Method and system for detecting antibacterial and air permeability of a composite fiber warp-knitted fabric

Abstract

The present application relates to the technical field of fabric performance detection, and provides a composite fiber warp-knitted fabric antibacterial and air permeability performance detection method and system, the method comprising: obtaining first original performance measurement information and second original performance measurement information of a fabric to be detected; correcting the first original performance measurement information according to the influence degree of environmental factors on the first performance measurement path to obtain corrected first performance measurement information; correcting the second original performance measurement information according to the influence degree of environmental factors on the second performance measurement path to obtain corrected second performance measurement information; and performing fabric performance evaluation based on the corrected first performance measurement information and the corrected second performance measurement information to complete fabric performance detection. The present application has the effect of improving the accuracy and reliability of composite fiber warp-knitted fabric antibacterial and air permeability performance detection.

Description

Technical Field

[0001] This invention relates to the technical field of fabric performance testing, specifically to a method and system for testing the antibacterial and breathability properties of composite fiber warp-knitted fabrics. Background Technology

[0002] In the production process of high-performance composite fiber warp-knitted fabrics, especially after the antibacterial finishing agent impregnation and heat setting processes, real-time online monitoring of the product's antibacterial and air permeability properties is crucial. Existing technologies typically employ online quality monitoring systems integrating fluorescent tracer technology and non-contact airflow resistance sensors. Fluorescent tracer technology assesses the amount and uniformity of antibacterial agent adhesion by detecting the intensity of the fluorescence signal, while non-contact airflow resistance sensors calculate the fabric's air permeability by measuring airflow rate. These systems can effectively improve production efficiency and product quality uniformity when the production environment is relatively stable.

[0003] However, in actual production operations, such online monitoring systems face multiple challenges. First, fine fibers, dust particles, and finishing agent volatiles in the production environment accumulate over time on the surface of the sensor's optical lenses or at the inlet of the airflow channel, forming a thin film. These accumulations not only attenuate the fluorescence signal but also alter the hydrodynamic characteristics of airflow through the sensor, causing a systematic drift in the sensor's output information and resulting in deviations between the measurement results and actual performance. Second, even with regular cleaning and drift compensation, the system may still exhibit abnormal fluctuations. These fluctuations stem from subtle differences in the microstructure of different batches of base fiber materials, such as variations in fiber surface roughness, cross-sectional shape, yarn twist, or inter-fiber cohesion. These differences affect the wetting, spreading, and curing effects of antibacterial polymer solutions on the fiber surface, as well as the connectivity of the fabric's internal pore structure, thus impacting the actual performance of antibacterial and breathability properties. Existing prediction mechanisms are insufficient in identifying and adapting to such intrinsic structural variations.

[0004] Furthermore, with the increasing demand for multifunctional fabrics, the problem becomes more complex when new functional finishing agents (such as fluorocarbon water-repellent finishing agents) are introduced. While water-repellent agents impart water-repellent properties to fabrics, they also interact with antibacterial agents during the deposition process on the fiber surface, further altering the fabric's pore structure. This physicochemical interaction between multifunctional finishing agents makes it difficult for the system to independently optimize each performance indicator. For example, water-repellent agents may interfere with the uniform adsorption of antibacterial polymers, leading to a reduction in antibacterial effectiveness; simultaneously, their film-filling effect can significantly increase air resistance through the fabric, reducing breathability. In this scenario of conflicting multiple objectives, existing systems struggle to accurately determine the cause of changes in measured values, leading to a predicament of blind adjustments in production control and an inability to effectively balance and optimize various performance indicators.

[0005] To address the aforementioned issues, existing technologies urgently need improvement. Summary of the Invention

[0006] This application discloses a method and system for testing the antibacterial and breathability properties of composite fiber warp-knitted fabrics, aiming to solve the technical problems of existing online monitoring systems in complex production environments, such as measurement result deviations, insufficient adaptability, and difficulty in accurately determining the causes of measurement value changes due to environmental factors, material differences, and the interaction of multifunctional finishing agents.

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

[0008] In a first aspect, this application discloses a method for testing the antibacterial and breathability properties of composite fiber warp-knitted fabrics, comprising the following steps:

[0009] A first reference fabric and a second reference fabric are set; the first reference fabric has a preset first performance standard, and the second reference fabric has a preset second performance standard; the measurement path of the first reference fabric and the first performance measurement path of the fabric to be tested are exposed to the production environment together, and the measurement path of the second reference fabric and the second performance measurement path of the fabric to be tested are exposed to the production environment together.

[0010] Obtain first performance measurement information of the first reference fabric in the production environment, and compare the first performance measurement information with the preset first performance standard to determine the degree of influence of environmental factors on the first performance measurement path;

[0011] Obtain second performance measurement information of the second reference fabric in the production environment, and compare the second performance measurement information with the preset second performance standard to determine the degree of influence of environmental factors on the second performance measurement path;

[0012] Obtain the first and second raw performance measurement information of the fabric to be tested;

[0013] Based on the degree of influence of environmental factors on the first performance measurement path, the first original performance measurement information is corrected to obtain the corrected first performance measurement information; based on the degree of influence of environmental factors on the second performance measurement path, the second original performance measurement information is corrected to obtain the corrected second performance measurement information.

[0014] Based on the corrected first performance measurement information and the corrected second performance measurement information, the fabric performance is evaluated to complete the fabric performance test.

[0015] This technical solution, by introducing a reference fabric and simultaneously exposing it to the production environment, enables real-time acquisition of the degree of influence of environmental factors on the measurement path, and corrects the original measurement information accordingly. This effectively solves the measurement deviation problem caused by environmental accumulations, material differences and the interaction of multifunctional finishing agents in the prior art, and significantly improves the accuracy and reliability of fabric antibacterial and breathability performance testing.

[0016] Secondly, this application also discloses a testing system for the antibacterial and breathability properties of composite fiber warp-knitted fabrics, used to perform testing on the antibacterial and breathability properties of composite fiber warp-knitted fabrics, including:

[0017] The reference fabric setting module is used to set a first reference fabric and a second reference fabric; the first reference fabric has a preset first performance standard, and the second reference fabric has a preset second performance standard; the measurement path of the first reference fabric and the first performance measurement path of the fabric to be tested are exposed to the production environment together, and the measurement path of the second reference fabric and the second performance measurement path of the fabric to be tested are exposed to the production environment together.

[0018] The first measurement information acquisition module is used to acquire the first performance measurement information of the first reference fabric in the production environment, and compare the first performance measurement information with the preset first performance standard to determine the degree of influence of environmental factors on the first performance measurement path.

[0019] The second measurement information acquisition module is used to acquire the second performance measurement information of the second reference fabric in the production environment, and compare the second performance measurement information with the preset second performance standard to determine the degree of influence of environmental factors on the second performance measurement path.

[0020] The raw information acquisition module is used to acquire the first and second raw performance measurement information of the fabric to be tested.

[0021] The measurement information correction module is used to correct the first original performance measurement information according to the degree of influence of environmental factors on the first performance measurement path, so as to obtain the corrected first performance measurement information; and to correct the second original performance measurement information according to the degree of influence of environmental factors on the second performance measurement path, so as to obtain the corrected second performance measurement information.

[0022] The fabric performance evaluation module is used to evaluate fabric performance based on the corrected first performance measurement information and the corrected second performance measurement information in order to complete the fabric performance test.

