Journal article
A probabilistic framework for single-sensor acoustic emission source localization in thin metallic plates
Smart materials and structures, v 26(9), p95026
01 Sep 2017
Abstract
Tracking edge-reflected acoustic emission (AE) waves can allow the localization of their sources. Specifically, in bounded isotropic plate structures, only one sensor may be used to perform these source localizations. The primary goal of this paper is to develop a three-step probabilistic framework to quantify the uncertainties associated with such single-sensor localizations. According to this framework, a probabilistic approach is first used to estimate the direct distances between AE sources and the sensor. Then, an analytical model is used to reconstruct the envelope of edge-reflected AE signals based on the source-to-sensor distance estimations and their first arrivals. Finally, the correlation between the probabilistically reconstructed envelopes and recorded AE signals are used to estimate confidence contours for the location of AE sources. To validate the proposed framework, Hsu-Nielsen pencil lead break (PLB) tests were performed on the surface as well as the edges of an aluminum plate. The localization results show that the estimated confidence contours surround the actual source locations. In addition, the performance of the framework was tested in a noisy environment simulated by two dummy transducers and an arbitrary wave generator. The results show that in low-noise environments, the shape and size of the confidence contours depend on the sources and their locations. However, at highly noisy environments, the size of the confidence contours monotonically increases with the noise floor. Such probabilistic results suggest that the proposed probabilistic framework could thus provide more comprehensive information regarding the location of AE sources.
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Details
- Title
- A probabilistic framework for single-sensor acoustic emission source localization in thin metallic plates
- Creators
- Arvin Ebrahimkhanlou - The University of Texas at AustinSalvatore Salamone - The University of Texas at Austin
- Publication Details
- Smart materials and structures, v 26(9), p95026
- Publisher
- IOP Publishing
- Number of pages
- 19
- Grant note
- This work was supported by the Office of Naval Res / Office of Naval Research (https://doi.org/10.13039/100000006)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering
- Web of Science ID
- WOS:000407457000024
- Scopus ID
- 2-s2.0-85028591366
- Other Identifier
- 991021889907004721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Instruments & Instrumentation
- Materials Science, Multidisciplinary