Efficient heat setting process of spandex Rome cloth bristle fabric

Abstract

The invention relates to the technical field of textile fabric treatment, in particular to an efficient heat setting process of spandex Rome cloth brushing fabric, which comprises the following steps: S1, fabric pretreatment: obtaining fabric with uniform stress and moisture content lower than 5% by installing a steaming box and an infrared pre-drying box of an on-line moisture content monitor; s2, fabric shaping: dividing a shaping machine into four sections of temperature zones, and additionally arranging a multi-point thermocouple array in each section of temperature zone; through the combination of multiple sections of temperature zones and a thermodynamic model and the innovation of the pretreatment process, the process has the advantages of high setting efficiency and reduced production cost, and solves the problems that the retention time of the fabric in a setting machine is long and the production cost is low due to inaccurate temperature control and low thermal penetration efficiency in the traditional heat setting process. The problems that the production efficiency is reduced, the heat energy utilization rate of the heat setting machine is not high, a large amount of heat energy is wasted, the energy consumption cost is increased, and environmental protection is not facilitated are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of textile fabric processing, in particular to an efficient heat setting process of spandex Roman fabric brushed fabric. BACKGROUND

[0002] Spandex Roman fabric brushed fabric is a fabric that is brushed on the basis of Roman fabric, which is a double-sided knitted fabric with excellent elasticity, woven by a weft knitting machine, also known as Pan Yang Roman fabric. In the textile industry, spandex Roman fabric brushed fabric is deeply loved by consumers due to its excellent elasticity and warmth, and is widely used in various clothing, especially winter clothing.

[0003] At present, in the production process of spandex Roman fabric brushed fabric, the heat setting step is a key step, which directly affects the dimensional stability, elasticity and appearance quality of the fabric. Although the traditional heat setting process can meet the basic setting requirements, there are the following technical bottlenecks in improving the setting efficiency and fabric quality: Long setting time: the traditional heat setting process has low temperature control accuracy and low heat penetration efficiency, resulting in long residence time of the fabric in the setting machine, which reduces the production efficiency; Low heat energy utilization rate: the traditional heat setting machine has low heat energy utilization rate, and a large amount of heat energy is wasted, which not only increases the energy cost, but also is not conducive to environmental protection.

[0004] Therefore, we propose an efficient heat setting process of spandex Roman fabric brushed fabric. SUMMARY

[0005] The present application relates to the technical field of textile fabric processing, in particular to an efficient heat setting process of spandex Roman fabric brushed fabric.

[0006] To achieve the above-mentioned purpose, the present application provides the following technical scheme: an efficient heat setting process of spandex Roman fabric brushed fabric, which comprises the following steps: S1: pretreatment of the fabric: through the steam box and infrared pre-drying oven equipped with an online moisture content monitor, a fabric with uniform stress and moisture content below 5% is obtained; S2: The setting of the fabric: The setting machine is divided into four temperature zones, and multiple-point thermocouple arrays are added to each temperature zone. A thermal imager generates a temperature distribution thermal map to automatically adjust the angle and speed of the hot air nozzle. A gradient heating mode is used, and the residence time of each section is intelligently adjusted according to the fabric thickness. A matrix-type multi-source heat exchange model is combined to optimize the hot air circulation in the drying room through fluid dynamics, improving the utilization rate of thermal energy. S3: Tension and overfeed control of the fabric: The fabric is wound around a combined roller shaft with high-precision tension sensors installed. The warp overfeed amount and weft stretch rate of the conveying fabric are monitored in real time. Cold rolling pre-flattening technology is introduced to pre-flatten the fabric surface fluff before setting to reduce the obstruction of fiber fluffing after brushing to heat penetration. S4: Fabric brushing and setting: Reverse rotating brushes are set at the fabric outlet end of the setting machine, and a negative pressure dust removal device is turned on simultaneously to remove loose fibers generated by brushing, preventing fluff from blocking the hot air nozzle or adhering to the inner wall of the drying room. The fabric is immediately cooled by a cold water roller after brushing to lock the fiber form and reduce the time consumption in the subsequent cooling stage. S5: Digital process parameter optimization of the fabric: Based on the heat setting expert database, input the parameters of fabric weight, spandex content, and brushing density to automatically generate the optimal process combination and monitor the setting effect in real time, dynamically adjusting the speed and energy consumption distribution. S6: Post-processing and quality control of the fabric: A hyperspectral imager is installed at the outlet of the setting machine to detect the fabric surface flatness, color difference, and elastic recovery rate in real time. The process parameters are automatically corrected through a closed-loop control system to avoid batch rework.