[0023] Through this technical solution, this application achieves accurate testing of the antibacterial and breathability properties of composite fiber warp-knitted fabrics via modular design. Its reference fabric setting module, measurement information acquisition module, raw information acquisition module, measurement information correction module, and fabric performance evaluation module work together to effectively overcome the challenges brought about by the complexity of the production environment, material differences, and the interaction of multifunctional finishing agents, significantly improving the accuracy and reliability of the test.

[0024] Beneficial Effects: The method for testing the antibacterial and breathability properties of composite fiber warp-knitted fabrics disclosed in this application, by setting up a first reference fabric and a second reference fabric, and exposing their measurement paths to the production environment along with the measurement path of the fabric under test, can obtain the degree of influence of environmental factors on the measurement path in real time. Specifically, by comparing the measurement information of the reference fabric with preset standards, the attenuation and distortion effects of environmental factors on the measurement paths of the first performance (such as antibacterial performance) and the second performance (such as breathability performance) are quantified. Based on this, the original measurement information is corrected to obtain corrected performance measurement information that is closer to the true value. This method effectively solves the problem of systematic sensor drift caused by the accumulation of fine fiber lint, dust particles, and finishing agent volatiles in the production environment in the prior art, as well as the measurement deviation caused by the microstructure differences of different batches of base fiber materials and the interaction of multifunctional finishing agents. By introducing a real-time compensation mechanism for environmental factors, this application significantly improves the accuracy and reliability of testing the antibacterial and breathability properties of composite fiber warp-knitted fabrics, enabling production control to more accurately balance and optimize various performance indicators, avoiding blind adjustments, thereby improving the uniformity of product quality and production efficiency. Attached Figure Description

[0025] Figure 1 This is a flowchart of a method for testing the antibacterial and breathability properties of a composite fiber warp-knitted fabric in one embodiment of the present invention;

[0026] Figure 2 This is a flowchart of a method for testing the antibacterial and breathability properties of a composite fiber warp-knitted fabric according to another embodiment of the present invention;

[0027] Figure 3 This is a system block diagram of a composite fiber warp-knitted fabric antibacterial and breathability testing system according to another embodiment of the present invention;

[0028] Explanation of reference numerals in the attached figures:

[0029] 1. Composite fiber warp-knitted fabric antibacterial and breathability performance testing system; 11. Reference fabric setting module; 12. First measurement information acquisition module; 13. Second measurement information acquisition module; 14. Raw information acquisition module; 15. Measurement information correction module; 16. Fabric performance evaluation module. Detailed Implementation

[0030] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0031] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0032] This application proposes a method for testing the antibacterial and breathability properties of composite fiber warp-knitted fabrics, combined with... Figure 1 As shown, it includes:

[0033] S1, set a first reference fabric and a second reference fabric; the first reference fabric has a preset first performance standard, and the second reference fabric has a preset second performance standard; the measurement path of the first reference fabric and the first performance measurement path of the fabric to be tested are exposed to the production environment together, and the measurement path of the second reference fabric and the second performance measurement path of the fabric to be tested are exposed to the production environment together.

[0034] S2, acquire the first performance measurement information of the first reference fabric in the production environment, and compare the first performance measurement information with the preset first performance standard to determine the degree of influence of environmental factors on the first performance measurement path;

[0035] S3, acquire the second performance measurement information of the second reference fabric in the production environment, and compare the second performance measurement information with the preset second performance standard to determine the degree of influence of environmental factors on the second performance measurement path;

[0036] S4, acquire the first and second raw performance measurement information of the fabric to be tested;

[0037] S5. Based on the degree of influence of environmental factors on the first performance measurement path, the first original performance measurement information is corrected to obtain the corrected first performance measurement information; based on the degree of influence of environmental factors on the second performance measurement path, the second original performance measurement information is corrected to obtain the corrected second performance measurement information.

[0038] S6. Based on the corrected first performance measurement information and the corrected second performance measurement information, the fabric performance is evaluated to complete the fabric performance test.

[0039] To better understand the technical solution proposed in this application, some key terms involved will be explained first.

[0040] The "first reference fabric" is a reference standard used to calibrate the antimicrobial performance measurement path. It has a known and stable first performance standard, such as specific fluorescence intensity or spectral response characteristics, and is used to assess the impact of production environment factors on the antimicrobial performance measurement path. The "second reference fabric" is another reference standard used to calibrate the breathability performance measurement path. It has a known and stable second performance standard, such as established airflow resistance or air transmittance, and is used to assess the impact of environmental factors on the breathability performance measurement path. The "first performance measurement path" refers to the optical or physical detection channel used to measure antimicrobial performance, such as the transmission path of fluorescent excitation and emission light; the "second performance measurement path" refers to the airflow detection channel used to measure breathability performance. "First raw performance measurement information" and "second raw performance measurement information" refer to antimicrobial performance data and breathability performance data obtained directly from the fabric under test, without considering environmental factor corrections, respectively; while "corrected first performance measurement information" and "corrected second performance measurement information" are more realistic measurement data obtained after correcting for environmental influences based on the reference fabric.

[0041] The proposed method for testing the antibacterial and breathability properties of composite fiber warp-knitted fabrics achieves high-precision testing of antibacterial and breathability properties through reference fabric measurement calibration and compensation for the influence of the production environment. Specifically, a first reference fabric and a second reference fabric are firstly set up. The first reference fabric has a preset first performance standard, such as stable fluorescence characteristics, with its fluorescence intensity and spectrum being known calibration values ​​under ideal conditions. The second reference fabric has a preset second performance standard, such as known airflow resistance or air transmittance. In actual operation, the first reference fabric is placed within the same first performance measurement path as the fabric under test, exposing it to the same optical environment; the second reference fabric is placed in the same airflow channel as the fabric under test, ensuring its breathability measurement is affected by the same aerodynamic conditions. This arrangement ensures that the reference fabric and the fabric under test are subjected to consistent environmental disturbances during the testing process, providing a reliable basis for subsequent calibration.

[0042] Subsequently, by performing the same measurement operations as on the test fabric on the first reference fabric, its first performance measurement information in the production environment is obtained. This information is then compared with a preset first performance standard to determine the degree of influence of environmental factors on the first performance measurement path. For example, if the fluorescence signal of the first reference fabric is lower than its standard value, it indicates that the optical path may be affected by dust, fiber particles, or light source attenuation. Similarly, by measuring the airflow resistance of the second reference fabric in the current environment and comparing it with its standard value, the impact on the airflow detection path can be determined, such as increased resistance due to channel deposits or humidity changes.

[0043] While measuring the reference fabric, the system simultaneously acquires first and second original performance measurement information of the fabric under test. For example, the fluorescence intensity of the fabric is obtained through a fluorescence detection system as an antibacterial performance indicator, or the airflow resistance of the fabric is obtained through an airflow sensor as a breathability performance indicator. Subsequently, based on the degree of environmental influence reflected in the measurement results of the reference fabric, the above-mentioned original measurement information is adjusted for environmental compensation, thereby obtaining the corrected first and second performance measurement information. For example, when the signal of the first reference fabric attenuates by 10%, the fluorescence signal of the fabric can be compensated proportionally; when the resistance of the second reference fabric increases by 5%, the breathability measurement value of the fabric can be corrected accordingly to eliminate environmental interference factors.

