摘要
利用近红外光谱分析技术研究了喷气燃料防冰添加剂浓度的检测方法。通过实验得到不同防冰剂浓度喷气燃料试样的近红外吸收光谱,分析表明:防冰剂浓度与吸光度之间存在一定的数量关系。分别用一元线性回归、多元线性回归和主成分回归法建立预测模型,并对3个不同浓度的样品进行预测,验证结果表明:主成分回归法测量误差最小,其平均相对误差为5.7%,平均绝对误差为0.007%。该研究表明,利用近红外光谱分析技术对防冰剂浓度的预测是完全可行的。
Near infraed spectroscopy（NIR）technology was used to measure the concentration of fuel system icing inhibitor（FSII）in jet fuel.NIR absorption spectra of jet fuel specimens with different FSII concerntration were obtained experimentally and the spectral diagram showed that there is a certain quantity relation between the concentration of FSII concerntration and absorbance,respectively.Linear regression,multivariate linear regression and principal component regression were used to establish a prediction model and 3 samples with different FSII concentrations are predicted.The results showed that the measurement error of principal component regression method is lowest,which has an 5.7% average relative error of and 0.007% mean absolute error.The study showed that it is feasible to predict the concentration of FSII by NIR.
作者
王烨
郭忠烈
王立
孟凡芹
Wang Ye;Guo Zhonglie;Wang Li;Meng Fanqin(Graduate Brigade,Air Force Logistics College,Xuzhou 221000,Jiangsu,China;Academy of Engineer Corps,Air Force Logistics College,Xuzhou 221000,Jiangsu,China)
出处
《精细石油化工》
CAS
CSCD
北大核心
2018年第4期58-61,共4页
Speciality Petrochemicals
基金
徐州市科技项目(KH17009)
关键词
近红外光谱法
防冰添加剂
主成分回归法
near-infrared spectrometry
fuel system icing inhibitor
principal component regression
