A soft sensor for the Bayer process
نویسندگان
چکیده
*Correspondence: [email protected] 1Centre de Recerca Matemàtica, Bellaterra, Barcelona, 08193, Spain 2Mathematics Applications Consortium for Science and Industry, University of Limerick, Limerick, Ireland Full list of author information is available at the end of the article †Equal contributors Abstract A soft sensor for measuring product quality in the Bayer process has been developed. The soft sensor uses a combination of historical process data recorded from online sensors and laboratory measurements to predict a key quality indicator, namely particle strength. Stepwise linear regression is used to select the relevant variables from a large dataset composed of monitored properties and laboratory data. The developed sensor is employed successfully by RUSAL Aughinish Alumina Ltd to predict product strength five days into the future with R-squared equal to 0.75 and to capture deviations from standard operating conditions.
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