Avaliação da incorporação de enxofre no clínquer em um forno de cimento
Ano de defesa: | 2012 |
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Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal de Minas Gerais
UFMG |
Programa de Pós-Graduação: |
Não Informado pela instituição
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Departamento: |
Não Informado pela instituição
|
País: |
Não Informado pela instituição
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Palavras-chave em Português: | |
Link de acesso: | http://hdl.handle.net/1843/BUOS-9ACHME |
Resumo: | During the clínquer Portland manufacturing, the relationships evaluation among the variety of quality and operation variables and their effect on the product is a complex task due to the great number of physicochemical phenomenon and the environmental of great variability and different variables sampling collect times. It was sought at this work, through statistical tools, trend-cycle-seasonal filter and the application of a neural network model, to evaluate the impact of these mentioned variables on the rotary kiln clinker sulphur incorporation. When the physicochemical conditions are favoring to the sulphur in the clinker structure volatilize, gases that are rich in sulphur displace to the kiln colder parts where there are conditions to precipitate in solid agglomeration form which reduces the material and gases duct area and sometimes stops the flow of them causing a kiln shutdown. The use of a filter to extract the trend of the variables is an alternative to this environment of great variability and, particularly, when the target is to identify kiln operation zones. The neural network model, which has presented a correlation r among evaluation data and simulation data above 0,94, it has allowed identifying two variables groups with different behaviors: the quality variables presenting a high linear correlation with the sulphur in the clinker and the processes variables that present non-linear relations that show the difficulty to correlate these variables and the clinker sulphur using linear regression. Furthermore, the neural network model was effective to evaluate the effect of small changes in several variables simultaneously on the response. For quality variables, the CaO, with a variation range of 1.2%, changes the tendency of SO3 in the clinker by 50% of its total variation range, showing to be the most meaningful. For the process variables, the change of 2.1% in the O2 2o stage changes the tendency of SO3 by 23% of its total variation range. Combination of small changes in the variables of both groups has been tested as the increase of fluorine (+0.04) and O2 2º stage (+1.3%) the tendency of SO3 by 23% of its total variation range. In a qualitative point of view, this work has shown that the amount of secondary firing in the rotary kiln should be reevaluated because it has been favoring the sulphur volatizing and that the correlation between the sulphur in the clinker and the individual chemical elements is more appropriate than the correlation with the chemical modules commonly used by the cement industry. |