Title :
Prediction model of end-point for AOD furnace based on neural network
Author :
Guan, Changjun ; You, Wen ; Lin, Xiaomei
Author_Institution :
Dept. of Electr. & Electron. Eng., Changchun Univ. of Technol., Changchun, China
Abstract :
Accurate prediction of the end-point temperature and carbon content of AOD furnace is of great significance to raise the hitting rate of the end-point. Based on AOD refining practice, the predictive model of end-point temperature and carbon content of AOD furnace low carbon Chromium iron making based on BP neural network was put forward. The results showed that the model is much accurate and applicable.
Keywords :
backpropagation; carbon; furnaces; iron; metal refining; neural nets; production engineering computing; steel manufacture; AOD furnace; AOD refining practice; BP neural network; carbon content; end-point temperature; low carbon chromium iron making; prediction model; Artificial neural networks; Chromium; Furnaces; Iron; Neural networks; Predictive models; Production; Raw materials; Smelting; Temperature control; AOD furnace; carbon content; end-point temperature; neural network;
Conference_Titel :
Mechatronics and Automation, 2009. ICMA 2009. International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4244-2692-8
Electronic_ISBN :
978-1-4244-2693-5
DOI :
10.1109/ICMA.2009.5246049
