Modeling of Pulp Washing Process Based on Two-Step BP Neural Network

Abstract

The most important quality indexes to evaluate pulp washing performance are residual soda and the Baume degree. But it is difficult to measure the two indexes directly. To solve the problem of optimization control of the washing process, the model of the residual soda and the Baume degree are studied in this paper. Simulating residual soda and the Baume degree via a two-step neural network and modeling them based on least square method and steady-state data obtained by neural network model. Simulation results show that this method can effectively locate the pulp washing process.