基于分子组成的减压渣油聚类分析

摘要/Abstract

摘要： 基于减压渣油的结焦性能受化合物的类型分布的影响，将高分辨质谱分析得到的数据按照芳烃（HC）、含1个硫原子的硫化物(S1)、含2个硫原子的硫化物(S2)、含1个氮原子的氮化物(N1)，按碳数的分布分成10类，并从分子组成上对71种减压渣油进行了聚类分析。结果表明：聚类分析将71种减压渣油按分子组成特点分为Ⅰ类、Ⅱ类和Ⅲ类减压渣油；为验证聚类的准确性，以减压渣油的残炭值作为聚类分析结果合理性判断的依据，发现Ⅰ类减压渣油残炭值最低，属于不易结焦的减压渣油；Ⅲ类减压渣油残炭值最大，属于最易结焦的减压渣油；Ⅱ类减压渣油残炭值高于Ⅰ类减压渣油，低于Ⅲ类减压渣油，结焦倾向居中。本研究利用聚类分析对多个减压渣油样本按分子组成进行分类，实现了FT-ICR MS数据的有效管理，为减压渣油的加工提供指导。

关键词: 生焦, 减压渣油, FT-ICR MS, 聚类分析, 残炭

Abstract: Coke-forming is a serious problem in vacuum residue processing, and affected by its compound classes distribution. Deepening its understanding at the molecular level is important in guiding vacuum residue processing. The detailed carbon numbers and double bond equivalent (DBE) distributions of various compounds in vacuum residues were obtained by Fourier transform ion cyclotron resonance mass spectrometry (APPI FT-ICR MS) and were grouped into 10 categories according to the carbon number distribution of the aromatic hydrocarbons, S1 compounds (single S atom in molecule), S2 compounds (two S atoms in molecule), and N1 compounds (single N atom in molecule), respectively. The cluster analysis was applied for 71 kind of vacuum residues based on above molecular group compositions. Results showed that 71 vacuum residues were divided into type I, type II, and type III according to their molecular composition characteristics. To verify the accuracy of cluster analysis, carbon residue value of the vacuum residue was acted as the basis of rational judgment of the cluster analysis. The type I vacuum residues have the lowest carbon residue values, and is classified as less coking residue. The carbon residue value of type III vacuum residues is the highest, belonging to coking residue. The type II vaccum residue is in the middle. This work used cluster analysis to classify vacuum residue samples based on their molecular composition, the effective management of FT-ICR MS data could be realized, and the molecular composition of vacuum residue is closely linked to its processing performance is proved.

Key words: coking, vacuum residue, FT-ICR MS, cluster analysis, carbon residue

刘玲田松柏李敬岩李虎王威. 基于分子组成的减压渣油聚类分析[J]. , 2018, 49(8): 43-48.

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