Article | Proceedings of The 60th SIMS Conference on Simulation and Modelling SIMS 2019, August 12-16, Västerås, Sweden | On-line Monitoring of Viscous Properties of Anti-icing Fluid Based on Partial Least Squares Regression Modeling Linköping University Electronic Press Conference Proceedings
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Title:
On-line Monitoring of Viscous Properties of Anti-icing Fluid Based on Partial Least Squares Regression Modeling
Author:
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
DOI:
https://doi.org/10.3384/ecp2017026
Download:
Full text (pdf)
Year:
2019
Conference:
Proceedings of The 60th SIMS Conference on Simulation and Modelling SIMS 2019, August 12-16, Västerås, Sweden
Issue:
170
Article no.:
004
Pages:
26-31
No. of pages:
6
Publication type:
Abstract and Fulltext
Published:
2020-01-24
ISBN:
978-91-7929-897-5
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press, Linköpings universitet


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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

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

Author:
Maths Halstensen, Joachim Lundberg, Per Ivan Januschas, Hans-Petter Halvorsen
Title:
On-line Monitoring of Viscous Properties of Anti-icing Fluid Based on Partial Least Squares Regression Modeling
DOI:
10.3384/ecp2017026
References:

ASTM D-2196-18. Standard Test Methods for Rheological Properties of Non-Newtonian Materials by Rotational Viscountess. ASTM International, PA, USA, 2018.

Benjamin K. Arvoh, Steinar Asdhal, Karsten Rabe, Rolf Ergon, and Maths Halstensen. Online estimation of reject gas and liquid flow rates in compact flotation units for produced water treatment. Flow Meas Instrum, 24:63-70, 2012.

Benjamin K. Arvoh, Steinar Asdhal, Karsten Rabe, and Maths Halstensen. Online estimation of reject gas flow rates in compact flotation units for produced water treatment: A feasibility study. Chemometrics and Intelligent Laboratory Systems. 114:87-98, 2012.

Emanuel Ifeachor and Barrie Jervis. Digital Signal Processing, a Practical Approach, Addison-Wesley Publishing, 1993.

Felicia N. Ihunegbo, Michael Madsen, Kim H. Esbensen, Jens-Bo Holm-Nielsen, and Maths Halstensen. Acoustic chemometric prediction of total solids in bioslurry: A full-scale feasibility study for on-line biogas process monitoring. Chemometrics and Intelligent Laboratory Systems, 110:135–143, 2012.

Harald Martens and Tormod Næs. Multivariate Calibration, Wiley, UK, 1989 reprint 1994.

Kim H. Esbensen, Bjørn Hope, Thorbjørn T. Lied, Maths Halstensen, Tore Gravermoen, and Kenneth Sundberg. Acoustic chemometrics for fluid flow quantifications - II: A small constriction will go a long way.  J. Chemometrics 13, 27:209-236, 1999.

Kim H. Esbensen and Paul Geladi. Principles of Proper Validation: use and abuse of re-sampling for validation. Journal of Chemometrics, 24: 168-187, 2010 (www.interscience.wiley.com). DOI: 10.1002/cem.1310.

Kim H. Esbensen and Brian Swarbrick. Multivariate Date Analysis – An introduction to Multivariate Data Analysis, Process Analytical Technology and Quality by Design. 462 p, 6th edition, CAMO Software AS, 2018. ISBN 978-82-691104-0-1.

Maths Halstensen, Peter de Bakker, and Kim H. Esbensen. Acoustic chemometric monitoring of an industrial granulation production process – a PAT feasibility study. Chemometrics and Intelligent Laboratory Systems, 84:88-97, 2006.

Maths Halstensen and Kim H. Esbensen. Acoustic chemometric monitoring of chemical production processes. Process Analytical Technology, 2nd Edition, Chapter 9, Wiley, 2010.  ISBN: 9780470722077. 

Rolf Ergon. Re-interpretation of NIPALS results solves PLSR inconsistency problems. J Chemometr, 23:72-75, 2009.

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

Author:
Maths Halstensen, Joachim Lundberg, Per Ivan Januschas, Hans-Petter Halvorsen
Title:
On-line Monitoring of Viscous Properties of Anti-icing Fluid Based on Partial Least Squares Regression Modeling
DOI:
https://doi.org10.3384/ecp2017026
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