Antistatic wear-resistant modification preparation method of polyester fiber fabric

Abstract

The invention relates to the technical field of textile, in particular to an antistatic wear-resistant modified preparation method of a polyester fiber fabric, which comprises the following steps: preparing antistatic yarns, preparing warm-keeping yarns, weaving the fabric by using a weaving machine, and compounding to obtain a fabric gray fabric with a three-layer composite structure; and carrying out after-treatment on the gray fabric to obtain the final anti-static warm-keeping fabric. According to the manufacturing process of the anti-static warm-keeping fabric, a dynamic regulation and control system is introduced in the fiber mixing stage, the spinning stage and the compounding and after-finishing stage, performance related parameters of the actual fabric in each stage are monitored in real time, and spinning manufacturing process data in each stage are determined to be adjusted according to the performance related parameters of the actual fabric; the fluctuation of conductivity and heat retention property of the fabric is reduced or even eliminated, so that the consistency of the actual fabric performance is ensured, and the problems of unstable quality, insufficient reliability and the like of the fabric prepared by only depending on fixed process data in the prior art are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of textiles, in particular to a method for modifying and preparing anti-static and wear-resistant polyester fabric. BACKGROUND

[0002] Anti-static and warm-keeping fabric is a functional textile with both anti-static and high-efficiency warm-keeping performance. It forms a conductive network through blending of conductive fibers (such as carbon fibers and metal fibers) or surface anti-static agent treatment to quickly discharge static electricity. At the same time, it uses hollow structure fibers (such as hollow polyester), far infrared heating materials (such as graphene and ceramic fibers) and multi-layer weaving processes (such as air layer and shake pile) to lock in human body heat and reflect heat energy, achieving long-lasting warmth. The material often combines conductive components (carbon fibers and conductive polyester) with warm-keeping components (wool and acrylic), giving consideration to safety and comfort, and is suitable for winter protective clothing in petrochemical and electronic manufacturing industries, sterile environment surgical gowns in medical field, polar exploration clothing and cold-weather outdoor equipment.

[0003] Chinese Patent Application Publication No. CN117962435A discloses an anti-static and warm-keeping fabric and a manufacturing process, relating to a textile fabric. It includes a base cloth layer, an anti-static layer, a warm-keeping layer, and a windproof layer. The base cloth layer is woven from wear-resistant fibers and polypropylene fibers. The anti-static layer is woven from warp and weft threads, each of which has a plurality of nano silver particles. This eliminates static electricity generated by the fabric and improves its antibacterial effect. The warm-keeping layer is woven from cashmere fibers, cotton fibers, and polyurethane fibers, with the cashmere fibers accounting for 40-45% of the weight, the cotton fibers accounting for 40-45% of the weight, and the polyurethane fibers accounting for 10-20% of the weight. This provides good warm-keeping effect and improves the comfort of the fabric. As can be seen, the manufacturing of the anti-static and warm-keeping fabric of the prior art relies on specific proportions of mixed fibers and process parameters (such as fiber proportion, temperature and pressure). These data are usually optimized based on experience or experiments. However, factors such as differences in individual textile equipment, mechanical operation errors (such as tension fluctuations and weaving speed deviations), and changes in environmental temperature and humidity during production can cause the actual fabric performance to deviate from the preset parameters. Even if the processes are the same, there are still fluctuations in conductivity and warm-keeping performance between batches of fabric. Therefore, fabric prepared only by fixed process data is prone to quality instability and insufficient reliability. SUMMARY

[0004] To this end, the present application provides a method for modifying and preparing anti-static and wear-resistant polyester fabric to overcome the problem of quality instability and insufficient reliability of fabric prepared only by fixed process data in the prior art.

[0005] To achieve the above object, the application provides an anti-static wear-resistant modification preparation method of polyester fiber fabric, comprising the following steps: Anti-static yarn preparation: select base fibers, mix carbon fibers, silver-plated nylon filaments and graphene modified polyester according to a certain proportion, and fully mix them through a mixing machine to obtain first mixed fibers, sample and detect the conductive fiber distribution of the first mixed fibers, adjust the fiber mixing ratio of the first mixed fibers according to the conductive fiber distribution, twist into anti-static yarns by using a siro-spinning process, and measure the resistance of the anti-static yarns in real time and adjust the siro-spinning twist according to the resistance; Warm yarn preparation: mix hollow polyester, far-infrared ceramic fibers and acrylic according to a certain proportion, and fully mix them through a mixing machine to obtain second mixed fibers, spin the warm yarns by using an eddy spinning process, and measure and calculate the bulkiness of the warm yarns in real time and adjust the fiber mixing ratio of the second mixed fibers according to the bulkiness. Use a weaving machine to weave the fabric in three layers, the surface layer is the anti-static layer, the inner layer is the warm layer, the anti-static layer and the warm layer are connected through the linking stitch, monitor the linking point quantity data in real time and correct the warp let-off of the weaving machine according to the linking point quantity data, reserve a composite space for the nano aerogel film between the surface and inner layers, lay the nano aerogel film in the composite space and composite by using a hot press, monitor the thermal reflectivity of the composite area in real time and correct the composite temperature and time according to the thermal reflectivity, and obtain the fabric gray cloth with a three-layer composite structure. Dip the fabric gray cloth in a polypyrrole finishing liquid, monitor the polypyrrole coverage in real time and adjust the polypyrrole finishing liquid according to the coverage, then remove the excess liquid by rolling and drying and solidifying, uniformly spray the nano ceramic finishing agent on the surface of the fabric by using a spraying machine, monitor the far-infrared emissivity data of the fabric in real time and adjust the spraying amount of the nano ceramic finishing agent in real time according to the far-infrared emissivity data of the fabric, and finally make the fabric absorb the amino silicone oil emulsion through the dip-nip tank and then perform preshrinking and setting to obtain the final anti-static and warm fabric.

[0006] Further, the sampling and detecting the conductive fiber distribution of the first mixed fibers and adjusting the fiber mixing ratio of the first mixed fibers according to the conductive fiber distribution comprises the following steps: Randomly extract a plurality of samples from the first mixed fibers, obtain and calculate the conductive fiber proportion data of each sample, calculate the uniformity data of the conductive fiber distribution according to the conductive fiber proportion data, if the uniformity data of the conductive fiber distribution is greater than or equal to a first preset threshold, increase the proportion of the conductive fibers in the first mixed fibers, and retest the uniformity of the first mixed fibers after increasing the proportion of the conductive fibers until the uniformity data of the first mixed fibers is less than the first preset threshold.

