A dynamic evaluation system for color fastness of textile fabric

Abstract

The application discloses a kind of textile fabric color fastness dynamic evaluation system, it is related to optical detection field, including: regular module, for fetching the textile fabric to be evaluated, to the textile fabric to be evaluated is taut and is handled;Excitation module, for the optical signal dynamic output of different wavelength, intensity and illumination angle to tight state fabric;The application adjusts optical correlation parameter by adapting fabric initial characteristic, improves the integrity and signal-to-noise ratio of signal acquisition, guarantees feature extraction accuracy, controls the taut state of fabric scientifically, avoids damage while ensuring test condition consistency, effectively shields ambient light interference, and reduces signal error by dynamic noise reduction and baseline correction, strengthens color fastness associated signal by feature fusion and normalization processing, improves quantitative evaluation accuracy.

Description

Technical Field

[0001] This invention relates to the field of optical testing technology, specifically to a dynamic evaluation system for color fastness of textile fabrics. Background Technology

[0002] Textile fabrics are made from natural fibers, chemical fibers, or composite fibers through spinning, weaving, dyeing, finishing, and functional finishing processes. They possess core properties such as breathability, moisture absorption, abrasion resistance, and wrinkle resistance. Customized functions such as antibacterial properties, UV protection, and intelligent temperature control can be achieved through fiber ratio optimization, structure design, and special finishing technologies. They are widely used in clothing, home textiles, industrial fabrics, and other applications.

[0003] Patent application number 202210694160.5 discloses a textile color detection system and method, as well as a material detection method. This application aims to solve the problem that "the color identification of textiles generally relies on professional color experts, which has a large degree of subjectivity and human uncertainty, resulting in poor accuracy. Although there are many color measuring instruments on the market, these instruments are easily affected by external light sources during the measurement process, and their accuracy in measuring the color of textiles is still relatively poor."

[0004] However, in the textile sector, existing technologies do not pay much attention to the testing and evaluation of color fastness of textile fabrics, and related testing technologies are scarce. As a result, the surface dye of finished textile products is often lost due to washing by the buyer, which reduces the quality of textile products and the user experience.

[0005] To address this, we propose a dynamic evaluation system for color fastness of textile fabrics. Summary of the Invention

[0006] In view of the above-mentioned shortcomings of the prior art, the present invention provides a dynamic evaluation system for color fastness of textile fabrics, which can effectively solve the problems of the prior art.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions; This invention discloses a dynamic evaluation system for color fastness of textile fabrics, comprising: The system comprises the following modules: a conditioning module for grasping the textile fabric to be evaluated and tensioning it; an excitation module for dynamically outputting optical signals of different wavelengths, intensities, and irradiation angles onto the taut fabric; a capture module for capturing the reflected and transmitted optical signals of the taut fabric under dynamic optical excitation in real time; a processing module for dynamically denoising, baseline correction, and feature extraction of the captured optical signals to generate standardized signal data related to color fastness; a construction module for building a dynamic evaluation model using the standardized optical signal data and performing quantitative evaluation of the color fastness of the textile fabric based on the model; and an output module for receiving the color fastness evaluation results, storing the results, and synchronously feeding them back to a preset receiving end. The regularization module is interconnected with the excitation module via a wireless network. The excitation module is interconnected with the capture module and the processing module via a wireless network. The capture module is interconnected with the construction module via a wireless network. The construction module is interconnected with the output module via a wireless network. The straightening module consists of two clamping devices integrated together. The clamping ends of the clamping devices are in a straight line shape. When clamping the textile fabric to be evaluated, the two clamping ends clamp the textile fabric on both sides of the conveying direction of the conveying equipment. The clamping ends of the two clamping devices are horizontal to each other, parallel and aligned when viewed from above. After clamping the textile fabric, the clamping ends move away from each other to keep the textile fabric in a taut state at a preset distance. Furthermore, the tensioning process of the regularization module is adaptively controlled by quantifying the tension stress: ; In the formula: The tension stress of textile fabric; The elastic modulus of the textile fabric to be evaluated; This represents the relative displacement between the two clamping ends; The effective length of the fabric in its initial clamped state; This is the clamping force stress conversion factor; The clamping force of the clamping device; This represents the actual contact area between the clamping end and the fabric. The clamping end is made of flexible wear-resistant ceramic composite material, and its surface has micron-level anti-slip texture. The tension stress must be controlled within the preset safe stress range of the fabric.

