روش های جداسازی فراورده های نفتی به وسیله روش های نوین آماری و کمومتریکس

Fuel oil is one of the petroleum fractions and it can be classified into different grades according to itscomposition and properties. Discrimination of the types of fuel oil is important in quality control,environmental monitoring and industry. In this work, some chemometric methods were examined forthe classification of 264 fuel oil samples from three types of oil (furnace oil, gas oil and mazut oil) withthe aid of attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy. For thispurpose, principal component analysis (PCA), extended canonical variates analysis (ECVA) and intervalextended canonical variates analysis (iECVA) were used. PCA was not able to discriminate fuel oils butECVA showed a good ability for classification purposes. On the other hand, iECVA was effective inindicating the fingerprint sub-regions in the FTIR spectra and decreasing the model’s complexity. Theproposed models were validated by different statistical methods and excellent specificity and selectivitywere obtained. ATR-FTIR spectroscopy coupled with chemometrics helps to present a fast, powerful andreliable approach for the discrimination of the grade of fuel oils which is important in quality control andenvironmental monitoring.