Measure the gravity value of the heating block of the ironing sublimation color fastness tester using an FSR sensor, and perform linear calibration on the sensor. The linear relationship between the digital analog quantity and weight is 0.9556≥0.95, which is considered to be in a usable state. The correction value of the sensor at 16N is measured to be-0.728 N using a 16N weight group composed of force value weights. A rubber pad with a thickness of 1.4 mm is used to cut into a circular rubber pad with a diameter of 30mm and a square rubber pad with a length of 50 mm and a width of 50 mm. The circular rubber pad is placed in the center above the force sensor, and the square rubber pad is placed below the force sensor. The test results are corrected from 8.132 N without rubber pad to 16.608 N with rubber pad according to the measurement process of the gravity value of the hot block in JJF (Textile)029—2023“Calibration Specification for Ironing Sublimation Color Fastness Tester”. The experimental results indicate that it is feasible to use FSR sensors to measure the gravity value of the heating block in the ironing sublimation color fastness tester.

To attain efficient particulate matter capture with ultra-low resistance, an air filtration system is constructed by applying a high voltage, comprising a charging zone and a high-voltage polarization capture zone with three-dimensional woven fabrics as the core filters. Three types of warp-knitted spacer filters (Thin 3D, Medium 3D, and Thick 3D) are used to systematically investigate the impact of fabric structure on the filtration performance. The results demonstrate that the woven-structured filters possess robust mechanical properties. Under an electric field intensity of 7.5 kV/cm, the filtration efficiencies of the three filters are 3.8 to 55.5 times greater than mechanical filtration, ranging from 51.20% to 93.90%, while maintaining an ultra-low pressure drop of 1.53 to 3.1 Pa. Among them, Medium 3D shows the most significant improvement in filtration efficiency. Further optimization of the filtration system reveals that using two stacked layers of Medium 3D fabric with a parallel-arranged-spacing-yarn model and a 100-mesh electrode achieves a filtration efficiency of 94.24% and a low pressure drop of 1.63 Pa at the same low electric field intensity (7.5 kV/cm). The corresponding quality factor could reach 1.747 2 Pa-1, underscoring the superior comprehensive filtration performance of this system.

A side-suction fill power pre-treatment dust collection device has been developed to address the serious pollution of harmful substances such as flying threads and dust in the testing environment during the pre-treatment process of fill power, which affects the physical and mental health of operators. The device adopts a 7° side-suction air inlet design, combined with a 200 mesh stainless steel screen and a dedicated non-woven dust collection bag, to efficiently collect the fluff, feather, dust, etc. generated during the fluffiness pre-treatment process, and effectively separate down components and impurities. The device can effectively improve the current situation of flying silk caused by the pre-treatment of fluffiness, and the dust concentration in the experimental environment is basically zero.

Textile-based pressurised medical devices for vascular pressure therapy have attracted much attention in terms of their research status and development direction as a medical aid widely used in clinical practice. For vascular diseases such as venous insufficiency and lymphatic reflux disorders, the current mechanism and methods of vascular pressure therapy are introduced with the research background of haemodynamics, biomechanics and ergonomics, and the advantages and disadvantages of different methods are summarized according to the classification of the existing vascular pressure therapy. Meanwhile, the structural characteristics, design principles and research directions of traditional pressure textiles and modern intelligent pressure devices at home and abroad are analyzed. It is found that the existing textile-based compression medical devices for vascular pressure therapy still have problems such as poor pressure durability, difficulty in monitoring the therapeutic pressure value, and inability to adjust the applied pressure. In-depth research and optimisation of the processes of raw material preparation and fabric shaping to improve the intelligence and personalisation of textile-based compression medical devices is the future development direction.

Teenage consumers and adult consumers have different lifestyles and consumption characteristics, and a differentiated design model is needed. To better understand the design needs of young women for autumn and winter outdoor sportswear, the following design requirements analysis will be conducted. Firstly, using the KANO model to collect data from the KANO model questionnaire, organize and classify different types of clothing design requirements; Secondly, due to the inability of the KANO model to quantify the importance of demand factors, a weight analysis of each design demand is conducted using the Analytic Hierarchy Process (AHP), and the scientific and reliable results are ensured through expert scoring and consistency testing. The results show that the design of outdoor clothing for adolescent women should prioritize the functionality of fabrics, followed by adjustable structural design and fashionable color to meet their diverse needs. The comprehensive application of KANO model and analytic hierarchy process in the theoretical research of outdoor clothing design for adolescent women can quickly assist designers in choosing design directions, making the design scheme more scientific and reasonable.

The evaluation of intangible cultural heritage is crucial for its safeguarding and sustainable development prospects. In order to objectively evaluate the qualitative and quantitative aspects of intangible cultural heritage related to textile techniques, the evaluation indicators and their weights are determined using literature research, Delphi method, and analytic hierarchy process. A potential evaluation index system for the development of intangible cultural heritage related to textile techniques is constructed, and the fuzzy comprehensive evaluation method is used to evaluate and analyze the development potential of five national level intangible cultural heritage projects related to textile techniques in Xinjiang. The results indicate that in the evaluation system, cultural value, aesthetic value, popularity, and economic value are the key factors affecting the industrial development of intangible cultural heritage projects. The development potential level of Uyghur carpet weaving skills and Edeles silk weaving and dyeing skills is higher; In contrast, the development potential of Uyghur flower felt, printed fabric weaving and dyeing techniques, and traditional cotton textile techniques is relatively lower. The constructed evaluation system is helpful in guiding the industrialization development of intangible cultural heritage of textile skills in Xinjiang.

