Table of Content

10 February 2025, Volume 33 Issue 02

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Research progress of spreading technology for large tow carbon fibers

ZHU Fanqiang, SHEN Wei, YANG Xiaobing, YAO Jiangweia, ZHAO Defanga, ZHANG Wanhu, ZOU Zhuanyong

2025, 33(02):  1-9. 

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Carbon fiber-reinforced composites have a series of advantages such as light weight, high strength and high modulus, corrosion resistance, strong designability, and easy integral molding, and are widely used in automobile manufacturing, aerospace, sports, energy, wind turbine blades, and so on. In the entire carbon fiber production chain, the cost of raw silk required for the production of small tow carbon fiber is more than four times the cost of raw silk required for the production of large tow carbon fiber, which somewhat restricts the wide application of carbon fibers. In order to expand the application of carbon fibers, large tow carbon fibers with lower cost can be chosen. In the application of large tow carbon fibers, it is necessary to spread the fibers to improve the wettability of the resin to the carbon fiber tows.
The exploration of spreading fiber technology began in the 1970s, but the initial research on this technology was still relatively simple and slowly evolved into a diversified development trend by the end of the 1990s. Entering the 21st century, the carbon fiber production technology has gradually improved, and the spreading technology for tow carbon fibers tends to be increasingly mature. Fiber spreading technology helps large tow carbon fibers maximize the advantages of small tow carbon fibers, fully exerts the reinforcing effect of large-tow carbon fibers, and achieves high efficiency and low cost in the preparation of composite materials. Thus, the spreading technology of large tow carbon fibers is crucial in the preparation and application of composite materials reinforced by carbon fibers.
The spreadability of carbon fiber tows can be measured by the change in width of carbon fiber tow before and after spreading. The spreading effect affects the morphology of carbon fiber tow, permeability and structural properties of composites. The commonly used fiber spreading technologies for large tow carbon fibers mainly includes the following six types: multi-roller thermal rolling spreading method, mechanical multi-roller spreading method, acoustic wave-assisted spreading method, electrostatic-assisted spreading method, microbump array-assisted spreading method and air flow disturbance spreading method.
Various fiber spreading methods can delaminate large tow carbon fibers into thin layers, and obtain thin-layer carbon fiber bundles with small deviations in physical properties and excellent mechanical properties, making the preparation of composite materials more efficient and cost-effective, and expanding the application fields of carbon fibers. However, different fiber spreading methods have their own advantages and disadvantages. Among them, air flow disturbance spreading technology is the most cost-effective and promising one. In order to reduce the fiber damage caused by fiber spreading and increase the effect of fiber bundle widening, the spreading methods should be diversified. In practical applications, a combination of fiber spreading technologies with less fiber damage should be considered. Furthermore, new-type fiber spreading devices with refined functions and a complete range of types should be designed to promote the continuous iterative development of fiber spreading technology.


Research progress on the application of melt spinning profiled fibers and nonwoven materials

WU Wanhua, QIAN Xiaoming, TANG Xiaoyan, LOU Wei, YANG Xueke, LAN Yina

2025, 33(02):  10-22. 

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To improve the problems of product homogenization, low added value and performance homogenization in the fiber market, it is imperative to conduct relevant research on fiber profilization technology. Melt spinning, an efficient and environmentally friendly fiber production technique, proves suitable for industrial-scale manufacturing of profiled fibers. The melt spinning process's fiber profilization technology is comprehensively analyzed from various perspectives. Firstly, we provide a detailed introduction to the principles of melt spinning and specialized equipment used for producing profiled fibers while emphasizing the pivotal role played by profile spinnerets in the production process. Subsequently, we present an overview of profiled fibers along with enumerating their cross-sectional shapes and characteristic features. Additionally, we describe the fiber profiled technology in detail, focusing on the profiled spinneret method, the bulking and sticking method, the composite fiber processing technology and the micro-nano stacking technology. Furthermore, we present an overview of the recent status and research findings pertaining to these technologies.
After the implementation of fiber profiling technology, profiled fibers exhibit distinctive characteristics, rendering them suitable for diverse applications. For instance, in the field of moisture-absorbing and quick-drying materials, Yang et al. developed a moisture-absorbing and quick-drying fabric using polylactic acid as a raw material by using profile spinnerets, and the special-shaped  fibers effectively enhanced the hygroscopic properties of the fabric. In terms of thermal materials, Jia et al. combined polyethylene hollow fibers with polyacrylonitrile nanofibers through electrospinning technology to construct a stable porous structure that exhibits exceptional thermal insulation properties. Furthermore, in the domains of air filtration, oil-water separation, and sound absorption materials, the intricate three-dimensional structure, large specific surface area, good adsorption properties and high porosity inherent in nonwoven materials enable further optimization by incorporating the characteristics of profiled fibers. For example, Zheng et al. employed a combination of spunbond mesh process and thermal phase separation to prepare C-shaped polypropylene spunbond nonwoven material featuring submicron holes, and this material demonstrated excellent reusability performance in oil-water separation.
Finally, the development of profiled fibers is prospected. According to the current situation of fiber special-shaped technology, we put forward four research directions. Firstly, it is necessary to expand the application fields of fiber special-shaped technology in combination with nonwoven mesh technology to promote its further development. Secondly, in the future technology development and industrialization trend, it is an important direction to combine and innovate fiber special-shaped technology with nonwoven fixed network technology. Thirdly, it is necessary to research and develop  green polymer slicing to promote the environmental development of fiber raw materials. Finally, profiled fibers are applied in the field of nonwoven wipes, and product performance is optimized to improve competitiveness. By continuously promoting the development of fiber special-shaped technology, more innovation and development opportunities can be brought to various industries.


