Identification matching method and system for novel technical fabric, medium and electronic equipment

Abstract

The invention provides an identification and matching method and system for a novel technical fabric, a medium and electronic equipment. The identification matching method of the novel scientific and technological fabric comprises the following steps: obtaining the novel scientific and technological fabric; a natural language model is utilized to quantify the multiple fabric characteristics of the novel technological fabric to obtain multiple quantitative indexes, wherein the fabric characteristics of the novel technological fabric comprise the fabric thickness, the fabric elasticity, the fabric smoothness degree and the fabric gram weight; acquiring a comprehensive parameter vector according to the plurality of quantitative indexes; performing data fitting on the comprehensive parameter vector and an existing fabric parameter vector to obtain the overall similarity of the novel science and technology fabric and the existing fabric; performing threshold judgment on the overall similarity to obtain a similarity judgment result; and obtaining a fabric parameter package based on the similarity judgment result, wherein the fabric parameter package comprises an overall fabric parameter package and a combined fabric parameter package. According to the invention, the accuracy of fabric identification and matching can be improved.

Description

Technical Field

[0001] The present application belongs to the field of textile technology and relates to a new type of technological fabric, and in particular to an identification and matching method, system, medium and electronic equipment for the new type of technological fabric. Background Art

[0002] In the apparel industry, new high-tech fabrics are constantly emerging. These fabrics offer unique properties and advantages, significantly improving the functionality and comfort of clothing. Currently, the identification of fabric properties relies primarily on manual experience and traditional testing methods. Manual experience in judging fabric properties is subject to high subjectivity, low accuracy, and low efficiency. Different people may have significant differences in their judgments of the same fabric's properties, which can easily lead to deviations in fabric selection and application. Traditional testing methods, such as using specialized instruments and equipment to test fabric properties, while capable of producing relatively accurate results, are complex, costly, and time-consuming, making them unable to meet the rapidly developing apparel industry's demand for high-volume, efficient testing of new high-tech fabrics.

[0003] Furthermore, existing methods for matching the properties of new technical fabrics with existing fabric parameters lack systematicity and precision. They often rely on superficial comparisons, failing to conduct in-depth, comprehensive analysis and quantitative matching of multiple properties. This makes it difficult to provide scientific, comprehensive, and practical solutions when searching for similar fabrics or recommending appropriate parameter packages for new fabrics, limiting the rational application and promotion of new technical fabrics in apparel production.

[0004] Therefore, how to accurately identify the characteristics of new technological fabrics and effectively match them with existing fabric parameters has become an important issue facing the industry. Summary of the Invention

[0005] The purpose of this application is to provide a new type of technical fabric identification and matching method, system, medium and electronic equipment for improving the accuracy of fabric identification and matching.

[0006] In a first aspect, the present application provides a method for identifying and matching new technological fabrics, the method comprising: obtaining a new technological fabric; quantifying multiple fabric properties of the new technological fabric using a natural language model to obtain multiple quantitative indicators, the fabric properties of the new technological fabric including fabric thickness, fabric elasticity, fabric smoothness and fabric weight; obtaining a comprehensive parameter vector based on the multiple quantitative indicators; performing data fitting on the comprehensive parameter vector and the existing fabric parameter vector to obtain the overall similarity between the new technological fabric and the existing fabric; performing a threshold judgment on the overall similarity to obtain a similarity judgment result; obtaining a fabric parameter package based on the similarity judgment result, the fabric parameter package including an overall fabric parameter package and a combined fabric parameter package.

[0007] In an implementation method of the first aspect, the natural language model is used to quantify the various fabric properties of the new scientific and technological fabric to obtain multiple quantitative indicators, including: using the natural language model to quantify the thickness of the fabric of the new scientific and technological fabric to obtain a thickness quantitative indicator; using the natural language model to quantify the fabric elasticity of the new scientific and technological fabric to obtain an elasticity quantitative indicator; using the natural language model to quantify the fabric smoothness of the new scientific and technological fabric to obtain a smoothness quantitative indicator; using the natural language model to quantify the fabric weight of the new scientific and technological fabric to obtain a grammage quantitative indicator.

[0008] In an implementation of the first aspect, obtaining a fabric parameter package based on the similarity judgment result includes: when the overall similarity is greater than a standard threshold, obtaining an overall fabric parameter package, wherein the overall fabric parameter package is a parameter package corresponding to an existing similar fabric; when the overall similarity is less than the standard threshold, performing independent dimension comparison on multiple fabric properties of the new technological fabric to obtain a combined fabric parameter package.

