A method for predicting color fastness of a textile

Abstract

The application discloses a kind of textile color color fastness prediction method, after obtaining the fastness grade of different concentrations of basic color sample by using existing color fastness test standard detection, it is converted into fastness value, and according to different concentrations of basic color sample and corresponding fastness value, a concentration-fastness linear relationship matrix is constructed, the fastness value corresponding to each dye in the color sample formula of the textile to be evaluated is obtained by concentration-fastness linear relationship matrix and is corrected, then the minimum value of the corrected fastness value is converted into fastness grade as color fastness prediction result and is output.

Description

Technical Field

[0001] This invention relates to the field of textile color prediction, and more specifically to a method for predicting the color fastness of textiles. Background Technology

[0002] Color fastness (also known as dyeing fastness) of textiles refers to the ability of textiles to maintain their original color when subjected to various physical or chemical factors during processing or use. Generally, based on the factors causing fading or discoloration, it can be divided into wash fastness, light fastness, perspiration fastness, and rubbing fastness. Currently, three commonly used testing standards are: ISO (International Organization for Standardization), AATCC (American Association of Colorists and Chemists), and GB / T (China). The fastness grade is determined based on the color change of the sample and the staining of the lining fabric; a higher grade indicates better performance.

[0003] Colorfastness performance affects the aesthetic appearance of textiles and human health and safety, making it a crucial indicator of textile quality. However, in practical applications, the most common method for assessing the colorfastness of textiles is to test a sample. If no sample is available, it must be prepared before testing can begin. This process is time-consuming, taking anywhere from one to two to three days, and is inefficient. This is especially problematic for dyeing and printing factories. After receiving an order and going through several rounds of sampling to obtain the required color sample, if the tested colorfastness does not meet customer requirements, a new sample must be produced, which is not only time-consuming and labor-intensive but also carries the risk of delivery delays.

[0004] There is a wealth of information on color fastness of textiles, but very little research is available on the prediction of color fastness. To the inventor's knowledge, only a few publications (e.g., "Support Vector Machine Classification Model for Wash Fastness of Reactive Dyes," Journal of Hunan Institute of Engineering, Huang Lei, Yu Xinliang, et al., 2018, 28(4): 62-66; "Classification Model for Ironing Fastness of Vat Dyes," Journal of Hunan Institute of Engineering, Qiu Jianxia, ​​Huang Lei, et al., 2018, 38(2): 09-13) have conducted research on this topic. The aforementioned publications used the Support Vector Machine (SVC) classification model and the Structure-Reactivity Relationship (SAR) model, respectively, to predict the wash fastness of reactive dyes and the ironing fastness of vat dyes. The overall prediction accuracy was 84.1% and 83.9%, respectively, which has some reference value. However, the above prediction methods can only predict one fastness of a single dye and cannot provide a specific fastness grade; they can only determine whether the fastness is greater than or less than a set fastness grade. In practical applications, most color samples are prepared from two or more dyes, requiring testing of multiple fastness indicators and specific fastness grades. Therefore, the above prediction method has significant limitations and is quite difficult to apply in practice. Summary of the Invention

[0005] The following provides a brief overview of one or more aspects to offer a basic understanding of them. This overview is not an exhaustive summary of all conceived aspects, nor is it intended to identify key or decisive elements of all aspects, nor to define the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form to prepare for the more detailed descriptions that follow.

[0006] The purpose of this invention is to solve the above-mentioned problems and provide a method for predicting the color fastness of textiles. This method uses color fastness testing standards to detect the fastness grades of base color samples of different concentrations and converts them into fastness values. A concentration-fastness linear relationship matrix is ​​constructed based on the fastness values ​​corresponding to the base color samples of different concentrations. The fastness values ​​corresponding to each dye in the color sample formulation of the textile to be evaluated are obtained through this concentration-fastness linear relationship matrix. After correction, the minimum value is selected and converted into a fastness grade, which is then output as the color fastness prediction result.

[0007] The technical solution of this invention is as follows:

[0008] This invention provides a method for predicting the color fastness of textiles, comprising the following steps:

[0009] Based on different dye concentrations, blank fabrics are dyed with dyes of the corresponding dye types to obtain basic color samples;

[0010] Based on the fabric type and fastness items of the basic color sample, the fastness grades corresponding to different concentrations of basic color samples were tested.

