Data-Driven Optimal Control for Pulp Washing Process Based on Neural Network

Abstract

Pulp washing process has the features of multivariate, time delay, nonlinearity. Considering the difficulties of modeling and optimal control in pulp washing process, a data-driven operational-pattern optimization method is proposed to model and optimize the pulp washing process in this paper. The most important quality indexes of pulp washing performance are residual soda in the washed pulp and Baume degree of extracted black liquor. Considering the difficulties of modeling, online measurement of these indexes, two-step neural networks, and multivariate logistic regression are used to establish the prediction models of residual soda and Baume degree. The mathematical model of the washing process can be identified, and the indexes can meet the production requirements. In the target of better product quality, low cost, and low energy consumption, a multiobjective problems is solved by ant colony optimization algorithm based on the optimized operational-pattern database. It shows that the theoretical analyses are correct and the practical applications are feasible, optimization control system has been designed for the pulp washing process, and the practical results show that pulp production increased by 20% and water consumption decreased by nearly 30%. This method is effective in the pulp washing process.

Evaluation of sodium salt scaling in black liquor evaporators using existing process data

“…Even if measures are taken in the industry to mitigate evaporator scaling, there are no systems available (at least not widespread) that quantify the scaling rate and thereby allow for adequate monitoring and follow-up of evaporator scaling. Improved monitoring of important process parameters can also allow for optimization of the operation, which, for examples, has already been shown for the pulp washing process by Shan and Tang (2020). Traditionally and today, the wash frequency is the most common measurement used for determining the extent of evaporator scaling because it has the advantage of being easy to both measure and understand (Grace 1975, Schmidl andFrederick 1998).…”