[0009] In an implementation of the first aspect, the process of performing independent dimension comparison on multiple fabric properties of the new technological fabric to obtain the combined fabric parameter package includes: based on each fabric characteristic dimension, performing separate data fitting on the quantitative indicators of the new technological fabric and the existing fabric parameters to obtain independent fitting results of the new technological fabric and the existing fabric under a single characteristic dimension; and obtaining the combined fabric parameter package based on the independent fitting results.

[0010] In an implementation of the first aspect, obtaining the combined fabric parameter package according to the independent fitting result includes: obtaining a weight coefficient of each quantitative indicator; and obtaining the combined fabric parameter package according to the independent fitting result and the weight coefficient.

[0011] In an implementation of the first aspect, obtaining the combined fabric parameter package according to the independent fitting result and the weight coefficient includes: obtaining the score result of the existing fabric in each fabric characteristic dimension according to the independent fitting result and the weight coefficient, the score result being used to indicate the degree of matching between the existing fabric and the new technological fabric in the weighted characteristic dimension; and obtaining the combined fabric parameter package according to the score result.

[0012] In an implementation of the first aspect, obtaining the combined fabric parameter package according to the scoring result includes: obtaining existing fabrics in an existing fabric library that are related to the new technological fabric in key characteristics according to the scoring result; and combining the existing fabrics related to the key characteristics to obtain the combined fabric parameter package.

[0013] In the second aspect, the present application provides a new type of scientific and technological fabric identification and matching system, which includes: a fabric acquisition module for acquiring new scientific and technological fabrics; a quantification module for using a natural language model to quantify multiple fabric properties of the new scientific and technological fabrics to obtain multiple quantitative indicators, and the fabric properties of the new scientific and technological fabrics include fabric thickness, fabric elasticity, fabric smoothness and fabric weight; a parameter vector acquisition module for obtaining a comprehensive parameter vector based on the multiple quantitative indicators; a data fitting module for performing data fitting on the comprehensive parameter vector and the existing fabric parameter vector to obtain the overall similarity between the new scientific and technological fabric and the existing fabric; a threshold judgment module for performing a threshold judgment on the overall similarity to obtain a similarity judgment result; a fabric parameter package acquisition module for obtaining a fabric parameter package based on the similarity judgment result, and the fabric parameter package includes an overall fabric parameter package and a combined fabric parameter package.

[0014] In a third aspect, the present application provides an electronic device comprising: a memory storing a computer program; and a processor communicatively connected to the memory for executing the computer program to implement the above-mentioned method for identifying and matching novel technological fabrics.

[0015] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by an electronic device, implements the above-mentioned method for identifying and matching new technological fabrics.

[0016] As described above, the novel technical fabric identification and matching method, system, medium, and electronic device described in this application have the following beneficial effects:

[0017] (1) The natural language model is used to identify and quantitatively analyze the fabric properties of new technological fabrics, thereby improving the accuracy of fabric identification.

[0018] (2) The comprehensive parameter vector of the new technological fabric is obtained based on the multiple quantitative indicators after quantification of the new technological fabric. The parameters of the new technological fabric are fitted with the parameters in the existing fabric library, and the fabric parameter package of the new technological fabric that matches the existing fabric is obtained based on the similarity judgment results after data fitting, thereby improving the matching accuracy of the new technological fabric and the existing fabric. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 Shown is a schematic diagram of an application scenario of an embodiment of the present application.

[0020] Figure 2 Shown is a process diagram of the novel technical fabric identification and matching method described in an embodiment of the present application.

[0021] Figure 3 Shown is a schematic diagram of the process of obtaining a combined fabric parameter package as described in an embodiment of the present application.

[0022] Figure 4 Shown is a flow chart of the novel technical fabric identification and matching method described in an embodiment of the present application.

[0023] Figure 5 Shown is a structural schematic diagram of the new technical fabric identification and matching system described in an embodiment of the present application.

[0024] Figure 6 Shown is a structural schematic diagram of an electronic device described in an embodiment of the present application.