[0007] Preferably, the temperature of the steaming box in step S1 ranges from 100-120℃, and the time ranges from 1-5 minutes. The wavelength of the infrared pre-drying box is 3-5μm, the infrared radiation temperature is 80-130℃, and the time ranges from 30 seconds to 3 minutes. The moisture content monitoring is real-time feedback to ensure uniformity.

[0008] Preferably, the four temperature zones of the setting machine in step S2 are 150-170℃, 170-190℃, 190-210℃, and 200-220℃, respectively, and the corresponding residence time of each temperature zone is 10-30 seconds, 30-60 seconds, 60-120 seconds, and dynamically adjusted. Meanwhile, the fabric thickness corresponding to each temperature zone is thin, medium-thick, and extra-thick, and dynamically adjusted.

[0009] Preferably, the wind speed range of the hot air nozzle control in step S2 is 2-10 m / s, and the angle adjustment is ±30°. Through fluid dynamics optimization, the thermal energy utilization rate is ≥85%.

[0010] Preferably, the warp overfeed rate in step S3 is 8%-12%, and the weft stretching rate is controlled at 5%-8%, wherein the warp tension range monitored by the tension sensor is 5-30N / cm, and in the cold rolling pre-flattening parameters of the cold rolling pre-flattening technology, the roller temperature to avoid thermal shrinkage is room temperature -60°C, and the line pressure adjusted according to the fabric weight is 2-8MPa, and the line speed is 10-30m / min.

[0011] Preferably, the reverse rotating brush in step S4 adopts adjustable frequency control, and the brush speed is 500-1200RPM, and the negative pressure value of the negative pressure dust removal device is 500-1500Pa, wherein the cold water roller in the cooling locking parameter adopts circulating water constant temperature, the temperature of which is 5-15°C, and the cooling rate is ≤30 seconds to below 30°C.

[0012] Preferably, the input parameter range for the digital process parameter optimization in step S5 is a fabric weight of 50-300 g / m², a spandex content of 1-20%, and a bristle density of 1-5 levels. The process combination generation time based on the expert database is ≤10 seconds, and the dynamic allocation strategy is adopted to reduce the energy consumption by 10-25%, and the vehicle speed is 20-30 m / min.

[0013] Preferably, in step S6, the hyperspectral data range is 400-2500 nm, and the millimeter wave imaging range is 30-300 GHz.

[0014] Preferably, the surface flatness detected by hyperspectral imaging in step S6 is corrected in real time, with an error of ±0.3 mm, a color difference ΔE value of ≤1.2, and an elastic recovery rate of ≥92% after a 30-second rebound test.

[0015] Preferably, the vehicle speed correction range of the closed-loop control adjustment in step S6 is ±15%, the temperature correction accuracy is ±3°C, and the wind speed correction accuracy is ±10%.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention combines multiple temperature zones with a thermodynamic model to divide the setting machine into four temperature zones. Each zone is combined with a multi-point thermocouple array and a thermal imager to generate a temperature thermodynamic map. The hot air circulation is optimized through fluid dynamics to achieve more uniform heat penetration and molecular chain adjustment, thereby improving the setting effect.

[0017] 2. The present invention innovates the pretreatment process and adopts the synergistic effect of a steamer and an infrared pre-drying oven, which can monitor the moisture content in real time, effectively eliminate internal stress, and provide a stable base material for subsequent shaping.

[0018] 3. The application can support intelligent dwell time adjustment of thin, medium-thick and thick fabrics through dynamic process adaptability and compatibility, meet customized needs of different spandex content and gram weight, and expand the process application range.

