纺织基弹力拉伸带强力力学预测模型的构建  

Construction of Predictive Model for the Strength of Textile-based Stretch Belts

作　　者：郑淑月 王妮[1] 丁亦 ZHENG Shu-yue;WANG Ni;DING Yi(College of Textiles,Donghua University,Shanghai 201620)

机构地区：[1]东华大学纺织学院,上海201620

出　　处：《纺织科学与工程学报》2022年第2期11-15,20,共6页Journal of Textile Science & Engineering

摘　　要：为帮助使用者有针对性地选择不同抗阻强度的体育用品和设计者开发分级阻力的织带款弹力拉伸带产品,需要探究织带拉伸强力变化规律。从纱线原料、织物结构和织造过程分析影响其拉伸强力关键因素有:弹力包覆纱的粗细、数量、组织结构、织物纬密。通过控制变量法改变各个参数并织造样品,根据行业标准测试后,训练BP-ANN神经网络以构建拉伸强力预测模型,验证后模型平均误差率在2.12%,可为弹性织带相关产品的开发设计提供参考。In order to help users to select sporting goods with different resistance strengths in a targeted manner and designers to develop webbing elasticstretch belt products with graded resistance,it is necessary to explore the law of webbing tensile strength changes.From the analysis of yarn raw materials,fabric structure and weaving process,the key factors affecting its tensile strength were:the thickness,quantity,structure and weft density of the elastic covering yarn.Through the control variable method to change each parameter and weave samples,after testing according to industry standards,the BP-ANN neural network was trained to build a tensile strength prediction model.After verification,the average error rate of the model was 2.12%,which could provide reference for the development and design of elastic webbing related products.

关 键 词：弹力拉伸带 织带 机织松紧带 神经网络 预测强力 

分 类 号：TS106[轻工技术与工程—纺织工程]