基于人工神经网络的纱线条干均匀度预测研究  

Predication of yarn unevenness by using artificial neural network

作　　者：李惠军[1] 

机构地区：[1]新疆大学,新疆乌鲁木齐830046

出　　处：《上海纺织科技》2010年第10期49-50,共2页Shanghai Textile Science & Technology

基　　金：国家自然科学基金项目(60965003)

摘　　要：研究了纱线条干均匀度预测问题,用HVI测试原棉指标,用USTER^(?) TESTER 5-S400测试成纱指标,采用标准BP算法建立断裂伸长预测的模型,进行纱线的条干均匀度预测,结果表明BP模型预测速度和精度较高,可以实现棉纱条干均匀度预测。The objective of this research is to predict yarn unevenness. HVI is used to test raw cotton index whilst USTER TENSOJET 5 - S400 is used to test formed yarn index. The model of breaking elongation predication is built based on standard BP neural network. The result shows that the prediction model based on BP neural network is more precise and efficient.

关 键 词：BP 纱线条干 CV值 粗节 棉结 纱线 测试 

分 类 号：TS104.1[轻工技术与工程—纺织工程]