Research on soft sensing of cement clinker f-CaO based on LS_SVM and burning zone temperature

In the burning system of cement rotary kiln, free calcium oxide (f-CaO) is an important control index in the burning process of clinker. Aiming at the problem that the content of f-CaO in cement clinker is difficult to be detected online, a soft sensing modeling method based on least squares support vector machine (LS-SVM) is proposed in this paper. The temperature of burning zone is taken as the input variable of the model and combined with other auxiliary variables, a set of auxiliary variables of least square support vector machine (LS-SVM) model is constructed for f-CaO content prediction. Finally, the experimental results show that the f-CaO soft-sensing model based on least squares support vector machine and the temperature of the burning zone can predict the f-CaO content accurately, which is of great significance for ensuring the quality of cement clinker and realizing the optimal control of rotary kiln burning system.