A method and system for predicting deformation of textiles that remain unchanged after washing

Abstract

The present invention relates to the technical field of image processing, and provides a deformation prediction method for textiles that are not deformed by washing, comprising the following steps: S1, collecting image data of manufactured textile products through an acquisition module, and processing the image data; S2, collecting tension and twist state data of supplied spinning threads through a state sampling module; S3, acquiring historical deformation data of textile products that have been produced and used by washing through an experimental feedback module; S4, acquiring pre-processed image data, tension and twist state data of spinning threads, and historical deformation data of textile products by washing through a deformation prediction module, and calculating the deformation index Undeformation of the textile products; S5, acquiring the calculated deformation index Undeformation and a monitoring threshold range [range1, range2] set by the system through a feedback control module to determine new production process parameters; S6, adjusting the production process of the textile process according to the new production process parameters through a process adjustment module.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and in particular to a method and system for predicting deformation of textiles that remain unchanged after washing. Background Art

[0002] At present, knitted T-shirts often have curling, warping and deformation of the collar after washing. This not only affects the appearance of the clothes, but also brings inconvenience to users, who need to use an iron to iron them before wearing them every time. In addition, the collar is prone to yellowing after being worn for a long time. These problems seriously affect the user experience and life of knitted T-shirts.

[0003] For example, the Chinese patent CN114526996B discloses a deformation and tear detection device for textile fabrics. Although a specific deformation and tear detection device is provided, the detection results are relatively independent and online dynamic feedback cannot be realized, which is not conducive to the dynamic adjustment of the textile weaving process, resulting in textile products that cannot meet actual needs.

[0004] At the same time, the existing technologies have alleviated the problem of deformation caused by washing to a certain extent through fiber and yarn modification, weaving process improvement and post-treatment process, but they generally have the following limitations:

[0005] 1. Lack of systematic prediction methods: Existing methods mainly focus on post-processing, lack of systematic prediction and prevention methods for textile deformation, and it is difficult to adjust process parameters in real time during the production process.

[0006] 2. Unable to adjust process parameters in real time: Due to the lack of effective prediction models and feedback mechanisms, key parameters such as twist and tension cannot be adjusted in real time according to actual conditions during the production process, resulting in fluctuations in product quality.

[0007] 3. Delayed feedback in textile production: Lack of a systematic experimental data feedback mechanism, which increases production costs and does not meet the needs of sustainable development.

[0008] The present invention is made to solve the common problems in the field, such as insufficient deformation prediction ability, inability to provide feedback, poor real-time adjustment ability, low intelligence, back-end feedback lag, process parameter adjustment lag and poor anti-deformation ability. Summary of the invention

[0009] The purpose of the present invention is to propose a method and system for predicting deformation of textiles that do not deform after washing, in view of the current shortcomings.

[0010] In order to overcome the shortcomings of the prior art, the present invention adopts the following technical solutions:

[0011] A method for predicting deformation of a textile that does not deform after washing, the method comprising the following steps:

[0012] S1. Collecting image data of the manufactured textile product through a collection module and processing the image data;

[0013] S2, collecting the tension and twist state data of the supplied spinning thread through the state sampling module;

[0014] S3, obtaining historical washing deformation data of textile products that have been produced and used through the experimental feedback module;

[0015] S4, obtaining the pre-processed image data, the tension and twist state data of the spinning yarn, and the historical washing deformation data of the textile product through a deformation prediction module, and calculating the undeformation index Undeformation of the textile product;

[0016] S5, obtaining the calculated undeformation index Undeformation and the monitoring threshold range [range1, range2] set by the system through the feedback control module, so as to determine new production process parameters according to the undeformation index Undeformation and the monitoring threshold range [range1, range2] set by the system;

[0017] S6. The process adjustment module adjusts the production process of the textile process according to the new production process parameters.

[0018] Optionally, the deformation prediction method further includes: in step S1, the acquisition module needs to unfold or stretch the textile product during the process of acquiring the image of the textile product.

[0019] Optionally, the deformation prediction method further comprises: in step S2, collecting and storing historical washing deformation data of textile products to form a database;

[0020] Among them, the textile products for which historical washing deformation data are collected cover different batches, different processes and different usage conditions, and the historical washing deformation data of the textile products are measured, wherein the historical washing deformation data include the size change of the textile products, the shape change of the textile products, the curling of the textile products, and the warping index of the textile products, and the historical washing deformation data are transmitted to the experimental data feedback module.

[0021] The present invention also provides a deformation prediction system for textiles that do not deform after washing, the textile deformation prediction system comprising a server, a data acquisition module, a state sampling module, an experimental data feedback module, a deformation prediction module, a feedback control module, and a process adjustment module, wherein the server is respectively connected to the data acquisition module, the state sampling module, the experimental data feedback module, the deformation prediction module, the feedback control module, and the process adjustment module;

[0022] The data acquisition module is used to collect image data of the manufactured textile products, the experimental data feedback module is used for users and managers to feedback the historical water washing deformation data of the manufactured textile products, the deformation prediction module evaluates the non-deformation degree of the textile products according to the image data and the historical water washing deformation data to form an evaluation result, the feedback control module controls the production process parameters of the process adjustment module according to the evaluation result to determine new production process parameters, and the process adjustment module adjusts the production process of the textile process according to the new production process parameters;

[0023] The data acquisition module includes a collection unit, an unfolding unit and a supporting unit, wherein the supporting unit supports the manufactured textile product, the unfolding unit unfolds the manufactured textile product, and the collection unit collects image data of the unfolded textile product;

[0024] Wherein, the unfolding unit and the supporting unit are arranged on a recovery or transfer route of the textile product, and the collecting unit is arranged above the manufactured textile product.

[0025] Optionally, the support unit includes a support plate, an adsorption component and a limiting component, the support plate supports the textile product, the adsorption component adsorbs the textile product, and the limiting component limits the textile product;

[0026] The adsorption component includes an adsorption pump, an adsorption pipe, a lifting rod, a lifting drive mechanism, and an adsorption nozzle, wherein the adsorption pump is connected to the adsorption nozzle through the adsorption pipe, and the adsorption nozzle adsorbs the textile product, one end of the lifting rod is connected to the adsorption pump, and the other end of the lifting rod is driven and connected to the lifting drive mechanism to form a driving part, and the driving part is arranged on the recovery or transfer route of the textile product;

[0027] The adsorption components are symmetrically arranged on the recovery or transfer route of the textile products, and adsorb the textile products from opposite sides of the textile products to achieve support for the textile products.

[0028] Optionally, the unfolding unit includes a toggling member and a telescopic member, the toggling member toggles the textile product, and the telescopic member adjusts the position of the toggling member;

[0029] The unfolding units are symmetrically arranged on both sides of the recycling and delivery route of the textile products, and unfold the textile products from both sides of the recycling and delivery route of the textile products.

[0030] Optionally, the experimental data feedback module includes a feedback unit and a data acquisition unit, the data acquisition unit is used by a manager / operator to record the historical water washing deformation data of the textile product, and the feedback unit transmits the historical water washing deformation data collected by the data acquisition unit to the deformation prediction module;

[0031] Wherein, the data acquisition unit includes a feedback recording terminal and a recording manager, wherein the feedback recording terminal records the historical washing deformation data of the textile product recorded by the manager / operator, and the recording manager records the historical washing deformation data.

[0032] Optionally, the deformation prediction module obtains the preprocessed image data and the historical washing deformation data of the textile product, and calculates the undeformation index Undeformation according to the following:

[0033]

[0034] Where T is the yarn twist, J is the yarn tension, S is the characteristic parameter of the weaving structure, and its value is calculated after image preprocessing, and D is the historical washing deformation data;

[0035] If the undeformation index Undeformation does not fall within the monitoring threshold range [range1, range2] set by the system, the feedback control module is triggered to calculate new production process parameters.

