摘要
分析了某合成的在用航空润滑油的组成和需检测的指标项目,研究了润滑油红外光谱信息与检测项目之间的关系。采用偏最小二乘法、人工神经网络法等建立红外光谱和运动粘度、闪点、酸值和水分等理化指标的多元校正分析模型。根据朗伯-比尔定律,建立红外光谱峰面积或峰高与被测组分的工作曲线,实现了燃油、抗氧剂、抗磨剂的定量分析。针对基础油酯基降解程度无法定量检测的特点,将酯基降解与酸值、粘度值进行关联性研究,酸值与酯基降解红外谱峰相关性很好,可通过酸值变化确定酯基降解程度。
Component and test items in a certain type of used lubricants were analysed, and the relation between infrared spectrum and test item was studied. Multivariate calibration methods of partial least squares(PLS) and artificial neural network(ANN) were used in infrared spectrum to set analytical model about kinematic viscosity, flash point, acid number and water content. Working curves of peak area or peak height were drawn based on Beer-Lambert law, then the contens of fuel oil, antioxidant and antiwear additive in aviation lubricants were determined. The ester base-stock can not be measured directly. There is a relevance between ester base-stock breakdown and kinematic viscosity or acid number, and acid number can be used to estimate the degree of ester base-stock breakdown because of a good correlation.
出处
《分析仪器》
CAS
2017年第2期58-63,共6页
Analytical Instrumentation
关键词
在用航空润滑油
红外光谱
偏最小二乘
神经网络
快速分析
used aviation lubricating oil
infrared spectrum
partial least squares
artificial neural net-work
quick analysis