Phosphorus endpoint prediction of AOD furnace ferroalloy melting based on wavelet neural network

Author

Dongmei, Wang ; Wen, You ; Xiaomei, Lin ; Yantao, T. Ian

Author_Institution

Dept. of Electr. & Electron. Eng., Changchun Univ. of Technol., Changchun, China

fYear

2009

fDate

5-7 Aug. 2009

Firstpage

1302

Lastpage

1306

Abstract

Dephosphorization is one of the most important part of AOD furnace ferroalloy melting, and it is also one of the basic reaction. Bing the smelting process is complex in this paper promote the wavelet neural network algorithm in order to predict the endpoint of phosphorus value and using on-line data to training the wavelet neural network. The simulation results showed that the prediction relative error between the prediction and the practical value is within plusmn5% and the convergence rate of the learning algorithm is fast.

Keywords

furnaces; iron alloys; melting; neural nets; phosphorus; production engineering computing; smelting; AOD furnace; dephosphorization; ferroalloy melting; learning algorithm; phosphorus endpoint prediction; smelting process; wavelet neural network; Continuous wavelet transforms; Discrete wavelet transforms; Feedforward neural networks; Furnaces; Neural networks; Predictive models; Production; Smelting; System identification; Wavelet analysis; Dephosphorization; Prediction model; Wavelet neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation and Logistics, 2009. ICAL '09. IEEE International Conference on

Conference_Location

Shenyang

Print_ISBN

978-1-4244-4794-7

Electronic_ISBN

978-1-4244-4795-4

Type

conf

DOI

10.1109/ICAL.2009.5262776

Filename

5262776