[0007] Further, the real-time measurement of the resistance of the anti-static yarns and the adjustment of the siro-spinning twist according to the resistance comprises the following steps: Real-time acquisition of several certain length of anti-static yarn samples and measurement of the resistance of each anti-static yarn sample, calculation of the average resistance, if the average resistance of the anti-static yarn sample is greater than or equal to the second preset threshold, the twist of the Siro spinning is reduced, and the resistance of the anti-static yarn twisted after the reduction of the Siro spinning twist is retested until the average resistance of the anti-static yarn sample is less than the second preset threshold.

[0008] Further, the real-time measurement calculates the loft of the thermal yarn and adjusts the fiber mixing ratio of the second mixed fiber according to the loft includes: Real-time acquisition of a certain length of thermal yarn and weighing, calculating the loft of the thermal yarn according to the length data and weight data of the thermal yarn, if the loft of the thermal yarn is less than or equal to the third preset threshold, increasing the proportion of hollow fibers in the second mixed fiber, and retesting the loft of the thermal yarn spun from the second mixed fiber with increased hollow fiber proportion until the loft of the thermal yarn is greater than the third preset threshold.

[0009] Further, the real-time monitoring of the number of binding points and the correction of the warp let-off of the loom according to the number of binding points includes: Real-time selection of a certain area of fabric and acquisition of the number of binding points, calculation of the real-time deviation according to the number of binding points data, if the real-time deviation is greater than or equal to the preset deviation, the warp let-off of the loom is corrected; The correction of the warp let-off of the loom includes: According to the number of binding points data, the density of the binding points is calculated, and the correction direction is determined according to the density of the binding points: if the density of the binding points is greater than the fourth preset threshold, the warp let-off of the loom is reduced, and if the density of the binding points is less than or equal to the fourth preset threshold, the warp let-off of the loom is increased; The real-time deviation is re-monitored and calculated until the real-time deviation is less than the preset deviation.

[0010] Further, the real-time monitoring of the thermal reflectivity of the composite area and the correction of the composite temperature and time according to the thermal reflectivity includes: The thermal reflectivity of the composite area is monitored in real time by an infrared thermal imager, if the thermal reflectivity of the composite area is less than or equal to the fifth preset threshold, the composite temperature is increased and the composite time is extended according to the preset step length, until the thermal reflectivity of the composite area is greater than the fifth preset threshold.

[0011] Further, real-time monitoring of the polypyrrole coverage rate and adjusting the polypyrrole finishing liquid according to the coverage rate includes: The polypyrrole coverage rate on the surface of the fabric gray cloth is analyzed in real time by SEM image, if the polypyrrole coverage rate is less than or equal to the sixth preset threshold, the concentration of the polypyrrole finishing liquid is increased, until the polypyrrole coverage rate is greater than the sixth preset threshold.

[0012] Further, the real-time adjustment of the spraying amount of the nano-ceramic finishing agent according to the far-infrared emissivity data of the fabric comprises: The far-infrared emissivity data of the fabric is compared with the seventh preset threshold value, and if the infrared emissivity data is less than or equal to the seventh preset threshold value, the spraying amount of the nano-ceramic finishing agent is increased by controlling the spraying machine.

[0013] Further, the surface resistance, static half-life, heat retention rate and thermal resistance value of the anti-static warm-keeping fabric are tested, and the performance of the anti-static warm-keeping fabric is evaluated according to the surface resistance, static half-life, heat retention rate and thermal resistance value of the anti-static warm-keeping fabric.

[0014] On the other hand, the application also provides an anti-static warm-keeping fabric, and the base fiber of the anti-static yarn of the fabric is polyester or polyamide.

[0015] Compared with the prior art, the application has the following beneficial effects: The anti-static and wear-resistant modification preparation method of the polyester fiber fabric introduces a dynamic control system in the fiber mixing stage, the textile stage, the composite and finishing stage, monitors the performance related parameters of each stage of fabric preparation in real time, adjusts the textile manufacturing process data according to the actual fabric performance related parameters, reduces or even eliminates the conductivity and warmth fluctuation of the fabric, ensures the consistency of the actual fabric performance, and solves the problems of unstable quality and insufficient reliability of the fabric prepared by relying on fixed process data in the prior art.

[0016] Further, the application first mixes the base fiber and the conductive fiber in a certain proportion to prepare a first mixed fiber in the anti-static yarn preparation stage, detects the conductive fiber distribution of the obtained first mixed fiber, calculates the uniformity of the conductive fiber distribution according to the detection result, and adjusts the fiber mixing ratio according to the calculation result. Through the above method, the uniformity of the conductive fiber distribution can be accurately quantified and guaranteed, and the consistency of the anti-static performance of the fabric is guaranteed from the source.

[0017] Further, the resistance of the anti-static yarn is negatively correlated with the sirospun twist degree, the fibers are tightly held, the conductive fibers are wrapped in the yarn core, the exposed surface area is reduced, the conductive path of the yarn is physically blocked, the resistance is increased, and the conductive performance of the anti-static yarn is reduced. Therefore, the application measures the resistance of the anti-static yarn in real time in the anti-static yarn preparation stage, adjusts the sirospun twist degree when the resistance is too high, and then reduces the order of magnitude of the resistance of the anti-static yarn, so as to ensure the good conductive performance and resistance consistency of the anti-static yarn.

[0018] Furthermore, this invention utilizes the hollow structure of the hollow polyester in the heat-insulating fiber to store still air. Air has an extremely low thermal conductivity, which can effectively block heat loss. Loft is a core indicator that determines the performance of heat-insulating yarn. For every 10% increase in yarn loft, its thermal resistance (heat-insulating index) can be increased by about 15%-20%. Therefore, this invention measures and calculates the loft of the heat-insulating yarn during the heat-insulating yarn preparation stage. When the measured and calculated loft of the heat-insulating yarn is too low, the proportion of hollow fibers in the second mixed fiber is adjusted and increased, thereby ensuring good heat insulation of the heat-insulating yarn and the consistency of yarn heat insulation.