[0008] Furthermore, the optical signal output of the excitation module is dynamically adjusted based on the initial color characteristics of the fabric to be evaluated. The optical signal includes visible light and near-infrared bands, and the combination of wavelength, intensity, and illumination angle is determined by the following formula: ; In the formula: To adjust the optical signal intensity; This is the baseline strength value; This is the reflectivity correction factor; To ensure the fabric operates at the optimal wavelength Initial reflectivity; The attenuation coefficient is the illumination angle. To achieve the optimal illumination angle; Reference wavelength; This refers to the color deviation adaptation coefficient. The total color difference between the initial color of the fabric and the standard white plate in the CIELab color space; The dynamic switching period of the optical signal is synchronized with the sampling period of the acquisition module.

[0009] Furthermore, the capture module comprises an ambient light shielding component and a signal synchronization triggering unit, and the sampling frequency of the capture is adapted to the period of the optical excitation signal, so that... ,in Indicates the signal capture sampling frequency. Represents the timing synchronization coefficient. Indicates the period of the optical excitation signal. This represents the signal resolution correction factor. Indicates the resolution level of the captured signal. This represents the effective signal after ambient light compensation. Indicates the original capture signal, Indicates the ambient light response coefficient. This indicates the ambient light intensity monitored in real time.

[0010] Furthermore, the dynamic noise reduction in the processing module follows the following rules: ; In the formula: The signal strength after noise reduction; The original signal strength output by the capture module; These are the noise reduction weighting coefficients. ∈ (0, 1]; This represents the real-time signal-to-noise ratio of the current signal. The preset minimum allowable signal-to-noise ratio; The baseline correction eliminates the slow drift of the signal through linear fitting. The fitting benchmark is based on the sliding mean of the background signal of the capture module in the absence of optical excitation. Feature extraction targets the peak value, integral area and time series change rate of the signal to generate an original feature set directly related to color fastness.

[0011] Furthermore, the standardized signal data in the processing module is generated through feature fusion and normalization: ; In the formula: The fused, standardized feature vector; These are the feature weight coefficients; The rate of change of reflectivity within a continuous excitation cycle; The rate of change of reflectivity during different excitation cycles; This is the stability coefficient of the transmitted signal; This is the time decay coefficient; The duration of the optical excitation; The normalization process will Map to a preset standardized range.

[0012] Furthermore, the dynamic evaluation model of the building module is based on standardized feature vectors. And fabric material parameters, color fastness ,in , , These represent the characteristic gain coefficient, characteristic exponent coefficient, and material correction coefficient. Indicates the system reference offset. This indicates the fabric material parameters.

[0013] Furthermore, after the construction module quantitatively evaluates the color fastness of textile fabrics, it synchronously performs an output operation carrying the reliability coefficient of the evaluation results. The reliability coefficient of the evaluation results ; In the formula: This serves as a reference value for colorfastness to standard fabrics of the same type. The preset maximum colorfastness threshold; Among them, when If the result exceeds the preset confidence threshold, the evaluation result is deemed valid; otherwise, the system operation is refreshed.

[0014] Compared with the known prior art, the technical solution provided by this invention has the following beneficial effects: This invention improves the integrity and signal-to-noise ratio of signal acquisition by adjusting optical parameters according to the initial characteristics of the fabric, ensuring the accuracy of feature extraction, scientifically controlling the fabric tension to avoid damage while ensuring consistent testing conditions, effectively shielding ambient light interference, and reducing signal errors by combining dynamic noise reduction and baseline correction. It also enhances the color fastness correlation signal through feature fusion and normalization processing, improving the accuracy of quantitative assessment, optimizing the assessment model by associating fabric material parameters, and adapting to different fabric types to enhance applicability. Furthermore, the assessment results include a reliability coefficient to ensure validity, thereby avoiding unnecessary repeated testing and improving assessment efficiency and reliability. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0016] Figure 1 This is a schematic diagram of a dynamic evaluation system for color fastness of textile fabrics. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0018] The present invention will be further described below with reference to embodiments.