[0011] The fastness grades of the base color samples are converted into fastness values, and a concentration-fastness linear relationship matrix is ​​constructed based on the concentration of the base color samples and the corresponding fastness values.

[0012] Obtain the color sample formula of the textile to be evaluated, and obtain the fastness value of the dye in the color sample formula of the textile to be evaluated based on the concentration-fastness linear relationship matrix.

[0013] Correct the colorfastness value and convert the minimum corrected colorfastness value into a colorfastness grade as the output of the colorfastness prediction result.

[0014] According to one embodiment of the textile color fastness prediction method of the present invention, the dye type includes reactive dyes, disperse dyes, and acid dyes, and the fabric type includes cotton, cotton-spandex blends, polyester, polyester-spandex blends, nylon, nylon-spandex blends, and wool. The textile color fastness prediction method detects the fastness grades of basic color samples of different concentrations according to the color fastness test standard, and then converts the fastness grades of basic color samples of different concentrations into fastness values ​​according to the fastness value conversion method.

[0015] According to an embodiment of the color fastness prediction method for textiles of the present invention, the fastness value conversion method includes:

[0016] If the fastness rating is an integer, then the fastness value is the fastness rating value;

[0017] If the fastness rating is an interval rating, then the fastness value is the median value of the two fastness rating values.

[0018] According to one embodiment of the textile color fastness prediction method of the present invention, after obtaining the fastness values ​​of basic color samples of different concentrations, the method constructs a concentration-fastness linear relationship matrix based on the concentration of the basic color samples and the corresponding fastness values. The constructed matrix is ​​as follows:

[0019]

[0020] Where m is the number of concentrations of the basic color samples, n is the number of fastness types, and F mn This is the fastness value of the nth fastness type corresponding to the mth concentration of the base color sample.

[0021] According to an embodiment of the textile color fastness prediction method of the present invention, the textile color fastness prediction method uses a piecewise linear function of fastness to calculate the fastness value corresponding to each point in the concentration-fastness linear relationship matrix, thereby constructing the concentration-fastness linear relationship matrix; wherein, the calculation formula of the piecewise linear function of fastness is as follows:

[0022]

[0023] Among them, F j This represents the fastness value of the dye product at the j-th point;

[0024] x i This represents the concentration of the dye product at point i.

[0025] x i-1 This indicates the concentration of the dye product at point i-1.

[0026] y i-1 This represents the fastness value of the dye product at point i-1.

[0027] y i This represents the fastness value of the dye product at the i-th point.

[0028] According to one embodiment of the method for predicting the color fastness of textiles according to the present invention, the color sample formulation of the textile to be evaluated includes one or more dyes, and the fastness values ​​of each dye in the color sample formulation of the textile to be evaluated are obtained according to the concentration-fastness linear relationship matrix; wherein, the color sample formulation includes the dye product name and the corresponding concentration value.

[0029] According to one embodiment of the textile color fastness prediction method of the present invention, after obtaining the fastness values ​​of each dye in the color sample formulation of the textile to be evaluated, the method corrects the fastness values ​​using a fastness value correction formula to obtain the corrected fastness values; wherein, the fastness correction formula is as follows:

[0030]

[0031] ;in, This represents the corrected fastness value for the i-th dye.

[0032] μ i Let be the correction factor corresponding to the i-th dye.

[0033] F i This represents the fastness value of the i-th dye.

[0034] According to one embodiment of the color fastness prediction method for textiles of the present invention, after obtaining the corrected fastness value, the method takes the minimum fastness value as the fastness value corresponding to the color sample of the textile to be evaluated, and then converts the fastness value of the color sample of the textile to be evaluated into the corresponding fastness grade as the color fastness prediction result of the textile to be predicted.

[0035] According to an embodiment of the color fastness prediction method for textiles of the present invention, the fastness value is expressed as a + 0.1b; where a and b are both natural numbers from 0 to 9. The color fastness prediction method for textiles uses the following conversion method to convert the fastness value into the corresponding fastness grade:

[0036] When a = 0, the fastness grade is 1;

[0037] When a≥1 and b<3, the fastness grade is "a";

[0038] When a≥1 and 3≤b≤7, the fastness grade is “a-a+1”.

[0039] When a≥1 and 7<b≤9, the fastness grade is “a+1”.