[0019] Furthermore, this invention ensures uniformity of the joints by real-time monitoring of the number of joints (the number of joints per unit area), preventing interlayer delamination or decreased insulation due to density deviations. Simultaneously, through real-time monitoring of the number / density of joints and closed-loop control of the warp feed, the structural stability of the antistatic layer and the insulation layer can be dynamically coordinated, ensuring a uniform and reliable joint structure. This technology balances the performance requirements of functional fabrics (antistatic, insulation) with production efficiency, making it suitable for the production of high-precision industrial textiles.

[0020] Furthermore, this invention compares real-time monitored thermal reflectivity data of the composite area with a fifth preset threshold to form a closed-loop feedback. Temperature and duration are gradually adjusted using preset step sizes to avoid material thermal damage or equipment instability caused by sudden parameter changes, ensuring process controllability and resulting in a tighter interfacial bond between the antistatic layer, the thermal insulation layer, and the nano-aerogel membrane, thus optimizing antistatic and thermal insulation performance. This dynamic adjustment strategy can adapt to instability in the interfacial bonding quality and function of the fabric due to batch differences in raw materials or environmental fluctuations, improving process robustness. Attached Figure Description

[0021] Figure 1 This is an overall flow chart of the method for preparing antistatic and abrasion-resistant modified polyester fiber fabric according to the present invention. Figure 2 This is a schematic diagram illustrating the process of adjusting the fiber mixing ratio of the first mixed fiber according to the distribution of conductive fibers in an embodiment of the present invention. Figure 3 This is a schematic diagram of the process for adjusting the twist of Siro spinning based on resistance in an embodiment of the present invention; Figure 4 This is a schematic diagram illustrating the process of adjusting the fiber mixing ratio of the second mixed fiber according to the loft of an embodiment of the present invention; Figure 5 This is a schematic diagram illustrating the process of correcting the warp feed of a loom based on the number of joints in an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0023] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0024] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0025] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0026] Please see Figure 1 As shown, a method for preparing antistatic and abrasion-resistant modified polyester fiber fabric includes: S1: Preparation of antistatic yarn: Select the base fiber, mix it with carbon fiber, silver-plated nylon filament and graphene modified polyester in proportion, and mix them thoroughly in a mixer to obtain the first mixed fiber. Take a sample to detect the distribution of conductive fibers in the first mixed fiber, adjust the fiber mixing ratio of the first mixed fiber according to the distribution of conductive fibers, and twist it into antistatic yarn using Siro spinning process. Measure the resistance of the antistatic yarn in real time and adjust the Siro spinning twist according to the resistance. S2: Preparation of thermal insulation yarn: Hollow polyester, far-infrared ceramic fiber and acrylic fiber are mixed in proportion and fully mixed by a mixer to obtain a second mixed fiber. The second mixed fiber is spun into thermal insulation yarn by vortex spinning. The bulkiness of the thermal insulation yarn is measured and calculated in real time, and the fiber mixing ratio of the second mixed fiber is adjusted according to the bulkiness. S3: The fabric is woven using a loom. The outer layer is an antistatic layer, and the inner layer is a thermal insulation layer. The antistatic layer and the thermal insulation layer are connected by a bonding structure. The number of bonding points is monitored in real time, and the warp feed of the loom is adjusted according to the number of bonding points. A composite space for a nano-aerogel membrane is reserved between the outer and inner layers. The nano-aerogel membrane is laid flat in the composite space and composited using a hot press. The heat reflectivity of the composite area is monitored in real time, and the composite temperature and time are adjusted according to the heat reflectivity to obtain a fabric with a three-layer composite structure. S4: The fabric is impregnated with polypyrrole finishing liquid, the polypyrrole coverage is monitored in real time and the polypyrrole finishing liquid is adjusted according to the coverage. Then, excess liquid is removed by squeezing with rollers and dried and cured. The nano-ceramic finishing agent is evenly sprayed onto the fabric surface by a sprayer. The far-infrared emissivity data of the fabric is monitored in real time and the amount of nano-ceramic finishing agent sprayed is adjusted according to the far-infrared emissivity data of the fabric. Finally, the fabric is pre-shrinked and shaped after absorbing amino silicone oil emulsion in the padding tank to obtain the final antistatic and thermal insulation fabric.

[0027] The antistatic and thermal insulation fabric manufacturing process of this invention introduces a dynamic control system in the fiber mixing stage, spinning stage, compounding and finishing stage. It monitors the performance-related parameters of the actual fabric at each stage in real time, and adjusts the textile manufacturing process data at each stage according to the actual fabric performance-related parameters. This reduces or even eliminates the fluctuations in the conductivity and thermal insulation of the fabric, so as to ensure the consistency of the actual fabric performance. This solves the problems of unstable quality and insufficient reliability of fabrics prepared by relying solely on fixed process data in the prior art.

[0028] In one embodiment, the matrix fiber is polyester, with polyester accounting for 80% to 90% by mass, carbon fiber accounting for 5% to 8% by mass, silver-plated nylon filament accounting for 5% to 10% by mass, and graphene-modified polyester accounting for 2% to 3% by mass.

[0029] In one specific embodiment, the matrix fiber is polyester, accounting for 85% by mass, carbon fiber accounting for 6% by mass, silver-plated nylon filament accounting for 7% by mass, and graphene-modified polyester accounting for 2% by mass.

[0030] In one embodiment, hollow polyester accounts for 45% to 55% of the mass, far-infrared ceramic fiber accounts for 15% to 25% of the mass, and acrylic fiber accounts for 20% to 40% of the mass.

[0031] In one specific embodiment, hollow polyester accounts for 50% of the mass, far-infrared ceramic fiber accounts for 20% of the mass, and acrylic fiber accounts for 30% of the mass.

[0032] Please see Figure 2 Specifically, the conductive fiber distribution of the first mixed fiber is sampled and detected, and the fiber mixing ratio of the first mixed fiber is adjusted according to the conductive fiber distribution, including: Several samples are randomly selected from the first mixed fiber, and the conductive fiber ratio data of each sample is obtained and calculated. The uniformity data of conductive fiber distribution is calculated based on the conductive fiber ratio data. If the uniformity data of conductive fiber distribution is greater than or equal to the first preset threshold, the conductive fiber ratio in the first mixed fiber is increased, and the uniformity of the first mixed fiber after the increase in conductive fiber ratio is retested until the uniformity data of the first mixed fiber is less than the first preset threshold.

