Mass-balance based soft sensor for monitoring ash content at two-ply paperboard manufacturing |
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Author: | Tomperi, Jani1; Ohenoja, Markku2; Ritala, Risto3; |
Organizations: |
1Environmental and Chemical Engineering Research Unit, Control Engineering, University of Oulu, P.O. Box 8000, FI-90014 University of Oulu, Finland 2Environmental and Chemical Engineering Research Unit, Control Engineering, University of Oulu, P.O. Box 8000, FI-90014 University of Oulu 3Automation Technology and Mechanical Engineering, Faculty of Technical Sciences, Tampere University, P.O. Box 692, FIN-33101 Tampere, Finland
4Valmet Automation Inc., P.O. Box 237, FIN-33101 Tampere, Finland
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Format: | article |
Version: | published version |
Access: | open |
Online Access: | PDF Full Text (PDF, 1.5 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe2022041929457 |
Language: | English |
Published: |
De Gruyter,
2022
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Publish Date: | 2022-04-19 |
Description: |
AbstractContinuous and robust measurements are needed for the high end-product quality and efficient and eco-friendly process in paperboard manufacturing. As the online measurements enable the optimization of the manufacturing process making it more cost effective and environmentally friendly, these measurements must be validated carefully and continuously. This paper presents the development of a mass-balance based soft sensor for online estimation of a two-ply paperboard ash content. The developed soft sensor considers the basis weight, moisture and fiber measurements to derive the ash content of the paperboard at the reel. The development of the soft sensor was success (Mean Absolute Percentage Error was 11.80) and during the long-term simulation with measured data, this robust online estimator showed the level and changes in ash content accurately, enabling also the continuous validation of the hardware sensor. see all
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Series: |
Nordic pulp & paper research journal |
ISSN: | 0283-2631 |
ISSN-E: | 2000-0669 |
ISSN-L: | 0283-2631 |
Volume: | 37 |
Issue: | 1 |
Pages: | 175 - 183 |
DOI: | 10.1515/npprj-2021-0046 |
OADOI: | https://oadoi.org/10.1515/npprj-2021-0046 |
Type of Publication: |
A1 Journal article – refereed |
Field of Science: |
213 Electronic, automation and communications engineering, electronics |
Subjects: | |
Funding: |
This research work was carried out as a part of Business Finland Co-innovation joint action APASSI (Autonomous Processes Facilitated by Artificial Sensing Intelligence). |
Copyright information: |
© 2022 Tomperi et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution 4.0 International License. |
https://creativecommons.org/licenses/by/4.0/ |