Objective Special protective clothing are used against high temperature, acid and alkali corrosion, fire and other special environments, and high-performance fibers are essential for special protective clothing. Polyphenylene sulfide (PPS) fiber is a high-performance fiber with excellent mechanical properties, chemical resistance, self-flame retardancy and insulation and other outstanding properties, and it is a suitable raw material for special protective clothing. However, the poor moisture absorption, dyeing performance and light resistance of PPS fiber, limit the applications in apparel.

Method PPS fibers were modified with sodium polyacrylate (PAAS) and nano-TiO₂ to obtain PPS/PAAS/TiO₂ composite fibers with better hygroscopic property, dyeing performance and UV resistance. The PPS/PAAS/TiO₂ composite masterbatches were prepared by melt blending the vacuum-dried PPS with PAAS and nano-TiO₂ using a twin-screw extruder before these composite masterbatches were vacuum dried at 130 ℃ for 13 h. The composite fibers were prepared by a one-step spinning and drawing process using melt spinning. The spinning speed was 800 m/min, the pump supply was 22 g/min, and two-zone drafting was used, with the temperature of each drafting hot plate setting at 88, 102 and 108 ℃, and the drafting multiplier was 3.2. The mechanical properties, moisture absorption properties, dyeing rate, color fastness, and ultraviolet(UV) resistance of the prepared fibers were characterized.

Results PAAS and nano-TiO₂ were able to disperse uniformly in the polyphenylene sulfide (PPS) fiber matrix and form a good cross-compatibility (Fig.2), but when the mass fraction of PAAS exceeded 3%, agglomeration appeared and the poor dispersion led to poor spinnability of PPS composite fibers (Tab. 1). The use of Nano-TiO₂ improved the crystallinity of PPS fibers, while PAAS made the glass transition temperature and crystallinity of composite fibers decrease (Fig. 3 and Tab. 2). Increasing the internal free volume and amorphous zone of fibers resulted in a slight decrease in the breaking strength of PPS fibers compared with pure PPS fibers, but the elongation at break increases (Fig. 4). When the mass fraction of PAAS was 2%, the breaking strength of PPS/PAAS/TiO₂ composite fiber reached 3.06 cN/dtex and the elongation at break 30.4%, indicating the mechanical properties meeting the requirements of fabrics for apparel. The moisture absorption performance and dyeing performance of the PPS/PAAS/TiO₂ composite fiber was improved, the water contact angle decreased with the increase of PAAS content from 73.7° for the pure PPS fiber to 51.2° for the PPS-5 composite fiber (Fig. 5). The standard moisture regain rate increased with the increase of PAAS content from 0.22% for the pure PPS fiber to 3.9% for the PPS-5 composite fiber (Fig. 6). Under the same dyeing conditions, the dyeing rate of PPS-4 composite fiber (90.9%) was twice as high as that of the pure PPS fiber (44.8%) (Fig. 7). The color fastness of PPS/PAAS/TiO₂ composite fiber all reached levels 5 and 5 for soaping resistance (Tab. 3), and 6 and 7 for light fastness. The resistance of PPS composite fibers to light aging was significantly improved by addition of nano-TiO₂, and the strength remained at more than 85% after 120 h, although there was also strength loss with time (Fig. 8).

Conclusion The hygroscopic property, dyeing performance and UV resistant of PPS/PAAS/TiO₂ composite fibers are all enhanced to a certain extent, partly because of the functional groups of PAAS and nano-TiO₂, and partly because of the formation of a good spatial cross-linked network structure with the PPS matrix (Fig. 9). PAAS itself has a long molecular chain entanglement cross-linked structure. There are many reactive —COONa, —COOH groups inside the network, which have super hygroscopic ability. It is proved that nano TiO₂ plays a role in preventing UV aging by absorbing and reflecting ultraviolet light and the scattering and shielding ultraviolet light. Water molecules and dyestuffs that penetrate and diffuse into the interior of PPS fibers produce certain hydrogen bonding with the functional groups, resulting in improved moisture regain and color fastness of the fibers. On the basis of maintaining the original properties of PPS fibers, improved moisture absorption, dyeing and UV resistant properties make it a prospective candidate fibre for apparel applications. For further development, it is necessary to focus on the deterioration of the spinnability and mechanical properties of PPS fibers that occur after the PAAS content is increased.

Objective With low power consumption and environmental friendliness, interfacial solar-driven steam generation technology has been expected to moderate water scarcity from the explosive growth of industry and population. Based on this technology, the multistage desalination devices are prepared for high-efficient freshwater collection.

Method The 3-D carbon fiber array structure was constructed on the copper plate with excellent thermal conductivity by electrostatic flocking technology, and it was used as a photothermal layer to achieve outstanding light absorption. Non woven fabric with excellent hydrophilicity was used as a water transport channel. After the hydrophobic treatment, the copper plate acted as a water collection layer to rapidly obtain lots of freshwater. Based on the above three components, a ten-stage multistage desalination device with an inclined angle was prepared for high-efficient freshwater collection.

Results The photothermal layer, which was fabricated with carbon fiber arrays and copper plate by electrostatic flocking technology, can reach a high temperature of 78.4 ℃ for the top surface and 73.7 ℃ for the bottom surface under one-sun irradiation(Fig. 4). It shows the excellent photothermal effect and heat conduction. And it mainly benefits from the design of a three-dimensional array structure and the excellent photothermal properties of carbon fiber. It is seen that after the optimization of materials and fabric weight, the non-woven viscose fabric with 80 g/m² can reach a wicking height of 18.1 cm within 30 min, and it spreads rapidly to 5 cm in 3 min. It has an excellent ability for water transport and diffusion, and it can continuously supply water for the photothermal layer during solar-vapor generation(Fig. 5, Fig. 7). The optimized copper plate has excellent hydrophobicity after the hydrophobic treatment. The surface of the copper plate has the shape of hierarchical porous petal-like nanostructures. The tightly packed petal-like structures increase the surface roughness of the copper plate and reduce the surface energy, to improve the surface hydrophobicity of the copper plate. At last, its water contact angle can reach 130°. Based on the above three components, firstly, a single-stage device was constructed to optimize the air gap in Fig. 10. And the highest water collection rate of 0.39 kg/(m²·h) was obtained when the air gap was 3 mm. Therefore, with an air gap of 3 mm, a ten-stage multistage desalination device can achieve a water collection rate of 2.05 kg/(m²·h)(Fig. 11). The water collection rate kept unchanged when the number of device stages was further increased.

Conclusion In our work, with low-cost and simple materials, such as copper plate, carbon fiber and non-woven fabric, a ten-stage multistage desalination device was prepared for high-efficient water collection. With excellent water transport performance, the nonwoven fabric can transport water from bulk water to every photothermal layer for evaporation. Due to the good photothermal effect, the photothermal layer can obtain a high temperature. And with outstanding heat conductivity, the photothermal layer efficiently evaporates the water of non-woven fabric to generate steam. Large amounts of steam condense on the copper sheet to form freshwater. Moreover, the hydrophobic copper plate causes the condensed water to form a waterdrop. Thus, it can reduce latent heat loss. Finally, due to the design of the inclined copper plate, the water droplets slide quickly and are collected. Our multistage seawater desalination device can provide a new idea for the design of efficient solar-driven interfacial devices. It is expected to be one of the effective ways to obtain freshwater in remote and backward areas.

Objective The pollution of dye wastewater to the environment seriously harms people's health and is also an important factor restricting the development of textile enterprises. The adsorption method is a promising one for dye wastewater treatment. Natural polymeric cellulose and chitosan are widely used as adsorption materials for wastewater treatment because of the advantages in large capacity for storage, good adsorption, non-toxicity and easy degradation. In this research, an cotton stalk microcrystalline cellulose/chitosan(MCC/CS) adsorption fiber was prepared for the adsorption of Congo Red.

Method Firstly, modified chitosan (DCS) was prepared by surface modification to CS with formaldehyde as crosslinking agent and 2,5-disulfide diurea as modifier, to improve their adsorption of Congo Red. The modified chitosan process was optimized by the orthogonal test method. Urea solvent method was used to dissolve MCC at low temperature as spinning matrix, DCS was added as insoluble dispersion adsorption material, composite fiber was prepared by wet spinning and freeze-drying, and the spinning process was optimized by the single factor method. Finally, the chemical structure of DCS was analyzed, the morphology and dye adsorption properties of MCC/DCS adsorbed fibers were tested and characterized.

Results The modification of CS was carried out successfully, where the new C=S characteristic absorption peaks at 1 209 cm^-1appear and the absorption peak of -NH₂ (2,5-dithiourea, DB) disappeared at 1 640 cm^-1 in DCS infrared spectrum. The combination of conditions obtained by orthogonal test for preparation of DCS was optimized, where acetic acid dosage was 55 mL, DB dosage was 0.60 g, CS dosage was 1.0 g, and formaldehyde dosage was 8 mL. The modified chitosan increased the contents of N and S elements, and the changes were obvious. The pore size of the MCC/DCS was larger than the MCC adsorbent fibers, and the modification CS was more beneficial to the adsorption of Congo Red by adsorbent fibers. The fracture strength of MCC/DCS adsorption fiber decreased gradually with the increase of the amount of DCS in the fiber, while the linear density increased gradually because DCS is insoluble in alkaline solution. With the addition of DCS, the viscosity of the spinning solution decreased gradually. When the concentration of dye solution was 60 mg/L, the adsorption capacity of unmodified CS for Congo Red was 13.85 mg/g, and the DCS under optimal conditions was 17.63 mg/g, the adsorption capacity of DCS was increased by 27.29% compared with CS. At the same dye solution concentration, the adsorption capacity of MCC/DCS fiber was 49.55 mg/g, which was 47.82% higher than that of MCC/CS fiber 33.52 mg/g. The analysis of the influencing factors of adsorption performance showed that the adsorption capacity of MCC/DCS adsorption fiber for Congo Red decreased gradually with the increase of adsorption temperature. The adsorption capacity was increased with the adsorption time of MCC/DCS fiber and the change of the initial concentration of dye solution, and the adsorption equilibrium was reached when the concentration of dye solution was 250 mg/L. Ho kinetic model was suitable to simulate the adsorption process of DCS adsorption fibers. The adsorption thermodynamic analysis showed that the Langmuir model was suitable to simulate the adsorption process of DCS adsorbed fibers.

Conclusion CS was successfully modified with formaldehyde as crosslinking agent and 2, 5-dithiourea as modifier. The modification process of CS was optimized by orthogonal test, and the optimum process was obtained. The MCC was dissolved by urea dissolution system at low temperature as a spinning matrix, coated with DCS powder prepared by the optimized process. Adsorption experiment test results are as follows: when the concentration of dye solution was 60 mg/L, the average removal rate of MCC/DCS fiber Congo Red was 82.58%, and the average removal rate of MCC/CS fiber for Congo Red was 55.87%. The removal rate of MCC/DCS fiber was 47.82% higher than that of MCC/CS fiber, and the expected effect was achieved.

Objective Air pollution is increasingly a serious global problem. Traditional filtration media are reported to have insufficient mechanical properties and low filtration efficiency. Therefore, in order to reduce the ecological and public health hazards of PM_0.3 suspended particles emitted from human production activities, the preparation and property evaluation of the nanofiber membrane with improved mechanical properties and filtration efficiency were reported in the paper.

Method Polyurethane (PU) with outstanding flexibility was selected as electrospinning polymer material and the solution mass fraction was fixed at 14%. Polyvinyl butyral (PVB) was used as additives to improve morphology, structure, and properties of PU nanofiber membrane. Different PU/PVB composite fiber membrane was fabricated by changing the mass ratios (8∶2, 7∶3, 6∶4) of PU and PVB. After a series of tests such as scanning electron microscope, Fourier transform infrared spectroscope, thermogravimetric analyzer, differential scanning calorimeter, stretching and filtration, the effects of PVB percentage on the morphological structure, chemical structure, mechanical properties, thermal properties, and filtration properties of PU/PVB composite nanofiber membranes were discussed.

