Title :
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
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;
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
DOI :
10.1109/ICAL.2009.5262776
