A flame retardant fiber fabric performance control method, system and device

Abstract

The present invention discloses a method, system and device for controlling the performance of flame-retardant fiber fabrics, and relates to the technical field of fabric performance detection. The method, system and device for controlling the performance of flame-retardant fiber fabrics include the following steps: S1, obtaining the wearing state data of flame-retardant fabrics and preprocessing the wearing state data of flame-retardant fabrics; S2, analyzing the unit heat-driven temperature response capability of the fabric in the wearing state based on the flame-retardant fabric wearing data after grid binding preprocessing, and performing combustion trigger judgment; S3, extracting the ignition time, quantifying the ignition deviation between the standard test and the wearing state, and correcting the temperature rise path of the test distortion grid to generate a wearing flame-retardant performance response data set; S4, evaluating the degree of distortion risk of the standard test in the wearing state, determining the dominant distortion source and performing response compensation, and outputting a credibility label and correction path covering the entire domain. This solves the problem of flame-retardant evaluation distortion caused by the disconnection between the standard test and the actual wearing state.

Description

Technical Field

[0001] The present invention relates to the technical field of fabric performance detection, and in particular to a method, system and device for controlling the performance of flame-retardant fiber fabrics. Background Art

[0002] Flame-retardant fiber fabrics, as specialized protective textile materials, are widely used in high-heat-risk environments, such as firefighting, military and police work, and power generation. Existing flame-retardant performance evaluation methods are mostly based on standard test conditions, such as vertical combustion and limiting oxygen index, and focus on structured testing of the fabric's physical properties and thermal response.

[0003] For example, the invention with the announcement number CN118566253A discloses a comprehensive performance testing device and method for electrothermal cotton composite home textile fabrics, comprising a frame, wherein the left and right sides of the top of the frame are fixedly connected to support members, and the interior of the support members is fixedly connected to a fixing plate. The present invention is provided with a first telescopic mechanism and a second telescopic mechanism for coordinated use, so that four sets of clamping mechanisms can clamp the four corners of the home textile fabric respectively to fix the home textile fabric, and can also stretch the fixed home textile fabric in the transverse direction by contracting the first telescopic mechanism on both sides, thereby determining the tensile strength of the home textile fabric in the transverse direction, and can also stretch the fixed home textile fabric in the longitudinal direction by contracting the second telescopic mechanism, thereby determining the tensile strength of the home textile fabric in the longitudinal direction. Secondly, by cooperating with the transverse motion mechanism, the vertical motion mechanism and the longitudinal motion mechanism, the wear resistance and flame retardancy of the home textile fabric can be determined.

[0004] However, the traditional technical testing process ignores the structural changes of the fabric under actual wearing conditions and the interference of the humid and hot environment, such as wrinkle accumulation, strain deformation, moisture content fluctuations, etc. This leads to obvious deviations between the evaluation results and the actual flame retardant behavior in the wearing scenario, making it difficult to accurately support the judgment of protection capabilities under high-risk working conditions.

[0005] Therefore, in order to solve the above problems, there is an urgent need for a method, system and device for controlling the performance of flame retardant fiber fabrics. Summary of the Invention

[0006] Technical problems solved

[0007] In response to the deficiencies of the prior art, the present invention provides a method, system and device for controlling the performance of flame-retardant fiber fabrics, which solves the problem of flame-retardant evaluation distortion caused by the disconnection between standard testing and actual wearing conditions.

[0008] Technical Solution

[0009] To achieve the above objectives, the present invention is implemented through the following technical solutions: a performance control method, system and device for flame-retardant fiber fabrics, comprising the following steps: S1, acquiring flame-retardant fabric wearing status data through collaborative collection of an integrated multimodal fabric sensing device and a thermal, moisture and force sensing network, and preprocessing the flame-retardant fabric wearing status data; S2, analyzing the unit thermal drive temperature response capability of the fabric in the wearing state based on the flame-retardant fabric wearing data after grid binding preprocessing, and performing combustion trigger judgment; S3, extracting the ignition time according to the combustion judgment result, quantifying the ignition deviation between the standard test and the wearing state, and correcting the temperature rise path of the test distortion grid to generate a wearing flame-retardant performance response data set; S4, retrieving the wearing flame-retardant performance response data set, evaluating the distortion risk degree of the standard test in the wearing state, determining the dominant distortion source and performing response compensation, and outputting a credibility label and correction path covering the entire domain.

[0010] Furthermore, the specific steps of acquiring the flame retardant fabric wearing state data by collaboratively collecting data through an integrated multimodal fabric sensing device and a thermal, moisture and force sensing network, and preprocessing the flame retardant fabric wearing state data are as follows: collaboratively collecting data through an integrated multimodal fabric sensing device and a thermal, moisture and force sensing network, respectively deploying temperature and humidity sensors, heat flux meters, strain gauges and fabric surface geometry recognition components, continuously recording the heat input, structural deformation and environmental interaction state of the flame retardant fabric during wearing, and acquiring the flame retardant fabric wearing state data, which includes fabric moisture content, surface temperature, heat flux density, wrinkle angle, surface tensile strain, specific heat capacity and latent heat of evaporation; The structured grid interpolation algorithm is used to reconstruct and fill the spatial missing areas in the flame-retardant fabric wearing data, repairing the structural information loss problem caused by fabric wrinkle occlusion, measurement point detachment and sensor failure; the flame-retardant fabric wearing data is smoothed in the time dimension by a double-window sliding average smoothing algorithm, reducing the short-term temperature and heat flux fluctuations caused by environmental disturbances and dynamic movements; the outliers in the flame-retardant fabric wearing data are identified by a shear compression combined with anomaly detection algorithm, eliminating strain anomalies caused by unnatural movements or extreme measurement point deformation; the flame-retardant fabric wearing data is converted to a standard scale by a maximum-minimum normalization algorithm to achieve normalization of the flame-retardant fabric wearing data.

[0011] Furthermore, based on the flame-retardant fabric wearing data after grid binding preprocessing, the specific steps of analyzing the unit heat-driven temperature response ability of the fabric in the wearing state are as follows: map the preprocessed flame-retardant fabric wearing data to the two-dimensional grid area, construct the physical input field of the simulation domain, and bind each grid to a set of measured flame-retardant fabric wearing data; take each grid as the unit, analyze the unit heat-driven temperature response ability of the fabric in the wearing state: divide the heat flux density by the specific heat capacity as the unit temperature rise benchmark item; divide the product of the fabric moisture content and the latent heat of evaporation by the product of the specific heat capacity and the surface temperature, and then subtract this ratio from one as the moisture buffer ratio item; divide the pleat angle by 90 to characterize the change ratio of the effective heated area of ​​the fabric surface, and subtract this change ratio from one as the heat shielding adjustment item; multiply the unit temperature rise benchmark item, the moisture buffer ratio item and the heat shielding adjustment item to obtain the temperature rise response evaluation value.

