基于软测量技术的重石脑油芳潜含量的预测

Prediction of Aromatic Potential Content of Heavy Naphtha Based on Soft Measurement Technology

重石脑油的芳潜含量(N+2A)是衡量重石脑油品质的关键因素。针对重石脑油分子结构种类多、组分复杂难以直接分析出分子构成的难题,基于软测量技术,采用与主导变量密切联系的二次变量(或称辅助变量)来预测主导变量。通过分析重石脑油的隔断馏分,运用人工神经网络建立软测量模型,并通过计算机仿真,实现对重石脑油芳潜含量的预测。

Aromatic potential content of heavy naphtha is a key factor of heavy naphtha quality. Aiming to the problems of many molecular structure types, complicated composition and difficult to define the molecular structure directly, based on soft measurement technology, secondary variables that are closely related to primary variables are used to predict primary variables. The aromatic potential content of naphtha can be predicted through analyzing distillated fraction of heavy naphtha and applying artificial neural network to establish soft measurement mode and computer simulation.