摘要
根据近红外光谱表征的内燃机油结构族组成信息,采用Kohonen神经网络数据处理数学模型,预测了内燃机油的粘度指数,结果表明Kohonen神经网络是1种有效的定性分析内燃机油粘度特性的工具,内燃机油的组成与粘度特性有良好的相关性。
According to the characteristic number of composition and structure of engine oil expressed by near - infrared spectroscopy, the viscosity index of engine oil is forecasted by Kohonen nervous network data treat mathematical model, the result shows that Kohonen nervous network is an effective tool for qualitative analyzing viscosity characteristic of engine oil, the relationship between composition of engine oil and viscosity characteristic is good.
出处
《合成润滑材料》
CAS
2004年第1期13-16,共4页
Synthetic Lubricants
关键词
内燃机油
粘度
近红外光谱法
KOHONEN神经网络
Kohonen nervous network
near - infrared spectroscopy
engine oil
viscosity index
qualitative analysis