[0025] Component number description

[0026] 100 New Technology Fabric Parameter Package System

[0027] 101 Fabric Information Acquisition Module

[0028] 102 Fabric property quantitative analysis module

[0029] 103 Fabric parameter package acquisition module

[0030] 1. Identification and matching system for new technological fabrics

[0031] 11 Fabric Acquisition Module

[0032] 12 Quantization Module

[0033] 13 Parameter vector acquisition module

[0034] 14 Data Fitting Module

[0035] 15. Threshold judgment module

[0036] 16 Fabric parameter package acquisition module

[0037] 2 Electronic devices

[0038] 21 Memory

[0039] 22 processors

[0040] 23 Display

[0041] Steps S11 to S16

[0042] Steps S31-S32

[0043] Steps S100 to S106 DETAILED DESCRIPTION

[0044] The following describes the embodiments of the present application through specific examples. Those skilled in the art can easily understand the other advantages and effects of the present application from the content disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments. The details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other unless they conflict.

[0045] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present application. Therefore, the illustrations only show components related to the present application and are not drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component can be changed at will, and the component layout type may also be more complicated.

[0046] In the apparel industry, new high-tech fabrics are constantly emerging. These fabrics offer unique properties and advantages, significantly improving the functionality and comfort of clothing. Currently, the identification of fabric properties relies primarily on manual experience and traditional testing methods. Manual experience in judging fabric properties is subject to high subjectivity, low accuracy, and low efficiency. Different people may have significant differences in their judgments of the same fabric's properties, which can easily lead to deviations in fabric selection and application. Traditional testing methods, such as using specialized instruments and equipment to test fabric properties, while capable of producing relatively accurate results, are complex, costly, and time-consuming, making them unable to meet the rapidly developing apparel industry's demand for high-volume, efficient testing of new high-tech fabrics.

[0047] Furthermore, existing methods for matching the properties of new technical fabrics with existing fabric parameters lack systematicity and precision. They often rely on superficial comparisons, failing to conduct in-depth, comprehensive analysis and quantitative matching of multiple properties. This makes it difficult to provide scientific, comprehensive, and practical solutions when searching for similar fabrics or recommending appropriate parameter packages for new fabrics, limiting the rational application and promotion of new technical fabrics in apparel production.

[0048] Therefore, how to accurately identify the characteristics of new technological fabrics and effectively match them with existing fabric parameters has become an important issue facing the industry.

[0049] At least to address the above-mentioned issues, the following embodiments of the present application provide a method for identifying and matching new technological fabrics.

[0050] The technical solutions in the embodiments of the present application will be described in detail below with reference to the accompanying drawings in the embodiments of the present application.

[0051] Figure 1 The following is a schematic diagram of an application scenario in one embodiment of the present application. Figure 1 As shown, the new high-tech fabric parameter package system 100 includes a fabric information acquisition module 101, a fabric property quantitative analysis module 102, and a fabric parameter package acquisition module 103. The fabric information acquisition module 101 is used to obtain fabric information of the new high-tech fabric. The fabric property quantitative analysis module 102 uses a natural language model to perform quantitative analysis on the fabric information of the new high-tech fabric. The fabric parameter package acquisition module 103 compares the fabric parameter results of the quantitative analysis module 102 with the fabric parameters in the existing fabric library to obtain the parameter package of the new high-tech fabric.

[0052] Figure 2 Shown is a schematic diagram of the process of identifying and matching a novel technical fabric in one embodiment of the present application. Figure 2 As shown, the novel technical fabric identification and matching method includes the following steps S11 to S15:

[0053] Step S11, obtaining new technological fabrics.

[0054] In step S12, a natural language model is used to quantify various fabric properties of the novel technical fabric to obtain multiple quantitative indices. These fabric properties include thickness, elasticity, smoothness, and weight. Descriptive information about the novel technical fabric is input into the natural language model, which then learns and analyzes the information and outputs quantitative values ​​corresponding to the descriptive information. The input descriptive information about the novel technical fabric may be in the form of text or audio, but this application is not limited thereto.

[0055] For example, the natural language model is used to quantify the various fabric properties of the novel technical fabric to obtain multiple quantitative indicators, including:

[0056] 1) Quantify the thickness of the novel technical fabric using the natural language model to obtain a thickness quantification index. Input the thickness description information of the novel technical fabric into the natural language model, and output the corresponding quantified value of the fabric thickness through the natural language model. The quantified value of the fabric thickness serves as the thickness quantification index of the novel technical fabric. Set the fabric thickness to a continuous value range from extremely thin to extremely thick, and map the fabric thickness of the novel technical fabric to a specific value within the continuous value range. For example, the continuous value range of the fabric thickness is 1-10, where 1 represents an extremely thin novel technical fabric and 10 represents an extremely thick novel technical fabric.

