Version 1
: Received: 20 November 2023 / Approved: 20 November 2023 / Online: 21 November 2023 (09:34:38 CET)
How to cite:
Garcia dela Yedra, A.; Muñoz, I.E.; Vivas, J.; Zubiri, O.; Zurutuza, X.; Sommerhuber, R.; Kettner, M. Acoustic Emission and Digital Image Correlation Based Methods for Early Damage Identification during Heat Exchanger Testing. Preprints2023, 2023111278. https://doi.org/10.20944/preprints202311.1278.v1
Garcia dela Yedra, A.; Muñoz, I.E.; Vivas, J.; Zubiri, O.; Zurutuza, X.; Sommerhuber, R.; Kettner, M. Acoustic Emission and Digital Image Correlation Based Methods for Early Damage Identification during Heat Exchanger Testing. Preprints 2023, 2023111278. https://doi.org/10.20944/preprints202311.1278.v1
Garcia dela Yedra, A.; Muñoz, I.E.; Vivas, J.; Zubiri, O.; Zurutuza, X.; Sommerhuber, R.; Kettner, M. Acoustic Emission and Digital Image Correlation Based Methods for Early Damage Identification during Heat Exchanger Testing. Preprints2023, 2023111278. https://doi.org/10.20944/preprints202311.1278.v1
APA Style
Garcia dela Yedra, A., Muñoz, I.E., Vivas, J., Zubiri, O., Zurutuza, X., Sommerhuber, R., & Kettner, M. (2023). Acoustic Emission and Digital Image Correlation Based Methods for Early Damage Identification during Heat Exchanger Testing. Preprints. https://doi.org/10.20944/preprints202311.1278.v1
Chicago/Turabian Style
Garcia dela Yedra, A., Ryan Sommerhuber and Matthias Kettner. 2023 "Acoustic Emission and Digital Image Correlation Based Methods for Early Damage Identification during Heat Exchanger Testing" Preprints. https://doi.org/10.20944/preprints202311.1278.v1
Abstract
Aircraft heat exchangers play a crucial role in maintaining thermal balance and ensuring that essential components operate efficiently and safely. In this context, it is highly relevant to gain knowledge about the deterioration and the predominant damage mechanisms of these components. In this study, two different non-destructive methods are employed to analyze the damage initiation of a heat exchanger part during fatigue test. On the one hand, Acoustic Emission technique is employed using membrane-free microphones capable of capturing a broad bandwidth. The acoustic events were classified by a machine learning algorithm to determine their source and damage mechanisms. On the other side, Digital Image Correlation (DIC) allowed the measurement of the strain evolution along the test and more precisely, redistributions were considered as damage indicators. As a result, it was identified that AE served as early damage indicator as the cumulative number of events was in good agreement with the severity of the damage. With respect to classification two clear clusters ascribed to different type of events were identified. In the case of DIC, strain redistributions gave clear indications of damage or deterioration but at a later stage compared to AE
Keywords
Acoustic Emission; Digital Image Correlation; Heat Exchanger; Damage Mechanism.
Subject
Engineering, Industrial and Manufacturing Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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