Analysis of innovation capabilities and development trends of key generic technologies in China's textile industry

WANG Pengfei, CHENG Hua

2025, 33(02):  23-32. 

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Under the requirements of upgrading, reconstruction and high-quality development, China's textile industry is confronted with fierce competition and transformation pressure. Based on the data of 38,295 invention patent applications, this paper takes the key generic technologies of China's textile industry as the research object, analyzes their innovation capability, development trend and technology life cycle by using patent measurement, patent index analysis and Logistic model. The results show that the key generic technologies of China's textile industry are closely related to the technical classifications of D01F, D06M, D01D, D04H, D06P and C08G, involving major categories like mechanical engineering, chemistry, physics and electronic circuits. Among them, technological breakthroughs in new textile materials, such as carbon fiber and aramid fiber, have become an important engine for the high-quality development of the chemical fiber industry and the textile industry. However, the life cycle of key generic technologies in the textile industry has entered a mature stage, and it is expected that the patent growth will have a recession after 2028. After China proposed to transform from a "major textile country" to a "powerful textile country" , green, flexible, intelligent and refined production has become the main trend in the development of key common technologies in the textile industry, and it is also a crucial force to improve technological innovation in the textile industry and promote its transformation and upgrading.
Under the influence of the concept of sustainable development and the "Made in China 2025" policy, it is extremely important to optimize the technology innovation ecology and realize the systematic improvement of innovation capabilities of the key generic technologies in the textile industry. And the rapid growth of key common technologies such as mechanical methods of chemical fibers, dyeing or printing of textiles, polymer compounds, vapor-phase or steam treatment of textiles and knitting has become a key force to promote the rapid development of domestic textile industry. At the same time, a number of patents with prominent new technological features, such as the chemical characteristics of artificial filament fibers or carbon fiber equipment, as well as the biochemical treatment of fiber products, have played a positive role in promoting the green development of the textile industry.
This paper is helpful to sort out the meaning and concept of key common technologies in the textile industry, as well as to analyze the subject of patent application, the capability of technological innovation and each stage of the technology life cycle. Under the guidance of the innovation-driven development strategy proposed by the Chinese government, the development of science and technology in the textile industry has achieved remarkable results, the innovation ability has been steadily improved, and the key common technologies have received extensive attention from enterprises, academia and local governments. Although the existing research objects involve a number of emerging industries and technologies, there is no research on the integration of key common technologies in the textile industry, including new textile fiber materials, advanced textile products, green manufacturing, intelligent manufacturing and advanced equipment. Therefore, this study attempts to supplement the existing research in terms of research object and research content, so as to potentially fill the gap in current research.


Preparation and photothermal conversion properties of MoS2/AgNPs@ANFs composite aerogels

ZHANG Gongyu, SUN Kai, LIU Yuanjun, XIA Lei, ZHUANG Xupin

2025, 33(02):  33-41. 

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With the global shortage of water resources and the increasingly severe energy crisis, solar interface evaporation technology, as an innovative solution, is gradually becoming a research hotspot. The solar interface evaporation system must have three key elements: efficient photothermal conversion materials, excellent hydrophilicity and reasonable thermal management structure design. First of all, efficient photothermal conversion materials are the basis. They must be able to effectively absorb sunlight and convert it into heat energy. Ideal materials such as graphene, carbon nanotubes, metal nanoparticles and polymer composites should have high light absorption, good thermal stability and long-term durability. Secondly, the design of hydrophilic surface is crucial to accelerate the transmission of water to the evaporation surface, which can be achieved by introducing hydrophilic groups or constructing micro nano structures on the material surface. Finally, the reasonable thermal management structure design ensures that the absorbed heat is mainly concentrated on the evaporation surface, rather than lost to the environment. By using thermal insulation materials or building multi-layer structures, such as isolating the photothermal conversion layer from the water body, the heat can be effectively locked at the evaporation interface, so as to improve the evaporation efficiency. 
The complex structural design of the solar evaporation system limits its large-scale production and cost-effectiveness. The large specific surface area, high porosity, extremely low thermal conductivity and excellent hydrophilicity of the aramid nanofiber aerogel meet the requirements for the preparation of an integrated solar evaporation system. In this paper, the ice template method was used to construct MoS2/AgNPs@ANFs composite aerogels with porous cellular skeleton structure. The nano porous structure increases the refraction path of the optical path, enhances the light scattering, and improves the light absorption ability. The absorbance in the visible region reaches 93.58%; the cellular structure improves the capillary effect, effectively improves the water transmission capacity, and provides a path for water vapor transmission; the density of multi-stage porous aerogels is as low as 10 mg/cm3, and the aerogels have the ability of self-floating and provide the basis for rapid evaporation rate; the porous cellular skeletal structure limits the heat convection and heat conduction, resulting in an extremely low thermal conductivity, which is conducive to the heat management of interface evaporation; MoS2/ AgNPs@ANFs composite aerogels are hydrophilic. Under the irradiation of five times of sunlight, the surface temperature rises to 74.66 ℃, and the maximum evaporation rate of water vapor is 11.7 kg/(m2·h). The evaporation rate remains stable in six cycles, which provides a data basis for the structural design of solar interface water evaporator.
Solar evaporation technology, with its characteristics of high efficiency, low cost and environmental protection, provides a sustainable solution for the global water shortage and energy crisis. With the continuous progress and innovation of technology, solar evaporation technology will play a more important role in the field of water purification and energy conversion in the future.


