Manuscript-revised-final.pdf (1.44 MB)
Ultrasonic measurements and machine learning for monitoring the removal of surface fouling during clean-in-place processes
journal contribution
posted on 2020-05-11, 09:21 authored by Josep Escrig-Escrig, Alessandro Simeone, Elliot WoolleyElliot Woolley, Shreedhar Rangappa, A Rady, Nicholas WatsonCleaning is an essential operation in the food and drink manufacturing sector, although it comes with significant economic and environmental costs. Cleaning is generally performed using autonomous Clean-in-Place (CIP) processes, which often over-clean, as suitable technologies do not exist to determine when fouling has been removed from the internal surfaces of processing equipment. This research combines ultrasonic measurements and machine learning methods to determine when fouling has been removed from a test section of pipework for a range of different food materials. The results show that the proposed methodology is successful in predicting when fouling is present on the test section with accuracies up to 99% for the range of different machine learning algorithms studied. Various aspects relating to the training data set and input data selection were studied to determine their effect on the performance of the different machine learning methods studied. It was found that the classification models performed better when data points were extracted directly from the ultrasonic waves and when data sets were combined for different fouling materials.
Funding
Innovate UK projects 103936 and 132205.
History
School
- Mechanical, Electrical and Manufacturing Engineering
Published in
Food and Bioproducts ProcessingVolume
123Pages
1 - 13Publisher
Elsevier B.V. on behalf of Institution of Chemical EngineersVersion
- AM (Accepted Manuscript)
Rights holder
© Crown CopyrightPublisher statement
This paper was accepted for publication in the journal Food and Bioproducts Processing and the definitive published version is available at https://doi.org/10.1016/j.fbp.2020.05.003.Acceptance date
2020-05-06Publication date
2020-05-23Copyright date
2020ISSN
0960-3085Publisher version
Language
- en
Depositor
Dr Elliot Woolley. Deposit date: 7 May 2020Usage metrics
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