Abstract
In blast furnace(BF) iron-making process, it usually used the hot metal silicon content to measure the quality of hot metal and to reflect the thermal state of BF (BF temperature). For better prediction and control of total variance contribution with 87.72% were extracted according to Principal Component Analysis (PCA). A regression model for predictive control of silicon content was established. The model was tested on datasets from BF No.6 in Baotou Steel Corporation and good accuracy was received with 88.4%. According to the model, air volume and air temperature control range could be improved with the influence of molten iron blast furnace silicon content.
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.