Results The addition of PVB not only increased the spinnability of the fiber solution, but also improved the morphology of the nanofibers(Fig. 1). Under different ratio conditions (8∶2, 7∶3, 6∶4), the average diameter of the fibers was all less than 400 nm, with PU/PVB-8∶2 having the largest average diameter of 385 nm. PU/PVB composite nanofiber membranes presented similar characteristic peaks with PU nanofiber membrane, and the decrease of PU mass share in electrospinning solution leaded to a decreasing trend of the characteristic peaks at 3 318 cm^-1, 1 700-1 600 cm^-1 and 1 100 cm^-1(Fig. 2). PU/PVB composite nanofiber membranes also showed similar decomposition trends and characteristic peaks with those of PU membranes (Fig. 3). These indicated that the addition of PVB did not change chemical structure of PU in the composite membranes. The decomposition onset temperature of PU nanofiber membrane was 249.49 ℃, while the temperature of PU/PVB composite nanofiber membranes was higher than 280 ℃(Tab. 1), indicating that the addition of PVB increased the thermal stability of PU nanofiber membrane. At this time, the introduction of PVB effectively promoted the mixing of molecules within the blend and thus moderating the thermodynamic process and enhancing the thermal stability of the composite nanofiber membranes(Fig. 4). PU nanofiber membrane exhibited a fracture stress of 11 MPa and a fracture strain of 189%, while PU/PVB-8∶2 nanofiber membrane showed mechanical properties with a fracture stress of 16 MPa and a fracture strain of 148%. At this point, the elastic modulus of the composite nanofiber membrane reached a maximum of 8 MPa(Fig. 5), indicating that the mechanical properties of the composite nanofiber membrane were optimal at this mass ratio. The average pore size and porosity of PU nanofiber membrane was 7.24 μm and 55% separately. PU/PVB nanofiber membranes showed decreased pore size ranging from 1.57 to 2.95 μm and increased porosity ranging from 77% to 81% (Tab. 2). For various PU/PVB nanofiber membranes, the pore size of PU/PVB-8∶2 was only 1.78 μm and the pore size distribution was uniform. Compared to the permeability of PU fiber membrane ((63.39±1.83) mm/s), the permeability of the composite nanofiber membranes ranged from 29.04 to 37.57 mm/s. The Q_F values of PU/PVB composite nanofiber membranes were all greater than 0.02 Pa^-1, and the filtration efficiencies for PM_0.3 particles were all greater than 95%.

Conclusion The addition of PVB effectively reduces the diameter of the nanofiber and the pore size of nanofibers membranes, increases the porosity of the nanofiber membranes and improves the thermal, mechanical and filtration properties of the nanofiber membranes. When the mass ratio of PU to PVB is 8∶2, the average diameter of the fibers is 385 nm, the fracture stress is 16 MPa, the fracture strain is 148% and initial decomposition temperature is 289.37 ℃. The composite nanofiber membrane also shows the smallest pore size of 1.78 μm, a permeability of 29.37 mm/s, a filtration efficiency of 98.851% for PM_0.3, a resistance pressure drop of 181.7 Pa, and a quality factor of 0.024 6 Pa^-1,indicating that it is an ideal medium for microfiltration.

Objective Collagen peptide (COP) is a small molecular weight polypeptide with excellent solubility, but is difficult in filament formation compared with collagen. In this study, polyethylene glycol (PEG) was incorporated with COP, aiming to improve the poor spinnability of COP.

Method COP was blended with PEG to form the spinning solution with 60% formic acid as solvent. The surface tension and conductivity properties of the solution were measured by a tensiometer and conductivity meter. Scanning electron microscope was utilized to observe the surface morphology of the electrospun nanofibers. The interaction between COP and PEG was analyzed by Fourier transform infrared spectroscope, and the positions and strength distributions of different types of hydrogen bonds were fitted by the Gaussian method in the range of 3 000-3 600 cm^-1. The fibrous membranes' thermal characteristics and crystalline structure were also examined using differential scanning calorimeter and X-ray diffractometer(XRD), respectively.

Results By testing the solution properties of different COP mass fraction blended spinning solutions, it was found that the electrical conductivity and surface tension increased with the increase of COP mass fraction (Tab. 1). The incorporation of PEG improved the spinnability of COP obviously (Fig.1). The average diameter of fibers increased with COP mass fraction increasing and became most uniform when the COP content reached 20%. Moreover, when the mass fraction of COP is 12%, 16%, 20% and 24%, the average diameter of the fiber is 173, 205, 308, 319 nm respectively (Fig.2). FT-IR spectrum Gaussian fitting results showed that COP and PEG formed hydrogen bond, and the intramolecular hydrogen bond decreased while intermolecular hydrogen bond increased. It was discovered that the intramolecular hydrogen bond contact was primarily of OH … OH interaction, with some occurring as cyclic polymers, while the intermolecular hydrogen bond had a variety of OH … O, OH … N and OH … π interactions (Fig.3 and Tab.2). During electrospinning, the endothermic peak of the nanofiber membrane occured at 88 ℃, but the endothermic peaks for COP and PEG were at 100 ℃ and 72 ℃, respectively (Fig.4). From the XRD curves and statistical results of relative crystallinity of COP, PEG and nanofibrous membranes, it was found that COP at 2θ of 21.6° with a broad peak, PEG at 2θ of 19.2° and 23.4°, respectively, had one crystal diffraction peak, and 2θ exhibited a smaller peak in the 26°-28° range (Fig. 5). The nanofiber membrane, there were broad peaks representing COP and crystal diffraction peaks of PEG, respectively, with the addition of COP, the strength increases, and the crystallinity of the fiber membrane after electrospinning also increased (Tab.3).

Conclusion It was difficult to obtain well formed nanofibers by electrospinning using pure COP, but the addition of PEG was shown to have improved the poor spinnability of COP. The effect of the size of its mass fraction on the surface tension of the spinning fluid fluctuated in a small range due to the low COP molecular weight, while the conductivity increased with increasing COP mass fraction. When the COP mass fraction was 20%, the electrospun fibers exhibit uniform morphology, the relative strength of intermolecular hydrogen bonding was 52.42%, and the crystallinity also reached a maximum (62.53%) with a melting enthalpy of 55.81 J/g. PEG and COP formed hydrogen bond when the solutions were mixed. It is found that after electrospinning the intramolecular hydrogen bond of the fiber membrane decreases, while the intermolecular hydrogen bond increases.

Objective At present, the problem of air pollution is becoming increasingly serious. Melt-blown nonwovens have the characteristics of fine fibers, high porosity, and small pore size, which can effectively filter out dust and ensure the health of the wearer. Most of the commercially available melt-blown nonwovens are made from polypropylene (PP) due to their excellent filtration performance, but their non-renewable and non-degradable nature of the materials themselves may lead to resource crises and environmental pollution issues. Therefore, the development of green and renewable melt-blown nonwovens is of great significance.

Method Different types of electrets and polylactic acid(PLA) were selected to prepare PLA/electret composites by melt blending and hot pressing, in order to obtain the best electret SiO₂ for PLA. Next, the SiO₂ was modified by silane coupling agent KH570 to reduce its agglomeration. As the last step, PLA/SiO₂ melt-blown nonwovens were prepared by melt-blown spinning and high pressure in-situ electret technology, and charge storage capacity and air filtration performance of the samples were systematically investigated.

Result The PLA/electret composite membrane material was successfully prepared using the melt blending method. The PLA/SiO₂ membrane material showed an increase in peak intensity at 1 109 cm^-1, which is the symmetric stretching vibration peak of Si—O of SiO₂, proving the successful composite(Fig.2). The starting thermal decomposition temperature of the PLA/polytetrafluoroethylene(PTFE) membrane material is reduced to around 240 ℃ and the starting thermal decomposition temperature of the PLA/ SiO₂ membrane material is set at around 302 ℃, demonstrating that the addition of the electret SiO₂ has little effect on the thermal stability of PLA(Fig.3). The electret significantly improves the charge storage capacity of the PLA membrane material, where the surface electrostatic charge is 8.154 kV for the pure PLA membrane material and 17.44 kV for the PLA/ SiO₂ membrane material, an increment of up to 113.88%(Fig.3). The residual electrostatic charge on the surface of the PLA membrane material was 3.23 kV after 48 h, while the residual electrostatic charge on the surface of the PLA/ SiO₂ membrane material was still as high as 6.34 kV. This demonstrates that the addition of a 1% mass fraction of SiO₂ nanoparticles resulted in a better electret effect on the PLA membrane materials. In order to reduce the agglomeration of SiO₂, the silane coupling agent KH570 was used to modify the SiO₂. The modified SiO₂-570 sample shows a C—H vibration peak at a wavelength of 2 930 cm^-1 and a weak C=O stretching vibration peak at 1 720 cm^-1, both of which are characteristic peaks of KH570 Both of them are characteristic peaks of KH570, which proves that KH570 was successfully grafted onto the SiO₂ surface(Fig.5). The modified SiO₂-570 nanoparticles are more uniformly dispersed in the PLA matrix, effectively reducing the agglomeration of SiO₂(Fig.6). The air filtration efficiency of the PLA melt-blown nonwovens was only 37.5% at a gas flow rate of 32 L/min (Fig.8). The filtration performance of the PLA/SiO₂-570 melt-blown nonwovens was superior, with a signifi-cant increase in filtration efficiency to 88.4% and a filtration resistance of only 6.2 Pa, making it more valuable for practical applications.

Conclusions Firstly, PLA/PTFE, PLA/tourmaline and PLA/SiO₂ composite membrane materials were prepared by melt blending method. Among them, the electret SiO₂ has less influence on the thermal stability of PLA, and the prepared composite membrane materials have a high surface charge and relatively slow charge decay. Secondly, in order to reduce the agglomeration of SiO₂, the silane coupling agent KH570 was successfully grafted onto the SiO₂ surface, and the SiO₂-570 nanoparticles were more uniformly dispersed in the PLA matrix, significantly reducing the agglomeration of SiO₂. Finally, the PLA/SiO₂-570 melt-blown nonwovens prepared by melt-blown spinning processing and in situ electret technology has excellent filtration performance, with a significant increase in filtration efficiency to 88.4% and a filtration resistance of only 6.2 Pa. It has great potential for applications in personal protection and air filtration.

Objective At present, the development of water treatment technology is a global task,because of the water pollution and the shortage of pure water faced by mankind. In consideration of its superior performance, nanofiber composite filtering materials are widely used to efficiently filter micron sized particulate pollutants in sewage. However, how to increase the filtering efficiency and the adhesion between nanofiber layers and how to evaluate the adhesion are crucial. Therefore, this work is set out to prepare the multilayer materials with high filtering efficiency and adhesion between nanofiber layers and to set up test method for the adhesion.

Method In this work, a firmly bonded multilayer nanofiber composites was prepared by putting five types of low melting point polymer fibers, which are polyethylene oxide (PEO), polyvinylidene difluoride(PVDF), polystyrene (PS), polymethyl methacrylate(PMMA), metallocene linear low density polyethylene(mLLDPE), together with polyamide 6 (PA6) nanofibers on industrial filter fabrics through eletrospun technology pressed with glass fiber at a designed temperature. Meanwhile, a tensile test method was established to measure the bonding strength of multilayer nanocomposites. The effects of the content of PA6 nanofibers of the materials and initial turbidity value of PS microspheres with a diameter of 1μm solution on the filtration efficiency and filtration flux were also studied.

Results The low melting point polymer fibers containing PEO, PVDF, PS, PMMA and mLLDPE were made to have different fiber diameters, which are 0.27, 0.36, 0.42, 1.29 and 35.31 μm, respectively(Tab. 1). The multilayer nanocomposite material was successfully prepared by hot pressing the industrial filter cloth spun with low melting point polymer fiber and glass fiber, and the adhesion between nanofiber layers of the multilayer nanocomposite material was significantly improved compared with the common sandwich materials, increasing from 2.6 N/cm² to 8.2 N/cm². When the concentration of PS microsphere suspension with a diameter of 1 μm was 80 NTU, the filtration efficiency of multilayer nanofiber composite materials enhances with the increase of the surface density of the PA6 nanofibers(Fig. 5). When the surface density of PA6 nanofibers was constant, the filtration efficiency of the multilayer nanofiber composite materials increaseds with the increase of initial turbidity value of PS microspheres solution, and the filtration efficiency was up to 97.75%. When the initial turbidity of the solution was 160 NTU and the PA6 nanofiber membrane density was 2.5 g/m², the filtration efficiency of materials on PS microspheres with a diameter of 1μm reached 98.9%, the flux recovery rate was 76.3%, and the interception rate reached above 98%(Tab. 2). With the increase of the surface density of the PA6 nanofiber, the filtration flux of the material to PS microsphere filtrate gradually decreased (Fig. 6). Moreover, a tensile test method was designed to measure the adhesion between nanofiber layers of the multilayer nanocomposite material(Fig. 2).

