DocumentCode
3359852
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
fYear
2009
fDate
9-12 Aug. 2009
Firstpage
2426
Lastpage
2430
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/ICMA.2009.5246049
Filename
5246049
Link To Document