Bioethanol is produced on an industrial scale by means of fermentation of a sugar substrate by Saccharomyces cerevisiae. Models for the detection of anomalies and their possible evolution are difficult to elaborate due to the biological nature of the fermentation process. This paper describes a method able to characterize patterns for explaining industrial bioethanol production using self-organised maps. Also, this method allows for an estimation of the probabilities of evolution to any pattern that the process may have from its last recognized state, therefore helping to take measures to correct a possible problem as soon as possible.
Keywords: fermentation patterns; bioethanol production; chemical analysis monitoring; pattern recognition; selforganised maps; machine learning.
2nd International Symposium on Computational Intelligence for Engineering Systems - ISCIES 2011
Publication date: November 2011.
M.A. Sanz-Bobi, P.R. Castelló, J. Montes, The process of industrial bioethanol production explained by self-organised maps, 2nd International Symposium on Computational Intelligence for Engineering Systems - ISCIES 2011. ISBN: 978-989-8331-12-0, Coimbra, Portugal, 16-18 November 2011