Abstract
The most important quality indexes to evaluate pulp washing performance are residual soda for the washed pulp and the Baume degree for the yielded thick black liquor. However, the two requirements are incompatible. In view of the existing problem of the former control system of the pulp washing process, an adaptive soft-sensor instrument for measuring residual soda and Baume degree is proposed. Voluminous plant operation data collected by DCS and simulated results from a theoretical model are pooled together and used to build the adaptive soft-sensor instrument based on the BP neural network and least square method. Application of the soft-sensor technique in pulp washing control system shows that the control system can run smoothly over a long period in worksites, and has realized the close-loop control of pulp washing quality.
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