[Investigation and application of gasoline sample identity technique]

Chemometrics method was used to solve the problem of automatic selecting model for the detailed hydrocarbon analysis (DHA) of gasoline samples by gas chromatography/ flame ionization detection (GC/FID). The 29 peaks in GC/FID DHA chromatogram and their amounts were selected as the discriminating parameters to establish the five pattern models for different gasoline samples, such as fluid catalytic cracking (FCC) gasoline, coking gasoline, straight run gasoline, reformed gasoline, and alkylation gasoline. The principle component analysis (PCA) and Soft Independent Modeling of Class Analogies (SIMCA) were used to classify the gasoline samples and to identify the unknown samples according to the above pattern models. One hundred gasoline samples, derived from known resources, were employed to validate the reliability of the sample identity technique. With the help of the pattern identity method referred here, the automation of GC/FID DHA method becomes possible.