A Review: Modeling of pH Probability Density Distribution in Zinc Hydrometallurgy Based on Gaussian Mixture Model

In the neutral leaching process of zinc hydrometallurgy, exploring the characteristics of pH fluctuations in the reactor is an effective approach for improving the zinc leaching rate. A modeling method of the pH probability density distribution based on the Gaussian mixture model (GMM) has thus been proposed to describe the characteristics of pH fluctuation in the reactor. This method, based on the pH time series of the highest period of zinc leaching rate, extracts the pH probability density distribution characteristics, and then identifies the pH probability density distribution of the reactor by GMM, and finally combines an enhanced expectation-maximization (EEM) algorithm to estimate GMM parameters. The experimental result shows that the EEM algorithm improves the fitting accuracy of the model by 10 percentage points. Compared with single distribution models, the GMM is more suitable for the distribution characteristics of pH probability density. It provides a theoretical basis for pH optimization control.