A composition soft-sensing model of FeO-Fe₂O₃-SiO₂ ternary slag system based on two-temperature two-density method

According to the characteristics of composition strong coupling with physical properties of smelting slag, the temperature and density of slag system were selected as the secondary variables of soft sensor, and the regression algorithm with Taylor series three times expansion was used, then a composition soft-sensing model of the ternary slag system was established based on two-temperature two-density method. Practical experimental results of slag system of FeO-Fe₂O₃-SiO₂ show that regression calculation has high accuracy, and the average relative error (absolute value) of density is only 0.412%. Multi-group soft measurements have achieved superior predictive hit rate, and the model is suitable for compositions of the slag system with wide range. Analysis of the density-temperature characteristic curves drawn show that the model can well take account of the inherent law of density, composition and temperature of the ternary slag system. The research serves as a nice soft-sensing model for predicting compositions of the ternary slag system.