[0012] Furthermore, the specific steps for executing combustion trigger judgment are as follows: compare the temperature rise response evaluation value of each grid with the temperature rise response threshold in real time, and implement a partitioned asynchronous thermal response strategy: mark the grid cells with temperature rise response evaluation values ​​higher than the temperature rise response threshold as potential high-risk areas, and assign a smaller temperature rise response time step; mark the grids with temperature rise response evaluation values ​​lower than the temperature rise response threshold as low-response areas, and assign a standard time step; use the response label and surface temperature of the grid as the joint triggering conditions for flame spread: the potential high-risk area is judged to be in a combustion state if the surface temperature exceeds the combustion judgment threshold at any time; the low-response area enters a combustion state only when the surface temperature continues to be higher than the combustion judgment threshold for three consecutive combustion judgment cycles.

[0013] Furthermore, the specific steps for extracting the ignition time based on the combustion judgment results and quantifying the ignition deviation between the standard test and the wearing state are as follows: after completing the combustion judgment in the wearing state, track the temperature change process of each grid, and take the time step when the surface temperature first reaches the combustion judgment threshold as the ignition time of the grid in the wearing state; synchronously run the thermal diffusion process of the corresponding grid under the standard conditions of the fabric being flat, dry and strain-free to extract the standard ignition time; subtract the standard ignition time from the ignition time in the wearing state and multiply it by the temperature rise response evaluation value to obtain the ignition response offset term; divide the fabric moisture content by the fabric moisture content plus one, and then subtract this ratio from 1 to obtain the moisture suppression term; multiply the heat flux density, heat shielding adjustment term and moisture suppression term to obtain the comprehensive heat input attenuation term; divide the ignition response offset term by the comprehensive heat input attenuation term to obtain the ignition offset evaluation value.

[0014] Furthermore, the specific steps for correcting the temperature rise path of the test distorted grid and generating a wearing flame retardant performance response data set are as follows: comparing the ignition offset evaluation value with the ignition offset threshold: if the biased ignition offset evaluation value is less than the ignition offset threshold, the grid test result is judged to be credible, marked as a credible area, and its original evaluation path is retained; if the biased ignition offset evaluation value is greater than or equal to the ignition offset threshold, the grid test result is judged to be distorted, and the fabric moisture content, fold angle and surface tensile strain of the grid are extracted and fed back as biasing factors to the correction path of the temperature rise response evaluation value, and the temperature rise response evaluation value is recalculated; then the wearing state ignition time and ignition offset evaluation value of the grid are updated; the evaluation data of the grid that has completed the correction calculation are unified and integrated, and the evaluation data include the temperature rise response evaluation value, the wearing state ignition time and the ignition offset evaluation value to form a wearing flame retardant performance response data set covering the entire domain.

[0015] Furthermore, the specific steps of retrieving the flame retardant performance response data set for wearing and evaluating the degree of distortion risk of the standard test in the wearing state are as follows: Retrieve the flame retardant performance response data set for wearing, and analyze the degree of distortion risk of the standard test in the wearing state based on the temperature rise response evaluation value and the flame retardant fabric wearing data: divide the temperature rise response evaluation value by the heat flux density as the thermal response intensity normalization item; divide the product of the fabric moisture content and the latent heat of evaporation by the product of the specific heat capacity and the surface temperature as the moisture-heat buffer item; convert the wrinkle angle into radians and take the sine value as the thermal shielding nonlinear interference item; add the moisture-heat buffer item, surface tensile strain and shielding nonlinear interference item as the wearing evaluation interference item; multiply the thermal response intensity normalization item by the wearing evaluation interference item to obtain the standard test distortion evaluation value.

[0016] Furthermore, the specific steps of determining the dominant distortion source and performing response compensation, and outputting the credibility label and correction path covering the entire domain are as follows: comparing the standard test distortion evaluation value with the test distortion threshold, and establishing an evaluation credibility classification strategy: if the standard test distortion evaluation value is less than the test distortion threshold, and the corresponding temperature rise response evaluation value is lower than the temperature rise response threshold, then the grid is determined to be a standard evaluation credibility area, and its original test path is retained; otherwise, the grid is determined to be an evaluation distortion risk area; for the grid in the evaluation distortion risk area, the proportion of moisture and heat buffer items, shielding interference items, and tensile strain items in the wearing evaluation interference items is analyzed to determine the dominant distortion source and select the corresponding compensation modeling path: if the moisture and heat buffer item is dominant, the temperature rise response time step is dynamically increased according to the moisture content of the fabric, and the grid is delayed from entering the combustion judgment state to simulate the flame suppression effect in the wet area; if the shielding interference item is dominant, the heat flux of the grid is reconstructed. Density distribution, correct the effective heated area based on the fold angle, and replace the uniform input assumption under the standard state; if the tensile strain term is dominant, dynamically reduce the temperature rise response step and the spread propagation path according to the surface tensile strain, simulate the influence of the structural tension change caused by the strain on the heat conduction rate and the flame advancement direction, and give priority to the high strain area in the temperature rise judgment window; integrate the grid response results of the standard evaluation credible area and the evaluation distortion risk area, update the wearing flame retardant performance response data set, and bind each grid to the temperature rise response evaluation value, ignition offset evaluation value, standard test distortion evaluation value, evaluation status label, dominant component of the wearing evaluation interference item, adjusted temperature rise response time step and combustion judgment trigger mode; use the wearing flame retardant performance response data set to mark the blind area covered by the standard test, and replace the original evaluation path of the distorted area to form a response judgment and path correction closed loop for the real wearing state.

[0017] According to a second aspect of the present invention, a performance control system for flame-retardant fiber fabrics is provided, comprising: a flame-retardant fabric wearing data collection and preprocessing module, a temperature rise response evaluation and combustion judgment module, a response feature fusion and offset identification module, and an evaluation credibility reconstruction and response output module, wherein: the flame-retardant fabric wearing data collection and preprocessing module is used to obtain flame-retardant fabric wearing state data through collaborative collection of an integrated multimodal fabric sensing device and a thermal, moisture and force sensing network, and preprocess the flame-retardant fabric wearing state data; the temperature rise response simulation and combustion judgment module is used to analyze the unit heat-driven temperature response capability of the fabric in the wearing state based on the flame-retardant fabric wearing data after grid binding preprocessing, and perform combustion trigger judgment; the response feature fusion and offset identification module is used to extract the ignition time based on the combustion judgment result, quantify the ignition deviation between the standard test and the wearing state, and correct the temperature rise path of the test distortion grid to generate a wearing flame-retardant performance response data set; the evaluation credibility reconstruction and response output module is used to retrieve the wearing flame-retardant performance response data set, evaluate the distortion risk level of the standard test in the wearing state, determine the dominant distortion source and perform response compensation, and output a credibility label and correction path covering the entire domain.

