Stochastic modeling of the transient regime of an electronic nose for waste cooking oil classification

Autor(es)

Siqueira, A. F. ^[1] ; Melo, M. P. ^[1] ; Giordani, D. S. ^[2] ; Galhardi, D. R. V. ^[2] ; Santos, B. B. ^[2] ; Batista, P. S. ^[2] ; Ferreira, A. L. G. ^[1]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Engn Sch Lorena, Dept Basic & Environm Sci, Sao Paulo - Brazil

^[2] Univ Sao Paulo, Engn Sch Lorena, Dept Chem Engn, Sao Paulo - Brazil

• Tipo de documento: Artigo Científico
• Fonte: Journal of Food Engineering; v. 221, p. 114-123, MAR 2018.
• Citações Web of Science: 2

Resumo

The present work aims to propose an empirical kinetic model based on sorption and the precursor state, which is capable of describing the variation in electrical resistances of olfactory sensors used in assembling a device known as the e-nose. In addition, a new approach to model its noise has been proposed by means of a stochastic differential equation. As regards its application, waste cooking oil from different sources was better characterized by this new model when compared to traditional techniques of data analysis for such device. (C) 2017 Elsevier Ltd. All rights reserved. (AU)

• Processo FAPESP: 15/09766-1 - Pré-classificação de Óleo e Gordura Residual (OGR) para aplicação em biodiesel
• Beneficiário: Daniel Rodrigues Valle Galhardi
• Modalidade de apoio: Bolsas no Brasil - Iniciação Científica
• Processo FAPESP: 14/25001-2 - Desenvolvimento de metodologia de pré-classificação de óleo e gordura residual (OGR) para produção de biocombustível
• Beneficiário: Ana Lúcia Gabas
• Modalidade de apoio: Auxílio à Pesquisa - Programa BIOEN - Regular