Abstract
On the status quo that being lack of the testing equipment which gives reliable and direct parameters on measuring the quality of pulp in the cooking process, this article focus on the lignin value soft-measurement technology in the pulp and papermaking process. The pulp lignin value soft-measurement model is built basing on artificial neural network; It takes cooking process temperature, cooking time and the effective alkaline concentration as network input, and an improved BP algorithm to train the network for obtaining the predictive output value of the lignin value. Utilizing online measurement of cooking process temperature, cooking time and effective alkaline concentration, the soft-measurement model can monitor the quality of pulp.
The research is supported by Guangxi Province Nanning Key Technology Research Project (200501007A).
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Su, J., Meng, Y., Chen, C., Lu, F., Yan, S. (2008). The Quality Monitoring Technology in the Process of the Pulping Papermaking Alkaline Steam Boiling Based on Neural Network. In: Sun, F., Zhang, J., Tan, Y., Cao, J., Yu, W. (eds) Advances in Neural Networks - ISNN 2008. ISNN 2008. Lecture Notes in Computer Science, vol 5264. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87734-9_9
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DOI: https://doi.org/10.1007/978-3-540-87734-9_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87733-2
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