[0018] The third aspect of the present invention provides a performance control device for flame-retardant fiber fabrics, comprising: a state perception integrator, a thermal drive response analyzer, an ignition offset quantizer, and an adaptability evaluation compensator, wherein: the state perception integrator is used to complete the collection, processing, and structural mapping of multi-source physical data under the wearing state of the fabric; the thermal drive response analyzer is used to analyze the temperature rise behavior under the action of heat input and identify potential high-risk areas for spread; the ignition offset quantizer is used to evaluate the response offset under standard and wearing conditions and perform path correction; the adaptability evaluation compensator is used to determine the evaluation distortion area and implement a response compensation strategy dominated by the wearing factor.

[0019] Beneficial effects

[0020] The present invention has the following beneficial effects:

[0021] (1) The performance control method, system and device of a flame-retardant fiber fabric realizes the quantitative evaluation of the heat-driven temperature rise capability of different areas of the flame-retardant fabric when it is worn by constructing a temperature rise response evaluation value index system, provides a judgment basis for the rapid identification of high-risk areas and asynchronous response strategy, and improves the evaluation model's ability to capture heterogeneous thermal response behavior.

[0022] (2) This flame-retardant fiber fabric performance control method, system and device, by combining multi-physics field CFD simulation and ignition timing comparative analysis, measures the difference between the predicted ignition time under standard test conditions and the ignition time under actual wearing conditions, realizes quantitative judgment of response offset, effectively identifies the evaluation deviation area, and provides data support for subsequent thermal response correction and model compensation, thereby enhancing the evaluation model's ability to identify and regulate the time lag effect in real wearing scenarios.

[0023] (3) The performance control method, system and device for flame-retardant fiber fabrics, by introducing a standard test distortion evaluation value index system, realizes quantitative judgment of the degree of applicability deviation of standard evaluation results under different wearing conditions, and supports marking credibility levels by grid area, thereby enhancing the model's ability to adapt to complex wearing conditions.

[0024] (4) This flame-retardant fiber fabric performance control method, system and device can dynamically correct the temperature rise response time step and spread judgment strategy according to the dominant influence of the moisture and heat buffer term, the shielding interference term or the tensile strain term by establishing a closed-loop correction path for the evaluation deviation and constructing a response compensation mechanism driven by the wearing factor, thereby improving the modeling integrity of the simulation process for the actual deformation-heat coupling effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 The present invention is a flow chart of a method for controlling the performance of flame-retardant fiber fabrics;

[0026] Figure 2 This is a structural diagram of a performance control system for a flame-retardant fiber fabric;

[0027] Figure 3 This is the evaluation value and threshold analysis diagram of the simulated grid temperature rise response;

[0028] Figure 4 Distortion decision map for mesh-level standard evaluation under wearing conditions. DETAILED DESCRIPTION

[0029] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0030] See also Figure 1-Figure 4, an embodiment of the present invention provides a technical solution: a performance control method, system and device for flame-retardant fiber fabrics, comprising the following steps: S1, acquiring flame-retardant fabric wearing status data through collaborative collection of an integrated multimodal fabric sensing device and a thermal, moisture and force sensing network, and preprocessing the flame-retardant fabric wearing status data; S2, analyzing the unit heat-driven temperature response capability of the fabric in the wearing state based on the flame-retardant fabric wearing data after grid binding preprocessing, and performing combustion trigger judgment; S3, extracting the ignition time according to the combustion judgment result, quantifying the ignition deviation between the standard test and the wearing state, and correcting the temperature rise path of the test distortion grid to generate a wearing flame-retardant performance response data set; S4, retrieving the wearing flame-retardant performance response data set, evaluating the distortion risk degree of the standard test in the wearing state, determining the dominant distortion source and performing response compensation, and outputting a credibility label and correction path covering the entire domain.

[0031] Specifically, the flame retardant fabric wearing state data is obtained by integrating a multimodal fabric sensing device and a thermal, moisture and force sensing network, and the specific steps of preprocessing the flame retardant fabric wearing state data are as follows: by integrating a multimodal fabric sensing device and a thermal, moisture and force sensing network, respectively, temperature and humidity sensors, heat flux meters, strain gauges and fabric surface geometry recognition components are deployed to continuously record the heat input, structural deformation and environmental interaction state of the flame retardant fabric during the wearing process, and obtain the flame retardant fabric wearing state data. The flame retardant fabric wearing data includes fabric moisture content, surface temperature, heat flux density, fold angle, surface Surface tensile strain, specific heat capacity, and latent heat of evaporation; among them, the moisture content of the fabric is obtained through a fabric-embedded micro-humidity sensor; the surface temperature is obtained through a high-precision surface infrared temperature measuring element; the heat flux density is obtained through a fabric surface heat flux meter; the wrinkle angle is extracted through a surface morphology visual recognition component; by arranging high-sensitivity resistance strain gauges in areas prone to deformation on the fabric surface, the degree of tensile deformation of the fabric when worn is monitored in real time, and the surface tensile strain value is obtained; the specific heat capacity is obtained by matching the actual material of the fabric through the material specific heat capacity parameter database; the latent heat of evaporation is obtained through the linkage measurement of fabric component analysis and thermal analysis equipment. Then, the spatial missing areas in the flame-retardant fabric wearing data are reconstructed and filled through the structural grid interpolation algorithm, repairing the structural information loss problem caused by fabric wrinkle occlusion, measurement point detachment and sensor failure; the flame-retardant fabric wearing data is smoothed in the time dimension through the double-window sliding average smoothing algorithm, reducing the short-term temperature and heat flux fluctuations caused by environmental disturbances and dynamic movements; the outliers in the flame-retardant fabric wearing data are identified through the shear compression combined with the anomaly detection algorithm, and the strain anomalies caused by unnatural movements or extreme measurement point deformation are eliminated; the flame-retardant fabric wearing data is converted to a standard scale through the maximum and minimum normalization algorithm to achieve the normalization of the flame-retardant fabric wearing data.

[0032] In this implementation, a multimodal fabric sensing device is coordinated with a thermal, moisture, and force sensing network to independently extract moisture content, surface temperature, heat flux density, wrinkle angle, surface tensile strain, specific heat capacity, and latent heat of evaporation from flame-retardant fabric wearing state data, ensuring that each physical quantity has a clear measurement source and physical unit basis. Furthermore, through a structured grid interpolation, sliding average smoothing, combined anomaly detection, and normalization process, the data is preprocessed to ensure spatial integrity, temporal stability, data reliability, and scale uniformity. This provides accurate and stable physical input support for subsequent thermal response modeling and regional assessment mechanisms based on measured input.

