服用织物透气性研究进展及运动面料透气性提升策略OA

Fabric air permeability refers to the rate of air flow passing vertically through a fabric sample under specified conditions of sample area,pressure difference and time,and it is also one of the most important properties of fabrics.To systematically sort out the research progress of fabric air permeability and clarify the current technical bottlenecks and innovation directions,this paper first takes the air permeability of apparel woven fabrics as the research object.Through literature research,it summarizes the research progress of air permeability of apparel woven fabrics from the aspects of testing methods and instruments for the air permeability of woven fabrics,factors influencing fabric air permeability,numerical simulation of fabric air permeability,prediction methods for fabric air permeability,new technologies for improving fabric air permeability,and other relevant research on fabric air permeability.Then,it generalizes the research on the air permeability of apparel knitted fabrics,and combs the strategies for improving the air permeability of sportswear fabrics,which are the most concerned about air permeability among all fabrics.Finally,the paper prospects the research on fabric air permeability in light of the current development trend of artificial intelligence technology. Several main conclusions are drawn.In terms of the characterization of fabric air permeability,the pressure difference-type fabric air permeability tester is the most widely used.In terms of the factors influencing fabric air permeability,the warp and weft yarn count,apparent diameter of warp and weft yarns,warp and weft density,fabric thickness,float factor and pore size all affect the air permeability of apparel woven fabrics;the type of knitting loop,loop length,needle gauge,wale and course density,and yarn type all influence the air permeability of apparel knitted fabrics,and these influencing factors have a strong correlation with each other.Therefore,in predicting fabric air permeability based on fabric structural parameters,it is often necessary to use principal component analysis to reduce the dimensionality of multiple groups of influencing factors,and then use the results of principal component analysis to realize the prediction of fabric air permeability.In the aspect of air permeability prediction,shallow fitting models such as multivariate nonlinear fitting,neural networks and support vector machines can achieve certain fitting results,but the conclusions drawn from such results are only valid for a small range of fabrics of specific types.At present,there is a lack of fabric air permeability prediction models based on big data(covering a large number of different types of fabrics)and large models(such as convolutional neural networks or graph neural networks). Efficient calculation or prediction of fabric air permeability can focus on three directions;building a cross-structure adaptive model combined with deep learning,and mining the correlation between microstructures and air flow fields by means of multi-modal deep learning to reduce the dependence on artificial parameters;collecting large-scale fabric parameters and air permeability data in production scenarios relying on the industrial internet of things to construct a standardized database;and aiming at the inefficiency of manual measurement,developing a machine vision combined with image processing system to automatically extract parameters such as warp and weft density and yarn diameter,and integrating feature extraction and prediction models in an end-to-end manner to form an intelligent full-process system of"image-feature-prediction"and reduce manual intervention. In terms of improving the air permeability of sportswear fabrics,endowing fabrics with stepped moisture absorption capacity,using profiled cross-section fibers or superfine fibers,increasing yarn elasticity,adjusting the unevenness of yarn thickness,changing the woven fabric weave or knitting loop type,constructing larger fabric pores,or adopting coatings with nano-scale pores can all improve the air permeability of fabrics within a certain range.