Exploring the development of machine learning in yarn quality prediction aims to enhance digital production management level of textile enterprises gradually. Four machine learning algorithms: linear regression, grey system model, support vector machine, and neural networks are used to analyze the current research status of yarn quality prediction models. Elucidating the network structures and optimization algorithms of two types of neural networks——artificial neural networks and deep neural networks are focused on yarn quality prediction models deficiencies and proposing solutions for these networks in the yarn quality prediction field are also dissected. Further exploration of the application of deep neural networks based on sample databases in the field of yarn quality prediction is crucial to enhance prediction accuracy andaccelerate computational speed.

Using polylactic acid (PLA) as raw material, a spinning solution is prepared using dioxane (DIOX)/acetone (AC)/N, N-dimethylformamide (DMF) as solvent. PLA nanofiber membranes are prepared by needle and needleless electrospinning respectively. The effects of solvent ratio, PLA mass fraction and spinning voltage on spinnability and fiber morphology are studied, and the forming mechanism of needle and needleless electrospinning fibers is analyzed. The results show that there are differences in the effect of solvent ratio on the spinnability of PLA needle electrospinning and needleless electrospinning, but the fiber formability law is consistent. Similar fiber diameters are obtained after needle and needleless electrospinning, which can be explained by the simplified jet stretching model.

As a key element in fashion design, the precise identification of suit collar shape is of great significance for the intelligent development of the fashion industry. This study selected Faster R-CNN as the main model to construct the Blaze6480 image dataset, which includes four types of collar types: flat collar, ridge collar, green fruit collar, and no collar. At the same time, accuracy (A), precision (P), recall (R), average precision (AP), mean accuracy (mAP), and F1 score key indicators were used to comprehensively evaluate the performance of the Faster R-CNN model in women’s suit collar recognition tasks. The experimental results show that Faster R-CNN performs well in both recall rate (73.8%) and average accuracy (mAP 73.5%) in complex background collar detection, but the accuracy (62.1%) still needs to be optimized. This study provides technical reference for clothing attribute recognition and practical significance for automated classification of collar shapes in scenarios such as e-commerce platforms and intelligent clothing manufacturing.

In response to the challenges associated with traditional worsted wool fabrics, such as susceptibility to static electricity, wrinkles, a strong sense of constraint, and difficulty in machine washing, a new type of worsted wool fabric with anti-static, high elasticity, machine-washable, and wrinkle-resistant properties has been successfully developed by optimizing the dyeing, spinning, weaving, and finishing process parameters through the use of a blend of silk wool, SORONA fiber, and conductive fiber. The results show that when the blending ratio of silk wool/SORONA fiber/conductive fiber is 80/19/1, the yarn twist coefficient is 90/160, the weaving machine tightness is 103, and the fabric structure is 2/2 diagonal, the fabric performance can meet the first grade product assessment indicators such as charge surface density, elastic elongation, dimensional change rate after washing, and crease recovery angle specified in relevant standards.

In order to explore the role of digital intelligence technology in the protection and inheritance of intangible cultural heritage of ethnic costumes in the new era, the style, structure and data collection of Mongolia costumes are conducted based on DB 15/T 506-2012“Mongolian Tribal Costumes”. Taking Balhu women's as an example, CLO3D software is used to to carry out the 3D virtual restoration design and practice of national costumes from the aspects of virtual model selection, 2D plate production, virtual stitching and simulation, clothing pattern and fabric application, and clothing virtual display. The results show that CLO3D digital technology can efficiently and accurately restore the overall appearance of national costumes, and carry out three-dimensional display of the shape, color, pattern, accessories and other aspects of clothing culture, which is an effective method for the protection and inheritance of intangible cultural heritage national costumes.

In order to determine the material composition of the 3D printed shoe upper structure and to ensure the best results of 3D printed shoe uppers, the 3D printed shoe upper structure with thermoplastic polyurethane (TPU), flexible polylactic acid (PLA), and polyvinyl alcohol (PVA) as the main 3D printing materials are discussed, and the 3D printed thermoplastic polyurethane (TPU) and flexible polylactic acid (PLA) consumables are analyzed by scanning electron microscopy, infrared spectroscopy, IR, X-ray diffraction, differential thermal analysis, tensile properties and elastic recovery rate test analysis on 3D printed thermoplastic polyurethane (TPU) and flexible poly (lactic acid)(PLA) consumables, and scanning electron microscope (SEM), differential thermal analysis and solvency properties analysis on 3D printed support material poly (vinyl alcohol)(PVA), to explore the mechanical properties of these three materials. The results show that thermoplastic polyurethane (TPU) and flexible polylactic acid (PLA) materials are suitable for 3D printed shoe upper fabrics, and polyvinyl alcohol (PVA) can be used as a 3D printing support material in physical form.

In order to further understand the current research progress of piezoelectric materials in intelligent heating shoes, the application advantages of piezoelectric intelligent heating shoes are analyzed, and the existing research results are summarized. It is pointed out that due to the inherent limitations of piezoelectric materials, low piezoelectric power generation and difficulty in storing piezoelectric energy s are the technical bottlenecks that limit the development and application of piezoelectric intelligent heating shoes. Currently, piezoelectric heating shoes generally suffer from poor thermal and wet comfort, low miniaturization of electronic components, low functional integration and bulky shoe body, which affect wearing comfort and convenience. Suggestions can be addressed from the following five aspects: developing and upgrading a new generation of piezoelectric materials, designing new piezoelectric structures using the piezoelectric effect of piezoelectric materials, optimizing the design of new energy collection circuits, and improving the integration and intelligence of functions through the use of antibacterial, odor proof, breathable, and comfortable new materials.