Conclusion In conclusion, after the addition of low melting point polymer fiber, a firmly bonded multilayer nanofiber composite was prepared, and a test method for the adhesion of nanofiber composite was established. The multilayer nanofiber composite was found to have high interlayer adhesion, which is significantly higher than the common sandwich purification material, and the composite has good filtration performance for PS microspheres with a diameter of 1 μm. It would have broad application prospects in the field of sewage filtration.

Objective In order to analyze and predict the tensile stress-stain relationship of core/sheath composite yarn with double filaments, a viscoelastic tensile model needs to be developed, which would enable numerical prediction of tensile strength of this composite yarn.

Method The yarn was regarded as a viscoelastic body and its tensile property was shown in the form of the stress-strain corresponding to time. The models commonly used for the research of the tensile fracture mechanism of yarn are varied, such as linear spring, nonlinear spring, nonlinear dashpot, and Maxwell and Kelvin models. Some models above are selected in series or parallel configuration to establish suitable tensile model for core/sheath composite yarn with double filament. Additionally, experimental tests are conducted to verify the correctness of the viscoelastic model.

Results In this study, a nonlinear viscoelastic model was established to predict the tensile stress-strain relationship of core/sheath composite yarn with double filaments. The tensile properties of the yarn were tested, and different stages of the tensile curve were analyzed. The tensile properties of the composite yarns were simulated and calculated by employing the developed model, and the stress-strain relationship was fitted by applying a polynomial on the foundation of the proposed model. According to the results of tensile tests, the strength of the composite yarn was the highest in comparison with filament and staple yarn. Nevertheless, Young's modulus of composite yarn was the lowest among three types of yarns. In terms of elongation, the fracture elongation of staple yarn was much lower than that of the filament and the composite yarn (Fig. 2). The experimental results revealed that the tensile fracture curve of the composite yarn comprised three stages (Fig. 3). In the first stage, the stress and strain of the yarn showed a linear relationship when only staple yarn understood the load. In the second stage, the stress increased rapidly, and the sheath filament began to be stressed. In the final stage, some monofilaments started to fracture and the strength fluctuated, but the overall strength increased slowly. In accordance with the tensile fracture characteristics, a five-element nonlinear viscoelastic model composed of Kelvin element, Maxwell element, and linear springs were established (Fig.4). Thus, the equation of stress-strain relationship on the core/sheath composite yarn with double filaments was attained based on the model. Then, a scipy.optimize.root function in Python was employed to make a solution to the equation and several parameters were calculated. The viscoelastic tensile model can decently explain the three-stage stress-strain characteristics of the composite yarn tensile curve. The theoretical results were consistent with the experimental results, and the pearson correlation coefficient was greater than 0.999 (Fig. 5).

Conclusion This paper presented a five-element nonlinear viscoelastic mechanical model to forecast the tensile properties of core/sheath composite yarn with double filaments, according to an experimental and analytical study of the composite yarn. A polynomial function corresponding to the stress-strain relationship of the composite yarn was constructed to analyze and predict the practical tensile curve. The theoretical predictions showed good consistency with the experimental results. The yield stress derived from the model accurately reflected the different stages of the experimental tensile curve. The proposed five-element viscoelastic tensile model can provide theoretical and experimental reference values for the tensile fracture mechanism of core/sheath composite yarn with double filament. Moreover, a novel concept for research on the yarn tensile fracture mechanism is proposed.

Objective The yarn breakage in ring spinning directly affects the production efficiency and product quality of the yarns. At present, the commonly used automatic yarn break detection mainly employs a single spindle detection method with photoelectricity or magnetoelectricity as the core, both requiring costly modification of the spinning machine and is difficult to implement. Therefore, this paper proposes a break detection method based on machine vision, which provides a new direction for achieving low-cost and high-precision break detection.

Method An online detection method for yarn breaks based on visual feature reinforcement extraction was proposed. For the problem of difficult yarn feature extraction due to yarn trailing, a neighborhood gradient reinforcement operator was designed for yarn clustering to achieve yarn feature reinforcement. To deal with the problem that yarn targets are small and easily disturbed by environment, an Otsu small target segmentation threshold search method inspired by valley bottom was designed to achieve the segmentation of yarn and background, to extract adaptively yarn features from the yarn image after feature reinforcement, and to enable broken end detection by Euler distance discriminant method.

Results Inspection devices were installed at a textile factory in Wuxi to collect data, with 1 000 captured images selected for analyze. The factory mainly produces pure cotton high count yarns, with 400 spindles per vehicle. To verify the superiority of the weak feature enhancement proposed in this research, the proposed algorithm was compared with Retinex, homomorphic filtering, and histogram averaging for enhancement experiments. The algorithm developed in this research enhanced the yarn features and effectively suppressed the background areas based on the gradient step characteristics of the yarn (Fig. 8 (e)). Choices of different weights for neighborhood gradient reinforcement operators had different effects on the separation of yarn features and background features. In order to select the optimal weight value, this research adopts the method of controlling variables and conducts experimental comparison on the center weight value between 2 and 3. It was found that the optimal selection range of weight values was between 2.4 and 2.7. Distinct image and dim image enhancement renderings under different weight show clear and blurred images, respectively.

To verify the effectiveness of the algorithm in extracting yarn features, Otsu, Otsu with added pixel proportion weight, and Otsu threshold segmentation method inspired by valley points were applied to the images. Using this algorithm, it was demonstrated that the proposed algorithm effectively extracted yarn features and a small number of background features at the same pixel level. It was also be demonstrated that the proposed algorithm was able to search effectively for valley thresholds and achieve yarn feature extraction.

To verify the effectiveness of the feature extraction algorithm, the processing effects and detection results of the Hough transform line extraction method, LSD line detection algorithm, Sobel, Robert and Otsu combined algorithm, Linknet algorithm, and this algorithm were compared(Fig. 13). The results obtained by this algorithm were best fitted to the original image (Fig. 13 (g)).

The experimental results showed that the detection rate of this method reached 97.3% and the processing efficiency reached 59.76 ms per frame, which was carried out by collecting 1 000 spinning pictures of a spinning factory. It was evident that this method was able to effectively detect yarn breakage in real-time.

Conclusion The algorithm reported in this paper decomposes the acquisition of yarn features into two parts: reinforcement and extraction, solving the problems of yarn feature dispersion, low proportion of yarn features, and susceptibility to background noise interference in visual ring spinning breakage detection in dynamic environments. Experiments have shown that the algorithm proposed in this article can meet the real-time and accuracy requirements for factory inspection.

The algorithm currently has difficulty to identify linear noise and yarn features, as the linear filter only considers its morphological features and does not combine its color and morphology. Neural networks can solve problem effectively. In the future, the standard of industrial real-time performance can be achieved by streamlining network models and improving hardware configuration. It is necessary to study how to combine the characteristics of break detection with deep learning to achieve high-precision, robust, and efficient yard breakage detection methods.

Objective During textile production, yarn tension has an important impact on product quality and production efficiency, and it is necessary to monitor the peak value of yarn tension in real time and obtain the stable value of current yarn tension. The textile equipment measures the yarn tension transmitted by the yarn conveyor in real time through the yarn tension sensor, and transmits the measurement results to the yarn conveyor for regulation. The existing yarn tension sensor can monitor the yarn tension, but because the measured tension signal has problems such as non convergence, large chattering, low accuracy and many burrs, it cannot be applied to the feedback regulation of yarn tension. Otherwise, the measurement error and amplitude will become larger.

Method When the yarn is fed and knitted into a loop by the yarn feeder and the needle cylinder at a certain speed ratio, the tension will fluctuate with high frequency while keeping relatively constant under the dynamic traction and transportation of the knitting needle and the yarn feeder. On the one hand, the yarn drawn by the knitting needle is a process of intermittently variable speed yarn bending and looping, with periodic motion characteristics. On the other hand, the yarn itself has certain elasticity. Under the action of periodic traction, the stress wave in the yarn body will also be scattered and reflected during the transmission process. The dominant performance is the high-frequency fluctuation of yarn tension. Taking the high-speed seamless underwear machine as an example, the highest frequency of yarn tension measurement is 2.6 kHz, so the tension sensor should meet the highest frequency response requirements. At the same time, on the premise that the yarn tension measurement does not distort and amplify the effective signal, the signal higher than this frequency should be filtered out. This paper first analyzes the characteristics of the problems existing in the existing yarn tension sensors, divides the interference signals into three types, namely, low frequency, high frequency and singular point noise, and then designs three algorithms to deal with them: first, filter the singular noise through the amplitude limiting filtering algorithm (the amplitude of the tension measurement results at a moment is far greater than the actual tension measurement results). High frequency noise is removed by low-pass filtering, and the yarn tension working frequency is taken as the threshold value. The signal above this frequency is defined as high frequency signal; The S-G convolution algorithm is used to remove the low-frequency coupling noise. The low-frequency even coupling signal and the actual working frequency are intertwined, and the low-frequency signal cannot be removed separately. In order to verify the reliability and practicability of the algorithm, an experimental platform for yarn tension measurement was built to compare and analyze the yarn tension measurement data and standard data under constant tension and variable tension conditions.

Results In order to further verify the accuracy and effectiveness of the algorithm, the yarn conveyor of the control platform changed the yarn tension from 36 cN to 42 cN, and used TENSOMETRIC tension sensor and the sensor designed in this paper to conduct real-time testing of tension fluctuation. It can be seen that the actual measured yarn tension conforms to the mutation law, and the yarn mutation tension fitted by this method is better than the tension fitted by the standard sensor. The results show that this method can control the tension measurement error within 0.6%, which has guiding significance for the yarn tension detection and control system under complex working conditions.

Conclusion By using the cantilever structure, filtering and convolution algorithm, this paper proposes a contact yarn tension detection method based on convolution filtering algorithm. Firstly, according to the characteristics of the yarn fluctuation of the high-speed seamless underwear machine and the structural characteristics of the cantilever beam, the optimization method of the yarn tension sensor is determined. Then, the acquired data are processed by amplitude limiting filtering, low-pass filtering and S-G convolution algorithm. Finally, the measured results are compared with those of TENSOMETRIC tension sensor through experiments. The tension error is within 0.6% and the standard deviation is within 0.62%. Moreover, this method has good applicability to the detection of yarn sudden change tension, and can meet the real-time measurement of yarn tension under complex working environment.

Objective Textile fabric defects are generally caused by raw materials (warp or weft yarns), mechanical failures and human factors in the production process, and they seriously impair the quality of final products. At present, most of the defect inspection is conducted by human inspectors, resulting in low efficiency and high laboring cost. Therefore, it is of great significance to apply fast and reliable image processing and machine vision techniques to perform automated defect detection instead of human.

Method Sparse dictionary learning method has excellent adaptability in representing complex fabrics textures. However, the learning and solving of sparse dictionary take a long time, making it hard to meet the real time requirements in the industrial scenarios. This work proposed a novel dictionary grouping strategy to speed up the sparse coding process in detection stage while guaranteeing the detection accuracy. Firstly, the sliding patch scheme was adopted to learn dictionary from normal fabric samples. Secondly, the learned dictionary was optimized by dividing into groups, and such strategy is to select several optimal dictionary groups with respect to the degree of approximation. Next, the optimized dictionary groups were used to reconstruct a test image to obtain its residual image. As the final step, the reconstructed errors were applied to identify defect areas from normal ones.

Results To compare the computation time of different algorithms, only the total running time in detection stage was calculated, not including the dictionary learning or dictionary grouping. The experimental results showed that the sparse dictionary algorithm took a longest running time among them, the proposed algorithm took the second longest time, and the unconstrained dictionary used the shortest time(Tabl. 1). The reason that the proposed algorithm was able to reduce most of the time is that the entire algorithm process advances the process of finding the optimal dictionary atoms for the sparse dictionary (sparse coding) and limits the number of dictionary atoms and the reconstruction error, thus significantly reducing the computational effort. The proposed algorithm also achieved a high accuracy rate, slightly lower than the sparse dictionary. The possible reason for it may be that the sparse dictionary do not use all dictionary elements patches each time, but selecting the least number of elements for patch approximation, helping ignore details such as defective areas. The three dictionary learning algorithms have relatively good detection results for various types of defects in plain gray fabrics, and the detection rates are above 90% (Tab. 2). This proposed method has excellent and stable detection for warp defects such as broken warp and knots, and poor detection for weft defects only for few images, which may be caused by their low contrast or minor anomalous defective areas. In summary, the detection accuracy of the proposed method is comparable to that of the unconstrained dictionary and the sparse dictionary in terms of detection accuracy.

