Application of the Soft-Sensing Technique Based on Neural Network to Pulp Washing Process

Wei Tang; Wen Juan Shan

doi:10.4028/www.scientific.net/AMR.505.93

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 505Application of the Soft-Sensing Technique Based on...

Application of the Soft-Sensing Technique Based on Neural Network to Pulp Washing Process

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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Periodical:

Advanced Materials Research (Volume 505)

Pages:

93-100

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.505.93

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Online since:

April 2012

Authors:

Wei Tang, Wen Juan Shan

Keywords:

DCS, Least-Square Method (LSM), Neural Network (NN), Pulp Washing Process, Soft Sensor

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