Sensor virtual para estimativa de umidade e temperatura na fase sólida durante processo de secagem em leito de jorro

• Ano de defesa: 2019
• Autor(a) principal: Paula, Eduardo Rodrigues de
• Orientador(a): Freire, José Teixeira
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Engenharia Química - PPGEQ
• Palavras-chave em Português: Secagem; Sensor virtual; Leito de jorro
• Palavras-chave em Inglês: Drying; Soft sensor; Spouted bed
• Área do conhecimento CNPq: ENGENHARIAS::ENGENHARIA QUIMICA::OPERACOES INDUSTRIAIS E EQUIPAMENTOS PARA ENGENHARIA QUIMICA
• Link de acesso: https://repositorio.ufscar.br/handle/ufscar/14236

Control systems are used to suppress the influence of external disturbances, to guarantee operational stability and to optimize the performance of chemical processes. Whatever the purpose, the means of controlling a chemical process go through the measurement of process variables and the adoption of different control strategies. Regards drying processes, the humidity and temperature of the solid product are related to the quality and the maintenance of its physicochemical properties. However, the direct measurement of this variable depends on slow, expensive and imprecise processes, especially in particulate systems and in constant movement, such as a spouted bed. A technological alternative is the use of virtual sensors, also known as soft sensors, which essentially have the role of linking simplified models and available measures in order to estimate the value of variables for which a "physical" meter is not available. In this context, the objective of this work was to develop soft sensors to jointly estimate the moisture and temperature of the solid phase during the drying process of granular porous solids in spouted bed, in view of the potential application in control purposes. It was used mathematical models found in the literature for different applications both in relation to the dryer and the material to be dried. For the moisture estimation, a mechanistic-empirical model was adjusted to minimize the difference between the experimental observations and the respective estimates. For the solids temperature, a fundamental model based on the energy balance equations for the solid and gaseous phases was adjusted so that the estimate outlet drying air temperature corresponded to the experimentally measured value. The results obtained for the humidity soft sensor showed good correspondence to the experimental measurements. For the temperature soft sensor, the unavailability of solid temperature measurements prevented a direct comparison between the estimated and experimental values. However, the results obtained were consistent with the heat and mass transfer phenomena that occur during batch drying.