[0040] Compared with existing technologies, this invention offers the following advantages: After obtaining the fastness grades of basic color samples at different concentrations using existing color fastness testing standards, these grades are converted into fastness values. A concentration-fastness linear relationship matrix is ​​then constructed based on the fastness values ​​corresponding to the basic color samples at different concentrations. Through this matrix, the fastness values ​​of each dye in the color sample formulation of the textile to be evaluated can be quickly obtained. These values ​​are then converted into fastness grades using a fastness grade conversion method, thus facilitating the rapid acquisition of various fastness grades for the color sample formulation of the textile to be evaluated, improving the efficiency of color fastness prediction. Furthermore, this invention overcomes the limitation of existing prediction methods that can only predict one fastness grade for a single dye at a time. It can simultaneously predict multiple fastness grades for formulations containing multiple dyes and obtain specific fastness grades, making it highly practical in actual production applications. In addition, this invention constructs a piecewise linear function to optimize the relationship between dye concentration and fastness values, thereby improving the accuracy of the prediction results. Attached Figure Description

[0041] The above-described features and advantages of the present invention will be better understood after reading the following detailed description of embodiments of the present disclosure in conjunction with the accompanying drawings. In the drawings, components are not necessarily drawn to scale, and components having similar related characteristics or features may have the same or similar reference numerals.

[0042] Figure 1 This is a flowchart illustrating an embodiment of the textile color fastness prediction method of the present invention. Detailed Implementation

[0043] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. It should be noted that the aspects described below with reference to the accompanying drawings and specific embodiments are merely exemplary and should not be construed as limiting the scope of protection of the present invention in any way.

[0044] An embodiment of a method for predicting the color fastness of textiles is disclosed herein. Figure 1 This is a flowchart illustrating an embodiment of the textile color fastness prediction method of the present invention. Please refer to... Figure 1 The following is a detailed description of each step in the method for predicting the color fastness of textiles.

[0045] Step S1: Dye the blank fabric with the corresponding dye type according to different dye concentrations to obtain a basic color sample.

[0046] In this embodiment, the dye concentration range is 0-10%, and it is divided into 10-20 concentrations according to the pre-grade classification standard. The blank fabric sample is dyed according to the different concentrations to serve as the basic color sample.

[0047] Step S2: Based on the fabric type and fastness items of the basic color sample, the fastness grade corresponding to different concentrations of basic color sample is obtained.

[0048] In this embodiment, the blank fabrics and corresponding dyes used to create the basic color samples are divided into several categories. The dye types include reactive dyes, disperse dyes, and acid dyes; the fabric types include cotton, cotton-spandex blends, polyester, polyester-spandex blends, nylon, nylon-spandex blends, and wool. The color fastness prediction method for textiles, after detecting the corresponding fastness grades of different concentrations of basic color samples according to color fastness testing standards, converts the fastness grades of different concentrations of basic color samples into fastness values ​​using a fastness value conversion method.

[0049] Specifically, in this embodiment, the color fastness testing standards include ISO (International Organization for Standardization), AATCC (American Association of Colorists and Chemists), and GB / T (Chinese National Standard). One or more of these standards can be selected according to the testing requirements to detect the fastness grades of basic color samples of different concentrations.

[0050] Step S3: Convert the fastness grade of the base color sample into a fastness value, and construct a concentration-fastness linear relationship matrix based on the concentration of the base color sample and the corresponding fastness value.

[0051] In this embodiment, after the color fastness prediction method for textiles obtains the fastness grades of basic color samples at different concentrations, it converts these grades into fastness values ​​using a fastness value conversion method. Specifically, if the fastness grade is an integer grade, the fastness value is the corresponding fastness grade value; if the fastness grade is an interval grade, the fastness value is the median of the two fastness grade values. For example, if the fastness grade is 1, the converted fastness value is 1; if the fastness grade is between 1 and 2, the converted fastness value is 1.5. After obtaining the fastness values ​​of basic color samples at different concentrations using this conversion method, a concentration-fastness linear relationship matrix is ​​constructed based on the concentration of the basic color sample and the corresponding fastness value. The constructed matrix is ​​as follows:

[0052]

[0053] Where m is the number of concentration grades for the basic color sample, n is the number of fastness types, and F mn This matrix represents the fastness value of the nth fastness type corresponding to the mth concentration of the base color sample. Using this matrix, the fastness rating corresponding to different concentration values ​​can be quickly obtained.