[0019] 4. The application integrates brush and post-processing through innovation, integrates brush and cooling links at the cloth outlet end of the setting machine, quickly locks the fiber morphology through the reverse brush and cold water roller, and reduces the efficiency loss caused by multi-process switching in traditional processes.

[0020] 5. The application can generate a quality heat map in real time through data-driven process optimization combined with hyperspectral imaging and millimeter wave imaging, and automatically correct parameters through a closed-loop system to realize full-process digital management from production to detection. DETAILED DESCRIPTION EMBODIMENT

[0021] The application provides a technical solution: efficient heat setting process for spandex Roman cloth brush fabric, which comprises the following steps: S1: Pretreatment of fabric: through the steam box and infrared pre-oven equipped with online moisture content monitor, the temperature range of the steam box is 100 DEG C, the time range is 1 minute, the wavelength of the infrared pre-oven is 3 microns, the infrared radiation temperature is 80 DEG C, and the time range is 30 seconds, wherein the moisture content monitoring is real-time feedback to ensure uniformity, and the fabric with uniform stress and moisture content below 5% is obtained; S2: Fabric setting: the setting machine is divided into four temperature zones, the temperatures of the four temperature zones of the setting machine are 150 DEG C, 170 DEG C, 190 DEG C and 200 DEG C respectively, and the corresponding dwell time of each temperature zone is 10 seconds, 30 seconds, 60 seconds and dynamic adjustment, at the same time, the corresponding fabric thickness of each temperature zone is thin, medium-thick, thick and dynamic adjustment, and a plurality of thermocouple arrays are additionally arranged in each temperature zone, a temperature distribution heat map is generated by combining a thermal imager, the angle and speed of the hot air nozzle are automatically adjusted, the speed range of the hot air nozzle control is 2 m / s, the angle adjustment is 30 DEG, the heat energy utilization rate is greater than or equal to 85% through fluid dynamics optimization, a gradient heating mode is adopted, the dwell time of each section is intelligently adjusted according to the fabric thickness, and the hot air circulation in the drying room is optimized through fluid dynamics optimization combined with a matrix type multi-source heat exchange model to improve the heat energy utilization rate. S3: Tension and overfeed control of the fabric: The fabric is wound around a combined roller shaft with a high-precision tension sensor installed, real-time monitoring of the warp overfeed amount and weft stretch rate of the conveying fabric, the warp overfeed rate is 8%, the weft stretch rate is controlled at 5%, the warp tension range monitored by the tension sensor is 5 N / cm, and the cold rolling pre-flattening technology is introduced, in the cold rolling pre-flattening parameters of the cold rolling pre-flattening technology, the roller temperature to avoid heat shrinkage is normal temperature-60℃, and the linear pressure according to the fabric weight is 2MPa, the linear speed is 10m / min, the fabric surface fluff is pre-flattened by the low-temperature roller before setting, reducing the hindering of fiber fluff after brushing to heat penetration; S4: Fabric brushing and setting: A reverse rotating brush is set at the outlet of the setting machine, and a negative pressure dust removal device is started at the same time, the reverse rotating brush adopts adjustable frequency control, and the brush speed is 500RPM, and the negative pressure value of the negative pressure dust removal device is 500Pa, to remove the loose fibers generated by brushing, prevent lint from blocking the hot air nozzle or adhering to the inner wall of the drying room, immediately cool down after brushing through the cold water roller to lock the fiber form, reduce the time consumption in the subsequent cooling stage, the cold water roller in the cooling and locking parameters adopts circulating water constant temperature, the temperature is 5℃, and the cooling rate is ≤30 seconds to below 30℃; S5: Digital process parameter optimization of the fabric: Based on the heat setting expert database, input the parameters of fabric weight, spandex content and brushing density, the input parameter range of digital process parameter optimization, fabric weight is 50g / m², spandex content is 1%, and brushing density is 1 level, the optimal process combination is automatically generated, and the setting effect is monitored in real time, the speed and energy consumption distribution are dynamically adjusted, based on the expert database, the process combination generation time is ≤10 seconds, the energy consumption reduction rate is 10% by using the dynamic distribution strategy, and the speed is 20m / min; S6: Post-treatment and quality control of the fabric: A hyperspectral imager is installed at the outlet of the setting machine, the hyperspectral data range is 400nm, and the millimeter wave imaging range is 30GHz, real-time detection of fabric surface flatness, color difference and elastic recovery rate, the surface flatness of hyperspectral imaging detection adopts real-time correction, the error is ±0.3mm, the color difference ΔE value is ≤1.2, the elastic recovery rate after 30 seconds of rebound test is ≥92%, the process parameters are automatically corrected through the closed-loop control system to avoid batch rework, the speed correction range of closed-loop control adjustment is ±15%, the temperature correction accuracy is ±3℃, and the wind speed correction accuracy is ±10%.

