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Adulteration of diesel/biodiesel blends by vegetable oil as determined by Fourier transform(FT)near infrared spectrometry and FT-Raman spectroscopy

机译:傅立叶变换(FT)近红外光谱和FT拉曼光谱法测定植物油对柴油/生物柴油混合物的掺假

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In this work it has been shown that the routine ASTM methods(ASTM 4052,ASTM D 445,ASTM D 4737,ASTM D 93,and ASTM D 86)recommended by the ANP(the Brazilian National Agency for Petroleum,Natural Gas and Biofuels)to determine the quality of diesel/biodiesel blends are not suitable to prevent the adulteration of B2 or B5 blends with vegetable oils.Considering the previous and actual problems with fuel adulterations in Brazil,we have investigated the application of vibrational spectroscopy(Fourier transform(FT)near infrared spectrometry and FT-Raman)to identify adulterations of B2 and B5 blends with vegetable oils.Partial least square regression(PLS),principal component regression(PCR),and artificial neural network(ANN)calibration models were designed and their relative performances were evaluated by external validation using the F-test.The PCR,PLS,and ANN calibration models based on the Fourier transform(FT)near infrared spectrometry and FT-Raman spectroscopy were designed using 120 samples.Other 62 samples were used in the validation and external validation,for a total of 182 samples.The results have shown that among the designed calibration models,the ANN/FT-Raman presented the best accuracy(0.028%,w/w)for samples used in the external validation.
机译:这项工作表明,ANP(巴西国家石油,天然气和生物燃料国家机构)推荐了常规ASTM方法(ASTM 4052,ASTM D 445,ASTM D 4737,ASTM D 93和ASTM D 86)确定柴油/生物柴油混合物的质量不适合防止B2或B5混合物与植物油掺假。考虑到巴西燃料掺假的先前和实际问题,我们研究了振动光谱法(傅里叶变换(FT)红外光谱法和FT-拉曼光谱法)来鉴定植物油中B2和B5混合物的掺假。设计了偏最小二乘回归(PLS),主成分回归(PCR)和人工神经网络(ANN)校准模型及其相对模型使用F检验通过外部验证评估性能。使用120个样品设计基于傅立叶变换(FT)近红外光谱和FT-拉曼光谱的PCR,PLS和ANN校准模型s。其他62个样品用于验证和外部验证,总共182个样品。结果表明,在所设计的校准模型中,ANN / FT-Raman的精度最高(0.028%,w / w)用于外部验证的样品。

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