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Detection and tracking of cracks based on thermoelastic stress analysis

Thermoelastic stress analysis using arrays of small, low-cost detectors has the potential to be used in structural health monitoring. However, evaluation of the collected data is challenging using traditional methods, due to the lower resolution of these sensors, and the complex loading conditions e...

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Autores principales: Middleton, C. A., Weihrauch, M., Christian, W. J. R., Greene, R. J., Patterson, E. A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7813230/
https://www.ncbi.nlm.nih.gov/pubmed/33489256
http://dx.doi.org/10.1098/rsos.200823
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author Middleton, C. A.
Weihrauch, M.
Christian, W. J. R.
Greene, R. J.
Patterson, E. A.
author_facet Middleton, C. A.
Weihrauch, M.
Christian, W. J. R.
Greene, R. J.
Patterson, E. A.
author_sort Middleton, C. A.
collection PubMed
description Thermoelastic stress analysis using arrays of small, low-cost detectors has the potential to be used in structural health monitoring. However, evaluation of the collected data is challenging using traditional methods, due to the lower resolution of these sensors, and the complex loading conditions experienced. An alternative method has been developed, using image decomposition to generate feature vectors which characterize the uncalibrated map of the magnitude of the thermoelastic effect. Thermal data have been collected using a state-of-the-art photovoltaic effect detector and lower cost, lower thermal resolution microbolometer detectors, during crack propagation induced by both constant amplitude and frequency loading, and by idealized flight cycles. The Euclidean distance calculated between the feature vectors of the initial and current state can be used to indicate the presence of damage. Cracks of the order of 1 mm in length can be detected and tracked, with an increase in the rate of change of the Euclidean distance indicating the onset of critical crack propagation. The differential feature vector method therefore represents a substantial advance in technology for monitoring the initiation and propagation of cracks in structures, both in structural testing and in-service using low-cost sensors.
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spelling pubmed-78132302021-01-21 Detection and tracking of cracks based on thermoelastic stress analysis Middleton, C. A. Weihrauch, M. Christian, W. J. R. Greene, R. J. Patterson, E. A. R Soc Open Sci Engineering Thermoelastic stress analysis using arrays of small, low-cost detectors has the potential to be used in structural health monitoring. However, evaluation of the collected data is challenging using traditional methods, due to the lower resolution of these sensors, and the complex loading conditions experienced. An alternative method has been developed, using image decomposition to generate feature vectors which characterize the uncalibrated map of the magnitude of the thermoelastic effect. Thermal data have been collected using a state-of-the-art photovoltaic effect detector and lower cost, lower thermal resolution microbolometer detectors, during crack propagation induced by both constant amplitude and frequency loading, and by idealized flight cycles. The Euclidean distance calculated between the feature vectors of the initial and current state can be used to indicate the presence of damage. Cracks of the order of 1 mm in length can be detected and tracked, with an increase in the rate of change of the Euclidean distance indicating the onset of critical crack propagation. The differential feature vector method therefore represents a substantial advance in technology for monitoring the initiation and propagation of cracks in structures, both in structural testing and in-service using low-cost sensors. The Royal Society 2020-12-23 /pmc/articles/PMC7813230/ /pubmed/33489256 http://dx.doi.org/10.1098/rsos.200823 Text en © 2020 The Authors. http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/http://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
spellingShingle Engineering
Middleton, C. A.
Weihrauch, M.
Christian, W. J. R.
Greene, R. J.
Patterson, E. A.
Detection and tracking of cracks based on thermoelastic stress analysis
title Detection and tracking of cracks based on thermoelastic stress analysis
title_full Detection and tracking of cracks based on thermoelastic stress analysis
title_fullStr Detection and tracking of cracks based on thermoelastic stress analysis
title_full_unstemmed Detection and tracking of cracks based on thermoelastic stress analysis
title_short Detection and tracking of cracks based on thermoelastic stress analysis
title_sort detection and tracking of cracks based on thermoelastic stress analysis
topic Engineering
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7813230/
https://www.ncbi.nlm.nih.gov/pubmed/33489256
http://dx.doi.org/10.1098/rsos.200823
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