Gasoline-diesel mixtures quantifying using terahertz time-domain waveform

Refined oil mixtures can be quantified using terahertz absorption coefficient spectra and dualistic linear regression fitting. When this method was used to quantify mixtures of -10# diesel and 97# gasoline, the volume fraction of 97# gasoline was well fitted. However, the absolute error between the real and fitted -10# diesel content was large (17.5%). To solve this problem, the present research addresses the possibility of developing a method that would allow direct, simple, and accurate determination of the -10# diesel content in gasolinediesel mixtures, using a terahertz time-domain pulse coupled to a multi-parameter combined analysis. The multi-parameter represents the time delay and amplitude of the first transmission dip and peak in the time-domain pulse. The relationship between these four parameters and the -10# diesel content in gasolinediesel mixtures was thoroughly investigated and four distinct calibration models for quantifying gasoline-diesel mixtures were built, using least square fitting. To enable the development of an informative and accurate calibration model, the four individual models were given proper weights and combined. The weight was determined by the cosine-optimal-method, which aimed to determine the most proper weight under the condition of the cosine of the angle between the fitted content vector and the real content vector that reaches the maximum. This method allows the determination of -10# diesel content in gasoline-diesel mixtures with a low absolute error (2.6%), resulting in predictions that are more accurate and precise than those obtained by the terahertz absorption coefficient spectra and dualistic linear regression fitting.