近红外光谱法检测纺织品中羊绒和羊毛含量

Determination of cashmere and wool contents in textile by near infrared spectroscopy

将纯羊绒、羊毛按不同比例混合配制101个标样,采用偏最小二乘法,建立近红外光谱定量分析的数学模型,预测模型的相关系数为0.99,标准差为2.8%。实验表明:采用近红外光谱技术对羊绒、羊毛进行定量分析是可行的,有望成为快速、非破坏性的检测手段。该试验的样品数量和代表性有限,预测模型的精确度有待提高,若将近红外光谱技术真正用于检测工作,需逐步积累样品,建立更具代表性的数据库和更为稳定、精确、可靠的数学模型。

A quantitative analysis model was established to determine the contents of cashmere and wool in textile by near infrared spectroscopy （NIRS）. 101 calibration samples were mixed by weighing and measured by NIRS, which were combined to establish the calibration model by partial least squares （PLS） method. The correlation coefficient between the predictive result and true value was 0.99, and the root mean standard error of prediction was 2.8 %. The results demonstrated that NIRS could be a rapid and nondestructive technique for quantitative analysis of cashmere and wool. However, extensive sample collections were suggested in the future work to set up a representative database and to establish a mathematical model with better stabilization, precision and dependability.