[0044] Finally, based on the corrected first and second performance measurement information, a comprehensive evaluation of the fabric's antibacterial and breathability properties is completed. Because the introduction of a reference fabric enables real-time compensation for complex environmental factors, this method significantly improves the accuracy and reliability of fabric performance testing results, thus providing strong support for production process control, quality stability maintenance, and product performance consistency improvement.

[0045] Optional, combined Figure 2 As shown, the steps for correcting the original second performance measurement information based on the degree of influence of environmental factors on the second performance measurement path to obtain the corrected second performance measurement information include:

[0046] A1. An array of capacitive sensors is set on the inner wall of the measurement path of the second reference fabric.

[0047] A2, collect the capacitance value of the capacitance sensor array and generate the corresponding charge distribution image of the inner wall adhesion layer;

[0048] A3 generates a humidity pulse in a localized area of ​​the measurement path on the second reference fabric;

[0049] A4, collect capacitance values ​​during the humidity pulse and extract the response characteristics of capacitance value changes over time;

[0050] A5. Based on the charge distribution image and response characteristics of the inner wall adhesion layer, the physical state of the inner wall adhesion layer is quantified.

[0051] A6. Calculate the actual airflow resistance of the measurement path of the second reference fabric based on the physical conditions.

[0052] A7 compares the actual airflow resistance with the preset standard airflow resistance and calculates the proportion of resistance drift caused by the inner wall adhesion layer.

[0053] A8. Based on the resistance drift ratio, the second original performance measurement information of the fabric to be tested is corrected to obtain the corrected second performance measurement information.

[0054] Specifically, a capacitive sensor array is positioned on the inner wall of the measurement path of the second reference fabric to monitor the presence and electrical characteristics of the adhesion layer on the inner wall of the channel in real time. The capacitive sensor array consists of multiple miniature capacitive sensing units, each capable of responding to changes in the dielectric constant of the adjacent medium, thereby reflecting parameters such as the thickness, density, and moisture content of the adhesion layer. By acquiring the capacitance values ​​of the capacitive sensor array, the system can generate a corresponding image of the charge distribution of the adhesion layer on the inner wall. This image visually presents the spatial distribution characteristics and charge distribution pattern of the adhesion layer on the inner wall of the measurement path, providing fundamental data for subsequent quantification of the physical state of the adhesion layer.

[0055] Furthermore, a humidity pulse is applied to a localized area of ​​the measurement path on the second reference fabric, inducing a rapid change in local humidity over a short period (e.g., by spraying a small amount of water mist or introducing humid air) to observe the response characteristics of the adhesion layer to humidity disturbances. A capacitive sensor array continuously acquires capacitance values ​​during the humidity pulse and extracts the dynamic response characteristics of capacitance over time. These response characteristics may include the rate of increase or decrease in capacitance, peak amplitude, and stable recovery time, reflecting the adhesion layer's hygroscopic capacity, pore structure, moisture diffusion rate, and hygroscopic-desorption dynamics.

[0056] Based on the response characteristics of charge distribution images and humidity pulses, the physical state of the inner wall adhesion layer can be quantified in multiple dimensions. For example, charge distribution images can be used to estimate the spatial distribution, thickness, and local uniformity of the adhesion layer, while response characteristics can reveal its microscopic pore structure, moisture gradient variation capability, and moisture absorption performance. By fusing this information, a physical state model reflecting the comprehensive physical properties of the adhesion layer can be established.

[0057] Based on the aforementioned physical state model, the actual airflow resistance of the measurement path of the second reference fabric can be calculated. This calculation can be based on the established physical model or empirical formulas, correlating key state quantities of the adhesion layer (such as thickness, density, porosity, hygroscopicity, etc.) with airflow resistance parameters to obtain the actual airflow resistance under the current adhesion layer state.

[0058] The calculated actual airflow resistance is then compared with a preset standard airflow resistance to determine the proportion of resistance drift caused by the adhesion layer. The standard airflow resistance is the baseline resistance value corresponding to the measurement path under ideal, adhesion-free conditions. The resistance drift proportion quantitatively describes the degree of deviation in airflow resistance caused by the adhesion layer under the current condition.

[0059] Based on this resistance drift ratio, the second original performance measurement information of the fabric under test is corrected to obtain the corrected second performance measurement information. This method accurately compensates for changes in path resistance caused by the attachment layer, allowing the final breathability measurement results to more accurately reflect the fabric's inherent breathability.

[0060] Optionally, the step of correcting the first original performance measurement information based on the degree of influence of environmental factors on the first performance measurement path to obtain the corrected first performance measurement information includes:

[0061] The first reference fabric includes several fluorescent regions with different spectral response characteristics;

[0062] According to a preset cycle, the fluorescence signal intensity of the fluorescent region of the first reference fabric in the production environment, as well as the fluorescence spectrum information of the fluorescent region, are obtained;

[0063] The fluorescence signal intensity is compared with a preset first performance standard to determine the overall signal attenuation of the first performance measurement path due to environmental factors.

[0064] The fluorescence spectral information is compared with the preset standard spectral information to determine the degree of spectral distortion of the first performance measurement path caused by environmental factors.

[0065] Obtain the first raw performance measurement information of the fabric to be tested;

[0066] Based on the overall signal attenuation and spectral distortion, the first original performance measurement information of the fabric under test is corrected to obtain the corrected first performance measurement information.

[0067] Specifically, the first reference fabric is designed to include several fluorescent regions with different spectral response characteristics. These fluorescent regions can be pre-prepared fluorescent material coatings or embedded fluorescent elements that are sensitive to specific environmental factors (such as temperature, humidity, specific chemical components, microbial adhesion, etc.). By assigning different fluorescent regions to different environmentally sensitive mechanisms, multi-dimensional capture of various interfering factors in the production environment can be achieved. For example, some fluorescent regions may exhibit significant wavelength shifts in response to temperature changes, while other regions may show fluorescence intensity decay corresponding to specific pollutants (such as volatile organic compounds, microbial metabolites), thus forming a comprehensive characterization capability for environmental interference.

[0068] Acquiring fluorescence signal intensity and fluorescence spectral information of each fluorescent region according to a preset cycle refers to using a spectrometer or fluorescence detection device to photoexcite a first reference fabric at fixed time intervals and record the emitted fluorescence intensity and spectral distribution. Fluorescence signal intensity reflects the activity, concentration, or degree of obscuring of the fluorescent substance by pollutants; spectral information reveals the fluorescence emission wavelength components, peak positions, and peak shape characteristics. By periodically acquiring these parameters, the dynamic impact of environmental changes on the first performance measurement path can be monitored in real time, thereby forming a quantifiable record of environmental interference.

[0069] The acquired fluorescence signal intensity is compared with a preset first performance standard to quantify the overall signal attenuation caused by environmental factors. The first performance standard is a fluorescence baseline value obtained under ideal, interference-free conditions. If the measured fluorescence intensity decreases relative to the baseline, it can be inferred that factors such as dust, fiber particles, light source instability, and slight degradation of fluorescent materials in the environment have led to signal loss. Therefore, the system can quantitatively assess the overall attenuation impact of environmental interference on the measurement path.

