Abstract
ABSTRACT The cross temperature measuring device is applied to monitor the top temperature and gas flow distribution in the blast furnace (BF) during the ironmaking process. However, the temperature of the BF roof is relatively high, which causes damage to the cross temperature measuring device. Therefore, this paper proposes an efficient estimation method. First of all, the data filtering method are used to solve the problems of noise interference. Moreover, as the fact that BF cross temperature measurement is affected by interference factors, it is easy to cause information redundancy. Aiming at this, the maximum information coefficient (MIC) correlation analysis and sequence dislocation method are used to determine the input variables and its action time of the model. Finally, an estimation model based three-layer long and short-term memory network (LSTM3) is established. The experimental results show that the LSTM3 can estimate the centre temperature of cross temperature measuring device.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
