丝绸2025，Vol.62Issue(9)：83-93,11.DOI:10.3969/j.issn.1001-7003.2025.09.009
机织物斜向剪切性及其预测研究
Research on the bias-shearing properties of woven fabrics and their prediction
摘要
Abstract
Fabric shear performance refers to the deformation performance of fabric yarns when they are subjected to two opposing forces acting along different but parallel axes simultaneously.This property is a critical factor in enabling fabrics to form elegant three-dimensional curved shapes and significantly influences the drape behavior of textiles.The human body is composed of intricate three-dimensional curved surfaces.To achieve perfect conformity between garments and body contours,create visually pleasing aesthetic effects,and enhance wearer comfort,fabrics must possess excellent shear properties.By investigating fabric shear properties,we can optimize textile structures and performance characteristics to better adapt to diverse wearing scenarios and functional requirements. In this study,18 woven fabrics were selected as research subjects.Samples were cut at 15° intervals from the warp direction(0°),resulting in 12 angular orientations per fabric with triplicate samples at each angle,to systematically investigate the anisotropic shear properties of the textiles.This study plots a polyline graph of shear stiffness to investigate the relationship between angles and shear stiffness.It analyzes the correlation between shear stiffness and shear hysteresis moments(2HG,and 2HG5).Two machine learning algorithms—a BP neural network and Support Vector Regression(SVR)model—are employed to predict bias shear stiffness based on warp-weft shear stiffness and yarn orientation angles. The results demonstrate that woven fabrics exhibit significant anisotropic shear behavior.Both shear stiffness and shear hysteresis moments(2HG,and 2HG5)show notable variations with fabric angle changes.For most fabrics,the maximum shear stiffness occurs at 45° or 60°,while the minimum values appear at 0°and 90°.Furthermore,the shear properties display good symmetry with the weft direction(90°)as the axis of symmetry.The study reveals that fabrics with high shear stiffness often exhibit unmeasurable bias-direction(30°,45°,and 60°)2HG5 values.Analysis of the relationship between shear stiffness and shear hysteresis moment 2HG indicates an inverse correlation—the lower the shear stiffness,the stronger the correlation.Notably,the strongest correlation is observed at 0°and 90°orientations.This study employs a SVR model to predict bias-direction shear stiffness based on warp-weft shear stiffness.The results demonstrate that the SVR model can effectively predict shear stiffness at various bias angles of woven fabrics. This study primarily investigates the relationship between shear behavior and fabric orientation angles.The findings reveal distinct anisotropic characteristics in fabric shearing,which can assist designers in strategically selecting optimal cutting angles based on specific requirements.By fully utilizing the fabric's shear properties,designers can achieve desired garment draping effects more effectively.关键词
织物/剪切刚度/剪切滞后矩/支持向量机回归预测/斜向/BP神经网络Key words
fabric/shear stiffness/shear hysteresis moment/support vector machine regression prediction/oblique/BP neural network分类
轻工纺织引用本文复制引用
杜秋雨,刘成霞..机织物斜向剪切性及其预测研究[J].丝绸,2025,62(9):83-93,11.基金项目
国家自然科学基金项目(51405446) （51405446）