[0070] Furthermore, the fluorescence spectral information is compared with preset standard spectral information to determine the degree of spectral distortion caused by environmental factors on the first performance measurement path. The standard spectral information is the typical spectral distribution of the first reference fabric under ideal conditions. Environmental factors (such as oxidants, reducing agents, pH changes, abrupt humidity changes, etc.) may alter the electronic structure or energy level transition behavior of fluorophores, resulting in peak position shift, peak broadening, changes in peak intensity ratio, and even the generation of new spectral signals. By analyzing spectral distortion, the chemical or physical interference of specific environmental factors on the measurement path can be identified, and the degree of their influence can be quantified.

[0071] Correcting the initial raw performance measurement information of the fabric under test based on the overall signal attenuation and spectral distortion involves using these two environmental influence parameters as correction factors to comprehensively compensate for environmental errors in the initial antimicrobial performance measurement data of the fabric. Overall signal attenuation provides macroscopic energy loss compensation, while spectral distortion compensation addresses subtle errors caused by changes in the excited state and emission process. By combining the two, interference from the production environment in antimicrobial performance measurement can be more effectively eliminated, resulting in more accurate and closer-to-true corrected initial performance measurement information.

[0072] Optionally, the steps for correcting the initial raw performance measurement information of the fabric under test based on the overall signal attenuation and spectral distortion include:

[0073] The pre-deployed dynamic fluorescence interaction effect sensing unit is activated to emit excitation light of different wavelengths to excite the fabric under test;

[0074] Capture the fluorescence emission spectra of the fabric under test at different excitation wavelengths;

[0075] The relative changes in fluorescence signal intensity and spectral shape in fluorescence emission spectra were analyzed to identify and quantify the degree of nonlinear interaction between the inner wall adhesion layer and the fluorescence signal.

[0076] Based on the degree of nonlinear interaction, the overall signal attenuation and spectral distortion are corrected to obtain the corrected overall signal attenuation and spectral distortion.

[0077] Based on the corrected overall signal attenuation and the corrected spectral distortion, the first original performance measurement information of the fabric under test is corrected to obtain the corrected first performance measurement information.

[0078] Specifically, the dynamic fluorescence interaction effect sensing unit is a specialized detection device used to detect the complex interactions between fluorescence signals and environmental factors. This unit is pre-positioned in the production environment and can actively emit excitation light in multiple wavelengths, including ultraviolet and visible light of different energy levels, to ensure sufficient excitation of fluorescent substances within the fabric under test and to induce any fluorescence response or optical interference that may occur in the adhesion layer on the inner wall of the measurement path. By selecting different excitation wavelengths, the fluorescence response behavior of the fabric under test under various energy input conditions can be obtained, thereby revealing deeper optical interaction characteristics between it and the adhesion layer.

[0079] Capturing the fluorescence emission spectrum of a fabric under test at different excitation wavelengths refers to the real-time or near-real-time acquisition of the fluorescence signal generated by the fabric under test after the excitation light is emitted by the dynamic fluorescence interaction effect sensing unit, using a high-sensitivity spectrometer or photodetector array, and decomposing it into intensity distributions at different wavelengths to form a complete fluorescence emission spectrum. This fluorescence spectrum can be regarded as the optical fingerprint of the fabric under test under specific excitation conditions, reflecting the fabric's intrinsic properties and the interference of environmental adhesion layers on the fluorescence signal.

[0080] Analyzing the changes in signal intensity and spectral shape of fluorescence emission spectra to identify and quantify the nonlinear interaction between the inner wall adhesion layer and the fluorescence signal is a process of further processing the aforementioned fluorescence data. Such nonlinear interactions typically manifest as fluorescence quenching (increased intensity), fluorescence enhancement (increased intensity), spectral peak shift, peak broadening, or the appearance of new fluorescence peaks. The patterns of these changes are not linearly related to the material composition, concentration, or structural characteristics of the adhesion layer. By comparing fluorescence characteristics at different excitation wavelengths and combining them with preset benchmark spectral data, the system can utilize methods such as multivariate curve resolution, principal component analysis, or machine learning models to perform pattern recognition of spectral changes, establish a mapping relationship between spectral changes and the properties of the adhesion layer, and thus quantify the degree of nonlinear interaction.

[0081] Based on the quantified degree of nonlinear interaction, the overall signal attenuation and spectral distortion are corrected. This involves using the nonlinear index as a correction factor to finely adjust the overall fluorescence signal attenuation and spectral distortion parameters previously determined by the first reference fabric. For example, when a certain type of pollutant is identified as causing a significant nonlinear fluorescence quenching effect, the compensation magnitude needs to be further increased on top of the overall signal attenuation compensation to avoid underestimating the antibacterial performance of the fabric under ideal conditions. If a shift in the spectral peak position is identified due to chemical reactions or environmental disturbances, the parameter model for spectral distortion needs to be corrected accordingly. In this way, the interference caused by nonlinear factors can be accurately isolated at the spectral level, making the corrected environmental impact parameters closer to the true physical state.

[0082] Finally, based on the corrected overall signal attenuation and spectral distortion, the initial original performance measurement information of the fabric under test is corrected to obtain the corrected initial performance measurement information. This step applies the parameters corrected by nonlinear interaction to the original antibacterial performance measurement data, achieving comprehensive compensation for various complex environmental interference factors during optical detection, making the obtained measurement results more accurate and reliable in reflecting the true antibacterial performance of the fabric itself.

[0083] Optionally, the steps of correcting the first original performance measurement information of the fabric under test based on the corrected overall signal attenuation and the corrected spectral distortion to obtain the corrected first performance measurement information include:

[0084] Deploy environmental parameter sensors to monitor temperature, humidity, and airflow speed in the production environment;

[0085] Adjust the correction parameters used to correct the overall signal attenuation and spectral distortion based on temperature, humidity, and airflow speed;

[0086] Based on the adjusted correction parameters, the first original performance measurement information of the fabric to be tested is corrected to obtain the corrected first performance measurement information.

[0087] Specifically, environmental parameter sensors can be understood as devices used to collect various physical parameters in the production environment in real time, such as temperature sensors, humidity sensors, and airflow velocity sensors. These sensors are strategically deployed in the production environment along the measurement paths of the first reference fabric and the first performance measurement path of the fabric under test to ensure that the monitored environmental data accurately reflects the actual working conditions. Specifically, the temperature sensor measures the ambient temperature, the humidity sensor measures the relative humidity, and the airflow velocity sensor measures the speed of airflow. These parameters have a significant impact on the formation and stability of the adhesion layer and its interference with fluorescence signals.

[0088] Furthermore, correction parameters refer to numerical or model coefficients used to adjust the overall signal attenuation and spectral distortion. These parameters are adjusted based on real-time monitoring of temperature, humidity, and airflow velocity. For example, when the ambient temperature rises, certain chemical reaction rates in the adhesion layer may accelerate, leading to enhanced attenuation or distortion of the fluorescence signal. In this case, the correction parameters will be adjusted accordingly to compensate for this enhancement. Similarly, changes in humidity and airflow velocity also affect the hygroscopicity, drying rate, and particulate deposition of the adhesion layer, thereby altering its impact on the fluorescence signal; therefore, dynamic adjustment of the correction parameters is necessary.