[0057] 2) Quantifying the elasticity of the novel technical fabric using the natural language model to obtain an elasticity quantitative index. Inputting a description of the elasticity of the novel technical fabric into the natural language model, the natural language model outputs a quantified value of the corresponding elasticity. This quantified value of the elasticity serves as the elasticity quantitative index of the novel technical fabric. The fabric elasticity description may include the elasticity of the fabric and its resilience. The elasticity quantitative index may include elastic elongation and elastic recovery.

[0058] 3) Quantifying the smoothness of the novel technical fabric using the natural language model to obtain a smoothness quantification index. Inputting a description of the smoothness of the novel technical fabric into the natural language model, the natural language model outputs a quantified value corresponding to the smoothness of the fabric. This quantified value of the smoothness of the fabric serves as the smoothness quantification index. The smoothness quantification index may be a friction coefficient. For example, the friction coefficient of the novel technical fabric is 0.2.

[0059] 4) Quantifying the fabric weight of the novel technical fabric using the natural language model to obtain a grammage quantitative index. The natural language model is fed with a description of the fabric weight of the novel technical fabric, and the natural language model outputs a quantified value for the corresponding fabric weight. This quantified value serves as the grammage quantitative index. The unit of the grammage quantitative index is grams per square meter.

[0060] Furthermore, thickness can be measured using actual thickness measurements (in millimeters), elasticity can be measured using physical quantities such as Young's modulus, and smoothness can be measured using surface roughness. It's important to note that when adopting a different quantitative index system, the natural language model needs to be retrained and optimized to adapt to the new quantitative index requirements.

[0061] Step S13: Obtain a comprehensive parameter vector according to the multiple quantitative indicators.

[0062] For example, multiple quantitative indices of the fabric properties of the new technical fabric are combined into a vector to form a comprehensive parameter vector, and the comprehensive parameter vector is, for example, [thickness quantitative index, elasticity quantitative index, smoothness quantitative index, grammage quantitative index].

[0063] Step S14: performing data fitting on the comprehensive parameter vector and the existing fabric parameter vector to obtain the overall similarity between the new technological fabric and the existing fabric.

[0064] Exemplarily, existing fabric parameter vectors are stored in an existing fabric library. A data fit is performed between the comprehensive parameter vector of the new technical fabric and the existing fabric parameter vectors in the existing fabric library. The overall similarity between the comprehensive parameter vector of the new technical fabric and the parameter vectors of each fabric in the existing fabric library is calculated using a data fitting algorithm. The data fitting algorithm may be a Euclidean distance algorithm or a cosine similarity algorithm.

[0065] Furthermore, given that different algorithms have different characteristics and applicable scenarios when measuring data similarity, data fitting algorithms can also use algorithms such as the Pearson correlation coefficient and Mahalanobis distance. Among them, the Pearson correlation coefficient focuses on the linear correlation between the parameters of new technical fabrics and the parameters in the existing fabric library, while the Mahalanobis distance considers the covariance structure of the data and can, to a certain extent, eliminate the correlation and dimensionality effects between fabric parameters.

[0066] Step S15: A threshold is applied to the overall similarity to obtain a similarity determination result. A standard threshold is set and compared with the overall similarity to obtain a similarity determination result between the existing fabric and the new technological fabric. This similarity determination result represents the degree of similarity between the existing fabric and the new technological fabric. The standard threshold can be set based on the actual fabric conditions and is not limited to this.

[0067] Step S16: Obtain a fabric parameter package based on the similarity determination result. The fabric parameter package includes an overall fabric parameter package and a combined fabric parameter package. The fabric parameter package may include fabric composition, applicable scenarios, and washing and maintenance methods.

[0068] In one embodiment, obtaining a fabric parameter package based on the similarity determination result includes the following steps:

[0069] 21) When the overall similarity exceeds a threshold, a comprehensive fabric parameter package is obtained. This comprehensive fabric parameter package corresponds to existing similar fabrics. When the overall similarity exceeds the threshold, it indicates that the new high-tech fabric has a high degree of compatibility with the specific fabric. By evaluating the overall performance of the new high-tech fabric and existing fabrics, the accuracy of the decision is improved.

[0070] For example, to determine whether the new technological fabric matches the traditional polyester in existing fabrics, the comprehensive parameter vector of the new technological fabric is fitted with the comprehensive parameter vector of the traditional polyester to obtain the overall similarity. When the overall similarity is less than the standard threshold of 90%, it means that the new technological fabric does not match the traditional polyester in overall performance.

[0071] 22) When the overall similarity is less than the standard threshold, the multiple fabric properties of the new technological fabric are compared in independent dimensions to obtain a combined fabric parameter package.