Mechanism of microbial degradation of silk fibroin based on proteomics

DING Chuanmiao, PAN Lindan, CHEN Hao, WANG Bing

2025, 33(02):  42-48. 

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Silk cultural relics, with their historical, cultural, and artistic value, offer invaluable insights into ancient civilizations. However, like all natural materials, silk is highly susceptible to physical, chemical and biological factors, losing its original value. Therefore, the preservation and restoration of silk cultural relics have always been the focus of cultural relic protection, and in-depth research on the microbial degradation process of silk fibers is of great importance to formulate effective strategies for the protection. The complex multi-level structure of silk fibroin leads to its complicated degradation mechanism, changes in each level of structure may lead to the degradation of silk. And the changeable environment also brings difficulties to the research of aging and degradation of silk cultural relics. The scarcity and non-renewability of silk cultural relics are also major challenges for cultural relics conservationists. To overcome these difficulties, the artificial simulation aging method can be used to study the aging and degradation behavior of silk fibroin.
To reveal the microbial degradation mechanism of silk, this paper investigated the macroscopic and microscopic structural changes of silk before and after degradation of Aspergillus oryzae metabolites using proteomics combined with thermal field emission scanning electron microscopy and XRD techniques. The results of morphological analysis showed that the color of silk changed significantly after aging, and a large number of fibres's shedding and axial cracks appeared on the surface of silk fibres. The results of secondary structure analysis showed that the molecular conformation of silk proteins was damaged, and the degree of crystallinity was significantly decreased. The proteomics results showed that both the number of polypeptides and the total abundance of proteins in silk fibroin decreased significantly, indicating that silk fibroin can be degraded by metabolites, and the abundance of heavy chains constituting the crystalline region of silk fibroin decreased the fastest.
A model of deterioration of silk fibroin by Aspergillus oryzae is postulated: Aspergillus oryzae focuses on the decomposition of fibroin heavy chain through degradation, and the structure of the crystalline region of the silk fibroin collapses into a loose amorphous structure, and the silk loses its original physicochemical properties, and is eventually completely degraded and destroyed. This study is of great significance for the in-depth understanding of the deterioration mechanism of ancient silk and provides an important basis for the targeted protection and restoration strategies for silk cultural relics.


Mesoscopic scale finite element analysis of crack propagation characteristics of carbon fiber fabric composites

WANG Sixin, YAN Yongjie, NI Qingqing

2025, 33(02):  49-58. 

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With the increasing demand for high-performance composites, textile composites have been widely used in aerospace, rail transportation, automotive, and other fields due to their excellent in-plane and interlaminar properties and directional designability. However, with the integrated design and application of textile composites, it is crucial to further elucidate the mechanical properties and crack propagation resistance of textile composites at the micro and mesoscopic scales to further advance the application of this material.
Based on the above background, predicting the failure behaviour of composites is important for the structural design of composites. The paper explored the influence law of fabric structure on the mechanical properties of composites, especially to explore the crack propagation resistance mechanism,  established a unilateral crack composite model with different carbon fiber structures at mesoscopic scale using finite element analysis, and elucidated the characteristics and mechanisms of different carbon fiber structures in composites that contribute to its resistance against crack propagation through experimental verification with graphical deformation processing. The results show that the crack propagation energy density of the plain weave structure is 1.69 J/mm3, and that of the 0°/90° ply composites is 1.47 J/mm3, indicating a 15% increase in crack propagation resistance compared to the 0°/90° ply composites. The impact of unilateral cracking on the stress concentration behavior in textile composites was quantitatively assessed. The fracture strengths of the phenoxy resin board, 0°laminated composite, 0°/90° ply structure, and plain weave structure were found to be 31.1 MPa, 32.1 MPa, 249.5 MPa, and 346.1 MPa, respectively, with corresponding stress concentration coefficients of 2.6, 2.5, 12.1, and 7.6. Comparison of the finite element analysis with experimental results from non-contact full-field strain measurements further verifies the alignment between simulated and experimental trends in crack propagation. During crack propagation, the weft yarns in the plain weave composites experience a stress of approximately 700 MPa, whereas those in the 0°/90° ply composites endure a stress of roughly 150 MPa, indicating that the plain weave structure bears 4.67 times the load of the 0°/90° ply structure, and the plain structure with the undulating interlacing of the warp and weft yarns has an even better ability to resist the propagation of the cracks. At the same time, the stress distribution carried by the warp and weft yarns and the load transfer mechanism at the intersection of the warp and weft yarns were clarified, revealing that the one-piece fabric structure exhibits superior resistance to crack propagation.
Thus, the composite material model with fiber arrangement established in this paper predicts the crack propagation behavior of textile composites more accurately, and elaborates that the warp and weft yarn crossing structure has a good crack propagation resistance, and thus may provide a method and reference for the structural optimization design of textile composites.