[0022] The technical solution: through the design of four-stage gradient temperature zones and segmented temperature control (150-220°C), combined with a matrix-type multi-source heat exchange model and fluid dynamics optimization, the thermal energy utilization rate is ≥85%, significantly reducing energy consumption and saving costs. Through dynamic parameter adjustment, the residence time can be intelligently adjusted according to the fabric thickness (10-120 seconds), avoiding over-drying or under-setting, reducing invalid energy consumption, and through precise tension regulation, the warp overfeed rate is 8-12%, and the weft stretch rate is 5-8%, combined with a high-precision tension sensor (5-30 N / cm), effectively balancing fabric elasticity and dimensional stability, reducing permanent creases, using cold-rolling pre-flattening technology, low-temperature rollers (room temperature-60°C) to pre-flatten the fluff, reducing the obstruction of fiber fluffiness to heat penetration, and improving surface flatness. Through digital parameter optimization, based on expert database input parameters such as grammage (50-300 g / m²) and spandex content (1-20%), the optimal process combination is generated within 10 seconds, dynamically adjusting the speed (20-30 m / min) and energy consumption distribution, with an efficiency improvement of more than 20%. Closed-loop quality control uses hyperspectral imaging (400-2500 nm) to detect flatness (error ±0.3 mm), color difference (ΔE≤1.2), and elastic recovery rate (≥92%) in real time, automatically correcting temperature (±3°C) and air speed (±10%), reducing rework rate, and negative pressure dust removal and fiber recovery, reverse rotating brush (500-1200 RPM) combined with negative pressure device (500-1500 Pa) to efficiently remove loose fibers, prevent fluff from blocking hot air nozzles or causing fire risk, and cold water roller (5-15°C) to cool to below 30°C within 30 seconds, fixing fiber shape and reducing cooling time, avoiding heat shrinkage deformation. Compared with industry standards, although the fourth temperature zone reaches 200-220°C, through gradient heating and intelligent residence time control (dynamic adjustment), it can avoid spandex damage (temperature tolerance upper limit 195°C), especially suitable for blended fabrics, with a thermal energy utilization rate of ≥85%, better than traditional hot air setting (usually 60-70%), and close to the energy-saving effect of infrared setting (80-120°C low temperature high efficiency). Its quality consistency is high, with a color difference ΔE controlled at ≤1.2 (industry A-level standard is ΔE≤1.5) and an elastic recovery rate of ≥92%, significantly higher than conventional processes (≥90%). Embodiment

