Using Wavelet Network in Estimating the BOF Temperature

摘要

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.