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| Research on Cooking End Point Modeling Based on Recursive PLS for Displacement Cooking |
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| DOI：10.11981/j.issn.1000-6842.2015.03.47 |
| Key Words:displacement digester； optical fiber on-line measurement； cooking end point； multivariable binomial regression |
| Fund Project:国家国际科技合作项目(2010DFB43660)；陕西省重点科技创新团队计划项目(2014KCT-15)。 |
| Author Name | Affiliation | | 汤 伟1 | 1.陕西科技大学轻工与能源学院,陕西西安,710021 | | 于东伟1 | 1.陕西科技大学轻工与能源学院,陕西西安,710021 | | 张怡真1 | 1.陕西科技大学轻工与能源学院,陕西西安,710021 | | 党世红1 | 1.陕西科技大学轻工与能源学院,陕西西安,710021 | | 王 锋2 | 2.浙江力诺流体控制科技股份有限公司,浙江瑞安,325200 |
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| Abstract: |
| Kappa number model based on offline data can not be updated with the pulping process changes. By combining rolling window with recursive partial least squares (PLS), a new adaptive Kappa number model was proposed in the paper. In order to determine the supplementary variables for modeling instrumental, the pulping process and the factors influencing the cooking end point were analyzed. The model could be updated by using the latest data in a rolling window with specific dimension, if could ensure the ability of the model to follow the track of cooking process. Simulation results with real industrial data showed that the adaptive Kappa number model had higher precision and better prediction of cooking end point of displacement cooking than the traditional PLS model. |
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