[0033] Specifically, based on the flame-retardant fabric wearing data after grid binding pretreatment, the specific steps of analyzing the unit heat-driven temperature response ability of the fabric in the wearing state are as follows: map the pretreated flame-retardant fabric wearing data to the two-dimensional grid area, construct the physical input field of the simulation domain, and bind each grid to a set of measured flame-retardant fabric wearing data, including fabric moisture content, surface temperature, heat flux density, fold angle, surface tensile strain, specific heat capacity and latent heat of evaporation; take each grid as a unit, analyze the unit heat-driven temperature response ability of the fabric in the wearing state: divide the heat flux density by the specific heat capacity, and extract it as the benchmark item of the heating ability under unit heat input conditions; divide the fabric moisture content by the evaporation The product term of latent heat is used as a characterizing factor of the moisture and heat buffering capacity of the fabric, and then divided by the product of specific heat and surface temperature. The calculated result is used as the moisture and heat buffer proportion term, which reflects the delayed inhibition effect of local moisture content in the fabric on the thermal response process; the fold angle is divided by 90 to extract the influence of the geometric shielding degree of the fabric surface on the directional disturbance of heat input, and further used as the heat shielding adjustment term minus the angle ratio to correct the effective heated area of ​​local non-flat areas; the unit temperature rise benchmark term, the moisture and heat buffer proportion term and the heat shielding adjustment term are multiplied to obtain the temperature rise response evaluation value after comprehensively considering the heat input intensity, moisture suppression effect and structural shielding characteristics.

[0034] The specific calculation formula for the temperature rise response evaluation value is:

[0035] ;

[0036] Where S represents the temperature rise response evaluation value, Q represents the heat flux density, C represents the specific heat capacity, W represents the moisture content of the fabric, L represents the latent heat of evaporation, and D represents the surface temperature. Indicates the fold angle.

[0037] In this embodiment, Table 1 is a temperature rise response evaluation value data table, listing the measured input parameters and corresponding temperature rise response evaluation value calculation results for five grids in the wearing state. The variables included in the data table include heat flux density, specific heat capacity, fabric moisture content, latent heat of evaporation, surface temperature, pleat angle, and the final calculated temperature rise response evaluation value. For grid C1, the heat flux density is 20.62, the specific heat capacity is 1.378, the fabric moisture content is 0.152, the latent heat of evaporation is 2250, the surface temperature is 321.0, and the pleat angle is 48.4. The calculated temperature rise response evaluation value is 3.56. For grid C2, the heat flux density is 29.26, the specific heat capacity is 1.329, the fabric moisture content is 0.076, the latent heat of evaporation is 2250, the surface temperature is 328.3, and the pleat angle is 34.2. The calculated temperature rise response evaluation value is 5.23. The heat flux density of grid C3 is 25.98, the specific heat capacity is 1.733, the fabric moisture content is 0.117, the latent heat of evaporation is 2250, the surface temperature is 341.5, and the pleat angle is 38.8. The calculated temperature rise response evaluation value is 4.73. The heat flux density of grid C4 is 253.98, the specific heat capacity is 1.601, the fabric moisture content is 0.127, the latent heat of evaporation is 2250, the surface temperature is 335.9, and the pleat angle is 41.0. The calculated temperature rise response evaluation value is 3.82. The heat flux density of grid C5 is 17.34, the specific heat capacity is 1.654, the fabric moisture content is 0.056, the latent heat of evaporation is 2250, the surface temperature is 327.5, and the pleat angle is 43.7. The calculated temperature rise response evaluation value is 4.14.

[0038] Table 1 Temperature rise response evaluation value data table

[0039]

[0040] like Figure 3 The figure shows the temperature rise response evaluation value and threshold analysis diagram of the simulated grid. The figure shows the changes in the temperature rise response evaluation value of the five grids under the wearing state. The horizontal axis is the grid number, and the vertical axis is the temperature rise response evaluation value of the corresponding grid. The gray dotted line marks the temperature rise response threshold, the red data points mark the potential high-risk area, and the blue data points mark the low response area. Among them, the temperature rise response evaluation values ​​of grids C2 and C3 are higher than the temperature rise response threshold and are marked as potential high-risk areas, displayed as red data points; the temperature rise response evaluation values ​​of the remaining grids are lower than the temperature rise response threshold and are marked as low response areas, displayed as blue data points. This figure intuitively reflects the difference in thermal drive response intensity of different grids under non-homogeneous wearing conditions, which helps to quickly identify local areas with prominent thermal sensitivity and further supports the setting of spread prediction paths and the construction of response step control strategies.

[0041] In this implementation, pre-processed flame-retardant fabric wear data is mapped to a two-dimensional simulation grid region and a physical input field is constructed for the simulation domain, achieving a structured binding of fabric moisture content, surface temperature, heat flux density, wrinkle angle, surface tensile strain, specific heat capacity, and latent heat of evaporation within each grid. By constructing a unit temperature rise benchmark term, a moisture-heat buffer ratio term, and a thermal shielding adjustment term, the system comprehensively characterizes the local influence of heat input intensity, fabric moisture content, and surface geometric perturbations, ultimately forming a partitioned calculation mechanism for temperature rise response assessment. This helps reveal the heterogeneous thermal response capabilities of fabrics under real-world wear conditions and provides fundamental indicators for subsequent asynchronous propagation trigger determination and response time step adjustment.

[0042] Specifically, the specific steps for executing combustion trigger judgment are as follows: The temperature rise response evaluation value of each grid is compared with the temperature rise response threshold in real time, and a partitioned asynchronous thermal response strategy is implemented based on the coupling of heat flux density, specific heat capacity, fabric moisture content, latent heat of evaporation, surface temperature, fold angle, and surface tensile strain: Grid cells with temperature rise response evaluation values ​​higher than the temperature rise response threshold are marked as potential high-risk areas. Such grids are usually accompanied by high heat flux density, low specific heat capacity, high fold angle, and significant stretching state, which are prone to thermal stress response. A smaller temperature rise response time step is assigned to them to improve the response resolution; Meshes with temperature-rise response assessment values ​​lower than the temperature-rise response threshold are marked as low-response areas. Such areas generally have high specific heat capacity, low moisture content, and limited temperature-rise capacity. A standard time step is assigned to them to maintain response stability. The response label and surface temperature of the grid are used as the joint triggering conditions for flame spread: potential high-risk areas are judged to be in a combustion state if the surface temperature exceeds the combustion judgment threshold at any time, reflecting their rapid response thermal instability characteristics. Low-response areas only enter a combustion state when the surface temperature continues to be higher than the combustion judgment threshold for three consecutive combustion judgment cycles, reflecting their hysteresis in temperature-rise response.

[0043] In this implementation, a partitioned asynchronous thermal response mechanism is constructed through real-time comparison of temperature-rise response assessments with temperature-rise response thresholds, combined with multi-source inputs consisting of heat flux density, specific heat capacity, fabric moisture content, latent heat of evaporation, surface temperature, wrinkle angle, and surface tensile strain. This mechanism distinguishes between potentially high-risk and low-response areas, assigning differentiated temperature-rise response time steps to each. Furthermore, the response label is combined with the surface temperature to trigger combustion state determination. This improves the flame spread model's ability to identify heterogeneous thermal response behaviors under wear conditions and enhances the accuracy of dynamic capture of early combustion initiation processes within the simulation domain.