[0019] Example: This embodiment provides a dynamic evaluation system for the color fastness of textile fabrics, such as... Figure 1 As shown, it includes: The straightening module is used to grab the textile fabric to be evaluated and to tighten it. The tensioning process of the regularization module is adaptively controlled by quantifying the tension stress: ; In the formula: The tension stress of textile fabric; The elastic modulus of the textile fabric to be evaluated; This represents the relative displacement between the two clamping ends; The effective length of the fabric in its initial clamped state; This is the clamping force stress conversion factor; The clamping force of the clamping device; This represents the actual contact area between the clamping end and the fabric. The above formula fully considers the elastic deformation and clamping force transmission effect when the textile fabric is stretched. It takes into account the elastic modulus of the fabric, the relative displacement of the clamping end and the initial effective length to reflect the stress change caused by elastic deformation. At the same time, it corrects the stress transmission efficiency during the clamping process by the clamping force stress conversion coefficient, the clamping force and the actual contact area. The conversion coefficient is related to the contact fit between the clamping end and the fabric and the friction coefficient of the fabric surface. Finally, it achieves accurate calculation of the tensioning stress and ensures that the stress is controlled within the safe range of the fabric, so as to ensure the stability of the tensioning state and avoid damage to the fabric. The clamping end is made of flexible wear-resistant ceramic composite material, and its surface has micron-level anti-slip texture. The tension stress must be controlled within the preset safe stress range of the fabric. in, Used to improve the efficiency of the transmission of clamping force to the internal stress of the fabric. The preset value range is [0.6, 0.95], and its value is positively correlated with the contact fit between the clamping end and the fabric and the coefficient of friction of the fabric surface; The excitation module is used to dynamically output optical signals of different wavelengths, intensities, and irradiation angles to the taut fabric. The optical signal output of the excitation module is dynamically adjusted based on the initial color characteristics of the fabric to be evaluated. The optical signal includes visible light and near-infrared bands, and the combination of wavelength, intensity, and illumination angle is determined by the following formula: ; In the formula: To adjust the optical signal intensity; This is the baseline strength value; This is the reflectivity correction factor; To ensure the fabric operates at the optimal wavelength Initial reflectivity; The attenuation coefficient is the illumination angle. To achieve the optimal illumination angle; Reference wavelength; This refers to the color deviation adaptation coefficient. The total color difference between the initial color of the fabric and the standard white plate in the CIELab color space; The above formula combines the initial color characteristics of textile fabrics. The determination of the optimal wavelength is based on the reference wavelength. A color deviation adaptation coefficient and the total color difference between the fabric and the standard white plate are introduced to ensure that the wavelength can accurately match the color difference of the fabric. The optical signal intensity is adjusted by combining the reference intensity value with the reflectivity correction coefficient, the initial reflectivity of the fabric at the optimal wavelength, the illumination angle attenuation coefficient, and the optimal illumination angle. The reflectivity correction coefficient is negatively correlated with the initial reflectivity of the fabric, and the illumination angle attenuation coefficient is positively correlated with the surface smoothness of the fabric. This adjustment method allows the optical excitation to accurately adapt to the initial state of different fabrics. At the same time, the dynamic switching cycle of the optical signal is synchronized with the sampling cycle of the capture module, ensuring the coordination and consistency of signal excitation and capture. The dynamic switching period of the optical signal is synchronized with the sampling period of the acquisition module; in, The preset value range is [0.3, 1.2], and its value is negatively correlated with the initial reflectivity of the fabric; The preset value range is [0.02, 0.15], and its value is positively correlated with the smoothness of the fabric surface; Based on the surface roughness of the fabric to be evaluated and the optimized signal acquisition path, the integrity of the acquisition of reflected and transmitted signals and the signal-to-noise ratio are maximized. The preset value range is [0.05-0.3] μm / Its value is positively correlated with the initial color deviation of the fabric. The capture module is used to capture the reflected and transmitted optical signals of the taut fabric under dynamic optical excitation in real time; The capture module consists of an ambient light shielding component and a signal synchronization triggering unit. The sampling frequency of the capture is adapted to the period of the optical excitation signal, enabling... ,in Indicates the signal capture sampling frequency. Represents the timing synchronization coefficient. Indicates the period of the optical excitation signal. This represents the signal resolution correction