[0033] In one embodiment, at least five samples are randomly selected from the first batch of mixed fibers, each weighing ≥1g, covering different locations in the first batch of mixed fibers, such as the front, middle, and rear sections of the mixer. The samples are dispersed on a glass slide, sprayed with an antistatic agent to prevent fiber adhesion, and gently pressed with a coverslip to flatten the fibers. A scanning electron microscope (SEM) or fiber analyzer (such as the OFD 3000) is used at a magnification of 100-200x. At least five images of non-overlapping areas are taken for each sample, ensuring the field of view covers fiber intersections and dispersed areas. Conductive fibers (carbon fiber, silver-plated nylon filament, and graphene-modified polyester) are identified using image processing software (such as ImageJ or FiberMetric), and the matrix fibers (polyester) are distinguished by color or grayscale differences. The percentage of the cross-sectional area of ​​conductive fibers in each image relative to the total fiber cross-sectional area is calculated, i.e., the conductive fiber percentage data.

[0034] The uniformity of conductive fiber distribution is calculated based on the conductive fiber percentage data, i.e., the variance of the conductive fiber percentage data is calculated, in order to evaluate the uniformity of conductive fiber distribution within the first mixed fiber.

[0035] In one embodiment, the first preset threshold is 0.5%, and the conductive fiber proportions of the five samples are 4.8%, 5.2%, 4.5%, 5.5%, and 4.7%, respectively. The mean of the conductive fiber proportion is 4.94%, and the uniformity (sample variance) of the conductive fiber distribution is 0.163%, which is less than the first preset threshold. Therefore, it is determined that the conductive fiber distribution in the first mixed fiber is qualified, and no adjustment is needed to the conductive fiber proportion in the first mixed fiber.

[0036] In another embodiment, the first preset threshold is 0.5%. The conductive fiber proportions of the five samples are 5.8%, 5.2%, 4.1%, 3.9%, and 4.3%, respectively. The mean of the conductive fiber proportion is 4.66%, and the uniformity (sample variance) of the conductive fiber distribution is 0.653%, which is greater than the first preset threshold. Therefore, the conductive fiber distribution in the first mixed fiber is deemed unqualified, and the fiber mixing ratio is adjusted in 1% increments. For example, the overall proportion of conductive fibers (carbon fiber, silver-plated nylon filament, and graphene-modified polyester) increases by 1%, while the overall proportion of matrix fiber (polyester) decreases by 1%. The original mixed fiber proportions are: polyester 85% by mass, carbon fiber 6% by mass, silver-plated nylon filament 7% by mass, and graphene-modified polyester 2% by mass. The adjusted mixed fiber proportions are: polyester 84.0% by mass, carbon fiber 6.3% by mass, silver-plated nylon filament 7.3% by mass, and graphene-modified polyester 2.4% by mass. The first mixed fiber with the adjusted proportion of mixed fibers is obtained by thoroughly mixing in a mixer, and its uniformity is retested until the uniformity data of the first mixed fiber is less than the first preset threshold.

[0037] In the antistatic yarn preparation stage, the present invention first prepares a mixed fiber by mixing a base fiber and a conductive fiber in a certain proportion to obtain a first mixed fiber. The distribution of conductive fibers in the first mixed fiber is detected, and the uniformity of conductive fiber distribution is calculated based on the detection results. The fiber mixing ratio is then adjusted based on the calculation results. Through the above method, the uniformity of conductive fiber distribution can be accurately quantified and guaranteed, ensuring the consistency of antistatic performance of the fabric from the source.

[0038] Please see Figure 3 The real-time measurement of antistatic yarn resistance and adjustment of Siro spinning twist based on the resistance includes: Several antistatic yarn samples of a certain length are acquired in real time and the resistance of each antistatic yarn sample is measured. The average resistance is calculated. If the average resistance of the antistatic yarn sample is greater than or equal to the second preset threshold, the Siro spinning twist is reduced, and the resistance of the antistatic yarn twisted after the Siro spinning twist is reduced is re-measured until the average resistance of the antistatic yarn sample is less than the second preset threshold.

[0039] In one embodiment, the conductive fiber and the matrix fiber are twisted using a Sirospinning process, with the twist controlled at 600-800 TPM, and the spinning environment humidity adjusted to 60%-65%. The second preset threshold is 1×10⁻⁶. 6 Ω / cm.

[0040] In one embodiment, several 10cm length antistatic yarn samples are acquired in real time, and the unit resistance of each sample is measured. The average value is calculated. If the average value is greater than or equal to 1×10⁻⁶, the sample is considered safe. 6Ω / cm, automatically reduce Siro spinning twist by 20-50 TPM and retest until the average resistance of the antistatic yarn sample is less than 1×10 Ω / cm. 6 Ω / cm.

[0041] There is a negative correlation between the resistance of antistatic yarn and the twist of Siro spinning. Tight fiber cohesion means that conductive fibers are wrapped within the yarn core, reducing the exposed surface area and physically blocking the conductive pathways of the yarn. This results in increased resistance and reduced conductivity of the antistatic yarn. Therefore, this invention measures the resistance of the antistatic yarn in real time during the yarn preparation stage. When the resistance is too high, the Siro spinning twist is adjusted to reduce the resistance by an order of magnitude, thereby ensuring good conductivity and consistent resistance of the antistatic yarn.

[0042] Please see Figure 4 The real-time measurement and calculation of the bulkiness of the thermal insulation yarn and the adjustment of the fiber blending ratio of the second blended fiber based on the bulkiness include: A certain length of thermal insulation yarn is acquired and weighed in real time. The bulkiness of the thermal insulation yarn is calculated based on the length and weight data. If the bulkiness of the thermal insulation yarn is less than or equal to the third preset threshold, the proportion of hollow fibers in the second mixed fiber is increased. The bulkiness of the thermal insulation yarn spun from the second mixed fiber with the increased proportion of hollow fibers is retested until the bulkiness of the thermal insulation yarn is greater than the third preset threshold.