[0036] Optionally, the production process parameters include tension and twist of the textile thread.

[0037] Optionally, the feedback control module obtains the calculated undeformation index Undeformation and the monitoring threshold range [range1, range2] set by the system, and calculates the new yarn twist T according to the following formula: new :

[0038]

[0039] Where, T oldis the original yarn twist, range1 is the lower limit of the monitoring threshold range set by the system, range2 is the upper limit of the monitoring threshold range set by the system, and α is the adjustment coefficient value.

[0040] The beneficial effects achieved by the present invention are:

[0041] 1. Through the cooperation between the deformation prediction module and the feedback control module, the process parameter evaluation capability is more timely, ensuring that the entire system has the advantages of high dynamic feedback timeliness, strong real-time adjustment capability, good process analysis capability and strong anti-deformation ability of textile products;

[0042] 2. Through the mutual cooperation between the process adjustment module and the feedback control module, the real-time adjustment of the process parameters is more efficient, ensuring that the entire system has the advantages of good real-time adjustment capability, high intelligence, high accuracy of process parameter adjustment, strong process capability feedback capability and strong anti-deformation ability of textile products;

[0043] 3. Through the cooperation of the data acquisition module, the experimental data feedback module and the deformation prediction module, the real-time deformation prediction capability of textile products is made more accurate, ensuring that the entire system has the advantages of good real-time feedback effect, accurate deformation prediction capability, timely back-end effect feedback and high intelligence;

[0044] 4. Through the cooperation between the collection unit, the unfolding unit and the supporting unit, the state of the textile products can be evaluated, and the prediction ability and reliability of the entire system for textile products are improved, ensuring that the entire system has the advantages of strong prediction ability and high intelligence;

[0045] 5. Through the cooperation of the process adjustment module and the state sampling module, the tension data and twist data of the spinning line can be collected, which improves the advantages of the whole system with strong control ability of tension and twist process parameters, high control precision and good control effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The present invention can be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily drawn to scale, but the emphasis is placed on illustrating the principles of the embodiments. In different views, the same reference numerals designate the same parts.

[0047] Figure 1 It is a schematic diagram of the flow chart of the textile deformation prediction method of the present invention.

[0048] Figure 2 It is an overall block diagram of the textile deformation prediction system of the present invention.

[0049] Figure 3 It is a partial structural schematic diagram of the data acquisition module of the present invention.

[0050] Figure 4 It is a bottom view schematic diagram of the limiting component of the present invention.

[0051] Figure 5 It is a schematic structural diagram of the support unit, the unfolding unit and the collecting unit of the present invention.

[0052] Explanation of the accompanying reference numerals: 1. Collection probe; 2. Vertical pole; 3. Conveyor plate; 4. Placement slot; 5. Light source; 6. Textile product; 7. Support rod; 8. Positioning seat; 9. Telescopic rod; 10. Auxiliary rod; 11. Toggle rod; 12. Buffer contact pad; 13. Temperature collection probe. DETAILED DESCRIPTION

[0053] The following is an explanation of the embodiments of the present invention through specific embodiments. Those skilled in the art can understand the advantages and effects of the present invention from the contents disclosed in this specification. The present invention can be implemented or applied through other different specific embodiments, and the details in this specification can also be modified and changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. In addition, the drawings of the present invention are only simple schematic illustrations and are not depicted according to actual sizes. It is stated in advance. The following embodiments will further explain the relevant technical contents of the present invention in detail, but the disclosed contents are not intended to limit the scope of protection of the present invention.

[0054] Embodiment 1: According to Figure 1 , Figure 2 , Figure 3 , Figure 4 and Figure 5 As shown, this embodiment provides a method for predicting deformation of a textile that does not deform after washing, and the method for predicting deformation of a textile comprises the following steps:

[0055] S1, collecting image data of the manufactured textile product 6 through a collection module, and processing the image data, wherein the processing includes but is not limited to the following: grayscale and binarization;

[0056] S2, collecting tension and twist state data of the supplied spinning thread through a state sampling module;

[0057] S3, obtaining historical washing deformation data of the textile products 6 that have been produced and used through the experimental feedback module;

[0058] S4, obtaining the pre-processed image data, the tension and twist state data of the spinning yarn, and the historical washing deformation data of the textile product 6 through a deformation prediction module, and calculating the undeformation index Undeformation of the textile product 6;

[0059] S5, obtaining the calculated undeformation index Undeformation and the monitoring threshold range [range1, range2] set by the system through the feedback control module, so as to determine new production process parameters according to the undeformation index Undeformation and the monitoring threshold range [range1, range2] set by the system;

[0060] In this embodiment, the monitoring threshold range [range1, range2] set by the system is set by the manager or operator according to the actual situation, which is related to the nature of the actual production product. Therefore, the monitoring threshold range [range1, range2] set by the system is a technical means well known to those skilled in the art. Those skilled in the art can refer to relevant technical manuals to learn about the technology, so it will not be described one by one in this embodiment;

[0061] S6, the process adjustment module adjusts the production process of the textile process according to the new production process parameters;

[0062] Among them, after the new production process parameters are determined, the new production process parameters are directly transmitted to the textile production line (including the textile device and the yarn supply device), so that the textile production line can respond quickly and adjust the textile parameters in real time;

[0063] In addition, in the present embodiment, the process adjustment module is connected to the equipment control of the textile production line, so that the process adjustment module transmits the new production process parameters to the equipment of the textile production line; at the same time, the equipment of the textile production line is a commonly used equipment of the textile production line, which is a technical means or equipment well known to technicians in the field, so technicians in the field can refer to the relevant technical manuals to learn about the technology, so it is not repeated one by one in the present embodiment;

[0064] Optionally, the deformation prediction method further includes: in the process of the acquisition module acquiring the image of the textile product 6 in step S1, the textile product 6 needs to be unfolded or stretched to expose the weaving structure characteristic parameter S of the textile product 6;

[0065] Optionally, the deformation prediction method further comprises: in step S2, collecting and storing historical washing deformation data of the textile product 6 to form a database;

[0066] The textile products 6 for which historical washing deformation data are collected cover different batches, different processes and different use conditions, and the historical washing deformation data of the textile products 6 are measured, wherein the historical washing deformation data include the size change of the textile products 6, the shape change of the textile products 6, the curling of the textile products 6, and the warping index of the textile products 6, and the historical washing deformation data are transmitted to the experimental data feedback module;

[0067] In this embodiment, twisting treatment is carried out during spinning, and the twisting degree is 350-500, and then the finished line is obtained, and the finished line is dyed. At the same time, after dyeing, a yarn steamer is used to steam the yarn. Water vapor is needed to steam the yarn to make the yarn more colorful and flexible.

[0068] The treated thread will be put on the modified 18-needle weaving machine, and the textile product 6 will be sent to high-temperature washing and degreasing. The high-temperature washing temperature is 110-130 degrees Celsius, and the washing time is 10 minutes. In this embodiment, a total of 2 high-temperature washings are required.

[0069] After washing, the fabric is dried, and the last step is shaping (shaping machine). The steam temperature is 110-130 degrees Celsius and the drying time is 10 minutes.

[0070] The historical washing deformation data collects the size change of the textile product 6 before and after washing, the shape change of the textile product 6, the curling of the textile product 6, and the curling index of the textile product 6.

[0071] In this example, by twisting the yarn and spinning the yarn, the defects of curling, warping and deformation of the textile product 6 are solved, and the textile product 6 has the advantages of no ironing, maintaining the original shape of the textile product 6, and no curling or deformation.