[0044] Specifically, the specific steps of extracting the ignition time according to the combustion judgment results and quantifying the ignition deviation between the standard test and the wearing state are as follows: after completing the combustion judgment in the wearing state, based on the surface temperature change process recorded in the flame-retardant fabric wearing data, track the temperature evolution trajectory of each grid, and take the time step when the surface temperature first reaches the combustion judgment threshold as the grid's wearing state ignition time. This time node reflects the earliest combustion response of the fabric under the combined influence of fabric moisture content, heat flux density, fold angle, specific heat capacity and surface tensile strain; synchronously run the thermal diffusion process of the corresponding grid under the standard conditions of flatness, dryness and no strain of the fabric, and extract the standard ignition time without considering the influence of structural disturbance and moisture and heat, as a reference for the response time of the corresponding area in the standard test results; the wearing state The state ignition time is subtracted from the standard ignition time and multiplied by the temperature rise response evaluation value. This operation combines the response time difference and the local thermal sensitivity characteristics as the ignition response offset term, which is used to reflect the degree of disturbance of the ignition rhythm under actual wearing conditions; the fabric moisture content is divided by the fabric moisture content plus one, and then this ratio is subtracted from 1 as the moisture inhibition term, which is used to characterize the buffering effect of the local moisture state of the fabric on heat accumulation; the heat flux density, the heat shielding adjustment term and the moisture inhibition term are multiplied together to form a comprehensive heat input weakening term, which further quantifies the joint effect of the pleat angle, moisture heat buffering and heat input intensity; the ignition response offset term is divided by the comprehensive heat input weakening term to obtain the ignition offset evaluation value, which is used as the criterion variable for quantifying the degree of ignition timing offset, and is used to identify the timeliness mismatch risk of the standard test results under wearing conditions.

[0045] The specific calculation formula for the ignition offset evaluation value is:

[0046] ;

[0047] Where E represents the ignition offset evaluation value, Indicates the ignition time in wearing state, represents the standard ignition time, S represents the temperature rise response evaluation value, Q represents the heat flux density, Indicates the wrinkle angle, and W indicates the moisture content of the fabric.

[0048] In this implementation, the time steps at which the surface temperature reaches the combustion threshold are tracked to extract the worn ignition time and the standard ignition time. This is combined with the temperature rise response assessment to construct an ignition response offset term. This term incorporates fabric moisture content, heat flux density, specific heat capacity, surface temperature, pleat angle, and thermal shielding adjustments to form a comprehensive heat input attenuation term. Ultimately, an ignition offset assessment value is calculated. This assessment quantifies the difference in ignition time between standard testing and actual wear conditions, capturing the rhythmic changes in combustion response caused by both the moisture and heat conditions and structural disturbances. This provides a benchmark for subsequent evaluation of distortion identification and response correction mechanisms.

[0049] Specifically, the specific steps for correcting the temperature rise path of the test distorted grid and generating a data set of flame retardant performance response of clothing are as follows: compare the ignition offset evaluation value with the ignition offset threshold, and judge whether the ignition timing of the current area deviates from the standard test expectation based on the temperature rise response evaluation value, ignition response offset item and comprehensive heat input weakening item corresponding to each grid; if the ignition offset evaluation value is less than the ignition offset threshold, the grid test result is judged to be credible, marked as a credible area, and its original evaluation path is retained, and the response process of the grid based on heat flux density, specific heat capacity and fold angle is maintained; if the ignition offset evaluation value is greater than or equal to the ignition offset threshold, the grid test result is judged to be distorted, and the surface corresponding to the grid is extracted. The moisture content, wrinkle angle and surface tensile strain of the material are used as biasing factors to feed back to the correction path of the temperature rise response evaluation value. The temperature rise response evaluation value is recalculated on the basis of reconstructing the unit temperature rise benchmark item, the moisture heat buffer ratio item and the heat shielding adjustment item; then, combined with the corrected thermal driving capacity, the wearing state ignition time and ignition offset evaluation value of the grid are updated to reflect the regulatory effect of the actual structural state of the fabric on the combustion response; the evaluation data of the grid that has completed the correction calculation are unified and integrated, and the evaluation data include the temperature rise response evaluation value, the wearing state ignition time and the ignition offset evaluation value, to form a wearing flame retardant performance response data set covering all test result distorted grids, providing basic data support for the subsequent evaluation structure output.

[0050] In this implementation, the credibility of the test results is determined by comparing the ignition offset assessment value with the ignition offset threshold. A local response structure is constructed, consisting of the temperature rise response assessment value, the ignition time under wear, and the ignition offset assessment value. For grids with deviated ignition rhythms, the fabric moisture content, wrinkle angle, and surface tensile strain are extracted as biasing factors and fed back into the evaluation path. Key thermal input parameters are recalculated, and the thermal drive capacity is corrected. Finally, the calculation results of each grid are unified and integrated to generate a wear flame retardant performance response dataset. This dataset provides a dynamic compensation expression of flame retardant behavior under wear, enhancing the evaluation results' adaptability to fabric structural perturbations and thermal-moisture coupling.

[0051] Specifically, the specific steps for retrieving the flame retardant performance response data set and evaluating the distortion risk degree of the standard test in the wearing state are as follows: retrieve the flame retardant performance response data set, extract the normalized flame retardant fabric wearing data such as the temperature rise response evaluation value, fabric moisture content, latent heat of evaporation, heat flux density, specific heat capacity, surface temperature, surface tensile strain and wrinkle angle bound to each grid, construct a distortion risk discrimination structure, and analyze the distortion risk degree of the standard test in the wearing state; divide the temperature rise response evaluation value by the heat flux density, extract the response intensity based on the heat input, and normalize it to measure the unit heat flow. the warming potential of the fabric; the product of the moisture content and the latent heat of evaporation is divided by the product of the specific heat capacity and the surface temperature to construct a moisture-heat buffer term, which is used to quantify the thermal inhibition effect of the local moisture state of the fabric during the temperature rise process; the fold angle is converted into radians and its sine value is taken as the thermal shielding nonlinear interference term, which is used to characterize the first-order disturbance effect of the surface geometric disturbance on the directionality of the heat input; the moisture-heat buffer term, the surface tensile strain and the thermal shielding nonlinear interference term are added together to form the wearing evaluation interference term, which is used to aggregate the key interference components that affect the stability of the thermal response; the thermal response intensity is normalized and multiplied by the wearing evaluation interference term to obtain the standard test distortion evaluation value.

[0052] The specific calculation formula for the standard test distortion evaluation value is:

[0053] ;

[0054] Where Z represents the standard test distortion evaluation value, S represents the temperature rise response evaluation value, Q represents the heat flux density, W represents the fabric moisture content, L represents the latent heat of evaporation, C represents the specific heat capacity, and D represents the surface temperature. represents the surface tensile strain, Indicates the fold angle.