Conclusion In this work, the grouped sparse dictionary method has been proposed to address the real time flaw inspection problem on textile fabric. Aiming at the time consumption of spare coding process, the large amount of spare dictionary are grouped into several groups with small dictionary atoms inside in advance. By converting the time-consuming sparse coding into a least square problem, the proposed method has been proved to be capable of reducing computation time in inspection phase significantly. The experimental results show that this method can combine the advantages of learning time of unconstrained dictionaries and high accuracy of sparse dictionaries, while ensuring real-time and low false detection rate, and has strong adaptability to different types of defects, especially for warp defects with high accuracy and stability.

Objective Knitted flexible capacitive sensors have been widely studied for their inherent softness and comfort, structural simplicity and low loss. However, most of the sensor electrode materials are exposed to the external environment or in direct contact with the human body, prone to oxidization with long-term use. Moreover, the traditional encapsulation materials used for sensors have poor air permeability, affecting the wearing comfort of human body. Therefore, a knitted composite structure capacitive sensor was proposed to place the electrodes inside the sensor to improve the sensing efficiency of the sensor and the human body experience.

Method The silver-plated conductive yarn and cotton yarn were used to prepare the double-side-effect electrode using the computerized flat knitting machine with different thickness intervals in the fabric to form the "sandwich structure" capacitive sensor. According to the formula C=(ε₀ε_rS)/d, the change in the distance between the electrodes causes change in capacitance value so as to achieve sensing. The assembled sensor was placed on an electronic universal testing machine for compression experiments, and leads from both ends of the electrodes were connected to the TH2830 LCR digital bridge, and the values were recorded simultaneously.

Results The electro-mechanical properties, sensitivity, linearity, compression reversibility, hysteresis and repeatability of the sensor were studied and analyzed. The strain-capacitance curve of the sensor showed that with increasing compressive strain the capacitance value increased gradually, which is consistent with the mechanism elaborated in Equation (1) (Fig. 5). As important index for sensing performance, which is usually expressed as the ratio of the relative rate of change of capacitance to the stress, sensitivity of the sensor was characterized. With the gradual increase of the strain value, the sensitivity of the three different thickness sensors demonstrated a gradual increase with two different output characteristics (Fig. 6). The sensor with a thickness of 20 mm achieved a sensitivity of 0.091 kPa^-1 within 15 to 50 kPa. The linearity of the sensor at each stage was tested, and it was found that the linearity became worsened as the compression distance was increased (Tab.1). It was also found that although the three thickness sensors produced the maximum height difference at the maximum compression distance, the difference was within the error range and produced useful value (Fig. 7). Hysteresis and repeatability were used to characterize the dynamic performance index of the sensor, and a 20 mm thickness sensor was selected for hysteresis study. Repetitive compression tests with different strains were performed for all thickness sensors (Fig. 8), and the capacitance curves of the output during continuous cyclic stress loading and unloading at the same strain value were consistent overall, and the capacitance output curves of the sensor with 20 mm thickness at different strain values produced less fluctuation and smoother curves. The loading and unloading curves of the sensors had a certain height difference and the maximum hysteresis error of 16.2% took place at the stress value of 8.79 kPa (Fig. 9).

Conclusion Flexible capacitive sensors of knitted composite structure were prepared by attaching double-side-effect flexible electrodes to three different thicknesses of warp knitted spacer fabrics. The sensors show two different compression output characteristics, with good linearity but lower sensitivity when the strain is in the range of 0-30%, and reduced linearity when the strain range is 30%-60%. With the increase of compression distance, the sensitivity of the sensor is improved. Among them, the larger the thickness of the dielectric layer, the greater the rate of sensitivity increase, which is expected to be applied in the field of large strain limb motion monitoring. Continuous repetitive compression electrical curves of the three different thickness capacitive sensors at different strain values show good repeatability, which also indicates that the designed sensors have good and stable sensing performance. However, the increase in thickness makes the spacer filaments less stiff against bending and increases the sensing hysteresis. This provides some suggestions for the selection of the fabric dielectric layer in the future. To further improve the durability in practical applications, it would be an interesting research to explore the one-piece double-sided effect knitted capacitive sensor in the future.

Objective In order to realize the efficient design and simple formation of warp knitted spacer shoe fabrics, the structure and forming principle of shoe fabrics are studied, the application benefit of spacer shoe fabrics is explored, and a design method of spacer shoe material is proposed. With the help of JavaScript and C # computer programming language, fast 3-D simulation of several types of spacer shoe fabrics is carried out with different mesh structures, enriching the choices of the mesh spacer shoe materials.

Method The functional structure of different areas of the shoe upper was divided, and the matrix model of process design was established, including the mathematical model of yarn padding number and threading cycle. 3-D loop models of 8-point unit loop, 2-point weft lining, 16-point double warp knit structure were constructed. The classification table of the retransmitted structures was listed by using the transverse displacement difference between the needle and the back of the needle. The stress analysis of the rerun loop and the spacer loop was carried out.

Results The vamp divided into different mesh areas according to functional requirements. Large mesh is used at the toe to improve breathability, small mesh is used at the toe cap and heel area, and tight structure was used at the hem to improve wear resistance (Fig. 1). The construction principle of the 3-D structure of the 4-comb spacer vamp fabric was analyzed. The re-woven weave can be applied to the top and bottom woven surfaces, and the mesh and pattern are only formed on the top or bottom (Fig. 2). The mathematical matrix was used to visually represent the padding number of the spacer shoe fabric and the warp cycle. The knitting action was expressed according to formula of the front and back needle transverse movement difference. Based on the loop control points, the basic 8-point single-needle loop, 16-point double-needle double-needle loop, and 2-point weft lining 3-D models were established, focusing on the hierarchical relationship between the double-needle loop and the two loop on the horizontal single-needle, and the classification table of the double-needle tissue was established according to the transverse movement of the needle back before the needle (Fig. 4, Tab. 1, Fig. 5). According to the formation mechanism of mesh in the spacer shoe material, stress analysis was carried out on both longitudinal lines, and the stress solution of the spacer wire loop in the 3-D space is also carried out (Fig. 6 and Fig. 7). According to different functional requirements, three types of spacer upper fabric processes with different mesh structures were designed, including raw material, knit structure, warp cycle, warp let-off and other parameters. 3-D simulation of three types of spacer mesh upper fabrics was set up using C# and JavaScript programming languages. The comparison between the physical image and the simulation image was shown (Fig. 8, Fig. 9 and Fig. 10).

Conclusion On the basis of summing up and analyzing the structural characteristics of the interval mesh shoe material, using the practical significance of the mesh structure in the shoe material fabric, the relevant technological mathematical model and geometric model are constructed, the mechanical analysis of the tension on the loop during the fabric knitting and the calculation of the corresponding offset are carried out, and the application of the warp weave structure is discussed, which provides a new idea for the design of the three-layer structure warp knitted shoe material. It provides reliable technical support for three-dimensional mesh simulation of Jacquard shoe fabric.

Objective Tubular composites are widely used in petrochemical, construction, aerospace and other fields. The traditional processing method is winding fiber or fabric and curing after resin impregnation. Because the interlayer is only bonded by resin, it is easy to cause delamination. If the tube wall is made of three-dimensional (3-D) woven fabric, the material's ability to resist delamination would be enhanced. In order to improve the design efficiency based on normal looms, a design method and matrix model of 3-D tubular woven fabric are proposed on the basis of combining the weaving rules of tubular and 3-D woven fabrics.

Method The weaving method of 3-D tubular woven fabric is "flattening-weaving-restoring". First, the weaving process takes the fabric as a two-layer 3-D woven fabriclinked at both selvedges, and then opened up to form a tubular section after removal from the loom. The weave diagram is divided into three steps. Firstly, the face weave diagram is obtained by selecting 3-D woven fabrics such as orthogonal, angle-interlocking and stitched multi-layer as the tube wall. Secondly, the back weave diagram is obtained by method called "negative and flip". Finally, according to the method of layered weaving, the weave diagram of 3-D tubular woven fabric is determined.

Results To verify the feasibility of the proposed method, a design example on 3-D tubular woven fabric based on weft through-thickness type orthogonal weave is given (Fig. 3). Firstly, the arrangement ratio of yarn is determine, for example, face warp∶back warp=1∶1, face weft∶back weft=1∶1, then number of warp and weft in a unit of 3-D tubular woven fabric R_gj=12 and R_gw=12. Secondly, the face weave (Fig. 3(a)) is entered at the intersection of odd columns and odd rows and the back weave(Fig. 3(b)) is input at the intersection of even columns and even row. Finally, according to the method of layered weaving, the intersection of the odd columns and even rows is indicated by "⚪" (Fig. 3(c)). The example shows that the proposed method is feasible. Other examples, 3-D tubular woven fabrics using warp through-thickness type angle-interlock weave (Fig. 4) and stitched multilayer type weave (Fig. 5) can both prove the effectiveness of the proposed method

In order to speed up the design efficiency, a matrix model of 3-D tubular woven fabric is proposed. The elements "1" and "3" represent the floating point of warp and weft of face and back weave, element "0" represents the floating point of warp and weft of face and back weave, and element "5" represents the lifting point of face warp when weaving back weft. Replace the elements of the face weave matrix and adjust the order of the columns of the matrix through the MatLab function to obtain the back weave matrix, then the Kronecker product operation is used to realize the proportional embedding of the face weave matrix in the back weave matrix and the assignment of the lifting point elements in the face warp, so as to obtain the matrix of 3-D tubular woven fabric.

In order to prove the effectiveness of the proposed matrix model, the following example is given (Fig. 6). Firstly, matrix B (face weave) with 6 rows and 6 columns. The element "0" is replaced by "3" through the find function of the MatLab program, and then the element "1" is replaced by "0" to complete the "negative" effect. Secondly,the fliplr function of the MatLab program is used to realize the left and right order adjustment of the matrix columns to complete the "flip" effect, and the matrix L (back weave) of 6 rows and 6 columns can be obtained. Thirdly, to generate a matrix C with 6 rows and 6 columns, to set elements are all "5", then matrix K₁, K₂, K₃. Finally, according to Equation (1), through the Kronecker product operation of the matrix, the matrix W of 3-D tubular woven fabric can be obtained.

According to the plotting functions of the MatLab program, different matrix elements print different symbols, such as the elements "1", "3", "5", and "0" are printed "■", "×", "⚪", "□" respectively, which can realize the automatic drawing of the weave diagram.

Conclusion The design method on weave diagram of 3-D tubular fabric is proposed. Firstly, the 3-D woven fabric is selected as the face weave. Secondly, the back weave is obtained according to the "negative and flip" method. Finally, according to the layered weaving method, the weave diagram of 3-D tubular woven fabric can be constructed. The matrix model of 3-D tubular woven fabric weave is established, which uses different matrix elements to represent the floating point of warp and weft of face and back weave, lifting point of face warp when weaving back weft. Matlab function is used to realize the matrix generation of 3-D tubular woven fabric, that is, through element replacement, sequence adjustment of matrix to realize "negative and flip", matrix Kronecker product operation, and automatic drawing of weave diagram.

Objective With the increasing proportion of patterned fabrics produced in fabric manufacturing enterprises, there have been more requirements relating to the production and management of such fabrics, including querying the production materials of imitation, reducing the inventory management costs. The current textile pattern retrieval algorithm has low retrieval efficiency and poor adaptability, which is not conducive to the retrieval of fabric patterns by fabric enterprises. Therefore, a fast and accurate retrieval algorithm for similar patterns was proposed to help enterprises improve the utilization rate of production materials and reduce the cost of fabric inventory management, and promote textile fabric enterprises to enhance the competitiveness of the industry.