[0089] Therefore, by correcting the first original performance measurement information of the fabric under test according to the adjusted correction parameters, the influence of environmental factors and nonlinear interaction of the adhesion layer on the measurement results can be eliminated more accurately, thereby obtaining more realistic and reliable corrected first performance measurement information.

[0090] Optionally, the steps of adjusting the correction parameters used to correct the overall signal attenuation and spectral distortion based on temperature, humidity, and airflow velocity include:

[0091] Deploy specific contaminant sensors in production environments;

[0092] Based on measurement information from specific pollutant sensors, the concentrations of pollutants with different properties can be identified and quantified.

[0093] Based on the quantified concentrations of pollutants of different properties, as well as temperature, humidity, and airflow velocity, a correlation of pollutant response characteristics is established.

[0094] Based on the correlation of pollutant response characteristics, the independent influence weight of each pollutant on the overall signal attenuation and spectral distortion is determined; the independent influence weight is used to adjust the overall signal attenuation and spectral distortion.

[0095] Specifically, deploying specific pollutant sensors refers to installing sensors capable of detecting and distinguishing different types of pollutants in real time in key areas of the fabric production line, such as near the fabric processing area, drying area, or storage area. These sensors may include, but are not limited to, gas sensors (for detecting volatile organic compounds, ammonia, sulfides, etc.), particulate matter sensors (for detecting suspended particulate matter such as PM2.5 and PM10), or chemical vapor sensors. The aim is to comprehensively capture microscopic environmental factors in the production environment that may affect the accuracy of fabric antibacterial and breathability performance testing.

[0096] This process involves identifying and quantifying the concentrations of pollutants of different properties based on measurement information from specific pollutant sensors. This can be understood as converting raw measurement data—such as ppm, ppb, or mg / m³—into specific pollutant concentration values ​​by combining electrical, optical, or other physicochemical signals acquired by the sensors with a pre-defined calibration curve or machine learning model. The purpose is to provide accurate pollutant quantification data for subsequent adjustment of correction parameters.

[0097] In practical applications, based on the quantified concentrations of pollutants with different properties, as well as temperature, humidity, and airflow velocity, a correlation of pollutant response characteristics can be established. For example, a multi-dimensional response model or lookup table can be constructed. This model or lookup table describes the specific influence patterns and intensities of changes in the concentration of each specific pollutant on the overall signal attenuation and spectral distortion under different temperature, humidity, and airflow velocity conditions. The aim is to reveal the complex interaction mechanism between pollutants and fabric performance detection signals.

[0098] Furthermore, based on the correlation of pollutant response characteristics, determining the independent influence weight of each pollutant on the overall signal attenuation and spectral distortion involves quantifying the relative importance of each pollutant's contribution to signal attenuation and spectral distortion under specific environmental conditions from the established response characteristic correlations using regression analysis, principal component analysis, or other statistical methods. The independent influence weight can be a numerical value representing the intensity of the pollutant's influence on a specific signal parameter. The independent influence weight is used to weight and adjust the overall signal attenuation and spectral distortion. Specifically, this can be achieved by multiplying or weighting the original overall signal attenuation and spectral distortion with the independent influence weight of each pollutant and its concentration, thereby obtaining a more accurate correction value.

[0099] Optionally, the steps of adjusting the correction parameters used to correct the overall signal attenuation and spectral distortion based on temperature, humidity, and airflow velocity include:

[0100] When switching product models on the production line, identify the fiber composition, finishing agent type, and production speed of the current product model;

[0101] Based on fiber composition, finishing agent type and production speed, the system retrieves preset parameters from a pre-stored product characteristic library, including the adhesion layer formation rate, adhesion characteristics, and nonlinear interaction with the antibacterial agent, corresponding to the current product model.

[0102] Based on preset parameters such as the adhesion layer formation rate, adhesion characteristics, and nonlinear interaction with the antibacterial agent, and combined with the temperature, humidity, and airflow velocity monitored in the production environment, correction parameters are adjusted to correct the overall signal attenuation and spectral distortion.

[0103] Specifically, when a production line switches from one fabric product to another, it needs to identify the model of the product currently being produced. This identification process can be done manually by operators or automatically through an automated system (e.g., by scanning product batch barcodes or reading data from a production planning system). Key information about the identified product model includes its fiber composition, the type of finishing agent used, and the current production speed. Fiber composition refers to the specific types and proportions of fiber materials used in the fabric, such as polyester, nylon, and spandex; finishing agent type refers to various functional additives added during the fabric production process, such as antibacterial agents, softeners, and waterproofing agents; and production speed reflects the processing rate of the fabric on the production line.

[0104] Furthermore, based on the identified fiber composition, finishing agent type, and production speed, the system queries and retrieves preset parameters matching the current product model from a pre-stored product characteristic library. This product characteristic library can be a database containing detailed characteristic data for various known product models, accumulated through previous experiments, simulations, or historical production data. The retrieved preset parameters specifically include the adhesion layer formation rate, adhesion characteristics, and parameters related to the nonlinear interaction with the antimicrobial agent. The adhesion layer formation rate refers to the rate at which contaminants accumulate on the fabric surface or the inner wall of the measurement path under specific environmental conditions; adhesion characteristics describe the strength and manner of binding between contaminants and the fabric or measurement path surface; and the preset parameters for the nonlinear interaction with the antimicrobial agent quantify how environmental factors (such as temperature, humidity, and specific contaminants) affect the activity of the antimicrobial agent and its fluorescence signal response, as well as the nonlinear relationship between this effect and the antimicrobial agent concentration or adhesion layer thickness.

[0105] Therefore, the acquired parameters for the adhesion layer formation rate, adhesion characteristics, and nonlinear interaction with the antibacterial agent are combined with real-time monitored temperature, humidity, and airflow velocity in the production environment. A pre-defined algorithm or model is used to finely adjust the correction parameters used to correct the overall signal attenuation and spectral distortion. For example, if a fabric has a faster adhesion layer formation rate, then under the same environmental conditions, its correction parameters need to reflect signal attenuation to a greater extent; if a finishing agent has a strong nonlinear interaction with a specific contaminant, the adjustment of the correction parameters needs to take this nonlinear effect into account to avoid over- or under-correction.

[0106] Optionally, the step of adjusting correction parameters to correct the overall signal attenuation and spectral distortion based on preset parameters of the adhesion layer formation rate, adhesion characteristics, and nonlinear interaction with the antimicrobial agent, combined with temperature, humidity, and airflow velocity monitored in the production environment, includes:

[0107] If there are no preset parameters in the product characteristic library that perfectly match the current product model, then based on the fiber composition, finishing agent type and production speed, the preset parameters of several similar product models with similar fiber composition, finishing agent type or production speed will be searched from the product characteristic library.

[0108] Based on preset parameters of several similar product models, combined with the degree of difference between the current product model and similar product models, as well as the temperature, humidity and airflow speed monitored in the production environment, the preset parameters are weighted and fused to generate the initial correction parameters for the adhesion layer formation rate, adhesion characteristics and nonlinear interaction with the antibacterial agent of the current product model.

[0109] Based on the initial correction parameters, and combined with the temperature, humidity, and airflow velocity monitored in the production environment, the correction parameters used to correct the overall signal attenuation and spectral distortion are adjusted.

