Real-time monitoring of wood cladding spray painting properties and nozzle condition using acoustic chemometrics

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

Onyinye Victoria Agu
Department of Electrical Engineering, IT and Cybernetics, University of South-Eastern Norway

Ulrich Hundhausen
Norwegian Institute of Wood Technology (NTI), Oslo, Norway

Kim H. Esbensen
KHE Consulting, Copenhagen, Denmark

Ladda ner artikelhttps://doi.org/10.3384/ecp20176352

Ingår i: Proceedings of The 61st SIMS Conference on Simulation and Modelling SIMS 2020, September 22-24, Virtual Conference, Finland

Linköping Electronic Conference Proceedings 176:50, s. 352-359

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Publicerad: 2021-03-03

ISBN: 978-91-7929-731-2

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


An experimental setup simulating real-time wood cladding coating monitoring of nozzle conditions and spray paint properties has been investigated. This approach is based on affixed nozzle accelerometer sensors with appropriate signal conditioning and chemometric data analysis (PCA). The aim was to develop effective visualization of different process states using PCA score plots. The present feasibility study shows that this approach can be used as a basis for further development towards a Process Analytical Technology (PAT) spray monitoring system able to work in the harsh environment of an industrial wood cladding paint box. However, there is still a significant amount of on-site industrial calibration and R&D necessary before a final method validation can be executed. The present results rely on permanently affixed PAT sensors. Further studies will a.o. focus on the degree to which replacement of acoustic accelerometer sensors necessitates recalibration of the multivariate data models employed, which is a critical success factor in industrial implementations.


process analytical technology (PAT), multivariate data analysis, accelerometer, principal component analysis, process monitoring, nozzle spray condition, statistical quality control


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