Preparation of recycled DMT by K2CO3 catalytic glycolysis-transesterification and its purification by decompression sublimation method

LI Xiaojun, GUAN Jun, LÜ Weiyang , , YAO Yuyuan ,

2025, 33(02):  59-66. 

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Polyester fibers are widely used in textiles and apparel, automotive interiors, civil engineering and other fields because of their excellent mechanical properties, chemical stability and processability. As the application fields of polyester fibers continue to expand and production capacity continues to increase, the cumulative amount of waste polyester textiles is also growing steadily. A large amount of waste polyester textiles are landfilled or incinerated, causing serious waste of resources and environmental pollution. The glycolysis method, which can depolymerize waste polyester into bis(hydroxyethyl) terephthalate (BHET), has mild reaction conditions, good safety and high product yield, but its traditional depolymerization catalysts are based on heavy metal salts such as zinc, manganese, cobalt, antimony and other heavy metal salts. Although their catalytic effects are significant, they can easily cause heavy metal pollution.
Furthermore, waste polyester textiles come from a wide range of sources and often contain impurities such as cotton, oil stains and dyes. Moreover, the product BHET is prone to polycondensation under high temperature conditions, makeing it extremely difficult to remove impurities and decolorize, thus limiting this method to the treatment of pure bottle flakes and films and hindering its application in the recycling of waste polyester textiles. Utilizing the inherent advantages of the depolymerization system of the glycolysis method, the waste polyester is depolymerized to produce glycolysis products, which can then be esterified with methanol to produce dimethyl terephthalate (DMT), one of the most promising process routes at present. However, the traditional strong alkaline transesterification catalyst NaOH is easy to cause equipment corrosion, and the conventional recrystallization method of purification is time-consuming and energy-intensive, and consumes a large amount of methanol consumption. In this way, the quality of DMT is difficult to reach high purity grade.
Based on the above, glycolysis products of waste polyester textiles were prepared by using K2CO3 as catalyst, and then K2CO3 was used as catalyst for methanol transesterification to transform the glycolysis products into recycled DMT. The recycled DMT containing impurities was purified by decompression sublimation method, and the specific components of the glycolysis products and transesterification products were analyzed in depth. The results indicated that the main component of the glycolysis product was BHET, with trace amounts of BHET oligomer and monohydroxyethyl terephthalate. After optimization, the optimal reaction parameters of the transesterification process were as follows: the reaction temperature was 70 ℃, the reaction time was 118 min, the mass ratio of methanol to the glycolysis products was 2.13:1, and the addition ratio of K2CO3 was 0.94% of the mass of the glycolysis products, the actual yield of recycled DMT under this condition was 88.50%. After three times of purification by decompression sublimation method, impurities such as 2-hydroxyethyl methyl terephthalate, monomethyl terephthalate and dimethyl isophthalate were effectively removed from recycled DMT, and the purity of recycled DMT was as high as 99.89%. The results provide useful reference for the selection of catalysts, the regulation of transesterification reaction parameters and the purification of products in the recovery of waste polyester textiles based on the glycolysis-transesterification method.


Three-proof finishing process and performance of cotton fabrics based on foam finishing technology

ZHAO Yanan, GE Tiantian, ZhANG Yan, ZHU Bo, ZHANG Ning, PAN Ruru

2025, 33(02):  67-74. 

