Conference article

On-line Monitoring of Viscous Properties of Anti-icing Fluid Based on Partial Least Squares Regression Modeling

Maths Halstensen
Department of Electrical Engineering, IT and Cybernetics, Universityof South-Eastern Norway, Norway

Joachim Lundberg
Department of Process, Energy and Environmental Technology,University of South-Eastern Norway, Norway

Per Ivan Januschas
MSG Production AS, Norway

Hans-Petter Halvorsen
Department of Electrical Engineering, IT and Cybernetics, Universityof South-Eastern Norway, Norway

Download articlehttps://doi.org/10.3384/ecp2017026

Published in: Proceedings of The 60th SIMS Conference on Simulation and Modelling SIMS 2019, August 12-16, Västerås, Sweden

Linköping Electronic Conference Proceedings 170:4, s. 26-31

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Published: 2020-01-24

ISBN: 978-91-7929-897-5

ISSN: 1650-3686 (print), 1650-3740 (online)

Abstract

MSG Production is a company specializing in automated washing, de-icing, anti-icing and inspection of commercial passenger aircrafts. It is critically important that the viscosity of the anti-icing fluid is according to specifications. This study investigates if a combination of acoustic/vibrational measurements on the spraying nozzle of the system and multivariate regression modelling provides reliable viscosity estimates can be used for real time monitoring. The estimated viscosity based on independent test data show promising results for real time monitoring with a root mean square error of prediction of 278 [cP] within the valid range of the model which is 1900-8400 [cP].

Keywords

partial least squares, multivariate regression, viscosity, anti-icing fluid, acoustic monitoring

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