[0023] Based on Embodiment One, the high-efficiency heat setting process for spandex Roman cloth brushed fabric includes the following steps: S1: Pretreatment of the fabric: through the installation of a steaming box and an infrared pre-oven with online moisture content monitors, the temperature range of the steaming box is 120°C, the time range is 5 minutes, the wavelength of the infrared pre-oven is 5μm, the infrared radiation temperature is 130°C, and the time range is 3 minutes, wherein the moisture content monitoring is real-time feedback to ensure uniformity, obtaining a fabric with uniform stress and moisture content below 5%; S2: Setting of the fabric: the setting machine is divided into four temperature zones, the temperatures of the four temperature zones of the setting machine are 170°C, 190°C, 210°C and 220°C respectively, and the corresponding residence time of each temperature zone is 30 seconds, 30 seconds, 120 seconds and dynamic adjustment, at the same time, the corresponding fabric thickness of each temperature zone is thin, medium-thick, extra-thick and dynamic adjustment, and a multi-point thermocouple array is added in each temperature zone, combined with a thermal imager to generate a temperature distribution thermal map, to automatically adjust the angle and speed of the hot air nozzle, the speed range of the hot air nozzle control is 10 m / s, the angle adjustment is -30°, and through fluid dynamics optimization, the thermal energy utilization rate is ≥85%, a gradient temperature rising mode is adopted, and the residence time of each section is intelligently adjusted according to the fabric thickness, combined with a matrix-type multi-source heat exchange model, the hot air circulation in the drying room is optimized through fluid dynamics, and the thermal energy utilization rate is improved; S3: Tension and overfeed control of the fabric: the fabric is wound on a combined roller shaft with a high-precision tension sensor installed, real-time monitoring of the warp overfeed amount and weft stretch rate of the conveying fabric, the warp overfeed rate is 12%, and the weft stretch rate is controlled at 8%, wherein the warp tension range monitored by the tension sensor is 30N / cm, and a cold rolling pre-flattening technology is introduced, in the cold rolling pre-flattening parameters of the cold rolling pre-flattening technology, the roller temperature to avoid heat shrinkage is normal temperature-60°C, and the linear pressure adjusted according to the fabric grammage is 8MPa, and the linear speed is 30m / min, the fabric surface fluff is pre-flattened by a low-temperature roller before setting to reduce the hindrance of fiber fluffiness after brushing to heat penetration; S4: Brushing and setting of the fabric: a reverse rotating brush is set at the fabric outlet end of the setting machine, and a negative pressure dust removal device is started simultaneously, the reverse rotating brush adopts adjustable frequency control, and the brush speed is 1200RPM, while the negative pressure value of the negative pressure dust removal device is 1500Pa, to remove the loose fibers generated by brushing, prevent the fluff from blocking the hot air nozzle or adhering to the inner wall of the drying room, and immediately cool down through a cold water roller after brushing to lock the fiber form, reduce the time consumption in the subsequent cooling stage, the cold water roller in the cooling and locking parameters adopts circulating water constant temperature, the temperature is 15°C, and the cooling rate is ≤30 seconds to below 30°C; S5: Digital process parameter optimization of the fabric: based on the heat setting expert database, input the parameters of fabric weight, spandex content, and brush density, the input parameter range of digital process parameter optimization, the fabric weight is 300 g / m2, the spandex content is 20%, and the brush density is 5 levels, the optimal process combination is automatically generated, the setting effect is monitored in real time, the speed and energy consumption distribution are dynamically adjusted, the process combination generation time is less than or equal to 10 seconds based on the expert database, the energy consumption reduction rate is 25% by using the dynamic distribution strategy, and the speed is 30 m / min; S6: Post-treatment and quality control of the fabric: a hyperspectral imager is installed at the outlet of the setting machine, the hyperspectral data range is 2500 nm, the millimeter wave imaging range is 300 GHz, the fabric surface flatness, color difference and elastic recovery rate are detected in real time, the surface flatness detected by the hyperspectral imaging is corrected in real time, the error is ±0.3 mm, the color difference ΔE value is less than or equal to 1.2, the elastic recovery rate after 30 seconds of rebound test is greater than or equal to 92%, the process parameters are automatically corrected through the closed loop control system to avoid batch rework, the speed correction range of the closed loop control adjustment is ±15%, the temperature correction accuracy is ±3 DEG C, and the air speed correction accuracy is ±10%. Embodiment