factor. Indicates the resolution level of the captured signal. This represents the effective signal after ambient light compensation. Indicates the original capture signal, Indicates the ambient light response coefficient. This indicates the ambient light intensity being monitored in real time. The above formula addresses the interference of ambient light during optical signal capture. By introducing an ambient light response coefficient and real-time monitoring of ambient light intensity, the original captured signal is compensated, effectively offsetting the impact of ambient light fluctuations. At the same time, the sampling frequency of the capture module is matched with the period of the optical excitation signal. With the help of a narrow-band filter lens, only light signals of the corresponding wavelength are allowed to enter. Then, through the synchronous trigger unit and linkage with the regularization module, signal capture and ambient light shielding are only activated after the fabric tensioning process is completed, ensuring that the captured signal is both complete and has a high signal-to-noise ratio, accurately reflecting the true response of the fabric under optical excitation. The ambient light shielding component is used to shield the ambient light of the scene where the optical signal is dynamically output; the synchronization triggering unit is used to link the regularization module and trigger the capture module and the ambient light shielding component to run after the regularization module has finished running. The lens of the capture module adopts a narrowband filter design, which only allows narrowband light signals corresponding to the wavelength of the excitation signal to enter, so as to improve the signal-to-noise ratio; in, The preset value range is [0.8, 2.0]. When the optical excitation period is short and more sampling points need to be obtained in a single period to ensure the integrity of feature extraction, the value is larger. When the optical excitation period is long and the existing number of sampling points already meets the signal analysis requirements, the value is smaller. The preset value range is [0.3, 1.5]. When the original resolution of the captured signal is low and it is necessary to compensate for the loss of signal details by increasing the sampling frequency, the value is larger. When the resolution of the captured signal itself is high and there is no need to optimize the signal quality by additional sampling frequency, the value is smaller. The preset value range is 1-10. When the system hardware supports high-resolution acquisition and the color fastness of the fabric to be evaluated is subtle and the signal change needs to be accurately captured, the value is larger. When the hardware resolution is limited or the color fastness of the fabric is significant and can be distinguished without a high-resolution signal, the value is smaller. The preset value range is [0.01, 0.5]. When the real-time ambient light intensity fluctuates greatly and significantly interferes with the original captured signal, the value is larger; when the ambient light is in a stable state and has little interference with the signal, the value is smaller. The processing module is used to perform dynamic noise reduction, baseline correction, and feature extraction on the captured optical signals to generate standardized signal data related to color fastness. Dynamic noise reduction in the processing module follows these rules: ; In the formula: The signal strength after noise reduction; To capture the raw signal strength output by the module; These are the noise reduction weighting coefficients. ∈ (0, 1]; This represents the real-time signal-to-noise ratio of the current signal. The preset minimum allowable signal-to-noise ratio; The above formula dynamically adjusts the denoising weight coefficient based on the relationship between the real-time signal-to-noise ratio of the captured signal and the preset minimum allowable signal-to-noise ratio. When the real-time signal-to-noise ratio is closer to the minimum allowable value, the weight coefficient is larger and the denoising strength is stronger. Conversely, the denoising strength is weakened. This design can effectively suppress noise interference in the signal and avoid the loss of useful signal features due to excessive denoising, thus providing a high-quality signal foundation for subsequent baseline correction and feature extraction. Baseline correction eliminates slow signal drift through linear fitting. The fitting benchmark is based on the moving average of the background signal of the capture module in the absence of optical excitation. Feature extraction targets the peak value, integral area and time series change rate of the signal to generate an original feature set directly related to color fastness. Among them, the closer the real-time signal-to-noise ratio of the current signal is to the preset minimum allowable signal-to-noise ratio, the better. The larger the value, the higher the real-time signal-to-noise ratio of the current signal when it exceeds the preset minimum allowable signal-to-noise ratio. The smaller the value; In the processing module, standardized signal data is generated through feature fusion and normalization. ; In the formula: The fused, standardized feature vector; These are the feature weight coefficients; The rate of change of reflectivity within a continuous excitation cycle; The rate of change of reflectivity during different excitation cycles; This is the stability coefficient of the transmitted signal; This is the time decay coefficient; The duration of the optical excitation; The above formula