[0072] The present invention also provides a deformation prediction system for textiles that do not deform after washing, the textile deformation prediction system comprising a server, a data acquisition module, a state sampling module, an experimental data feedback module, a deformation prediction module, a feedback control module, and a process adjustment module, the server is respectively connected to the data acquisition module, the experimental data feedback module, the state sampling module, the deformation prediction module, the feedback control module, and the process adjustment module, and stores intermediate data and process data of the data acquisition module, the state sampling module, the experimental data feedback module, the deformation prediction module, the feedback control module, and the process adjustment module in a database of the server for query or call;

[0073] The data acquisition module is used to collect image data of the manufactured textile product 6, the experimental data feedback module is used for users and managers to feedback historical water washing deformation data of the manufactured textile product 6, the deformation prediction module evaluates the non-deformation degree of the textile product 6 according to the image data and the historical water washing deformation data to form an evaluation result, the feedback control module controls the production process parameters of the process adjustment module according to the evaluation result to determine new production process parameters, and the process adjustment module adjusts the production process of the textile process according to the new production process parameters;

[0074] The textile deformation prediction system also includes a central processor, which is respectively connected to the data acquisition module, the state sampling module, the experimental data feedback module, the deformation prediction module, the feedback control module, and the process adjustment module, and the data acquisition module, the state sampling module, the experimental data feedback module, the deformation prediction module, the feedback control module, and the process adjustment module are centrally controlled based on the central processor. The control data of the central processor is stored in the database of the server, so as to improve the accuracy and reliability of the whole system for non-deformation prediction;

[0075] The data acquisition module includes a collection unit, an unfolding unit and a supporting unit, wherein the supporting unit supports the manufactured textile product 6, the unfolding unit unfolds the manufactured textile product 6, and the collection unit collects image data of the unfolded textile product 6;

[0076] Wherein, the unfolding unit and the supporting unit are arranged on the recovery or transfer route of the textile product 6, and the collecting unit is arranged above the manufactured textile product 6;

[0077] Optionally, the support unit includes a support plate, an adsorption member and a limiting member, the support plate supports the textile product 6, the adsorption member adsorbs the textile product 6, and the limiting member limits the position of the textile product 6;

[0078] The adsorption component includes an adsorption pump, an adsorption pipe, a lifting rod, a lifting drive mechanism, and an adsorption nozzle. The adsorption pump is connected to the adsorption nozzle through the adsorption pipe, and the adsorption nozzle adsorbs the textile product 6. One end of the lifting rod is connected to the adsorption pump, and the other end of the lifting rod is driven and connected to the lifting drive mechanism to form a driving part, and the driving part is arranged on the recovery or transfer route of the textile product 6;

[0079] The adsorption components are symmetrically arranged on the recovery or transfer route of the textile product 6, and adsorb the textile product 6 from opposite sides of the textile product 6 to achieve support for the textile product 6;

[0080] Optionally, the unfolding unit includes a toggling member and a telescopic member, the toggling member toggles the textile product 6, and the telescopic member adjusts the position of the toggling member;

[0081] The unfolding unit is symmetrically arranged on both sides of the recycling and delivery route of the textile product 6, and unfolds the textile product 6 from both sides of the recycling and delivery route of the textile product 6;

[0082] The toggle member includes a toggle rod 11 and a buffer contact pad 12 disposed on the toggle rod 11, wherein the toggle rod 11 is used to support the buffer contact pad 12, and during the toggle process, the buffer contact pad 12 contacts the surface of the textile product 6, and under the telescopic operation of the telescopic member, the textile product 6 is toggled in directions away from each other, thereby exposing the density and pore size of the textile structure of the textile product 6;

[0083] The buffer contact pad 12 is made of rubber material, and when the buffer contact pad 12 is in contact with the textile product 6, the buffer contact pad 12 can be pressed against the surface of the textile product 6 and cooperate with the telescopic rack to unfold the textile product 6;

[0084] The telescopic member includes a conveying plate 3, a telescopic rod 9, an auxiliary rod 10, a positioning seat 8, a telescopic driving mechanism, an auxiliary driving mechanism, and a support rod 7. The textile product 6 is transferred or recovered through the upper end surface of the conveying plate 3 (that is, the textile product 6 passes through the upper end surface of the conveying plate 3). One end of the telescopic rod 9 is connected to the toggle rod 11, and the other end of the telescopic rod 9 is driven and connected to the telescopic driving mechanism to form a telescopic portion, and the telescopic portion is arranged on the positioning seat 8. One end of the support rod 7 is hinged to the positioning seat 8, and the other end of the support rod 7 is connected to the side edge of the conveying plate 3. One end of the auxiliary rod 10 is hinged to the telescopic rod 9, and the other end of the auxiliary rod 10 is driven and connected to the auxiliary driving mechanism to form an auxiliary driving portion, and the auxiliary driving portion is arranged on the rod body of the support rod 7;

[0085] The telescopic member further comprises an extension detection member and a telescopic detection member, wherein the extension detection member collects the real-time telescopic amount of the auxiliary rod 10 to obtain the real-time telescopic amount data of the auxiliary rod 10, and the telescopic detection member collects the telescopic amount of the telescopic rod 9 to obtain the real-time telescopic amount data of the telescopic rod 9;

[0086] The auxiliary driving unit drives the auxiliary rod 10 to perform a telescopic action, so that the telescopic rod 9 contacts and causes the buffer contact pad 12 to abut against the surface of the textile product 6, and pulls the textile product 6 from opposite sides, causing the textile product 6 to expose the density and pore size of the textile structure of the textile product 6, such as Figure 3 or Figure 5 The pulling schematic diagram shown (the supply direction of the textile product 6 is perpendicular to the paper surface);

[0087] The collection unit includes a light source 5, a collection component and a data storage device, wherein the light source 5 and the collection component are respectively arranged on both sides of the textile product 6, that is, the light source 5 is arranged in the plate body of the transmission plate 3 (hereinafter referred to as the placement slot 4), so that the light passes through the textile product 6 and is collected by the collection component from the other side of the textile product 6, and the data storage device stores the image data of the textile product 6 collected by the collection component;

[0088] The transmission plate 3 includes a placement groove 4 provided on the body of the transmission plate 3, and a light-transmitting baffle plate buckled on the placement groove 4. The light source 5 is arranged in the placement groove 4 and transmits light to the textile product 6 through the baffle plate. Figure 5 As shown;

[0089] The collecting component includes a collecting probe 1 and a vertical pole 2, wherein the vertical pole 2 is L-shaped, and one end of the vertical pole 2 is connected to the collecting probe 1, and the other end of the vertical pole 2 is connected to a side edge of the conveying plate 3, so that the collecting probe 1 can be arranged above the recycling or conveying path of the textile product 6, so that the image data of the textile product 6 can be collected by the collecting probe 1;

[0090] Wherein, the image data includes an image associated with density and pore size of the textile structure of the textile product 6;

[0091] In the process of the collecting component collecting the textile product 6, the textile product 6 is stretched by the unfolding unit, so that the textile product 6 is more evenly light-transmissive;

[0092] In this embodiment, the force (force involved in pulling or unfolding) applied by the unfolding unit to the textile product 6 is the same for the same batch or type of textile materials, so as to ensure that the measurement and prediction process complies with the single variable principle;

[0093] Through the cooperation between the collection unit, the unfolding unit and the supporting unit, the state of the textile product 6 can be evaluated, and the prediction ability and reliability of the entire system for the textile product 6 are improved, ensuring that the entire system has the advantages of strong prediction ability and high intelligence;

[0094] The data acquisition module further includes a data processing unit, which processes the acquired image data to expose the density and pore size of the textile structure of the textile product 6;

[0095] The data processing unit performs processing according to the following steps:

[0096] S11, grayscale: converting the collected color image into a grayscale image;

[0097] S12, binarization: converting the grayscale image into a binary image by threshold processing to highlight the transparent part and the opaque part; wherein, threshold processing, grayscale processing and binarization processing methods for the image are well known to those skilled in the art, and those skilled in the art can refer to relevant technical manuals to learn about the technology, so they are not described one by one in this embodiment;

