Monitoring Mixing Processes Using Ultrasonic Sensors and Machine Learning

Bowler, A.L. orcid.org/0000-0003-3209-2774, Bakalis, S. and Watson, N.J. orcid.org/0000-0001-5216-4873 (2020) Monitoring Mixing Processes Using Ultrasonic Sensors and Machine Learning. Sensors, 20 (7). 1813. ISSN 1424-8220

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Item Type: Article
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© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Keywords: food and drink manufacturing; industry 4.0; digital manufacturing; mixing; ultrasonic sensors; machine learning; convolutional neural networks; long short-term memory neural networks; wavelet transform
Dates:
  • Published: 1 April 2020
  • Published (online): 25 March 2020
  • Accepted: 24 March 2020
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > School of Food Science and Nutrition (Leeds) > FSN Nutrition and Public Health (Leeds)
The University of Leeds > Faculty of Environment (Leeds) > School of Food Science and Nutrition (Leeds) > FSN Colloids and Food Processing (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 12 Jul 2024 09:41
Last Modified: 12 Jul 2024 09:41
Status: Published
Publisher: MDPI
Identification Number: 10.3390/s20071813
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