Method This research proposed a textile pattern retrieval algorithm based on SURF (speeded up robust features) and VLAD (vector of locally aggregated descriptors) feature coding. A fabric database with patterns was constructed, and SURF features of the image were extracted to express the image content, before the original fabric was clustered to generate a visual dictionary. The generated visual dictionary encoded the SURF features of the fabric image in the database with VLAD features to aggregate to generate VLAD vectors. On the premise of ensuring the ability of VLAD to express images, principal component analysis was performed on the generated VLAD vectors to reduce the vector dimensions and improve the retrieval efficiency. Finally, the Ball tree algorithm was used to build the index to accelerate the matching speed and improve the retrieval efficiency.

Results In order to obtain good retrieval performance, the parameters of the algorithm used were optimized. Through the comparison of retrieval precision and time, it was seen that within a certain range the precision of fabrics was improved with the increase of dictionary size K. However, when K was increased to 1 024, the precision only increased slightly with the retrieval time doubled. As the size of the visual dictionary was increased, the complexity and time cost of training the visual dictionary were greatly increased. Considering comprehensively, the dictionary size K=512 was taken in this research. From the perspectives of the retrieval precision and time, it was seen that with the reduction of feature dimensions, the precision of fabrics was constantly decreasing. When the dimension was reduced to 64, the precision of fabrics decreased greatly, with a slow reduction in retrieval time. Considering the effectiveness and time complexity of the algorithm, the feature dimension D=512 was selected in the subsequent experiments of this research. In order to highlight the advantages of the algorithm in this paper, this paper compared the "ORB (Oriented FAST and Rotated BRIEF)+VLAD", "HOG (Histogram of Oriented Gradient)+VLAD", "Color Moments (CM)", "Color Moments+ Gray-level Co-occurrence Matrix" and "Color Histogram+ Gray-level Co-occurrence Matrix" for retrieval verification. The average retrieval accuracy of the algorithm reached 83.5%, the average retrieval time was 0.488s, and the comprehensive performance was better than other algorithms. From the P-R curves, it was evident that the algorithm developed in this research performed the best on the data set built. "HOG+VLAD" was slightly better than "ORB+VLAD", indicating that SURF was able to better describe the characteristics of patterned fabrics than ORB and HOG.

Conclusion The experimental results show that when the scale of visual dictionary K is 512 and the number of reserved dimensions is 512, the average retrieval accuracy of the algorithm for fabric pattern retrieval is 83.5%, the average retrieval time is 0.488 seconds, and the algorithm has good size invariance and rotation invariance. It has good performance and adaptability for fabric pattern retrieval, which has certain practical significance for the practical application of textile enterprises.

Objective In order for fabrics to automatically adjust the moisture loss according to the change of human body humidity, the microstructure of pine cone leaves, which open and close following humidity change, was studied and simulated. Polyurethane coating was used on polyester-ammonia knitted fabric to form the active layer and the driven layer with big difference in moisture absorption and elongation, so that the pine cone-like functional fabric responding to moisture was developed. Its pine cone-like leaves can automatically open and close according to the change of the wearer's body humidity, and the humidity can be quickly adjusted to improve the comfort of the wearer.

Method According to the response mechanism of pine-ball-like fabric to humidity, a self-made testing device for fabric moisture conductivity was designed, including water vapor generation, fabric moisture exchange and moisture conductivity detection. The relationship between the leaf aspect ratio (the ratio of longitudinal dimension to transverse dimension of leaf opening), leaf direction (the angle between leaf opening direction and cloth warp direction of driven layer), coating attach rate (the ratio of coating weight to cloth weight of driven layer) and moisture conductivity of leaf opening time, opening angle, opening speed and effective opening rate of pine-like fabric was studied.

Results It was found that as the leaf aspect ratio decreased (Fig.7-9), the opening time of the leaves gradually increased, and other moisture conductivity indicators of the leaves, namely, full opening angle, opening speed and effective opening rate, increased at first and then decreased. The change of leaf aspect ratio had the greatest influence on the effective opening rate of pine cone-like leaves, fluctuating in the range of 73%-92%. When the leaf aspect ratio was 65%, all the properties were the best. With the increase of the blade direction (Fig.10-12), the moisture conductivity indicators of the pine-ball-like fabric, including opening time, opening angle, opening speed and effective opening rate, exhibited a sudden decrease. When the blade direction was 90° the pine-ball-like fabric had no obvious opening phenomenon when wet, and when the blade direction is 0° the pine-ball-like fabric was shown to achieve the best performance. With the increase of coating attach rate of pine-cone-like fabric (Fig.13-15), all properties were increased at first and then decreased except for the opening time of the leaves. The increase of coating amount had the greatest influence on the effective opening ratio of pine-cone-like fabric, which fluctuated in the range of 77%-93%. When the coating attach rate was 66.7%, the moisture conductivity of pine-cone-like fabric reached the best. When the aspect ratio of pine cone-like leaves was 65%, the direction of the leaves was the warp direction of the driven layer and the attach rate of the coating was 66.7%, the moisture conductivity of pine cone-like fabric was the best, with its opening time of 47s, opening angle of 85.59°, average opening speed of 1.82(°)/s and effective opening rate of 93%.

Conclusion According to the research on the factors affecting the moisture conductivity of pine-cone-like fabric, the change of pine-cone-like leaf direction has the greatest influence on the opening performance of the leaves. With the increase of the angle between the leaf direction and the warp direction of cloth, all the properties of pine-cone-like leaves drop rapidly until they close completely. The change of aspect ratio and coated attach rate of pine cone-like leaves had a great influence on the effective opening rate of leaves, followed by a certain influence on opening speed, but a little influence on opening time and opening angle.

Objective Cotton fabrics have the advantages of breathable moisture permeability and comfort, and is widely used for summer clothing. However, cotton fabrics are weak in UV protection. It is known that excessive ultraviolet irradiation, particularly in the summer, causes great harm to the human body, but the common anti-ultraviolet finishing agent is easy to be washed off during laundering. It is necessary to improve the fastness of anti-ultraviolet agents on cotton fabrics. In this research, BN-CQDs and isocyanate microcapsules are used to finish cotton fabric.

Method BN-CQDs were fixed to the fabric using microcapsule core material isophorone diisocyanate. In this research, the structure and surface morphology of finished cotton fabric and microcapsules were studied, and characterized by Fourier infrared spectroscopy, three-purpose ultraviolet analyzer and video microscope. In addition, the UV protection factor (UPF) of the finished cotton fabric was measured to examine the effect of the volume proportion of different modified liquid on the UV protection and UV water-resistant properties of the fabric. The moisture permeability of the cotton fabric was tested to study whether the finished fabric was qualified in the moisture permeability.

Results Isocyanate group and —NH appeared in the prepared microcapsules at 2 257 cm^-1 and 3 365 cm^-1, respectively, while the isocyanate group was stronger in the pure core material and there was no —NH (Fig. 1). Isocyanate-type microcapsules showed smooth surface without wrinkles, particle size of about 200 nm and relatively concentrated distribution, core material mass fraction of microcapsules reaches 42%, and encapsulation efficiency is 75% (Fig. 2, Fig. 3 and Fig. 4). As the content of microcapsules in the modified solution increased, the strength of the hydroxyl group in the finished fabric also decreased (Fig. 5). The original fabric appeared almost white under ultraviolet lamp, while the cotton fabric after finishing illustrated bright blue fluorescence. The fluorescence of pure BN-CQDs finishing fabric became weaker sharply after 20 times of washing. However, after the same washing, the fluorescence intensity of the BN-CQDs/ microcapsules composite reinforced by the finished fabric was only reduced slightly, and the blue fluorescence of microcapsules was also slightly improved with the increase of microcapsule content in the modified solution (Fig. 6). The UPF value of the original fabric was low, and the UPF value of the BN-CQDs fabric only was increased slightly to 19 and the UV transmittance of the two fabrics was greater than 5%. The UPF value of BN-CQDs/ microcapsule fabric was maintained at 34-36, which reached the level for ptoviding better protection, and increased by 192.6%-207.7% compared with the original. After 20 washes, the UPF value of the BN-CQDs fabric was decreased to 14, and the declining rate of the UPF value of the BN-CQDs/ microcapsule fabric also decreased with the increase of the microcapsule content in the modified solution. Because IPDI reacted with the cellulose and the surface OH of the BN-CQDs, it was fixed on the fabric. However, when its content reached 3 mL, the decrease rate of its UPF value did not change much. For example, the UPF value of A6 fabric was still as high as 32, representing a decrease by 11%, and the ultraviolet transmittance of A1-A5 fabrics were less than 5% (Fig. 7 and Fig. 8). For the finished fabric, the moisture permeability was found in the range of 2 712-3 101 g/(m²·d), in comparison to the moisture permeability of 3 154 g/(m²·d) untreated fabric, representing a reduction from 2% to 14%, meeting the moisture permeability requirement (Fig. 9).

Conclusion Isocyanate microcapsules have smooth surface, complete morphology, uniform dispersion and no agglomeration. The original fabric and BN-CQDs are not up to the "requirements of UV protection products", and the addition of BN-CQDs on the surface of the fabric will improve its UV protection performance, at the same time adding isoferone diisocyanate microcapsules not only improve the UV water resistance, but also reduce the UV transmittance, BN-CQDs/ Microcapsule fabric meets the requirements of "UV protection products". BN-CQDs/ microcapsule finishing can reduce the moisture permeability of fabric slightly, but still meet all the requirements of moisture permeability.

Objective Waterborne polyurethane fabric finishing agents are limited in their applications due to their poor hydrophobicity and electrical conductivity. This study aims to enhance the hydrophobicity, mechanical properties and electrical conductivity of waterborne polyurethane by incorporating functionalized graphene oxide. The goal is to create a multifunctional waterborne polyurethane fabric finishing agent that can expand its range of applications.

Method Functionalized graphene oxide (MPD-I-GO) was synthesized by sequentially reacting isophorone diisocyanate (IPDI) and m-phenylenediamine (MPD) with graphene oxide (GO). MPD-I-GO was then incorporated into waterborne polyurethane(WPU) at a specific mass fraction to produce an MPD-I-GO/WPU fabric coating. The chemical structure, crystallinity and microscopic morphology of MPD-I-GO were characterized using infrared spectroscopy, Raman spectroscopy, X-ray diffraction, scanning electron microscopy and X-ray photoelectron spectroscopy. Additionally, the hydrophobicity, mechanical properties and electrical conductivity of the composite films were evaluated and analyzed using a surface wetting angle meter, universal tensile tester and four-probe conductivity meter.

Results The MPD was introduced into the GO surface with IPDI as a bridge to make MPD-I-GO (Fig. 2). It also intercalates into the GO sheet layer, making part of the layer spacing increase and disorder increase (Fig. 3 and Fig. 4). When the MPD-GO addition is 0.18% and below, the composite latex particles were spherical with uniform sizes and were evenly distributed with no aggolomeration, and the average particle size was about 44.77 nm (Fig. 7 and Fig. 8). The contact angle of the composite latex membrabe showed an increasing trend with the increase of MPD-I-GO mass fraction (Fig. 10), and when MPD-I-GO was added, wrinkles appeared in the cross section of the composite latex membrane and became more and more obvious with the increase of MPD-I-GO mass fraction (Fig. 12). The addition of MPD-I-GO significantly improved the mechanical properties of WPU (Fig. 13). The resistivity of the composite latex membrane decreased significantly after the addition of MPD-I-GO, and with the increase of the mass fraction of MPD-I-GO the resistivity of the composite latex membrane all showed a trend of first decreasing and then increasing, and reaching the minimum value of 205 Ω/cm at 0.18% (Fig. 14).

Conclusion In this work, MPD-I-GO was prepared by modifying GO with IPDI and MPD successively and introduced into WPU, and the effect of mass fraction of MPD-I-GO on the properties of composite adhesive films was investigated. The study showed that IPDI and MPD were successfully grafted onto GO without completely destroying the lamellar structure of GO. In addition, when the addition amount of MPD-I-GO was below 0.18%, MPD-I-GO could be uniformly dispersed in WPU and effectively promoted the improvement of hydrophobicity, mechanical properties and electrical conductivity at the same time. The introduction of MPD-I-GO improved the roughness of the surface of the latex film, thus improving the hydrophobicity of the composite at the structural level. This indicates that the introduction of MPD-I-GO can effectively enhance the performance of WPU and promote the functionalized application of waterborne polyurethane fabric finishing agents.