[0110] Specifically, when the system fails to find preset parameters in the product characteristic library that perfectly match the current fabric product model being tested, an intelligent matching mechanism is activated. This mechanism searches the product characteristic library for and identifies several approximate product models with similar characteristics to the current product model, based on key attributes such as fiber composition, finishing agent type, and production speed. The similarity can be quantified using a predefined distance function or matching algorithm. For example, the similarity of fiber composition can be evaluated based on chemical structure or physical properties, finishing agent types can be classified according to their main functions or chemical categories, and production speeds can be directly compared numerically.

[0111] Furthermore, after obtaining the preset parameters of these similar product models, this application uses a weighted fusion method to generate the initial correction parameters for the current product model. The weighted fusion process not only considers the preset parameters of these similar product models themselves, but also comprehensively considers the degree of difference between the current product model and each similar product model, as well as the temperature, humidity, and airflow velocity monitored in real time in the production environment. The degree of difference can be understood as the quantitative difference between the current product model and similar product models in terms of fiber composition, finishing agent type, and production speed; the smaller the difference, the larger its corresponding weight. Weighted fusion can be implemented by constructing a multivariate regression model or using a machine learning-based algorithm. Environmental parameters (temperature, humidity, airflow velocity) serve as important regulating factors, reflecting the dynamic changes in adhesion layer formation and antimicrobial agent interaction under different environments. In this way, an initial correction parameter that more closely reflects the current actual situation regarding adhesion layer formation rate, adhesion characteristics, and nonlinear interaction with the antimicrobial agent can be generated.

[0112] Finally, based on the generated initial correction parameters and combined with the real-time monitoring of temperature, humidity, and airflow velocity in the production environment, the correction parameters used to correct the overall signal attenuation and spectral distortion are adjusted. This process ensures that even in the absence of perfectly matching data, accurate correction parameters can be obtained through intelligent inference and data fusion, thereby guaranteeing the accuracy of fabric performance testing.

[0113] Optionally, the step of weightedly fusing the preset parameters based on preset parameters of several similar product models, combined with the degree of difference between the current product model and similar product models, and the temperature, humidity, and airflow velocity monitored in the production environment, to generate initial correction parameters for the adhesion layer formation rate, adhesion characteristics, and nonlinear interaction with the antimicrobial agent of the current product model includes:

[0114] Based on the monitored temperature, humidity, and airflow speed, as well as the degree of difference between the current product model and similar product models, the response mode of the preset parameters under different environmental conditions is determined.

[0115] Based on the response pattern, preset parameters are adjusted to compensate for nonlinear or coupling effects caused by environmental factors.

[0116] The adjusted preset parameters are weighted and fused to generate initial correction parameters for the adhesion layer formation rate, adhesion characteristics, and nonlinear interaction with the antibacterial agent of the current product model.

[0117] "Determining the response patterns of preset parameters under different environmental conditions" refers to understanding and quantifying how preset parameters of similar product models (such as adhesion layer formation rate, adhesion characteristics, and preset parameters of nonlinear interaction with antibacterial agents) change with temperature, humidity, airflow velocity, and the degree of difference from the current product model under test in the production environment, through analyzing historical data, experimental data, or establishing physical models. For example, in a high-temperature and high-humidity environment, the adhesion layer formation rate of a certain fiber may exhibit exponential rather than nonlinear growth; this pattern of change is the response pattern. The aim is to reveal the inherent laws governing the influence of environmental factors and product differences on the parameters.

[0118] Furthermore, "adjusting preset parameters based on response patterns to compensate for nonlinear or coupling effects caused by environmental factors" refers to using these patterns to correct the preset parameters of approximate product models after identifying the response patterns of the preset parameters. Nonlinear effects refer to the disproportionate relationship between input and output changes; for example, a doubling of temperature may more than double the rate of adhesion layer formation. Coupling effects refer to the fact that when multiple environmental factors (such as temperature and humidity) act together, their combined impact is not a simple additive effect, but rather a mutual influence. By establishing mathematical models or lookup tables, and based on the currently monitored environmental parameters, the preset parameters of approximate product models are finely adjusted to eliminate or reduce the errors caused by these nonlinear or coupling effects.

[0119] Therefore, "weighting and fusing the adjusted preset parameters to generate initial correction parameters for the adhesion layer formation rate, adhesion characteristics, and nonlinear interaction with the antibacterial agent of the current product model" means that after compensating for the nonlinearity and coupling effect of the preset parameters of similar product models, different weights are assigned according to the similarity between the similar product models and the current product model (e.g., the matching degree of fiber composition, finishing agent type, and production speed), and a weighted average or more complex fusion algorithm is performed to finally obtain a more accurate initial correction parameter that better matches the actual situation of the fabric under test.

[0120] This application proposes a testing system for the antibacterial and breathability properties of composite fiber warp-knitted fabrics, used to perform testing on the antibacterial and breathability properties of composite fiber warp-knitted fabrics, combined with... Figure 3 As shown, the composite fiber warp-knitted fabric antibacterial and breathability testing system 1 includes:

[0121] The reference fabric setting module 11 is used to set a first reference fabric and a second reference fabric; the first reference fabric has a preset first performance standard, and the second reference fabric has a preset second performance standard; the measurement path of the first reference fabric and the first performance measurement path of the fabric to be tested are exposed to the production environment together, and the measurement path of the second reference fabric and the second performance measurement path of the fabric to be tested are exposed to the production environment together.

[0122] The first measurement information acquisition module 12 is used to acquire the first performance measurement information of the first reference fabric in the production environment, and compare the first performance measurement information with the preset first performance standard to determine the degree of influence of environmental factors on the first performance measurement path.

[0123] The second measurement information acquisition module 13 is used to acquire the second performance measurement information of the second reference fabric in the production environment, and compare the second performance measurement information with the preset second performance standard to determine the degree of influence of environmental factors on the second performance measurement path.

[0124] The raw information acquisition module 14 is used to acquire the first raw performance measurement information and the second raw performance measurement information of the fabric to be tested.

[0125] The measurement information correction module 15 is used to correct the first original performance measurement information according to the degree of influence of environmental factors on the first performance measurement path, so as to obtain the corrected first performance measurement information; and to correct the second original performance measurement information according to the degree of influence of environmental factors on the second performance measurement path, so as to obtain the corrected second performance measurement information.

[0126] The fabric performance evaluation module 16 is used to evaluate the fabric performance based on the corrected first performance measurement information and the corrected second performance measurement information in order to complete the fabric performance test.

[0127] To better understand the technical solution proposed in this application, some key terms involved will be explained first.

[0128] "First reference fabric" refers to a reference standard used to calibrate the antimicrobial performance measurement path. It has a known and stable "first performance standard", such as a specific fluorescence intensity or spectral characteristics, to assess the impact of environmental factors on the antimicrobial performance measurement path.

[0129] "Second reference fabric" refers to a reference standard used to calibrate the breathability measurement path. It has a known and stable "second performance standard", such as a specific airflow resistance or air permeability, to assess the impact of environmental factors on the breathability measurement path.

[0130] "First performance measurement path" refers to the physical or optical channel used to measure the antimicrobial properties of the fabric under test, such as the transmission path of fluorescent excitation light and emission light.

[0131] The "second performance measurement path" refers to the physical channel used to measure the breathability of the fabric under test, such as the channel through which airflow passes through the sensor.