[0072] For example, when the overall similarity is less than a standard threshold, it indicates that the comprehensive parameter vector of the new technical fabric has a low degree of overall performance match with the fabrics in the existing fabric library, resulting in significant differences. Therefore, in the event of a mismatch in overall similarity, the various fabric properties of the new technical fabric are broken down and individually compared with each fabric in the existing fabric parameter library based on the independent dimensions of quantitative indicators such as fabric thickness, fabric elasticity, fabric smoothness, and fabric weight to obtain a fabric parameter package. For example, a new technical fabric may be thinner than an existing fabric in terms of fabric thickness but more elastic. After breaking down the fabric properties, existing fabrics that match fabric thickness and fabric elasticity can be found separately, increasing the flexibility of fabric combination substitution.

[0073] Figure 3 Shown is a schematic diagram of the process of obtaining a combined fabric parameter package in one embodiment of the present application. Figure 3 As shown, the process of obtaining the combined fabric parameter package includes the following steps S31 to S32:

[0074] Step S31 : Based on each fabric characteristic dimension, the quantitative index of the new technological fabric is individually fitted with the existing fabric parameters to obtain an independent fitting result of the new technological fabric and the existing fabric under a single characteristic dimension.

[0075] For example, each characteristic dimension of a new technical fabric is broken down and analyzed separately against fabrics in the existing fabric library. The degree of fit between the new technical fabric and each fabric in the existing fabric library is compared across each characteristic dimension. By breaking down the new technical fabric, it is possible to identify existing fabrics that better match the new technical fabric in terms of thickness or elasticity.

[0076] Step S32: obtaining the combined fabric parameter package according to the independent fitting result.

[0077] For example, after independent fitting under a single characteristic dimension, we obtain fabric A that is more matching in fabric thickness, fabric B that is more matching in fabric elasticity, fabric C that is more matching in fabric smoothness, and fabric D that is more matching in fabric weight. Fabric A, fabric B, fabric C, and fabric D are combined to obtain a combined fabric parameter package for the new technological fabric.

[0078] In one embodiment, obtaining the combined fabric parameter package according to the independent fitting results includes the following steps:

[0079] 41) Obtain weight coefficients for each quantitative indicator. The weight coefficients can be set based on actual needs and experience, and this application does not impose any restrictions on this. For example, in some application scenarios, the importance of fabric elasticity is relatively high, so the fabric elasticity dimension is given a higher weight coefficient of 0.4, the fabric thickness can be 0.2, the fabric smoothness can be 0.2, and the fabric weight can be 0.2.

[0080] 42) Obtaining the combined fabric parameter package according to the independent fitting results and the weight coefficients.

[0081] In one embodiment, obtaining the combined fabric parameter package according to the independent fitting results and the weight coefficients includes the following steps:

[0082] 51) Obtaining a score for the existing fabric in each fabric characteristic dimension based on the independent fitting results and the weight coefficients. The score indicates the degree of matching between the existing fabric and the novel technological fabric in the weighted characteristic dimensions.

[0083] For example, when the fabric elasticity of the new technological fabric accounts for a larger proportion in each fabric characteristic dimension, a weight is assigned to each fabric characteristic dimension, and the matching score of the new technological fabric with each fabric in the existing fabric parameter library in the weighted characteristic dimension is calculated. When the weight of the new technological fabric in fabric elasticity is higher and the fabric elasticity of the existing fabric A is closer, the score of the existing fabric A in the fabric elasticity dimension is higher.

[0084] 52) Obtaining the combined fabric parameter package according to the scoring result.

[0085] In one embodiment, obtaining the combined fabric parameter package according to the scoring result includes the following steps:

[0086] 61) Based on the scoring results, existing fabrics in the existing fabric library that are related to the new technological fabric in terms of key characteristics are obtained. The key characteristics can be those with higher weight coefficients or those required, and are specifically determined based on actual conditions.

[0087] 62) Combining existing fabrics related to key characteristics to obtain the combined fabric parameter package.

[0088] For example, when the overall similarity between a new technical fabric and an existing fabric falls below a threshold, it indicates a low degree of match. By breaking down the fabric properties of the new technical fabric and comparing them across individual dimensions, we can identify existing fabrics that match the new technical fabric in key characteristics. By combining several existing fabrics that match these key characteristics, we can create a combined fabric parameter package that partially replaces the new technical fabric's characteristics.