comprehensively considers the multi-dimensional response characteristics of textile fabrics under dynamic optical excitation, and incorporates the reflectivity change rate within the continuous excitation cycle, the CIELab color space difference within different excitation cycles, and the stability coefficient of the transmission signal into the fusion range. At the same time, it introduces the time decay coefficient and the duration of optical excitation, and achieves a reasonable ratio of features in each dimension by setting a feature weight coefficient with a sum of 1. Then, the fused feature vector is mapped to a preset standardized range to ensure the uniformity and comparability of feature data. Normalization processing will Map to a preset standardized range; in, The values ​​of are all in the range of (0,1), and The sum is 1. The value range is (0, 10]. The smaller the standard deviation of the transmission signal fluctuation within the preset time window, the larger the value; the larger the standard deviation of the fluctuation, the smaller the value. The value range is [0.01, 0.15]. The more sensitive the color fastness of the fabric to be evaluated is to the duration of optical excitation, the larger the value; the less sensitive the color fastness of the fabric is to the duration of light exposure, the smaller the value. The module is used to call standardized optical signal data to build a dynamic evaluation model, and to perform quantitative evaluation of color fastness of textile fabrics based on the model. The dynamic evaluation model for building modules is based on standardized feature vectors. And fabric material parameters, color fastness ,in , , These represent the characteristic gain coefficient, characteristic exponent coefficient, and material correction coefficient. Indicates the system reference offset. Indicates the fabric material parameters; The above formula organically combines the standardized fusion feature vector with the fabric material parameters. The feature gain coefficient reflects the correlation strength between optical features and color fastness, the feature index coefficient adapts the nonlinear relationship between the two, the material correction coefficient reflects the inherent stability of the fabric's own color fastness, and the fabric material parameters integrate fiber crystallinity, yarn density and fabric structure tightness to achieve quantitative calculation of color fastness, so that the evaluation results can fully match the essential properties of the fabric. in, The preset value range is [0.8, 3.2]. The stronger the correlation between the optical characteristics of the fabric to be evaluated and the color fastness, the larger the value, and vice versa. The preset value range is [0.6, 2.4]. The more significant the nonlinear relationship between the fabric's optical characteristics and color fastness, the larger the value, and vice versa. The preset value range is [-0.3, 1.5]. The better the inherent stability of the color fastness of the fabric itself, the larger the value, and vice versa. The preset value range is [0.2, 4.8]. The higher the fiber crystallinity, the greater the yarn density, and the tighter the fabric structure, the larger the value, and vice versa. After constructing the module to quantitatively evaluate the color fastness of textile fabrics, the output operation is executed synchronously with the confidence coefficient of the evaluation results; Reliability coefficient of the evaluation results ; In the formula: This serves as a reference value for colorfastness to standard fabrics of the same type. The preset maximum colorfastness threshold; The above formula calculates the reliability coefficient of the evaluation result by comparing the color fastness result obtained from the quantitative evaluation with the color fastness reference value of the same type of standard fabric, combined with the preset maximum color fastness threshold. When the coefficient is higher than the preset threshold, it means that the deviation between the evaluation result and the standard reference value is within an acceptable range, and the evaluation is deemed valid. If it is lower than the threshold, it means that the deviation exceeds the reasonable range, triggering the system to refresh and run again, thereby ensuring the reliability and accuracy of the color fastness evaluation result. Among them, when If the result exceeds the preset confidence threshold, the evaluation result is deemed valid; otherwise, the system operation is refreshed. The output module is used to receive the color fastness assessment results, store the assessment results, and synchronously feed them back to the preset receiving end. The regularization module interacts with the excitation module via a wireless network. The excitation module interacts with the capture module and the processing module via a wireless network. The capture module interacts with the construction module via a wireless network. The construction module interacts with the output module via a wireless network. The straightening module is integrated with two clamping devices. The clamping ends of the clamping devices are in a straight line shape. When clamping the textile fabric to be evaluated, the clamping ends of the two clamping devices clamp the textile fabric on both sides of the conveying direction of the conveying equipment. The clamping ends of the two clamping devices are horizontal to each other, and are parallel and aligned when viewed from above. After clamping the textile fabric, the clamping ends move away from each other so that the textile fabric is in a taut state at a preset distance.