[0055] In this embodiment, Table 2 is a table of standard test distortion evaluation values, listing the wear state input data for five simulation grids and the corresponding standard test distortion evaluation value calculation results. The variables included in the data table include: temperature rise response evaluation value, heat flux density, fabric moisture content, latent heat of evaporation, specific heat capacity, surface temperature, surface tensile strain, fold angle, and the resulting standard test distortion evaluation value. For grid G1, the temperature rise response evaluation value is 8.48, the heat flux density is 21.35, the fabric moisture content is 0.151, the latent heat of evaporation is 2250, the specific heat capacity is 1.695, the surface temperature is 348.1, the surface tensile strain is 0.132, and the fold angle is 32.8. The calculated standard test distortion evaluation value is 0.496. The temperature rise response evaluation value for grid G2 is 6.43, the heat flux density is 29.71, the fabric moisture content is 0.209, the latent heat of evaporation is 2250, the specific heat capacity is 1.473, the surface temperature is 361.0, the surface tensile strain is 0.136, the wrinkle angle is 43.0, and the calculated standard test distortion evaluation value is 0.368. The temperature rise response evaluation value for grid G3 is 6.13, the heat flux density is 25.27, the fabric moisture content is 0.166, the latent heat of evaporation is 2250, the specific heat capacity is 1.470, the surface temperature is 353.5, the surface tensile strain is 0.123, the wrinkle angle is 42.9, and the calculated standard test distortion evaluation value is 0.369. The temperature rise response evaluation value for grid G4 is 7.76, the heat flux density is 22.21, the fabric moisture content is 0.109, the latent heat of evaporation is 2250, the specific heat capacity is 1.613, the surface temperature is 346.7, the surface tensile strain is 0.129, the wrinkle angle is 44.8, and the calculated standard test distortion evaluation value is 0.444. The temperature rise response evaluation value for grid G5 is 8.60, the heat flux density is 20.88, the fabric moisture content is 0.160, the latent heat of evaporation is 2250, the specific heat capacity is 1.613, the surface temperature is 353.3, the surface tensile strain is 0.163, the wrinkle angle is 42.8, and the calculated standard test distortion evaluation value is 0.607.

[0056] Table 2 Standard test distortion evaluation value data table

[0057]

[0058] like Figure 4The figure shows a grid-level standard evaluation distortion determination diagram under different wearing conditions. It displays the standard test distortion assessment values ​​for five grid areas under different wearing conditions, and uses color to distinguish between the standard evaluation trustworthy areas and the evaluation distortion risk areas. The horizontal axis of the figure represents the grid number, and the vertical axis represents the standard test distortion assessment value for the corresponding grid. The gray dashed line represents the test distortion threshold. Grid G5's standard test distortion assessment value exceeds the test distortion threshold and is determined to be in the evaluation distortion risk area, shown as a red column. The remaining grids' assessment values ​​are below the test distortion threshold, marked as blue columns, and are determined to be in the standard evaluation trustworthy areas. This diagram helps identify the adaptability limitations of the standard evaluation method under different wearing conditions, thereby guiding subsequent compensation modeling and activation of response correction mechanisms.

[0059] In this implementation scheme, by calling the wearing flame retardant performance response data set, a standard test distortion evaluation value calculation path is constructed based on the temperature rise response evaluation value, heat flux density, fabric moisture content, latent heat of evaporation, specific heat capacity, surface temperature, surface tensile strain and wrinkle angle, forming a step-by-step derivation structure of thermal response intensity normalization term, moisture and heat buffer term, thermal shielding nonlinear interference term and wearing evaluation interference term, to achieve quantitative evaluation of the degree of standard test credibility deviation of each grid in the wearing state, provide direct indicator support for identifying the evaluation distortion area, and enhance the adaptive discrimination ability of the evaluation mechanism to multi-source disturbance input conditions.

[0060] Specifically, the specific steps of determining the dominant distortion source and performing response compensation, and outputting the credibility label and correction path covering the entire domain are as follows: Compare the standard test distortion evaluation value with the test distortion threshold, and establish an evaluation credibility classification strategy: If the standard test distortion evaluation value is less than the test distortion threshold, and the corresponding temperature rise response evaluation value is lower than the temperature rise response threshold, then the grid is determined to be a standard evaluation credibility area, and its original test path is retained; otherwise, the grid is determined to be an evaluation distortion risk area; for the grid in the evaluation distortion risk area, analyze the proportion of moisture and heat buffer items, shielding interference items, and tensile strain items in the wearing evaluation interference items to determine the dominant distortion source and select the corresponding compensation modeling path: If the moisture and heat buffer item is dominant, dynamically increase the temperature rise response time step according to the moisture content of the fabric, and delay the grid from entering the combustion judgment state to simulate the flame suppression effect in the wet area; if the shielding interference item is dominant, reconstruct the heat flux density of the grid. The effective heated area is corrected based on the wrinkle angle to replace the uniform input assumption under the standard state. If the tensile strain term is dominant, the temperature rise response step and the propagation path are dynamically reduced according to the surface tensile strain to simulate the influence of the structural tension change caused by the strain on the heat conduction rate and the flame advancement direction, and the high strain area is preferentially included in the temperature rise judgment window. The grid response results of the standard evaluation credible area and the evaluation distortion risk area are integrated to update the flame retardant performance response dataset of the clothing. Each grid is bound to the temperature rise response evaluation value, the ignition offset evaluation value, the standard test distortion evaluation value, the evaluation state label, the dominant component of the wearing evaluation interference item, the adjusted temperature rise response time step and the combustion judgment triggering mode. The flame retardant performance response dataset of the clothing is used to mark the blind area covered by the standard test and replace the original evaluation path of the distorted area to form a response judgment and path correction closed loop for the real wearing state.

[0061] In this implementation plan, a standard assessment credibility classification strategy is constructed by jointly comparing the standard test distortion assessment value with the test distortion threshold, combined with the response level of the temperature rise response assessment value, to determine the assessment status label of each grid. After identifying the assessment distortion risk area, the component proportions of the moisture buffer item, shielding interference item, and tensile strain item in the wearing assessment interference items are extracted to clarify the dominant distortion source. Response compensation modeling paths driven by fabric moisture content, wrinkle angle, and surface tensile strain are established, respectively, and differentiated corrections are made to the temperature rise response time step and flame spread judgment method. Finally, the various correction results are unified and integrated with the assessment credibility zone data to construct a wearing flame retardant performance response data set that binds the temperature rise response assessment value, ignition offset assessment value, standard test distortion assessment value, and compensation path parameters. This is used to replace the original test output of the distorted area, completing the closed-loop correction of the standard test path to the response structure under the actual wearing state.

[0062] like Figure 2As shown, the second aspect of the present invention provides a performance control system for flame-retardant fiber fabrics, including: a flame-retardant fabric wearing data acquisition and preprocessing module, a temperature rise response evaluation and combustion judgment module, a response feature fusion and offset identification module, and an evaluation credibility reconstruction and response output module, wherein: the flame-retardant fabric wearing data acquisition and preprocessing module is used to obtain flame-retardant fabric wearing state data through the coordinated acquisition of an integrated multimodal fabric sensing device and a thermal, moisture and force sensing network, and preprocess the flame-retardant fabric wearing state data; the temperature rise response simulation and combustion judgment module is used to analyze the unit heat-driven temperature response capability of the fabric in the wearing state based on the flame-retardant fabric wearing data after grid binding preprocessing, and perform combustion trigger judgment; the response feature fusion and offset identification module is used to extract the ignition time based on the combustion judgment result, quantify the ignition deviation between the standard test and the wearing state, and correct the temperature rise path of the test distortion grid to generate a wearing flame-retardant performance response data set; the evaluation credibility reconstruction and response output module is used to call the wearing flame-retardant performance response data set, evaluate the distortion risk level of the standard test in the wearing state, determine the dominant distortion source and perform response compensation, and output a credibility label and correction path covering the entire domain.