Objective This research is to tackle the poor adhesion between ultra-high molecular weight polyethylene (UHMWPE) fiber fabric and thermoplastic polyurethane (TPU) by using atmospheric pressure dielectric barrier discharge (DBD) plasma to treat the surface of UHMWPE fabric and adjust the adhesive process aiming to improve the composite material interface bonding properties.

Method The UHMWPE fiber fabrics were treated by hot-pressing using a hot melt bonding machine with different parameters such as voltage and number of atmospheric pressure in DBD plasma treatment. The composite properties such as fiber structure, surface morphology, chemical composition, breaking strength and peeling strength were tested and characterized by scanning electron microscope, X-ray diffractometer, X-ray photoelectron spectrometer and electronic universal material testing machine.

Results With the increase of heating temperature and time in the thermal compounding process, the monoclinic crystalline shape gradually disappeared and the diffraction peaks of orthogonal crystalline shape became smaller, and the high heating temperature easily led to the destruction of the regular fiber structure (Fig. 2), causing decrease in fracture strength of fibers. For the adhesion performance of UHMWPE fiber fabric and TPU without atmospheric pressure DBD plasma treatment, the peel strength became larger with the increase of hot-pressing time at the lower temperature of 110 ℃ and below.The peel strength increased and then decreased with the increase of hot-pressing time when the treatment temperature increases to 120 ℃ and 130 ℃. When the hot-pressing temperature was 120 ℃ and the time is 30 s, the adhesion performance of UHMWPE fiber fabric and TPU reached the optimum, and the peel strength reached 42.88 N/(25 mm) (Fig. 5). After the atmospheric pressure DBD plasma treatment, the surface of UHMWPE fibers produced obvious etching marks (Fig. 6), while a large number of free radicals were generated on the fiber surface under the excitation of plasma, and the free radicals reacted with oxygen in the air to produce oxygen-containing polar groups such as C=O and O—C=O (Fig. 7), and the content of polar groups increased from 0% to 7.02% and 3.85% (Tab. 2), the increase of reactive groups were shown to significantly improve the adhesion performance of UHMWPE fabric and TPU. The mechanical properties of the filament bundle and the peel strength of the fabric increased and then decreased with the increase of the treatment voltage and the number of treatments. When subjected to three atmospheric DBD plasma treatments under 200 V, the fabric composite performance reached the optimal state, where the filament bundle breaking strength increased by 1.8%, and the peel strength reached 56.05 N/(25 mm), representing an increase of 30.72% (Fig. 8).

Conclusion In the composite manufacturing process of UHMWPE fiber fabric and TPU, when the hot-pressing temperature is 120 ℃ and the hot-pressing time is 30 s, the bonding property of UHMWPE fabric and TPU is the best, with the peel strength being 42.88 N/(25 mm). After atmospheric pressure DBD plasma treatment, obvious etching marks are produced on the UHMWPE fiber surface, the oxygen-containing polar functional groups on the fiber surface are increased, and the mechanical properties of the tow and the peel strength of the fabric increase and then decrease with the increase of the treatment voltage and the number of treatments. When the treatment voltage was 200 V for 3 times, the breaking strength of the tow is increased by 1.8% and the peel strength is increased by 30.72%. In this paper, through the exploration of composite process, atmospheric pressure DBD plasma was used to improve the interfacial bonding properties of UHMWPE fiber fabric/TPU composites, which promoted the application of UHMWPE fiber fabric in light and high strength tent membrane materials.

Objective Reactive dyeing is known for its complex dyeing process, high energy and water consumption, and large discharge of colored wastewater, which seriously restricts the transformation and upgrading of the printing process. As an effort to reach "emission peak and carbon neutrality", the development of reactive dye cyclic dyeing with energy saving and emission reduction advantages is conducive to promoting the green and low-carbon production in the printing and dyeing industry.

Method The treatment agent contains compounds with bleaching and oxidizing functions. This wastewater treatment agent was selected for dyeing fabric soaping, realizing the low temperature fast soaping of dyeing fabric and recycling of dyeing wastewater. Taking a type of simulated wastewater as the research object and absorbance as the evaluation index, the treatment and reuse process of wastewater was explored. The feasibility of cyclic dyeing was verified by the determination of dye exhaustion rate, fixation rate and color parameters of dyed fabric.

Results The results showed that the decolorization rate of dye solution increased with the increase of temperature, and the higher the temperature the shorter the treatment time (Fig. 2). Under the same treatment time, the higher the treatment agent concentration, the higher the decolorization rate of dye solution, indicating that increasing the concentration of treatment agent was conducive to reducing the number of dye molecules in the waste liquid. In addition, it was found that the same effect could be achieved by prolonging the treatment time when the concentration of treatment agent was low (Fig. 3). When the treatment time was 5 min, the decolorization rate of dye solution with 20 g/L of NaCl was up to 64.7%, which was 21.9% higher than that of without NaCl. Further increasing NaCl concentration to 50 g/L had no significant effect on the decolorization rate of dye solution. Further extending the treatment time to 30 min, NaCl showed little effect on decolorization rate of dye solution (Fig. 6). After treatment at 85 ℃ for 15 min, the maximum absorption wavelength in the visible region disappeared, and the decolorization rate of the dye solution was as high as 99.1% (Fig. 7). When the reactive dye was dyed with recycled water, the dye percentage in the first 30 min was 9.0%-13.9% higher than that of the deionized water at the same time. Increasing the number of dyeing cycles did not change the overall trend of dyeing rate curve (Fig. 8). Compared with the color parameters of the fabric dyed by deionized water, the color of the fabric dyed by cycle was darker, the red and blue light were weakened (Tab. 1).

Conclusion The treatment agent of 3%, the temperature of 85 ℃ and the time of 15 min were appropriate for dealing with 0.07 g/L of C.I. Reactive Red 218 simulated wastewater. The decolorization rate of dyeing wastewater is up to 99.1% after 15 min treatment. Under the same treatment process, the acid condition has the best treatment effect, the neutral condition is the next, and the alkaline condition is the worst. Compared with deionized water, the percentage of reactive dye increased with the extension of dyeing time. During cyclic dyeing, reactive dyes have higher dye exhaustion and fixation rate, and the dyed fabric is darker, and the red and blue light are weakened. This method not only realizes the efficient treatment of dyeing wastewater, but also realizes the reuse of inorganic salts in dyeing residue, which is conducive to energy saving and emission reduction.

Objective Heavy metal ions as a common toxic substance in printing and dyeing wastewater cause great harm and much efforts have been made to treat the wastewater aiming to reducing the concentration of heavy metal ions. The adsorption method has the advantages of simple operation, high efficiency and no secondary pollution. As a novel adsorbent, β-cyclodextrin organic skeleton material is explored for adsorbability for heavy metal ions along with simple, eco-friendly and low-cost preparation.

Method β-cyclodextrin organic matrix (β-CDMOF) was synthesized by hydrothermal method with β-cyclodextrin and potassium chloride as raw materials. A series of β-cyclodextrin based adsorbents (β-CDMOF/CA) with good water stability were prepared by using citric acid as crosslinking agent and controlling the different feeding ratios of β-cyclodextrin based MOFs and citric acid in the reaction process, and were named as β-CDMOF/CA (1∶1), β-CDMOF/CA (1∶2) and β-CDMOF/CA (1∶3), respectively. The structures of these adsorbents were analyzed by SEM, FT-IR and XRD, and the adsorption properties of these adsorbents for Sb(Ⅲ) and Pb(Ⅱ) ions were studied.

Results Compared with the irregular morphology of β-CDMOF, the crosslinked β-CDMOF/CA exhibited more regular appearance, and more stable appearance with the increase of CA addition, indicating significant improvement with crosslinking treatment in morphological stability of the prepared adsorbent (Fig. 1). The main frame and structural integrity of β-CD were preserved during the cross-linking process of CA (Fig. 2). The cross-linking reaction between CA and β-CDMOF resulted in the continuous reduction in the crystallinity and the gradual change of crystal structure of β-CDMOF (Fig. 3). The water stability of the adsorbent was gradually enhanced with the increase of crosslinking. The adsorption process of the prepared three adsorbents for Sb(Ⅲ) and Pb(Ⅱ) accorded with the Langmuir adsorption isothermal model and the quasi second-order adsorption kinetic equation, namely chemical adsorption. β-CDMOF/CA(1∶3) demonstrated the best adsorption performance, and its maximum saturated adsorption capacity to Sb(Ⅲ) and Pb(Ⅱ) reached 515.46 and 591.71 mg/g, respectively. After 5 times of adsorption-desorption, the removal rate of Sb(Ⅲ) and Pb(Ⅱ) by β-CDMOF/CA(1∶3) was still higher than 75%, showing a stable cyclic adsorption performance. The adsorption mechanism of Sb(Ⅲ) and Pb(Ⅱ) by the adsorbent was mainly determined through electrostatic interaction and chelation.

Conclusion β-CDMOF was synthesized by hydrothermal method with β-CD and KCl as raw materials, and then the adsorbent β-CDMOF/CA with good water stability and heavy metal ion adsorption was prepared by crosslinking with CA. The results show that the prepared adsorbent is a crystal with relatively uniform size, and its solubility in water is lower than 0.034 g/L, which is easy to filter and separate from wastewater. The adsorption results show that the maximum adsorption capacities of β-CDMOF/CA for Sb(Ⅲ) and Pb(Ⅱ) are 515.46 mg/g and 591.71 mg/g, respectively. The adsorption kinetic results show that the adsorption process of β-CDMOF/CA for two metal ions conforms to the pseudo-second-order kinetic model, which is a chemical adsorption process. After 5 times of adsorption-desorption cycles, the removal rate of β-CDMOF/CA for two metal ions is still more than 75%, indicating good recycling performance. The adsorbent developed in this research has the characteristics of low cost, simple preparation, green environmental protection and excellent adsorption performance, and shows a good application prospect for the treatment of heavy metal ions in textile printing and dyeing wastewater.

Objective In order to solve the problem of ambiguity in the amount of front crotch bulge in men's underwear pattern and the problem of ill-fitting crotch of underwear, a surface simulation model of waist, hip and crotch of male human body was established by extracting point cloud data, and a well-fitting men's underwear pattern was generated based on the surface model to improve the comfort of wearing men's underwear by improving the underwear pattern, and also to broaden the new idea of fast access to the fit and body-fitting clothing pattern.

Method A 3-D body scanner was used to obtain the point cloud data of the waist, hip and crotch of the experimental subject, and the point cloud coordinate set was extracted from the point cloud data using reverse engineering software to describe the waist, hip and crotch morphology. NURBS curve and surface principle were used to construct the waist, hip and crotch surface model, the 3-D surface was developed into a 2-D plane in Solidworks software, and the developed plane was processed using ET software to generate a fitted digital underwear pattern.

Results Using the 3-D body scanner to obtain the point cloud data of the male mannequin, 7 feature sections characterizing the morphology of the waist, hip and crotch were selected, and 50 equidistant points of each feature section were extracted from the point cloud data to form a point cloud coordinate set as indicated in Fig. 2(b) for the point cloud coordinate set imported into Solidworks software. The male waist, hip and crotch were reasonably divided into 16 areas, and NURBS curves and surfaces were constructed based on the information of point coordinates in the point cloud coordinates set (Fig. 4). The waist, hip and crotch surface models were established in Solidworks software by using common connecting lines of adjacent surfaces, and the surface models were made to accurately describe the body surface morphology of the waist, hip and crotch. The surface flattening tool was used to flatten the three-dimensional surface into a two-dimensional plane, and the area error ≤1 cm² and the boundary length error ≤1 cm during the flattening process were within the acceptable range of dimensional error. The 2-D plane was exported into the ET software for 4 simple steps (Fig. 7): curve point optimization, plate alignment and shape docking, front and back crotch line adjustment and waist adjustment, and the final digital men's underwear pattern was generated. Based on the virtual fitting of 3-D scanned mannequins in CLO3D software and the actual garment fitting on the male mannequin, the fitting effect was verified for the underwear pattern. Using an air bag contact pressure tester, the pressure test was conducted on seven key parts of the underwear wear. The garment pressure generated by the underwear ranged from 0 to 2.4 kPa (Tab. 4), verifying that the digital underwear version met the garment pressure comfort requirements.