[0132] "First raw performance measurement information" refers to the antimicrobial performance measurement data obtained directly from the fabric being tested before any environmental factor corrections are made.

[0133] "Second raw performance measurement information" refers to the breathability measurement data obtained directly from the fabric under test before environmental factor correction.

[0134] "Corrected first performance measurement information" and "Corrected second performance measurement information" refer to measurement data that more accurately reflect the true antibacterial and breathability properties of the fabric under test after correction for the degree of influence of environmental factors.

[0135] The composite fiber warp-knitted fabric antibacterial and breathability testing system proposed in this application, through a series of carefully designed modules, effectively compensates for complex factors in the production environment, thereby improving the accuracy of the test results.

[0136] In some embodiments of this application, the specific steps of the method for testing the antibacterial and breathability properties of composite fiber warp-knitted fabrics have already been described in the above embodiments, and will not be repeated here. It should be emphasized that the testing system proposed in this application provides an automated, online testing solution by transforming these method steps into specific system modules.

[0137] Specifically, the reference fabric setting module is configured to set up a first reference fabric and a second reference fabric on the production line. The first reference fabric has a preset first performance standard, such as a standard sample with stable fluorescence characteristics, whose fluorescence intensity and spectral curve under ideal conditions are known benchmarks. The second reference fabric has a preset second performance standard, such as a porous material sample with calibrated airflow resistance. The reference fabric setting module exposes the measurement path of the first reference fabric and the first performance measurement path of the fabric under test to the same production environment, ensuring that both are affected by factors such as changes in light source, particulate matter deposition, and temperature and humidity disturbances. Similarly, the module ensures that the measurement path of the second reference fabric and the second performance measurement path of the fabric under test share the same airflow channel conditions, making the impact of environmental factors on air permeability measurement comparable. For example, the module can place the first reference fabric within the field of view of the fluorescence detector and test it in parallel with the fabric under test; simultaneously, it can place the second reference fabric in the detection channel of the airflow sensor, keeping it consistent with the airflow path of the fabric under test.

[0138] The first measurement information acquisition module is used to acquire the first performance measurement information of the first reference fabric in the production environment and compare it with the preset first performance standard. This module obtains the actual fluorescence intensity of the reference fabric through a measurement method consistent with that of the fabric under test (e.g., periodically exciting the reference fabric and detecting its fluorescence signal), and determines the degree of environmental interference in the first performance measurement path accordingly. For example, when the measured fluorescence intensity is lower than the standard value, it can be determined that there may be environmental factors in the optical path that cause signal attenuation, such as dust, fiber lint, or unstable lighting.

[0139] The second measurement information acquisition module is used to acquire second performance measurement information of the second reference fabric in the production environment and compare it with a preset second performance standard. This module identifies resistance deviations in the airflow channel caused by particle adhesion, humidity changes, or channel contaminants by performing the same air permeability measurement operation (such as measuring airflow resistance) on the second reference fabric as on the fabric under test. For example, when the measured airflow resistance is higher than its standard value, it can be determined that the second performance measurement path is affected by adhering substances or humidity disturbances.

[0140] The raw information acquisition module is used to simultaneously acquire the first and second raw performance measurement information of the fabric under test. The first raw performance measurement information can be fluorescence intensity data directly obtained through a fluorescence detection system; the second raw performance measurement information can be airflow resistance data directly obtained through an airflow sensor. Neither of the above raw information has been compensated for by any environmental factors.

[0141] The measurement information correction module is used to correct the first and second original performance measurement information based on the degree of influence of environmental factors on different measurement paths, thus obtaining corrected first and second performance measurement information. For example, when the fluorescence signal of the first reference fabric attenuates by 10%, this module will perform corresponding intensity compensation correction on the fluorescence measurement data of the fabric under test; when the airflow resistance of the second reference fabric increases by 5%, this module will perform corresponding magnitude environmental compensation on the original measurement data of the fabric's air permeability. The correction process ensures a linear or non-linear mapping of environmental influences, so that the corrected values ​​can truly reflect the fabric's inherent performance, rather than environmental disturbances.

[0142] The fabric performance evaluation module comprehensively assesses the antibacterial and breathability properties of the tested fabric based on corrected first and second performance measurement information. By eliminating biases caused by environmental factors, the accuracy, repeatability, and stability of the test results can be significantly improved, enabling them to more accurately reflect the inherent properties of the fabric and providing a reliable basis for production process control and product quality optimization.

[0143] The above are merely embodiments of this application and are not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for testing the antibacterial and breathability properties of composite fiber warp-knitted fabrics, characterized in that, include: A first reference fabric and a second reference fabric are set; the first reference fabric has a preset first performance standard, and the second reference fabric has a preset second performance standard; the measurement path of the first reference fabric and the first performance measurement path of the fabric to be tested are exposed together in the production environment, and the measurement path of the second reference fabric and the second performance measurement path of the fabric to be tested are exposed together in the production environment. Obtain the first performance measurement information of the first reference fabric in the production environment, and compare the first performance measurement information with the preset first performance standard to determine the degree of influence of environmental factors on the first performance measurement path; Obtain the second performance measurement information of the second reference fabric in the production environment, and compare the second performance measurement information with the preset second performance standard to determine the degree of influence of environmental factors on the second performance measurement path; Obtain the first and second raw performance measurement information of the fabric to be tested; Based on the degree of influence of environmental factors on the first performance measurement path, the first original performance measurement information is corrected to obtain the corrected first performance measurement information. Based on the degree of influence of environmental factors on the second performance measurement path, the second original performance measurement information is corrected to obtain the corrected second performance measurement information. Based on the corrected first performance measurement information and the corrected second performance measurement information, the fabric performance is evaluated to complete the fabric performance test.

2. The method for testing the antibacterial and breathability properties of composite fiber warp-knitted fabric according to claim 1, characterized in that, The step of correcting the second original performance measurement information based on the degree of influence of environmental factors on the second performance measurement path to obtain the corrected second performance measurement information includes: An array of capacitive sensors is set on the inner wall of the measurement path of the second reference fabric; The capacitance values ​​of the capacitive sensor array are collected to generate a corresponding image of the charge distribution of the inner wall adhesion layer; A humidity pulse is generated in a local area of ​​the measurement path of the second reference fabric; Capacitance values ​​are collected during humidity pulses, and the response characteristics of capacitance values ​​changing over time are extracted. The physical state of the inner wall adhesion layer is quantified based on the charge distribution image of the inner wall adhesion layer and the response characteristics. Based on the physical state, calculate the actual airflow resistance of the measurement path of the second reference fabric; The actual airflow resistance is compared with the preset standard airflow resistance, and the resistance drift ratio caused by the inner wall adhesion layer is calculated. Based on the resistance drift ratio, the second original performance measurement information of the fabric to be tested is corrected to obtain the corrected second performance measurement information.

3. The method for testing the antibacterial and breathability properties of composite fiber warp-knitted fabric according to claim 1, characterized in that, The step of correcting the first original performance measurement information based on the degree of influence of environmental factors on the first performance measurement path to obtain the corrected first performance measurement information includes: The first reference fabric includes several fluorescent regions with different spectral response characteristics; According to a preset cycle, the fluorescence signal intensity of the fluorescent region of the first reference fabric in the production environment, as well as the fluorescence spectral information of the fluorescent region, are acquired. The fluorescence signal intensity is compared with a preset first performance standard to determine the overall signal attenuation degree of environmental factors on the first performance measurement path. The fluorescence spectral information is compared with preset standard spectral information to determine the degree of spectral distortion of the first performance measurement path caused by environmental factors. Obtain the first raw performance measurement information of the fabric to be tested; Based on the overall signal attenuation and the spectral distortion, the first original performance measurement information of the fabric to be tested is corrected to obtain the corrected first performance measurement information.

