Abstract
The passive imaging based on the Green’s functions reconstruction from ambient noise correlation became a promising technique in structural health monitoring. Here, this approach is used to detect and locate linear defects (cracks, holes...) in thin reverberant plates with a small number of sensors. Correlation matrices before and after defect occurrence are estimated from friction noise. Based on a dispersive backpropagation algorithm in a thin plate, the differential matrix of correlations (before and after defect) is used for defect localization. This technique shows satisfactory results for linear defects, but refers to a measurement on a baseline healthy sample, which can be strongly affected by environmental conditions. In this context, an active baseline-free damage localization method that uses a repetitive pump-probe experiment, is proposed. A series of experiments are conducted in a thin aluminum plate using 7 PZTs sensors glued at known positions. One transducer generates a high frequency probe wave with central frequency 20 kHz, while a continuous low frequency pump of 1 Hz is produced by a shaker. A steel ball pressed against the plate to mimic a nonlinear defect is considered. The aim here is to produce solid-solid contact that will be modulated by the pump wave, as would be the case for instance in fatigue cracks. In order to enhance this effect, signals recorded at different times (corresponding to different loading states of the contact) are subtracted and back-propagated to locate the origin of the modulation.
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Acknowledgment
This work has been supported by the French National Research Agency (ANR): Grant ANR2011-BS09-03901 (PASNI Project), and Grant ANR2017-CE08-0013-01 (PANSCAN project).
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Chehami, L., Moulin, E., Terzi, M. (2021). Non Destructive Auscultation and Imaging of Damages by Distributed Sensor Array: Step Towards Passive SHM Under Real Conditions. In: Rizzo, P., Milazzo, A. (eds) European Workshop on Structural Health Monitoring. EWSHM 2020. Lecture Notes in Civil Engineering, vol 127. Springer, Cham. https://doi.org/10.1007/978-3-030-64594-6_35
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DOI: https://doi.org/10.1007/978-3-030-64594-6_35
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