[0043] In one embodiment, the hollow polyester fiber accounts for 50% of the mass of the blended fibers, the far-infrared ceramic fiber accounts for 20% of the mass of the blended fibers, and the acrylic fiber accounts for 30% of the mass of the blended fibers. These are thoroughly mixed using a mixer to obtain a second blended fiber, which is then spun into a thermal insulation yarn using a vortex spinning process. The weight (G) of 1 m (L) of the thermal insulation yarn is weighed, and the bulk index is calculated: Bulk index = Thermal insulation yarn volume / Thermal insulation yarn weight. r is the radius of the thermal insulation yarn, L is the length of the thermal insulation yarn, G is the weight of the thermal insulation yarn, and the third preset threshold is 15 cm³ / g. In this embodiment, the calculated bulk is 13.4 cm³ / g, which is less than the third preset threshold. The proportion of hollow fibers in the second mixed fiber is increased by 1% in increments. The adjusted mixed fiber has a hollow polyester mass ratio of 51%, a far-infrared ceramic fiber mass ratio of 20%, and an acrylic fiber mass ratio of 29%. The bulk of the thermal insulation yarn spun from the second mixed fiber with the increased hollow fiber proportion is retested until the bulk of the thermal insulation yarn is greater than the third preset threshold.

[0044] This invention utilizes the hollow structure of hollow polyester in insulating fibers to store still air. Air has an extremely low thermal conductivity, which can effectively block heat loss. Loft is a core indicator that determines the performance of insulating yarn. For every 10% increase in yarn loft, its thermal resistance (insulation index) can be improved by about 15%-20%. Therefore, this invention measures and calculates the loft of insulating yarn during the yarn preparation stage. When the measured loft of the insulating yarn is too low, the proportion of hollow fibers in the second blended fiber is increased to ensure good insulation and consistency of yarn insulation.

[0045] Please see Figure 5 The real-time monitoring of the number of splice points and the correction of the warp feed of the loom based on the number of splice points include: A certain area of ​​fabric is selected in real time and the number of splice points is obtained. The real-time deviation is calculated based on the number of splice points. If the real-time deviation is greater than or equal to the preset deviation, the warp feed of the loom is corrected. Correcting the warp feed of the loom includes: Calculate the joint density based on the number of joints, and determine the correction direction based on the joint density data: if the joint density is greater than the fourth preset threshold, reduce the warp feed of the loom; if the joint density is less than or equal to the fourth preset threshold, increase the warp feed of the loom. Re-monitor and calculate the real-time deviation until the real-time deviation is less than the preset deviation.

[0046] It is understandable that the antistatic layer and the thermal insulation layer are connected by a bonding structure, that is, by interlacing warp or weft yarns (such as plain weave or bonded weft yarns), the antistatic layer and the thermal insulation layer are fixed together to prevent delamination.

[0047] In one embodiment, a high-speed industrial camera or laser sensor is installed behind the weave stop of the loom to capture the number and distribution of seams on the fabric surface and to calculate the number of seams per unit area (one square centimeter). Preset target value for node density Calculate the real-time deviation: Deviation The preset deviation is 5%, and the fourth preset threshold is 10 per square centimeter.

[0048] In this embodiment, the calculated real-time deviation is 6.5%. Therefore, if the real-time deviation is greater than the preset deviation, the number of connection points per unit area (one square centimeter) is... If the number is 13 per square centimeter, which is greater than the fourth preset threshold, it indicates that the density is too high. It is necessary to reduce the warp feed of the loom (reduce the warp tension and increase the distance between the joints). After adjustment, re-detect the number of joints until the deviation is ≤ 5% of the preset deviation.

[0049] In another embodiment, if the calculated real-time deviation is 6.5%, then the real-time deviation is greater than the preset deviation, and the number of connection points per unit area (one square centimeter) is... If the number of warp points is 9 per square centimeter, which is less than the fourth preset threshold, it indicates that the density is too low. It is necessary to increase the warp feed of the loom (increase the warp tension and reduce the distance between the joints). After adjustment, re-detect the number of joints until the deviation is ≤ 5% of the preset deviation.

[0050] This invention ensures uniformity of joints by real-time monitoring of the number of joints (number of joints per unit area), preventing interlayer delamination or decreased insulation due to density deviations. Simultaneously, through real-time monitoring of the number / density of joints and closed-loop control of warp feed, the structural stability of the antistatic and insulation layers can be dynamically coordinated, ensuring uniform and reliable joint structure. This technology balances the performance requirements of functional fabrics (antistatic, insulation) with production efficiency, making it suitable for high-precision industrial textile production.

[0051] Specifically, real-time monitoring of the thermal reflectivity of the composite region and correction of the composite temperature and duration based on the thermal reflectivity include: The thermal reflectivity of the composite area is monitored in real time by an infrared thermal imager. If the thermal reflectivity of the composite area is less than or equal to the fifth preset threshold, the hot press is controlled to increase the composite temperature and extend the composite time according to the preset step size until the thermal reflectivity of the composite area is greater than the fifth preset threshold.

[0052] In one embodiment, the process conditions for the intermediate hot-pressed nano-aerogel membrane are: composite temperature 150-180℃, composite pressure 0.5-1.0MPa, and composite time 20-30 seconds. The fifth preset threshold is set to 85%.

[0053] In one embodiment, the infrared thermal imager monitors the thermal reflectivity of the composite area in real time. If the thermal reflectivity of the composite area is ≤85%, the temperature of the hot press is automatically increased by 10-15°C and the composite time is extended by 5 seconds until the thermal reflectivity of the composite area is >85%.

[0054] Thermal reflectivity reflects the heat exchange efficiency of a material surface and is closely related to the quality of the composite interface. Increasing the composite temperature promotes the melting of polymer materials, while extending the composite time ensures sufficient heat transfer, thereby optimizing the interfacial bonding state and improving thermal reflectivity. This invention is based on real-time monitoring of thermal reflectivity data of the composite area, compared with a fifth preset threshold to form a closed-loop feedback. A "preset step size" is used to gradually adjust the temperature and time, avoiding material thermal damage (such as charring or deformation) or equipment instability caused by sudden parameter changes, ensuring process controllability, and resulting in a tighter interfacial bond between the antistatic layer, the thermal insulation layer, and the nano-aerogel film, optimizing antistatic performance (such as conductive network continuity) and thermal insulation performance (such as reduced heat loss). The dynamic adjustment strategy can adapt to the instability of the interfacial bonding quality and function of the fabric caused by batch differences in raw materials (such as changes in fiber moisture content and conductive agent content) or environmental fluctuations (such as workshop temperature and humidity), improving process robustness.

