Paper Title:
Using Wavelet Network in Estimating the BOF Temperature
  Abstract

Temperature of the BOF flame is an important evident in the steel making process. A kind of wavelet neural network (SWNN) is constructed to get the mapping relation between the flame true temperature and radiation which can be effectively separated from emission information. The temperature predicted by the summation wavelet neural network is inosculated to the temperature measured by sub-lance comparatively.

  Info
Periodical
Chapter
Chapter 1: Manufacturing Engineering and Material Science
Edited by
Gary Yang
Pages
88-91
DOI
10.4028/www.scientific.net/AMR.429.88
Citation
Y. Q. Wang, Y. R. Chen, F. N. Chen, J. J. Chen, "Using Wavelet Network in Estimating the BOF Temperature", Advanced Materials Research, Vol. 429, pp. 88-91, 2012
Online since
January 2012
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Mu Lan Wang, Yong Feng, Xiao Xia Li, Bao Sheng Wang
Chapter 4: Fluid Mechanics and Thermodynamics
Abstract:An experimental system used for temperature measurement is designed by the K-type thermocouple thermometry to achieve a direct measurement of...
594
Authors: Li De Fang, Ji Ke Zhang, Xiao Ting Li, Xiu Ming Xiang
Chapter 30: Automation, Mechatronics and Robotics
Abstract:The dynamic characteristics of temperature sensor are very important in industrial temperature measure. In this paper, the dynamic...
7637
Authors: Zi Yu Zhao, Guang Tao Zhou, Bi Bo Xia, Su Zhi Zhang
Abstract:Experimental system of CCD real-time acquisition is developed according to high temperature property of plasma jet. Mathematical model of...
1259