[0020] In this embodiment, the regularization module grabs the textile fabric to be evaluated and tightens it. The excitation module then dynamically outputs optical signals of different wavelengths, intensities, and irradiation angles to the taut fabric. The capture module further captures the reflected and transmitted optical signals of the taut fabric under dynamic optical excitation in real time. The processing module then performs dynamic noise reduction, baseline correction, and feature extraction on the captured optical signals to generate standardized signal data related to color fastness. The construction module calls the standardized optical signal data to build a dynamic evaluation model. Based on the model, the color fastness of the textile fabric is quantitatively evaluated. Finally, the output module receives the color fastness evaluation results, stores the evaluation results, and synchronously feeds them back to the preset receiving end.

[0021] In the above embodiments, the system can accurately adapt to the characteristics of different fabrics, dynamically adjust optical excitation parameters, effectively shield environmental interference, and achieve quantitative evaluation of color fastness through precise signal processing and feature fusion. The results are accompanied by credibility verification, which not only improves the accuracy and efficiency of the evaluation, but also ensures the reliability of the results. It can also be conveniently stored and synchronously fed back, adapting to the diverse testing needs of textile fabrics.

[0022] Application Example 2: Apparel manufacturers need to conduct color fastness testing on a batch of polyester-cotton blended fabrics and will use this system.

[0023] First, the two straight clamping devices of the straightening module are horizontally aligned on both sides of the fabric conveying direction to clamp the fabric. Then, the clamping ends move away from each other to tighten the fabric. The calculated tension of the fabric is 0.32MPa, which is within the preset safe stress range. The clamping ends are made of flexible wear-resistant ceramic composite material with micron-level anti-slip texture to ensure that the clamping is stable and does not damage the fabric.

[0024] Next, the excitation module adaptively adjusts the optical signal based on the initial color characteristics of the fabric, covering the visible light and near-infrared bands. The optimal illumination wavelength is calculated to be 560nm, the optical signal intensity is 820lux, and the optimal illumination angle is 28°. The dynamic switching cycle of the optical signal is consistent with the subsequent capture and sampling cycle.

[0025] After the sizing module completes the tensioning operation, the capture module is activated by the synchronous triggering unit. The ambient light shielding component isolates external light interference. The lens improves the signal-to-noise ratio through narrow-band filter design. The sampling frequency is precisely matched with the optical excitation period. After ambient light compensation, the effective signal strength is 1150 counts.

[0026] The processing module first performs dynamic noise reduction on the captured signal, and the signal strength after processing is 1130 counts. Then, it eliminates the slow drift of the signal through baseline correction, extracts features such as signal peak value, integral area and time series change rate, and obtains a standardized feature vector value of 0.68 through feature fusion. Subsequently, it is normalized and mapped to a preset standardized range.

[0027] The construction module calls the standardized feature vector and the material parameters of the polyester-cotton blended fabric (value 2.1). The color fastness of the fabric is quantified as 4.3 through the dynamic evaluation model. At the same time, the confidence coefficient of the evaluation result is calculated to be 0.91. This coefficient is higher than the preset confidence threshold, so the evaluation result is determined to be valid.

[0028] Finally, the output module stores the color fastness assessment results and simultaneously feeds them back to the enterprise's production quality control terminal, providing reliable data support for fabric warehousing and subsequent production applications.

[0029] In summary, the system in the above embodiments improves the integrity and signal-to-noise ratio of signal acquisition by adjusting optical parameters according to the initial characteristics of the fabric, ensuring the accuracy of feature extraction, scientifically controlling the fabric tension to avoid damage while ensuring consistent test conditions, effectively shielding ambient light interference, and reducing signal errors by combining dynamic noise reduction and baseline correction. It also enhances the color fastness correlation signal through feature fusion and normalization processing, improves the accuracy of quantitative evaluation, optimizes the evaluation model by associating fabric material parameters, and enhances applicability to different fabric types. In addition, the evaluation results are accompanied by a reliability coefficient to ensure the validity of the results, thereby avoiding unnecessary repeated testing and improving evaluation efficiency and reliability.