[0054] Furthermore, in this embodiment, the method for predicting the color fastness of textiles also employs a piecewise linear function of fastness to calculate the fastness value corresponding to each point in the concentration-fastness linear relationship matrix, thereby constructing the concentration-fastness linear relationship matrix. The formula for calculating the piecewise linear function of fastness is as follows:

[0055]

[0056] Among them, F j This represents the fastness value of the dye product at the j-th point; x i x represents the concentration of the dye product at point i. i-1 y represents the concentration of the dye product at point i-1. i-1 y represents the fastness value of the dye product at point i-1. i This represents the fastness value of the dye product at the i-th point.

[0057] Step S4: Obtain the color sample formula of the textile to be evaluated, and obtain the fastness value of the dye in the color sample formula of the textile to be evaluated according to the concentration-fastness linear relationship matrix.

[0058] In this embodiment, after the color fastness prediction method for textiles constructs a concentration-fastness linear relationship matrix using a basic color sample, the color sample formula of the textile to be evaluated is input into it to obtain the fastness values ​​of each dye in the color sample formula of the textile to be evaluated. The color sample formula includes the dye product name Ai and the corresponding concentration Ci, and the dyes in the color sample formula are included in all the dyes used to make the basic color sample. Based on the dye product name Ai and the corresponding concentration Ci in the color sample formula, the corresponding fastness values ​​can be obtained by traversing the concentration-fastness linear relationship matrix.

[0059] Furthermore, in this embodiment, the fastness value obtained through the concentration-fastness linear relationship matrix is ​​corrected using a fastness correction formula to obtain the corrected fastness value. The fastness correction formula is as follows:

[0060]

[0061] in, μ represents the fastness value of the i-th dye after correction. i F is the correction factor corresponding to the i-th dye. i This represents the fastness value of the i-th dye. After obtaining the corrected fastness value, the color fastness prediction method for textiles uses the minimum fastness value as the corresponding fastness value of the color sample of the textile to be evaluated, and then converts this fastness value into the corresponding fastness grade as the output of the color fastness prediction result of the textile to be predicted.

[0062] Specifically, in this embodiment, the fastness value is represented by the form a+0.1b, where a and b are both natural numbers from 0 to 9. The color fastness prediction method for textiles uses the following conversion methods to convert the fastness value into the corresponding fastness grade: (1) When a = 0, the fastness grade is grade 1, for example: the fastness value is 0.8, and the converted fastness grade is grade 1; (2) When a ≥ 1 and b < 3, the fastness grade is "a", for example: the fastness value is 1.2, and the converted fastness grade is grade 1; (3) When a ≥ 1 and 3 ≤ b ≤ 7, the fastness grade is "a-a+1", for example: the fastness value is 1.6, and the converted fastness grade is grade 1-2; (4) When a ≥ 1 and 7 < b ≤ 9, the fastness grade is "a+1", for example: the fastness value is 1.9, and the converted fastness grade is grade 2.

[0063] The prior description of this disclosure is provided to enable any person skilled in the art to make or use this disclosure. Various modifications to this disclosure will be apparent to those skilled in the art, and the general principles defined herein may be applied to other variations without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not intended to be limited to the examples and designs described herein, but should be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0064] Those skilled in the art will further appreciate that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments disclosed herein can be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate this interchangeability between hardware and software, the various illustrative components, blocks, modules, circuits, and steps are described above in a generalized manner in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. Those skilled in the art may implement the described functionality in different ways for each specific application, but such implementation decisions should not be construed as departing from the scope of the invention.

[0065] The various illustrative logic blocks, modules, and circuits described in conjunction with the embodiments disclosed herein can be implemented or performed using a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. The general-purpose processor may be a microprocessor, but in alternatives, it may be any conventional processor, controller, microcontroller, or state machine. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors cooperating with a DSP core, or any other such configuration.

[0066] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of both. The software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor such that the processor can read and write information to / from the storage medium. In an alternative, the storage medium may be integrated into the processor. The processor and storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In an alternative, the processor and storage medium may reside as discrete components in the user terminal.

