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Paper Tissue Softness Rating by Acoustic Emission Analysis

  • Softness is one of the essential properties of hygiene tissue products. Reliably measuring it is of utmost importance to ensure the balance between customer expectations and cost-effective tissue production. This study presents a method for assessing softness by analyzing acoustic emissions produced while tearing a tissue specimen. The aim was to train neural network models using the corrected results of human panel tests as the ground truth labels and to predict the tissue softness in two- and three-class recognition tasks. We also investigate the possibility of predicting some production parameters related to the softness property. The results proved that tissue softness and production parameters could be reliably estimated only by the tearing noise.

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Metadaten
Author: Ivan Kraljevski, Frank Duckhorn, Constanze Tschöpe, Frank Schubert, Matthias WolffORCiD
DOI:https://doi.org/10.3390/app13031670
ISSN:2076-3417
Title of the source (English):Applied Sciences
Document Type:Scientific journal article peer-reviewed
Language:English
Year of publication:2022
Tag:acoustic emission; machine learning; tissue softness analysis
Volume/Year:13
Issue number:3
Article number:1670
Way of publication:Open Access
Faculty/Chair:Fakultät 1 MINT - Mathematik, Informatik, Physik, Elektro- und Informationstechnik / FG Kommunikationstechnik
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