4. The method for testing the antibacterial and breathability properties of composite fiber warp-knitted fabric according to claim 3, characterized in that, The step of correcting the first original performance measurement information of the fabric under test based on the overall signal attenuation and the spectral distortion to obtain the corrected first performance measurement information includes: The pre-deployed dynamic fluorescence interaction effect sensing unit is activated to emit excitation light of different wavelengths to excite the fabric under test; Capture the fluorescence emission spectra of the fabric under test at different excitation wavelengths; The relative changes in fluorescence signal intensity and spectral shape of the fluorescence emission spectrum are analyzed to identify and quantify the degree of nonlinear interaction between the inner wall adhesion layer and the fluorescence signal. Based on the degree of nonlinear interaction, the overall signal attenuation and the spectral distortion are corrected to obtain the corrected overall signal attenuation and the corrected spectral distortion. Based on the corrected overall signal attenuation and the corrected spectral distortion, the first original performance measurement information of the fabric under test is corrected to obtain the corrected first performance measurement information.

5. The method for testing the antibacterial and breathability properties of a composite fiber warp-knitted fabric according to claim 4, characterized in that, The step of correcting the first original performance measurement information of the fabric under test based on the corrected overall signal attenuation and the corrected spectral distortion to obtain the corrected first performance measurement information includes: Deploy environmental parameter sensors to monitor temperature, humidity, and airflow speed in the production environment; Based on the temperature, humidity, and airflow speed, adjust the correction parameters used to correct the overall signal attenuation and the degree of spectral distortion; Based on the adjusted correction parameters, the first original performance measurement information of the fabric to be tested is corrected to obtain the corrected first performance measurement information.

6. The method for testing the antibacterial and breathability properties of a composite fiber warp-knitted fabric according to claim 5, characterized in that, The step of adjusting the correction parameters used to correct the overall signal attenuation and the spectral distortion based on the temperature, humidity, and airflow velocity includes: Deploy specific contaminant sensors in production environments; Based on measurement information from specific pollutant sensors, the concentrations of pollutants with different properties can be identified and quantified. Based on the quantified concentrations of pollutants of different properties, as well as the temperature, humidity, and airflow velocity, a correlation of pollutant response characteristics is established. Based on the correlation of the pollutant response characteristics, the independent influence weight of each pollutant on the overall signal attenuation and the spectral distortion is determined; the independent influence weight is used to adjust the overall signal attenuation and the spectral distortion.

7. The method for testing the antibacterial and breathability properties of composite fiber warp-knitted fabric according to claim 5, characterized in that, The step of adjusting the correction parameters used to correct the overall signal attenuation and the spectral distortion based on the temperature, humidity, and airflow velocity includes: When switching product models on the production line, identify the fiber composition, finishing agent type, and production speed of the current product model; Based on the fiber composition, finishing agent type, and production speed, preset parameters for the adhesion layer formation rate, adhesion characteristics, and nonlinear interaction with the antibacterial agent corresponding to the current product model are obtained from a pre-stored product characteristic library. Based on the preset parameters of the adhesion layer formation rate, adhesion characteristics, and nonlinear interaction with the antibacterial agent, and combined with the temperature, humidity, and airflow velocity monitored in the production environment, the correction parameters used to correct the overall signal attenuation and the degree of spectral distortion are adjusted.

8. The method for testing the antibacterial and breathability properties of a composite fiber warp-knitted fabric according to claim 7, characterized in that, The step of adjusting the correction parameters used to correct the overall signal attenuation and the degree of spectral distortion based on preset parameters of the adhesion layer formation rate, adhesion characteristics, and nonlinear interaction with the antibacterial agent, combined with temperature, humidity, and airflow velocity monitored in the production environment, includes: If there is no preset parameter in the product characteristic library that perfectly matches the current product model, then based on the fiber composition, finishing agent type and production speed, the preset parameters of several similar product models with similar fiber composition, finishing agent type or production speed are searched from the product characteristic library. Based on preset parameters of several similar product models, combined with the degree of difference between the current product model and the similar product models, as well as the temperature, humidity and airflow speed monitored in the production environment, the preset parameters are weighted and fused to generate the initial correction parameters for the adhesion layer formation rate, adhesion characteristics and nonlinear interaction with the antibacterial agent of the current product model. Based on the initial correction parameters, and in conjunction with the temperature, humidity, and airflow velocity monitored in the production environment, the correction parameters used to correct the overall signal attenuation and the degree of spectral distortion are adjusted.

9. The method for testing the antibacterial and breathability properties of a composite fiber warp-knitted fabric according to claim 8, characterized in that, The step of weightedly fusing the preset parameters based on a number of similar product models, combined with the degree of difference between the current product model and the similar product models, and the temperature, humidity, and airflow velocity monitored in the production environment, to generate initial correction parameters for the adhesion layer formation rate, adhesion characteristics, and nonlinear interaction with the antibacterial agent of the current product model includes: Based on the monitored temperature, humidity, and airflow speed, as well as the degree of difference between the current product model and similar product models, the response mode of the preset parameters under different environmental conditions is determined; Based on the response mode, the preset parameters are adjusted to compensate for nonlinear or coupling effects caused by environmental factors; The adjusted preset parameters are weighted and fused to generate initial correction parameters for the adhesion layer formation rate, adhesion characteristics, and nonlinear interaction with the antibacterial agent of the current product model.

10. A testing system for the antibacterial and breathability properties of composite fiber warp-knitted fabrics, used for testing the antibacterial and breathability properties of composite fiber warp-knitted fabrics, characterized in that, include: A reference fabric setting module is used to set a first reference fabric and a second reference fabric; the first reference fabric has a preset first performance standard, and the second reference fabric has a preset second performance standard; the measurement path of the first reference fabric and the first performance measurement path of the fabric to be tested are exposed together in the production environment, and the measurement path of the second reference fabric and the second performance measurement path of the fabric to be tested are exposed together in the production environment. The first measurement information acquisition module is used to acquire the first performance measurement information of the first reference fabric in the production environment, and compare the first performance measurement information with the preset first performance standard to determine the degree of influence of environmental factors on the first performance measurement path. The second measurement information acquisition module is used to acquire the second performance measurement information of the second reference fabric in the production environment, and compare the second performance measurement information with the preset second performance standard to determine the degree of influence of environmental factors on the second performance measurement path. The raw information acquisition module is used to acquire the first and second raw performance measurement information of the fabric to be tested. The measurement information correction module is used to correct the first original performance measurement information according to the degree of influence of environmental factors on the first performance measurement path, so as to obtain the corrected first performance measurement information. Based on the degree of influence of environmental factors on the second performance measurement path, the second original performance measurement information is corrected to obtain the corrected second performance measurement information. The fabric performance evaluation module is used to evaluate fabric performance based on the corrected first performance measurement information and the corrected second performance measurement information in order to complete the fabric performance test.

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