Research on Modeling and Optimization Method of Cement Clinker Calcination Process Based on EGPR Model and Steady State Detection

This paper proposes a modeling and optimization method for cement clinker calcination process based on gaussian process regression ensemble (EGPR) model and steady-state detection. Firstly, a modeling strategy based on EGPR model is proposed achieve an accurate description of the dynamic relationship between coal consumption, free calcium oxide (f-CaO) and operation status variables. Secondly, a multivariate steady-state detection method based on trend feature extraction is proposed for the characteristics of mixing steady-state data and dynamic data in the clinker calcination process, which achieves steady-state detection of the process and completes data denoising at the same time.Then, the optimization problem is solved using the bayesian optimization (BO) algorithm Finally, the production data of cement companies are used for validation. The results show that the overall modeling and optimization strategy proposed in this paper provides a feasible solution for achieving the optimization of energy consumption in cement clinker calcination process.