[0098] S13. Calculation of weaving density D of textile products

[0099] Translucent hole detection: In a binary image, the holes in the translucent part can reflect the weaving density;

[0100] Wherein, the weaving density D of the textile product is calculated according to the following formula:

[0101]

[0102] Where N f is the number of light-transmitting holes per unit area of ​​the textile product, A is the unit area set for the textile product, i.e., the real-time weaving area of ​​the textile product (the area of ​​the textile product on the transmission plate, whose value is set by the real-time forming / weaving area of ​​the textile product)

[0103] S14. Calculation of pore size of textile products

[0104] Hole area measurement: measure the area Ai of each light-transmitting hole;

[0105] Aperture calculation: Calculate the average area of ​​all holes;

[0106] The pore size P of textile products is calculated according to the following formula:

[0107]

[0108] Where N h is the number of holes detected;

[0109] S15. Calculation of comprehensive braiding structure characteristic parameter S

[0110] The braiding density D and pore size P are obtained by integrating the braiding structure characteristic parameter S and calculated according to the following formula:

[0111]

[0112] In the formula, D is the weaving density of the textile product, and P is the pore size of the textile product;

[0113] In this embodiment, a method for calculating the number N of light-transmitting holes per unit area of ​​a textile product is provided. f , Textile product hole area A i and the number of holes detected N h The specific process and detailed steps:

[0114] S21. Image acquisition

[0115] Use a high-resolution camera or image acquisition probe to capture images of textile products, and ensure that the light source is evenly irradiated on the textile products to enhance the contrast of the light-transmitting parts;

[0116] S22, grayscale processing

[0117] Convert the collected color image into a grayscale image; the purpose of grayscale conversion is to simplify the image processing process and highlight the light transmission characteristics of textile products;

[0118] In this embodiment, a grayscale image is converted using a grayscale formula;

[0119] Specifically, the grayscale formula (weighted average method):

[0120] Grey(x,y)=0.299·R+0.587·G+0.114·B;

[0121] Where R, G, B are the pixel values ​​of the red, green, and blue channels respectively, and Grey(x, y) is the grayscale image pixel value;

[0122] S23, Binarization

[0123] Convert the grayscale image into a binary image to make the hole and non-hole areas more obvious; the commonly used methods are global threshold method or adaptive threshold method;

[0124] In this embodiment, the global and threshold values ​​are used for explanation, specifically:

[0125]

[0126] Where B(x,y) is the binary image pixel value, Grey(x,y) is the grayscale image pixel value, and T is the global threshold value, which is set by the system or the administrator / operator.

[0127] S24, Noise Removal

[0128] Use morphological operations (such as opening and closing) to remove noise and retain the main hole features;

[0129] Opening operation: first perform corrosion operation, then dilation operation to remove small noise points;

[0130] Closing operation: first perform dilation operation, then erosion operation to fill small holes;

[0131] Among them, the opening operation and the closing operation are conventional image processing technologies, which are well known to those skilled in the art. Those skilled in the art can refer to relevant technical manuals to learn about the technologies, and thus they will not be described in detail in this embodiment.

[0132] S25, Hole Detection

[0133] Use the connected component labeling algorithm to detect holes and count the number and area of ​​holes;

[0134] Connected component labeling algorithm: Mark all connected components (holes) in a binary image and calculate the area of ​​each component;

[0135] The specific steps are as follows:

[0136] 1) Scan the image: Scan the image row by row and column by column to find non-background pixels (i.e., pixels with a value of 255 in a binary image); Scan the image row by row and column by column to find foreground pixels (i.e., pixels with a value of 255 in a binary image) from the upper left corner to the lower right corner;

[0137] 2) Connectivity check: For each non-background pixel, check whether its neighboring pixels (4-connected or 8-connected) are also non-background pixels; if so, mark these pixels as the same connected component;

[0138] Among them, the four-connected (4-Connected) four-connected area or four-neighborhood refers to the four directions of up, down, left and right of the corresponding pixel position, which are the adjacent positions;

[0139] Features: According to the four-connectivity principle, if the values ​​of the pixels above, below, left, and right of the central pixel are the same as the value of the central pixel, then these pixels are considered to belong to the same area as the central pixel;

[0140] Example: Consider a binary image (with only two pixel values, 0 and 1). If a pixel with a value of 1 has at least one pixel with a value of 1 in the four directions above, below, left, and right, then the two points are considered four-connected.

[0141] 8-Connected: An 8-connected region or 8-neighborhood includes not only the four directions of up, down, left, and right, but also the four diagonally adjacent positions of upper left, upper right, lower left, and lower right.

[0142] Features: According to the eight-connected principle, if there is a pixel with the same value as the central pixel in the eight-connected directions (up, down, left, right, upper left, upper right, lower left, lower right) of the central pixel, then the two points are considered to belong to the same area;

[0143] Example: Consider a binary image. If a pixel with a value of 1 has at least one pixel with a value of 1 in its eight-connected direction, then the two points are considered eight-connected.

[0144] 3) Record connected components: assign a unique identifier to each connected component and record its number of pixels;

[0145] S26. Calculate the number of holes detected N h According to the results of the connected component labeling algorithm, the total number of holes N in the entire image is counted h , where the total number of holes N h It is one of the outputs of the connected component labeling algorithm and represents the number of all connected components in the image;

[0146] S27. Count the number of light-transmitting holes per unit area N f According to the results of the connected component labeling algorithm, count the number of holes N per unit area (e.g. 1 square centimeter) f :

[0147] Assume the physical size of the image is W×H (unit: cm) and the resolution is P x ×P y (Unit: pixel);

[0148]

[0149] The number of holes per unit area N f for:

[0150]

[0151] Where N h is the number of holes detected, δ ij is the indicator function. When the i-th hole is located within the unit area j, δ ij =1, otherwise 0;

[0152] S27, measure the hole area A i According to the results of the connected component labeling algorithm, calculate the area A of each hole i ;

[0153] Let the number of pixels of the i-th hole be n i , the actual area of ​​each pixel is a p (Unit: square centimeters), then

[0154]

[0155] Hole area A i Calculate according to the following formula:

[0156] A i =n i ·a p ;

[0157] The state sampling module includes a tension sampling unit and a twist sampling unit, wherein the tension sampling unit collects the tension of the yarn supply, and the twist sampling unit collects the twist of the yarn;

[0158] The tension sampling unit includes a data acquisition card and at least two tension sensors, and the at least two tension sensors respectively collect the tension of the warp yarn (or warp yarn) and the weft yarn (or weft yarn) to obtain the tension data of the yarn in the warp direction and the tension data of the yarn in the weft direction, and the data acquisition card stores the tension data collected by the at least two tension sensors;

[0159] Wherein, the tension sensor is arranged on the supply route of the yarn, so as to collect the tension data of the spinning thread;

[0160] In addition, the tension sensor obtains tension data by measuring the tension on the spinning thread. In this example, the tension sensor includes but is not limited to the following types: a resistance strain tension sensor, a piezoelectric tension sensor, etc.;

[0161] The tension sensor should be installed on the path of the spinning thread, usually at the spinning thread outlet position, the middle yarn guide position or the spinning thread forming position, to ensure that the sensor can directly feel the tension of the spinning thread;

[0162] In this embodiment, the bracket of the tension sensor is fixed to the frame or base of the equipment using screws or clamps to ensure that the sensor bracket is stable and will not move due to machine vibration or changes in spinning tension;

[0163] In addition, the roller of the tension sensor is mounted on the bracket so that the yarn passes through the roller to ensure that the roller can rotate freely and the yarn remains stable on the roller without slipping or falling off;

[0164] It is worth noting that after the sensor is installed, calibration is performed to ensure the accuracy of the measurement, and a standard yarn with known tension is used for calibration to adjust the sensitivity and accuracy of the sensor;

[0165] The twist sampling unit includes at least two twist sensors and a vertical rod, wherein the at least two vertical rods are respectively provided with at least two twist sensors for installation, and the twist sensors are used to measure the number of twists of the yarn per unit length;

