Engineering Mechanics

International Conference

Proceedings Vol. 27/28 (2022)


May 9 – 12, 2022, Milovy, Czech Republic
Editors: Cyril Fischer and Jiří Náprstek

Copyright © 2022 Institute of Theoretical and Applied Mechanics of the Czech Academy of Sciences, Prague

ISBN 978-80-86246-48-2 (printed)
ISBN 978-80-86246-51-2 (electronic)
ISSN 1805-8248 (printed)
ISSN 1805-8256 (electronic)

list of papers scientific commitee

Smart operational load monitoring using decision trees and artificial neural networks: A comparative study
Mucha W., Viana J. C., Nunes J. P.
pages 269 - 272, full text

Operational Load Monitoring is an industrial process that allows to predict the remaining in-service life of a mechanical structure under variable loads. Data from sensors embedded or mounted on the structure is acquired and allows to estimate the number and amplitude of load cycles that the structure has withstood so far in its working environment. This process is especially important in the aerospace industry where mechanical structures of an aircraft are monitored in order to maximize their operating lifetime. Smart Operational Load Monitoring means implementation of artificial intelligence techniques to the process in order to make predictions based on measurements from reduced number of sensors. In this paper a composite lightweight structure of typical geometry used in aircraft structures is taken as an example for Smart Operational Load Monitoring. The predictions are made from measurements from six strain gauges mounted to the structure, using carefully prepared artificial intelligence-based models. Efficiency of the models is compared, in terms of their prediction accuracies and computational complexities.

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Ownership of copyright in original research articles remains with the Authors, and provided that, when reproducing parts of the contribution, the Authors acknowledge and/or reference the Proceedings, the Authors do not need to seek permission for re-use of their material.

All papers were reviewed by members of the scientific committee.

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