| 1. |
- Bengtsson, Fredrik, 1989, et al.
(author)
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Modeling of tensile index using uncertain data sets
- 2020
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In: Nordic Pulp and Paper Research Journal. - : Walter de Gruyter GmbH. - 2000-0669 .- 0283-2631. ; 35:2, s. 231-242
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Journal article (peer-reviewed)abstract
- The objective of this investigation is to analyze and model tensile index. Two approaches are used, one based on training and validation data, while the other novel approach tests models using all possible combinations of data points. This approach is focused on small data sets which have here been obtained from nineteen pulp samples at different refining conditions in a full-scale TMP production line with a CD-76 refiner as a primary stage. From each pulp sample twenty handsheet strips for tensile index measurements were performed. Initially, specific energy and the external variables (dilution water feed rates and plate gaps) are used as predictors in a modeling approach based on an adjusted R 2 {R^{2}} approach. Thereafter, the resulting models are compared with a combination of specific energy and internal variables (primarily consistencies) obtained from temperature measurements inside the refining zones using a soft sensor concept. It is found that specific energy and internal variables as predictors outperform the external variables when estimating tensile index.
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| 2. |
- Bengtsson, Fredrik, 1989, et al.
(author)
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On the modeling of pulp properties in CTMP processes
- 2021
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In: Nordic Pulp and Paper Research Journal. - : Walter de Gruyter GmbH. - 2000-0669 .- 0283-2631. ; 36:2, s. 234-248
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Journal article (peer-reviewed)abstract
- The goal of this paper is to model the pulp properties fiber length, shives width and freeness. This will be done utilizing specific energy, flat zone inlet consistency and the internal variables, consistencies and fiber residence times estimated from refining zone soft sensors. The models are designed using more than 3600 hours of data from a RGP82CD refiner. The pulp properties are sampled using a measurement device positioned after the latency chest. Such measurements are noisy and irregularly sampled which opens for a number of challenges to overcome in modeling procedures. In this paper it is shown that the models for shives width and fiber length are capable of predicting most of the major dynamics. However, for freeness no reliable linear models can be derived. When estimating fiber length, the specific energy together with flat zone inlet consistency, fiber residence times and the consistency in the conical zone were the dominant inputs. For shives width it was found that a similar set of inputs resulted in the best models, except that the consistencies during normal process conditions did not significantly influence shives width. Furthermore, fiber residence times were shown to have considerably more pronounced impact on fiber length compared with shives width estimates.
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| 3. |
- Karlström, Anders, 1958, et al.
(author)
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Data-Driven Soft Sensors in Pulp Refining Processes Using Artificial Neural Networks
- 2024
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In: BioResources. - 1930-2126 .- 1930-2126. ; 19:1, s. 1030-1057
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Journal article (peer-reviewed)abstract
- Pulp refining processes are most often complicated to describe using linear methodologies, and sometimes an artificial neural network (ANN) is a preferable alternative when assimilating non-linear operating data. In this study, an ANN is used to predict pulp properties, such as shives (wide), fiber length, and freeness. Both traditional process variables (external variables) and refining zone variables (internal variables) are necessary to include as model inputs. The estimation of shives (wide) results achieved an R2 (coefficient of determination) of 0.9 (0.7) for the training and (validation) sets. Corresponding measures for fiber length and freeness can be questioned using this methodology. It is shown that the maximum temperature in the flat zone can be modeled using the external variables motor load and production instead of the specific energy. This resulted in an R2 of approximately 0.9 for the training sets, while the R2 for the validation set did not reach an acceptable level – most likely due to inherent non-linearities in the process. Additional results showed that the consistency profile is difficult to estimate properly using an ANN. Instead, a model-driven sensor is preferred to be used. The main results from this study indicate that shives (wide) should be the prime candidate when introducing advanced pulp property control concepts.
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| 4. |
- Karlström, Anders, 1958, et al.
(author)
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Data-Driven Soft Sensors in Refining Processes – Pulp Property Estimation Using ARX-Models
- 2023
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In: BioResources. - 1930-2126 .- 1930-2126. ; 18:4, s. 8163-8186
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Journal article (peer-reviewed)abstract
- This paper focuses on estimation of shives(wide) and fiber length in RGP82CD-refiners using an AutoRegressive eXogenous (ARX) structure in a data-driven soft sensor concept. Both external and internal variables are considered as model inputs. The pulp properties were sampled every 15 min from an on-line device positioned after the latency chest, whereas other process data were sampled every 6 seconds. Notably, despite the high data sampling rate, the development of robust models necessitated a dataset spanning over two months of process information. The external variables studied in this paper were specific energy, the sawmill chip content, plate gaps, and dilution water feed rates to each refining zone. Additional internal variables, such as the inlet flat zone temperature, the maximum temperature, and the periphery temperature in the conical zone, were also used as model inputs. It was concluded that both shives(wide) and fiber length can be estimated with relatively good accuracy although large uncertainties exist in the measured properties. Finally, it was shown that fast pulp property dynamics in the blow-line can be followed, which outperforms current practices of using pulp measurement devices positioned after the latency chest. This offers implementation of more advanced future pulp property control concepts.
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| 5. |
- Sund, Johan, et al.
(author)
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The effect of process design on refiner pulp quality control performance
- 2021
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In: Nordic Pulp & Paper Research Journal. - : Walter de Gruyter GmbH. - 0283-2631 .- 2000-0669. ; 36:4, s. 594-607
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Journal article (peer-reviewed)abstract
- In this study, the effect of process- and online analyser configuration on pulp quality control is explored. The following parameters were included: analyser sampling interval, time delay, measurement error magnitude, and latency chest residence time. Using different values of parameters in a process model, a range of configurations were constructed. For each configuration, the achievable control performance was evaluated using an optimization approach. PI controller settings were chosen based on minimization of the integrated absolute error (IAE) in pulp quality after an input step disturbance. The results show that reducing the sampling interval improves performance also when the interval is smaller than the chest residence time or the analyser delay. Moreover, reducing the chest residence time can reduce the IAE by up to 40 %. However, reducing the residence time to lower than 1/3 of the sampling interval does not improve performance. Further improvement is possible if the analyser delay is reduced. The compromise between reducing the IAE and avoiding creating variation by acting on measurement error has a strong influence on the results. In conclusion, pulp quality control performance can be improved significantly by making changes to the studied configuration parameters.
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