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In recent years, with the advancement of science and technology and the rise of environmental awareness, three-proof functional finishing, green dyeing and finishing, energy  conservation and emission reduction of cotton fabrics have become the focus of the textile industry. Traditional finishing methods of cotton fabrics are difficult to meet the demand for fabric multifunctionality in modern society, while three-proof finishing can effectively solve this problem. Therefore, three-proof foam finishing of cotton fabrics has become one of the important methods of functional finishing of textile materials. This technology can not only prevent moisture penetration, but also resist oil and stains, meeting the modern demand for fabric composite multifunctional finishing. In the actual production process, foam finishing technology achieves green production with water conservation and energy consumption reduction by adjusting the force of foam application and changing the solution carrying rate of fabrics. However, traditional three-proof finishing agents such as C8-type contain toxic substances like perfluorooctanoic acid ammonium (PFOA) and perfluorooctane sulfonyl compounds (PFOS), which pose a potential threat to the environment and human health. C6 three-proof finishing agents become a greener option because of their lower bioaccumulation and environmental damage. Experiments have shown that C6 three-proof finishing agents can improve the waterproof, oil-proof and stain-proof performance of cotton fabrics while reducing energy consumption and realizing green production.
In this paper, the foam finishing technology was used and the C6 three-proof finishing agent was selected to conduct three-proof finishing on pure cotton fabrics, and the optimal finishing process was determined by testing the apparent morphology, waterproof, oil-proof and stain-proof properties of the finished fabrics. The experimental results showed that the optimal process parameters were as follows: the mass concentration of the finishing agent was 60g/L, the liquid carrying rate was 50%, the baking temperature was 130 ℃, and the baking time was 2.5 minutes; the cotton fabric after the three-proof foam finishing had a water contact angle of 155.3°, an oil contact angle of 130.3°, and achieved a staining grade of 5. It was found by comparing the traditional padding method and the foam finishing method that the foam-finished cotton fabric had better water-phase and oil-phase contact angles, higher breaking strength and breaking elongation, longer breaking time, fuller and softer handfeel and good drape, as well as smaller difference in washing resistance; in terms of the uniformity of finishing, the average variance of the water-phase contact angle of the three-proof foam-finished cotton fabrics was 1.7, that of the oil-phase contact angle was 2.7, and that of the staining grade was 0.04, all of which were smaller than those of the traditional padding method, which were 1.9 for the water contact angle, 3.6 for the oil contact angle, and 0.16 for the stain grade. This is because the higher liquid carrying rate of the conventional padding method is more prone to migrating, resulting in uneven finishing on the fabric surface. Therefore, the cotton fabric finished with the three-proof foam has better finishing uniformity. 
This kind of high energy-saving, low liquid-supply finishing greatly reduces the use of chemicals, decreases environmental pollution and production costs, provides an effective way for the green and sustainable development of functional pure cotton fabrics, and has a broad application prospect. It is hoped that this finishing process can be more widely promoted and applied, and make greater contributions to the sustainable development of the textile industry.


 Error analysis and calibration of a resistance sizing moisture regain tester

WEI Yao, WANG Wencong, WANG Jing'an, GUO Mingrui, GAO Weidong,

2025, 33(02):  75-82. 

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The sizing moisture regain rate is one of the three major indicators of sizing performance. It is the ratio of the weight of moisture in the sized yarn to the dry weight of the sized yarn, expressed as a percentage, reflecting the drying level of the sized yarn. The drying level of sized yarn is not only related to the energy consumption of sizing, but also affects the properties (elasticity, softness, strength, re-viscosity, etc.) of the sizing film, thus affecting the mechanical properties of the sized yarn. To realize the accurate control of sizing moisture regain, modern sizing machines are mostly equipped with a resistance type moisture regain tester to monitor sizing moisture regain online. However, current research mainly focuses on the relationship between yarn raw materials and sizing moisture regain. Other key factors in actual sizing production, such as yarn linear density, coverage coefficient, environmental temperature and humidity, size type and sizing rate, are rarely involved, resulting in some errors in the actual measurement of sizing moisture regain. 
To improve the testing accuracy of moisture regain, on the basis of the existing resistance method, the effects of yarn linear density, coverage coefficient and environmental relative humidity on moisture regain were studied. First of all, a set of sheet yarn moisture regain testing device was established in this paper based on the operation simulation of the sizing machine to realize the convenient adjustment of experimental parameters and the accurate collection of test data. Based on the relationship between yarn linear density, coverage coefficient, environmental relative humidity, test moisture regain and real moisture regain, a mechanism model was established, a deviation correction model between moisture regain and various influencing factors was established, and an objective function was established. The deviation correction model was used to improve the detection accuracy of sizing moisture regain. The levels of the three influencing factors were set at 4, 4, and 10, respectively, and a comprehensive experiment was carried out on all the combinations of the three parameters. The collected data were fitted by using the least squares method with the particle swarm optimization algorithm, and the model fitting coefficient was obtained. The goodness-of-fit R² value of the model was 0.8827, and the mean squared error (MSE) was 0.0273, which showed that the mathematical model established in this paper had a good ability to express the experimental data.
To validate the aforementioned mathematical model, another batch of samples were prepared and subjected to testing with the same four kinds of yarn linear density, 10 kinds of coverage coefficient and four kinds of environmental relative humidity. The different yarn linear density t, coverage coefficient f, environmental relative humidity h and test moisture regain value W were input into the model to obtain the corrected test moisture regain W' after correction. The average absolute error (MAE) between the uncorrected test moisture regain W and the true moisture regain W1 was 0.3086, while the MAE between the true moisture regain W1 and the corrected test moisture regain W' using the model constructed in this paper was 0.2321, and the error was reduced by 24.8%. Therefore, it can be concluded that the correction effect of the mathematical model constructed in this paper is satisfactory, and the testing accuracy of moisture regain is effectively improved.


Effect and evaluation of UV-resistant finishing of cool-feeling aluminum nitride polyester fabrics

QIU Jiangen, XU Yalan, ZHANG Chen, HONG Xinghua

2025, 33(02):  83-89. 