[0089] The following describes in detail the novel technical fabric identification and matching method provided in the embodiments of this application through a specific example. It should be noted that the content of this example is intended solely to illustrate and describe the novel technical fabric identification and matching method provided in the embodiments of this application, and is not intended to limit the scope of protection of this application in any way. In specific applications, appropriate steps may be added or deleted based on this example according to actual needs. Figure 4 The flowchart of the identification and matching method of the new technical fabric in this example is shown. Figure 4 As shown, the identification and matching method of the new technical fabric in this example includes the following steps.

[0090] Step S100: quantifying various fabric properties of the new technical fabric using a natural language model to obtain quantitative indicators corresponding to the various fabric properties.

[0091] Step S101: combining multiple quantitative indicators to obtain a comprehensive parameter vector of the new technological fabric.

[0092] Step S102 : performing data fitting on the comprehensive parameter vector of the new technical fabric and the parameter vectors of existing fabrics in the existing fabric library to obtain the overall similarity between the new technical fabric and the existing fabrics.

[0093] Step S103: compare and judge the overall similarity with the standard threshold. When the overall similarity is greater than the standard threshold, the parameter package corresponding to the existing fabric is used as the fabric parameter package of the new technical fabric.

[0094] Step S104: When the overall similarity is less than the standard threshold, the various fabric properties of the new technological fabric are decomposed and compared in separate dimensions to obtain independent fitting results of the new technological fabric and the existing fabric in a single characteristic dimension.

[0095] Step S105: Obtain the weight coefficient of each quantitative index, and obtain the score result under each fabric characteristic dimension according to the weight coefficient and the independent fitting result.

[0096] Step S106, obtaining existing fabrics related to key characteristics of the new technological fabric based on the scoring results, and combining the existing fabrics related to key characteristics to obtain a combined fabric parameter package after partial replacement of the new technological fabric.

[0097] It should be noted that the above-mentioned numbers S100 to S106 are only used to mark different steps, rather than to limit the execution order of these steps.

[0098] In summary, this application utilizes a natural language model to identify the fabric properties of new technical fabrics and obtains quantitative indices of the new technical fabric properties through quantitative analysis of the natural language model. This reduces the subjectivity of manual judgment, enables more accurate determination of various fabric property indicators, and improves the accuracy of fabric property identification. By combining multiple quantitative indices to obtain a comprehensive parameter vector, the comprehensive parameter vector of the new technical fabric is fitted with the comprehensive parameters in an existing fabric library to obtain the overall similarity between the new technical fabric and the existing fabric. This overall similarity is then used to evaluate the overall performance of the new technical fabric and the existing fabric. When the overall similarity between the new technical fabric and the existing fabric falls below a threshold, the new technical fabric is determined to be mismatched in overall performance. In this case, the fabric properties of the new technical fabric are decomposed, and the new technical fabric is individually fitted and analyzed with fabrics in the existing fabric library along each fabric property dimension. This results in a matching result for each fabric property of the new technical fabric with that of the existing fabric. Key properties of the desired fabric are assigned corresponding weight coefficients, and scores are calculated based on the weight coefficients and the independent fitting results of the individual properties. Based on the scores, a combined fabric parameter package for the new technical fabric is obtained. This application not only takes into account the single characteristics of the fabric, but also comprehensively analyzes multiple characteristics such as thickness, elasticity, smoothness, and weight. Through similarity calculation and characteristic dimension decomposition and matching, weights are set according to the importance of different characteristic dimensions, making the fitting results with the existing fabric parameter library more accurate, and the parameter package recommendations provided for new fabrics are more in line with actual needs.

[0099] The scope of protection of the method for identifying and matching new technological fabrics described in the embodiment of the present application is not limited to the order of execution of the steps listed in this embodiment. All solutions implemented by adding, subtracting, or replacing steps in the prior art based on the principles of the present application are included in the scope of protection of the present application.

[0100] The embodiments of the present application also provide a new type of scientific and technological fabric identification and matching system, which can implement the new type of scientific and technological fabric identification and matching method described in the present application. However, the implementation device of the new type of scientific and technological fabric identification and matching method described in the present application includes but is not limited to the structure of the new type of scientific and technological fabric identification and matching system listed in this embodiment. All structural deformations and replacements of the existing technology made according to the principles of the present application are included in the protection scope of the present application.

