A Framework for Soft Sensing of Liquid Pool Length of Continuous Casting Round Blooms

Abstract

Liquid pool length is a vital parameter for solidification control of continuous casting round bloom but it is difficult to be measured by direct hardware measurement. So in this paper, a framework based on heat transfer model for soft sensing of the liquid pool length has been presented. In the framework, the heat transfer model is the kernel and it has been calibrated for its machine-dependent parameters by solving the inverse heat transfer problem with the surface temperature measurements using a color pyrometer. The inverse heat transfer problem has been solved by the optimizer using chaos particle swarm optimization algorithm. After the calibration, the liquid pool lengths were predicted under different casting conditions. Finally, the predictions were validated by shell-thickness measurements using nail-shooting, as the measurements and calculations showed good agreement with the relative errors less than 1.5 pct. And the application of the framework for final electromagnetic stirring has also been presented.