[0024] On the basis of the embodiment one, the efficient heat setting process of the spandex Roman cloth brush fabric of the application comprises the following steps: S1: Pretreatment of the fabric: through the installation of a steaming box and an infrared pre-oven with an online moisture content monitor, the temperature range of the steaming box is 110 DEG C, the time range is 3 minutes, the wavelength of the infrared pre-oven is 4 mu m, the infrared radiation temperature is 100 DEG C, and the time range is 1.5 minutes, wherein the moisture content monitoring is real-time feedback to ensure uniformity, and the fabric with uniform stress and moisture content below 5% is obtained; S2: Fabric setting: the setting machine is divided into four temperature zones, the temperatures of the four temperature zones of the setting machine are 160 DEG C, 180 DEG C, 200 DEG C and 210 DEG C respectively, and the corresponding residence time of each temperature zone is 20 seconds, 45 seconds, 90 seconds and dynamic adjustment, at the same time, the corresponding fabric thickness of each temperature zone is thin, medium thick, extra thick and dynamic adjustment, and a plurality of thermocouple arrays are additionally arranged in each temperature zone, a temperature distribution thermal map is generated in combination with a thermal imager, the angle and speed of the hot air nozzle are automatically adjusted, the speed range controlled by the hot air nozzle is 6 m / s, the angle adjustment is 2 DEG, the heat energy utilization rate is greater than or equal to 85% through fluid dynamics optimization, a gradient heating mode is adopted, the residence time of each section is intelligently adjusted according to the fabric thickness, and the hot air circulation in the drying room is optimized through fluid dynamics optimization based on the matrix type multi-source heat exchange model to improve the heat energy utilization rate; S3: Tension control of fabric and overfeed: The fabric is wound around the combined roller shaft with high-precision tension sensors installed, real-time monitoring of the warp overfeed amount and weft stretch rate of the conveying fabric, the warp overfeed rate is 10%, the weft stretch rate is controlled at 6.5%, the warp tension range monitored by the tension sensor is 20 N / cm, and the cold rolling pre-flattening technology is introduced, in the cold rolling pre-flattening parameters of the cold rolling pre-flattening technology, the roller temperature to avoid heat shrinkage is normal temperature-60℃, and the linear pressure according to the fabric gram weight is 5MPa, the linear speed is 20m / min, the fabric surface fluff is pre-flattened by the low-temperature roller before setting, reducing the hindrance of fiber fluff after brushing to heat penetration; S4: Brushing and setting of the fabric: A reverse rotating brush is arranged at the outlet of the setting machine, and a negative pressure dust removal device is started synchronously, the reverse rotating brush adopts adjustable frequency control, and the rotating speed of the brush is 850 RPM, and the negative pressure value of the negative pressure dust removal device is 1000 Pa, to remove the loose fibers generated by brushing, prevent the fluff from blocking the hot air nozzle or adhering to the inner wall of the drying room, and immediately pass through a cold water roller for rapid cooling after brushing to lock the fiber form, reduce the time consumption in the subsequent cooling stage, the cold water roller in the cooling and locking parameters adopts circulating water constant temperature, the temperature is 10℃, and the cooling rate is ≤30 seconds to reduce to below 30℃; S5: Digital process parameter optimization of the fabric: based on the heat setting expert database, input the parameters of fabric gram weight, spandex content and brushing density, the input parameter range of digital process parameter optimization, fabric gram weight is 160g / m², spandex content is 11%, brushing density is level 3, automatically generate the optimal process combination, and real-time monitor the setting effect, dynamically adjust the speed and energy consumption distribution, based on the expert database, the process combination generation time is ≤10 seconds, and the energy consumption reduction rate is 18% by using the dynamic distribution strategy, and the speed is 25m / min; S6: Post-treatment and quality control of the fabric: a hyperspectral imager is installed at the outlet of the setting machine, the hyperspectral data range is 2000nm, and the millimeter wave imaging range is 200GHz, real-time detection of fabric surface flatness, color difference and elastic recovery rate, the surface flatness of the hyperspectral imaging detection adopts real-time correction, the error is ±0.3mm, the color difference ΔE value is ≤1.2, the elastic recovery rate after 30 seconds of rebound test is ≥92%, the process parameters are automatically corrected through the closed-loop control system to avoid batch rework, the speed correction range of the closed-loop control adjustment is ±15%, the temperature correction accuracy is ±3℃, and the wind speed correction accuracy is ±10%.