[0067] In one or more exemplary embodiments, the described functionality may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functionality may be stored or transmitted as one or more instructions or code on or through a computer-readable medium. A computer-readable medium includes both computer storage media and communication media, encompassing any medium that facilitates the transfer of a computer program from one location to another. A storage medium may be any available medium accessible to a computer. By way of example and not limitation, such a computer-readable medium may include RAM, ROM, EEPROM, CD-ROM or other optical disc storage, disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and is accessible to a computer. Any connection is also legitimately referred to as a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of a medium. As used in this article, disk and disc include compact discs (CDs), laser discs, optical discs, digital multi-purpose discs (DVDs), floppy disks, and Blu-ray discs. Disks typically reproduce data magnetically, while discs reproduce data optically using lasers. Combinations of these should also be included within the scope of computer-readable media.

Claims

1. A method for predicting the color fastness of textiles, characterized in that, Includes the following steps; Based on different dye concentrations, blank fabrics are dyed with dyes of the corresponding dye types to obtain basic color samples; Based on the fabric type and fastness items of the basic color sample, the fastness grades corresponding to different concentrations of basic color samples were obtained. The fastness grades of the base color samples are converted into fastness values, and a concentration-fastness linear relationship matrix is ​​constructed based on the concentration of the base color samples and the corresponding fastness values. Obtain the color sample formula of the textile to be evaluated, which includes one or more dyes, and obtain the fastness value of each dye in the color sample formula of the textile to be evaluated according to the concentration-fastness linear relationship matrix. The color sample formula includes the dye product name and the corresponding concentration value. Correct the colorfastness value and convert the minimum value of the corrected colorfastness value into a colorfastness grade as the output of the colorfastness prediction result; The concentration-fastness linear relationship matrix is ​​constructed as follows: ； Where m is the number of concentrations of the basic color samples, n is the number of fastness types, and F mn This is the fastness value of the nth fastness type corresponding to the mth concentration of the base color sample.

2. The method for predicting the color fastness of textiles according to claim 1, characterized in that, The dye types include reactive dyes, disperse dyes, and acid dyes. The fabric types include cotton, cotton-spandex blends, polyester, polyester-spandex blends, nylon, nylon-spandex blends, and wool. The method for predicting the color fastness of textiles involves detecting the fastness grades of basic color samples of different concentrations according to the color fastness testing standards, and then converting the fastness grades of the basic color samples of different concentrations into fastness values ​​according to the fastness value conversion method.

3. The method for predicting the color fastness of textiles according to claim 2, characterized in that, The method for converting the strength value includes: If the fastness rating is an integer, then the fastness value is the fastness rating value; If the fastness rating is an interval rating, then the fastness value is the median value of the two fastness rating values.

4. The method for predicting the color fastness of textiles according to claim 1, characterized in that, The method for predicting the color fastness of textiles uses a piecewise linear function to calculate the fastness value corresponding to each point in the concentration-fastness linear relationship matrix, thereby constructing the concentration-fastness linear relationship matrix; wherein, the calculation formula of the piecewise linear function is as follows: ； in, This represents the fastness value of the dye product at the j-th point; This represents the concentration of the dye product at point i. This indicates the concentration of the dye product at point i-1. This represents the fastness value of the dye product at point i-1. This represents the fastness value of the dye product at the i-th point.

5. The method for predicting the color fastness of textiles according to claim 1, characterized in that, The method for predicting the color fastness of textiles obtains the fastness values ​​of each dye in the color sample formula of the textile to be evaluated, and then corrects the fastness values ​​using a fastness value correction formula to obtain the corrected fastness values; wherein, the fastness value correction formula is as follows: ； in, This represents the corrected fastness value for the i-th dye. Let be the correction factor corresponding to the i-th dye. This represents the fastness value of the i-th dye.

6. The method for predicting the color fastness of textiles according to claim 5, characterized in that, The color fastness value of the textile sample to be evaluated is expressed as a + 0.1b; where a and b are both natural numbers from 0 to 9. The color fastness prediction method for textiles uses the following conversion method to convert the fastness value into the corresponding fastness grade: When a=0, the fastness grade is 1; When a≥1 and b<3, the fastness grade is "a"; When a≥1 and 3≤b≤7, the fastness grade is "a to a+1"; When a≥1 and 7<b≤9, the fastness grade is "a+1".

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