimal drawstring pressure data for differential production.

[0191] The process of identifying the historical motion data of the target person according to the drawstring pressure prediction model is as follows:

[0192] Obtain the historical motion data of the target person, identify the historical motion data to obtain the historical motion process data;

[0193] The historical motion process data includes historical motion duration, historical motion mileage, historical motion temperature, historical motion humidity, and historical motion intensity;

[0194] Identify the historical motion process data according to the drawstring pressure prediction model to obtain the optimal drawstring pressure data.

[0195] The present invention trains a model based on the motion process data, drawstring pressure data, and drawstring pressure labels in the obtained reference data, and uses the corresponding leg type similarity as the data weight to obtain the drawstring pressure prediction model; then, by identifying the historical motion data of the target person through the drawstring pressure prediction model, the optimal drawstring pressure data can be accurately obtained; according to the optimal drawstring pressure data, differential design and production of the drawstring of the football sock product can be carried out, which can effectively guarantee the sports experience of athletes.

[0196] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A socks design and weaving integrated system, characterized in that: include: A database construction module is used to obtain parameter information of socks, including sock design data and cuff pressure data; By adjusting the tie mouth pressure data, the test sample is produced; A test person wearing a test sample is selected to perform a sports test to obtain a test data set; the test data set includes the test person's leg shape data, sports process data, cuff mark data, cuff slip data, and cuff pressure data; the sports process data includes sports duration, sports mileage, sports temperature, sports humidity, and sports intensity; a test database is constructed based on the test data set; The information matching module obtains the leg shape data and historical movement data of the target person; obtains the leg shape similarity based on the leg shape data of the target person and the leg shape data of the test person; and screens the test database based on the leg shape similarity to obtain a reference data set; A data processing module is used to obtain the cuff mark data and cuff slippage data in the reference data set; A first pressure label is obtained according to the cuff mark data, and a second pressure label is obtained according to the cuff slippage data; and a cuff pressure label is obtained by measuring the first pressure label and the second pressure label; The process of obtaining the first pressure tag is as follows: Acquiring cuff mark data, wherein the cuff mark data includes cuff mark volume and cuff contact area; The drawstring mark volume is the volume of the tester's skin depression at the drawstring of the test sample after the exercise test is completed; the drawstring contact area is the contact area between the drawstring of the test sample and the tester's skin; The average mark depth is calculated based on the volume of the mark at the cuff and the contact area of ​​the cuff, and the first pressure label is calculated based on the average mark depth; the calculation formula of the first pressure label is: in, Indicates the first pressure label; Indicates the volume of the cuff mark; Indicates the contact area of ​​the beam; Indicates the strangulation mark threshold; The process of obtaining the second pressure tag is as follows: The position of the test sample drawstring on the test person's leg at the beginning of the motion test is obtained as the initial drawstring position; the position of the test sample drawstring on the test person's leg at the end of the motion test is obtained as the sliding drawstring position; The horizontal plane at the initial drawstring position is used as the initial drawstring position horizontal plane, and the horizontal plane at the slide-off drawstring position is used as the slide-off drawstring position horizontal plane; the drawstring slide-off data is obtained according to the leg shape data of the tester between the initial drawstring position horizontal plane and the slide-off drawstring position horizontal plane; Taking the horizontal plane of the drawstring position as the xy plane, and the vertical line between the horizontal plane of the initial drawstring position and the horizontal plane of the drawstring position as the z axis, a three-dimensional coordinate system is constructed for the drawstring sliding data to obtain the corresponding relationship between the height of the drawstring sliding data and the leg circumference data; the leg circumference data is the section perimeter data of the drawstring sliding data in the horizontal plane at different heights; According to the extreme value points of the leg circumference data, the leg circumference extreme value horizontal plane and its corresponding height data are determined to obtain the height division point; The first height division point is obtained according to the height of the initial drawstring position, the final height division point is obtained according to the height of the sliding drawstring position, and the intermediate height division points are numbered along the z-axis; The sliding height is weighted according to the leg circumference data corresponding to the height division point to obtain a second pressure label; the calculation formula of the second pressure label is: in, Indicates the second pressure label; Indicates the number of height division points; Indicates the height division point Leg circumference data; Indicates the height division point Height data; Indicates the height threshold; The model building module trains the model based on the motion process data, cuff pressure data and cuff pressure labels in the reference data set, and uses the corresponding leg shape similarity as the data weight to obtain the cuff pressure prediction model; The pressure prediction module identifies the historical movement data of the target person according to the cuff pressure prediction model, obtains the optimal cuff pressure data, and performs differentiated production.

2. The socks design and weaving integrated system according to claim 1, characterized in that: The pressure data of the crotch of the socks when worn is used as the crotch pressure data, and the process of obtaining the crotch pressure data is as follows: Determine the standard mold according to the sock design data; Different test samples are put on the standard mold, and a pressure sensor is set on the contact surface between the test sample's cuff and the standard mold; the pressure data measured by the pressure sensor is used as the cuff pressure data of the test sample.

3. The socks design and weaving integrated system according to claim 1, characterized in that: The exercise duration refers to the duration that the tester wears the test sample to perform the exercise test; The exercise mileage refers to the total mileage moved by the tester during the exercise time; The sports temperature refers to the temperature data of the area where the tester wears socks during the sports test; The sports humidity refers to the humidity data of the area where the tester wears socks during the sports test; The exercise intensity is used to reflect the intensity of the tester's exercise during the exercise test, and is calculated based on the tester's heart rate data, vibration frequency data, and electromyographic signal data; the calculation formula is: in, Indicates the intensity of exercise; represents the heart rate weight; Indicates average heart rate data, Indicates the heart rate threshold; Indicates the frequency weight; Indicates average frequency data; Indicates the frequency threshold; represents the myoelectric weight; represents the average EMG data; Represents the electromyographic threshold.

