Mariana S. Godinho

Evaluation of transformer insulating oil quality using NIR, fluorescence, and NMR spectroscopic data fusion

Power transformers are essential components in electrical energy distribution. One of their most important parts is the insulation system, consisting of Kraft paper immersed in insulating oil. Interfacial tension and color are major parameters used for assessing oil quality and the system׳s degradation. This work proposes the use of near infrared (NIR), molecular fluorescence, and (1)H nuclear magnetic resonance (NMR) spectroscopy methods combined with chemometric multivariate calibration methods (Partial Least Squares - PLS) to predict interfacial tension and color in insulating mineral oil samples. Interfacial tension and color were also determined using tensiometry and colorimetry as standard reference methods, respectively. The best PLS model was obtained when NIR, fluorescence, and NMR data were combined (data fusion), demonstrating synergy among them. An optimal PLS model was calculated using the selected group of variables according to their importance on PLS projections (VIP). The root mean square errors of prediction (RMSEP) values of 2.9 mN m(-1) and 0.3 were estimated for interfacial tension and color, respectively. Mean relative standard deviations of 1.5% for interfacial tension and 6% for color were registered, meeting quality control requirements set by electrical energy companies. The methods proposed in this work are rapid and simple, showing great advantages over traditional approaches, which are slow and environmentally unfriendly due to chemical waste generation.

Classificação de refrigerantes através de análise de imagens e análise de componentes principais (PCA)

CARBONATED SOFT DRINK CLASSIFICATION BASED ON IMAGE ANALYSIS AND PCA. This paper describes an approach for the colour-based classification of RGB (red-green-blue) images, acquired using a common scanner, of commercial carbonated soft drinks. Mean histograms of image colour channels were evaluated for the PCA classification of 29 brands of Guarana, Cola, and orange flavors. Loadings for principal component axes resulted in different patterns for sample grouping on score plots according to RGB histograms. pH, sorbic acid and sucrose measurements were also correlated to the analyzed brands through PCA score plots of the digitalized images.

ANÁLISE MULTIVARIADA DE IMAGENS NA QUÍMICA: UM EXPERIMENTO PARA DETERMINAÇÃO DO pH DE ÁGUAS POTÁVEIS

A Multivariate Image Analysis (MIA) laboratory activity was proposed estimating pH of drinking water samples from its digital images after adding bromothymol blue as a pH indicator, and using the PLS multivariate calibration method. All computational work was done using GNU Octave free software. The MIA-PLS based approach exemplified with drinking water pH estimates is tailored to meet the needs of both students and researchers. MIA-PLS method was statically equivalent to the reference method using a conventional glass pH electrode. This lab activity combines analytical methodology, computing, and chemometrics.

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

The aim of this study was to develop and validate a multivariate calibration method based on partial least squares (PLS) and near infrared spectroscopy for determining the interfacial tension of insulating oils used in electricity power transformers. Forty-eighty oil samples were obtained from an electricity power company and were divided into a calibration set of 38 leaving 10 for the validation set. The reference values were measured with a ring tensiometer and ranged from 15 dyn cm−1 to 45 dyn cm−1. The spectra were registered from 1280 nm to 2500 nm and the best PLS model was selected with 10 latent variables, providing a root mean square error of prediction of 2 dyn cm−1 and a coefficient of determination between reference and predicted values of 0.962. This method was validated in the context of multivariate calibration and was considered to have adequate accuracy (prediction errors between −9% and 12%), precision and linearity. A bias test verified the absence of systematic errors in the model. A pseudo-univariate calibration curve was constructed based on the concept of net analyte signal. The proposed method was simple, rapid, non-destructive and considered appropriate for the routine use in a quality control laboratory of an electricity power company.

A formação dos docentes de química: uma perspectiva multivariada aplicada à rede pública de ensino médio de Goiás

This paper presents a multivariate statistical analysis as a valuable tool for educational management applied to public high school chemistry teacher formation. From 2003 to 2007, a decrease of 10% in the number of public high schools was seen, as well as a reduction of 7% in the number of teachers. Contrarily, there was an increase in the number of university graduate teachers. Principal Component Analyses reveal that in 2003, most chemistry teachers were not university graduates. In 2007, eight Regional Offices of Education reported teachers holding academic degrees, qualifying them as chemistry teacher in the school system