Soft sensing of iron-ion concentration for iron removal process based on NIWVP-PSO

The iron-ion concentration for iron removal process in zinc hydrometallurgy is a very important index which cannot be measured online. Based on the analysis of the mechanism and the kinetics of chemical reaction of iron removal process, the mathematical soft sensing model of the iron removal process is established. Then a nonlinear inertia weight with varying position particle swarm optimization (NIWVP-PSO) is proposed to optimize the parameters of the mechanism model. At last, the mechanism model is validated using the industry application data. Simulation results show that the method has high accuracy and good generalization ability than traditional nonlinear least square method. The soft sensing results meet the technology requirements of production and can be used for optimal control of the iron removal process.