[0025] Compared with example 1, the difference in comparative example 1 is that the steaming box with online moisture content monitor is not used in step S1, specifically "S1: Pretreatment of the fabric: through the infrared pre-drying oven, the fabric with uniform stress and moisture content below 5%" is obtained, and the remaining steps remain unchanged, and the spandex Roman cloth fabric after heat setting is recorded as comparative example 1.

[0026] Compared with Example 1, the difference in Comparative Example 1 is that the fluid dynamics is not used to optimize the hot air circulation in the oven in step S2, specifically, “S2: shaping of the fabric: divide the shaping machine into four temperature zones, and add a multi-point thermocouple array in each temperature zone, combine with the thermal imager to generate a temperature distribution thermal map, automatically adjust the hot air nozzle angle and air speed, use a gradient heating mode, and the residence time of each section is intelligently adjusted according to the fabric thickness, and combined with a matrix type multi-source heat exchange model”, and the remaining steps remain unchanged. The spandex Roman cloth brushed fabric after heat setting is denoted as Comparative Example 2.

[0027] Compared with Example 1, the difference in Comparative Example 1 is that the fluid dynamics is not used to optimize the hot air circulation in the oven in step S2, specifically, “S2: shaping of the fabric: divide the shaping machine into four temperature zones, and add a multi-point thermocouple array in each temperature zone, combine with the thermal imager to generate a temperature distribution thermal map, automatically adjust the hot air nozzle angle and air speed, use a gradient heating mode, and the residence time of each section is intelligently adjusted according to the fabric thickness, and combined with a matrix type multi-source heat exchange model”, and the remaining steps remain unchanged. The spandex Roman cloth brushed fabric after heat setting is denoted as Comparative Example 2.

[0028] Performance test experiment: select the traditional heat-set spandex Roman cloth brushed fabric and the heat-set spandex Roman cloth brushed fabric of Examples 1-3 and Comparative Examples 1-3 to perform the following experiments.

[0029] The experimental content and results are shown in the following table As can be seen from the table, through various experiments, it can be found that the heat-set spandex Roman cloth brushed fabric of Examples 1, 2 and 3 has higher advantages in heat energy utilization rate, production speed, energy consumption cost, dimensional stability error, surface flatness error and rework rate compared with the heat-set spandex Roman cloth brushed fabric of Comparative Examples 1, 2 and 3. At the same time, the heat-set spandex Roman cloth brushed fabric of Examples 1, 2 and 3 has a great degree of improvement in heat energy utilization rate, production speed, energy consumption cost, dimensional stability error, surface flatness error and rework rate compared with the traditional fabric.

[0030] Finally, it should be noted that the above examples are only used to illustrate the technical solutions of the present application, and are not intended to limit the scope of protection of the present application. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced by equivalents without departing from the essence and scope of the technical solutions of the present application.

Claims

1. The efficient heat setting process of spandex Roman cloth brushed fabric is characterized by: The process includes the following steps: S1: Fabric pretreatment: A steam oven and infrared pre-drying oven equipped with an online moisture content monitor are used to obtain fabrics with uniform stress and a moisture content below 5%. S2: Fabric shaping: The shaping machine is divided into four temperature zones, and a multi-point thermocouple array is added to each temperature zone. A thermal imager is used to generate a temperature distribution thermogram, automatically adjust the hot air nozzle angle and wind speed, and adopt a gradient heating mode. The residence time of each section is intelligently adjusted according to the fabric thickness. In addition, a matrix multi-source heat exchange model is combined with fluid dynamics to optimize the hot air circulation in the drying room. S3: Fabric tension and overfeed control: The fabric is wound around a combination roller shaft equipped with a high-precision tension sensor to monitor the warp overfeed and weft stretch of the fabric in real time. Cold rolling pre-flattening technology is also introduced to pre-flatten the fabric surface lint using low-temperature rollers before shaping. S4: Brushing and shaping fabrics: A counter-rotating brush is installed at the fabric outlet of the shaping machine, and a negative pressure dust removal device is simultaneously turned on to remove loose fibers generated by the brushing to prevent the fluff from clogging the hot air nozzle or adhering to the inner wall of the drying room. After brushing, the fabric is immediately cooled by a cold water roller to lock the fiber shape. S5: Digital process parameter optimization for fabrics: Based on the heat setting expert database, input parameters such as fabric weight, spandex content, and brushing density to automatically generate the optimal process combination, monitor the setting effect in real time, and dynamically adjust the speed and energy consumption distribution; S6: Fabric post-processing and quality control: A hyperspectral imager is installed at the exit of the setting machine to detect the surface flatness, color difference and elastic recovery rate of the fabric in real time, and automatically correct the process parameters through a closed-loop control system.