[0030] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A dynamic evaluation system for color fastness of textile fabrics, characterized in that, include: The straightening module is used to grab the textile fabric to be evaluated and to tighten it. The excitation module is used to dynamically output optical signals of different wavelengths, intensities, and irradiation angles to the taut fabric. The capture module is used to capture the reflected and transmitted optical signals of the taut fabric under dynamic optical excitation in real time. The processing module is used to perform dynamic noise reduction, baseline correction, and feature extraction on the captured optical signals to generate standardized signal data related to color fastness. The dynamic noise reduction in the processing module follows the following rules: ； In the formula: The signal strength after noise reduction; The original signal strength output by the capture module; These are the noise reduction weighting coefficients. ∈ (0, 1]; This represents the real-time signal-to-noise ratio of the current signal. The preset minimum allowable signal-to-noise ratio; The baseline correction eliminates the slow drift of the signal through linear fitting. The fitting benchmark is based on the sliding mean of the background signal of the capture module in the absence of optical excitation. Feature extraction targets the peak value, integral area and time series change rate of the signal to generate an original feature set directly related to color fastness. The standardized signal data in the processing module is generated through feature fusion and normalization: ； In the formula: The fused, standardized feature vector; These are the feature weight coefficients; The rate of change of reflectivity within a continuous excitation cycle; The rate of change of reflectivity during different excitation cycles; This is the stability coefficient of the transmitted signal; This is the time decay coefficient; The duration of the optical excitation; The normalization process will Map to a preset standardized range; The module is used to call standardized optical signal data to build a dynamic evaluation model, and to perform quantitative evaluation of color fastness of textile fabrics based on the model. The dynamic evaluation model of the building module is based on standardized feature vectors. And fabric material parameters, color fastness ,in , , These represent the characteristic gain coefficient, characteristic exponent coefficient, and material correction coefficient. Indicates the system reference offset. Indicates the fabric material parameters; The output module is used to receive color fastness assessment results, store the assessment results, and synchronously feed them back to the preset receiving end. The straightening module is integrated with two clamping devices. The clamping ends of the clamping devices are in a straight line shape. When clamping the textile fabric to be evaluated, the clamping ends of the two clamping devices clamp the textile fabric on both sides of the conveying direction of the conveying equipment. The clamping ends of the two clamping devices are horizontal to each other, and are parallel and aligned when viewed from above. After clamping the textile fabric, the clamping ends move away from each other so that the textile fabric is in a taut state at a preset distance.

2. The dynamic evaluation system for color fastness of textile fabrics according to claim 1, characterized in that, The tensioning process of the regularization module is adaptively controlled by quantifying the tension stress: ； In the formula: The tension stress of textile fabric; The elastic modulus of the textile fabric to be evaluated; This represents the relative displacement between the two clamping ends; The effective length of the fabric in its initial clamped state; This is the clamping force stress conversion factor; The clamping force of the clamping device; This represents the actual contact area between the clamping end and the fabric. The clamping end is made of flexible wear-resistant ceramic composite material, and its surface has micron-level anti-slip texture. The tension stress must be controlled within the preset safe stress range of the fabric.

3. The dynamic evaluation system for color fastness of textile fabrics according to claim 1, characterized in that, The optical signal output of the excitation module is dynamically adjusted based on the initial color characteristics of the fabric to be evaluated. The optical signal includes visible light and near-infrared bands, and the combination of wavelength, intensity, and illumination angle is determined by the following formula: ； In the formula: To adjust the optical signal intensity; This is the baseline strength value; This is the reflectivity correction factor; To ensure the fabric operates at the optimal wavelength Initial reflectivity; The attenuation coefficient is the illumination angle. To achieve the optimal illumination angle; Reference wavelength; This refers to the color deviation adaptation coefficient. The total color difference between the initial color of the fabric and the standard white plate in the CIELab color space; The dynamic switching period of the optical signal is synchronized with the sampling period of the acquisition module.

4. The dynamic evaluation system for color fastness of textile fabrics according to claim 1, characterized in that, The capture module consists of an ambient light shielding component and a signal synchronization triggering unit. The sampling frequency of the capture is adapted to the period of the optical excitation signal, so that... ,in Indicates the signal capture sampling frequency. Represents the timing synchronization coefficient. Indicates the period of the optical excitation signal. This represents the signal resolution correction factor. Indicates the resolution level of the captured signal. This represents the effective signal after ambient light compensation. Indicates the original capture signal, Indicates the ambient light response coefficient. This indicates the ambient light intensity monitored in real time.

5. The dynamic evaluation system for color fastness of textile fabrics according to claim 1, characterized in that, After the construction module quantitatively evaluates the color fastness of textile fabrics, it synchronously performs an output operation carrying the reliability coefficient of the evaluation results. The reliability coefficient of the evaluation results ; In the formula: This serves as a reference value for colorfastness to standard fabrics of the same type. The preset maximum colorfastness threshold; Among them, when If the result exceeds the preset confidence threshold, the evaluation result is deemed valid; otherwise, the system operation is refreshed.

6. The dynamic evaluation system for color fastness of textile fabrics according to claim 1, characterized in that, The regularization module interacts with the excitation module via a wireless network. The excitation module interacts with the capture module and the processing module via a wireless network. The capture module interacts with the construction module via a wireless network. The construction module interacts with the output module via a wireless network.

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