Image-Based Casting Rate Estimation for Molten Iron Jet Released From Blast Furnace

Monitoring the casting rate of molten iron released from the blast furnace in real time is essential for maintaining the efficiency of the smelting process. This research is dedicated to developing an image-based method to estimate iron casting rate. A live video of the hot metal jet is recorded and processed with an image processing algorithm to extract both the velocity and the size of the jet, which are then used to estimate the casting rate. After validation in the laboratory, this method will be integrated into the blast furnace monitoring system used for industrial operation.

Weixiao Shang | Purdue University
 

Jun Chen | Purdue University
 

Tyamo Okosun | Purdue University Northwest
 

Chenn Zhou | Purdue University Northwest
 

Kosta Leontaras | United States Steel Corporation
 

Joseph Morey | United States Steel Corporation
 

Jason Entwistle | United States Steel Corporation
 

Brian Rogers | United States Steel Corporation