[0166] The twist sensor should be installed on the path of the spinning thread, usually near the spinning thread outlet position or the spinning thread forming position, to ensure that the spinning thread maintains a certain tension in the measuring area of ​​the sensor, so as to accurately measure the twist;

[0167] At the same time, use a vertical rod to fix it to the frame or base of the equipment to ensure that the sensor bracket is stable and will not move due to machine vibration or changes in spinning tension;

[0168] The twist sensor includes an optical twist sensor and a mechanical twist sensor, wherein the probe of the twist sensor is mounted on a bracket so as to be in contact with or close to the spinning thread;

[0169] If using an optical twist sensor, make sure the optical probe can accurately scan the surface of the yarn;

[0170] If using a mechanical twist sensor, make sure the probe is in close contact with the yarn so that the twist of the yarn can be measured;

[0171] In this embodiment, the state sampling module is used to collect the tension and twist state data of the supplied spinning thread, and the devices and equipments understood or commonly set by those skilled in the art may also be used, and are not limited to the specific installation methods given above, so they will not be described one by one;

[0172] Optionally, the experimental data feedback module includes a feedback unit and a data acquisition unit, the data acquisition unit is used by a manager / operator to record the historical water washing deformation data of the textile product, and the feedback unit transmits the historical water washing deformation data collected by the data acquisition unit to the deformation prediction module;

[0173] Wherein, the data acquisition unit includes a feedback recording terminal and a record manager, wherein the feedback recording terminal records the historical washing deformation data of the textile product recorded by the manager / operator, and the record manager records the historical washing deformation data;

[0174] The feedback unit includes a transmitter and a communicator, wherein the communicator is used for the data acquisition unit and the deformation prediction module to communicate, and the transmitter transmits the historical water washing deformation data to the deformation prediction module through the communicator;

[0175] The experimental data feedback module includes a data processing unit, and the data processing module processes the historical water washing deformation data to determine the historical water washing deformation data D;

[0176] In this embodiment, the historical washing deformation data includes the size change of the textile product, the shape change of the textile product, the curling of the textile product, and the warping index of the textile product;

[0177] The data processing unit obtains the historical water washing deformation data obtained by the feedback recording end, and determines the historical water washing deformation data D according to the following steps:

[0178] S31, calculate the dimension change coefficient △ based on the feedback of the length and width changes before and after washing size :

[0179]

[0180] In the formula, the length of △L changes, and its value satisfies: △L=L Before -L after , where L before is the length before washing, L after is the length after washing, △W is the width change, and its value satisfies: △W=W Before -W after , where W before is the width before washing, W after It is the width after washing;

[0181] S32, the shape change coefficient Δ before and after washing obtained based on the feedback shape :

[0182] Shape change refers to the overall change in the shape of a textile product before and after washing. In this embodiment, image processing technology is used to record the contours of the textile product before and after washing. In this embodiment, the contour point set of the textile product is obtained by collecting images of the textile product before and after washing and using edge detection and contour extraction algorithms. Commonly used edge detection algorithms include Canny edge detection, etc. The following are the specific steps:

[0183] 1) Edge detection: Apply Canny edge detection to the grayscale processed image to obtain the edge image of the textile product; Contour extraction: Extract the contour point set from the edge image;

[0184] Among them, edge detection and contour extraction are technical means well known to those skilled in the art, and those skilled in the art can refer to relevant technical manuals to learn about the technology, so they will not be described one by one in this embodiment;

[0185] 2) Calculation of shape change coefficient

[0186] Assume that the coefficient of difference of the contour of textile products before and after washing is Δ shape , can be represented by calculating the average distance between two contours; assuming that the contour is represented by the point set {P before} and {P after}express:

[0187]

[0188] Where n is the number of contour points, which is extracted from the contour of textile products through image processing technology, and P before，i is the contour point of the i-th water wash, P after，i is the contour point after the i-th washing, ||P before,i -P after,i || is the Euclidean distance of the contour points before and after washing, calculated according to the following formula:

[0189]

[0190] In the formula, (x before,i ,y before,i ) represents the contour point before washing, (x after,i ,y after,i ) represents the i-th contour point after washing;

[0191] S33, calculating the curl difference coefficient Δ according to the curl degree before and after washing obtained by feedback curl :

[0192] Measurement methods include:

[0193] Use image processing techniques to record the curvature of the edges of textile products before and after washing;

[0194] Among them, an edge detection algorithm (such as Canny edge detection) is used to extract the edge contours of textile products before and after washing;

[0195] Edge detection steps:

[0196] 1) Perform Gaussian smoothing on the grayscale image to remove noise;

[0197] 2) Use the Sobel operator to calculate the gradient of the image;

[0198] 3) Perform non-maximum suppression to refine the edges;

[0199] 4) Apply double thresholding to connect edges;

[0200] Curvature calculation

[0201] After extracting the points on the edge contour, the curvature of each point can be calculated; curvature refers to the degree of bending of a point on the curve. For a curve on a 2D plane, the calculation formula for the curvature k is:

[0202]

[0203] Where a and b are the coordinates of the point on the curve, a' and b' are the first-order derivatives of the curve at that point (i.e., tangent vectors), and a" and b" are the second-order derivatives of the curve at that point (i.e., curvature vectors);

[0204] The specific steps of edge detection used in the curvature calculation process include:

[0205] S331, extract edge contour points: use edge detection algorithm to obtain the coordinate set of edge contour points {(a i , b i )};

[0206] S332. Calculate the derivative:

[0207] For discrete edge points, the derivative can be approximated using the difference method;

[0208] First derivative (using central difference method):

[0209]

[0210] In the formula, a i ' is the first-order derivative of the i-th edge point in the horizontal direction, b i ' is the first-order derivative of the ith edge point in the vertical direction, a i+1 is the horizontal coordinate of the i+1th edge point, a i-1 is the horizontal coordinate of the i-1th edge point, b i+1 is the ordinate of the i+1th edge point, b i-1 is the ordinate of the i-1th edge point;

[0211] Second derivative (using central difference method):

[0212]

[0213] In the formula, a i 〞 is the second-order derivative of the ith edge point in the horizontal direction, b i 〞 is the second-order derivative of the ith edge point in the vertical direction, a1 is the horizontal coordinate of the ith edge point, b i is the ordinate of the i-th edge point, a i+1 is the horizontal coordinate of the i+1th edge point, a i-1 is the horizontal coordinate of the i-1th edge point, b i+1is the ordinate of the i+1th edge point, b i-1 is the ordinate of the i-1th edge point;

[0214] S333, calculating the curvature of the i-th edge point of the textile product before and after washing:

[0215]

[0216] In the formula, k before,i is the curvature of the ith edge point of the textile product before washing, k after,i is the curvature of the ith edge point of the textile product after washing, a' after,i is the first-order derivative of the ith edge point of the textile product after washing in the horizontal direction, a″ after,i is the second-order derivative of the ith edge point of the textile product in the horizontal direction after washing, b' before，i is the first-order derivative of the ith edge point of the textile product in the vertical direction before washing, b″ before，i is the second-order derivative of the ith edge point of the textile product in the vertical direction before washing,

[0217] S334, repeat the above calculation process for all points to obtain the curvature of all points before and after washing, and then calculate the average curvature:

[0218]

[0219] In the formula, k before,i is the curvature of the ith edge point of the textile product before washing, k after,i is the curvature of the i-th edge point of the textile product after washing;

[0220] S335, calculating curvature change;

[0221] Assume that the difference in edge curvature of textile products before and after washing is Δ curl , can be expressed by calculating the change in edge curvature:

[0222]

[0223] In the formula, k before k is the average edge curvature of textile products after washing, after It is the average curvature of the edge of the textile product after washing;