[0101] Figure 5 Shown is a schematic diagram of the structure of the identification and matching system of the new technology fabric in one embodiment of the present application. Figure 5 As shown, the novel technical fabric identification and matching system 1 includes: a fabric acquisition module 11, a quantification module 12, a parameter vector acquisition module 13, a data fitting module 14, a threshold determination module 15, and a fabric parameter package acquisition module 16. The fabric acquisition module 11 is used to acquire novel technical fabrics. The quantification module 12 is used to quantify the various fabric properties of the novel technical fabric using a natural language model to obtain multiple quantitative indices. The fabric properties of the novel technical fabric include fabric thickness, fabric elasticity, fabric smoothness, and fabric weight. The parameter vector acquisition module 13 is used to obtain a comprehensive parameter vector based on the multiple quantitative indices. The data fitting module 14 is used to perform data fitting on the comprehensive parameter vector with existing fabric parameter vectors to determine the overall similarity between the novel technical fabric and existing fabrics. The threshold determination module 15 is used to perform a threshold determination on the overall similarity to obtain a similarity determination result. The fabric parameter package acquisition module 16 is used to obtain a fabric parameter package based on the similarity determination result. The fabric parameter package includes an overall fabric parameter package and a combined fabric parameter package.

[0102] It should be noted that Figure 5 The modules in the identification and matching system 1 of the new technical fabric shown are Figure 2 The steps in the identification and matching method of the novel technical fabric correspond to each other and are not described in detail here.

[0103] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices or methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of modules / units is only a logical function division. There may be other division methods in actual implementation. For example, multiple modules or units can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules or units, which can be electrical, mechanical or other forms.

[0104] The modules / units described as separate components may or may not be physically separate, and the components displayed as modules / units may or may not be physical modules, that is, they may be located in one place or distributed across multiple network elements. Some or all of the modules / units may be selected according to actual needs to achieve the purpose of the embodiments of the present application. For example, the functional modules / units in the various embodiments of the present application may be integrated into a processing module, or each module / unit may exist physically separately, or two or more modules / units may be integrated into a single module / unit.

[0105] Those skilled in the art should further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the composition and steps of each example according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0106] The present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the novel technology fabric identification and matching method provided by the present application embodiment. A person skilled in the art will appreciate that all or part of the steps in the method for implementing the above embodiment can be completed by instructing the processor through a program, and the program can be stored in a computer-readable storage medium, and the storage medium is a non-transitory medium, such as a random access memory, a read-only memory, a flash memory, a hard disk, a solid-state drive, a magnetic tape, a floppy disk, an optical disc, and any combination thereof. The above storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more available media. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a digital video disc (DVD)), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0107] An embodiment of the present application may also provide an electronic device. Figure 6 The diagram shows the structure of the electronic device 2 in one embodiment of the present application. Figure 6 As shown, in this embodiment, the electronic device 2 includes a memory 21 and a processor 22 .

[0108] The memory 21 is used to store computer programs. In some possible implementations, the memory 21 may include various media capable of storing program codes, such as ROM, RAM, a magnetic disk, a USB flash drive, a memory card, or an optical disk.

[0109] In the embodiment of the present application, the memory 21 may include a computer system readable medium in the form of a volatile memory, such as RAM and / or cache memory. The electronic device 2 may further include other removable / non-removable, volatile / non-volatile computer system storage media. The memory 21 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the various embodiments of the present application.

[0110] The processor 22 is connected to the memory 21 and is used to execute the computer program stored in the memory 21 so that the electronic device 2 can execute the identification and matching method of the new technical fabric.

[0111] Exemplarily, the processor 22 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc. In other embodiments, the processor 22 may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0112] In some implementations, the electronic device 2 provided in the embodiment of the present application may further include a display 23. The display 23 is communicatively connected to the memory 21 and the processor 22, and is configured to display a graphical user interface (GUI) related to the identification and matching method of the new technical fabric.

[0113] In the embodiment of the present application, the display 23 may include a display screen (display panel). In some implementations, the display panel may be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like. In addition, the display 23 may also be a touch panel (touch screen, touch screen), which may include a display screen and a touch-sensitive surface. When the touch-sensitive surface detects a touch operation on or near it, it is transmitted to the processor 22 to determine the type of touch event, and then the processor 22 provides a corresponding visual output on the display device according to the type of touch event.

[0114] The descriptions of the processes or structures corresponding to the above figures have different emphases. For parts that are not described in detail in a certain process or structure, please refer to the relevant descriptions of other processes or structures.

[0115] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Anyone skilled in the art may modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by one of ordinary skill in the art without departing from the spirit and technical concepts disclosed in this application shall be covered by the claims of this application.

