摘要
本文采用红外光谱表征的润滑油结构族组成信息，采用人工神经网络为数据处理工具，预测了润滑油的ＣＣＳ－１５℃粘度，得到很好结果，研究结果表明在润滑油组成、结构与性能研究中，人工神经网络是一种有效的处理工具。
The composition and structure of lubricating oil expressed by FTIR were used for its characterization.Artificial nervous network was used as a mathematical model.CCS -15℃ viscosity of base oil was forecasted and good result was obtained.The result has shown that the artificial nervous network is an effective mathematical model for studying the relation between the composition and structure of lubricating oil and its performance.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
1999年第4期559-561,共3页
Spectroscopy and Spectral Analysis
关键词
红外光谱
神经网络
低温流变性能
润滑油
调配
Infrared spectrometry, Artificial nervous network, Low temperature rheologic behavior