[0224] S34, calculating the curling difference coefficient Δ according to the degree of edge warping before and after washing obtained by feedback flip :

[0225] Measurement method:

[0226] 1) Use image processing technology to record the upturned height of the edges of textile products before and after washing;

[0227] Use edge detection algorithms (such as Canny edge detection) to extract edge contours of textile products before and after washing;

[0228] Edge warp height measurement: After extracting edge contour points, calculate the height change of each edge point; the warp height refers to the vertical displacement of the edge point relative to its initial position;

[0229] 2) Extract edge points

[0230] Edge points before washing: Let (u before,i ,v before,i ) represents the edge point before the i-th water washing;

[0231] Edge points after washing: Let (u after,i ,v after,i ) represents the edge point after the i-th water washing;

[0232] 3. Calculate the upturn height

[0233] Define the baseline:

[0234] Choose a reference line (e.g. the bottom edge or the center line of the textile product) as the reference line;

[0235] The baseline can be expressed as u = u base ;

[0236] The calculation formula of upturn height:

[0237] For each edge point, calculate its vertical displacement (upward height) relative to the baseline

[0238] Upward height before washing:

[0239] h before,i =u before,i -u base ;

[0240] Upward height after washing:

[0241] hafter,i=u after,i -u base ;

[0242] Calculate the average curl height: In order to compare the curl of the edge before and after washing, the average curl height of all edge points can be calculated;

[0243] Average upturn height before washing:

[0244]

[0245] Where N is the number of contour points extracted before washing, h before,iis the upturn height of the i-th contour point before washing;

[0246] Average upturn height after washing:

[0247]

[0248] Where N is the number of contour points extracted after washing, h after,i is the upturn height of the i-th contour point after washing;

[0249] Suppose the difference in the height of the edge of the textile product before and after washing is Δ flip , its value is calculated according to the following formula:

[0250]

[0251] In the formula, h before is the average upturn height before washing, h after They are the average upturn height after washing;

[0252] S35. Comprehensively analyze various deformation data and calculate the historical water washing deformation data D:

[0253]

[0254] In the formula, △ size Calculate the coefficient of dimensional change, Δ, for the change in length and width before and after washing curl Calculate the curl difference coefficient, Δ shape is the shape change coefficient before and after washing, Δ flip The curling difference coefficient was calculated for the degree of edge lift before and after washing;

[0255] Optionally, the deformation prediction module obtains the preprocessed image data and the historical washing deformation data of the textile product, and calculates the undeformation index Undeformation according to the following:

[0256]

[0257] Where, T is the yarn twist, J is the yarn tension, S is the characteristic parameter of the weaving structure, and its value is calculated after image preprocessing; D is the historical washing deformation data, and its value is calculated after processing by the experimental data feedback module;

[0258] If the undeformation index Undeformation does not fall within the monitoring threshold range [range1, range2] set by the system, the feedback control module is triggered to calculate new production process parameters;

[0259] If the undeformation index Undeformation falls within the monitoring threshold range [range1, range2] set by the system, it means that the current process parameters meet the system requirements and the original process parameters are maintained;

[0260] Among them, the monitoring threshold range [range1, range2] set by the system is set by the system or the administrator / operator according to the actual situation of the textile products. This is a technical means well known to those skilled in the art. Those skilled in the art can refer to relevant technical manuals to learn about the technology, so it will not be described one by one in this embodiment;

[0261] Through the cooperation of the data acquisition module, the experimental data feedback module and the deformation prediction module, the real-time deformation prediction capability of the textile product is made more accurate, ensuring that the entire system has the advantages of good real-time feedback effect, accurate deformation prediction capability, timely back-end effect feedback and high intelligence;

[0262] Optionally, the production process parameters include tension and twist of the textile thread;

[0263] Optionally, the feedback control module obtains the calculated undeformation index Undeformation and the monitoring threshold range [range1, range2] set by the system, and calculates the new yarn twist T according to the following formula: new :

[0264]

[0265] Where, T old is the original yarn twist, and its value is obtained by sampling the state sampling module. range1 is the lower limit of the monitoring threshold range set by the system, range2 is the upper limit of the monitoring threshold range set by the system, and α is the adjustment coefficient value, and its value is determined according to the following formula:

[0266]

[0267] In the formula, △U avg is the average value of the deformation index change, △T avg is the average value of yarn twist change, Undeformation is the undeformation index;

[0268] The feedback control module obtains the calculated undeformation index Undeformation and the monitoring threshold range [range1, range2] set by the system, and calculates the new yarn tension J according to the following formula: new :

[0269]

[0270] In the formula, J old is the original yarn tension, and its value is obtained by sampling the state sampling module. range1 is the lower limit of the monitoring threshold range set by the system, range2 is the upper limit of the monitoring threshold range set by the system, and β is the adjustment coefficient value, and its value is calculated according to the following formula:

[0271]

[0272] In the formula, △U avg is the average value of the deformation index change, △J avg is the average value of yarn tension change, Undeformation is the undeformation index;

[0273] In this embodiment, for △U avg is the average value of the deformation index change, △J avg is the average value of yarn tension change, △T avg is the average value of the yarn twist change, and the specific calculation and determination steps provided in this embodiment include:

[0274] S41. Analyze historical data and experience values:

[0275] Collect a batch of historical data of textile products, including the current twist T, tension J, undeformation index Undeformation and the corresponding process parameter adjustment data, and preliminarily determine the reasonable adjustment range by analyzing these data;

[0276] S42. Calculate the average value of the change in the non-deformation index ΔU avg :

[0277]

[0278] Where C is the number of samples, Undeformation after，i is the adjusted undeformation index, before，i is the deformation-free index before adjustment;

[0279] S43. Calculate the average value of yarn twist and tension changes:

[0280]

[0281] In the formula, ΔT avg is the average value of the yarn twist change, C is the sample size, that is, the number of textile product samples measured and calculated, T after,i is the yarn twist of the i-th sample after adjustment; T before,i is the yarn twist of the i-th sample before adjustment;

[0282]

[0283] Where, ΔJ avg is the average value of yarn tension change, C is the sample size, that is, the number of textile product samples measured and calculated, J after,i is the yarn length of the i-th sample after adjustment, J before,i is the yarn tension of the i-th sample before adjustment;

[0284] In this embodiment, through the mutual cooperation between the deformation prediction module and the feedback control module, the process parameter evaluation capability is made more timely, ensuring that the entire system has the advantages of high dynamic feedback timeliness, strong real-time adjustment capability, good process analysis capability and strong anti-deformation ability of textile products;

[0285] The process adjustment module includes a twist adjustment unit and a tension adjustment unit, wherein the twist adjustment unit controls the twist of the yarn, and the tension adjustment unit adjusts the supply tension of the yarn;

[0286] In the process of adjusting the twist of the yarn by the twist adjustment unit, the new yarn twist T is obtained. new , so that the twist trigger device can be adjusted according to the new yarn twist T new Control the real-time supply twist of the yarn;

[0287] Similarly, in the process of adjusting the twist of the yarn by the tension adjustment unit, the new yarn tension J is obtained. new , so that the tension trigger device can be adjusted according to the new yarn tension J new Control the real-time supply tension of yarn;

[0288] The twist trigger device and the tension trigger device are conventional devices of a textile product production line, which are well known to those skilled in the art. Those skilled in the art can refer to relevant technical manuals to learn about the technology, and thus will not be described in detail in this embodiment.

[0289] Through the mutual cooperation between the process adjustment module and the feedback control module, the real-time adjustment of the process parameters is made more efficient, ensuring that the entire system has the advantages of good real-time adjustment capability, high intelligence, high accuracy of process parameter adjustment, good process capability feedback capability and strong anti-deformation ability of textile products.