[0055] Specifically, real-time monitoring of polypyrrole coverage and adjustment of the polypyrrole finishing solution based on the coverage includes: The polypyrrole coverage of the fabric surface is analyzed in real time using SEM images. If the polypyrrole coverage is less than or equal to the sixth preset threshold, the concentration of the polypyrrole finishing solution is increased until the polypyrrole coverage is greater than the sixth preset threshold.

[0056] In one embodiment, the concentration of the impregnating polypyrrole finishing solution is 3%-5%, the temperature is 40-50℃, the soaking time is 20-30 minutes, the roll is pressed to a roll yield of 70%-80%, and the drying and curing temperature in the dryer is 120℃-150℃. The dryer process is divided into two stages: first drying at 120℃ for 5 minutes, then curing at 150℃ for 3 minutes. The amount of nano-ceramic agent sprayed is 10-15 g / m², and it is baked at 120℃ for 2 minutes. A 5%-8% amino silicone oil emulsion is then applied, and finally, it is shaped using an ultra-heat-setter at 160-180℃ at a speed of 20 m / min, with the pre-shrinkage rate controlled at 3%-5%.

[0057] In one embodiment, the sixth preset threshold is set to 90%. The polypyrrole coverage on the surface of the fabric is analyzed in real time using SEM images. If the polypyrrole coverage is less than or equal to 90%, the concentration of the polypyrrole finishing solution is increased by 0.5%-1%, and the polypyrrole coverage is retested until the polypyrrole coverage is greater than 90%.

[0058] Polypyrrole is a key conductive material that imparts antistatic properties to fabrics, and its coverage (surface distribution density) directly affects the integrity of the conductive network and antistatic performance. By analyzing the distribution of polypyrrole particles on the fabric surface in real time using SEM images, the coverage (e.g., particle area ratio or number of particles per unit area) is calculated. When the coverage is ≤ a sixth preset threshold, it indicates a discontinuous conductive network and substandard antistatic performance. Increasing the concentration of the polypyrrole finishing solution increases the loading of polypyrrole in the solution, promoting its adsorption or deposition on the fiber surface until the coverage exceeds the sixth preset threshold. Early detection and immediate correction of insufficient coverage prevent the accumulation of defective products in subsequent processes (such as lamination and cutting), reducing the overall scrap rate. A step-by-step adjustment strategy (increasing concentration in fixed increments) avoids abrupt concentration changes that could lead to agglomeration or excessive deposition (potentially clogging fiber pores and affecting warmth retention). This invention eliminates the impact of batch-to-batch differences in raw materials (e.g., changes in fiber hydrophilicity), environmental fluctuations (e.g., temperature and humidity affecting adsorption rates), or equipment errors (e.g., uneven spraying) on ​​the coverage through a real-time feedback mechanism, ensuring process stability.

[0059] Specifically, adjusting the amount of nano-ceramic finishing agent applied in real time based on the far-infrared emissivity data of the fabric includes: The far-infrared emissivity data of the fabric is compared with the seventh preset threshold. If the infrared emissivity data is less than or equal to the seventh preset threshold, the spraying machine is controlled to increase the spraying amount until the infrared emissivity data is greater than the seventh preset threshold.

[0060] In one embodiment, the seventh preset threshold is set to 0.85, and the far-infrared emissivity detection data is fed back to the spraying machine. When the emissivity is <0.85, the spraying amount of the spraying machine is increased by 2-3 g / m².

[0061] Far-infrared emissivity is a key indicator of a fabric's ability to convert absorbed heat energy into far-infrared radiation, directly affecting its warmth retention performance (through radiant heat feedback to the human body). Using a far-infrared spectrometer or dedicated radiometer, the far-infrared emissivity data of the fabric is monitored in real time. When the emissivity is ≤ the seventh preset threshold, it indicates insufficient distribution of far-infrared functional materials (such as ceramic particles or carbon-based materials) in the coating, failing to meet design requirements. The spraying machine is controlled to increase the spraying volume in preset steps (e.g., increasing spraying pressure, extending spraying time, or increasing slurry concentration) to increase the functional material load until the emissivity > the seventh preset threshold. Real-time feedback compensates for differences in fiber substrate (such as fluctuations in liquid absorption), environmental interference (such as the impact of temperature and humidity on coating curing), or equipment errors (such as nozzle blockage), ensuring stable emissivity compliance. This control scheme forms a closed-loop system of "detection-feedback-correction" by real-time monitoring of far-infrared emissivity and dynamic adjustment of the spraying volume, minimizing material costs to achieve precise compliance with warmth retention performance while ensuring a balance of the fabric's multifunctional properties. Its core value lies in solving the pain point of "performance-cost-efficiency" that is difficult to balance due to fixed parameters in traditional processes through data-driven dynamic control, and providing a scalable technical path for the intelligent manufacturing of functional textiles.

[0062] The present invention also includes: statistically analyzing the adjustment data of various process parameters during different batches of manufacturing processes, including the adjustment of the fiber mixing ratio of the first mixed fiber, the adjustment of the Siro spinning twist, the adjustment of the fiber mixing ratio of the second mixed fiber, the adjustment of the warp feed of the loom, the adjustment of the composite temperature, the adjustment of the composite time, the adjustment of the polypyrrole finishing liquid concentration, and the adjustment of the spraying amount of the nano-ceramic finishing agent; calculating the fluctuation correlation of each process parameter based on the adjustment data of various process parameters during different batches of manufacturing processes; and adjusting the initial values ​​of each process parameter based on the fluctuation correlation of each process parameter.

