Neural Modeling as a Tool to Support Blast Furnace Ironmaking
نویسندگان
چکیده
This paper describes the development of a hybrid model based on artificial neural network and its industrial application to the ironmaking at Companhia Siderúrgica Nacional (CSN -Volta Redonda/Brazil). The Iron Blast Furnace is highly complex process subject to oscillations in raw material characteristics. A precise model is essential to adjust © 2002 charging and blow conditions to match productivity, chemical quality and costs targets. A neural model was developed in order to estimate chemical and thermal parameters to feed a first principles model capable of evaluating alternative operation standards. As a consequence, operation efficiency is enhanced leading to higher productivity and lower costs. Copyright © 2002 IFAC
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