4. The socks design and weaving integrated system according to claim 1, characterized in that: The process of obtaining and comparing the leg shape data of the tester and the target person is as follows: Scan the legs of the tester who is standing and wearing the test sample to obtain the three-dimensional data of the legs within the scope of the test sample as the leg shape data of the tester; The height of the tester's leg shape data is obtained, and the legs of the target person are identified according to the height of the tester's leg shape data to obtain the target person's leg shape data; the height of the tester's leg shape data is consistent with the height of the socks; The leg shape similarity is obtained according to the data similarity between the leg shape data of the target person and the leg shape data of the test person; A similarity threshold is obtained, and when the leg shape similarity is greater than the similarity threshold, the test data of the tester is selected as reference data.

5. The socks design and weaving integrated system according to claim 1, characterized in that: In the data processing module, the calculation formula of the tie pressure label is: in, Indicates the label of the drawstring pressure; Indicates the first pressure label; represents the first pressure weight; Indicates the second pressure label; Indicates the second pressure weight.

6. The socks design and weaving integrated system according to claim 1, characterized in that: The process of identifying the historical movement data of the target person based on the cuff pressure prediction model is as follows: Obtain the historical movement data of the target person, identify the historical movement data, and obtain the historical movement process data; The historical exercise process data includes historical exercise duration, historical exercise mileage, historical exercise temperature, historical exercise humidity and historical exercise intensity; The historical motion process data is identified according to the crotch pressure prediction model to obtain optimal crotch pressure data.

7. A sock design and weaving integrated method, characterized in that: S10. Obtaining parameter information of the socks, including sock design data and cuff pressure data; and producing a test sample by adjusting the cuff pressure data; A test person wearing a test sample is selected to perform a sports test to obtain a test data set; the test data set includes the test person's leg shape data, sports process data, cuff mark data, cuff slip data, and cuff pressure data; the sports process data includes sports duration, sports mileage, sports temperature, sports humidity, and sports intensity; a test database is constructed based on the test data set; S20. Obtain the target person's leg shape data and historical motion data; obtain the leg shape similarity based on the target person's leg shape data and the test person's leg shape data; filter the test database based on the leg shape similarity to obtain a reference data set; S30. Obtaining the cuff mark data and cuff slip data in the reference data set; A first pressure label is obtained according to the cuff mark data, and a second pressure label is obtained according to the cuff slippage data; and a cuff pressure label is obtained by measuring the first pressure label and the second pressure label; The process of obtaining the first pressure tag is as follows: Acquiring cuff mark data, wherein the cuff mark data includes cuff mark volume and cuff contact area; The drawstring mark volume is the volume of the tester's skin depression at the drawstring of the test sample after the exercise test is completed; the drawstring contact area is the contact area between the drawstring of the test sample and the tester's skin; The average mark depth is calculated based on the volume of the mark at the cuff and the contact area of ​​the cuff, and the first pressure label is calculated based on the average mark depth; the calculation formula of the first pressure label is: in, Indicates the first pressure label; Indicates the volume of the cuff mark; Indicates the contact area of ​​the beam; Indicates the strangulation mark threshold; The process of obtaining the second pressure tag is as follows: The position of the test sample drawstring on the test person's leg at the beginning of the motion test is obtained as the initial drawstring position; the position of the test sample drawstring on the test person's leg at the end of the motion test is obtained as the sliding drawstring position; The horizontal plane at the initial drawstring position is used as the initial drawstring position horizontal plane, and the horizontal plane at the slide-off drawstring position is used as the slide-off drawstring position horizontal plane; the drawstring slide-off data is obtained according to the leg shape data of the tester between the initial drawstring position horizontal plane and the slide-off drawstring position horizontal plane; Taking the horizontal plane of the drawstring position as the xy plane, and the vertical line between the horizontal plane of the initial drawstring position and the horizontal plane of the drawstring position as the z axis, a three-dimensional coordinate system is constructed for the drawstring sliding data to obtain the corresponding relationship between the height of the drawstring sliding data and the leg circumference data; the leg circumference data is the section perimeter data of the drawstring sliding data in the horizontal plane at different heights; According to the extreme value points of the leg circumference data, the leg circumference extreme value horizontal plane and its corresponding height data are determined to obtain the height division point; The first height division point is obtained according to the height of the initial drawstring position, the final height division point is obtained according to the height of the sliding drawstring position, and the intermediate height division points are numbered along the z-axis; The sliding height is weighted according to the leg circumference data corresponding to the height division point to obtain a second pressure label; the calculation formula of the second pressure label is: in, Indicates the second pressure label; Indicates the number of height division points; Indicates the height division point Leg circumference data; Indicates the height division point Height data; Indicates the height threshold; S40. Perform model training based on the motion process data, cuff pressure data and cuff pressure labels in the reference data set, and use the corresponding leg type similarity as the data weight to obtain a cuff pressure prediction model; S50. Identify the historical movement data of the target person according to the cuff pressure prediction model, obtain the optimal cuff pressure data, and perform differentiated production.

8. The method for integrated design and weaving of socks according to claim 7, characterized in that: The calculation formula for calculating the pressure label of the drawstring mouth according to the first pressure label and the second pressure label is: in, Indicates the label of the drawstring pressure; Indicates the first pressure label; represents the first pressure weight; Indicates the second pressure label; Indicates the second pressure weight.

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