[0063] Taking the Siro spinning twist adjustment amount as an example, the Siro spinning twist adjustment amount during the manufacturing process of 10 batches is statistically analyzed. The Siro spinning twist amount at the beginning of the manufacturing process in the 10 batches should be the same. The Siro spinning twist adjustment amount during the manufacturing process of one batch is the absolute value of the difference between the Siro spinning twist amount at the end of the manufacturing process of that batch and the Siro spinning twist amount at the beginning of the manufacturing process of that batch. After statistically analyzing the Siro spinning twist adjustment amount during the manufacturing process of 10 batches, the variance of the Siro spinning twist adjustment amount during the manufacturing process of 10 batches is calculated as the fluctuation correlation of Siro spinning twist, and compared with the correlation threshold (preferably set to 5% of Siro spinning twist). If the fluctuation correlation of Siro spinning twist is less than the correlation threshold, the Siro spinning twist is adjusted. The adjusted Siro spinning twist amount = the Siro spinning twist amount at the beginning of the manufacturing process + the average of the Siro spinning twist adjustment amount during the manufacturing process of 10 batches. The adjusted Siro spinning twist amount is then used as the Siro spinning twist amount at the beginning of the manufacturing process of the next batch. If the correlation of Siro spinning twist fluctuation is greater than or equal to the correlation threshold, the Siro spinning twist will not be adjusted. The Siro spinning twist at the start of the manufacturing process in the next batch will be the same as the Siro spinning twist at the start of the manufacturing process in the statistical batch.

[0064] The correlation of Siro spinning twist fluctuation characterizes the dispersion of Siro spinning twist adjustment amount in several batches of manufacturing processes. When the correlation of Siro spinning twist fluctuation is less than the correlation threshold, it indicates that the fluctuation of Siro spinning twist adjustment amount in several batches of manufacturing processes is small and relatively close to the mean of Siro spinning twist adjustment amount in several batches of manufacturing processes. This indicates that the actual fabric performance deviates from the preset parameters (i.e., Siro spinning twist at the beginning of the manufacturing process) due to factors such as individual differences in textile equipment, mechanical operation errors (such as tension fluctuations and weaving speed deviations), and changes in environmental temperature and humidity during the manufacturing process is relatively uniform. Therefore, the Siro spinning twist at the beginning of the manufacturing process in the next batch can be adjusted to optimize the Siro spinning twist in the manufacturing process and ensure the stability of the process.

[0065] The adjustment data for other process parameters during the manufacturing process, including the adjustment of the fiber mixing ratio of the first mixed fiber, the adjustment of the fiber mixing ratio of the second mixed fiber, the adjustment of the warp feed of the loom, the adjustment of the composite temperature, the adjustment of the composite time, the adjustment of the concentration of the polypyrrole finishing liquid, and the adjustment of the spraying amount of the nano-ceramic finishing agent, are calculated in the same way as the Siro spinning twist mentioned above, and will not be repeated here.

[0066] It is understandable that different process parameters in the manufacturing process have different correlation thresholds; that is, each process parameter in the manufacturing process has its own correlation threshold. The correlation threshold can be determined through experimental verification, such as by verifying it using historical data, testing the threshold's effectiveness with historical data, and adjusting it through A / B testing. Alternatively, sensitivity analysis can be used to observe the impact of small changes in the threshold on the results, selecting the most robust threshold as the correlation threshold. Historical data verification and sensitivity analysis are both existing data processing methods and will not be elaborated upon here.

[0067] Specifically, this also includes testing the surface resistance, electrostatic half-life, heat retention rate, and thermal resistance of antistatic thermal fabrics, and evaluating the performance of antistatic thermal fabrics based on these parameters.

[0068] Surface resistance directly reflects the conductivity of a fabric. Lower surface resistance indicates a more complete conductive network, stronger charge dissipation ability, and better antistatic performance. Testing surface resistance verifies the uniformity of conductive material distribution (such as polypyrrole and conductive fibers) and whether the load capacity meets standards. Static half-life measures the speed at which a fabric dissipates static electricity. A shorter static half-life (e.g., ≤2 seconds) indicates higher charge dissipation efficiency, preventing static buildup that can cause sparks and dust accumulation. This parameter verifies the rationality of the antistatic functional layer design (e.g., conductive fiber weaving density and surface coating continuity). Insulation efficiency reflects a fabric's ability to prevent heat loss. A higher insulation efficiency (e.g., ≥30%) indicates that the fabric reduces heat loss through convection and radiation, resulting in a more significant warmth retention effect. Testing insulation efficiency verifies the thermal barrier efficiency of insulation layer materials (e.g., hollow fibers and far-infrared ceramic particles). Thermal resistance measures a fabric's ability to impede heat conduction. A higher thermal resistance value indicates a stronger effect in slowing the transfer of body heat to the outside, making it particularly suitable for warmth requirements in low-temperature environments. This parameter can verify the rationality of fiber structure (such as bulkiness) and composite process (such as multi-layer bonding).

[0069] Antistatic properties and warmth retention are the core of the fabric and manufacturing process of this invention. Through the coordinated testing of four indicators, it can be verified whether the product meets design requirements or industry standards (such as GB / T 12703.1-2021 antistatic performance standard and FZ / T73022-2019 thermal underwear standard), avoiding the defect of meeting one performance standard but failing in another. Simultaneously, the test data can provide a basis for adjusting process parameters. This invention, by testing the surface resistance, electrostatic half-life, heat retention rate, and thermal resistance value of the antistatic and warm insulation fabric, scientifically quantifies the core indicators of antistatic and warm insulation performance, ensuring that the fabric achieves an optimal balance between functionality, process reliability, and cost-effectiveness. This process is not only a necessary link in quality control but also a key technical means to drive product innovation and meet diversified application needs.

[0070] It is understood that the specific values ​​of the first preset threshold, the second preset threshold, the third preset threshold, the fourth preset threshold, the fifth preset threshold, the sixth preset threshold, and the seventh preset threshold in the above embodiments of the present invention are merely exemplary, and those skilled in the art can selectively set them according to the actual performance requirements of the fabric.

[0071] On the other hand, the present invention also provides an antistatic and wear-resistant modified polyester fiber fabric, wherein the base fiber of the antistatic yarn of the fabric is polyester or nylon.

