Abstract
This work exploits a model for Aluminium Fluoride Concentration Measurement in the Aluminium Smelting process. This process variable is usually measured every 50-100 hours since it requires long laboratory analysis. This variable has a strong influence on the whole process, thus it should be controlled in a shorter basis. In order to prevent the long time between measurements, we developed a soft sensor based on neural networks which allows estimating the fluoride concentration at any moment by querying against the available process database. This database encompasses the consolidated knowledge on this chemical process and thus can be used both to build and validate the model.
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Fontes, O., Soares, F.M., Limão, R. (2012). Estimation of Aluminium Fluoride Concentration in Aluminium Reduction Cells through a Soft Sensors Approach. In: Yin, H., Costa, J.A.F., Barreto, G. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2012. IDEAL 2012. Lecture Notes in Computer Science, vol 7435. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32639-4_37
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DOI: https://doi.org/10.1007/978-3-642-32639-4_37
Publisher Name: Springer, Berlin, Heidelberg
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