Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 60,
  • Issue 8,
  • pp. 892-897
  • (2006)

Spectral Range Optimization for the Near-Infrared Quantitative Analysis of Petrochemical and Petroleum Products: Naphtha and Gasoline

Not Accessible

Your library or personal account may give you access

Abstract

The proper selection of the spectral range in partial least squares (PLS) calibration is critical when highly overlapping spectra from compositionally complex samples are used, such as naphtha and gasoline. In particular, the relevant spectral information related to a given property is frequently localized in a narrow range, and the most selective region may be difficult to locate. We have presented the importance of range optimization in near-infrared (NIR) spectroscopy for the analyses of petrochemical and petroleum products that are generally highly complex in composition. For this purpose, the determination of a detailed compositional analysis (so called PIONA) and the distillation temperature of naphtha were evaluated. In the same fashion, the research octane number (RON) and Reid vapor pressure (RVP) were selected for gasoline. By optimizing the range using moving window (MW) PLS, the overall calibration performance was improved by finding the optimal spectral range for each property. In particular, for a detailed compositional analysis of naphtha, it was effective to search for localized spectral information in a relatively narrow range with fewer factors.

PDF Article
More Like This
Terahertz quantitatively distinguishing gasoline mixtures using multiparameter-combined analysis

Yi-nan Li, Zhou-mo Zeng, Jian Li, Zhen Tian, Li-jun Sun, and Nan Zhou
Appl. Opt. 52(30) 7382-7388 (2013)

Terahertz surface plasmon sensor for distinguishing gasolines

Guanlin Liu, Mingxia He, Zhen Tian, Jingyan Li, and Jiazheng Liu
Appl. Opt. 52(23) 5695-5700 (2013)

Distinguishing octane grades in gasoline using terahertz metamaterials

J. Li, Z. Tian, Y. Chen, W. Cao, and Z. Zeng
Appl. Opt. 51(16) 3258-3262 (2012)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.