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

Hua Zhong Wang; Wen Juan Shan

doi:10.4028/www.scientific.net/AMM.198-199.1712

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 198-199Modeling of Pulp Washing Process Based on Two-Step...

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.

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Periodical:

Applied Mechanics and Materials (Volumes 198-199)

Pages:

1712-1715

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.198-199.1712

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Online since:

September 2012

Authors:

Hua Zhong Wang, Wen Juan Shan

Keywords:

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

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References

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