Conclusion For the study of fitted men's underwear patterns, a method is proposed to establish a surface model of the waist and hip crotch and generate a digital men's underwear pattern through the surface model, which solves the problem of ill-fitting men's underwear crotch and provides a new approach for the rapid generation of fitted men's underwear patterns. The digital pattern-making method can be applied to the acquisition of fitted and close-fitting garment patterns by establishing a simulated surface model of the human body form to generate a fitted garment pattern, and the structure of the garment pattern is more in line with the detailed morphological characteristics of the human body.

Objective In personal customization of cheongsam, the existing clothing recommendation system has a single type of recommended style and the clothing style is not clearly defined, resulting in a long-time recommendation process. As such, the cheongsam matching recommendation system is difficult to meet the needs of users.

Method Four typical modern cheongsam styles were selected for component classification and coding, and a database of modern cheongsam style design components was constructed. A modern cheongsam style recommendation system was constructed by using the interactive evolutionary computation method. Finally, modern cheongsam styles were displayed in the interactive interface of the modern cheongsam style recommendation system, and the main cheongsam component styles including the traditional Chinese style and sexy style were considered in the modern cheongsam style recommendation system, and the query times and query accuracy of the interactive evolutionary algorithm were verified.

Results Four typical modern cheongsam styles, i.e. the traditional Chinese style, sexy style, sweet style and simple style, were selected for analysis, and a database of modern cheongsam style design components were constructed. The part library of modern cheongsam was mainly composed of style parts and decorative parts. The style part library was divided into profile, collar, sleeve, placket and slit sub-part library, and the decorative part library included fabric, color, pattern and craft sub-part library. Modern cheongsam components and styles were encoded to facilitate subsequent interactive recommendations. Interactive evolutionary computing was used to build a modern cheongsam style recommendation system, involving user evaluation and population evolution. Users were able to score the style design scheme of modern cheongsam in the interactive evolutionary computing system. The system involved individuals through the initial setting, so as to achieve the crossover and mutation operation of interactive evolution. Through evolution, a new population was generated for users to select and evaluate, and finally the evolution operation was completed, so that the system could produce the optimal modern cheongsam design scheme to meet the needs of users. The system was verified by the recommendation of traditional Chinese style and sexy style cheongsam. The verification results indicated high accuracy and high efficiency of proposed method.

Conclusion The research uses the interactive evolutionary algorithm to build a modern cheongsam style recommendation system, and the system is mainly based on the modern cheongsam style components classification, scientific analysis. The modern cheongsam components are encoded, which is conducive to the recommendation system to efficiently pass information to users. The modern cheongsam recommendation system uses the interactive evolutionary calculation method to be superior to the sequential query in the selection of intensive reading and selection time. It can recommend the modern cheongsam style to the user more accurately and quickly, and can effectively improve the user's satisfaction with purchasing modern cheongsam. The modern cheongsam recommendation system can quickly grasp the user's preference for modern cheongsam style, greatly reduce the time for users to select cheongsam, make users more efficient and convenient to find personalized and customized modern cheongsam, and have innovative significance for modern cheongsam interactive style recommendation. In the future, the modern cheongsam recommendation system can also establish a variety of style library, to bring users personalized custom style of modern cheongsam recommendation system for the field of interactive clothing to provide reference and reference.

Objective It is reported that manual quality detection of sewing stitch is inefficient and that the existing algorithms are difficult to detect the sewing stitch and the detection is easily interfered by factors such as fabric wrinkles and illumination changes. An improved YOLOv4-Tiny object detection algorithm is proposed to recognize and locate the sewing stitch points. The number and position information of the sewing stitch points yielded by the model are used for sewing quality detection.

Method The convolutional attention mechanism improved by SoftPool was introduced in YOLOv4-Tiny to enhance the object detection network’s attention to the features of sewing stitch points, before a Soft-SPPF module composed of SoftPool was introduced in front of YOLO Head to realize the model's utilization of multi-scale features in prediction. The improved algorithm was used to calculate the number and coordinate information of all sewing stitch points in the sewing stitch image, together with the density and uniformity of stitch points.

Results The improved YOLOv4-Tiny algorithm and other object detection models were trained by data augmentation on a self-built sewing dataset (Fig. 2) and converge after 150 epochs of training (Fig. 7), and were tested on a test set. By comparing the improved YOLOv4-Tiny algorithm, MobileNet-SSD, YOLOv5s and the original YOLOv4 algorithm, the detection performance in sewing stitch points of the improved method was notably improved. The improved YOLO-Tiny algorithm achieved a mean average accuracy of 85.50% and a detection time of 15.9 ms (Tab. 3), which is more suitable than the original algorithm for sewing stitch detection. In addition (Fig. 8 and Tab. 2), the improved YOLOv4-Tiny algorithm was found to obtain accurately information on the number and coordinates of sewing stitch points in the images of the five sewing stitch types, and density and uniformity were obtained by calculating the number of stitch points per 10 cm and the average relative error between the distance of all adjacent stitch points and the average pixel distance. The quality results obtained from the detection were all within 0.6 stitches per 10 cm difference between density and manual detection, while the maximum difference in uniformity is 1.21%, proving the feasibility of this method. Finally, ablation experiments were carried out and the results are shown in (Tab. 5). The introduction of other modules significantly improved the detection performance of the YOLOv4-Tiny algorithm, and there was no significant decrease in the detection speed. The Soft-CBAM and Soft-SPPF after the introduction of SoftPool improved the detection performance of YOLOv4-Tiny more significantly than the original CBAM and SPPF, and the difference between the detection speed and the original modules was within 0.5 ms, which is a much better performance.

Conclusion The improved algorithm can achieve stitch point recognition despite interference from factors such as fabric folds and accurately obtain location information, which is suitable for sewing stitch detection scenarios. The proposed density and uniformity calculation method is verified by comparing with the manual inspection results, which can meet the actual inspection accuracy requirements and is significantly faster compared with the manual sizing inspection, which can effectively improve the production efficiency of the garment industry.

Objective In response to the increasing requirements for steady temperature and humidity control in textile workshops, this study proposes a directional uniform flow inlet to meet the process requirements of different the workshop equipped with spinning-winding unit based on numerical and experimental studies. A comparison of the new air supply effect with the conventional mixed flow inlet is carried out to provide technical guidance for the actual engineering design.

Method A combination of numerical simulations and experiments was used to analyze the airflow organization of the directional uniform flow inlet and the conventional mixed flow inlet with different equipment arrangements. ANSYS Fluent was used to simulate the flow field in the defined area of the different air supply outlets. The airflow organization of the different air supply outlets was evaluated qualitatively and quantitatively using velocity, temperature, relative humidity, and distribution deviation coefficients. Based on this, an experimental benchmark was set up to compare the airflow effects so as to verify the feasibility of the numerical simulation in the textile workshop and to evaluate the respective airflow effects using the velocity and temperature distribution deviation coefficients.

Results The simulated and experimental results of the temperature distribution for the directional uniform flow inlet showed high agreement with each other, which verified the effectiveness of the numerical model used. In terms of velocity distribution, (Fig. 3, 4), the directional uniform flow inlet had a more even airflow distribution due to the presence of the split blades, ensuring the airflow range meeting the requirements of the working area. The velocity showed a trend of being lower at both ends and higher in the middle, with a relatively gentle curve. The velocity was higher the winder area than in the spinner area in the model, demonstrating the capability of the new design for air volume distribution for a small environment. In contrast, the conventional mixed flow inlet did not have dispersed airflow, and the outflow direction was mostly on both ends. Due to the convergence phenomenon caused by the partial airflow passing through the air-supply structure, the velocity distribution was high at both ends and low in the middle, with considerable fluctuation in the spinner area. The velocity deviation coefficients for the two types of inlet were 0.209 3 and 0.088 9 respectively, indicating that the directional uniform flow inlet had a more even airflow velocity distribution. In terms of the temperature and humidity distribution in the calculation domain (Fig. 5, 6, 7), the mixed flow inlet exhibited local areas with obvious fluctuation in both temperatures and humidity due to unreasonable regulation of the air volume under different equipment heat dissipation situations. The directional uniform flow inlet had a uniform temperature and humidity distribution in each area due to the implementation of the split blades and the equal-flow guide plate. The new design was proven to meet the required environmental conditions of the winder area with low temperature and high humidity and the spinner area with high temperature and low humidity. The average temperature deviation coefficients for the two types of inlet were 0.015 2 and 0.008 3 respectively. Therefore, the directional uniform flow inlet had a more uniform temperature distribution.

Conclusion In summary, the airflow organization of the directional uniform flow inlet proposed in this paper is more uniform than traditional composite type mixed flow inlet. The temperature and humidity in all areas generally meet the required environmental requirements. Its set of the split blades and the equal-flow guide plate can achieve small environmental adjustment and directional air supply under different equipment arrangements. Its average deviation coefficient of velocity and temperature is smaller than that of the conventional mixed flow inlet, so the directional uniform flow inlet will have a better air supply effect in engineering applications.

Objective In response to problems such as high labor demand, low automation, and low efficiency in the process of fabric stitching, machine vision, industrial robot, and sewing machine technologies were studied and applied to the design and development of intelligent sewing equipment. By combining these technologies, it helps to improve the absolute positioning accuracy of the industrial robot, as well as the ability to extract fabric contours and ensure the consistency of sewing quality. This has reduced the need for manual labor and has helped drive the transformation and upgrading of the garment sewing industry.

Method Firstly, the absolute positioning kinematics parameter error compensation technology of industrial robot based on wire encoder was studied, so that the absolute positioning accuracy of industrial robot can meet the requirements of sewing task. Secondly, the technology of fabric contour and key points extraction based on Canny operator was studied, which provides data basis for the sewing path plan. Thirdly, the speed synchronization control algorithm of industrial robot and sewing machine based on proportional integral differential (PID) law was developed to solve the problem of irregular stitches caused by the unsynchronization of industrial robot and sewing machine.

Results A double-layer garment piece intelligent sewing equipment consisting of industrial robot, camera, sewing machine, working platform, loading, unloading and other auxiliary mechanisms was developed according to customer needs (Fig. 3,4). The calibration software was developed by applying the optimization compensation technology for the absolute positioning error of the industrial robot based on the wire encoder, which reduced the absolute positioning accuracy error of the central point of the industrial robot tool from the average 1.263 5 mm to 0.128 5 mm. Sewing effect showed the comparison of sewing effects before and after optimization of absolute positioning error. Sewing effect before error compensation shows the sewing stitches prior to error optimization and sewing effect after error compensation shows the sewing stitches after error optimization. It can be seen from sewing effect that the sewing quality of the fabric was greatly improved by adopting the error optimization technology. Using fabric contour extraction technology based on Canny operator, a fabric contour and key point's extraction program based on OpenCV was developed. The original fabric image was a fabric of arbitrary shape, representing various contours of real fabric such as straight line, arc and curve. Fabric contour extraction showed the effect of the contour and key points extraction program, generating different numbers of key points according to different contour curvature. The larger the curvature, the more key points were to be extracted, which was convenient for trajectory planning of the industrial robot and improves the sewing quality. The control block diagram and corresponding control program were constructed by using the speed synchronization control technology of the industrial robot and the sewing machine. The sewing machine needle speed was on open loop control, and its speed was proportional to the Tool Center Point (TCP) speed of the industrial robot. The speed of the cloth feeding wheel of the sewing machine was controlled in a closed loop, which improved the ability of the cloth feeding wheel speed to follow the TCP speed of the industrial robot. Sewing effect and stitches demonstrated the effect before and after the speed synchronization of the industrial robot and the sewing machine, leading to significant improvement of the quality of stitches.

Conclusion Combined with machine vision, absolute positioning error compensation of industrial robot, contour extraction technology, synchronous control technology of manipulator and sewing machine, and this research systematically studied the technical system required for intelligent sewing equipment. The research and development of intelligent sewing equipment has effectively reduced the number of equipment operators, solved the problem of shortage of sewing workers, provided technical accumulation for the automation and intelligence of sewing equipment, and also provided a technical basis for the automation, intelligence and digital transformation of the sewing process in the sewing industry. It is recommended that the sewing equipment should be further improved mainly from the following two aspects, i.e., the 6-axis industrial robot should be changed to Selective Compliance Assembly Robot Arm (SCARA) to reduce equipment costs and improve the absolute positioning accuracy, and a simple and easy-to-use human-computer interface should be designed to facilitate operation and switching sewing tasks.