[0063] In this implementation scheme, by constructing a performance control system consisting of a flame-retardant fabric wearing data acquisition and preprocessing module, a temperature rise response simulation and combustion judgment module, a response feature fusion and offset identification module, and an evaluation credibility reconstruction and response output module, a thermal response judgment path based on the measured wearing state data is established, and the structured input of fabric moisture content, surface temperature, heat flux density, wrinkle angle, surface tensile strain, specific heat capacity and latent heat of evaporation, dynamic extraction of temperature rise response evaluation value and ignition offset evaluation value, credibility identification of standard test distortion evaluation value and differentiated correction of response parameters are realized in turn, forming a closed-loop driven global response control mechanism, which provides multi-scale and multi-factor collaborative support for the accurate modeling of flame retardant performance for real wearing conditions.

[0064] The third aspect of the present invention provides a performance control device for flame-retardant fiber fabrics, comprising: a state perception integrator, a thermal drive response analyzer, an ignition offset quantizer, and an adaptability evaluation compensator, wherein: the state perception integrator is used to complete the collection, processing, and structural mapping of multi-source physical data under the wearing state of the fabric; the thermal drive response analyzer is used to analyze the temperature rise behavior under the action of heat input and identify potential high-risk areas for spread; the ignition offset quantizer is used to evaluate the response offset under standard and wearing conditions and perform path correction; the adaptability evaluation compensator is used to determine the evaluation distortion area and implement a response compensation strategy dominated by the wearing factor.

[0065] In this implementation scheme, by constructing a performance control device consisting of a state perception integrator, a thermal drive response analyzer, an ignition offset quantifier and an adaptability assessment compensator, the integrated collection and structural mapping of the moisture content, heat flux density, surface temperature, wrinkle angle, surface tensile strain, specific heat capacity and latent heat of evaporation of the flame-retardant fabric in the wearing state are realized, and then the determination of the temperature rise response evaluation value, the positioning of the high-risk area, the calculation of the ignition offset evaluation value and the output of the difference compensation strategy in the path correction process are completed, and a model compensation mechanism covering thermal input response analysis, standard test credibility judgment and wearing factor is constructed, providing a unified physical quantity input and structural level output path for the determination and regulation of flame retardant behavior under the action of multiple physical fields.

[0066] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0067] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to the specific embodiments described. Obviously, many modifications and variations are possible based on the content of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for controlling the performance of flame-retardant fiber fabrics, characterized in that: The following steps are involved: S1, acquires the wearing status data of flame-retardant fabrics through collaborative collection of the integrated multimodal fabric sensing device and the thermal, moisture and force sensing network, and pre-processes the wearing status data of flame-retardant fabrics; S2, based on the flame-retardant fabric wearing data after grid binding preprocessing, analyzes the unit heat-driven temperature response capability of the fabric in the wearing state and performs combustion trigger judgment; The specific steps of analyzing the unit heat-driven temperature response capability of the fabric in the wearing state based on the flame-retardant fabric wearing data after grid binding preprocessing are as follows: The pre-processed flame-retardant fabric wearing data is mapped to a two-dimensional grid area to construct the physical input field of the simulation domain. Each grid is bound to a set of measured flame-retardant fabric wearing data. Taking each grid as a unit, the unit heat-driven temperature response capability of the fabric under wear is analyzed: the heat flux density is divided by the specific heat capacity as the unit temperature rise benchmark term; the product of the fabric moisture content and the latent heat of evaporation is divided by the product of the specific heat capacity and the surface temperature, and this ratio is subtracted from one to obtain the moisture heat buffer ratio term; the pleat angle is divided by 90 to represent the change ratio of the effective heated area of ​​the fabric surface, and this change ratio is subtracted from one to obtain the thermal shielding adjustment term; the unit temperature rise benchmark term, the moisture heat buffer ratio term, and the thermal shielding adjustment term are multiplied together to obtain the temperature rise response assessment value; The specific steps of executing combustion trigger judgment are as follows: The temperature rise response assessment value of each grid is compared with the temperature rise response threshold in real time, and a partitioned asynchronous thermal response strategy is implemented: grid cells with temperature rise response assessment values ​​higher than the temperature rise response threshold are marked as potential high-risk areas and assigned a smaller temperature rise response time step; grid cells with temperature rise response assessment values ​​lower than the temperature rise response threshold are marked as low-response areas and assigned a standard time step; The grid's response label and surface temperature are used as the combined triggering conditions for flame spread: a potential high-risk area is considered to be in a burning state if its surface temperature exceeds the combustion judgment threshold at any time; a low-response area enters a burning state only if its surface temperature remains above the combustion judgment threshold for three consecutive combustion judgment cycles. S3: Extract the ignition time based on the combustion judgment results, quantify the ignition deviation between the standard test and the worn state, and correct the temperature rise path of the test distortion grid to generate a wearing flame retardant performance response data set; The specific steps of extracting the ignition time based on the combustion judgment result and quantifying the ignition deviation between the standard test and the wearing state are as follows: After the combustion judgment is completed in the wearing state, the temperature change process of each grid is tracked, and the time step when the surface temperature first reaches the combustion judgment threshold is used as the grid's wearing state ignition time; Simultaneously run the thermal diffusion process of the corresponding grid under standard conditions of fabric flatness, dryness and no strain, and extract the standard ignition time; Subtract the standard ignition time from the wearing ignition time and multiply it by the temperature rise response assessment value to obtain the ignition response offset term. Divide the fabric moisture content by the fabric moisture content plus one, and then subtract this ratio from 1 to obtain the moisture suppression term. Multiply the heat flux density, heat shielding adjustment term, and moisture suppression term to obtain the comprehensive heat input attenuation term. Divide the ignition response offset term by the comprehensive heat input attenuation term to obtain the ignition offset assessment value. S4 retrieves the flame retardant performance response dataset of the wearer, evaluates the distortion risk of the standard test under the wear state, determines the dominant distortion source and performs response compensation, and outputs the credibility label and correction path covering the entire domain.