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In the context of global warming, the heat of summer and the intense ultraviolet radiation have become a problem that cannot be ignored in people's Daily life. It has become particularly important for textiles to meet people's needs for coolness, comfort, protection against UV burning and tanning. Therefore, the research and development of textiles with these functions has become an important topic in the textile industry. In response to this demand, we have deeply studied the processing methods of cool textiles and UV-resistant textiles. First of all, we focus on reducing the thermal resistance of textiles, improving the thermal conductivity, so that the heat generated by the human body can be quickly released and discharged, the stuffy feeling of the human body can be overcome and the comfort of wearing can be improved. To this end, we modified the fiber raw materials with aluminum nitride and spun it successfully to make cool-feeling polyester fabrics.
At present, the commonly used ultraviolet finishing agents in the domestic market are mainly organic ultraviolet absorbers based on benzophenone and benzotriazole compounds, and they are suitable for anti-ultraviolet finishing of all kinds of clothing fabrics, giving clothing fabrics excellent anti-ultraviolet properties. Inorganic substances have refractivity and optical activity to incident light, and ultraviolet scatters mainly utilize this feature to reflect and scatter ultraviolet light to varying degrees. These substances are metals, metal oxides and their salts, such as titanium dioxide, silicon dioxide, iron oxide and carbon black. Nanoscale UV scattering particles, which can also absorb ultraviolet rays and have stronger blocking ability against ultraviolet rays, have become an important material for the development of anti-ultraviolet finishing agents.
Considering the particularity of AlN cool-feeling modified polyester fabrics, we adopted an innovative method to prepare a UV protective finishing agent TQ-100 by combining nano inorganic dispersion with organic UV absorbent. We used one dip and one roll finishing method to treat the cool polyester fabric with UV protection, and compared it with common UV protection finishing agents sold in the market. Through testing, comparison and analysis of the surface morphology, thermal conductivity, washable resistance, air permeability and UV light resistance of the cool-feeling polyester fabrics before and after finishing, we have drawn the following conclusions: the TQ-100 finishing agent can significantly improve the cool-feeling effect of the polyester fabric, and has good durability and UV light resistance. At the same time, the finishing agent has little effect on the air permeability of the fabric under proper usage amount. The results show that it is a more reasonable method to finish AlN cool polyester fabric with agent combined inorganic nanomaterials with mechanical UV-resistant materials. This not only meets people's needs for coolness and UV protection, but also ensures the fabric's air permeability and durability. We believe that this research result will have great guiding significance for the UV and suntan protection finishing of cool textiles in summer.


Exploring intelligent spinning applications from the perspective of digital twins

CHEN Mingliang, , ZHANG Junhui, QIAN Yuhan, LIU Yuxi, LIU Junze,

2025, 33(02):  90-99. 

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Intelligent spinning, as a key path for the modernization and automation evolution of the textile industry, aims to improve the efficiency, quality, and flexibility of the spinning process by integrating advanced automation technology, information technology, and intelligent control systems. Its development has undergone multiple critical stages from mechanical automation to intelligent control. Initially, innovations in devices such as ring spinning machines and air-jet spinning machines achieved operational automation, significantly boosting production efficiency. Subsequently, the introduction of computer control technology marked the phase of semi-automation and localized intelligence. Entering the stage of intelligent control, the application of information technology, sensor technology, and artificial intelligence enabled real-time monitoring, data analysis, and automatic optimization of the spinning process, driving the industry towards high efficiency, stability, and intelligence.
Digital twin technology has become a revolutionary concept since it was first introduced by Michael Grieves in his Product Lifecycle Management (PLM) course in 2002. The core of this technology lies in building a virtual model of physical entities to achieve real-time monitoring, simulation, and optimization of physical entities. With the advent of Industry 4.0, digital twin technology has been widely applied in various industries, including energy, healthcare, urban management, etc. Its application scenarios have expanded from a single device to the entire production line and even the entire supply chain. The combination of data analysis and artificial intelligence technology enables digital twin systems to perform more complex simulations and predictions.
In the context of the development of intelligent spinning, the introduction of digital twin technology has brought new opportunities and transformations. This paper explores the implementation strategies of digital twin technology in intelligent spinning, including the architecture and core technical components of the digital twin system in spinning factories. Specifically, it delineates the components of geometric, logical, and decision models in multi-dimensional modeling, along with specific modeling steps. In terms of equipment fault prediction and health management, the paper emphasizes the advantages of integrating digital twin technology with Prognostics and Health Management (PHM) systems, and analyzes methods for achieving consistency between virtual and real data and iterative optimization of models. Furthermore, the integration of Augmented Reality (AR) visualization management systems with digital twin technology creates advanced data presentation methods, detailing the implementation of key technologies such as tracking registration, virtual-real fusion, and human-machine interaction in AR systems.
The deep integration of digital twin technology and spinning will bring more efficient, intelligent, and sustainable production methods to the textile industry. In the future, the application of digital twin technology will focus on enhancing precise modeling, refining mechanistic models, improving the accuracy of predictive maintenance, and strengthening data interaction security, to continuously advance its implementation in the spinning field.


A single-spindle monitoring system and its application for intelligent spinning construction

ZHAO Longfei, LI Hui, ZHANG Yang, JIA Zhengqing, XUE Yuan

2025, 33(02):  100-106. 

