化学演进过程数据的自动分辨——复杂石油样品的GC-MS分析

Automatic Resolution of Data from Evolutionary Process GC - MS Analysis of Petroleum Sample

基于几种新化学计量学方法,提出了可自动解析化学演进数据的新途径.在该法中,首先选择关键向量.通过子空间比较法确定数据的化学秩.以关键向量为起点,通过初等变换不断迭代而实现对数据的解析.并利用数据非负性等检验解析结果的可靠程度.结合GC-MS数据的特点,选择的关键变量可为关键质谱或关键浓度曲线.该方法能极大地减少人为干预,大大降低数据分析时间.对文中的石油样本共解析出557个成分.

A new procedure, based on several recent chemometric methods, is proposed for automatic analysis of data from evolutionary process. It runs in the following steps: first, select key spectra or variables; second, determine the chemical rank of data by subspace comparison; third, iterative into pure spectra and concentration profiles by elementary transform. Criteria, e.g. non - negativity, are used to check the reliability of results. As far as data from GC - MS is concerned, key variables can also be used for analysis besides key spectra. The proposed procedure greatly reduces user intervention and therefore saves analysis time. It promises a powerful tool for the resolution of complex system. There are 557 components resolved from petroleum sample in this paper.