Claims

1. A new type of technical fabric identification and matching method, characterized in that: The identification and matching method of the novel technical fabric includes: access to new technical fabrics; quantifying multiple fabric properties of the novel technical fabric using a natural language model to obtain multiple quantitative indicators, wherein the fabric properties of the novel technical fabric include fabric thickness, fabric elasticity, fabric smoothness, and fabric weight; Obtaining a comprehensive parameter vector according to the multiple quantitative indicators; Performing data fitting on the comprehensive parameter vector and the existing fabric parameter vector to obtain the overall similarity between the new technological fabric and the existing fabric; Perform threshold judgment on the overall similarity to obtain the similarity judgment result; A fabric parameter package is obtained based on the similarity judgment result, where the fabric parameter package includes an overall fabric parameter package and a combined fabric parameter package.

2. The method for identifying and matching novel technical fabrics according to claim 1, characterized in that: The natural language model is used to quantify the various fabric properties of the new technical fabric to obtain multiple quantitative indicators including: quantifying the thickness of the novel technical fabric using the natural language model to obtain a thickness quantification index; quantifying the elasticity of the novel technical fabric using the natural language model to obtain an elasticity quantitative index; quantifying the smoothness of the novel technical fabric using the natural language model to obtain a smoothness quantification index; The natural language model is used to quantify the fabric weight of the novel technical fabric to obtain a quantified index of the fabric weight.

3. The method for identifying and matching novel technical fabrics according to claim 1, characterized in that: The package for obtaining fabric parameters based on the similarity judgment result includes: When the overall similarity is greater than a standard threshold, an overall fabric parameter package is obtained, where the overall fabric parameter package is a parameter package corresponding to an existing similar fabric; When the overall similarity is less than the standard threshold, independent dimension comparison is performed on multiple fabric properties of the new technical fabric to obtain a combined fabric parameter package.

4. The method for identifying and matching novel technical fabrics according to claim 3, characterized in that: The process of comparing the characteristics of the new technical fabric in multiple dimensions to obtain the combined fabric parameter package includes: Based on the characteristic dimensions of each fabric, the quantitative indicators of the new technical fabric are individually fitted with the parameters of the existing fabric to obtain independent fitting results of the new technical fabric and the existing fabric under a single characteristic dimension; The combined fabric parameter package is obtained according to the independent fitting results.

5. The method for identifying and matching novel technical fabrics according to claim 4, characterized in that: The package for obtaining the combined fabric parameters according to the independent fitting results includes: Obtain the weight coefficient of each quantitative indicator; The combined fabric parameter package is obtained according to the independent fitting results and the weight coefficients.

6. The method for identifying and matching novel technical fabrics according to claim 5, characterized in that: The package for obtaining the combined fabric parameter according to the independent fitting result and the weight coefficient includes: Obtaining a score result of the existing fabric in each fabric characteristic dimension according to the independent fitting result and the weight coefficient, wherein the score result is used to indicate the degree of matching between the existing fabric and the new technological fabric in the weighted characteristic dimension; The combined fabric parameter package is obtained according to the score result.

7. The method for identifying and matching novel technical fabrics according to claim 6, characterized in that: The package for obtaining the combined fabric parameters according to the score result includes: Obtain existing fabrics in an existing fabric library that are related to the new technical fabric in terms of key properties according to the scoring results; Existing fabrics with related key characteristics are combined to obtain the combined fabric parameter package.

8. A new type of technical fabric identification and matching system, characterized by: The identification and matching system of the new technical fabric includes: Fabric acquisition module, used to obtain new technological fabrics; a quantification module, configured to quantify various fabric properties of the novel technical fabric using a natural language model to obtain a plurality of quantitative indicators, wherein the fabric properties of the novel technical fabric include fabric thickness, fabric elasticity, fabric smoothness, and fabric weight; A parameter vector acquisition module, configured to acquire a comprehensive parameter vector according to the plurality of quantitative indicators; A data fitting module is used to perform data fitting on the comprehensive parameter vector and the existing fabric parameter vector to obtain the overall similarity between the new technical fabric and the existing fabric; A threshold judgment module is used to perform a threshold judgment on the overall similarity to obtain a similarity judgment result; The fabric parameter package acquisition module is used to acquire a fabric parameter package based on the similarity judgment result, and the fabric parameter package includes an overall fabric parameter package and a combined fabric parameter package.

9. An electronic device, characterized in that: The electronic device comprises: a memory having a computer program stored thereon; A processor is communicatively connected to the memory and is used to execute the computer program to implement the method for identifying and matching the novel technical fabric according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by an electronic device, the identification and matching method of the novel technical fabric according to any one of claims 1 to 7 is realized.

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