Significance With the start of a new round of technological revolution and industrial advancement, China's textile industry has stepped into a new stage of high-quality development. This paper provides a comprehensive overview of the development and application of artificial intelligence technology in the textile industry and explores the tasks and goals of future intelligent development. Based on the latest global developments in digitalization, networking, and intelligence in the textile industry, it analysed the current technical challenges and summarised the key technologies urgently needed in the textile industry. Typical application cases and production models were introduced such as whole-process intelligent textile production lines, intelligent operation and maintenance of textile equipment, and intelligent textile testing. The core technological challenges facing the Chinese textile industry and the development directions of the industrial ecology were to be reviewed. Ideas on developing a new generation of textile-intelligent manufacturing systems and creating an intelligent textile ecology with the collaboration of the whole industrial chain were presented.

Progress At this stage, the Chinese textile industry intelligent manufacturing is in a critical period of digital, networked, and intelligent development (Fig. 1). The critical technologies related to the intelligence of the textile industry are developing rapidly, and big-data technology for the whole textile production process is being applied rapidly (Fig. 2). Digital-twin technology in the textile industry is applied to intelligent garment design and intelligent textile factories (Fig. 3 and Fig. 4). As automated equipment replaces manual labor in typical textile processes, robots in the textile industry have become an essential part of intelligent production. Machine vision technology based on deep learning plays a role in the intelligent control of textile equipment and intelligent inspection of textile quality scenarios (Fig. 5). Intelligent scheduling technology based on machine learning effectively improves the production efficiency of textile enterprises. Based on these technologies, typical examples of intelligent applications in the textile industry have emerged. A data-driven intelligent operation and maintenance system for high-speed winders (Fig. 6), enables data-based intelligent fault diagnosis and remaining life prediction of equipment. The "edge-cloud" collaborative fabric defect detection system enables the detection and identification of a wide range of fabric defects. Xinfengming Group realizes the intelligence of the whole production chain based on 5G and product identification resolution technology (Fig. 7). Wuhan Yudahua's 100000-spindle full-process intelligent spinning line solves the discontinuity problem between some of the ring spinning processes, with an automation rate of over 95% (Fig. 8).

Conclusion and Prospect China's textile industry has made a breakthrough in digitalizing equipment, networking, and workshop intelligence. Significant progress has been made in improving quality and efficiency and optimizing the industrial structure. However, a series of standards system for intelligent manufacturing in the textile industry has yet to be established. In the field of cotton spinning, for example, there are still breakpoints in the automated production of the whole process. The quality traceability of the whole process of product production needs to be strengthened. Data processing and other software are primarily selected from general software developed by information technology developers, which is challenging to meet the precise professional needs of spinning enterprises. The core equipment and industrial software in the field of textiles have not yet formed the technical support capacity, from the true meaning of "intelligent" still has a large gap. The intelligent textile ecology of the whole industrial chain needs to be established. Developing a new generation of intelligent textile manufacturing systems should be based on the study of intelligent textile process, intelligent textile equipment as the focus of development, and intelligent equipment collaboration as the core. At the same time, through the construction of a textile innovative factory demonstration production model, the development of critical technologies of the textile industry Internet, the construction of a blockchain-based networked collaborative rapid response service system, the creation of the whole industry chain collaborative textile intelligent ecology, improve the rapid response service capacity, to achieve the development of the textile industry multi-cluster synergy.

Significance Silica aerogel is known as a super thermal insulation material due to its low density, high porosity, low thermal conductivity and strong design. It can be made into powder, microspheres, films and other forms of materials. These excellent properties make it widely used in heat insulation, adsorption, electromagnetic shielding, photocatalysis and other fields. The traditional silica aerogel preparation process is mature, but its network skeleton is slender and fragile offering poor mechanical properties, which seriously limits its applications. The research methods and the strategy for achieving flexible enhancement of silica aerogels are systematically reviewed, including the preparation process and material properties of different silica aerogels, aiming to establish thorough understanding of the design, preparation and applications of flexible aerogel materials for future development.

Progress Silica aerogels prepared by simple hydrophobic modification have slender skeleton and poor mechanical properties, which limits the allocation. At present, the flexible enhancement strategy is mainly divided into two aspects, i.e. component enhancement and process optimization. The technologies for organic group enhancement, polymer crosslinking and fiber enhancement are relatively mature. The simple blending of silicon sources containing organic groups can effectively increase the macromolecular chain segments and improve the compressive strength and elasticity of the material. When polymer crosslinking is used, the mechanical properties of aerogels are improved by introducing organic groups on the hydroxyl groups of silica aerogels and coating organic layers on the outer layer of the slender silicon skeleton. The active groups of different polymers can give different structures and properties of silica aerogels. When the fiber is used as the reinforcing phase, a more stable three-dimensional network can be formed by physical entanglement to improve the flexibility and structural stability of the aerogel composite. In terms of process optimization, two new processes of bionic drying technology and 3D printing technology are mainly introduced. Through detailed analysis of the problems existing in the flexible enhancement research, it is proposed that the component enhancement should be carried out by properly selecting the silane precursor and compounding it with organic polymer or fiber to construct a flexible network skeleton to create the regulation of chemical structure and network skeleton. In terms of process optimization, bionic drying technology has greater comprehensive advantages than atmospheric pressure drying. 3D printing technology can prepare a variety of geometric shapes of materials, which has potential application value for thermal insulation materials and medical fields.

Conclusion and Prospect The preparation of flexible aerogel composites with light heat insulation and good mechanical properties is the future development direction. In terms of component enhancement, the preparation process of organic group enhancement method is relatively simple and easy to achieve results, but the space for improvement is still limited because of the singular inorganic skeleton structure. The introduction of different polymers in the precursor solution can give aerogels different properties, and the study of the crosslinking mechanism is conducive to optimizing the enhancement process. It is feasible to use fibers with different characteristics as reinforcing phases. Different preparation processes can obtain aerogel fiber composites with different molding effects, which solves the problem of direct application of silicon-based aerogels. In terms of process optimization, exploring new bionic drying technology provides a new idea for the optimization of aerogel preparation process. It is worth noting that the new 3D printing technology can meet the design requirements of special material components. Finally, the breakthrough of ambient pressure drying technology, the development of polymer crosslinking or nanofiber reinforced preparation of flexible composite aerogels with orderly and controllable structure are prospected.

Significance Computer-aided cotton blending integrates advanced intelligent technology and traditional manufacturing, which is an important foothold of intelligent transformation of textile industry. The "Fourteenth Five-Year Plan" for developing the textile industry and demand for intelligent textile manufacturing call for comprehensively accelerating the industry's digital transformation, optimizing the production process, improving production efficiency, and achieving lean manufacturing. The textile industry's intelligent infrastructure has received a lot of attention during the "Thirteenth Five-Year Plan" period. Many technically advanced raw cotton information platforms and production information systems have emerged, gathering a sizable amount of raw cotton sales and public inspection data on the supply side of the raw cotton, and forming an internal enterprise including procurement, inventory, process, scheduling, products, sales and other dimensions of Standardized production data, constituting a sizable set of "supply and production" big-data system. For the intellectual development of China's cotton spinning firms, it is now imperative to find a way to maximize the value of supply and production data and to investigate intelligent management technologies that can significantly boost production efficiency and process level.

Progress The system framework of computer-aided cotton blending is introduced, and its development and application are summarized and analyzed around technical modules and technical connotations, in order to explore the future development of computer-aided cotton blending technology and promote the improvement of advanced management level and production efficiency of cotton spinning enterprises. The current research on intelligent raw cotton management aims to solve the optimization of raw cotton usage, which mainly includes the yarn quality prediction model and the cotton blending optimization model. (1) The yarn quality prediction model methods use supervised machine learning models such as multiple linear regression, support vector machines, artificial neural networks, and other improved models. In terms of model training approaches, evolutionary optimization algorithms have gained considerable attention in addition to the conventional analytical solution method and gradient descent method. (2) The cotton blending optimization model prioritizes cotton cost and yarn quality and creates a multi-objective optimization model based on inventory, total cotton consumption, cotton type, and cotton similarity. (3) To meet the needs of cotton spinning businesses for yarn quality management, a set of cotton blending technology management decision support system will be created in practical applications, integrating four functional modules of raw cotton inventory database maintenance, yarn quality prediction and management, cotton blending program formulation, cotton blending and yarn quality files, and a human-computer interactive interface.

Conclusion and Prospect After analyzing the two key components of the computer-aided cotton blending process, namely yarn quality prediction and the core technology utilized in the design of the cotton blending scheme, a number of difficulties with the current research are proposed: (1) The current study yarn quality prediction model lacks useful characteristics to characterize the performance distribution data of raw cotton in the cotton blending scheme and cannot adapt to the cotton blending scheme with length variation. (2) The current cotton blending optimization model optimizes the formulation of each cotton blending scheme as a single task and only for the production of a single variety (or a single production line), ignoring the fact that cotton blending is a time series task for multiple varieties on the multi-production line. Methods to improve the efficiency, precision, and generalizability of models must be investigated from the viewpoints of feature expression, model structure, and optimization technique. Also, the processing efficiency of large data and the universality of production mode must be enhanced. On the one hand, the computer-aided cotton blending system continues to progress the standardization and expansion of raw cotton quality inspection, while focusing on the in-depth application of big data for raw cotton. On the other hand, it will likely accelerate the intelligent transformation and upgrading of the textile sector. As big data and artificial intelligence technologies continue to improve, it is expected that the computer-aided cotton blending system study will make major strides in integrating cloud market data and adapting to the personalized production mode of future businesses.

Significance Cooling clothing incorporated with phase change materials (PCMs) can provide thermal protection to the human body in extreme hot environments. Due to the capability of PCMs absorbing or releasing heat through phase change, heat transfer process of PCM clothing calls for comprehensive understanding. The poor moisture permeability and low surface temperature of the PCMs would not only impede water vapor transmission to the environment, but also increase the risk of moisture condensation, which makes the construction of heat and moisture transfer model of PCM clothing more complicated than that of ordinary clothing. Based on the analysis of the heat and moisture transfer mode and path in PCM clothing, the development process, characteristics and deficiencies of current heat and moisture transfer model were reviewed in this paper. The application status of heat and moisture transfer model in the development and performance optimization of PCM clothing was also discussed.

Progress At present, the development process of the model construction of PCM clothing was mainly divided into three stages (Tab. 1). In the first stage, the heat transfer model of the fabric-PCM was established with the enthalpy method. However, it was different from the actual heat transfer process because it neglected the effect of moisture transfer on energy conversion. In the second stage, the coupled heat and moisture transfer model of the fabric-PCM was established with the apparent heat capacity method, which considered the phase change during moisture transfer and its influence on energy conversion. In the third stage, the more complex coupled heat and moisture transfer model was established by using some optimized methods. For example, adding the solid desiccant layer onto the inner surface of PCMs to maintain dry cool microclimate air, placing the insulation layer onto the outer surface of PCMs to reduce the heat absorption from the hot environment, and adding the ventilation fan to enhance sweat evaporation. In addition, the established model was used for parametric study to provide suggestions for the development and performance optimization of PCM clothing. In the selection of PCMs, it was proposed to adjust the melting temperature, weight and distribution of PCMs according to the ambient temperature, working time and human physiological characteristics. When designing the working mode of ventilation fans, it was necessary to set the running time point of ventilation fans according to the human activity level or sweat production.

Conclusion and Prospect Although the model construction of PCM clothing has been developed from the heat transfer model to the coupled heat and moisture transfer model, problems exist. Firstly, existing models simplifies the air ventilation by fans as the air exchange between the clothing microclimate layer and the environment, and the air velocity and air layer thickness of each segment are regarded as uniformly distributed, so the influence of air ventilation on heat transfer is ignored. Then, due to the complexity of the radiative heat transfer process, existing models ignore or simplify the radiative heat transfer among human body, PCM clothing and environment. Besides, existing models regard the fabric as a porous medium with uniform thickness, and do not consider the influence of microcosmic factors such as fiber hygroscopic characteristics, yarn structure and the mixing ratio of each component in the cavities of the inner fabric layer on the thermal and humidity properties of PCM clothing. The future development trend is put forward as the multi-factor coupling of heat and moisture transfer, the dynamic simulation of air ventilation by fans, and the model construction changes from one dimension to multi-dimension and from macroscopic to microscopic.