[0072] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0073] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for preparing antistatic and abrasion-resistant modified polyester fiber fabric, characterized in that, include: The matrix fiber is selected, and carbon fiber, silver-plated nylon filament and graphene-modified polyester are mixed in proportion and then fully mixed in a mixer to obtain the first mixed fiber. The conductive fiber distribution of the first mixed fiber is detected, and the fiber mixing ratio of the first mixed fiber is adjusted according to the conductive fiber distribution. The antistatic yarn is twisted using the Siro spinning process, and the resistance of the antistatic yarn is measured in real time and the Siro spinning twist is adjusted according to the resistance. Hollow polyester, far-infrared ceramic fiber and acrylic fiber are mixed in proportion and mixed in a mixer to obtain a second mixed fiber. The mixed fiber is then spun into a warm yarn by vortex spinning. The bulkiness of the warm yarn is measured and calculated in real time, and the fiber mixing ratio of the second mixed fiber is adjusted according to the bulkiness. Fabric is woven using a loom. The outer layer is an antistatic layer, and the inner layer is a thermal insulation layer. The antistatic layer and the thermal insulation layer are connected by a bonding structure. The number of bonding points is monitored in real time, and the warp feed of the loom is adjusted according to the number of bonding points. A composite space for a nano-aerogel membrane is reserved between the outer and inner layers. The nano-aerogel membrane is laid flat in the composite space and composited using a hot press. The heat reflectivity of the composite area is monitored in real time, and the composite temperature and time are adjusted according to the heat reflectivity to obtain a fabric with a three-layer composite structure. The fabric is impregnated with polypyrrole finishing liquid, the polypyrrole coverage is monitored in real time and the concentration of polypyrrole finishing liquid is adjusted according to the coverage. Excess liquid is removed by squeezing with rollers and dried and cured. The nano-ceramic finishing agent is evenly sprayed onto the fabric surface through a spraying machine. The far-infrared emissivity data of the fabric is monitored in real time and the amount of nano-ceramic finishing agent sprayed is adjusted in real time according to the far-infrared emissivity data of the fabric. After the fabric absorbs amino silicone oil emulsion in the padding tank, it is pre-shrinked and shaped to obtain an antistatic and thermal insulation fabric.

2. The method for preparing antistatic and abrasion-resistant modified polyester fiber fabric according to claim 1, characterized in that, Adjusting the fiber mixing ratio of the first mixed fiber according to the distribution of conductive fibers includes: Several samples are randomly selected from the first mixed fibers, and the proportion of conductive fibers in each sample is obtained. The uniformity of the conductive fiber distribution is calculated based on the proportion of conductive fibers. If the uniformity data of the conductive fiber distribution is greater than or equal to the first preset threshold, the proportion of conductive fibers in the first mixed fiber is increased, and the uniformity of the first mixed fiber after the increase in the proportion of conductive fibers is retested until the uniformity data of the first mixed fiber is less than the first preset threshold.

3. The method for preparing antistatic and abrasion-resistant modified polyester fiber fabric according to claim 2, characterized in that, Adjusting the twist of Siro spinning based on resistance includes: Several antistatic yarn samples of a certain length are acquired in real time, and the resistance of each antistatic yarn sample is measured. The average resistance is then calculated. If the average resistance of the antistatic yarn sample is greater than or equal to the second preset threshold, the Siro spinning twist is reduced, and the resistance of the antistatic yarn twisted after the Siro spinning twist is reduced is retested until the average resistance of the antistatic yarn sample is less than the second preset threshold.

4. The method for preparing antistatic and abrasion-resistant modified polyester fiber fabric according to claim 3, characterized in that, Adjusting the fiber blending ratio of the second blended fiber includes: The system acquires and weighs a certain length of thermal insulation yarn in real time, and calculates the yarn's bulkiness based on the length and weight data. If the bulkiness of the thermal insulation yarn is less than or equal to the third preset threshold, the proportion of hollow fibers in the second mixed fiber is increased, and the bulkiness of the thermal insulation yarn spun from the second mixed fiber with the increased proportion of hollow fibers is retested until the bulkiness of the thermal insulation yarn is greater than the third preset threshold.

5. The method for preparing antistatic and abrasion-resistant modified polyester fiber fabric according to claim 4, characterized in that, Correcting the warp feed of the loom based on the number of joints includes: A certain area of ​​fabric is selected in real time, and the number of seams is obtained. The real-time deviation is calculated based on the number of seams. If the real-time deviation is greater than or equal to the preset deviation, the warp feed of the loom is corrected. Calculate the joint density based on the number of joints, and determine the correction direction based on the joint density data. If the density of the joints is greater than the fourth preset threshold, the amount of warp feed on the loom will be reduced. If the density of the joints is less than or equal to the fourth preset threshold, the warp feed of the loom is increased; After calibration, monitor and calculate the real-time deviation again until the real-time deviation is less than the preset deviation.

6. The method for preparing antistatic and abrasion-resistant modified polyester fiber fabric according to claim 5, characterized in that, Correcting the composite temperature and duration based on thermal reflectivity includes: The thermal reflectivity of the composite area is monitored in real time by an infrared thermal imager. If the thermal reflectivity of the composite area is less than or equal to the fifth preset threshold, the hot press is controlled to increase the composite temperature and extend the composite time according to the preset step size until the thermal reflectivity of the composite area is greater than the fifth preset threshold.

7. The method for preparing antistatic and abrasion-resistant modified polyester fiber fabric according to claim 6, characterized in that, Adjusting the polypyrrole finishing solution according to the coverage includes: The polypyrrole coverage of the fabric surface is analyzed in real time using SEM images. If the polypyrrole coverage is less than or equal to the sixth preset threshold, the concentration of the polypyrrole finishing solution is increased until the polypyrrole coverage is greater than the sixth preset threshold.

8. The method for preparing antistatic and abrasion-resistant modified polyester fiber fabric according to claim 7, characterized in that, The method of adjusting the spraying amount of nano-ceramic finishing agent in real time based on the far-infrared emissivity data of the fabric includes: The far-infrared emissivity data of the fabric is compared with the seventh preset threshold. If the far-infrared emissivity data is less than or equal to the seventh preset threshold, the spraying machine is controlled to increase the amount of nano-ceramic finishing agent sprayed.

9. The method for preparing antistatic and abrasion-resistant modified polyester fiber fabric according to claim 1, characterized in that, Also includes: The surface resistance, electrostatic half-life, heat retention rate, and thermal resistance of antistatic thermal fabrics are tested, and their performance is evaluated based on these parameters.

10. A fabric manufactured using the antistatic and abrasion-resistant modification preparation method for polyester fiber fabric according to any one of claims 1-9, characterized in that, The base fiber of the antistatic yarn is polyester or nylon.

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