2. The high-efficiency heat setting process for spandex roman cloth bristle fabric according to claim 1, characterized in that: In step S1, the temperature range of the steam oven is 100-120°C, the time range is 1-5 minutes, the wavelength of the infrared pre-drying oven is 3-5 μm, the infrared radiation temperature is 80-130°C, and the time range is 30 seconds to 3 minutes. The moisture content monitoring is real-time feedback to ensure uniformity.

3. The high-efficiency heat setting process for spandex roman cloth bristle fabric according to claim 1, characterized in that: In step S2, the four temperature zones of the setting machine are 150-170°C, 170-190°C, 190-210°C and 200-220°C, respectively, and the residence time corresponding to each temperature zone is 10-30 seconds, 30-60 seconds, 60-120 seconds and dynamic adjustment. At the same time, the fabric thickness corresponding to each temperature zone is thin, medium thick, extra thick and dynamic adjustment.

4. The high-efficiency heat setting process for spandex roman cloth bristle fabric according to claim 1, characterized in that: In step S2, the wind speed range of the hot air nozzle is controlled to be 2-10 m / s, the angle is adjusted to ±30°, and the heat energy utilization rate is ≥85% through fluid dynamics optimization.

5. The high-efficiency heat setting process for spandex roman cloth bristle fabric according to claim 1, characterized in that: In step S3, the warp overfeed rate is 8%-12%, and the weft stretching rate is controlled at 5%-8%, wherein the warp tension range monitored by the tension sensor is 5-30 N / cm, and in the cold rolling pre-flattening parameters of the cold rolling pre-flattening technology, the roller temperature to avoid thermal shrinkage is room temperature -60°C, and the line pressure adjusted according to the fabric weight is 2-8 MPa, and the line speed is 10-30 m / min.

6. The high-efficiency heat setting process for spandex roman cloth bristle fabric according to claim 1, characterized in that: In step S4, the reverse rotating brush adopts adjustable frequency control, and the brush speed is 500-1200RPM, and the negative pressure value of the negative pressure dust removal device is 500-1500Pa. The cold water roller in the cooling locking parameter adopts circulating water constant temperature, and its temperature is 5-15°C, and the cooling rate is ≤30 seconds to below 30°C.

7. The high-efficiency heat setting process for spandex roman cloth bristle fabric according to claim 1, characterized in that: The input parameter range for the digital process parameter optimization in step S5 is a fabric weight of 50-300 g / m², a spandex content of 1-20%, and a bristle density of 1-5 levels. The process combination generation time based on the expert database is ≤10 seconds, and the dynamic allocation strategy is adopted to reduce the energy consumption by 10-25% and the vehicle speed is 20-30 m / min.

8. The high-efficiency heat setting process for spandex roman cloth bristle fabric according to claim 1, characterized in that: In step S6, the hyperspectral data range is 400-2500 nm, and the millimeter wave imaging range is 30-300 GHz.

9. The high-efficiency heat setting process for spandex roman cloth bristle fabric according to claim 1, characterized in that: The surface flatness detected by hyperspectral imaging in step S6 is corrected in real time, with an error of ±0.3 mm, a color difference ΔE value of ≤1.2, and an elastic recovery rate of ≥92% after a 30-second rebound test.

10. The high-efficiency heat setting process for spandex roman cloth bristle fabric according to claim 1, characterized in that: The vehicle speed correction range of the closed-loop control adjustment in step S6 is ±15%, the temperature correction accuracy is ±3°C, and the wind speed correction accuracy is ±10%.