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近红外光谱法定性分析内燃机油的粘度特性 被引量:1

Qualitative Analysis of Engine Oil Viscosity Characteristic by Near - infrared Spectroscopy
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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.
机构地区 后勤工程学院
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
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