亚麻纤维线密度与直径回归相关模型的构建及验证  

Construction and confirmation of regression models of flax fiber line density and diameter

作　　者：杨喜爱[1] 肖爱平[1] 冷鹃[1] 程毅[1] 廖丽萍[1] 

机构地区：[1]中国农业科学院麻类研究所,湖南长沙410205

出　　处：《纺织学报》2014年第8期21-26,共6页Journal of Textile Research

基　　金：农业部农业行业标准项目(2011-53-442)

摘　　要：为建立一种快速有效的亚麻纤维线密度测试方法,采用传统中段称重法获得亚麻纤维线密度(ρL),用直径显微图像仪测出纤维直径(d),经统计软件分析二者的相关性,拟合出6个回归模型。其中最优回归方程为ρL=6.29+0.004×d2,相关系数r=0.801**,表明亚麻纤维直径和纤维线密度间具有较好的相关性。F-检验和T-检验证明该方法与传统中段称重法差异不显著。实验结果表明该方法具有比较好的精密度、重现性和再现性。因此通过显微图像仪测试纤维直径,再经过存储在主机上回归方程的换算,可同步实现亚麻纤维线密度的自动化快速检测。In order to build up a rapid and efficient method to measure the flax fiber line density, the paper employed the conventional cut-middles method and acquired the flax fiber line density （PL）, and used the microscopic image technique and acquired flax fiber diameter（d）. The correlation of the fiber line density and fiber diameter were analyzed by statistic software and six regresion models were worked out through fitting. Among them the optimmal regression equation is PL = 6.29 ＋ 0. 004 × d2 （ correlation line density r =0. 801 ＊＊） , indicating that there is a good correlation between the fiber diameter and fiber fineness of flax fiber. F-test and T-test results showed that there is no significant difference between the conventional cut-middles method and this new method. The experimental results revealed that this method has good precision, repeatability and reproducibility. Therefore, once the fiber diameter is acquired by microscpoic image technique and the data are stored into the host machine, through regression equation calculation, an automatic and fast detection of flax fiber line density simultaneously can be realized.

关 键 词：亚麻纤维线细密度 纤维直径 显微图像仪 回归模型 优化与验证 

分 类 号：TS101.1[轻工技术与工程—纺织工程]