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Traditional spinning enterprises rely on manual inspection of yarn breakage, which is inefficient and susceptible to human factors, making it difficult to meet the high quality and efficiency requirements of modern large-scale production, as well as the serious problem of yarn waste after yarn breakage. With the intensification of market competition and consumer expectations of product quality, spinning enterprises urgently need intelligent transformation and upgrading to cope with the increasingly complex market demand. To address the above problems, a single-spindle spinning monitoring system is established for the spinning of the smallest unit, and sensors are used to monitor the working conditions of each spindle, including twisting, drafting, and forming processes. On one hand, it provides visual alarms for perceived abnormalities, reducing the dependence on manual operations. On the other hand, it uploads all detected spindle condition information to a cloud server, forming a comprehensive spinning information database. This, in turn, supports the intelligent management of spinning workshop information through the integration of a spinning MES system.
The article focuses on the components and working mechanisms of a ring-spinning single-spindle monitoring system. It also examines the methods of signal acquisition and data processing through sensors on various operational components, including the steel wire ring, roller, spindle, and collar plate. By utilizing digital twins and data fusion techniques, the system extracts information characteristics of various abnormalities during the spinning process. This provides digital criteria for identifying abnormalities such as broken ends, weak twists, empty spindles, and uneven twists during the spinning process. On one hand, it informs the position of the blocker through headlamp alarms and provides the navigation service. On the other hand, it stops feeding the roving to reduce the waste of raw materials. Finally, the application effect of the single spindle monitoring system is analyzed, and the results show that the productivity of using the single spindle monitoring system is increased by 15%, resulting in a 22% reduction in the overall cost of labor and raw materials, and a 12% decrease in the annual defect rate of yarns. The single-spindle monitoring system collects data in the spinning production process and provides detailed production reports and visualization interfaces. This enables management to conduct real-time monitoring, make informed decisions, optimize production scheduling and resource allocation, automate spinning processes, ensure continuous production, facilitate networked information management and adopt intelligent spinning modes. 
In short, the single-spindle detection system not only addresses common issues in traditional spinning production, such as inefficiency and quality fluctuations but also provides solid technical support for the transformation of the textile industry to digitalization and intelligence, promoting the upgrading of the industry and innovation. As technology continues to advance, the future single-spindle detection system is poised to integrate additional functionalities, so as to further enhance the intelligence of the spinning process and generate even greater economic benefits and social value for the textile industry.


Research and implementation of an energy monitoring platform for spinning workshops#br#

JIANG Guoqiang, YUAN Yiping, CHAO Yongsheng

2025, 33(02):  107-117. 

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Against the backdrop of the accelerating global industrialization process and the increasingly scarce energy resources, the textile industry is undergoing a critical transformation phase. Driven by policy guidance and market competition, the textile industry is moving towards digitalization, intelligence and greening. However, many traditional spinning enterprises still rely on manual meter reading and analyzing and calculating energy consumption data. This method is not only inefficient but also prone to errors, making it difficult to accurately grasp workshop energy consumption and restricting the energy management capabilities and production efficiency of these enterprises.
To solve this problem, this paper proposes an energy monitoring platform for spinning workshops based on Internet of Things (IoT) and big data technology. The platform establishes an energy data IoT monitoring network through smart meters equipped with LoRa wireless transmission technology, which realizes the comprehensive and timely collection of energy data. Big data technologies, including HDFS, HBase, Spark and other components in the Hadoop ecosystem, are used to provide a multi-tiered storage and analysis architecture for energy consumption data, which ensures fast integration, efficient computation and flexible querying of data. A multi-step energy consumption prediction model based on variational modal decomposition (VMD), particle swarm optimization (PSO), and long-short-term memory neural network (LSTM) is proposed, and the power consumption data and relevant operational data of a spinning enterprise in Xinjiang were selected for verification is validated. The experimental results show that the model outperforms traditional algorithms such as BP, LSTM, PSO-LSTM, and VMD-LSTM in single-step, three-step, and six-step energy consumption prediction. Specifically, its single-step average prediction error is reduced by 74.50% compared to LSTM and 39.07% compared to VMD-LSTM, and the R² values for single-step, three-step, and six-step predictions are 0.9820, 0.9642, and 0.9151, respectively, demonstrating high prediction accuracy. Finally, based on the B/S architecture, this paper has developed a Web module, integrating functions such as real-time monitoring of energy consumption data, cluster management, and energy consumption prediction. Users can intuitively view energy consumption data, perform energy consumption predictions, and manage energy usage through a user-friendly interface.
In summary, the energy monitoring platform for spinning workshops proposed in this paper integrates the IoT technology, big data technology and software development technology, which provides a more intelligent solution for the energy management of traditional spinning enterprises, and a solid data basis for enterprise energy optimization decision-making, helping them to improve energy efficiency, reduce production costs, and enhance their competitiveness in the fierce market competition. It also serves as reference for the traditional textile industry's low-carbon emissions reduction, sustainable development, as well as digital and intelligent transformation.


A vortex spinning workshop scheduling method based on improved NSGAII algorithm

LUO Laibing , FANG Liaoliao, SHEN Chunya, SHI Luhong, HU Xudong

2025, 33(02):  118-129. 