[0290] Embodiment 2: This embodiment should be understood to include all the features of any of the above embodiments, and further improve upon them. Figure 1 , Figure 2 , Figure 3 , Figure 4 and Figure 5 As shown, the data acquisition module further includes a temperature acquisition unit and a temperature evaluation unit, wherein the temperature acquisition unit acquires the temperature generated by the unfolding unit in the process of moving the textile product 6, and the temperature evaluation unit evaluates the moving and unfolding process of the unfolding unit according to the temperature data acquired by the temperature acquisition unit to form an evaluation result, and triggers the adjustment of the unfolding unit;

[0291] Wherein, the temperature collection unit is arranged on the contact end surface between the limiting member and the textile product 6, and collects the temperature generated during the contact process between the textile product 6 and the limiting member;

[0292] The temperature acquisition unit includes a temperature acquisition probe 13 and a data buffer. The temperature acquisition probe 13 acquires the temperature generated when the limiting member and the textile product 6 are in contact and unfolded. The data buffer stores the temperature data acquired by the temperature acquisition probe 13.

[0293] The temperature acquisition probe 13 includes but is not limited to the following: thermocouple, thermistor and infrared temperature sensor;

[0294] Specifically: Thermocouple: Thermocouple can directly contact the surface of the limiting component and detect the temperature through voltage changes;

[0295] Thermistor: Thermistor can also directly contact the limit member to detect temperature through resistance change;

[0296] Infrared temperature sensor: Infrared temperature sensor can detect temperature without contact, which is suitable for occasions where direct contact is not possible or contamination needs to be avoided;

[0297] In this embodiment, the temperature is measured or collected in a contact manner, that is, a thermocouple or thermistor is arranged on the end surface in contact with the textile product 6;

[0298] The principle of measuring the temperature of the contact end surface of the textile product 6 by using a thermocouple or a thermistor is a technical means well known to those skilled in the art. Those skilled in the art can refer to relevant technical manuals to learn about the technology, so it will not be described in detail in this embodiment; the temperature evaluation unit obtains the temperature data collected by the temperature collection unit, and calculates the temperature feedback index TEM_Feedback according to the following formula:

[0299]

[0300] Where, T refis a reference temperature value, which is set by the system according to the type of textile products currently produced. This is a method well known to those skilled in the art, so it will not be described in detail. max is the maximum temperature obtained, and its value satisfies: T max =max(Tem1,Tem2,…,Tem i ,Tem n ), where Tem i is the temperature value collected for the i-th time, the value range of i is: (1, n], n is the number of times the temperature data is collected, △T is the temperature change rate, Tem avg is the average temperature, and its value is calculated according to the following formula:

[0301]

[0302] Where, Tem i is the temperature value collected for the i-th time, and n is the number of times the temperature data is collected;

[0303] The temperature change rate ΔT is calculated according to the following formula:

[0304]

[0305] Where, Tem i is the temperature value collected for the i-th time, Tem i+1 is the temperature value collected at the i+1th time, and n is the number of times the temperature data is collected;

[0306] If the temperature feedback index TEM_Feedback does not fall within the set temperature monitoring threshold range [Monitor1, Monitor2], the expansion unit is triggered to make adjustments;

[0307] If the temperature feedback index TEM_Feedback falls within the set temperature monitoring threshold range [Monitor1, Monitor2], it means that the current contact between the unfolding unit and the textile product meets the system requirements, and the status quo is maintained;

[0308] The analysis unit obtains the temperature feedback index TEM_Feedback and the temperature monitoring threshold Monitor set by the system, and calculates the contact pressure ΔP according to the following formula:

[0309] ΔP=k p ·min[|TEM_Feedback-Monitor1|,|TEM_Feedback-Monitor2|];

[0310] In the formula, Monitor1 is the lower limit of the temperature monitoring threshold range set by the system, Monitor2 is the upper limit of the temperature monitoring threshold range set, and k p It is the proportional coefficient of contact pressure adjustment, and its value is set by the system;

[0311] The analysis unit calculates the adjustment amount L of the auxiliary driving part according to the contact pressure amount ΔP:

[0312]

[0313] Where, L current is the real-time extension amount of the auxiliary driving part, and its value is directly measured by the elongation detection member; γ is the proportional coefficient between force and length, and its value is set by the system, that is, the auxiliary rod retracts 1mm to trigger the force applied by the limiting member on the textile product; for example, the auxiliary rod retracts 1mm, resulting in the limiting member applying a force of 0.5 Newton on the textile product, and γ=0.5 Newton / mm;

[0314] Among them, when the temperature feedback index TEM_Feedback>Monitor2, take the "-" sign, when the temperature feedback index TEM_Feedback<Monitor1, take the "+" sign;

[0315] The analysis unit obtains the temperature feedback index TEM_Feedback and the temperature monitoring threshold Monitor set by the system, and calculates the contact time adjustment amount △Time according to the following formula:

[0316] ΔTime=k t ·min[|TEM_Feedback-Monitor1|,|TEM_Feedback-Monitor2|];

[0317] In the formula, Monitor1 is the lower limit of the temperature monitoring threshold range set by the system, Monitor2 is the upper limit of the temperature monitoring threshold range set, and k t It is the proportional coefficient for contact time adjustment, and its value is set by the system;

[0318] The analysis unit calculates the expansion and contraction amount S of the expansion and contraction portion according to the contact pressure amount ΔP:

[0319] S=S current ±V·ΔTime;

[0320] In the formula, S current is the real-time extension and contraction amount of the telescopic rod, and its value is directly measured by the telescopic detection member, V is the extension and contraction speed of the telescopic rod, and △Time is the contact time adjustment amount;

[0321] Among them, when the temperature feedback index TEM_Feedback>Monitor2, take the "-" sign, when the temperature feedback index TEM_Feedback<Monitor1, take the "+" sign;

[0322] In this embodiment, the proportionality coefficient k of the contact pressure adjustment is provided. p and the proportionality factor k for contact time adjustment t The steps to determine include:

[0323] S51. Select samples: Select different types of fabric samples for testing;

[0324] S52, initial setting: setting the initial contact pressure adjustment proportional coefficient k p and the proportionality factor k for contact time adjustment t ;

[0325] S53, Experimental steps:

[0326] Set conditions: Conduct experiments under multiple different temperature feedback index conditions;

[0327] Record data: record the contact pressure, contact time and temperature response of the system in each experiment;

[0328] S54. Data analysis:

[0329] Curve fitting: Perform curve fitting on the experimental data to find the relationship between the proportional coefficient and the temperature feedback index;

[0330] Optimization: Determine the optimal contact pressure adjustment proportional coefficient k through optimization algorithms (such as least squares method) p and the proportionality factor k for contact time adjustment t ;

[0331] Among them, the final contact pressure adjustment proportional coefficient k is obtained by fitting the experimental data obtained through the least squares method. p and the proportionality factor k for contact time adjustment t This is a technical means well known to those skilled in the art, and those skilled in the art can refer to relevant technical manuals to learn about the technology, so it will not be described in detail in this embodiment;

[0332] In addition, in this embodiment, several contact pressure adjustment proportional coefficients k are provided. p and the proportionality factor k for contact time adjustment t The value examples are as follows:

[0333] 1) When textile products are made of cotton fabrics (cotton fabrics are highly sensitive to temperature, and higher temperatures can easily damage the fabrics):

[0334] Experimental setup:

[0335] Initial scale factor: k P = 5 Newton, k t = 2 seconds;

[0336] Experimental results:

[0337] Through many experiments, it is found that when the temperature feedback index TEM_Feedback is between 1.6 and 2.0, the optimal proportional coefficient is: k P = 8 Newton, k t = 3 seconds;

[0338] 2) When textile products are made of polyester fabrics (polyester fabrics are moderately sensitive to temperature and can withstand higher temperatures):

[0339] Experimental settings: Initial proportionality factor: k P = 4 Newtons, k t = 1.5 seconds;

[0340] Experimental results:

[0341] Through many experiments, it is found that when the temperature feedback index TEM_Feedback is between 1.6 and 2.0, the optimal proportional coefficient is: k P = 6 Newton, k t = 2.5 seconds;

[0342] 3) When the textile products are wool fabrics (wool fabrics are very sensitive to temperature, and higher temperatures can easily cause the fabrics to shrink and deform):

[0343] Experimental setup:

[0344] Initial scale factor: k P = 6 Newton, k t = 3 seconds;

[0345] Experimental results:

[0346] Through many experiments, it is found that when the temperature feedback index TEM_Feedback is between 1.4 and 1.8, the optimal proportional coefficient is: k P = 10 Newton, k t =4 seconds;

[0347] In summary, through experimental data and optimization algorithm, the contact pressure adjustment proportional coefficient k suitable for different fabrics can be determined. P and contact time adjustment proportionality factor k t; Proportional coefficient k for contact pressure adjustment p and the proportionality factor k for contact time adjustment t It reflects the response sensitivity of different fabrics when adjusting the contact pressure and contact time, which helps to dynamically adjust the system operation and ensure the quality of textile products;

[0348] In summary, the proportionality factor k of contact pressure adjustment is p and the proportionality factor k for contact time adjustment t The specific value of needs to be determined in combination with the actually generated textile products, which is a technical means well known to those skilled in the art, and therefore will not be described in detail in this embodiment;

[0349] Through the mutual cooperation between the unfolding unit, the temperature collection unit and the temperature evaluation unit, the collection accuracy of the textile product is made higher, ensuring that the entire system has the advantages of high textile product collection accuracy, accurate deformation prediction data source, high intelligence and strong deformation prediction ability.

[0350] The contents disclosed above are only preferred feasible embodiments of the present invention, and do not limit the protection scope of the present invention. Therefore, all equivalent technical changes made using the contents of the present invention specification and drawings are included in the protection scope of the present invention. In addition, the elements therein can be updated as technology develops.

Claims

1. A method for predicting deformation of textiles that do not deform after washing, characterized in that: The textile deformation prediction method comprises the following steps: S1. Collecting image data of the manufactured textile product through a collection module and processing the image data; S2, collecting the tension and twist state data of the supplied spinning thread through the state sampling module; S3, obtaining historical washing deformation data of textile products that have been produced and used through the experimental data feedback module; S4, obtaining the pre-processed image data, the tension and twist state data of the spinning yarn, and the historical washing deformation data of the textile product through the deformation prediction module, and calculating the undeformation index Undeformation of the textile product: Where T is the yarn twist, J is the yarn tension, S is the characteristic parameter of the weaving structure, and its value is calculated after image preprocessing, and D is the historical washing deformation data; S5, determining new production process parameters according to the undeformation index Undeformation and the monitoring threshold [range1, range2] through the feedback control module, the new production process parameters including the new yarn twist T new , and the new yarn tension J new ; Among them, range1 is the lower limit of the monitoring threshold range set by the system, and its value is set by the system according to the actual situation of the textile products; range2 is the upper limit of the monitoring threshold range set by the system, and its value is set by the system according to the actual situation of the textile products; S6. Adjust the production process of the textile process according to the new production process parameters through the process adjustment module.

2. The method for predicting deformation of a textile product that does not deform after washing according to claim 1, characterized in that: The deformation prediction method further includes: in step S1, the acquisition module needs to unfold or stretch the textile product during the process of acquiring the image of the textile product.

3. The method for predicting deformation of a textile product that does not deform after washing according to claim 2, characterized in that: The deformation prediction method further comprises: in step S2, collecting and storing historical washing deformation data of textile products to form a database; Among them, the textile products for which historical washing deformation data are collected cover different batches, different processes and different usage conditions, and the historical washing deformation data of the textile products are measured, wherein the historical washing deformation data include the size change of the textile products, the shape change of the textile products, the curling of the textile products, and the warping index of the textile products, and the historical washing deformation data are transmitted to the experimental data feedback module.

4. A deformation prediction system for a textile that does not deform after washing, applied to the deformation prediction method for a textile that does not deform after washing according to claim 3, characterized in that: The textile deformation prediction system comprises a server, a data acquisition module, a state sampling module, an experimental data feedback module, a deformation prediction module, a feedback control module, and a process adjustment module, wherein the server is respectively connected to the data acquisition module, the state sampling module, the experimental data feedback module, the deformation prediction module, the feedback control module, and the process adjustment module; The data acquisition module is used to collect image data of the manufactured textile products, the experimental data feedback module is used for users and managers to feedback the historical water washing deformation data of the manufactured textile products, the deformation prediction module evaluates the non-deformation degree of the textile products according to the image data and the historical water washing deformation data to form an evaluation result, the feedback control module controls the production process parameters of the process adjustment module according to the evaluation result to determine new production process parameters, and the process adjustment module adjusts the production process of the textile process according to the new production process parameters; The data acquisition module includes a collection unit, an unfolding unit and a supporting unit, wherein the supporting unit supports the manufactured textile product, the unfolding unit unfolds the manufactured textile product, and the collection unit collects image data of the unfolded textile product; Wherein, the unfolding unit and the supporting unit are arranged on a recovery or transfer route of the textile product, and the collecting unit is arranged above the manufactured textile product.

5. The deformation prediction system for textiles that remain unchanged after washing according to claim 4, characterized in that: The support unit comprises a support plate, an adsorption member and a limiting member, wherein the support plate supports the textile product, the adsorption member adsorbs the textile product, and the limiting member limits the position of the textile product; The adsorption component includes an adsorption pump, an adsorption pipe, a lifting rod, a lifting drive mechanism, and an adsorption nozzle, wherein the adsorption pump is connected to the adsorption nozzle through the adsorption pipe, and the adsorption nozzle adsorbs the textile product, one end of the lifting rod is connected to the adsorption pump, and the other end of the lifting rod is driven and connected to the lifting drive mechanism to form a driving part, and the driving part is arranged on the recovery or transfer route of the textile product; The adsorption components are symmetrically arranged on the recovery or transfer route of the textile products, and adsorb the textile products from opposite sides of the textile products to achieve support for the textile products.

6. The deformation prediction system for textiles that remain unchanged after washing according to claim 5, characterized in that: The unfolding unit comprises a toggle member and a telescopic member, wherein the toggle member is used to toggle the textile product, and the telescopic member is used to adjust the position of the toggle member; The unfolding units are symmetrically arranged on both sides of the recycling and delivery route of the textile products, and unfold the textile products from both sides of the recycling and delivery route of the textile products.

7. The deformation prediction system for textiles that remain unchanged after washing according to claim 6, characterized in that: The experimental data feedback module includes a feedback unit and a data acquisition unit, wherein the data acquisition unit is used by a manager / operator to record the historical water washing deformation data of the textile product, and the feedback unit transmits the historical water washing deformation data collected by the data acquisition unit to the deformation prediction module; Wherein, the data acquisition unit includes a feedback recording terminal and a recording manager, wherein the feedback recording terminal records the historical washing deformation data of the textile product recorded by the manager / operator, and the recording manager records the historical washing deformation data.

8. The deformation prediction system for textiles that remain unchanged after washing according to claim 7, characterized in that: If the undeformation index Undeformation does not fall within the monitoring threshold range [range1, range2] set by the system, the feedback control module is triggered to calculate new production process parameters.

9. The deformation prediction system for textiles that remain unchanged after washing according to claim 8, characterized in that: The production process parameters include the tension and twist of the textile thread.

10. The deformation prediction system for textiles that remain unchanged after washing according to claim 9, characterized in that: The feedback control module obtains the calculated undeformation index Undeformation and the monitoring threshold range [range1, range2] set by the system, and calculates the new yarn twist T according to the following formula: new : Where, T old is the original yarn twist, range1 is the lower limit of the monitoring threshold range set by the system, range2 is the upper limit of the monitoring threshold range set by the system, and α is the adjustment coefficient value.

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