2. The method for controlling the properties of a flame-retardant fiber fabric according to claim 1, wherein: The specific steps of acquiring the flame retardant fabric wearing status data by integrating the multimodal fabric sensing device and the thermal, moisture and force sensing network and preprocessing the flame retardant fabric wearing status data are as follows: By integrating a multimodal fabric sensing device with a thermal, moisture and force sensing network for collaborative collection, temperature and humidity sensors, heat flow meters, strain gauges and fabric surface geometry recognition components are deployed to continuously record the heat input, structural deformation and environmental interaction state of flame-retardant fabrics during wearing, and obtain the flame-retardant fabric wearing status data. The flame-retardant fabric wearing data includes fabric moisture content, surface temperature, heat flux density, wrinkle angle, surface tensile strain, specific heat capacity and latent heat of evaporation. The structural grid interpolation algorithm is used to reconstruct and fill in the spatial missing areas in the flame-retardant fabric wearing data, repairing the structural information loss caused by fabric wrinkles, measurement point loss and sensor failure. The flame-retardant fabric wearing data is smoothed in the time dimension using a double-window sliding average smoothing algorithm to reduce short-term temperature and heat flux fluctuations caused by environmental disturbances and dynamic movements. Outliers in the flame-retardant fabric wearing data are identified using a shear-compression combined with anomaly detection algorithm to eliminate strain anomalies caused by unnatural movements or extreme measurement point deformations. The flame-retardant fabric wearing data is converted to a standard scale using a maximum-minimum normalization algorithm to achieve normalization of the flame-retardant fabric wearing data.

3. The method for controlling the properties of a flame-retardant fiber fabric according to claim 1, wherein: The specific steps of correcting the temperature rise path of the test distortion grid and generating the wearing flame retardant performance response data set are as follows: The ignition offset assessment value is compared with the ignition offset threshold: if the biased ignition offset assessment value is less than the ignition offset threshold, the grid test result is determined to be credible, marked as a credible area, and its original assessment path is retained; if the biased ignition offset assessment value is greater than or equal to the ignition offset threshold, the grid test result is determined to be distorted, and the mesh fabric moisture content, fold angle, and surface tensile strain are extracted and fed back as biasing factors to the correction path of the temperature rise response assessment value, and the temperature rise response assessment value is recalculated; then the wearing state ignition time and ignition offset assessment value of the mesh are updated; The evaluation data of the grids that have completed the correction calculation are unified and integrated. The evaluation data include the temperature rise response evaluation value, the ignition time and ignition offset evaluation value of the wearing state, forming a wearing flame retardant performance response data set covering the entire area.

4. The method for controlling the properties of a flame-retardant fiber fabric according to claim 1, wherein: The specific steps of retrieving the flame retardant performance response dataset and evaluating the distortion risk of the standard test in the wearing state are as follows: Retrieving the flame retardant performance response dataset for wearing, and based on the temperature rise response assessment value and flame retardant fabric wearing data, analyzing the distortion risk of the standard test under wearing conditions: dividing the temperature rise response assessment value by the heat flux density as the thermal response intensity normalization term; dividing the product of the fabric moisture content and the latent heat of evaporation by the product of the specific heat capacity and the surface temperature as the moisture buffer term; converting the wrinkle angle into radians and taking the sine value as the thermal shielding nonlinear interference term; The moisture and heat buffer term, surface tensile strain and shielding nonlinear interference terms are added together to serve as the wearing evaluation interference term; the thermal response intensity normalization term is multiplied by the wearing evaluation interference term to obtain the standard test distortion evaluation value.

5. The method for controlling the properties of a flame-retardant fiber fabric according to claim 1, wherein: The specific steps for determining the dominant distortion source, performing response compensation, and outputting a global credibility label and correction path are as follows: The standard test distortion evaluation value is compared with the test distortion threshold to establish an evaluation credibility classification strategy: if the standard test distortion evaluation value is less than the test distortion threshold, and the corresponding temperature rise response evaluation value is lower than the temperature rise response threshold, then the grid is determined to be a standard evaluation credibility area and its original test path is retained; Otherwise, the grid is determined to be an assessment distortion risk area; For the grids in the distortion risk area, the proportion of moisture buffer items, shielding interference items, and tensile strain items in the wearing assessment interference items is analyzed to determine the dominant distortion source and select the corresponding compensation modeling path: If the moisture buffer item is dominant, the temperature rise response time step is dynamically increased according to the moisture content of the fabric, and the grid is delayed from entering the combustion judgment state to simulate the flame suppression effect in the wet area; if the shielding interference item is dominant, the heat flux density distribution of the grid is reconstructed, and the effective heated area is corrected based on the fold angle to replace the uniform input assumption under the standard state; if the tensile strain item is dominant, the temperature rise response step and the propagation path are dynamically reduced according to the surface tensile strain to simulate the influence of the structural tension change caused by the strain on the heat conduction rate and the flame propagation direction, and the high strain area is preferentially included in the temperature rise judgment window; Integrate the grid response results of the standard evaluation trust zone and the evaluation distortion risk zone, update the flame retardant performance response dataset of the clothing, and bind each grid to the temperature rise response evaluation value, ignition offset evaluation value, standard test distortion evaluation value, evaluation status label, dominant component of the wear evaluation interference item, adjusted temperature rise response time step, and combustion judgment trigger mode; The flame retardant performance response dataset of clothing is used to mark the blind areas covered by the standard test and replace the original evaluation path in the distorted area, forming a closed loop of response judgment and path correction for the actual wearing state.

6. A flame retardant fiber fabric performance control system, using a flame retardant fiber fabric performance control method according to any one of claims 1 to 5, characterized in that: include: Flame-retardant fabric wearing data collection and preprocessing module, temperature rise response assessment and combustion judgment module, response feature fusion and offset identification module, and assessment credibility reconstruction and response output module, among which: The flame-retardant fabric wearing data acquisition and preprocessing module is used to acquire the flame-retardant fabric wearing status data through the integrated multi-modal fabric sensing device and the thermal, moisture and force sensing network, and preprocess the flame-retardant fabric wearing status data; The temperature rise response simulation and combustion judgment module is used to analyze the unit heat-driven temperature response capability of the fabric in the wearing state based on the flame-retardant fabric wearing data after grid binding preprocessing, and perform combustion triggering judgment; The response feature fusion and offset identification module is used to extract the ignition time based on the combustion judgment results, quantify the ignition deviation between the standard test and the wearing state, and correct the temperature rise path of the test distortion grid to generate the wearing flame retardant performance response data set; The evaluation credibility reconstruction and response output module is used to retrieve the flame retardant performance response dataset, evaluate the distortion risk level of the standard test in the wearing state, determine the dominant distortion source and perform response compensation, and output the credibility label and correction path covering the entire domain.

7. A flame retardant fiber fabric performance control device, using a flame retardant fiber fabric performance control method according to any one of claims 1 to 5, characterized in that: include: State perception integrator, thermal drive response analyzer, ignition offset quantifier and adaptability assessment compensator, among which: The state perception integrator is used to complete the collection, processing and structural mapping of multi-source physical data of the fabric under wearing conditions; The thermal drive response analyzer is used to analyze the temperature rise behavior under the action of heat input and identify potential high-risk areas for spread; The light-off offset quantifier is used to evaluate the response offset between standard and wearing conditions and perform path correction; The adaptive evaluation compensator is used to determine the evaluation distortion area and implement a response compensation strategy dominated by the wearing factor.

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