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To cope with the challenge of gradually changing production of vortex spinning in the textile industry from the traditional single large-volume mode to the small-volume and multi-variety mode, a new scheduling method is proposed in this paper. The method is based on analyzing the order production of a vortex spinning enterprise in Jinhua, and by this method, the article constructs a multi-objective optimization model with the objectives of minimizing the maximum completion time, minimizing the overdue loss and minimizing the number of changeover times. The article also solves the model by the proposed INSGAII_SAA algorithm. The research focuses on improving the production scheduling efficiency to cope with diversified market demands and helping enterprises to reduce the comprehensive cost of production management.
In this paper, firstly, through the analysis of the vortex spinning production process, the vortex spinning scheduling optimization model under the small batch and multi-species mode is established. The model comprehensively considers several production constraints, such as equipment availability, the number of change machines, order priority, etc., to ensure the practical applicability of the model. On this basis, this paper proposes the INSGAII_SAA algorithm, which aims to improve the efficiency and effectiveness of the solution by avoiding the algorithm from falling into problems such as premature convergence. In terms of algorithm improvement, this paper mainly has three major innovations. Firstly, heuristic rules are used to initialize the population to reduce the redundancy of the initial solution space and improve the quality of the population. Secondly, the mechanism of adaptive selection of the cross-mutation operator is introduced. The traditional cross-mutation operation has a trade-off between local search and global search ability, while in this paper, by dynamically adjusting the selection probability of the cross-mutation operator, the algorithm is able to adaptively select the appropriate operator, which improves the algorithm's local and global search ability while guaranteeing the diversity of the population. Thirdly, this paper incorporates the simulated annealing algorithm (SAA) to locally search the individual with the largest crowding distance to further optimize the algorithm's solving ability and effectively avoid the solution set from falling into the local optimum. To verify the effectiveness of the improved algorithm, this paper selects the order data of a vortex spinning enterprise in Jinhua for experiments. The results show that the proposed INSGAII_SAA algorithm outperforms NSGAII in several performance indicators. INSGAII_SAA reduces the maximum completion time by about 8.7% on average, reduces the overdue loss by about 59.89% on average, and reduces the number of changeover times by about 34.91% on average compared to the original NSGAII.
The improved algorithm proposed in this paper shows good results in the experiments, but there are still some limitations. First of all, the production interruption problem that may be caused by factors such as insufficient supply of raw materials or equipment failure is not considered in the model construction process of this paper. In addition, situations such as order insertion or emergency orders that may occur in actual production are also not taken into account in the model. In future research, the scheduling model can be further optimized for these problems to improve the robustness of the model and the adaptability of the algorithm.


Production scheduling methods of colored spun yarn enterprises based on an improved ant colony algorithm

PAN Xinming, WANG Jing'an, QIU Zijun, GAO Weidong,

2025, 33(02):  130-139. 

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As a branch of textile industry, the colored spun yarn industry has its own characteristics of multi-variety, small batch, significant changes in color demands and short delivery time. The production scheduling of colored spun yarns differs from that of natural yarns in that workshops need to simultaneously produce various colored yarns with different blending ratios. Moreover, each type of colored yarn requires different semi-finished raw materials for each production process. However, traditional manual production scheduling involves a large workload, making it difficult to respond quickly and resulting in a high probability of errors. To address this issue, first, a production scheduling model for colored spinning processes was constructed, by taking into account factors such as machine downtime, order variety, and color sequences. The objective functions include minimum order delivery time, spinning frame changeover times, minimum and maximum completion times, and the total number of overdue orders. Additionally, this paper introduced flexible constraints on yarn variety similarity before and after production order, to manage issues such as fiber staining and order blocking caused by producing different colored yarn simultaneously. This enhances the adaptability of the model in handling urgent order insertions and order blocking issues.
Due to the large solution set range and complex constraints of the model, as well as the high computations and tendency of traditional ant colony algorithms to fall into local optimal solutions in solving large-scale scheduling problems, this paper proposed an improved ant colony algorithm incorporating candidate list strategy, adaptive pheromone updating, and a max-min ant system to solve the model. The algorithm's parameters were selected by using grid search: and pheromone factor α = 2.0, heuristic information factor β =3.0, evaporation factor ρ = 0.75, maximum pheromone concentration τmax = 6.0, and minimum pheromone concentration τmin = 0.15 were obtained, yielding the best optimization results for various scheduling objectives. Simulations were conducted for a workshop with 64 types of orders and 96 spinning machines, comprising 274 pending batch orders. The results demonstrated that while the traditional ant colony algorithm could improve scheduling objectives, its local pheromone updating strategy, which enhances the pheromone concentration of certain paths, could lead to local optimal solutions, causing order delays and exhibiting lower robustness. At the same time, the improved ant colony algorithm could solve the production scheduling problems of different-sized colored spun yarn enterprises with good robustness. The improved ant colony algorithm outperformed other methods in terms of scheduling objectives without order delays. Compared to manual scheduling, the proposed method reduced the order delivery time score fitness value by 83.77%, decreased the downtime for spinning machines waiting for retrofitting by 40.9%, and lowered the maximum completion time by 11.33%.