Development and Validation of a Multivariate Calibration Method for Determining Interfacial Tension of Transformers Insulating Oils by near Infrared Spectroscopy

2011 ◽  
Vol 19 (4) ◽  
pp. 243-251 ◽  
Author(s):  
Mariana S. Godinho ◽  
Anselmo E. Oliveira ◽  
Marcelo M. Sena
Keyword(s):  
Infrared Spectroscopy ◽  
Interfacial Tension ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Calibration Method ◽  
Development And Validation

Analysis of EPDM Terpolymers by Near-Infrared Spectroscopy and Multivariate Calibration Methods

1989 ◽  
Vol 43 (8) ◽  
pp. 1435-1443 ◽  
Author(s):  
Charles E. Miller
Keyword(s):  
Infrared Spectroscopy ◽  
Least Squares ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Calibration Method ◽  
Chemical Components ◽  
Multivariate Methods ◽  
Calibration Methods ◽  
Interchain Interactions

Near-infrared spectroscopy in the combination, first overtone, and second overtone regions is combined with the multivariate methods of Partial-Least-Squares (PLS) and Classical-Least-Squares (CLS) to provide calibrations for chemical components in ethylene-propylene-diene monomer (EPDM) terpolymers. EPDM samples with 1,4-hexadiene (HD) and ethylidene norbornene (ENB) diene monomers were used for this study. Because unknown interaction effects are present in the spectra of these materials, the PLS calibration method gives more accurate calibrations than the CLS method. PLS coefficient spectra and CLS reconstructed spectra obtained from the calibrations are used to determine the sources of the unknown spectral effects. Results indicate that the combination, first overtone, and second overtone regions of the spectrum can be used to determine ethylene and propylene concentrations in the terpolymers, and the combination region can be used to determine diene concentrations. The presence of intrachain and interchain interactions in the terpolymers is indicated by observation of CLS reconstructed spectra.

Linear transformations of multivariate calibration models in near infrared spectroscopy: A comparative study

2017 ◽  
Vol 25 (4) ◽  
pp. 223-230 ◽  
Author(s):  
Joseph Dubrovkin
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Cetane Number ◽  
Total Protein Content ◽  
Prediction Errors ◽  
Calibration Data ◽  
Linear Transformations ◽  
Calibration Models

It was shown that linear transformations are suitable for use in multivariate calibration in near infrared spectroscopy as data compression tools. Partial Least Squares calibration models were built using spectral data transformed by expansion in the series of classical orthogonal polynomials, Fourier and wavelet harmonics. These models allowed effective prediction of the cetane number of diesel fuels, Brix and pol parameters of syrup in sugar production and fat and total protein content in milk. Depending on the compression ratio, prediction errors were no larger than 30% of corresponding errors obtained by the use of the non-transformed models. Although selection of the most suitable transformation depends on the calibration data and on the cross-validation method, in many cases Fourier transform gave satisfactory results.

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