Mathematical Model Based Control System for Silicon Steel Mill of Rourkela Steel Plant

• Published in: Procedia technology Vol. 4; pp. 867 - 872
• Main Authors: Goswami, Ayan, Singh, Rajeev Kumar, Prasad, Ashit, Chowdhuri, Subhasis
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 2012
• Subjects: control system; decarburisation; electrical steel; mathematical model; mathematical model; decarburisation; electrical steel; control system
• ISSN: 2212-0173; 2212-0173
• DOI: 10.1016/j.protcy.2012.05.142

Reactive annealing of semi-processed electrical steels is an important process to reduce electro-magnetic losses. The annealing process involves heating of the steel strip, which is passed continuously through the furnace, to a certain temperature. The heated steel strip gets decarburised and annealed in a warm gas atmosphere containing N2-H2-H2OCO-CO2 mixture. The composition of the warm gas atmosphere plays a major role in both the decarburisation and selective oxidation of carbon from the steel strip. The furnace settings are often changed to cater for products with different metallurgical properties and varying dimensions. Often the line speed of the process too needs to be changed to cater to varying input parameters of the steel strip such as composition, width, thickness etc. Thus an advanced mathematical model based system is desired to optimize the running of the furnace to achieve the desired properties at improved productivity.For effective control of system, mathematical model for the heating of the steel strip is developed. Decarburisation model for the steel strip has been coupled with the thermal model. The model takes in various inputs like line speed, composition of the steel strip, width and its thickness. Temperatures in the different zones of the furnace along with the decarburising gas flow rate, H2/H2O ratio etc, are taken as input parameters. The model predicts the thermal profile of the steel strip inside the furnace. It also predicts the carbon composition in the steel strip along the length of the furnace. Based on optimized temperature and carbon profile for different grades, the model suggests the desired line speed and the temperature settings in the different zones of the furnace. If there is a mismatch in the desired and the actual line speed the model also generates the desired set points of temperature for increasing or decreasing the furnace temperature which is downloaded to PLC in order to control the furnace parameters in real-time.