Solution Concentration Diffusion Prediction Using RBF Neural Network

Aiming at the problem that the electrolyte feeding is difficult to monitor online in the process of indium electrorefining, a solution diffusion concentration prediction model based on RBF neural network is proposed. Firstly, establish a finite element simulation model of solution diffusion to obtain concentration diffusion data. Then the data obtained through finite element simulation, the influencing factors are taked such as injection concentration, inlet flow rate and diffusion time as the independent variables and the concentration as the prediction target, train the RBF neural network to establish the prediction model. The prediction model is suitable for the analysis of a large number of data and can accurately predict the concentration. The prediction accuracy of the solution concentration diffusion prediction model based on RBF neural network reaches 99.971%, and the prediction accuracy meets the requirement of concentration prediction, which has certain engineering practical value.