Modeling method of boiler combustion system based on empirical mode decomposition

This paper proposes a modeling method of boiler combustion system based on Empirical Mode Decomposition (EMD). For the modeling of boiler combustion system, the current mainstream method is based on data-driven modeling method. However, the learning efficiency of the model is not ideal due to the complexity of the boiler system. In this paper, EMD is used to transform complex signals into multiple modal signals with periodic laws or relatively stable trends firstly, so as to reduce the data complexity. Then the Least Squares Support Vector Machine (LSSVM) is used for data-driven modeling to improve the learning efficiency and prediction accuracy of the model. Simulation results verify the effectiveness of the proposed modeling method.