Document Detail

Classification of jet fuel properties by near-infrared spectroscopy using fuzzy rule-building expert systems and support vector machines.
MedLine Citation:
PMID:  21073794     Owner:  NLM     Status:  In-Process    
Monitoring the changes of jet fuel physical properties is important because fuel used in high-performance aircraft must meet rigorous specifications. Near-infrared (NIR) spectroscopy is a fast method to characterize fuels. Because of the complexity of NIR spectral data, chemometric techniques are used to extract relevant information from spectral data to accurately classify physical properties of complex fuel samples. In this work, discrimination of fuel types and classification of flash point, freezing point, boiling point (10%, v/v), boiling point (50%, v/v), and boiling point (90%, v/v) of jet fuels (JP-5, JP-8, Jet A, and Jet A1) were investigated. Each physical property was divided into three classes, low, medium, and high ranges, using two evaluations with different class boundary definitions. The class boundaries function as the threshold to alarm when the fuel properties change. Optimal partial least squares discriminant analysis (oPLS-DA), fuzzy rule-building expert system (FuRES), and support vector machines (SVM) were used to build the calibration models between the NIR spectra and classes of physical property of jet fuels. OPLS-DA, FuRES, and SVM were compared with respect to prediction accuracy. The validation of the calibration model was conducted by applying bootstrap Latin partition (BLP), which gives a measure of precision. Prediction accuracy of 97 ± 2% of the flash point, 94 ± 2% of freezing point, 99 ± 1% of the boiling point (10%, v/v), 98 ± 2% of the boiling point (50%, v/v), and 96 ± 1% of the boiling point (90%, v/v) were obtained by FuRES in one boundaries definition. Both FuRES and SVM obtained statistically better prediction accuracy over those obtained by oPLS-DA. The results indicate that combined with chemometric classifiers NIR spectroscopy could be a fast method to monitor the changes of jet fuel physical properties.
Zhanfeng Xu; Christopher E Bunker; Peter de B Harrington
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Applied spectroscopy     Volume:  64     ISSN:  1943-3530     ISO Abbreviation:  Appl Spectrosc     Publication Date:  2010 Nov 
Date Detail:
Created Date:  2010-11-15     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0372406     Medline TA:  Appl Spectrosc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1251-8     Citation Subset:  -    
Center for Intelligent Chemical Instrumentation, Clippinger Laboratories, Department of Chemistry, Ohio University, Athens, Ohio 45701-2979, USA.
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